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RJR: Recommended Bibliography 25 Oct 2026 at 01:47 Created:
Ecological Informatics
Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are the National Science Foundation's Datanet , DataONE and Data Conservancy projects.
Created with PubMed® Query: ( "ecology OR ecological" AND ("data management" OR informatics) NOT "assays for monitoring autophagy" ) NOT pmcbook NOT ispreviousversion
Citations The Papers (from PubMed®)
RevDate: 2026-10-24
CmpDate: 2026-10-23
College mental health and the digital care transition: national trends in distress, help-seeking, and technology-mediated access, 2020-2025.
Frontiers in digital health, 8:1963340.
BACKGROUND: College mental health burden increased during the COVID-19 era while university mental health services rapidly adopted remote and digital modes of care. The population-level co-occurrence of these changes has rarely been described across the pandemic and post-pandemic period.
METHODS: We performed a secondary ecological trend analysis of seven publicly available, weighted Healthy Minds Study national reports based on successive independent cross-sectional samples from Winter/Spring 2020 through 2024-2025. The reports contained a nominal 553,785 response records across waves; they were not pooled as a single cohort. Harmonized outcomes included depression, anxiety, suicidal ideation, nonsuicidal self-injury, self-reported academic impairment, treatment use, stigma, resource awareness, and selected digital-care indicators. Changes were summarized descriptively as percentage-point and relative differences; no across-wave significance tests or individual-level associations were estimated.
RESULTS: Depression increased from 37% in Winter/Spring 2020 to 44% in 2021-2022 and was 37% in 2024-2025; anxiety increased from 31% to 37% and was 33% in 2024-2025. Self-reported academic impairment of at least 6 days in the prior 4 weeks declined from a Fall 2020 peak of 28% to 16% in 2024-2025. Therapy use increased from 27% to 38%, treatment among students with positive depression/anxiety screens from 51% to 61%, resource awareness from 72% to 83%, and perceived public stigma declined from 51% to 36%. Among therapy users, remote-only care increased from 29% in Fall 2020 to 42% in Winter/Spring 2021, while in-person-only care declined from 35% to 22%; remote-capable care (remote-only plus hybrid) increased from 65% to 77%. In 2024-2025, 7% of the weighted national sample reported a mobile app, online platform, or other digital mental health resource as a provider/resource category.
CONCLUSIONS: The observed national estimates show post-peak improvement in several mental health and functional indicators alongside an early-pandemic shift toward remote and hybrid care. Because the analysis used aggregate reports with changing institutional composition, these findings describe population-level trends rather than causal effects or individual recovery.
Additional Links: PMID-42910146
PubMed:
Citation:
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@article {pmid42910146,
year = {2026},
author = {Arévalo Guadalupe, GC and Gamboa Tama, LA and Gamboa Tama, JE},
title = {College mental health and the digital care transition: national trends in distress, help-seeking, and technology-mediated access, 2020-2025.},
journal = {Frontiers in digital health},
volume = {8},
number = {},
pages = {1963340},
pmid = {42910146},
issn = {2673-253X},
abstract = {BACKGROUND: College mental health burden increased during the COVID-19 era while university mental health services rapidly adopted remote and digital modes of care. The population-level co-occurrence of these changes has rarely been described across the pandemic and post-pandemic period.
METHODS: We performed a secondary ecological trend analysis of seven publicly available, weighted Healthy Minds Study national reports based on successive independent cross-sectional samples from Winter/Spring 2020 through 2024-2025. The reports contained a nominal 553,785 response records across waves; they were not pooled as a single cohort. Harmonized outcomes included depression, anxiety, suicidal ideation, nonsuicidal self-injury, self-reported academic impairment, treatment use, stigma, resource awareness, and selected digital-care indicators. Changes were summarized descriptively as percentage-point and relative differences; no across-wave significance tests or individual-level associations were estimated.
RESULTS: Depression increased from 37% in Winter/Spring 2020 to 44% in 2021-2022 and was 37% in 2024-2025; anxiety increased from 31% to 37% and was 33% in 2024-2025. Self-reported academic impairment of at least 6 days in the prior 4 weeks declined from a Fall 2020 peak of 28% to 16% in 2024-2025. Therapy use increased from 27% to 38%, treatment among students with positive depression/anxiety screens from 51% to 61%, resource awareness from 72% to 83%, and perceived public stigma declined from 51% to 36%. Among therapy users, remote-only care increased from 29% in Fall 2020 to 42% in Winter/Spring 2021, while in-person-only care declined from 35% to 22%; remote-capable care (remote-only plus hybrid) increased from 65% to 77%. In 2024-2025, 7% of the weighted national sample reported a mobile app, online platform, or other digital mental health resource as a provider/resource category.
CONCLUSIONS: The observed national estimates show post-peak improvement in several mental health and functional indicators alongside an early-pandemic shift toward remote and hybrid care. Because the analysis used aggregate reports with changing institutional composition, these findings describe population-level trends rather than causal effects or individual recovery.},
}
RevDate: 2026-10-23
CmpDate: 2026-10-23
Structural Control of Phthalate Toxicity in Agricultural Soil Biofilms: Aliphatic-Chain-Length-Driven Hazards Revealed by Field Evidence, Multiomics, and Quantum Chemical Analysis.
Journal of agricultural and food chemistry, 74(38):29956-29970.
Phthalates (PAEs) pose significant ecological risks in greenhouse soils because of their hydrophobicity and persistence. This study combined field survey, microcosm experiments, multiomics analysis profiling, and quantum chemical calculations to investigate how the aliphatic chain length influences the toxicity of PAEs toward soil biofilms. Results showed that longer-chain PAEs caused stronger inhibition of biofilm formation, reduced extracellular polymeric substance polysaccharide production, enhanced oxidative stress, and disrupted microbial community structure. Multiomics revealed that PAEs primarily affected energy metabolism, electron transport, and glycerophospholipid metabolism. Molecular docking and density functional theory (DFT) calculations further suggested that PAEs preferentially interact with the Trp198 region of NADH dehydrogenase I, with the binding strength increasing with the aliphatic chain length. This study establishes a structural toxicology framework linking the molecular structure to biofilm dysfunction, providing mechanistic insights into the ecological risk assessment of PAEs.
Additional Links: PMID-42915864
Publisher:
PubMed:
Citation:
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@article {pmid42915864,
year = {2026},
author = {He, S and Yu, F and Feng, P and Chen, J and He, Z and Yang, C and Luo, Y and Xiang, Y and Li, Z},
title = {Structural Control of Phthalate Toxicity in Agricultural Soil Biofilms: Aliphatic-Chain-Length-Driven Hazards Revealed by Field Evidence, Multiomics, and Quantum Chemical Analysis.},
journal = {Journal of agricultural and food chemistry},
volume = {74},
number = {38},
pages = {29956-29970},
doi = {10.1021/acs.jafc.6c05749},
pmid = {42915864},
issn = {1520-5118},
support = {2024C04048//Key Research and Development Program of Zhejiang Province/ ; 22376185//National Natural Science Foundation of China/ ; 22576183//National Natural Science Foundation of China/ ; LY24C030001//Natural Science Foundation of Zhejiang Province/ ; 2024YFC3714800//National Key Research and Development Program of China/ ; SPCS-2025-03003//State Key Laboratory of Soil Pollution Control and Safety/ ; },
mesh = {*Biofilms/drug effects ; *Soil Pollutants/chemistry/toxicity ; Soil Microbiology ; Multiomics ; *Phthalic Acids/chemistry/toxicity ; Bacteria/drug effects/genetics/metabolism/isolation & purification/growth & development/classification ; Soil/chemistry ; Molecular Docking Simulation ; Molecular Structure ; Oxidative Stress/drug effects ; },
abstract = {Phthalates (PAEs) pose significant ecological risks in greenhouse soils because of their hydrophobicity and persistence. This study combined field survey, microcosm experiments, multiomics analysis profiling, and quantum chemical calculations to investigate how the aliphatic chain length influences the toxicity of PAEs toward soil biofilms. Results showed that longer-chain PAEs caused stronger inhibition of biofilm formation, reduced extracellular polymeric substance polysaccharide production, enhanced oxidative stress, and disrupted microbial community structure. Multiomics revealed that PAEs primarily affected energy metabolism, electron transport, and glycerophospholipid metabolism. Molecular docking and density functional theory (DFT) calculations further suggested that PAEs preferentially interact with the Trp198 region of NADH dehydrogenase I, with the binding strength increasing with the aliphatic chain length. This study establishes a structural toxicology framework linking the molecular structure to biofilm dysfunction, providing mechanistic insights into the ecological risk assessment of PAEs.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Biofilms/drug effects
*Soil Pollutants/chemistry/toxicity
Soil Microbiology
Multiomics
*Phthalic Acids/chemistry/toxicity
Bacteria/drug effects/genetics/metabolism/isolation & purification/growth & development/classification
Soil/chemistry
Molecular Docking Simulation
Molecular Structure
Oxidative Stress/drug effects
RevDate: 2026-10-23
CmpDate: 2026-10-23
Imaging the Adverse Effects of Tire-Derived Contaminants via Coelenterazine-Facilitated Albumin Luminescence In Vivo.
Environmental science & technology, 60(40):28352-28362.
The widespread use of automotive tires has resulted in the global distribution of tire-derived contaminants in the environment. In this study, we developed a versatile molecular imaging platform using novel synthesized coelenterazine (CTZ) analogs to quantitatively assess the impacts of tire additives and the primary oxidation products, 6PPD and 6PPD-Q, in vitro and in vivo. The results indicate that these compounds competitively block the interaction of CTZ analogs with serum albumins, suppressing luminescence signals. Specifically, 6PPD significantly reduced CTZ-facilitated luminescence in vitro, with pronounced suppressive effects observed for rabbit (55%) and porcine (65%) serum albumins. Interestingly, 6PPD and 6PPD-Q also suppressed human serum albumin (HSA)-facilitated CTZ luminescence by 31% and 47% respectively, depending on the specific CTZ indicator utilized. Collectively, these findings demonstrate that 6PPD and 6PPD-Q significantly interfere with the normal ligand-binding capacity of serum albumins across various species, including humans. This work contributes to ongoing efforts to evaluate and mitigate the ecological and public health risks posed by emerging contaminants from automotive vehicles.
Additional Links: PMID-42915971
Publisher:
PubMed:
Citation:
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@article {pmid42915971,
year = {2026},
author = {Kim, SB and Furuta, T and Nihongi, R and Kinugasa, S and Kitada, N and Thangudu, S and Natarajan, A and Maki, SA and Citterio, D and Paulmurugan, R},
title = {Imaging the Adverse Effects of Tire-Derived Contaminants via Coelenterazine-Facilitated Albumin Luminescence In Vivo.},
journal = {Environmental science & technology},
volume = {60},
number = {40},
pages = {28352-28362},
doi = {10.1021/acs.est.6c06255},
pmid = {42915971},
issn = {1520-5851},
support = {23KK0101//Japan Society for the Promotion of Science/ ; 25H01207//Japan Society for the Promotion of Science/ ; 25K22883//Japan Society for the Promotion of Science/ ; JPMXP1223UE5037//Ministry of Education, Culture, Sports, Science and Technology/ ; JPMXP1224UE5037//Ministry of Education, Culture, Sports, Science and Technology/ ; JPMXP1225UE5037//Ministry of Education, Culture, Sports, Science and Technology/ ; 1S10OD02351801A1//National Institutes of Health (NIH)/ ; 5R01CA209888//National Institutes of Health (NIH)/ ; NA//Canary Center at Stanford, Department of Radiology/ ; R01EB031799//National Institutes of Health (NIH)/ ; },
mesh = {Animals ; *Imidazoles ; Humans ; *Pyrazines ; Serum Albumin ; Luminescence ; Rabbits ; Swine ; },
abstract = {The widespread use of automotive tires has resulted in the global distribution of tire-derived contaminants in the environment. In this study, we developed a versatile molecular imaging platform using novel synthesized coelenterazine (CTZ) analogs to quantitatively assess the impacts of tire additives and the primary oxidation products, 6PPD and 6PPD-Q, in vitro and in vivo. The results indicate that these compounds competitively block the interaction of CTZ analogs with serum albumins, suppressing luminescence signals. Specifically, 6PPD significantly reduced CTZ-facilitated luminescence in vitro, with pronounced suppressive effects observed for rabbit (55%) and porcine (65%) serum albumins. Interestingly, 6PPD and 6PPD-Q also suppressed human serum albumin (HSA)-facilitated CTZ luminescence by 31% and 47% respectively, depending on the specific CTZ indicator utilized. Collectively, these findings demonstrate that 6PPD and 6PPD-Q significantly interfere with the normal ligand-binding capacity of serum albumins across various species, including humans. This work contributes to ongoing efforts to evaluate and mitigate the ecological and public health risks posed by emerging contaminants from automotive vehicles.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Imidazoles
Humans
*Pyrazines
Serum Albumin
Luminescence
Rabbits
Swine
RevDate: 2026-10-23
CmpDate: 2026-10-23
Comparing the Impacts of a Biopesticide and a Synthetic Pesticide on Potato Production: A Multi-Omics Analysis of Carvacrol and Dimethomorph.
Journal of agricultural and food chemistry, 74(40):31951-31962.
Long-term application of synthetic pesticides for potato late blight control has raised many ecological concerns, while broader impacts of biopesticides on production systems remain unclear. Field trials compared the effects of pesticides dimethomorph (synthetic) and carvacrol (biological) against an untreated control in a potato production system, integrating untargeted metabolomics, metabarcoding and quality trait analyses. Compared with the control group, both pesticide treatments upregulated tuber lipid metabolism but downregulated leaf defense-associated metabolism. For rhizosphere communities, while both treatments reduced beneficial bacterial taxa, carvacrol exerted less suppressive effects than dimethomorph and resulted in superior pathogen suppression. These changes were associated with enhanced potato quality under carvacrol treatment, with starch, flavonoid, and vitamin C contents each more than 10% higher than under dimethomorph. This study highlights the importance of evaluating both productivity end points and soil ecological consequences in field conditions, providing novel insights into the integration of biopesticides in sustainable crop production.
Additional Links: PMID-42916036
Publisher:
PubMed:
Citation:
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@article {pmid42916036,
year = {2026},
author = {Wang, W and Huang, W and Knight, SJ and Müller, K and Cheng, L and Xiang, F and Long, J and Kah, M},
title = {Comparing the Impacts of a Biopesticide and a Synthetic Pesticide on Potato Production: A Multi-Omics Analysis of Carvacrol and Dimethomorph.},
journal = {Journal of agricultural and food chemistry},
volume = {74},
number = {40},
pages = {31951-31962},
doi = {10.1021/acs.jafc.6c09742},
pmid = {42916036},
issn = {1520-5118},
support = {202408440066//China Scholarship Council/ ; Qian (2022) 4008//Central Government Guiding Local Science and Technology of Guizhou Province/ ; },
mesh = {*Solanum tuberosum/drug effects/growth & development/metabolism/chemistry/microbiology/genetics ; Multiomics ; *Cymenes/pharmacology ; *Monoterpenes/pharmacology ; Plant Tubers/metabolism/chemistry/drug effects/growth & development/microbiology ; Metabolomics ; Plant Diseases/microbiology/prevention & control ; *Pesticides/pharmacology ; Bacteria/genetics/classification/isolation & purification/drug effects ; *Biological Control Agents/pharmacology ; },
abstract = {Long-term application of synthetic pesticides for potato late blight control has raised many ecological concerns, while broader impacts of biopesticides on production systems remain unclear. Field trials compared the effects of pesticides dimethomorph (synthetic) and carvacrol (biological) against an untreated control in a potato production system, integrating untargeted metabolomics, metabarcoding and quality trait analyses. Compared with the control group, both pesticide treatments upregulated tuber lipid metabolism but downregulated leaf defense-associated metabolism. For rhizosphere communities, while both treatments reduced beneficial bacterial taxa, carvacrol exerted less suppressive effects than dimethomorph and resulted in superior pathogen suppression. These changes were associated with enhanced potato quality under carvacrol treatment, with starch, flavonoid, and vitamin C contents each more than 10% higher than under dimethomorph. This study highlights the importance of evaluating both productivity end points and soil ecological consequences in field conditions, providing novel insights into the integration of biopesticides in sustainable crop production.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Solanum tuberosum/drug effects/growth & development/metabolism/chemistry/microbiology/genetics
Multiomics
*Cymenes/pharmacology
*Monoterpenes/pharmacology
Plant Tubers/metabolism/chemistry/drug effects/growth & development/microbiology
Metabolomics
Plant Diseases/microbiology/prevention & control
*Pesticides/pharmacology
Bacteria/genetics/classification/isolation & purification/drug effects
*Biological Control Agents/pharmacology
RevDate: 2026-10-23
CmpDate: 2026-10-23
Using Multimodal Large Language Models for Extracting Structured Life-Cycle Inventory Data from Scientific Literature.
Environmental science & technology, 60(39):27792-27802.
Life-cycle inventory (LCI) construction remains labor-intensive because relevant information is distributed across heterogeneous text, tables, and figures and is reported using inconsistent terminology, units, and system boundaries. Although large language models (LLMs) offer opportunities for automated information extraction, LCI-specific workflows that reliably convert literature-reported information to structured and traceable inventory records remain limited. Here, we present LCIMiner, an automated LLM-based workflow integrating literature retrieval and screening, text-based selection of LCI-relevant figures and tables, multimodal information extraction, task-specific self-review, and structured LCI construction without model retraining. We evaluated LCIMiner in aquaculture, polymer production, and biofuel production, which differ substantially in their production processes, inventory structures, and reporting conventions. Across these domains, LCIMiner achieved higher end-to-end extraction performance than matched single-model baselines and converted heterogeneous literature evidence to machine-readable, source-traceable LCI records. We further applied a separate human-guided harmonization procedure to organize the extracted aquaculture records into a cross-study analytical data set while preserving the original source information. Together, the automated extraction workflow and subsequent human-guided harmonization provide a transparent and extensible approach for developing reusable foreground LCI data sets from heterogeneous scientific literature.
Additional Links: PMID-42917023
Publisher:
PubMed:
Citation:
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@article {pmid42917023,
year = {2026},
author = {Wang, Y and Song, L and Wu, Y and Fantke, P and Li, S},
title = {Using Multimodal Large Language Models for Extracting Structured Life-Cycle Inventory Data from Scientific Literature.},
journal = {Environmental science & technology},
volume = {60},
number = {39},
pages = {27792-27802},
doi = {10.1021/acs.est.6c12624},
pmid = {42917023},
issn = {1520-5851},
support = {42361144862//National Natural Science Foundation of China/ ; 42576256//National Natural Science Foundation of China/ ; 72348004//National Natural Science Foundation of China/ ; },
mesh = {Large Language Models ; },
abstract = {Life-cycle inventory (LCI) construction remains labor-intensive because relevant information is distributed across heterogeneous text, tables, and figures and is reported using inconsistent terminology, units, and system boundaries. Although large language models (LLMs) offer opportunities for automated information extraction, LCI-specific workflows that reliably convert literature-reported information to structured and traceable inventory records remain limited. Here, we present LCIMiner, an automated LLM-based workflow integrating literature retrieval and screening, text-based selection of LCI-relevant figures and tables, multimodal information extraction, task-specific self-review, and structured LCI construction without model retraining. We evaluated LCIMiner in aquaculture, polymer production, and biofuel production, which differ substantially in their production processes, inventory structures, and reporting conventions. Across these domains, LCIMiner achieved higher end-to-end extraction performance than matched single-model baselines and converted heterogeneous literature evidence to machine-readable, source-traceable LCI records. We further applied a separate human-guided harmonization procedure to organize the extracted aquaculture records into a cross-study analytical data set while preserving the original source information. Together, the automated extraction workflow and subsequent human-guided harmonization provide a transparent and extensible approach for developing reusable foreground LCI data sets from heterogeneous scientific literature.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Large Language Models
RevDate: 2026-10-23
CmpDate: 2026-10-23
Phosphorylation-Mediated Regulatory Networks Fine-Tune Rye Responses to PVC Nanoplastic Stress: Evidence from Multiomics and Computational Biology.
Nano letters, 26(39):13309-13317.
Although polyvinyl chloride nanoplastics (NPs-PVC) are widespread emerging contaminants, their crop toxicity mechanisms─especially at the post-translational modification (PTM) level─remain unclear. Using multiscale exposures (short-term hydroponics and whole-life-cycle soil cultivation), integrated physiological, imaging, omics (transcriptomics and phosphoproteomics), molecular docking, and molecular dynamics simulations, we systematically evaluated NPs-PVC impacts on Secale cereale. Short-term exposure inhibited growth, reduced photosynthesis, and induced oxidative stress, with PVC stably binding cytochrome f and catalase. Long-term exposure decreased grain weight and tillers, accompanied by transcriptional shifts in metabolism and stress pathways. Phosphoproteomics revealed widespread phosphorylation changes in photosynthesis- and lipid metabolism-related proteins, with PVC-14-3-3λ binding confirmed by simulation. Structural equation modeling demonstrated that NPs-PVC regulates agronomic traits mainly through oxidative stress and photosynthesis disruption. Collectively, NPs-PVC suppresses rye growth via direct protein binding, transcriptional reprogramming, and PTM-mediated physiological tuning. This study advances the understanding of nanoplastic phytotoxicity mechanisms and agricultural ecological risk assessment.
Additional Links: PMID-42917363
Publisher:
PubMed:
Citation:
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@article {pmid42917363,
year = {2026},
author = {Hu, J and Bao, G and Guo, B and Nan, Y and Yi, X and Yang, X and Wang, K and Li, J},
title = {Phosphorylation-Mediated Regulatory Networks Fine-Tune Rye Responses to PVC Nanoplastic Stress: Evidence from Multiomics and Computational Biology.},
journal = {Nano letters},
volume = {26},
number = {39},
pages = {13309-13317},
doi = {10.1021/acs.nanolett.6c02670},
pmid = {42917363},
issn = {1530-6992},
support = {20250203129SF//Jilin Provincial Scientific and Technological Development Program/ ; 32371777//National Natural Science Foundation of China (NSFC)/ ; },
mesh = {Multiomics ; Phosphorylation/drug effects ; Oxidative Stress/drug effects ; *Secale/drug effects/metabolism/growth & development/genetics ; Computational Biology ; Photosynthesis/drug effects ; Protein Processing, Post-Translational/drug effects ; Molecular Docking Simulation ; },
abstract = {Although polyvinyl chloride nanoplastics (NPs-PVC) are widespread emerging contaminants, their crop toxicity mechanisms─especially at the post-translational modification (PTM) level─remain unclear. Using multiscale exposures (short-term hydroponics and whole-life-cycle soil cultivation), integrated physiological, imaging, omics (transcriptomics and phosphoproteomics), molecular docking, and molecular dynamics simulations, we systematically evaluated NPs-PVC impacts on Secale cereale. Short-term exposure inhibited growth, reduced photosynthesis, and induced oxidative stress, with PVC stably binding cytochrome f and catalase. Long-term exposure decreased grain weight and tillers, accompanied by transcriptional shifts in metabolism and stress pathways. Phosphoproteomics revealed widespread phosphorylation changes in photosynthesis- and lipid metabolism-related proteins, with PVC-14-3-3λ binding confirmed by simulation. Structural equation modeling demonstrated that NPs-PVC regulates agronomic traits mainly through oxidative stress and photosynthesis disruption. Collectively, NPs-PVC suppresses rye growth via direct protein binding, transcriptional reprogramming, and PTM-mediated physiological tuning. This study advances the understanding of nanoplastic phytotoxicity mechanisms and agricultural ecological risk assessment.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Multiomics
Phosphorylation/drug effects
Oxidative Stress/drug effects
*Secale/drug effects/metabolism/growth & development/genetics
Computational Biology
Photosynthesis/drug effects
Protein Processing, Post-Translational/drug effects
Molecular Docking Simulation
RevDate: 2026-10-23
CmpDate: 2026-10-23
Building the Foundations of AI-Driven Toxicology: How to Use Fragmented Data for Mechanism-Based Human Health Risk Assessment.
Environmental science & technology, 60(38):26908-26921.
Environmental human health assessment requires reliable, comprehensive, and standardized toxicology data to support regulatory decision-making. Yet, existing databases remain fragmented, with narrow and imbalanced coverage of species and organs, incomplete dose-response relationships, and inconsistent validation chains, limiting their utility for risk prediction. Meanwhile, regulatory and technological shifts toward AI-based computational models highlight the urgency of building high-quality toxicology databases as the foundation of next-generation methodologies. This perspective outlines key challenges in data curation, harmonization, and accessibility and presents strategic solutions, including building confidence grading frameworks to leverage heterogeneous data sets, using novel high-throughput platforms to generate interaction data with high accuracy and efficiency, and facilitating community-based data sharing. We further emphasize the development of AI-enabled strategies to improve the organization, interoperability, and usability of toxicological data infrastructures in support of AI-driven environmental toxicology and mechanism-based human health risk assessment. These strategies include integrating knowledge networks to construct mechanism-informed AI models, applying transfer learning frameworks that bridge large-scale pretraining with small-sample fine-tuning, and leveraging knowledge graph enhancement and prompt learning to predict systematic "Exposure-Biology-Disease" interactions. These efforts can transform fragmented resources into systematic, interpretable, and predictive systems. We concluded that building high-quality toxicology databases can accelerate the transition to AI-driven toxicology, providing a foundation for more reliable risk assessment and stronger global environmental health protection.
Additional Links: PMID-42484051
Publisher:
PubMed:
Citation:
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@article {pmid42484051,
year = {2026},
author = {Wang, B and Wu, T and Shou, Y and Ma, Y and Ren, M and Gago-Ferrero, P and Schlenk, D and Fang, M},
title = {Building the Foundations of AI-Driven Toxicology: How to Use Fragmented Data for Mechanism-Based Human Health Risk Assessment.},
journal = {Environmental science & technology},
volume = {60},
number = {38},
pages = {26908-26921},
doi = {10.1021/acs.est.5c17092},
pmid = {42484051},
issn = {1520-5851},
support = {42477455//National Natural Science Foundation of China/ ; 2023YFC3708305//National Key Research & Development Program of Ministry of Science and Technology of China/ ; BJST20250209//Beijing Municipal Ecology and Environment Bureau/ ; XDB0750300//Strategy Priority Research Program (Category B) of Chinese Academy of Sciences/ ; },
mesh = {Risk Assessment ; Humans ; *Artificial Intelligence ; *Toxicology ; Databases, Factual ; },
abstract = {Environmental human health assessment requires reliable, comprehensive, and standardized toxicology data to support regulatory decision-making. Yet, existing databases remain fragmented, with narrow and imbalanced coverage of species and organs, incomplete dose-response relationships, and inconsistent validation chains, limiting their utility for risk prediction. Meanwhile, regulatory and technological shifts toward AI-based computational models highlight the urgency of building high-quality toxicology databases as the foundation of next-generation methodologies. This perspective outlines key challenges in data curation, harmonization, and accessibility and presents strategic solutions, including building confidence grading frameworks to leverage heterogeneous data sets, using novel high-throughput platforms to generate interaction data with high accuracy and efficiency, and facilitating community-based data sharing. We further emphasize the development of AI-enabled strategies to improve the organization, interoperability, and usability of toxicological data infrastructures in support of AI-driven environmental toxicology and mechanism-based human health risk assessment. These strategies include integrating knowledge networks to construct mechanism-informed AI models, applying transfer learning frameworks that bridge large-scale pretraining with small-sample fine-tuning, and leveraging knowledge graph enhancement and prompt learning to predict systematic "Exposure-Biology-Disease" interactions. These efforts can transform fragmented resources into systematic, interpretable, and predictive systems. We concluded that building high-quality toxicology databases can accelerate the transition to AI-driven toxicology, providing a foundation for more reliable risk assessment and stronger global environmental health protection.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Risk Assessment
Humans
*Artificial Intelligence
*Toxicology
Databases, Factual
RevDate: 2026-10-23
CmpDate: 2026-10-23
Omics approaches in insect diapause research.
Journal of insect physiology, 174:105067.
Diapause is a genetically programmed developmental or reproductive arrest that helps insects survive adverse seasonal conditions. Our understanding of the molecular regulation of this complex trait has significantly improved through the use of omics technologies over the last few decades. In this review, we have compiled current omics research on insect diapause, spanning transcriptomics, proteomics, metabolomics, lipidomics, epigenomics, genomics, and post-transcriptional regulatory approaches. Transcriptomics has led the field, showing that the diapause program develops gradually through a series of gene expression changes involving insulin/Forkhead box O (FOXO) signaling, circadian clock genes, and juvenile hormone and ecdysteroid pathways. Proteomic studies consistently show that mRNA and protein levels do not always match during diapause, emphasizing the importance of translational and post-translational regulation. Metabolomic and lipidomic analyses have identified a conserved set of metabolic adjustments, including lipid accumulation, membrane remodeling, and cryoprotectant production. Although still limited, epigenomic studies are beginning to provide functional evidence linking chromatin modifications to diapause regulation. Genomics is connecting diapause traits to candidate loci in the genome and to the evolutionary processes shaping diapause across populations. Across these layers, omics has reframed diapause from a program defined by a few candidate genes into a coordinated, large-scale molecular reprogramming, and has exposed regulatory layers, particularly post-transcriptional and translational control, that were largely inaccessible to earlier candidate-gene and physiological approaches. We emphasize the emerging benefits of integrating multiple omics approaches, which reveal regulatory mechanisms inaccessible via a single method. We argue that critical gaps include cell and tissue heterogeneity, limited functional validation, broader taxonomic representation, greater integration across omics layers, and stronger links between omics data and the evolutionary context of diapause. We also discuss how new omics technologies, such as single-cell sequencing, could enable novel insights into diapause regulation.
Additional Links: PMID-42764118
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PubMed:
Citation:
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@article {pmid42764118,
year = {2026},
author = {Güney, G and Cedden, D and Lehmann, P},
title = {Omics approaches in insect diapause research.},
journal = {Journal of insect physiology},
volume = {174},
number = {},
pages = {105067},
doi = {10.1016/j.jinsphys.2026.105067},
pmid = {42764118},
issn = {1879-1611},
mesh = {Animals ; *Diapause, Insect/genetics ; Genomics ; *Insecta/genetics/physiology/metabolism ; Metabolomics ; Multiomics ; Proteomics ; },
abstract = {Diapause is a genetically programmed developmental or reproductive arrest that helps insects survive adverse seasonal conditions. Our understanding of the molecular regulation of this complex trait has significantly improved through the use of omics technologies over the last few decades. In this review, we have compiled current omics research on insect diapause, spanning transcriptomics, proteomics, metabolomics, lipidomics, epigenomics, genomics, and post-transcriptional regulatory approaches. Transcriptomics has led the field, showing that the diapause program develops gradually through a series of gene expression changes involving insulin/Forkhead box O (FOXO) signaling, circadian clock genes, and juvenile hormone and ecdysteroid pathways. Proteomic studies consistently show that mRNA and protein levels do not always match during diapause, emphasizing the importance of translational and post-translational regulation. Metabolomic and lipidomic analyses have identified a conserved set of metabolic adjustments, including lipid accumulation, membrane remodeling, and cryoprotectant production. Although still limited, epigenomic studies are beginning to provide functional evidence linking chromatin modifications to diapause regulation. Genomics is connecting diapause traits to candidate loci in the genome and to the evolutionary processes shaping diapause across populations. Across these layers, omics has reframed diapause from a program defined by a few candidate genes into a coordinated, large-scale molecular reprogramming, and has exposed regulatory layers, particularly post-transcriptional and translational control, that were largely inaccessible to earlier candidate-gene and physiological approaches. We emphasize the emerging benefits of integrating multiple omics approaches, which reveal regulatory mechanisms inaccessible via a single method. We argue that critical gaps include cell and tissue heterogeneity, limited functional validation, broader taxonomic representation, greater integration across omics layers, and stronger links between omics data and the evolutionary context of diapause. We also discuss how new omics technologies, such as single-cell sequencing, could enable novel insights into diapause regulation.},
}
MeSH Terms:
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Animals
*Diapause, Insect/genetics
Genomics
*Insecta/genetics/physiology/metabolism
Metabolomics
Multiomics
Proteomics
RevDate: 2026-10-20
Barriers and enablers to engagement with green social prescribing in primary care: a scoping review using the socio-ecological model.
BJGP open pii:BJGPO.2026.0219 [Epub ahead of print].
BACKGROUND: Green social prescribing (GSP) connects individuals with nature-based interventions (NBIs) through healthcare providers, link workers, and social and community networks. While evidence supports the health benefits of NBIs, further research is needed to understand the factors that influence engagement.
AIM: To explore barriers and enablers to GSP and NBIs for prescribers, service users and community providers.
DESIGN & SETTING: A scoping review in primary care and community settings.
METHOD: We systematically searched Medline, Embase, CINAHL, Web of Science, and SCOPUS from 2019. We assessed quality using the Critical Appraisal Skills Programme and the Mixed Methods Appraisal Tool. We mapped data to the socioecological framework during synthesis.
RESULTS: Out of 4864 screened records, 45 studies from 11 countries were included. GSP and NBIs face micro-level barriers such as knowledge gaps, cultural and social issues, time and cost constraints and perceptions of adverse weather; meso-level and macro-level challenges include unequal access, underfunded NBIs, an emphasis on biomedical models, safety concerns, limited training, and insufficient policy support and leadership. Engagement was enabled by flexible, person-centred approaches, tailored NBIs with clear pathways, including link workers, strong cross-sector partnerships, community co-design, and public health campaigns.
CONCLUSION: Promoting engagement with GSP and NBIs requires a multi-level approach that addresses systemic barriers through collaboration between prescribers, third-sector organisations and policymakers. Investment in workforce training and sustainable funding models is critical to support long-term success in primary care and community settings. Addressing health inequalities by improving access for people in areas of high socioeconomic deprivation remains a priority.
Additional Links: PMID-42901538
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PubMed:
Citation:
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@article {pmid42901538,
year = {2026},
author = {Frost, H and Mason, B and Tooman, TR and Bareham, BR and Ng, L and Haines, H and Arakelyan, S and Lewis, S and Wolters, MK and Hawkins, K and Ogden, ME and Pain, HG and Mercer, SW},
title = {Barriers and enablers to engagement with green social prescribing in primary care: a scoping review using the socio-ecological model.},
journal = {BJGP open},
volume = {},
number = {},
pages = {},
doi = {10.3399/BJGPO.2026.0219},
pmid = {42901538},
issn = {2398-3795},
abstract = {BACKGROUND: Green social prescribing (GSP) connects individuals with nature-based interventions (NBIs) through healthcare providers, link workers, and social and community networks. While evidence supports the health benefits of NBIs, further research is needed to understand the factors that influence engagement.
AIM: To explore barriers and enablers to GSP and NBIs for prescribers, service users and community providers.
DESIGN & SETTING: A scoping review in primary care and community settings.
METHOD: We systematically searched Medline, Embase, CINAHL, Web of Science, and SCOPUS from 2019. We assessed quality using the Critical Appraisal Skills Programme and the Mixed Methods Appraisal Tool. We mapped data to the socioecological framework during synthesis.
RESULTS: Out of 4864 screened records, 45 studies from 11 countries were included. GSP and NBIs face micro-level barriers such as knowledge gaps, cultural and social issues, time and cost constraints and perceptions of adverse weather; meso-level and macro-level challenges include unequal access, underfunded NBIs, an emphasis on biomedical models, safety concerns, limited training, and insufficient policy support and leadership. Engagement was enabled by flexible, person-centred approaches, tailored NBIs with clear pathways, including link workers, strong cross-sector partnerships, community co-design, and public health campaigns.
CONCLUSION: Promoting engagement with GSP and NBIs requires a multi-level approach that addresses systemic barriers through collaboration between prescribers, third-sector organisations and policymakers. Investment in workforce training and sustainable funding models is critical to support long-term success in primary care and community settings. Addressing health inequalities by improving access for people in areas of high socioeconomic deprivation remains a priority.},
}
RevDate: 2026-10-23
CmpDate: 2026-10-22
Virtual Reality Therapy Assistants for Adjunctive Cue Exposure Training in the Treatment of Alcohol Use Disorder (VITAACue-AUD): Protocol for a Technical Feasibility Study.
JMIR research protocols, 15:e99080.
BACKGROUND: Alcohol use disorder (AUD) is associated with a substantial individual and societal burden. Cue exposure approaches can support treatment by targeting conditioned cue reactivity and high-risk contextual associations. However, routine implementation is limited by therapist time, scalability constraints, and the difficulty of reproducing ecologically valid drinking situations in standard care settings. Virtual reality (VR) and AI have been proposed as promising tools to support scalable and contextually rich interventions in mental health care.
OBJECTIVE: This study aims to develop and technically evaluate a prototype virtual reality-based therapy assistant (VRTA) for narratively guided alcohol cue exposure in immersive VR.
METHODS: This is a single-site technical feasibility study conducted at the Central Institute of Mental Health in Mannheim, Germany. It builds on a participatory development process, including multistakeholder workshops with developers, researchers, clinicians, and patient and public involvement contributors. The study began with workshops to refine implementation priorities. A VRTA prototype will be developed to guide alcohol cue exposure scenarios through speech-based interaction with a computer-generated character in immersive VR, informed by established exposure manuals (development ongoing, currently with a text-based chatbot prototype and a separate VR environment). An iterative qualitative expert appraisal will be conducted during development (ongoing). In addition, 20 adult patients with AUD will participate in an observer-based evaluation in which therapeutic staff demonstrate the prototype and patients provide qualitative feedback.
RESULTS: Results are expected on the technical feasibility of the VRTA prototype, including interaction quality and integration into therapeutic workflows. Qualitative findings from expert appraisal and patient feedback (observed from a third-person perspective) will provide insights into usability, manual conformity, acceptability, and perceived therapeutic relevance (audio transcript coding and qualitative evaluation are ongoing). Funding for this study has been approved by the Hetzler Foundation from November 2025 to October 2027. Initial workshops were conducted in January 2026 and May 2026. Prototype testing by expert participants with patient observers is planned to start in November 2026 and continue until April 2027.
CONCLUSIONS: This study is intended to generate design specifications and feasibility data to inform subsequent prototype refinement and future clinical evaluation studies.
Additional Links: PMID-42902919
PubMed:
Citation:
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@article {pmid42902919,
year = {2026},
author = {Kammler-Sücker, KI and Heizmann, C and Eidenmueller, K and Werner, L and Prexl, T and Rust, F and Schiermeyer, RD and Mohr, MRM and Kellmeyer, P and Lenz, B},
title = {Virtual Reality Therapy Assistants for Adjunctive Cue Exposure Training in the Treatment of Alcohol Use Disorder (VITAACue-AUD): Protocol for a Technical Feasibility Study.},
journal = {JMIR research protocols},
volume = {15},
number = {},
pages = {e99080},
pmid = {42902919},
issn = {1929-0748},
mesh = {Humans ; Feasibility Studies ; *Virtual Reality Exposure Therapy/methods ; Cues ; *Alcoholism/therapy/psychology ; Germany ; Virtual Reality ; },
abstract = {BACKGROUND: Alcohol use disorder (AUD) is associated with a substantial individual and societal burden. Cue exposure approaches can support treatment by targeting conditioned cue reactivity and high-risk contextual associations. However, routine implementation is limited by therapist time, scalability constraints, and the difficulty of reproducing ecologically valid drinking situations in standard care settings. Virtual reality (VR) and AI have been proposed as promising tools to support scalable and contextually rich interventions in mental health care.
OBJECTIVE: This study aims to develop and technically evaluate a prototype virtual reality-based therapy assistant (VRTA) for narratively guided alcohol cue exposure in immersive VR.
METHODS: This is a single-site technical feasibility study conducted at the Central Institute of Mental Health in Mannheim, Germany. It builds on a participatory development process, including multistakeholder workshops with developers, researchers, clinicians, and patient and public involvement contributors. The study began with workshops to refine implementation priorities. A VRTA prototype will be developed to guide alcohol cue exposure scenarios through speech-based interaction with a computer-generated character in immersive VR, informed by established exposure manuals (development ongoing, currently with a text-based chatbot prototype and a separate VR environment). An iterative qualitative expert appraisal will be conducted during development (ongoing). In addition, 20 adult patients with AUD will participate in an observer-based evaluation in which therapeutic staff demonstrate the prototype and patients provide qualitative feedback.
RESULTS: Results are expected on the technical feasibility of the VRTA prototype, including interaction quality and integration into therapeutic workflows. Qualitative findings from expert appraisal and patient feedback (observed from a third-person perspective) will provide insights into usability, manual conformity, acceptability, and perceived therapeutic relevance (audio transcript coding and qualitative evaluation are ongoing). Funding for this study has been approved by the Hetzler Foundation from November 2025 to October 2027. Initial workshops were conducted in January 2026 and May 2026. Prototype testing by expert participants with patient observers is planned to start in November 2026 and continue until April 2027.
CONCLUSIONS: This study is intended to generate design specifications and feasibility data to inform subsequent prototype refinement and future clinical evaluation studies.},
}
MeSH Terms:
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hide MeSH Terms
Humans
Feasibility Studies
*Virtual Reality Exposure Therapy/methods
Cues
*Alcoholism/therapy/psychology
Germany
Virtual Reality
RevDate: 2026-10-23
CmpDate: 2026-10-22
Integrative and complementary practices, hypertension and social indicators: an ecological study, Brazil, 2023.
Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil, 35:e20250570.
Additional Links: PMID-42903007
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Citation:
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@article {pmid42903007,
year = {2026},
author = {do Nascimento, ADSF and de Souza, MCL and Rossoni, SL and Dos Santos, JH and Lopes, WA and Pujals, C and Pedroso, RB},
title = {Integrative and complementary practices, hypertension and social indicators: an ecological study, Brazil, 2023.},
journal = {Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil},
volume = {35},
number = {},
pages = {e20250570},
pmid = {42903007},
issn = {2237-9622},
mesh = {Humans ; Brazil/epidemiology ; *Hypertension/therapy/epidemiology ; Socioeconomic Factors ; *Primary Health Care/statistics & numerical data ; Gross Domestic Product ; Health Information Systems ; Socioeconomic Disparities in Health ; },
}
MeSH Terms:
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Humans
Brazil/epidemiology
*Hypertension/therapy/epidemiology
Socioeconomic Factors
*Primary Health Care/statistics & numerical data
Gross Domestic Product
Health Information Systems
Socioeconomic Disparities in Health
RevDate: 2026-10-22
CmpDate: 2026-10-22
Net ecosystem productivity of grasslands: A chamber-based global database.
Ecology, 107(10):.
Net ecosystem productivity (NEP) of global grasslands-one of the largest and most variable components of the terrestrial carbon budget-provides critical insight into the magnitude and dynamics of the global carbon balance. Extensive field measurements have been derived from static-chamber techniques; however, these data have remained fragmented at individual sites or regions and have seldom been synthesized into a consistent global product. Here, chamber-based NEP measurements from 221 publications (1992-2023) in global grasslands were obtained, critically filtered, and condensed in a comprehensive global database. This database comprised 1521 individual NEP records from 275 sites across 30 countries. The dataset further included information on site location, ecosystem type, dominant species, climatic variables, soil properties, measurement timing (year, month, and day), and sampling protocol. The study sites encompassed global grasslands with latitudinal range of 62.22° S to 78.88° N, longitudinal range of 156.62° W to 161.51° E, and altitudes from -1 to 4852 m above sea level, covering broad climatic gradients (mean annual temperature: -17°C to 32.1°C; mean annual precipitation: 17-2226 mm; potential evapotranspiration: 152-1819 mm year[-1]). Our database enables (1) elucidation of the biogeographic pattern of grassland NEP, (2) assessment of grassland carbon-sequestration potential under future global-change scenarios, and (3) validation of both machine-learning and process-based model estimates of grassland NEP at the global scale. The database is available under a CC BY 4.0 license. The authors kindly request users to cite this data paper while using the database in acknowledgment of all the hard work that went into compiling the data.
Additional Links: PMID-42905534
Publisher:
PubMed:
Citation:
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@article {pmid42905534,
year = {2026},
author = {Zheng, J and Peng, Z and Liu, Y and Cai, Q and Fang, W and Ma, S and Zhang, Z},
title = {Net ecosystem productivity of grasslands: A chamber-based global database.},
journal = {Ecology},
volume = {107},
number = {10},
pages = {},
doi = {10.1002/ecy.70354},
pmid = {42905534},
issn = {1939-9170},
support = {202505AA350008//Science and Technology Talents and Platform Program of Yunnan Province/ ; 202303AC100009//Key Research and Development Program of Yunnan Province/ ; 32571918//National Natural Science Foundation of China/ ; JYB2025XDXM904//Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China/ ; 2025Y0078//Scientific Research Foundation of Education Department of Yunnan Province/ ; //Scientific Research and Innovation Project of Postgraduate Students in the Academic Degree of Yunnan University/ ; },
mesh = {*Grassland ; *Databases, Factual ; Climate ; },
abstract = {Net ecosystem productivity (NEP) of global grasslands-one of the largest and most variable components of the terrestrial carbon budget-provides critical insight into the magnitude and dynamics of the global carbon balance. Extensive field measurements have been derived from static-chamber techniques; however, these data have remained fragmented at individual sites or regions and have seldom been synthesized into a consistent global product. Here, chamber-based NEP measurements from 221 publications (1992-2023) in global grasslands were obtained, critically filtered, and condensed in a comprehensive global database. This database comprised 1521 individual NEP records from 275 sites across 30 countries. The dataset further included information on site location, ecosystem type, dominant species, climatic variables, soil properties, measurement timing (year, month, and day), and sampling protocol. The study sites encompassed global grasslands with latitudinal range of 62.22° S to 78.88° N, longitudinal range of 156.62° W to 161.51° E, and altitudes from -1 to 4852 m above sea level, covering broad climatic gradients (mean annual temperature: -17°C to 32.1°C; mean annual precipitation: 17-2226 mm; potential evapotranspiration: 152-1819 mm year[-1]). Our database enables (1) elucidation of the biogeographic pattern of grassland NEP, (2) assessment of grassland carbon-sequestration potential under future global-change scenarios, and (3) validation of both machine-learning and process-based model estimates of grassland NEP at the global scale. The database is available under a CC BY 4.0 license. The authors kindly request users to cite this data paper while using the database in acknowledgment of all the hard work that went into compiling the data.},
}
MeSH Terms:
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*Grassland
*Databases, Factual
Climate
RevDate: 2026-10-22
CmpDate: 2026-10-22
The global burden of female breast cancer attributable to high fasting plasma glucose: A comprehensive analysis of the GBD database from 1990 to 2023.
PloS one, 21(10):e0359268.
BACKGROUND: High fasting plasma glucose (HFPG) is an established risk factor for breast cancer (BC). However, accurate and up-to-date estimates of the global burden of breast cancer attributable to high fasting plasma glucose (BC-HFPG) are scarce. This study aims to provide a comprehensive analysis of the burden of BC-HFPG using data from the Global Burden of Disease (GBD) database from 1990 to2023.
METHODS: We performed a comprehensive descriptive analysis of the burden of female BC-HFPG based on the GBD 2023 database. The core metrics analyzed were the absolute number of death and disability-adjusted life years (DALY). To ensure comparability across populations with differing age structures, we also analyzed the age-standardized mortality rate (ASMR) and the age-standardized DALY rate (ASDR). The average annual percent change (AAPC) was used to further comprehensively describe the burden of disease and its changing trends. In addition to the retrospective analysis from 1990 to 2023, we used the Bayesian age-period-cohort (BAPC) model to generate predicted data on the burden of female BC-HFPG from 2024 to 2050.
RESULTS: Female BC-HFPG accounted for 48,307 deaths and 1,406,186 DALYs globally in 2023. From 1990 to 2023, the global ASMR and ASDR of female BC-HFPG showed overall upward trends, with an average annual percentage change (AAPC) of 0.28% (95% CI: 0.18% to 0.38%) for ASMR and 0.44% (95% CI: 0.37% to 0.51%) for ASDR; the two rates increased from 0.92 and 26.22 per 100,000 in 1990 to 1.00 and 30.17 per 100,000 in 2023, respectively. The burden varied substantially across the 21 GBD regions and 204 countries and territories in 2023. In 2023, SDI was only weakly correlated with ASMR (Spearman ρ = 0.20, P = 0.004) and not significantly correlated with ASDR, and the burden peaked in low-middle SDI quintile countries. The BAPC model projected that the ASMR and ASDR of female BC-HFPG would continue to rise from 2024 to 2050.
CONCLUSION: The global burden of female BC-HFPG increased from 1990 to 2023 and is projected to continue rising through 2050, disproportionately affecting low- and low-middle SDI regions. These findings suggest that glycemic management and metabolic risk-factor control warrant consideration within comprehensive breast cancer prevention frameworks. However, because this is an ecological, population-level analysis, whether glucose lowering interventions can reduce breast cancer incidence remains to be established in prospective interventional studies. Our results may help prioritize regions and populations for future etiological and intervention research.
Additional Links: PMID-42905647
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@article {pmid42905647,
year = {2026},
author = {Shi, H and Song, Z and Chen, Y and Liu, S and Song, Y},
title = {The global burden of female breast cancer attributable to high fasting plasma glucose: A comprehensive analysis of the GBD database from 1990 to 2023.},
journal = {PloS one},
volume = {21},
number = {10},
pages = {e0359268},
pmid = {42905647},
issn = {1932-6203},
mesh = {Female ; *Breast Neoplasms/epidemiology/blood/mortality/etiology ; Humans ; *Blood Glucose/metabolism/analysis ; Global Burden of Disease ; *Fasting/blood ; Databases, Factual ; Bayes Theorem ; Disability-Adjusted Life Years ; Risk Factors ; Retrospective Studies ; Middle Aged ; },
abstract = {BACKGROUND: High fasting plasma glucose (HFPG) is an established risk factor for breast cancer (BC). However, accurate and up-to-date estimates of the global burden of breast cancer attributable to high fasting plasma glucose (BC-HFPG) are scarce. This study aims to provide a comprehensive analysis of the burden of BC-HFPG using data from the Global Burden of Disease (GBD) database from 1990 to2023.
METHODS: We performed a comprehensive descriptive analysis of the burden of female BC-HFPG based on the GBD 2023 database. The core metrics analyzed were the absolute number of death and disability-adjusted life years (DALY). To ensure comparability across populations with differing age structures, we also analyzed the age-standardized mortality rate (ASMR) and the age-standardized DALY rate (ASDR). The average annual percent change (AAPC) was used to further comprehensively describe the burden of disease and its changing trends. In addition to the retrospective analysis from 1990 to 2023, we used the Bayesian age-period-cohort (BAPC) model to generate predicted data on the burden of female BC-HFPG from 2024 to 2050.
RESULTS: Female BC-HFPG accounted for 48,307 deaths and 1,406,186 DALYs globally in 2023. From 1990 to 2023, the global ASMR and ASDR of female BC-HFPG showed overall upward trends, with an average annual percentage change (AAPC) of 0.28% (95% CI: 0.18% to 0.38%) for ASMR and 0.44% (95% CI: 0.37% to 0.51%) for ASDR; the two rates increased from 0.92 and 26.22 per 100,000 in 1990 to 1.00 and 30.17 per 100,000 in 2023, respectively. The burden varied substantially across the 21 GBD regions and 204 countries and territories in 2023. In 2023, SDI was only weakly correlated with ASMR (Spearman ρ = 0.20, P = 0.004) and not significantly correlated with ASDR, and the burden peaked in low-middle SDI quintile countries. The BAPC model projected that the ASMR and ASDR of female BC-HFPG would continue to rise from 2024 to 2050.
CONCLUSION: The global burden of female BC-HFPG increased from 1990 to 2023 and is projected to continue rising through 2050, disproportionately affecting low- and low-middle SDI regions. These findings suggest that glycemic management and metabolic risk-factor control warrant consideration within comprehensive breast cancer prevention frameworks. However, because this is an ecological, population-level analysis, whether glucose lowering interventions can reduce breast cancer incidence remains to be established in prospective interventional studies. Our results may help prioritize regions and populations for future etiological and intervention research.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Female
*Breast Neoplasms/epidemiology/blood/mortality/etiology
Humans
*Blood Glucose/metabolism/analysis
Global Burden of Disease
*Fasting/blood
Databases, Factual
Bayes Theorem
Disability-Adjusted Life Years
Risk Factors
Retrospective Studies
Middle Aged
RevDate: 2026-10-22
CmpDate: 2026-10-22
Capacity, Collaboration, and Thematic Structure in Health AI Research Over the Past Decade in the Gulf Cooperation Council: Scientometric Analysis.
JMIR medical informatics, 14:e105709.
BACKGROUND: Health AI investment is accelerating across the Gulf Cooperation Council (GCC), yet the region's health AI research output has never been systematically quantified. National research capacity is a structural precondition for the safe local development and governance of clinical AI, but no scientometric baseline exists for the 6 GCC states.
OBJECTIVE: We characterized the volume, growth, collaboration structure, and thematic composition of GCC health AI research and examined whether national output aligns with an existing measure of informatics readiness.
METHODS: We conducted an ecological scientometric analysis of all health AI publications affiliated with the 6 GCC states (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) for 2011 to 2024 (the last complete indexing year at extraction) using the open bibliographic database OpenAlex. A publication was eligible if it included both an AI family and a health or medicine family concept above a 0.30 relevance threshold. Bibliometric indicators (output, compound annual growth, per capita intensity, citation impact, international and intraregional collaboration, and institutional concentration) were computed; coauthorship and concept co-occurrence networks were constructed and clustered by modularity. National health AI intensity was correlated (Spearman) with the Health Informatics Readiness Index (HIRI) and Global Digital Health Monitor (GDHM) phase.
RESULTS: Of 112,480 GCC-affiliated AI publications, 3512 met the health AI definition. Regional output rose from 18 (2011) to 904 (2024) publications per year (compound annual growth=35.2%), with 86.4% (3034/3512) published from 2020 onward and a sharp inflection from 2019 to 2021. Saudi Arabia contributed 59.6% (2094/3512) of the output by itself and 81.5% (2862/3512) together with the United Arab Emirates; Qatar led on a per capita basis (approximately 136 publications per million population). International collaboration (2551/3512, 72.6% of the papers) predominated over intra-GCC collaboration (164/3327, 4.9%), with the latter being inversely related to national output. The principal external partners were India, the United States, Pakistan, the United Kingdom, and Egypt. Output spanned 3186 institutions; concentration ranged from 89.4% (328/367) of a country's output among the top 3 institutions for Qatar to 34.4% (721/2094) for Saudi Arabia. Concept co-occurrence was classified into 4 themes-classic machine learning clinical prediction, medical imaging and oncology, COVID-19 response, and diabetic eye disease. Health AI intensity (ρ=+0.60) and, more strongly, absolute output (ρ=+0.89) correlated with the HIRI; absolute output was also correlated with GDHM phase (ρ=+0.83).
CONCLUSIONS: GCC health AI research has grown rapidly but unevenly, is heavily dependent on international collaboration, is concentrated in medical imaging, and-outside Saudi Arabia-remains anchored in single national institutions. Informatics readiness was associated with both the intensity and the volume of national research output. The findings establish a reproducible baseline for monitoring regional health AI research capacity as GCC health systems move toward clinical AI deployment.
Additional Links: PMID-42905880
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Citation:
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@article {pmid42905880,
year = {2026},
author = {Alqheedan, A and Alzughaibi, S},
title = {Capacity, Collaboration, and Thematic Structure in Health AI Research Over the Past Decade in the Gulf Cooperation Council: Scientometric Analysis.},
journal = {JMIR medical informatics},
volume = {14},
number = {},
pages = {e105709},
pmid = {42905880},
issn = {2291-9694},
mesh = {*Bibliometrics ; Humans ; *Cooperative Behavior ; *Artificial Intelligence/statistics & numerical data/trends ; Middle East ; *Biomedical Research/statistics & numerical data ; Saudi Arabia ; Qatar ; Oman ; International Cooperation ; *Research ; United Arab Emirates ; },
abstract = {BACKGROUND: Health AI investment is accelerating across the Gulf Cooperation Council (GCC), yet the region's health AI research output has never been systematically quantified. National research capacity is a structural precondition for the safe local development and governance of clinical AI, but no scientometric baseline exists for the 6 GCC states.
OBJECTIVE: We characterized the volume, growth, collaboration structure, and thematic composition of GCC health AI research and examined whether national output aligns with an existing measure of informatics readiness.
METHODS: We conducted an ecological scientometric analysis of all health AI publications affiliated with the 6 GCC states (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) for 2011 to 2024 (the last complete indexing year at extraction) using the open bibliographic database OpenAlex. A publication was eligible if it included both an AI family and a health or medicine family concept above a 0.30 relevance threshold. Bibliometric indicators (output, compound annual growth, per capita intensity, citation impact, international and intraregional collaboration, and institutional concentration) were computed; coauthorship and concept co-occurrence networks were constructed and clustered by modularity. National health AI intensity was correlated (Spearman) with the Health Informatics Readiness Index (HIRI) and Global Digital Health Monitor (GDHM) phase.
RESULTS: Of 112,480 GCC-affiliated AI publications, 3512 met the health AI definition. Regional output rose from 18 (2011) to 904 (2024) publications per year (compound annual growth=35.2%), with 86.4% (3034/3512) published from 2020 onward and a sharp inflection from 2019 to 2021. Saudi Arabia contributed 59.6% (2094/3512) of the output by itself and 81.5% (2862/3512) together with the United Arab Emirates; Qatar led on a per capita basis (approximately 136 publications per million population). International collaboration (2551/3512, 72.6% of the papers) predominated over intra-GCC collaboration (164/3327, 4.9%), with the latter being inversely related to national output. The principal external partners were India, the United States, Pakistan, the United Kingdom, and Egypt. Output spanned 3186 institutions; concentration ranged from 89.4% (328/367) of a country's output among the top 3 institutions for Qatar to 34.4% (721/2094) for Saudi Arabia. Concept co-occurrence was classified into 4 themes-classic machine learning clinical prediction, medical imaging and oncology, COVID-19 response, and diabetic eye disease. Health AI intensity (ρ=+0.60) and, more strongly, absolute output (ρ=+0.89) correlated with the HIRI; absolute output was also correlated with GDHM phase (ρ=+0.83).
CONCLUSIONS: GCC health AI research has grown rapidly but unevenly, is heavily dependent on international collaboration, is concentrated in medical imaging, and-outside Saudi Arabia-remains anchored in single national institutions. Informatics readiness was associated with both the intensity and the volume of national research output. The findings establish a reproducible baseline for monitoring regional health AI research capacity as GCC health systems move toward clinical AI deployment.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Bibliometrics
Humans
*Cooperative Behavior
*Artificial Intelligence/statistics & numerical data/trends
Middle East
*Biomedical Research/statistics & numerical data
Saudi Arabia
Qatar
Oman
International Cooperation
*Research
United Arab Emirates
RevDate: 2026-10-22
CmpDate: 2026-10-22
National trends in cardiovascular deaths with concurrent accidental drug poisoning coding in the United States: a 22-year analysis of the CDC WONDER database (1999-2020).
BMC cardiovascular disorders, 26(1):.
OBJECTIVE: While the overdose epidemic garners significant public health attention, cardiovascular deaths with concurrent accidental drug poisoning coding remain understudied in the United States.Traditional drug mortality surveillance primarily focuses on direct overdose fatalities, with limited integration of modern CDC-aligned multi-cause coding frameworks and atherosclerotic cardiovascular disease (ASCVD) cardiotoxicity mechanisms.We examined national trends in this phenomenon from 1999 to 2020.
METHODS: We analyzed CDC WONDER data, identifying deaths where cardiovascular disease (ICD-10: I00-I99) was the underlying cause and accidental drug poisoning (ICD-10: X40-X44) was documented as a contributory cause on death certificates. Age-adjusted mortality rates (AAMR) were calculated, and trends were assessed using Joinpoint regression analysis.This study is explicitly framed as an ecological population-level surveillance analysis of death certificate co-coding patterns, rather than an assessment of individual-level drug user cardiovascular mortality risk, given the inherent general-population denominator limitation of CDC WONDER aggregate data.
RESULTS: We identified 33,536 deaths nationwide meeting these criteria. The AAMR nearly doubled from 0.500 to 0.979 per 100,000 population (annual percent change: +3.64%, P < 0.001). Three distinct phases emerged: rapid increase (1999-2003, + 9.746%,P < 0.001), plateau (2003-2014, + 0.843%,P = 0.188), and second increase (2014-2020, + 4.887%,P < 0.001). Significant disparities existed: mortality was 2.48 times higher in men than women, and highest among non-Hispanic Black individuals (AAMR = 1.451, 2.25 times that of non-Hispanic Whites). The West region had the highest regional mortality (AAMR = 1.165), with Nevada recording the highest state-level rate (AAMR = 3.341). Middle-aged adults(45-64 years) accounted for 60.02% of all deaths.
CONCLUSION: Cardiovascular deaths with concurrent drug poisoning coding rose significantly from 1999 to 2020 in the United States, with the age-adjusted mortality rate (AAMR) increasing from 0.50 to 0.98 per 100,000 population. The trend followed three phases: a rapid rise from 1999 to 2003, a period of relative stabilization from 2003 to 2014, and another rapid increase from 2014 to 2020. Disparities were substantial and uneven: in 2020, mortality in men was approximately 2.5 times higher than in women; the highest AAMR was among non-Hispanic Black or African American individuals, and the West region carried a significantly higher risk than other regions; the 45-64 age group had the highest mortality rate, while the 25-44 age group showed a fluctuating pattern. These findings underscore the need for strengthened cardiovascular assessment and monitoring within substance-use-disorder interventions and for tailored public health strategies targeting high-risk populations and regions. At the same time, interpretations should consider limitations of death certificate coding, including potential differences in surveillance intensity and misclassification across demographic and geographic groups.All population-level trends reflect coded mortality patterns and cannot be extrapolated to individual drug-user risk, consistent with modern CDC multi-cause surveillance standards.
Additional Links: PMID-42907745
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Citation:
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@article {pmid42907745,
year = {2026},
author = {Fang, C and Peng, J and Zhu, S and Yang, Z and Yu, X and Yu, L},
title = {National trends in cardiovascular deaths with concurrent accidental drug poisoning coding in the United States: a 22-year analysis of the CDC WONDER database (1999-2020).},
journal = {BMC cardiovascular disorders},
volume = {26},
number = {1},
pages = {},
pmid = {42907745},
issn = {1471-2261},
mesh = {Humans ; United States/epidemiology ; Male ; *Cardiovascular Diseases/mortality/diagnosis/ethnology ; Female ; Cause of Death/trends ; Databases, Factual ; Risk Factors ; Time Factors ; Adult ; Middle Aged ; Aged ; *Drug Overdose/mortality/diagnosis ; Young Adult ; Centers for Disease Control and Prevention, U.S./trends ; Risk Assessment ; Adolescent ; Death Certificates ; International Classification of Diseases ; },
abstract = {OBJECTIVE: While the overdose epidemic garners significant public health attention, cardiovascular deaths with concurrent accidental drug poisoning coding remain understudied in the United States.Traditional drug mortality surveillance primarily focuses on direct overdose fatalities, with limited integration of modern CDC-aligned multi-cause coding frameworks and atherosclerotic cardiovascular disease (ASCVD) cardiotoxicity mechanisms.We examined national trends in this phenomenon from 1999 to 2020.
METHODS: We analyzed CDC WONDER data, identifying deaths where cardiovascular disease (ICD-10: I00-I99) was the underlying cause and accidental drug poisoning (ICD-10: X40-X44) was documented as a contributory cause on death certificates. Age-adjusted mortality rates (AAMR) were calculated, and trends were assessed using Joinpoint regression analysis.This study is explicitly framed as an ecological population-level surveillance analysis of death certificate co-coding patterns, rather than an assessment of individual-level drug user cardiovascular mortality risk, given the inherent general-population denominator limitation of CDC WONDER aggregate data.
RESULTS: We identified 33,536 deaths nationwide meeting these criteria. The AAMR nearly doubled from 0.500 to 0.979 per 100,000 population (annual percent change: +3.64%, P < 0.001). Three distinct phases emerged: rapid increase (1999-2003, + 9.746%,P < 0.001), plateau (2003-2014, + 0.843%,P = 0.188), and second increase (2014-2020, + 4.887%,P < 0.001). Significant disparities existed: mortality was 2.48 times higher in men than women, and highest among non-Hispanic Black individuals (AAMR = 1.451, 2.25 times that of non-Hispanic Whites). The West region had the highest regional mortality (AAMR = 1.165), with Nevada recording the highest state-level rate (AAMR = 3.341). Middle-aged adults(45-64 years) accounted for 60.02% of all deaths.
CONCLUSION: Cardiovascular deaths with concurrent drug poisoning coding rose significantly from 1999 to 2020 in the United States, with the age-adjusted mortality rate (AAMR) increasing from 0.50 to 0.98 per 100,000 population. The trend followed three phases: a rapid rise from 1999 to 2003, a period of relative stabilization from 2003 to 2014, and another rapid increase from 2014 to 2020. Disparities were substantial and uneven: in 2020, mortality in men was approximately 2.5 times higher than in women; the highest AAMR was among non-Hispanic Black or African American individuals, and the West region carried a significantly higher risk than other regions; the 45-64 age group had the highest mortality rate, while the 25-44 age group showed a fluctuating pattern. These findings underscore the need for strengthened cardiovascular assessment and monitoring within substance-use-disorder interventions and for tailored public health strategies targeting high-risk populations and regions. At the same time, interpretations should consider limitations of death certificate coding, including potential differences in surveillance intensity and misclassification across demographic and geographic groups.All population-level trends reflect coded mortality patterns and cannot be extrapolated to individual drug-user risk, consistent with modern CDC multi-cause surveillance standards.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
United States/epidemiology
Male
*Cardiovascular Diseases/mortality/diagnosis/ethnology
Female
Cause of Death/trends
Databases, Factual
Risk Factors
Time Factors
Adult
Middle Aged
Aged
*Drug Overdose/mortality/diagnosis
Young Adult
Centers for Disease Control and Prevention, U.S./trends
Risk Assessment
Adolescent
Death Certificates
International Classification of Diseases
RevDate: 2026-10-22
CmpDate: 2026-10-22
Evolution of androdioecy in Berchemia (Rhamnaceae) revealed by phylogenomics and ancestral character reconstruction.
Molecular phylogenetics and evolution, 220:108610.
Androdioecy is an extremely rare sexual system in angiosperms, and its evolutionary origins and potential mechanisms remain poorly understood. The presence of androdioecy in Berchemia provides a valuable model for studying the evolution of plant reproductive strategies. In this study, we reconstructed a high-resolution phylogeny of Berchemia based on whole-genome resequencing data from 114 Rhamnaceae samples, confirming that the core Berchemia forms a monophyletic group and resolving four well-supported clades (Berchemia I-IV). Divergence time analysis indicated that the genus originated in the early Eocene (∼55.55 Ma), with key diversification events coinciding with the Eocene-Oligocene transition (EOT). Ancestral state reconstruction suggested that hermaphroditism and same-year fruit ripening were ancestral traits, whereas androdioecy and second-year fruit ripening evolved once and twice within the genus, respectively. Notably, all species in Berchemia IV exhibit the combined traits of androdioecy and second-year fruit ripening. We infer that the emergence of androdioecy may represent an adaptation to reproductive resource trade-offs imposed by second-year fruit ripening, which itself potentially emerged in a climatic context of EOT cooling. The results of this study suggest that historical climatic events and reproductive resource trade-offs may be associated with shifts in sexual systems and reproductive phenology in Berchemia, offering new insights into the origins of androdioecy and its ecological correlates.
Additional Links: PMID-41887342
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PubMed:
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@article {pmid41887342,
year = {2026},
author = {Tian, X and Zhao, Q and Ma, H and Zhang, Q and Chen, Q and Liu, WZ},
title = {Evolution of androdioecy in Berchemia (Rhamnaceae) revealed by phylogenomics and ancestral character reconstruction.},
journal = {Molecular phylogenetics and evolution},
volume = {220},
number = {},
pages = {108610},
doi = {10.1016/j.ympev.2026.108610},
pmid = {41887342},
issn = {1095-9513},
mesh = {*Phylogeny ; *Rhamnaceae/genetics ; Genomics ; *Genome, Plant ; *Evolution, Molecular ; Sequence Analysis, DNA ; Whole Genome Sequencing ; Polymorphism, Single Nucleotide ; Datasets as Topic ; Fruit/genetics ; Reproduction ; },
abstract = {Androdioecy is an extremely rare sexual system in angiosperms, and its evolutionary origins and potential mechanisms remain poorly understood. The presence of androdioecy in Berchemia provides a valuable model for studying the evolution of plant reproductive strategies. In this study, we reconstructed a high-resolution phylogeny of Berchemia based on whole-genome resequencing data from 114 Rhamnaceae samples, confirming that the core Berchemia forms a monophyletic group and resolving four well-supported clades (Berchemia I-IV). Divergence time analysis indicated that the genus originated in the early Eocene (∼55.55 Ma), with key diversification events coinciding with the Eocene-Oligocene transition (EOT). Ancestral state reconstruction suggested that hermaphroditism and same-year fruit ripening were ancestral traits, whereas androdioecy and second-year fruit ripening evolved once and twice within the genus, respectively. Notably, all species in Berchemia IV exhibit the combined traits of androdioecy and second-year fruit ripening. We infer that the emergence of androdioecy may represent an adaptation to reproductive resource trade-offs imposed by second-year fruit ripening, which itself potentially emerged in a climatic context of EOT cooling. The results of this study suggest that historical climatic events and reproductive resource trade-offs may be associated with shifts in sexual systems and reproductive phenology in Berchemia, offering new insights into the origins of androdioecy and its ecological correlates.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Phylogeny
*Rhamnaceae/genetics
Genomics
*Genome, Plant
*Evolution, Molecular
Sequence Analysis, DNA
Whole Genome Sequencing
Polymorphism, Single Nucleotide
Datasets as Topic
Fruit/genetics
Reproduction
RevDate: 2026-10-19
CmpDate: 2026-10-19
Birds shape biogeochemistry and ecosystem function globally.
Current biology : CB, 36(20):R1158-R1183.
Birds inhabit nearly every environment on Earth, shaping ecosystems through diverse functions that include contributions to biogeochemical cycles. By transporting and recycling nutrients, birds influence the availability and distribution of chemical elements that regulate key ecological processes. Yet, as bird populations decline, their biogeochemical roles remain poorly synthesized, limiting our understanding of the broader consequences of biodiversity loss. Here, we systematically review the role of birds in biogeochemistry, with consequences for ecosystem function, structure, and connectivity globally. We highlight key mechanisms, ecological impacts, and future research and management priorities. We find that birds - by virtue of their broad distribution and abundance, flight-enabled mobility, nutrient-rich diets, and high metabolic demands - play distinct roles in nutrient transport. Although research has focused largely on waterbirds, growing evidence reveals birds' substantial chemical impacts on diverse environments, locally restructuring plant, microbial, and animal communities. Delivery of key limiting elements, such as nitrogen and phosphorus, can boost primary productivity and increase autotroph nutrient content, with bottom-up effects on higher trophic levels. However, bird subsidies can also promote soil acidification, contaminant accumulation, plant damage, and eutrophication. Because birds vary in their diet, size, life history, and behavior, declines in diversity can trigger uneven and cascading ecosystem effects. Human-driven changes in bird abundance, distribution, movement, and nutrition are modifying and diminishing avian-mediated biogeochemical processes across the biosphere, with potential consequences for ecosystem fertility, productivity, functional connectivity, and carbon storage. Nevertheless, opportunities remain to harness bird biogeochemistry in ecological restoration to revitalize Earth's natural nutrient networks.
Additional Links: PMID-42896531
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PubMed:
Citation:
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@article {pmid42896531,
year = {2026},
author = {Duvall, ES and Abraham, AJ and Bellvé, A and Doughty, CE and Rodewald, AD and Subalusky, AL and Flecker, AS},
title = {Birds shape biogeochemistry and ecosystem function globally.},
journal = {Current biology : CB},
volume = {36},
number = {20},
pages = {R1158-R1183},
doi = {10.1016/j.cub.2026.06.061},
pmid = {42896531},
issn = {1879-0445},
mesh = {Animals ; *Birds/physiology ; *Ecosystem ; *Biodiversity ; },
abstract = {Birds inhabit nearly every environment on Earth, shaping ecosystems through diverse functions that include contributions to biogeochemical cycles. By transporting and recycling nutrients, birds influence the availability and distribution of chemical elements that regulate key ecological processes. Yet, as bird populations decline, their biogeochemical roles remain poorly synthesized, limiting our understanding of the broader consequences of biodiversity loss. Here, we systematically review the role of birds in biogeochemistry, with consequences for ecosystem function, structure, and connectivity globally. We highlight key mechanisms, ecological impacts, and future research and management priorities. We find that birds - by virtue of their broad distribution and abundance, flight-enabled mobility, nutrient-rich diets, and high metabolic demands - play distinct roles in nutrient transport. Although research has focused largely on waterbirds, growing evidence reveals birds' substantial chemical impacts on diverse environments, locally restructuring plant, microbial, and animal communities. Delivery of key limiting elements, such as nitrogen and phosphorus, can boost primary productivity and increase autotroph nutrient content, with bottom-up effects on higher trophic levels. However, bird subsidies can also promote soil acidification, contaminant accumulation, plant damage, and eutrophication. Because birds vary in their diet, size, life history, and behavior, declines in diversity can trigger uneven and cascading ecosystem effects. Human-driven changes in bird abundance, distribution, movement, and nutrition are modifying and diminishing avian-mediated biogeochemical processes across the biosphere, with potential consequences for ecosystem fertility, productivity, functional connectivity, and carbon storage. Nevertheless, opportunities remain to harness bird biogeochemistry in ecological restoration to revitalize Earth's natural nutrient networks.},
}
MeSH Terms:
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Animals
*Birds/physiology
*Ecosystem
*Biodiversity
RevDate: 2026-10-19
CmpDate: 2026-10-19
Large animal restoration and carbon storage across climate-relevant timescales.
Current biology : CB, 36(20):R1184-R1201.
By virtue of their size and mobility, large animals can play important roles in Earth's carbon cycle. This has led to suggestions that restoring their populations can contribute to mitigating the climate crisis through removal and storage of atmospheric carbon. However, as animals can affect both release and sequestration of carbon, understanding when, where and how much they impact climate-relevant carbon is critical for evaluating their potential to become a trustworthy climate nature-based solution. Here, we review scientific evidence for the carbon impacts of elephants and great whales - two well-studied animal groups commonly cited for climate mitigation and suggested for carbon monetization. We identify six lessons to guide future research, policy and practice: first, large animal carbon impacts vary considerably by individual, species, ecosystem and biospheric conditions, making predictions of future impacts hard and wildlife-based carbon investments high-risk; second, meaningful carbon impacts will likely take longer to manifest than the Paris Agreement's mid-century net-zero target, but wildlife restoration should nonetheless begin now to realize immediate co-benefits and potentially support longer-term climate recovery; third, current conservation remains highest priority, as loss of animals may exacerbate climate breakdown; fourth, caution is needed when incorporating wildlife into climate policy to prevent false confidence in mitigation potential or perverse outcomes; fifth, potential wildlife carbon benefits should be communicated transparently and cautiously to manage expectations; sixth, robust monitoring and validation are essential to ensure carbon sequestration is real and durable. With these lessons in mind, conservation and restoration of large animals may realize their potential to aid long-term climate recovery as well as ecological resilience and adaptation under ongoing global change.
Additional Links: PMID-42896532
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PubMed:
Citation:
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@article {pmid42896532,
year = {2026},
author = {Abraham, AJ and Roman, J and Pearson, HC and le Roux, E and Kristensen, JA and Malhi, Y and Duvall, ES},
title = {Large animal restoration and carbon storage across climate-relevant timescales.},
journal = {Current biology : CB},
volume = {36},
number = {20},
pages = {R1184-R1201},
doi = {10.1016/j.cub.2026.09.016},
pmid = {42896532},
issn = {1879-0445},
mesh = {Animals ; *Climate Change ; *Elephants/physiology ; *Conservation of Natural Resources/methods ; Ecosystem ; *Whales/physiology ; *Carbon Cycle ; *Carbon Sequestration ; *Carbon/metabolism ; Climate ; },
abstract = {By virtue of their size and mobility, large animals can play important roles in Earth's carbon cycle. This has led to suggestions that restoring their populations can contribute to mitigating the climate crisis through removal and storage of atmospheric carbon. However, as animals can affect both release and sequestration of carbon, understanding when, where and how much they impact climate-relevant carbon is critical for evaluating their potential to become a trustworthy climate nature-based solution. Here, we review scientific evidence for the carbon impacts of elephants and great whales - two well-studied animal groups commonly cited for climate mitigation and suggested for carbon monetization. We identify six lessons to guide future research, policy and practice: first, large animal carbon impacts vary considerably by individual, species, ecosystem and biospheric conditions, making predictions of future impacts hard and wildlife-based carbon investments high-risk; second, meaningful carbon impacts will likely take longer to manifest than the Paris Agreement's mid-century net-zero target, but wildlife restoration should nonetheless begin now to realize immediate co-benefits and potentially support longer-term climate recovery; third, current conservation remains highest priority, as loss of animals may exacerbate climate breakdown; fourth, caution is needed when incorporating wildlife into climate policy to prevent false confidence in mitigation potential or perverse outcomes; fifth, potential wildlife carbon benefits should be communicated transparently and cautiously to manage expectations; sixth, robust monitoring and validation are essential to ensure carbon sequestration is real and durable. With these lessons in mind, conservation and restoration of large animals may realize their potential to aid long-term climate recovery as well as ecological resilience and adaptation under ongoing global change.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Climate Change
*Elephants/physiology
*Conservation of Natural Resources/methods
Ecosystem
*Whales/physiology
*Carbon Cycle
*Carbon Sequestration
*Carbon/metabolism
Climate
RevDate: 2026-10-22
CmpDate: 2026-10-20
A ubiquitin carboxyl-terminal hydrolase facilitates H2A.Z removal in response to phosphate starvation.
Nature communications, 17(1):.
The histone variant H2A.Z plays a critical role in the modulation of environmental responses, but the mechanisms regulating H2A.Z dynamics in response to stresses remain poorly understood in plants. Here we identify the ubiquitin carboxyl-terminal hydrolase UCH2 as a Pi-responsive chromatin regulator that promotes Pi starvation-induced (PSI) gene activation. We show that PHR1 recruits UCH2 to PSI gene promoters under Pi deficiency, where UCH2 deubiquitinates H2A.Z and promotes reduction in H2A.Z occupancy at PSI gene promoters. Loss of UCH2 impairs this reduction in H2A.Z occupancy, represses PSI gene induction, and reduces Pi accumulation. A catalytically inactive UCH2 mutant fails to complement these defects, and ubiquitination-deficient H2A.Z variants render plants insensitive to UCH2 loss. Our findings establish UCH2 as a critical chromatin regulator linking Pi sensing with H2A.Z dynamics and provide insights into how plants integrate chromatin-based regulation to maintain Pi homeostasis.
Additional Links: PMID-42897203
PubMed:
Citation:
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@article {pmid42897203,
year = {2026},
author = {Meng, F and Xiao, X and Ma, G and Satheesh, V and Wu, Q and Zhao, Y and Chen, H and Lu, X and Jiang, J and Lei, M},
title = {A ubiquitin carboxyl-terminal hydrolase facilitates H2A.Z removal in response to phosphate starvation.},
journal = {Nature communications},
volume = {17},
number = {1},
pages = {},
pmid = {42897203},
issn = {2041-1723},
support = {32570313//National Natural Science Foundation of China (National Science Foundation of China)/ ; U24A20385//National Natural Science Foundation of China (National Science Foundation of China)/ ; 2025JCXK01//Hangzhou Normal University (HNU)/ ; },
mesh = {*Histones/metabolism/genetics ; *Arabidopsis Proteins/metabolism/genetics ; *Phosphates/deficiency/metabolism ; *Arabidopsis/genetics/metabolism ; Gene Expression Regulation, Plant ; *Ubiquitin Thiolesterase/metabolism/genetics ; Promoter Regions, Genetic ; Ubiquitination ; Chromatin/metabolism ; Transcription Factors/metabolism/genetics ; },
abstract = {The histone variant H2A.Z plays a critical role in the modulation of environmental responses, but the mechanisms regulating H2A.Z dynamics in response to stresses remain poorly understood in plants. Here we identify the ubiquitin carboxyl-terminal hydrolase UCH2 as a Pi-responsive chromatin regulator that promotes Pi starvation-induced (PSI) gene activation. We show that PHR1 recruits UCH2 to PSI gene promoters under Pi deficiency, where UCH2 deubiquitinates H2A.Z and promotes reduction in H2A.Z occupancy at PSI gene promoters. Loss of UCH2 impairs this reduction in H2A.Z occupancy, represses PSI gene induction, and reduces Pi accumulation. A catalytically inactive UCH2 mutant fails to complement these defects, and ubiquitination-deficient H2A.Z variants render plants insensitive to UCH2 loss. Our findings establish UCH2 as a critical chromatin regulator linking Pi sensing with H2A.Z dynamics and provide insights into how plants integrate chromatin-based regulation to maintain Pi homeostasis.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Histones/metabolism/genetics
*Arabidopsis Proteins/metabolism/genetics
*Phosphates/deficiency/metabolism
*Arabidopsis/genetics/metabolism
Gene Expression Regulation, Plant
*Ubiquitin Thiolesterase/metabolism/genetics
Promoter Regions, Genetic
Ubiquitination
Chromatin/metabolism
Transcription Factors/metabolism/genetics
RevDate: 2026-10-22
CmpDate: 2026-10-20
Persistent shortfalls in government health expenditure: a decade-long analysis of Abuja 15% target attainment across 52 African countries, 2014-2023.
Tropical medicine and health, 54(1):.
BACKGROUND: In 2001, African governments committed through the Abuja Declaration to allocating at least 15% of annual government budgets to health. More than 2 decades later, the extent to which this commitment has been achieved consistently, rather than in isolated years, remains unclear. We assessed recent trends, persistence of attainment, country trajectories and convergence in government prioritisation of health among the original Abuja Declaration endorsers.
METHODS: We conducted a longitudinal country-level (ecological) panel analysis of 52 original Abuja Declaration endorsers with complete comparable data from 2014 to 2023, supplemented by an analysis of all available data for 2001-2023. Annual data on domestic general government health expenditure as a percentage of general government expenditure were obtained from the World Bank World Development Indicators, drawing on the World Health Organisation Global Health Expenditure Database. Attainment was defined as an expenditure share of at least 15%. We summarised annual and subregional distributions, persistence of attainment and country-specific linear trends. Overall temporal change was examined using country fixed-effects regression with standard errors clustered by country. Exploratory beta- and sigma-convergence analyses, including specifications robust to regression to the mean, assessed whether lower-spending countries improved faster and whether between-country dispersion narrowed. Sensitivity analyses addressed classification thresholds and trend heterogeneity.
RESULTS: The unweighted mean government health-expenditure share increased from 6.73% in 2014 to 7.09% in 2023, while the median increased from 5.91 to 6.05%. Only South Africa met the 15% benchmark in 2023. Across the 10-year period, 48 countries (92.3%) never attained the benchmark, 3 (5.8%) attained it occasionally, and only South Africa demonstrated sustained attainment. Southern Africa had the highest mean share in 2023 at 13.79%, whereas Western Africa had the lowest at 5.87%. The average within-country linear trend was small and statistically uncertain at 0.053 percentage points per year (95%CI -0.052 to 0.157; p = 0.316). Country-specific trends varied substantially (standard deviation of slopes 0.32 percentage points per year; p < 0.001). Apparent catch-up by lower-baseline countries (β = -0.382; 95%CI -0.667 to -0.097) was not robust to regression to the mean, and dispersion did not consistently narrow. Over 2001-2023, 47 countries never attained the benchmark and the average within-country trend was 0.012 percentage points per year (95%CI -0.032 to 0.057).
CONCLUSIONS: Government prioritisation of health among original Abuja Declaration endorsers remained substantially below the 15% benchmark during 2014-2023. More than nine in ten countries never attained the target, and only one demonstrated sustained attainment. This stagnation is long-standing, and since 2001, the continental distribution has barely moved. The Abuja benchmark should be accompanied by stronger accountability mechanisms and complementary measures of absolute spending adequacy, fiscal capacity and financial protection.
Additional Links: PMID-42897695
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Citation:
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@article {pmid42897695,
year = {2026},
author = {Adebisi, MA and Ogunkola, IO and Lucero-Prisno, DE and Alhur, AA and Adeola, QA and Fajembola, A and Odey, GO and Jimoh, ND and Olarewaju, AA and Alade, L and Gideon, JA and Adebisi, YA},
title = {Persistent shortfalls in government health expenditure: a decade-long analysis of Abuja 15% target attainment across 52 African countries, 2014-2023.},
journal = {Tropical medicine and health},
volume = {54},
number = {1},
pages = {},
pmid = {42897695},
issn = {1348-8945},
abstract = {BACKGROUND: In 2001, African governments committed through the Abuja Declaration to allocating at least 15% of annual government budgets to health. More than 2 decades later, the extent to which this commitment has been achieved consistently, rather than in isolated years, remains unclear. We assessed recent trends, persistence of attainment, country trajectories and convergence in government prioritisation of health among the original Abuja Declaration endorsers.
METHODS: We conducted a longitudinal country-level (ecological) panel analysis of 52 original Abuja Declaration endorsers with complete comparable data from 2014 to 2023, supplemented by an analysis of all available data for 2001-2023. Annual data on domestic general government health expenditure as a percentage of general government expenditure were obtained from the World Bank World Development Indicators, drawing on the World Health Organisation Global Health Expenditure Database. Attainment was defined as an expenditure share of at least 15%. We summarised annual and subregional distributions, persistence of attainment and country-specific linear trends. Overall temporal change was examined using country fixed-effects regression with standard errors clustered by country. Exploratory beta- and sigma-convergence analyses, including specifications robust to regression to the mean, assessed whether lower-spending countries improved faster and whether between-country dispersion narrowed. Sensitivity analyses addressed classification thresholds and trend heterogeneity.
RESULTS: The unweighted mean government health-expenditure share increased from 6.73% in 2014 to 7.09% in 2023, while the median increased from 5.91 to 6.05%. Only South Africa met the 15% benchmark in 2023. Across the 10-year period, 48 countries (92.3%) never attained the benchmark, 3 (5.8%) attained it occasionally, and only South Africa demonstrated sustained attainment. Southern Africa had the highest mean share in 2023 at 13.79%, whereas Western Africa had the lowest at 5.87%. The average within-country linear trend was small and statistically uncertain at 0.053 percentage points per year (95%CI -0.052 to 0.157; p = 0.316). Country-specific trends varied substantially (standard deviation of slopes 0.32 percentage points per year; p < 0.001). Apparent catch-up by lower-baseline countries (β = -0.382; 95%CI -0.667 to -0.097) was not robust to regression to the mean, and dispersion did not consistently narrow. Over 2001-2023, 47 countries never attained the benchmark and the average within-country trend was 0.012 percentage points per year (95%CI -0.032 to 0.057).
CONCLUSIONS: Government prioritisation of health among original Abuja Declaration endorsers remained substantially below the 15% benchmark during 2014-2023. More than nine in ten countries never attained the target, and only one demonstrated sustained attainment. This stagnation is long-standing, and since 2001, the continental distribution has barely moved. The Abuja benchmark should be accompanied by stronger accountability mechanisms and complementary measures of absolute spending adequacy, fiscal capacity and financial protection.},
}
RevDate: 2026-10-20
CmpDate: 2026-10-20
Enrofloxacin Disrupts Microbiota-Gut-Brain Axes in Marine Medaka: Mechanistic Insights from Multiomics and Germ-Free Models.
Environmental science & technology, 60(41):29299-29312.
The widespread use of antibiotics has resulted in their frequent occurrence in marine environments, yet their ecological risks remain poorly understood. Enrofloxacin (ENR) is one of the most frequently detected antibiotics in aquatic ecosystems. However, its toxicological mechanisms in marine fish remain unclear. Here, multiomics, Vibrio parahemolyticus infection, short chain fatty acid supplementation and germ-free fish models were integrated to investigate ENR induced neurotoxicity and the role of gut microbiota. The results showed that ENR exposure impaired intestinal function in marine medaka (Oryzias melastigma), accompanied by behavioral abnormalities, neurotoxicity, and liver injury. ENR also induced gut microbiome dysbiosis and altered SCFAs levels. Furthermore, SCFAs supplementation and germ-free fish experiments provided complementary and supportive evidence that gut microbial dysbiosis and altered SCFAs levels may be involved in ENR neurotoxic responses. Moreover, ENR pretreated fish showed increased susceptibility to V. parahemolyticus challenge, which further disrupted the gut microbiome and aggravated neurological dysfunction. Collectively, these findings suggest that ENR induced neurotoxicity is linked to disruption of the microbiome-gut-brain axis and increased susceptibility to subsequent pathogenic stress. This study provides new insights into antibiotic toxicity in marine fish and supports ecological risk assessment of ENR in marine aquaculture.
Additional Links: PMID-42899660
Publisher:
PubMed:
Citation:
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@article {pmid42899660,
year = {2026},
author = {Zeng, BH and Li, P and Liu, B and Li, T and Yin, H and Sun, L and Liu, L and Li, ZH},
title = {Enrofloxacin Disrupts Microbiota-Gut-Brain Axes in Marine Medaka: Mechanistic Insights from Multiomics and Germ-Free Models.},
journal = {Environmental science & technology},
volume = {60},
number = {41},
pages = {29299-29312},
doi = {10.1021/acs.est.6c06063},
pmid = {42899660},
issn = {1520-5851},
support = {42677347,42277269//National Natural Science Foundation of China (NSFC)/ ; },
mesh = {Animals ; *Oryzias/microbiology ; *Enrofloxacin ; Multiomics ; *Gastrointestinal Microbiome/drug effects ; *Brain/drug effects ; Anti-Bacterial Agents ; },
abstract = {The widespread use of antibiotics has resulted in their frequent occurrence in marine environments, yet their ecological risks remain poorly understood. Enrofloxacin (ENR) is one of the most frequently detected antibiotics in aquatic ecosystems. However, its toxicological mechanisms in marine fish remain unclear. Here, multiomics, Vibrio parahemolyticus infection, short chain fatty acid supplementation and germ-free fish models were integrated to investigate ENR induced neurotoxicity and the role of gut microbiota. The results showed that ENR exposure impaired intestinal function in marine medaka (Oryzias melastigma), accompanied by behavioral abnormalities, neurotoxicity, and liver injury. ENR also induced gut microbiome dysbiosis and altered SCFAs levels. Furthermore, SCFAs supplementation and germ-free fish experiments provided complementary and supportive evidence that gut microbial dysbiosis and altered SCFAs levels may be involved in ENR neurotoxic responses. Moreover, ENR pretreated fish showed increased susceptibility to V. parahemolyticus challenge, which further disrupted the gut microbiome and aggravated neurological dysfunction. Collectively, these findings suggest that ENR induced neurotoxicity is linked to disruption of the microbiome-gut-brain axis and increased susceptibility to subsequent pathogenic stress. This study provides new insights into antibiotic toxicity in marine fish and supports ecological risk assessment of ENR in marine aquaculture.},
}
MeSH Terms:
show MeSH Terms
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Animals
*Oryzias/microbiology
*Enrofloxacin
Multiomics
*Gastrointestinal Microbiome/drug effects
*Brain/drug effects
Anti-Bacterial Agents
RevDate: 2026-10-20
CmpDate: 2026-10-20
Predicting cholesterol screening behavior using machine learning: Social-ecological approach.
Health informatics journal, 32(4):14604582261500291.
IntroductionCurrent preventive screening reminders use generic due-date notifications that lack personalization. Targeted reminders allow personalized messages and resource allocation, yet the accuracy of behavioral forecasting with cholesterol screening behaviors remains unconfirmed. Therefore, this study aims to examine the accuracy of machine learning in predicting adults' future cholesterol screening behavior.MethodsThis study included 8,288 participants from the Health and Retirement Study. Never receiving cholesterol screening over 12 years of follow-up (2007-2018) was identified as the target outcome. Predictors were constructed based on the Social-Ecological Model. Four machine learning (ML) algorithms were compared: logistic regression, random forests, gradient boosting machine (GBM), and eXtreme Gradient Boosting (XGBoost). Model performance was evaluated by Recall, Precision, and false-negative rate (FNR).ResultsAmong the four ML algorithms, XGBoost performed best, with higher Recall (average: 0.8850) and the lowest FNR (0.1311), but suboptimal precision (average: 0.6228). The top five predictors were past cholesterol screening behavior, diagnosis of hypertension, osteoarthritis or rheumatoid arthritis, number of private insurance plans, and gender.ConclusionML might be used to predict individuals' cholesterol screening behavior. Future research is needed to examine whether leveraging ML in targeted reminders might enhance cholesterol screening behaviors.
Additional Links: PMID-42900958
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PubMed:
Citation:
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@article {pmid42900958,
year = {2026},
author = {Kuo, WC and Chen, J and McDonald, AD and Li, T and Chang, JH and Johnson, HM},
title = {Predicting cholesterol screening behavior using machine learning: Social-ecological approach.},
journal = {Health informatics journal},
volume = {32},
number = {4},
pages = {14604582261500291},
doi = {10.1177/14604582261500291},
pmid = {42900958},
issn = {1741-2811},
mesh = {Humans ; *Machine Learning/standards/trends/statistics & numerical data ; *Mass Screening/methods/statistics & numerical data/standards ; Female ; Boosting Machine Learning Algorithms ; *Cholesterol/blood/analysis ; Middle Aged ; Prediction Algorithms ; Aged ; Predictive Learning Models ; Random Forest ; Classification Algorithms ; Logistic Models ; },
abstract = {IntroductionCurrent preventive screening reminders use generic due-date notifications that lack personalization. Targeted reminders allow personalized messages and resource allocation, yet the accuracy of behavioral forecasting with cholesterol screening behaviors remains unconfirmed. Therefore, this study aims to examine the accuracy of machine learning in predicting adults' future cholesterol screening behavior.MethodsThis study included 8,288 participants from the Health and Retirement Study. Never receiving cholesterol screening over 12 years of follow-up (2007-2018) was identified as the target outcome. Predictors were constructed based on the Social-Ecological Model. Four machine learning (ML) algorithms were compared: logistic regression, random forests, gradient boosting machine (GBM), and eXtreme Gradient Boosting (XGBoost). Model performance was evaluated by Recall, Precision, and false-negative rate (FNR).ResultsAmong the four ML algorithms, XGBoost performed best, with higher Recall (average: 0.8850) and the lowest FNR (0.1311), but suboptimal precision (average: 0.6228). The top five predictors were past cholesterol screening behavior, diagnosis of hypertension, osteoarthritis or rheumatoid arthritis, number of private insurance plans, and gender.ConclusionML might be used to predict individuals' cholesterol screening behavior. Future research is needed to examine whether leveraging ML in targeted reminders might enhance cholesterol screening behaviors.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Machine Learning/standards/trends/statistics & numerical data
*Mass Screening/methods/statistics & numerical data/standards
Female
Boosting Machine Learning Algorithms
*Cholesterol/blood/analysis
Middle Aged
Prediction Algorithms
Aged
Predictive Learning Models
Random Forest
Classification Algorithms
Logistic Models
RevDate: 2026-10-21
CmpDate: 2026-10-21
The tip of the iceberg: Profiling cooling agents using computational approaches to inform tobacco regulatory science.
PloS one, 21(4):e0346126.
Cooling agents (chemicals added to impart a cooling sensation) in tobacco products are receiving increased attention due to their use as menthol substitutes. However, detailed information on their chemical structures, physico-chemical properties, cooling activity, and human and ecotoxicity potential has not been compiled. Our goal was to profile cooling agents that could be used as menthol substitutes in tobacco products, along with descriptions of their cooling properties and estimated toxicological effects. First, we compiled a library of 228 cooling agents, including 180 unique two-dimensional (2-D) chemical structures based on a review of multiple public data sources (literature, invention patents, and public databases). The library includes chemicals with a "cool" and/or "mint" flavor profile as designated by the Flavor and Extract Manufacturers Association (FEMA), chemicals reported to activate the cation channel transient receptor potential melastatin 8 (TRPM8) receptor, and/or chemicals with reported subjective perceived sensory cooling. Second, we classified the cooling agents into three main chemical skeletons using similar structural motifs and estimated their physico-chemical properties related to cooling attributes using Schrödinger Canvas software, including log octanol-water partition coefficient (LogKow), vapor pressure, and electrotopological state index. Third, to investigate the cooling agents' similarity to each other and to menthol, we applied an unsupervised machine learning algorithm (Knowledge Discovery by Accuracy Maximization [KODAMA]) and hierarchical clustering techniques and identified six clusters. Fourth, we compiled available perceived cooling intensity data. Fifth, we used models based on experimental and predicted data (EPA's web-based Hazard Comparison Module [HCM]) to estimate human health toxicity and ecotoxicity. Some cooling agents are associated with genotoxicity, developmental toxicity, skin irritation, and eye irritation, and pose toxicity to fish, algae, and invertebrates. Using this surveillance approach will help inform future tobacco regulatory decisions and policies by profiling chemicals used as cooling agents in tobacco products and those that pose potential health hazard concerns.
Additional Links: PMID-41990046
PubMed:
Citation:
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@article {pmid41990046,
year = {2026},
author = {Chakraborty, S and Venugopal, PD and Kaltcheva, M and Kang, JC and Goel, R},
title = {The tip of the iceberg: Profiling cooling agents using computational approaches to inform tobacco regulatory science.},
journal = {PloS one},
volume = {21},
number = {4},
pages = {e0346126},
pmid = {41990046},
issn = {1932-6203},
mesh = {*Menthol/analogs & derivatives/analysis/chemistry/toxicity ; *Tobacco Products/analysis/standards ; *Flavoring Agents/analysis/chemistry/toxicity ; Cheminformatics/methods ; TRPM Cation Channels/metabolism ; Software ; Ecotoxicology/methods ; Humans ; United States Food and Drug Administration/standards ; United States ; Unsupervised Machine Learning ; },
abstract = {Cooling agents (chemicals added to impart a cooling sensation) in tobacco products are receiving increased attention due to their use as menthol substitutes. However, detailed information on their chemical structures, physico-chemical properties, cooling activity, and human and ecotoxicity potential has not been compiled. Our goal was to profile cooling agents that could be used as menthol substitutes in tobacco products, along with descriptions of their cooling properties and estimated toxicological effects. First, we compiled a library of 228 cooling agents, including 180 unique two-dimensional (2-D) chemical structures based on a review of multiple public data sources (literature, invention patents, and public databases). The library includes chemicals with a "cool" and/or "mint" flavor profile as designated by the Flavor and Extract Manufacturers Association (FEMA), chemicals reported to activate the cation channel transient receptor potential melastatin 8 (TRPM8) receptor, and/or chemicals with reported subjective perceived sensory cooling. Second, we classified the cooling agents into three main chemical skeletons using similar structural motifs and estimated their physico-chemical properties related to cooling attributes using Schrödinger Canvas software, including log octanol-water partition coefficient (LogKow), vapor pressure, and electrotopological state index. Third, to investigate the cooling agents' similarity to each other and to menthol, we applied an unsupervised machine learning algorithm (Knowledge Discovery by Accuracy Maximization [KODAMA]) and hierarchical clustering techniques and identified six clusters. Fourth, we compiled available perceived cooling intensity data. Fifth, we used models based on experimental and predicted data (EPA's web-based Hazard Comparison Module [HCM]) to estimate human health toxicity and ecotoxicity. Some cooling agents are associated with genotoxicity, developmental toxicity, skin irritation, and eye irritation, and pose toxicity to fish, algae, and invertebrates. Using this surveillance approach will help inform future tobacco regulatory decisions and policies by profiling chemicals used as cooling agents in tobacco products and those that pose potential health hazard concerns.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Menthol/analogs & derivatives/analysis/chemistry/toxicity
*Tobacco Products/analysis/standards
*Flavoring Agents/analysis/chemistry/toxicity
Cheminformatics/methods
TRPM Cation Channels/metabolism
Software
Ecotoxicology/methods
Humans
United States Food and Drug Administration/standards
United States
Unsupervised Machine Learning
RevDate: 2026-10-20
CmpDate: 2026-10-20
Multi-omics insights into the woolly trait of Saussurea medusa and the plant's coordinated regulation of flavonoid biosynthesis.
Communications biology, 9(1):.
The woolly plant Saussurea medusa is an endangered traditional Tibetan medicinal species and an ideal model to study high-altitude adaptation. Despite its ecological and pharmacological significance, the molecular mechanisms underlying its survival under harsh environments and its production of bioactive flavonoids remain poorly characterized. In this study, we assembled a high-quality chromosome-level genome of S. medusa (~3.8 Gb) with low heterozygosity and high repeat content. Comparative genomic analyses showed expansion of gene families related to DNA repair and hypoxia-adapted TCA cycle metabolism, and strong positive selection on light-harvesting complex pathways. Structural and functional analyses of the woolly trait demonstrated its roles in thermal insulation and light attenuation. Correspondingly, 48 key trichome-related genes were identified, reflecting a regulatory network dominated by the conserved GL1-GL3/(EGL3)-TTG1 transcriptional activator complex and linked to hormonal pathways. Metabolomics identified 1792 metabolites, including 18 bioactive metabolites with tissue-specific accumulation, most of which are flavonoids. Integrated metabolomics and transcriptomics analysis further revealed 27 flavonoid biosynthetic genes highly expressed in flowers and leaves, correlating strongly with the accumulation of flavonoids, indicating coordinated regulation of secondary metabolism. Our study provides multi-omic resources for S. medusa and provides insights into the genetic basis of its high-altitude adaptation, woolly trait, and medicinal properties.
Additional Links: PMID-42380481
PubMed:
Citation:
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@article {pmid42380481,
year = {2026},
author = {Hu, G and Wang, M and Yangjin, L and Du, M and He, T and Jia, X and Duan, R},
title = {Multi-omics insights into the woolly trait of Saussurea medusa and the plant's coordinated regulation of flavonoid biosynthesis.},
journal = {Communications biology},
volume = {9},
number = {1},
pages = {},
pmid = {42380481},
issn = {2399-3642},
support = {31960222//National Natural Science Foundation of China (National Science Foundation of China)/ ; },
mesh = {*Flavonoids/biosynthesis ; *Saussurea/genetics/metabolism ; Gene Expression Regulation, Plant ; Multiomics ; Transcriptome ; Metabolomics ; Gene Expression Profiling ; },
abstract = {The woolly plant Saussurea medusa is an endangered traditional Tibetan medicinal species and an ideal model to study high-altitude adaptation. Despite its ecological and pharmacological significance, the molecular mechanisms underlying its survival under harsh environments and its production of bioactive flavonoids remain poorly characterized. In this study, we assembled a high-quality chromosome-level genome of S. medusa (~3.8 Gb) with low heterozygosity and high repeat content. Comparative genomic analyses showed expansion of gene families related to DNA repair and hypoxia-adapted TCA cycle metabolism, and strong positive selection on light-harvesting complex pathways. Structural and functional analyses of the woolly trait demonstrated its roles in thermal insulation and light attenuation. Correspondingly, 48 key trichome-related genes were identified, reflecting a regulatory network dominated by the conserved GL1-GL3/(EGL3)-TTG1 transcriptional activator complex and linked to hormonal pathways. Metabolomics identified 1792 metabolites, including 18 bioactive metabolites with tissue-specific accumulation, most of which are flavonoids. Integrated metabolomics and transcriptomics analysis further revealed 27 flavonoid biosynthetic genes highly expressed in flowers and leaves, correlating strongly with the accumulation of flavonoids, indicating coordinated regulation of secondary metabolism. Our study provides multi-omic resources for S. medusa and provides insights into the genetic basis of its high-altitude adaptation, woolly trait, and medicinal properties.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Flavonoids/biosynthesis
*Saussurea/genetics/metabolism
Gene Expression Regulation, Plant
Multiomics
Transcriptome
Metabolomics
Gene Expression Profiling
RevDate: 2026-10-19
CmpDate: 2026-10-18
Characterizing multi-criteria decision analysis, risk stratification, and hotspot analysis methods to optimise health policymaking and evidence translation for medicines in low- and middle-income countries: A scoping review.
Gates open research, 10:68.
BACKGROUND: Implementing new medicines or health interventions in lower-income and middle-income countries (LMICs) may be complex and challenging, and there is a need for practical structured approaches and tools to support the translation of evidence into practice, including the implementation of evidence-informed interventions and health policy making.
OBJECTIVE: This scoping review aimed to characterise three data analytical methodologies - multi-criteria decision analysis (MCDA), risk stratification, and hotspot analysis - to evaluate their use in guiding the implementation of medicines for human health in LMICs between 2010-2025.
METHODS: Scientific articles were searched in databases PubMed and Scopus following guidelines from the Preferred Items for Systematic Reviews and Meta-Analysis (PRISMA). Data were extracted in relation to the study aims, geographic scope and scale, author affiliations, disease focus, medicine type (categorised as oral drugs or vaccines), target population, medicine implementation phase, use of templates or tools, and main steps of the methodological process. In addition, grey literature was searched by reviewing conference abstracts, national public health websites and journals.
RESULTS: From the 4,920 articles screened, a total of 40 articles (MCDA=8, risk stratification= 22, hotspot analysis=10) were included from 28 countries across five global regions, mostly Africa. Most articles focused on communicable infectious diseases, and drugs (oral regimens) and vaccines in the pre-implementation stage at a sub-national level. The processes and techniques used for each analytical method varied widely, limiting comparability. However, common methodological steps were identified and used to construct preliminary templates to summarise the processes involved in applying each methodology and support their potential adaptations for decision-making around medicine implementation.
CONCLUSION: These analytical methodologies provide a structured basis for further developing practical templates and decision-support tools to enhance the medicine translation; however, efforts are needed to raise awareness, strengthen capacity, and facilitate greater uptake.
Additional Links: PMID-42892762
PubMed:
Citation:
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@article {pmid42892762,
year = {2026},
author = {Norris, LE and Cornell, TR and Okorie, PN and Hudson, LM and Kelly-Hope, LA},
title = {Characterizing multi-criteria decision analysis, risk stratification, and hotspot analysis methods to optimise health policymaking and evidence translation for medicines in low- and middle-income countries: A scoping review.},
journal = {Gates open research},
volume = {10},
number = {},
pages = {68},
pmid = {42892762},
issn = {2572-4754},
mesh = {Humans ; *Decision Support Techniques ; *Developing Countries ; *Health Policy ; *Policy Making ; Risk Assessment ; *Translational Research, Biomedical ; },
abstract = {BACKGROUND: Implementing new medicines or health interventions in lower-income and middle-income countries (LMICs) may be complex and challenging, and there is a need for practical structured approaches and tools to support the translation of evidence into practice, including the implementation of evidence-informed interventions and health policy making.
OBJECTIVE: This scoping review aimed to characterise three data analytical methodologies - multi-criteria decision analysis (MCDA), risk stratification, and hotspot analysis - to evaluate their use in guiding the implementation of medicines for human health in LMICs between 2010-2025.
METHODS: Scientific articles were searched in databases PubMed and Scopus following guidelines from the Preferred Items for Systematic Reviews and Meta-Analysis (PRISMA). Data were extracted in relation to the study aims, geographic scope and scale, author affiliations, disease focus, medicine type (categorised as oral drugs or vaccines), target population, medicine implementation phase, use of templates or tools, and main steps of the methodological process. In addition, grey literature was searched by reviewing conference abstracts, national public health websites and journals.
RESULTS: From the 4,920 articles screened, a total of 40 articles (MCDA=8, risk stratification= 22, hotspot analysis=10) were included from 28 countries across five global regions, mostly Africa. Most articles focused on communicable infectious diseases, and drugs (oral regimens) and vaccines in the pre-implementation stage at a sub-national level. The processes and techniques used for each analytical method varied widely, limiting comparability. However, common methodological steps were identified and used to construct preliminary templates to summarise the processes involved in applying each methodology and support their potential adaptations for decision-making around medicine implementation.
CONCLUSION: These analytical methodologies provide a structured basis for further developing practical templates and decision-support tools to enhance the medicine translation; however, efforts are needed to raise awareness, strengthen capacity, and facilitate greater uptake.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Decision Support Techniques
*Developing Countries
*Health Policy
*Policy Making
Risk Assessment
*Translational Research, Biomedical
RevDate: 2026-10-19
CmpDate: 2026-10-18
Designing an AI-Responsive Early Childhood Curriculum: A Conceptual Framework for Supporting Developmental Learning Trajectories in Preschool Education.
F1000Research, 15:1172.
BACKGROUND: The rapid integration of artificial intelligence (AI) and deep learning technologies into education creates new opportunities for personalized learning in early childhood education (ECE). Yet limited research has examined how educators interpret and enact AI-responsive curriculum decisions in preschool settings, particularly in culturally diverse contexts.
PURPOSE: This study explores educators' experiences in designing and implementing AI-responsive curricula and develops a conceptual framework explaining how AI can inform curriculum decision-making for young children without displacing teacher judgment.
METHOD: An interpretive phenomenological study was conducted at TK Harapan Bangsa, Makassar, Indonesia, with nine adult participants: six preschool teachers, two curriculum specialists, and one AI tool developer-collaborator whose expert interview supplied technical context. Data comprised two in-depth interviews with each teacher, interviews with curriculum specialists and the developer-collaborator, 18 non-participant observations, and analysis of AI-supported planning documents. MAXQDA 2024 supported data management. Giorgi's phenomenological method was operationalized through first-order meaning units, second-order interpretive themes, and third-order composite constructs. Triangulation, reflexive memoing, an audit trail, member checking, and peer debriefing supported trustworthiness.
FINDINGS: Three interconnected constructs emerged. Predictive Developmental Tracking describes AI-supported identification of developmental readiness and possible concerns. AI-Responsive Curriculum Adaptation captures teachers' active interrogation and contextual modification of algorithmic recommendations. Deep Learning as Pedagogical Scaffold positions AI as a support that amplifies, rather than replaces, professional expertise. Together, the constructs informed the AI-Responsive Curriculum Design (ARCD) Framework.
CONCLUSION: The ARCD Framework explains AI-responsive curriculum implementation as a relational process combining predictive insight, ecological sensitivity, and educator agency. It offers implications for curriculum policy, teacher professional development, and ethical AI integration in ECE.
Additional Links: PMID-42892814
PubMed:
Citation:
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@article {pmid42892814,
year = {2026},
author = {Herlina, H and Apriyansyah, C and Rusmayadi, R and Herman, H},
title = {Designing an AI-Responsive Early Childhood Curriculum: A Conceptual Framework for Supporting Developmental Learning Trajectories in Preschool Education.},
journal = {F1000Research},
volume = {15},
number = {},
pages = {1172},
pmid = {42892814},
issn = {2046-1402},
mesh = {*Curriculum ; Humans ; *Artificial Intelligence ; Child, Preschool ; *Learning ; Deep Learning ; *Child Development ; },
abstract = {BACKGROUND: The rapid integration of artificial intelligence (AI) and deep learning technologies into education creates new opportunities for personalized learning in early childhood education (ECE). Yet limited research has examined how educators interpret and enact AI-responsive curriculum decisions in preschool settings, particularly in culturally diverse contexts.
PURPOSE: This study explores educators' experiences in designing and implementing AI-responsive curricula and develops a conceptual framework explaining how AI can inform curriculum decision-making for young children without displacing teacher judgment.
METHOD: An interpretive phenomenological study was conducted at TK Harapan Bangsa, Makassar, Indonesia, with nine adult participants: six preschool teachers, two curriculum specialists, and one AI tool developer-collaborator whose expert interview supplied technical context. Data comprised two in-depth interviews with each teacher, interviews with curriculum specialists and the developer-collaborator, 18 non-participant observations, and analysis of AI-supported planning documents. MAXQDA 2024 supported data management. Giorgi's phenomenological method was operationalized through first-order meaning units, second-order interpretive themes, and third-order composite constructs. Triangulation, reflexive memoing, an audit trail, member checking, and peer debriefing supported trustworthiness.
FINDINGS: Three interconnected constructs emerged. Predictive Developmental Tracking describes AI-supported identification of developmental readiness and possible concerns. AI-Responsive Curriculum Adaptation captures teachers' active interrogation and contextual modification of algorithmic recommendations. Deep Learning as Pedagogical Scaffold positions AI as a support that amplifies, rather than replaces, professional expertise. Together, the constructs informed the AI-Responsive Curriculum Design (ARCD) Framework.
CONCLUSION: The ARCD Framework explains AI-responsive curriculum implementation as a relational process combining predictive insight, ecological sensitivity, and educator agency. It offers implications for curriculum policy, teacher professional development, and ethical AI integration in ECE.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Curriculum
Humans
*Artificial Intelligence
Child, Preschool
*Learning
Deep Learning
*Child Development
RevDate: 2026-10-20
CmpDate: 2026-10-19
The genome sequence of a gelechiid moth, Gnorimoschema epithymella (Staudinger, 1859) (Lepidoptera: Gelechiidae).
Wellcome open research, 11:653.
We present a genome assembly from a female specimen of Gnorimoschema epithymella (Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 660.36 megabases and 557.93 megabases. Most of the haplotype 1 assembly (99.45%) was scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.23 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
Additional Links: PMID-42894520
PubMed:
Citation:
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@article {pmid42894520,
year = {2026},
author = {Mutanen, M and Kiljunen, N and Huemer, P and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of a gelechiid moth, Gnorimoschema epithymella (Staudinger, 1859) (Lepidoptera: Gelechiidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {653},
pmid = {42894520},
issn = {2398-502X},
abstract = {We present a genome assembly from a female specimen of Gnorimoschema epithymella (Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 660.36 megabases and 557.93 megabases. Most of the haplotype 1 assembly (99.45%) was scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.23 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-19
Pollution characteristics, source analysis and risk assessment of perfluoroalkyl and polyfluoroalkyl substances of Kui River.
Environmental toxicology and chemistry pii:8943354 [Epub ahead of print].
To investigate the pollution distribution characteristics and ecological risk levels of per- and polyfluoroalkyl substances (PFAS) in the surface water of the Kui River, this study tested 17 PFAS in the surface water and analyzed their pollution levels in the local aquatic environment. Results showed PFAS were ubiquitous in the Kui River, with ΣPFAS concentrations ranging from 241.83 to 700.09 ng·L-1. The main pollutants were perfluorobutyric acid (PFBA), perfluorohexanoic acid (PFHxA), and perfluorooctanoic acid (PFOA), with average concentrations of 124.62, 127.26, and 188.47 ng·L-1, respectively. Per- and polyfluoroalkyl substances (PFAS) composition had distinct seasonal variations: PFBA dominated in the wet season, while PFOA prevailed in the dry season. Principal component analysis indicated PFAS pollution mainly originated from food packaging, surfactant production, plastics, and metal plating/textiles. Ecological risk assessment showed most PFAS posed low risks; only PFOA had low risk at all dry-season sampling sites, and mixture Risk Quotient (RQmix) posed a general low-level risk. Health risk assessment found Hazard Quotient (HQ) values of seven PFAS for all age groups ranged from 1.36E-4 to 0.247. PFOA exposure had HQ > 0.1 (low hazard), while the other six showed no significant hazard. However, HQmix exceeded 0.1 for all four age groups, indicating adverse health effects. Future attention should focus on the management of dynamic PFAS sources and the combined risk posed by PFAS mixtures in the Kui River.
Additional Links: PMID-42895294
Publisher:
PubMed:
Citation:
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@article {pmid42895294,
year = {2026},
author = {Wu, S and Zhang, L and She, Y and Kang, G and Liu, X and Xu, Z and Huai, T and Li, R and Qi, L and Zhang, M},
title = {Pollution characteristics, source analysis and risk assessment of perfluoroalkyl and polyfluoroalkyl substances of Kui River.},
journal = {Environmental toxicology and chemistry},
volume = {},
number = {},
pages = {},
doi = {10.1093/etojnl/vgag144},
pmid = {42895294},
issn = {1552-8618},
abstract = {To investigate the pollution distribution characteristics and ecological risk levels of per- and polyfluoroalkyl substances (PFAS) in the surface water of the Kui River, this study tested 17 PFAS in the surface water and analyzed their pollution levels in the local aquatic environment. Results showed PFAS were ubiquitous in the Kui River, with ΣPFAS concentrations ranging from 241.83 to 700.09 ng·L-1. The main pollutants were perfluorobutyric acid (PFBA), perfluorohexanoic acid (PFHxA), and perfluorooctanoic acid (PFOA), with average concentrations of 124.62, 127.26, and 188.47 ng·L-1, respectively. Per- and polyfluoroalkyl substances (PFAS) composition had distinct seasonal variations: PFBA dominated in the wet season, while PFOA prevailed in the dry season. Principal component analysis indicated PFAS pollution mainly originated from food packaging, surfactant production, plastics, and metal plating/textiles. Ecological risk assessment showed most PFAS posed low risks; only PFOA had low risk at all dry-season sampling sites, and mixture Risk Quotient (RQmix) posed a general low-level risk. Health risk assessment found Hazard Quotient (HQ) values of seven PFAS for all age groups ranged from 1.36E-4 to 0.247. PFOA exposure had HQ > 0.1 (low hazard), while the other six showed no significant hazard. However, HQmix exceeded 0.1 for all four age groups, indicating adverse health effects. Future attention should focus on the management of dynamic PFAS sources and the combined risk posed by PFAS mixtures in the Kui River.},
}
RevDate: 2026-10-19
CmpDate: 2026-10-19
Biotic response networks are an important organizer of the transcriptome in wild Arabidopsis thaliana populations.
Proceedings of the National Academy of Sciences of the United States of America, 123(43):e2611539123.
Extensive laboratory experimentation has revealed conserved molecular pathways controlling growth and stress responses in plants, yet how these programs operate in natural settings remains poorly understood. We have investigated the organization of the transcriptome in wild populations of Arabidopsis thaliana by sampling plants across 60 natural sites in Europe and North America over two seasons. Transcriptomes varied extensively among individuals and were only weakly structured by geography or season. No groups of plants stood out due to clear biotic or abiotic stress signatures known from the laboratory. While only a small portion of transcriptome variance was explained by disease symptoms or environmental and phenotypic variables, infection-associated signals accounted for the largest share of the explainable fraction. Biotic-response networks identified in controlled laboratory conditions were well conserved in wild transcriptomes, while other networks, including abiotic-response networks were substantially reorganized in wild plants. Together, these results indicate that while certain transcriptional modules are easily reidentified when moving from the wild to controlled conditions, many regulatory relationships differ in these two contexts, highlighting how ecological complexity shapes transcriptome organization in natural populations.
Additional Links: PMID-42896052
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PubMed:
Citation:
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@article {pmid42896052,
year = {2026},
author = {Leite Montalvão, AP and Murray, KD and Bezrukov, I and Betz, N and Henry, LP and Duran, P and Boppert, P and Kolb, M and , and Roux, F and Bergelson, J and Weigel, D and Yuan, W},
title = {Biotic response networks are an important organizer of the transcriptome in wild Arabidopsis thaliana populations.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {123},
number = {43},
pages = {e2611539123},
doi = {10.1073/pnas.2611539123},
pmid = {42896052},
issn = {1091-6490},
support = {951444//EC | European Research Council (ERC)/ ; NONE//Charles H. Revson Foundation (CHRF)/ ; 101028577//EC | HORIZON EUROPE Framework Programme (Horizon Europe)/ ; SFI-PD-Grant-01308072//Simons Foundation (SF)/ ; CMFI//Deutsche Forschungsgemeinschaft (DFG)/ ; Novozymes Prize//Novo Nordisk Fonden (NNF)/ ; NONE//Max-Planck-Gesellschaft (MPG)/ ; },
mesh = {*Arabidopsis/genetics ; *Transcriptome/genetics ; Gene Expression Regulation, Plant ; *Gene Regulatory Networks ; Stress, Physiological/genetics ; Europe ; Gene Expression Profiling ; North America ; },
abstract = {Extensive laboratory experimentation has revealed conserved molecular pathways controlling growth and stress responses in plants, yet how these programs operate in natural settings remains poorly understood. We have investigated the organization of the transcriptome in wild populations of Arabidopsis thaliana by sampling plants across 60 natural sites in Europe and North America over two seasons. Transcriptomes varied extensively among individuals and were only weakly structured by geography or season. No groups of plants stood out due to clear biotic or abiotic stress signatures known from the laboratory. While only a small portion of transcriptome variance was explained by disease symptoms or environmental and phenotypic variables, infection-associated signals accounted for the largest share of the explainable fraction. Biotic-response networks identified in controlled laboratory conditions were well conserved in wild transcriptomes, while other networks, including abiotic-response networks were substantially reorganized in wild plants. Together, these results indicate that while certain transcriptional modules are easily reidentified when moving from the wild to controlled conditions, many regulatory relationships differ in these two contexts, highlighting how ecological complexity shapes transcriptome organization in natural populations.},
}
MeSH Terms:
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*Arabidopsis/genetics
*Transcriptome/genetics
Gene Expression Regulation, Plant
*Gene Regulatory Networks
Stress, Physiological/genetics
Europe
Gene Expression Profiling
North America
RevDate: 2026-10-19
CmpDate: 2026-10-19
Level-specific reliability coefficients from the perspective of latent state-trait theory.
The British journal of mathematical and statistical psychology, 79(3):621-638.
The growing popularity of the ecological momentary assessment method in psychological research requires adequate statistical models for intensive longitudinal data (ILD), with multilevel latent state-trait (ML-LST) models based on the latent state-trait theory revised (LST-R theory) as one possible alternative. Besides the traditional LST-R coefficients reliability, consistency and occasion-specificity, ML-LST models are also suitable for estimating reliability at Level 1 ("within-subject reliability") and Level 2 ("between-subject reliability"). However, these level-specific coefficients have not yet been defined in LST-R theory and, therefore, their interpretation has been unclear from the perspective of LST-R theory. In the current study, we discuss the interpretation and identification of these coefficients based on the (multilevel) versions of the Multistate-Singletrait (MSST), the Multistate-Indicator-specific trait (MSIT) and the Multistate-Singletrait model with M-1 correlated method factors (MSST-M-1). We show that, in the MSST-M-1 model, the between-subject coefficient is a measure of the indicator-unspecificity of an item (i.e. the portion of between-level variance that a specific item shares with a common trait) or the unidimensionality of a scale. Moreover, we highlight differences between occasion-specificity and within-subject reliability. The performance of the ML-MSST-M-1 model and the corresponding theoretical findings are illustrated using data from an experience sampling study on the within-person fluctuations of narcissistic admiration (Heyde et al., 2023).
Additional Links: PMID-41454688
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@article {pmid41454688,
year = {2026},
author = {Nacke, L and Mayer, A},
title = {Level-specific reliability coefficients from the perspective of latent state-trait theory.},
journal = {The British journal of mathematical and statistical psychology},
volume = {79},
number = {3},
pages = {621-638},
doi = {10.1111/bmsp.70027},
pmid = {41454688},
issn = {2044-8317},
mesh = {Reproducibility of Results ; Humans ; *Models, Statistical ; *Psychometrics/statistics & numerical data ; Longitudinal Studies ; *Ecological Momentary Assessment/statistics & numerical data ; Data Interpretation, Statistical ; },
abstract = {The growing popularity of the ecological momentary assessment method in psychological research requires adequate statistical models for intensive longitudinal data (ILD), with multilevel latent state-trait (ML-LST) models based on the latent state-trait theory revised (LST-R theory) as one possible alternative. Besides the traditional LST-R coefficients reliability, consistency and occasion-specificity, ML-LST models are also suitable for estimating reliability at Level 1 ("within-subject reliability") and Level 2 ("between-subject reliability"). However, these level-specific coefficients have not yet been defined in LST-R theory and, therefore, their interpretation has been unclear from the perspective of LST-R theory. In the current study, we discuss the interpretation and identification of these coefficients based on the (multilevel) versions of the Multistate-Singletrait (MSST), the Multistate-Indicator-specific trait (MSIT) and the Multistate-Singletrait model with M-1 correlated method factors (MSST-M-1). We show that, in the MSST-M-1 model, the between-subject coefficient is a measure of the indicator-unspecificity of an item (i.e. the portion of between-level variance that a specific item shares with a common trait) or the unidimensionality of a scale. Moreover, we highlight differences between occasion-specificity and within-subject reliability. The performance of the ML-MSST-M-1 model and the corresponding theoretical findings are illustrated using data from an experience sampling study on the within-person fluctuations of narcissistic admiration (Heyde et al., 2023).},
}
MeSH Terms:
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hide MeSH Terms
Reproducibility of Results
Humans
*Models, Statistical
*Psychometrics/statistics & numerical data
Longitudinal Studies
*Ecological Momentary Assessment/statistics & numerical data
Data Interpretation, Statistical
RevDate: 2026-10-18
CmpDate: 2026-10-18
Neonatal intensive care unit exposures reprogram microbiome-metabolome trajectories and modulate host calprotectin in preterm infants: a longitudinal multi-omics study.
NPJ biofilms and microbiomes, 12(1):.
Early-life gut microbiota development is critical for orchestrating mucosal barrier function and immune priming, as disruptions in this process can increase susceptibility to life-threatening diseases such as necrotizing enterocolitis (NEC) and sepsis. This longitudinal multi-omics study of 186 preterm infants (<32 weeks of gestation or <1500 g birth weight) explores the impact of early-life exposures in the neonatal intensive care units (NICUs) on gut microbiota, metabolism, and immune responses. We analyzed 1153 stool samples using quantitative microbial profiling, untargeted metabolomics, and fecal S100A8/A9 (calprotectin) levels. Antibiotic exposure suppressed anaerobic colonization and microbial diversity in a cumulative exposure-dependent manner, with breastmilk feeding partially mitigating these effects. The stool metabolome correlated with microbial colonization, showing antibiotic-driven disruptions in polyamine metabolism linked to anaerobe abundance. Host calprotectin levels followed a biphasic pattern, correlating with microbial diversity and polyamine metabolites. Mediation analysis identified anaerobe suppression and polyamine depletion as key drivers of antibiotic-associated reductions in calprotectin. This study reveals that NICU interventions, particularly antibiotics, reprogram the preterm gut ecosystem and immune response, with anaerobes and polyamines being key mediators linking microbial ecology to immune maturation during early life.
Additional Links: PMID-42135341
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Citation:
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@article {pmid42135341,
year = {2026},
author = {Huang, Y and Hong, L and Li, S and Zhang, L and Guo, X and Han, J and Yu, W and Chen, H and Luo, N and Chen, J and Peng, W and Zhou, Y and Hong, S and Yan, W and Jiang, S and Cao, Y},
title = {Neonatal intensive care unit exposures reprogram microbiome-metabolome trajectories and modulate host calprotectin in preterm infants: a longitudinal multi-omics study.},
journal = {NPJ biofilms and microbiomes},
volume = {12},
number = {1},
pages = {},
pmid = {42135341},
issn = {2055-5008},
support = {82402017//National Key Research and Development Program of China/ ; },
mesh = {Humans ; *Leukocyte L1 Antigen Complex/metabolism ; Infant, Newborn ; Multiomics ; *Infant, Premature ; Feces/microbiology/chemistry ; Longitudinal Studies ; Intensive Care Units, Neonatal ; *Metabolome ; *Gastrointestinal Microbiome/drug effects ; Anti-Bacterial Agents/pharmacology ; Female ; Metabolomics ; Male ; Enterocolitis, Necrotizing/microbiology ; Calgranulin A ; Calgranulin B ; Polyamines/metabolism ; },
abstract = {Early-life gut microbiota development is critical for orchestrating mucosal barrier function and immune priming, as disruptions in this process can increase susceptibility to life-threatening diseases such as necrotizing enterocolitis (NEC) and sepsis. This longitudinal multi-omics study of 186 preterm infants (<32 weeks of gestation or <1500 g birth weight) explores the impact of early-life exposures in the neonatal intensive care units (NICUs) on gut microbiota, metabolism, and immune responses. We analyzed 1153 stool samples using quantitative microbial profiling, untargeted metabolomics, and fecal S100A8/A9 (calprotectin) levels. Antibiotic exposure suppressed anaerobic colonization and microbial diversity in a cumulative exposure-dependent manner, with breastmilk feeding partially mitigating these effects. The stool metabolome correlated with microbial colonization, showing antibiotic-driven disruptions in polyamine metabolism linked to anaerobe abundance. Host calprotectin levels followed a biphasic pattern, correlating with microbial diversity and polyamine metabolites. Mediation analysis identified anaerobe suppression and polyamine depletion as key drivers of antibiotic-associated reductions in calprotectin. This study reveals that NICU interventions, particularly antibiotics, reprogram the preterm gut ecosystem and immune response, with anaerobes and polyamines being key mediators linking microbial ecology to immune maturation during early life.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Leukocyte L1 Antigen Complex/metabolism
Infant, Newborn
Multiomics
*Infant, Premature
Feces/microbiology/chemistry
Longitudinal Studies
Intensive Care Units, Neonatal
*Metabolome
*Gastrointestinal Microbiome/drug effects
Anti-Bacterial Agents/pharmacology
Female
Metabolomics
Male
Enterocolitis, Necrotizing/microbiology
Calgranulin A
Calgranulin B
Polyamines/metabolism
RevDate: 2026-10-19
CmpDate: 2026-10-19
A bioinformatics framework using public 16S rRNA gene amplicon data to assess the presence of target bacteria in bat and rodent samples.
Journal of microbiological methods, 250:107684.
Validating the ecological distribution of a newly isolated bacterial species in natural hosts remains challenging due to the lack of specific detection assays and the cost of large-scale screening. Here, we describe a dual-strategy bioinformatics pipeline that leverages publicly available 16S rRNA gene amplicon sequencing data to reliably and inexpensively confirm target bacterial presence. The method first extracts hypervariable regions from the target bacterium's full-length 16S rRNA gene and evaluates their specificity by calculating an A-value-defined as the highest sequence similarity to any non-target strain in reference databases. Regions with an A-value below the 98.7% species threshold are selected. These are then aligned against Amplicon Sequence Variants (ASVs) from public datasets to compute a B-value (highest similarity to ASVs within a sample). A novel classification logic (B > A) is applied to designate samples as positive or negative, reducing false positives. The pipeline incorporates multi-level controls, including process/biological negatives and positives. Testing with novel species (Clostridium sp. nov.) and a formally described species (Streptococcus lishijunsis), along with common commensal species demonstrated that region-specific performance varies, highlighting the need for pre-validation. The framework successfully distinguished target-positive from negative samples, with phylogenetic support for specificity. This approach provides a rigorous, cost-effective, and accessible workflow that links in vitro isolation to in vivo ecological validation using existing public data.
Additional Links: PMID-42686068
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@article {pmid42686068,
year = {2026},
author = {Zhou, J and Gu, T and Li, S},
title = {A bioinformatics framework using public 16S rRNA gene amplicon data to assess the presence of target bacteria in bat and rodent samples.},
journal = {Journal of microbiological methods},
volume = {250},
number = {},
pages = {107684},
doi = {10.1016/j.mimet.2026.107684},
pmid = {42686068},
issn = {1872-8359},
mesh = {Animals ; *RNA, Ribosomal, 16S/genetics ; *Computational Biology/methods ; *Bacteria/genetics/isolation & purification/classification ; DNA, Bacterial/genetics ; *Rodentia/microbiology ; Phylogeny ; Sequence Analysis, DNA/methods ; },
abstract = {Validating the ecological distribution of a newly isolated bacterial species in natural hosts remains challenging due to the lack of specific detection assays and the cost of large-scale screening. Here, we describe a dual-strategy bioinformatics pipeline that leverages publicly available 16S rRNA gene amplicon sequencing data to reliably and inexpensively confirm target bacterial presence. The method first extracts hypervariable regions from the target bacterium's full-length 16S rRNA gene and evaluates their specificity by calculating an A-value-defined as the highest sequence similarity to any non-target strain in reference databases. Regions with an A-value below the 98.7% species threshold are selected. These are then aligned against Amplicon Sequence Variants (ASVs) from public datasets to compute a B-value (highest similarity to ASVs within a sample). A novel classification logic (B > A) is applied to designate samples as positive or negative, reducing false positives. The pipeline incorporates multi-level controls, including process/biological negatives and positives. Testing with novel species (Clostridium sp. nov.) and a formally described species (Streptococcus lishijunsis), along with common commensal species demonstrated that region-specific performance varies, highlighting the need for pre-validation. The framework successfully distinguished target-positive from negative samples, with phylogenetic support for specificity. This approach provides a rigorous, cost-effective, and accessible workflow that links in vitro isolation to in vivo ecological validation using existing public data.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*RNA, Ribosomal, 16S/genetics
*Computational Biology/methods
*Bacteria/genetics/isolation & purification/classification
DNA, Bacterial/genetics
*Rodentia/microbiology
Phylogeny
Sequence Analysis, DNA/methods
RevDate: 2026-10-16
Real-Life Psychological Experiences and Cardiac Autonomic Physiology Among Survivors of a Myocardial Infarction in Midlife.
Journal of the American Heart Association [Epub ahead of print].
BACKGROUND: Young and middle-aged women with ischemic heart disease have a higher burden of psychosocial factors compared with male counterparts. They also have worse morbidity and mortality, despite less atherosclerotic burden. Data on daily life stress and autonomic physiology could help guide targeted interventions.
METHODS: We studied 302 individuals ≤61 years of age recently hospitalized for a myocardial infarction. All underwent a 7-day home monitoring of mood and stress using ecological momentary assessments, with concomitant Holter monitoring for autonomic physiology. Deceleration capacity, a prognostic marker of parasympathetic activity, was the primary autonomic outcome; heart rate variability was also examined.
RESULTS: The sample was 43% women with mean age of 51 years (SD, 7 years). Across the week of monitoring, women reported higher levels of negative mood and stress than men. Women also exhibited significantly lower parasympathetic activity (daily average of deceleration capacity) than men; heart rate variability was also lower. Among women, daily negative mood was inversely associated with lower deceleration capacity: for each 1-log unit higher daily negative mood score, deceleration capacity declined 4.5% in women, but among men, the difference was close to zero: 0.5% (P=0.02 for interaction). Adjustment for other risk factors did not materially affect the associations. A similar pattern of results was observed for heart rate variability metrics.
CONCLUSIONS: Young and middle-aged women who recently survived a myocardial infarction have more parasympathetic withdrawal than men in daily life, especially during moments of negative mood. These results underscore the need for greater attention to psychosocial management in women after myocardial infarction.
Additional Links: PMID-42885808
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PubMed:
Citation:
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@article {pmid42885808,
year = {2026},
author = {Vaccarino, V and She, H and Elon, L and Lewis, TT and Ko, YA and Clifford, G and Li, Q and Murrah, N and Shallenberger, LH and Roberts, T and Stefanos, L and Fan-Lou, E and Bremner, JD and Raggi, P and Quyyumi, A and Shah, AJ},
title = {Real-Life Psychological Experiences and Cardiac Autonomic Physiology Among Survivors of a Myocardial Infarction in Midlife.},
journal = {Journal of the American Heart Association},
volume = {},
number = {},
pages = {e052187},
doi = {10.1161/JAHA.126.052187},
pmid = {42885808},
issn = {2047-9980},
abstract = {BACKGROUND: Young and middle-aged women with ischemic heart disease have a higher burden of psychosocial factors compared with male counterparts. They also have worse morbidity and mortality, despite less atherosclerotic burden. Data on daily life stress and autonomic physiology could help guide targeted interventions.
METHODS: We studied 302 individuals ≤61 years of age recently hospitalized for a myocardial infarction. All underwent a 7-day home monitoring of mood and stress using ecological momentary assessments, with concomitant Holter monitoring for autonomic physiology. Deceleration capacity, a prognostic marker of parasympathetic activity, was the primary autonomic outcome; heart rate variability was also examined.
RESULTS: The sample was 43% women with mean age of 51 years (SD, 7 years). Across the week of monitoring, women reported higher levels of negative mood and stress than men. Women also exhibited significantly lower parasympathetic activity (daily average of deceleration capacity) than men; heart rate variability was also lower. Among women, daily negative mood was inversely associated with lower deceleration capacity: for each 1-log unit higher daily negative mood score, deceleration capacity declined 4.5% in women, but among men, the difference was close to zero: 0.5% (P=0.02 for interaction). Adjustment for other risk factors did not materially affect the associations. A similar pattern of results was observed for heart rate variability metrics.
CONCLUSIONS: Young and middle-aged women who recently survived a myocardial infarction have more parasympathetic withdrawal than men in daily life, especially during moments of negative mood. These results underscore the need for greater attention to psychosocial management in women after myocardial infarction.},
}
RevDate: 2026-10-19
CmpDate: 2026-10-16
Losing Sleep, Gaining Weight? Young Bangladeshi Adults' Perceptions of Sleep, Eating and Body Weight: A Qualitative Study.
Health expectations : an international journal of public participation in health care and health policy, 29(5):e70933.
BACKGROUND: Inadequate sleep and excess body weight are escalating global health concerns, especially among young adults facing academic pressures, digital lifestyles, and cultural norms. While quantitative research has shown links between sleep and body weight, little is known about the lived experiences shaping this relationship in Asian contexts.
METHODS: A qualitative study was conducted in urban Dhaka, Bangladesh, in 2022. Twenty-six young adults aged 18-25 years were recruited through purposive and snowball sampling methods. Semi-structured, in-depth interviews were conducted in Bangla, audio-recorded, transcribed verbatim, and translated into English. Thematic analysis was performed using an inductive approach, supplemented by deductive coding based on the socio-ecological model (SEM).
RESULTS: Five key themes emerged: (1) structural and environmental conditions disrupting sleep; (2) digital night culture and socially reinforced wakefulness; (3) the prioritisation of productivity over sleep; (4) unequal burdens of household labour and caregiving and opportunities for rest; and (5) perceived associations between irregular sleep, fatigue, and eating behaviours. Young adults described poor sleep as both a personal and structural issue and perceived connections with body weight and overall wellbeing. Across the identified themes, sleep and eating practices that appeared individual were embedded within interpersonal, institutional, environmental, and sociocultural contexts.
CONCLUSIONS: The findings indicate opportunities for healthy sleep are influenced by social, institutional, and environmental conditions in addition to individual practices. Consequently, sleep-health strategies targeting young adults may benefit from integrating individual education with interventions that address peer and family practices, institutional expectations, and environments conducive to sleep health. Further longitudinal and mixed-method research is required to investigate the pathways identified in these qualitative accounts.
The findings were discussed with patient and public involvement (PPI) members who are young adults. Their insights informed the development of the interview guide. A subset of participants helped interpret the results by engaging in member checking of preliminary findings and identified themes. Members of the public did not participate in study governance or manuscript preparation.
Additional Links: PMID-42886171
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Citation:
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@article {pmid42886171,
year = {2026},
author = {Moonajilin, MS and Islam, RU and Taher, L and Noshin, F and Taher, T and Kamal, S},
title = {Losing Sleep, Gaining Weight? Young Bangladeshi Adults' Perceptions of Sleep, Eating and Body Weight: A Qualitative Study.},
journal = {Health expectations : an international journal of public participation in health care and health policy},
volume = {29},
number = {5},
pages = {e70933},
pmid = {42886171},
issn = {1369-7625},
mesh = {Humans ; Bangladesh ; Young Adult ; Adult ; Qualitative Research ; Female ; Adolescent ; Male ; *Sleep ; *Feeding Behavior/psychology ; *Body Weight ; Interviews as Topic ; *Weight Gain ; },
abstract = {BACKGROUND: Inadequate sleep and excess body weight are escalating global health concerns, especially among young adults facing academic pressures, digital lifestyles, and cultural norms. While quantitative research has shown links between sleep and body weight, little is known about the lived experiences shaping this relationship in Asian contexts.
METHODS: A qualitative study was conducted in urban Dhaka, Bangladesh, in 2022. Twenty-six young adults aged 18-25 years were recruited through purposive and snowball sampling methods. Semi-structured, in-depth interviews were conducted in Bangla, audio-recorded, transcribed verbatim, and translated into English. Thematic analysis was performed using an inductive approach, supplemented by deductive coding based on the socio-ecological model (SEM).
RESULTS: Five key themes emerged: (1) structural and environmental conditions disrupting sleep; (2) digital night culture and socially reinforced wakefulness; (3) the prioritisation of productivity over sleep; (4) unequal burdens of household labour and caregiving and opportunities for rest; and (5) perceived associations between irregular sleep, fatigue, and eating behaviours. Young adults described poor sleep as both a personal and structural issue and perceived connections with body weight and overall wellbeing. Across the identified themes, sleep and eating practices that appeared individual were embedded within interpersonal, institutional, environmental, and sociocultural contexts.
CONCLUSIONS: The findings indicate opportunities for healthy sleep are influenced by social, institutional, and environmental conditions in addition to individual practices. Consequently, sleep-health strategies targeting young adults may benefit from integrating individual education with interventions that address peer and family practices, institutional expectations, and environments conducive to sleep health. Further longitudinal and mixed-method research is required to investigate the pathways identified in these qualitative accounts.
The findings were discussed with patient and public involvement (PPI) members who are young adults. Their insights informed the development of the interview guide. A subset of participants helped interpret the results by engaging in member checking of preliminary findings and identified themes. Members of the public did not participate in study governance or manuscript preparation.},
}
MeSH Terms:
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hide MeSH Terms
Humans
Bangladesh
Young Adult
Adult
Qualitative Research
Female
Adolescent
Male
*Sleep
*Feeding Behavior/psychology
*Body Weight
Interviews as Topic
*Weight Gain
RevDate: 2026-10-16
CmpDate: 2026-10-16
Occurrence, spatial distribution, and ecological and human health risks of antibiotic residues in the River Jhelum.
Environmental geochemistry and health, 48(16):.
Antibiotic residues in riverine environments are emerging contaminants of concern because of their persistence, ecological effects, and potential contribution to antimicrobial resistance. This study investigated the occurrence, spatial distribution, pollution status, and screening-level ecological and human-health risks of six antibiotics in the River Jhelum, Pakistan. Surface-water samples were collected from ten monitoring sites representing upstream, midstream, and downstream reaches during a post-monsoon sampling campaign. Antibiotics were quantified using High Performance Liquid Chromatography coupled with photodiode-array detection, while single-factor and comprehensive pollution indices and GIS-based spatial interpolation were applied to characterize contamination patterns. Azithromycin exhibited the highest concentration (20.30 µg/L), followed by ofloxacin (12.70 µg/L), ciprofloxacin (8.03 µg/L), linezolid (4.55 µg/L), cefixime (1.40 µg/L), and levofloxacin (0.51 µg/L). Azithromycin showed the greatest pollution burden across the monitoring sites investigated, whereas levofloxacin exhibited comparatively limited contamination. The comprehensive pollution assessment indicated substantial combined antibiotic contamination across the investigated river transect. Azithromycin produced the highest ecological risk quotient (RQ = 17.41), indicating high predicted ecological risk under the applied screening framework. Human health hazard quotients remained below unity, indicating non carcinogenic risks. These findings strengthen wastewater management, pharmaceutical discharge controls, and systematic monitoring of antibiotic residues in the River Jhelum.
Additional Links: PMID-42886401
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@article {pmid42886401,
year = {2026},
author = {Fatima, B and Mahmood, A and Urooj, A and Waseem, A and Mahmood, A and Ullah, R and Alamri, S and Irfan, HM and Mahmood, A},
title = {Occurrence, spatial distribution, and ecological and human health risks of antibiotic residues in the River Jhelum.},
journal = {Environmental geochemistry and health},
volume = {48},
number = {16},
pages = {},
pmid = {42886401},
issn = {1573-2983},
mesh = {*Rivers/chemistry ; Humans ; *Anti-Bacterial Agents/analysis ; *Water Pollutants, Chemical/analysis ; Environmental Monitoring ; Risk Assessment ; Pakistan ; Geographic Information Systems ; },
abstract = {Antibiotic residues in riverine environments are emerging contaminants of concern because of their persistence, ecological effects, and potential contribution to antimicrobial resistance. This study investigated the occurrence, spatial distribution, pollution status, and screening-level ecological and human-health risks of six antibiotics in the River Jhelum, Pakistan. Surface-water samples were collected from ten monitoring sites representing upstream, midstream, and downstream reaches during a post-monsoon sampling campaign. Antibiotics were quantified using High Performance Liquid Chromatography coupled with photodiode-array detection, while single-factor and comprehensive pollution indices and GIS-based spatial interpolation were applied to characterize contamination patterns. Azithromycin exhibited the highest concentration (20.30 µg/L), followed by ofloxacin (12.70 µg/L), ciprofloxacin (8.03 µg/L), linezolid (4.55 µg/L), cefixime (1.40 µg/L), and levofloxacin (0.51 µg/L). Azithromycin showed the greatest pollution burden across the monitoring sites investigated, whereas levofloxacin exhibited comparatively limited contamination. The comprehensive pollution assessment indicated substantial combined antibiotic contamination across the investigated river transect. Azithromycin produced the highest ecological risk quotient (RQ = 17.41), indicating high predicted ecological risk under the applied screening framework. Human health hazard quotients remained below unity, indicating non carcinogenic risks. These findings strengthen wastewater management, pharmaceutical discharge controls, and systematic monitoring of antibiotic residues in the River Jhelum.},
}
MeSH Terms:
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*Rivers/chemistry
Humans
*Anti-Bacterial Agents/analysis
*Water Pollutants, Chemical/analysis
Environmental Monitoring
Risk Assessment
Pakistan
Geographic Information Systems
RevDate: 2026-10-16
CmpDate: 2026-10-16
Ten simple rules for developing a reporting appraisal tool.
PLoS computational biology, 22(10):e1014841.
In an ideal world, authors would report clearly and transparently exactly what they conducted. In reality, reporting is often incomplete, and key elements of research conduct are frequently missing from manuscripts. Reporting guidelines were developed to address this problem by helping authors identify what should be reported. These guidelines have been highly valuable for authors, but they are not well suited for appraising reporting during peer review or editorial assessment despite common use. This is because authors and appraisers have different needs: authors require a comprehensive guide for writing, whereas appraisers need a tool that is concise, repeatable, and easy to use. We therefore propose the development of reporting appraisal tools: operationalised tools designed specifically to assess whether a paper has reported the minimum essential elements of a study. To support their development, we present 10 simple rules.
Additional Links: PMID-42886726
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@article {pmid42886726,
year = {2026},
author = {Morrison, K and Lagisz, M},
title = {Ten simple rules for developing a reporting appraisal tool.},
journal = {PLoS computational biology},
volume = {22},
number = {10},
pages = {e1014841},
pmid = {42886726},
issn = {1553-7358},
mesh = {*Peer Review, Research/standards ; Computational Biology ; Guidelines as Topic ; *Writing/standards ; Humans ; *Publishing/standards ; Research Design/standards ; },
abstract = {In an ideal world, authors would report clearly and transparently exactly what they conducted. In reality, reporting is often incomplete, and key elements of research conduct are frequently missing from manuscripts. Reporting guidelines were developed to address this problem by helping authors identify what should be reported. These guidelines have been highly valuable for authors, but they are not well suited for appraising reporting during peer review or editorial assessment despite common use. This is because authors and appraisers have different needs: authors require a comprehensive guide for writing, whereas appraisers need a tool that is concise, repeatable, and easy to use. We therefore propose the development of reporting appraisal tools: operationalised tools designed specifically to assess whether a paper has reported the minimum essential elements of a study. To support their development, we present 10 simple rules.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Peer Review, Research/standards
Computational Biology
Guidelines as Topic
*Writing/standards
Humans
*Publishing/standards
Research Design/standards
RevDate: 2026-10-19
CmpDate: 2026-10-17
Comparability of food frequency questionnaires between Korean Children's Environmental Health Study (Ko-CHENS) and Korean Genome and Epidemiology Study (KoGES) in pregnant women.
Nutrition research and practice, 20(5):866-878.
BACKGROUND/OBJECTIVES: The Korean Children's Environmental Health Study (Ko-CHENS) developed a food frequency questionnaire (FFQ) to assess maternal dietary intake during pregnancy. This FFQ shares high structural similarity with the validated FFQ of the Korean Genome and Epidemiology Study (KoGES), a representative dietary assessment tool for the Korean adult population, which includes 97 of the 112 items in the Ko-CHENS FFQ. The comparability of the Ko-CHENS and KoGES FFQs among pregnant women was evaluated.
SUBJECTS/METHODS: Ninety-four women recruited from Kangwon National University Hospital between December 2024 and February 2025 were included. The participants consecutively completed the Ko-CHENS and KoGES FFQs. The nutrient intakes were adjusted for the total energy intake using the residual method. Log-transformed intakes of energy, nutrients, and food groups were compared using the correlation coefficients, cross-classification percent agreement, weighted kappa statistics, and Bland-Altman plots.
RESULTS: The Ko-CHENS FFQ yielded higher absolute intake estimates for energy and the majority of nutrients and food groups than the KoGES FFQ. The Pearson or Spearman correlation coefficients ranged from 0.34 (vitamin E) to 0.68 (β-carotene) for energy and nutrients and from 0.15 (sugars and jams) to 0.77 (salted vegetables) for food groups, with median values of 0.55 and 0.61, respectively. The median proportions of the participants classified into the same or adjacent quartiles were 96.39% for energy and nutrients and 96.52% for food groups. The weighted kappa statistics ranged from 0.23 to 0.52 for energy and nutrients and from 0.06 to 0.59 for food groups, with median values of 0.38 and 0.45, respectively. The Bland-Altman plots for energy and macronutrients showed that the data points were primarily within the limits of agreement.
CONCLUSION: The Ko-CHENS and KoGES FFQs showed fair-to-moderate comparability, suggesting that the Ko-CHENS FFQ can be used for ranking Korean pregnant women based on their dietary intake levels.
Additional Links: PMID-42889450
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@article {pmid42889450,
year = {2026},
author = {Cho, M and Kim, B and Kim, H and Na, S and Lee, SJ and Ahn, TG and Son, KH and Kim, WJ and Lee, JE and , },
title = {Comparability of food frequency questionnaires between Korean Children's Environmental Health Study (Ko-CHENS) and Korean Genome and Epidemiology Study (KoGES) in pregnant women.},
journal = {Nutrition research and practice},
volume = {20},
number = {5},
pages = {866-878},
pmid = {42889450},
issn = {1976-1457},
abstract = {BACKGROUND/OBJECTIVES: The Korean Children's Environmental Health Study (Ko-CHENS) developed a food frequency questionnaire (FFQ) to assess maternal dietary intake during pregnancy. This FFQ shares high structural similarity with the validated FFQ of the Korean Genome and Epidemiology Study (KoGES), a representative dietary assessment tool for the Korean adult population, which includes 97 of the 112 items in the Ko-CHENS FFQ. The comparability of the Ko-CHENS and KoGES FFQs among pregnant women was evaluated.
SUBJECTS/METHODS: Ninety-four women recruited from Kangwon National University Hospital between December 2024 and February 2025 were included. The participants consecutively completed the Ko-CHENS and KoGES FFQs. The nutrient intakes were adjusted for the total energy intake using the residual method. Log-transformed intakes of energy, nutrients, and food groups were compared using the correlation coefficients, cross-classification percent agreement, weighted kappa statistics, and Bland-Altman plots.
RESULTS: The Ko-CHENS FFQ yielded higher absolute intake estimates for energy and the majority of nutrients and food groups than the KoGES FFQ. The Pearson or Spearman correlation coefficients ranged from 0.34 (vitamin E) to 0.68 (β-carotene) for energy and nutrients and from 0.15 (sugars and jams) to 0.77 (salted vegetables) for food groups, with median values of 0.55 and 0.61, respectively. The median proportions of the participants classified into the same or adjacent quartiles were 96.39% for energy and nutrients and 96.52% for food groups. The weighted kappa statistics ranged from 0.23 to 0.52 for energy and nutrients and from 0.06 to 0.59 for food groups, with median values of 0.38 and 0.45, respectively. The Bland-Altman plots for energy and macronutrients showed that the data points were primarily within the limits of agreement.
CONCLUSION: The Ko-CHENS and KoGES FFQs showed fair-to-moderate comparability, suggesting that the Ko-CHENS FFQ can be used for ranking Korean pregnant women based on their dietary intake levels.},
}
RevDate: 2026-10-16
CmpDate: 2026-10-16
From Prediction to Mechanism: Explainable AI for Plant-Microbiome Multi-Omics Integration and Biological Discovery.
International journal of molecular sciences, 27(19): pii:ijms27198615.
Predicting complex phenotypes from plant-microbiome multi-omics data has advanced significantly with machine learning and deep learning. However, traditional black-box models remain limited by their focus on predictive performance rather than mechanistic biological understanding. To bridge this gap, explainable artificial intelligence (XAI) has emerged as a key framework to transform biological data analysis from correlation mapping to hypothesis-driven discovery. This review synthesizes current advances in XAI methodologies, including post hoc feature attribution techniques and intrinsically interpretable neural architectures, and their applications in plant-microbiome interactions. We highlight how XAI enables multi-scale insights by mapping model predictions to functional genes, metabolic pathways, and microbial interaction networks. Furthermore, we address critical challenges in distinguishing statistical importance from true biological causality and advocate for a closed-loop framework that continuously integrates computational reasoning with wet-lab experimental validation. Finally, we explore future avenues, including biologically informed neural networks, causal AI, and multi-omics knowledge graphs. By facilitating the transition from predictive analytics to biologically interpretable and experimentally testable hypotheses, XAI may contribute to mechanistic discovery in plant-microbiome systems.
Additional Links: PMID-42883861
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@article {pmid42883861,
year = {2026},
author = {Deng, L and Liu, L and Luo, Y and Dai, M and Ye, Z and Xiong, X and Li, Y and Kong, D and Tan, X},
title = {From Prediction to Mechanism: Explainable AI for Plant-Microbiome Multi-Omics Integration and Biological Discovery.},
journal = {International journal of molecular sciences},
volume = {27},
number = {19},
pages = {},
doi = {10.3390/ijms27198615},
pmid = {42883861},
issn = {1422-0067},
support = {42577322//National Natural Science Foundation of China/ ; },
mesh = {Multiomics ; *Plants/microbiology/genetics ; *Artificial Intelligence ; *Microbiota ; Computational Biology/methods ; },
abstract = {Predicting complex phenotypes from plant-microbiome multi-omics data has advanced significantly with machine learning and deep learning. However, traditional black-box models remain limited by their focus on predictive performance rather than mechanistic biological understanding. To bridge this gap, explainable artificial intelligence (XAI) has emerged as a key framework to transform biological data analysis from correlation mapping to hypothesis-driven discovery. This review synthesizes current advances in XAI methodologies, including post hoc feature attribution techniques and intrinsically interpretable neural architectures, and their applications in plant-microbiome interactions. We highlight how XAI enables multi-scale insights by mapping model predictions to functional genes, metabolic pathways, and microbial interaction networks. Furthermore, we address critical challenges in distinguishing statistical importance from true biological causality and advocate for a closed-loop framework that continuously integrates computational reasoning with wet-lab experimental validation. Finally, we explore future avenues, including biologically informed neural networks, causal AI, and multi-omics knowledge graphs. By facilitating the transition from predictive analytics to biologically interpretable and experimentally testable hypotheses, XAI may contribute to mechanistic discovery in plant-microbiome systems.},
}
MeSH Terms:
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Multiomics
*Plants/microbiology/genetics
*Artificial Intelligence
*Microbiota
Computational Biology/methods
RevDate: 2026-10-17
CmpDate: 2026-10-16
The genome sequence of a gelechiid moth, Acompsia subpunctella Svensson, 1966 (Lepidoptera: Gelechiidae).
Wellcome open research, 11:581.
We present a genome assembly from a male specimen of Acompsia subpunctella (gelechiid moth; Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 475.14 megabases and 473.16 megabases. Most of the haplotype 1 assembly (99.91%) was scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.46 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
Additional Links: PMID-42885362
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@article {pmid42885362,
year = {2026},
author = {Mutanen, M and Vallinmäki, M and Kiljunen, N and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of a gelechiid moth, Acompsia subpunctella Svensson, 1966 (Lepidoptera: Gelechiidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {581},
pmid = {42885362},
issn = {2398-502X},
abstract = {We present a genome assembly from a male specimen of Acompsia subpunctella (gelechiid moth; Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 475.14 megabases and 473.16 megabases. Most of the haplotype 1 assembly (99.91%) was scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.46 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-16
CmpDate: 2026-10-16
Physiological-Biochemical Characteristics and Omics Landscape of Drought Tolerance in Chlorella sp. from the Taklamakan Desert of China.
International journal of molecular sciences, 27(19): pii:ijms27198439.
Microalgae endemic to desert ecosystems possess exceptional stress-resistance traits; however, the physiological and molecular drought-adaptation mechanisms of desert-dwelling Chlorella remain largely uncharacterized. Herein, we combined physiological-biochemical assays, ultrastructural observation, transcriptomics and metabolomics to dissect drought responses in Taklamakan-desert-origin Chlorella sp. under polyethylene glycol 6000 (PEG-6000)-simulated mild (10%), moderate (20%), and severe (30%) drought stress, with mechanistic focus on moderate-drought conditions. Moderate drought repressed algal biomass (-26.32%), chlorophyll a (-24.40%), maximum photosystem II quantum yield (Fv/Fm, -16.55%) and effective quantum yield of photosystem II (ΦPSII, -24.35%). Malondialdehyde (MDA) accumulated (+50.69%), alongside elevated activities of superoxide dismutase (SOD, +156.74%) and catalase (CAT, +11.61%). Compatible solutes, including proline, soluble sugars, total protein and total lipid, increased significantly by 39.00%, 39.36%, 26.35% and 23.06%, respectively (p < 0.05). Moderate drought triggered cell swelling, partial cell-wall rupture and prominent enlargement of intracellular starch granules and lipid droplets. Transcriptomic profiling demonstrated up-regulation of transcription-translation and DNA-repair machinery, ATP-binding cassette (ABC) transporters, abscisic acid (ABA)/jasmonic acid (JA) signaling, and biosynthetic pathways for protective metabolites, whereas catabolic pathways and mitogen-activated protein kinase (MAPK) signaling were suppressed. Untargeted metabolomics further validated accumulation of trehalose, stress-protective amino acids, vitamins and functional lipids, while chloroplast-membrane-related metabolites and catabolic intermediates declined. This multi-omics study systematically reveals physiological and molecular regulatory cascades underlying drought tolerance in desert Chlorella sp., providing candidate genes and metabolites to support microalgal resource exploitation for arid-zone applications.
Additional Links: PMID-42883689
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@article {pmid42883689,
year = {2026},
author = {Han, K and Zhou, Y and Tan, R and Fan, K and Ding, M and Li, J and Wu, J and Gao, J and Chen, F},
title = {Physiological-Biochemical Characteristics and Omics Landscape of Drought Tolerance in Chlorella sp. from the Taklamakan Desert of China.},
journal = {International journal of molecular sciences},
volume = {27},
number = {19},
pages = {},
doi = {10.3390/ijms27198439},
pmid = {42883689},
issn = {1422-0067},
support = {31960077//National Natural Science Foundation of China/ ; },
mesh = {*Chlorella/physiology/metabolism/genetics/ultrastructure ; Drought Resistance ; Metabolomics/methods ; China ; Desert Climate ; Droughts ; Stress, Physiological ; Multiomics ; Transcriptome ; Gene Expression Profiling ; Gene Expression Regulation, Plant ; Photosynthesis ; },
abstract = {Microalgae endemic to desert ecosystems possess exceptional stress-resistance traits; however, the physiological and molecular drought-adaptation mechanisms of desert-dwelling Chlorella remain largely uncharacterized. Herein, we combined physiological-biochemical assays, ultrastructural observation, transcriptomics and metabolomics to dissect drought responses in Taklamakan-desert-origin Chlorella sp. under polyethylene glycol 6000 (PEG-6000)-simulated mild (10%), moderate (20%), and severe (30%) drought stress, with mechanistic focus on moderate-drought conditions. Moderate drought repressed algal biomass (-26.32%), chlorophyll a (-24.40%), maximum photosystem II quantum yield (Fv/Fm, -16.55%) and effective quantum yield of photosystem II (ΦPSII, -24.35%). Malondialdehyde (MDA) accumulated (+50.69%), alongside elevated activities of superoxide dismutase (SOD, +156.74%) and catalase (CAT, +11.61%). Compatible solutes, including proline, soluble sugars, total protein and total lipid, increased significantly by 39.00%, 39.36%, 26.35% and 23.06%, respectively (p < 0.05). Moderate drought triggered cell swelling, partial cell-wall rupture and prominent enlargement of intracellular starch granules and lipid droplets. Transcriptomic profiling demonstrated up-regulation of transcription-translation and DNA-repair machinery, ATP-binding cassette (ABC) transporters, abscisic acid (ABA)/jasmonic acid (JA) signaling, and biosynthetic pathways for protective metabolites, whereas catabolic pathways and mitogen-activated protein kinase (MAPK) signaling were suppressed. Untargeted metabolomics further validated accumulation of trehalose, stress-protective amino acids, vitamins and functional lipids, while chloroplast-membrane-related metabolites and catabolic intermediates declined. This multi-omics study systematically reveals physiological and molecular regulatory cascades underlying drought tolerance in desert Chlorella sp., providing candidate genes and metabolites to support microalgal resource exploitation for arid-zone applications.},
}
MeSH Terms:
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*Chlorella/physiology/metabolism/genetics/ultrastructure
Drought Resistance
Metabolomics/methods
China
Desert Climate
Droughts
Stress, Physiological
Multiomics
Transcriptome
Gene Expression Profiling
Gene Expression Regulation, Plant
Photosynthesis
RevDate: 2026-10-16
CmpDate: 2026-10-16
Omics approaches to unveil biotic stress responses in olive: current knowledge and the future.
Journal of experimental botany, 77(19):6317-6333.
Olive (Olea europaea) is a perennial crop of major economic, cultural, and ecological importance in the Mediterranean basin and worldwide, yet its productivity and sustainability are increasingly constrained by diverse pathogens, including fungi, bacteria, and viruses. The primary objective of this review is to critically evaluate how recent omics advances have improved our understanding of olive immune regulation under biotic stress, and to clarify why an integrative systems-level multi-omics perspective is essential for developing durable disease management strategies. By synthesizing genomic, transcriptomic, and emerging proteomic, microbiomic, and metabolomic studies, we show that olive defense relies on tightly coordinated transcriptional reprogramming, hormone crosstalk, metabolic remodeling, and structural barriers, within a multilayered immune framework, supported by expanding genomic resources and resistance-associated loci in cultivated and wild germplasm. However, the review also identifies major limitations that currently hinder progress, including a predominant transcript-centric focus, limited proteomic, microbiomic, and metabolomic depth, insufficient attention to post-translational and epigenomic regulation, underdeveloped pan-genomic frameworks, and scarce functional validation using genome-editing approaches. We conclude that integrating multilayered omics with functional genomics and pan-genomics is crucial for translating molecular insights into resilient cultivars and sustainable disease management, and we outline key priority directions for future research and breeding applications.
Additional Links: PMID-42417423
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@article {pmid42417423,
year = {2026},
author = {Balan, AS and Giovino, A and Caruso, T and Marchese, A},
title = {Omics approaches to unveil biotic stress responses in olive: current knowledge and the future.},
journal = {Journal of experimental botany},
volume = {77},
number = {19},
pages = {6317-6333},
doi = {10.1093/jxb/erag337},
pmid = {42417423},
issn = {1460-2431},
support = {419161//MIPAAF/ ; },
mesh = {*Olea/genetics/physiology/metabolism/immunology ; Multiomics ; *Stress, Physiological ; *Genomics ; Proteomics ; Metabolomics ; },
abstract = {Olive (Olea europaea) is a perennial crop of major economic, cultural, and ecological importance in the Mediterranean basin and worldwide, yet its productivity and sustainability are increasingly constrained by diverse pathogens, including fungi, bacteria, and viruses. The primary objective of this review is to critically evaluate how recent omics advances have improved our understanding of olive immune regulation under biotic stress, and to clarify why an integrative systems-level multi-omics perspective is essential for developing durable disease management strategies. By synthesizing genomic, transcriptomic, and emerging proteomic, microbiomic, and metabolomic studies, we show that olive defense relies on tightly coordinated transcriptional reprogramming, hormone crosstalk, metabolic remodeling, and structural barriers, within a multilayered immune framework, supported by expanding genomic resources and resistance-associated loci in cultivated and wild germplasm. However, the review also identifies major limitations that currently hinder progress, including a predominant transcript-centric focus, limited proteomic, microbiomic, and metabolomic depth, insufficient attention to post-translational and epigenomic regulation, underdeveloped pan-genomic frameworks, and scarce functional validation using genome-editing approaches. We conclude that integrating multilayered omics with functional genomics and pan-genomics is crucial for translating molecular insights into resilient cultivars and sustainable disease management, and we outline key priority directions for future research and breeding applications.},
}
MeSH Terms:
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*Olea/genetics/physiology/metabolism/immunology
Multiomics
*Stress, Physiological
*Genomics
Proteomics
Metabolomics
RevDate: 2026-10-15
CmpDate: 2026-10-13
The genome sequence of a leaf-roller moth, Argyroploce noricana (Herrich-Schaffer, 1851) (Lepidoptera: Tortricidae).
Wellcome open research, 11:637.
We present a genome assembly from a male specimen of Argyroploce noricana (leaf-roller moth; Arthropoda; Insecta; Lepidoptera; Tortricidae). The assembly contains two haplotypes with total lengths of 799.31 megabases and 800.07 megabases. Most of haplotype 1 (99.7%) and haplotype 2 (99.8%) are scaffolded into 26 chromosomal pseudomolecules, including the Z sex chromosome. Hi-C data were used to phase the assembly, and both haplotypes were assembled to chromosome level. The mitochondrial genome has also been assembled, with a length of 16.57 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
Additional Links: PMID-42865367
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@article {pmid42865367,
year = {2026},
author = {Mutanen, M and Kiljunen, N and Vallinmäki, M and Huemer, P and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of a leaf-roller moth, Argyroploce noricana (Herrich-Schaffer, 1851) (Lepidoptera: Tortricidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {637},
pmid = {42865367},
issn = {2398-502X},
support = {/WT_/Wellcome Trust/United Kingdom ; },
abstract = {We present a genome assembly from a male specimen of Argyroploce noricana (leaf-roller moth; Arthropoda; Insecta; Lepidoptera; Tortricidae). The assembly contains two haplotypes with total lengths of 799.31 megabases and 800.07 megabases. Most of haplotype 1 (99.7%) and haplotype 2 (99.8%) are scaffolded into 26 chromosomal pseudomolecules, including the Z sex chromosome. Hi-C data were used to phase the assembly, and both haplotypes were assembled to chromosome level. The mitochondrial genome has also been assembled, with a length of 16.57 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-16
CmpDate: 2026-10-16
The influence of cell morphology on the dynamics and stability of model bacterial communities.
PLoS computational biology, 22(10):e1014874 pii:PCOMPBIOL-D-26-00433.
Understanding how structures arise in microbial communities remains an outstanding challenge in bacterial ecology. When replicating within dense and confined environments, bacterial populations may collectively self-organize as a result of mechanical interactions. We previously observed that model dual-populations of bacteria, colonizing open-ended microchannels, either quickly fixate to a single population or segregate into long-lived, coexisting populations. This latter quasi-stability results from the alignment of bacteria into lanes, forcing cells to grow toward the open ends of the channel, with inter-lane invasion events driving the boundary dynamics between populations. Here we apply agent-based (AB) simulations to explore the boundary dynamics between dual-bacterial populations of varying morphology and division rate. We find that the simulated boundary dynamics are well-described by a simple drift-diffusion model, which enables us to estimate the mean time to fixation within competitive scenarios where the fixation time is difficult to access by AB simulations. Coccus-like cells display a competitive advantage over bacillus cells as they can more effectively invade and ultimately fixate, while coexisting populations of bacillus cells are "effectively" stable. And while faster-dividing cells should have a selective advantage, their morphology determines if this advantage drives fixation or acts as a defensive strategy to maintain their population. These findings highlight the critical role that cell morphology and mechanics play in shaping bacterial communities.
Additional Links: PMID-42868198
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@article {pmid42868198,
year = {2026},
author = {Lim, IX and Halabeya, F and Milstein, JN},
title = {The influence of cell morphology on the dynamics and stability of model bacterial communities.},
journal = {PLoS computational biology},
volume = {22},
number = {10},
pages = {e1014874},
doi = {10.1371/journal.pcbi.1014874},
pmid = {42868198},
issn = {1553-7358},
mesh = {*Models, Biological ; Computer Simulation ; *Bacterial Physiological Phenomena ; Computational Biology ; *Bacteria/cytology ; },
abstract = {Understanding how structures arise in microbial communities remains an outstanding challenge in bacterial ecology. When replicating within dense and confined environments, bacterial populations may collectively self-organize as a result of mechanical interactions. We previously observed that model dual-populations of bacteria, colonizing open-ended microchannels, either quickly fixate to a single population or segregate into long-lived, coexisting populations. This latter quasi-stability results from the alignment of bacteria into lanes, forcing cells to grow toward the open ends of the channel, with inter-lane invasion events driving the boundary dynamics between populations. Here we apply agent-based (AB) simulations to explore the boundary dynamics between dual-bacterial populations of varying morphology and division rate. We find that the simulated boundary dynamics are well-described by a simple drift-diffusion model, which enables us to estimate the mean time to fixation within competitive scenarios where the fixation time is difficult to access by AB simulations. Coccus-like cells display a competitive advantage over bacillus cells as they can more effectively invade and ultimately fixate, while coexisting populations of bacillus cells are "effectively" stable. And while faster-dividing cells should have a selective advantage, their morphology determines if this advantage drives fixation or acts as a defensive strategy to maintain their population. These findings highlight the critical role that cell morphology and mechanics play in shaping bacterial communities.},
}
MeSH Terms:
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*Models, Biological
Computer Simulation
*Bacterial Physiological Phenomena
Computational Biology
*Bacteria/cytology
RevDate: 2026-10-13
Quantifying the drivers of ozone formation using localized photochemical reactivity and double machine learning.
Environmental research pii:S0013-9351(26)02172-9 [Epub ahead of print].
Surface ozone (O3) pollution remains severe in many Chinese cities despite declining precursor emissions, reflecting nonlinear interactions among emissions, meteorology, chemistry, and transport. Here, we integrated hourly observations from Yuncheng in the Fenwei Plain during 2020-2022 with a localized observation-constrained box model to develop a photochemically constrained double machine learning (DML) framework. From 2020 to 2022, the annual mean O3 concentration in Yuncheng increased from 76.2 to 79.9μg m[-3]. Compared with clean days, O3-polluted days had stronger southeasterly winds, higher temperatures, lower humidity. Box-model calculations indicated that O3 formation in Yuncheng was VOC-limited during the pollution season. Using MCM v3.3.1, we derived a localized maximum incremental reactivity scale for Yuncheng (MIR-YC), with reactivity decreasing in the order isoprene > anthropogenic alkenes > aromatics > oxygenated VOCs > alkanes. The resulting localized ozone formation potentials were subsequently used in place of measured VOC concentrations to constrain the machine-learning analysis. The optimized random forest model achieved a test R[2] of 0.923, and SHAP analysis attributed 44.6% and 26.4% of predictive importance to local precursors and photochemical drivers, respectively. DML then quantified conditional marginal responses beyond predictive attribution, associating a 1 °C temperature increase with a 4.04μg m[-3] increase in O3 after adjustment for observed covariates. This integrated framework links localized chemical sensitivity with observation-based atmospheric responses, providing a quantitative basis for locally tailored VOC-NOx control strategies.
Additional Links: PMID-42869359
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@article {pmid42869359,
year = {2026},
author = {Song, M and Liu, Y and Ru, X and Yang, H and Qu, Y and Qin, K and Qiu, Y and Zhang, G and Liu, X},
title = {Quantifying the drivers of ozone formation using localized photochemical reactivity and double machine learning.},
journal = {Environmental research},
volume = {},
number = {},
pages = {125841},
doi = {10.1016/j.envres.2026.125841},
pmid = {42869359},
issn = {1096-0953},
abstract = {Surface ozone (O3) pollution remains severe in many Chinese cities despite declining precursor emissions, reflecting nonlinear interactions among emissions, meteorology, chemistry, and transport. Here, we integrated hourly observations from Yuncheng in the Fenwei Plain during 2020-2022 with a localized observation-constrained box model to develop a photochemically constrained double machine learning (DML) framework. From 2020 to 2022, the annual mean O3 concentration in Yuncheng increased from 76.2 to 79.9μg m[-3]. Compared with clean days, O3-polluted days had stronger southeasterly winds, higher temperatures, lower humidity. Box-model calculations indicated that O3 formation in Yuncheng was VOC-limited during the pollution season. Using MCM v3.3.1, we derived a localized maximum incremental reactivity scale for Yuncheng (MIR-YC), with reactivity decreasing in the order isoprene > anthropogenic alkenes > aromatics > oxygenated VOCs > alkanes. The resulting localized ozone formation potentials were subsequently used in place of measured VOC concentrations to constrain the machine-learning analysis. The optimized random forest model achieved a test R[2] of 0.923, and SHAP analysis attributed 44.6% and 26.4% of predictive importance to local precursors and photochemical drivers, respectively. DML then quantified conditional marginal responses beyond predictive attribution, associating a 1 °C temperature increase with a 4.04μg m[-3] increase in O3 after adjustment for observed covariates. This integrated framework links localized chemical sensitivity with observation-based atmospheric responses, providing a quantitative basis for locally tailored VOC-NOx control strategies.},
}
RevDate: 2026-10-14
CmpDate: 2026-10-14
Digital twins for personalized management of opioid use disorder: A future outlook.
Journal of opioid management, 22(5):445-457.
INTRODUCTION: The opioid crisis, affecting over 16 million individuals globally and causing approximately 450,000 deaths annually, underscores the urgent need for personalized treatment approaches for opioid use disorder (OUD). Current treatments, such as medication-assisted therapy, suffer from low retention rates and variable responses due to individual differences.
METHODS: This study proposes a digital twin framework, integrating genetic profiles, eg, OPRM1 variants, electronic health records, ecological momentary assessments, and real-time physiological data from wearables. Machine learning and pharmacokinetic modeling are employed to develop patient-specific models, with validation planned across short-term (2 years), medium-term (5 years), and long-term (10 years) phases. Proposed framework: The framework enables personalized dosing, relapse risk prediction, and tailored behavioral interventions by synthesizing multimodal data into dynamic virtual models. It leverages cloud-based platforms for scalability and complies with Health Insurance Portability and Accountability Act and General Data Protection Regulation for data privacy.
DISCUSSION: The framework addresses OUD treatment gaps by improving retention and reducing overdose risks, eg, 87,000 overdose deaths in the United States (US) in 2024. It supports public health by optimizing resource allocation for the 2 million prescription-related and 600,000 heroin-related OUD cases in the US. Challenges include data integration, clinical validation, and equitable access.
CONCLUSION: Digital twins offer a transformative approach to OUD management, with future research needed to validate and integrate this technology into healthcare systems.
Additional Links: PMID-42873153
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PubMed:
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@article {pmid42873153,
year = {2026},
author = {Soltani, M and Karami-Mohajeri, S and Aghaei-Afshar, A and Oghabian, Z and Falahatipour, SK and Falahati-Pour, SK and Mavaei, M and Ghasemloo, A},
title = {Digital twins for personalized management of opioid use disorder: A future outlook.},
journal = {Journal of opioid management},
volume = {22},
number = {5},
pages = {445-457},
doi = {10.5055/jom.0987},
pmid = {42873153},
issn = {1551-7489},
mesh = {Humans ; *Opioid-Related Disorders/genetics/therapy/diagnosis ; *Precision Medicine/trends/methods ; Digital Health ; Electronic Health Records ; Analgesics, Opioid/pharmacokinetics/adverse effects ; *Patient-Specific Modeling ; Machine Learning ; },
abstract = {INTRODUCTION: The opioid crisis, affecting over 16 million individuals globally and causing approximately 450,000 deaths annually, underscores the urgent need for personalized treatment approaches for opioid use disorder (OUD). Current treatments, such as medication-assisted therapy, suffer from low retention rates and variable responses due to individual differences.
METHODS: This study proposes a digital twin framework, integrating genetic profiles, eg, OPRM1 variants, electronic health records, ecological momentary assessments, and real-time physiological data from wearables. Machine learning and pharmacokinetic modeling are employed to develop patient-specific models, with validation planned across short-term (2 years), medium-term (5 years), and long-term (10 years) phases. Proposed framework: The framework enables personalized dosing, relapse risk prediction, and tailored behavioral interventions by synthesizing multimodal data into dynamic virtual models. It leverages cloud-based platforms for scalability and complies with Health Insurance Portability and Accountability Act and General Data Protection Regulation for data privacy.
DISCUSSION: The framework addresses OUD treatment gaps by improving retention and reducing overdose risks, eg, 87,000 overdose deaths in the United States (US) in 2024. It supports public health by optimizing resource allocation for the 2 million prescription-related and 600,000 heroin-related OUD cases in the US. Challenges include data integration, clinical validation, and equitable access.
CONCLUSION: Digital twins offer a transformative approach to OUD management, with future research needed to validate and integrate this technology into healthcare systems.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Opioid-Related Disorders/genetics/therapy/diagnosis
*Precision Medicine/trends/methods
Digital Health
Electronic Health Records
Analgesics, Opioid/pharmacokinetics/adverse effects
*Patient-Specific Modeling
Machine Learning
RevDate: 2026-10-14
CmpDate: 2026-10-14
Cryptic microheterogeneity of the casing-layer microbiome and metabolome is associated with primordium fate in Phallus rubrovolvatus.
Fungal biology, 130(7):101864.
Commercial cultivation of Phallus rubrovolvatus relies on casing layers, yet yields remain unstable, with primordium development varying among individual microsites. This cryptic microheterogeneity is masked by conventional bulk sampling, limiting insight into casing-layer performance. Here, we combined phenotype-guided back-tracing with multi-omics to characterize microecological signatures associated with primordium fate. We identified two contrasting ecological regimes associated with reproductive outcomes. Productive microsites were characterized by a "Cooperative state" enriched in oligotrophic bacteria (e.g., Hyphomicrobium) and basidiomycetes (e.g., Clathrus columnatus). Productive microsites also showed lower available potassium (K[+]) and elevated catalase activity. Conversely, non-productive microsites were characterized by a Rhizopus-dominated "Disruptive state". This state was associated with elevated urease activity, lower catalase activity, and stress-associated metagenomic functional signatures. Overall, primordium fate was associated with distinct local microbial, functional, and metabolic configurations that were not fully explained by bulk physicochemical properties. We propose the "Cooperative vs. Disruptive" model as a conceptual framework and identify candidate microbial and metabolic features for future validation in microbiome-informed cultivation management.
Additional Links: PMID-42875131
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@article {pmid42875131,
year = {2026},
author = {Kang, C and Zheng, X and Liu, Z and Wang, W and Zeng, W and He, Y and Huang, J and Nie, W and Wang, J and Wang, F},
title = {Cryptic microheterogeneity of the casing-layer microbiome and metabolome is associated with primordium fate in Phallus rubrovolvatus.},
journal = {Fungal biology},
volume = {130},
number = {7},
pages = {101864},
doi = {10.1016/j.funbio.2026.101864},
pmid = {42875131},
issn = {1878-6146},
mesh = {*Microbiota ; *Metabolome ; *Agaricales/growth & development/metabolism ; Bacteria/classification/genetics/metabolism/isolation & purification ; Multiomics ; },
abstract = {Commercial cultivation of Phallus rubrovolvatus relies on casing layers, yet yields remain unstable, with primordium development varying among individual microsites. This cryptic microheterogeneity is masked by conventional bulk sampling, limiting insight into casing-layer performance. Here, we combined phenotype-guided back-tracing with multi-omics to characterize microecological signatures associated with primordium fate. We identified two contrasting ecological regimes associated with reproductive outcomes. Productive microsites were characterized by a "Cooperative state" enriched in oligotrophic bacteria (e.g., Hyphomicrobium) and basidiomycetes (e.g., Clathrus columnatus). Productive microsites also showed lower available potassium (K[+]) and elevated catalase activity. Conversely, non-productive microsites were characterized by a Rhizopus-dominated "Disruptive state". This state was associated with elevated urease activity, lower catalase activity, and stress-associated metagenomic functional signatures. Overall, primordium fate was associated with distinct local microbial, functional, and metabolic configurations that were not fully explained by bulk physicochemical properties. We propose the "Cooperative vs. Disruptive" model as a conceptual framework and identify candidate microbial and metabolic features for future validation in microbiome-informed cultivation management.},
}
MeSH Terms:
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hide MeSH Terms
*Microbiota
*Metabolome
*Agaricales/growth & development/metabolism
Bacteria/classification/genetics/metabolism/isolation & purification
Multiomics
RevDate: 2026-10-16
CmpDate: 2026-10-15
The genome sequence of the Corsican Dappled White, Euchloe insularis (Staudinger, 1861) (Lepidoptera: Pieridae).
Wellcome open research, 11:665.
We present a genome assembly from a female specimen of Euchloe insularis (Corsican Dappled White; Arthropoda; Insecta; Lepidoptera; Pieridae). The assembly contains two haplotypes with total lengths of 372.27 megabases and 351.06 megabases. Most of the haplotype 1 assembly (99.86%) was scaffolded into 32 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.27 kilobases. Gene annotation of this assembly by Ensembl identified 12,321 protein-coding genes. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
Additional Links: PMID-42876444
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@article {pmid42876444,
year = {2026},
author = {Joron, M and Elias, M and Linke, D and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of the Corsican Dappled White, Euchloe insularis (Staudinger, 1861) (Lepidoptera: Pieridae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {665},
pmid = {42876444},
issn = {2398-502X},
abstract = {We present a genome assembly from a female specimen of Euchloe insularis (Corsican Dappled White; Arthropoda; Insecta; Lepidoptera; Pieridae). The assembly contains two haplotypes with total lengths of 372.27 megabases and 351.06 megabases. Most of the haplotype 1 assembly (99.86%) was scaffolded into 32 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.27 kilobases. Gene annotation of this assembly by Ensembl identified 12,321 protein-coding genes. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-15
CmpDate: 2026-10-15
Interpersonal value regulates infection-risky social contact across 61 societies.
Proceedings of the National Academy of Sciences of the United States of America, 123(42):e2615739123.
Interpersonal contact is essential for cooperation and care, but it also provides a route for pathogen transmission between individuals. Hence, a key challenge for social organisms involves maintaining beneficial social contact while also limiting exposure to infection risks. Existing proposals suggest that this trade-off is guided by the interpersonal value of specific social targets. In addition, ecological and cultural factors, including historical pathogen prevalence, individualism-collectivism, tightness-looseness, and relational mobility, might also shape how people avoid pathogens. To test whether and how infection-risky social contact varies with individual-level interpersonal value and these societal-level factors, we collected data from 47,756 participants across 61 societies. Participants were randomly assigned to picture a social target - either a friend, acquaintance, stranger, or enemy. They then rated their comfort with infection-risky contact with that target (e.g., drinking from the same water bottle) and whether they would touch the target when greeting them. In all societies, participants were more comfortable with infection-risky contact and more likely to engage in physical contact during greetings with targets of higher interpersonal value. Such associations varied only modestly across societies. Notably, the associations between infection-risky contact and societal-level factors depended on target interpersonal value and were concentrated among high-value targets-contact was lower where historical pathogen prevalence and tightness were greater and higher where individualism and relational mobility were greater. These findings suggest that infection-risky contact is primarily guided by the value of social targets, with ecological and cultural factors playing a lesser role.
Additional Links: PMID-42879482
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@article {pmid42879482,
year = {2026},
author = {Sun, H and Spadaro, G and Pelica, S and Kamiloğlu, RG and Abrahams, L and Ackerman, JM and Adams, S and Al-Shawaf, L and Alvergne, A and Amponsah, B and Andersen, N and Antfolk, J and Atamtürk Duyar, D and Bai, S and Barbato, MT and Barbosa, S and Barclay, P and Becker, DV and de Souza, BB and Boggio, PS and Böhm, R and Boonyasiriwat, W and Camperio Ciani, AS and Can, AR and Case, TI and Chan, KQ and Contreras-Huerta, LS and Conway, P and Chevallier, C and Côté, É and Dale, SP and Delgado Espinoza, F and Dlouhá, D and Duyar, I and Elbæk, CT and Fan, Q and Fernández, AM and Ferreira, DCS and Fessler, DMT and Flores-Kanter, PE and Frankowska, N and Freitas, AL and Fülöp, M and Gallucci, M and Garfield, ZH and Garrido, MV and Gecer, E and González-Portilla, M and Grigoryev, D and Ha, MT and Hamdaoui, B and Hamid, SN and Hansson, LS and Havlíček, J and Hilbig, BE and Hohm, I and Holka, S and Hong, M and Horita, Y and Hsu, HP and Inbar, Y and Ishii, K and James, OM and Jarmakowski, T and Ji, T and Jiménez-Leal, W and Kamble, S and Kaňková, Š and Karabeliova, S and Kasali, HN and Kim, JP and Kiyonari, T and Kliatchko, JMR and Köbis, N and Kocsor, F and Kordsmeyer, TL and Kupfer, TR and Cuesta, LL and Leong, CXR and Lewis, DMG and Lieberman, D and Liu, H and López-Morales, H and López-Calle, C and Lund, IO and Macchiavello, F and Marchenko, O and Marcinkowska, UM and Marcu, GM and Meskó, N and Mishra, S and Mitev, K and Miura, A and Monge Rodríguez, FS and Morello, LY and Mota, BEF and Murray, DR and Obialo, FK and Ojedokun, O and Olsson, MJ and Palomo-Vélez, G and Panizza, F and Pantaleão, FN and Penke, L and Penn, D and Perinetti, A and Prodromitis, G and Putz, Á and Quiroga-Garza, A and Reddy, NN and Reyes, MES and Rojas-Thomas, F and Rothschild, R and Sabree, K and Sahli, FZ and Sarabian, C and Sarmento, A and See, YHM and Shavega, TJ and Shebani, Z and Sianipar, A and Singh, D and Sojoudi, S and Soler-Anguiano, FL and Soveri, A and Stevenson, RJ and Stewart-Williams, S and Suay, F and Suh, EM and Kambere, JS and Szepsenwol, O and Tadmor, CT and Tager-Shafrir, T and Tavakoli-Berg, E and Tewari, S and Tognetti, A and Tsitseli, A and Uriarte, IL and Heel, MV and van Leeuwen, F and Ventura, A and Wang, J and Wang, XT and Watts, J and Wu, J and Yeh, SL and Yau, EK and Yeung, VWL and Zickfeld, JH and Tybur, JM},
title = {Interpersonal value regulates infection-risky social contact across 61 societies.},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
volume = {123},
number = {42},
pages = {e2615739123},
doi = {10.1073/pnas.2615739123},
pmid = {42879482},
issn = {1091-6490},
support = {ERC-2021-COG NONPHARM 101045225//Horizon Europe Research Council Grant/ ; 202208120019//China Scholarship Council (CSC)/ ; NKFIH-OTKA-K 135963//National Research, Development and Innovation Office/ ; IG/EDU/PSYC/25/03//Sultan Qaboos University (SQU)/ ; NSTC 113-2410-H-002-252-MY3//National Science and Technology Council (NSTC)/ ; },
mesh = {Humans ; *Interpersonal Relations ; Female ; *Social Behavior ; Social Group ; Male ; Adult ; *Social Values ; },
abstract = {Interpersonal contact is essential for cooperation and care, but it also provides a route for pathogen transmission between individuals. Hence, a key challenge for social organisms involves maintaining beneficial social contact while also limiting exposure to infection risks. Existing proposals suggest that this trade-off is guided by the interpersonal value of specific social targets. In addition, ecological and cultural factors, including historical pathogen prevalence, individualism-collectivism, tightness-looseness, and relational mobility, might also shape how people avoid pathogens. To test whether and how infection-risky social contact varies with individual-level interpersonal value and these societal-level factors, we collected data from 47,756 participants across 61 societies. Participants were randomly assigned to picture a social target - either a friend, acquaintance, stranger, or enemy. They then rated their comfort with infection-risky contact with that target (e.g., drinking from the same water bottle) and whether they would touch the target when greeting them. In all societies, participants were more comfortable with infection-risky contact and more likely to engage in physical contact during greetings with targets of higher interpersonal value. Such associations varied only modestly across societies. Notably, the associations between infection-risky contact and societal-level factors depended on target interpersonal value and were concentrated among high-value targets-contact was lower where historical pathogen prevalence and tightness were greater and higher where individualism and relational mobility were greater. These findings suggest that infection-risky contact is primarily guided by the value of social targets, with ecological and cultural factors playing a lesser role.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Interpersonal Relations
Female
*Social Behavior
Social Group
Male
Adult
*Social Values
RevDate: 2026-10-15
CmpDate: 2026-10-15
Evaluating Large Language Model-Derived Outputs as Psychological Measures: A Five-Domain Psychometric Framework With Application to Daily Stress.
Journal of medical Internet research, 28:e102768 pii:v28i1e102768.
BACKGROUND: Large language models (LLMs) are increasingly used to quantify psychological constructs from natural language, yet their outputs are typically evaluated only as predictions of an external label. When that label is itself imperfect, optimizing prediction conflates label agreement with construct measurement. No study has applied a multidomain measurement-oriented evaluation to LLM-derived psychological outputs.
OBJECTIVE: We applied 5 psychometric evaluation domains to LLM-derived outputs to test whether measurement-oriented evaluation surfaces properties that prediction-oriented evaluation does not: extraction repeatability, convergent validity with a lexicon-based tool, ecological concurrent validity decomposed into within-person and between-person components, incremental value in a 4-arm comparison with that tool, and method-blinded expert evaluation with structured error attribution.
METHODS: Thirteen linguistic features were extracted by GPT-5.2 (OpenAI) from 3556 person-days of daily voice narratives collected from 279 call center workers over 15 days via ecological momentary assessment. Features were evaluated across the 5 domains, with Linguistic Inquiry and Word Count, version 22, as the lexicon-based comparator. Multimodel robustness was assessed by re-extracting all features with Google Gemini 2.5 Flash.
RESULTS: Features showed high repeatability (mean intraclass correlation coefficient=0.987), construct-dependent convergent validity (Spearman ρ=0.08 to 0.79), and within-person tracking of same-day stress (negative emotion β=0.68). In a 4-arm comparison (baseline, baseline plus lexicon features, baseline plus LLM-derived features, and baseline plus both), LLM features increased explained variance in daily stress from 13.2% to 30.4%, versus 16.9% for the lexicon-based comparator. Among transcripts sampled for maximal method discordance, experts preferred LLM-derived profiles in 83.7% (261/312) of blinded decisions. Error analysis showed that 53% (35/66) of false-positive attributions reflected reference-label limitations, not model failures. Re-extraction with Google Gemini 2.5 Flash replicated key properties (person-level r=0.94). Three phenomena were visible under measurement-oriented evaluation that prediction-oriented evaluation does not typically examine: divergence between within-person and between-person effects, reference-label limitations as a dominant error source, and moderation of feature meaning by individual differences.
CONCLUSIONS: Prediction metrics alone are insufficient for evaluating LLM-derived psychological measures. Measurement-oriented evaluation revealed properties, including level-dependent effects and asymmetric error attribution, that have direct implications for how LLM-based assessment studies interpret their results. For clinical use, the measure is a complement to existing screening instruments for longitudinal monitoring, not a stand-alone diagnostic.
Additional Links: PMID-42879778
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PubMed:
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@article {pmid42879778,
year = {2026},
author = {Jeong, I and Park, S and Jhon, M and Kim, DK and Park, JH and Kim, Y and Jang, M and Kim, JM and Kim, JW and Lee, H},
title = {Evaluating Large Language Model-Derived Outputs as Psychological Measures: A Five-Domain Psychometric Framework With Application to Daily Stress.},
journal = {Journal of medical Internet research},
volume = {28},
number = {},
pages = {e102768},
doi = {10.2196/102768},
pmid = {42879778},
issn = {1438-8871},
mesh = {Humans ; Large Language Models ; *Psychometrics/methods ; *Stress, Psychological/psychology ; },
abstract = {BACKGROUND: Large language models (LLMs) are increasingly used to quantify psychological constructs from natural language, yet their outputs are typically evaluated only as predictions of an external label. When that label is itself imperfect, optimizing prediction conflates label agreement with construct measurement. No study has applied a multidomain measurement-oriented evaluation to LLM-derived psychological outputs.
OBJECTIVE: We applied 5 psychometric evaluation domains to LLM-derived outputs to test whether measurement-oriented evaluation surfaces properties that prediction-oriented evaluation does not: extraction repeatability, convergent validity with a lexicon-based tool, ecological concurrent validity decomposed into within-person and between-person components, incremental value in a 4-arm comparison with that tool, and method-blinded expert evaluation with structured error attribution.
METHODS: Thirteen linguistic features were extracted by GPT-5.2 (OpenAI) from 3556 person-days of daily voice narratives collected from 279 call center workers over 15 days via ecological momentary assessment. Features were evaluated across the 5 domains, with Linguistic Inquiry and Word Count, version 22, as the lexicon-based comparator. Multimodel robustness was assessed by re-extracting all features with Google Gemini 2.5 Flash.
RESULTS: Features showed high repeatability (mean intraclass correlation coefficient=0.987), construct-dependent convergent validity (Spearman ρ=0.08 to 0.79), and within-person tracking of same-day stress (negative emotion β=0.68). In a 4-arm comparison (baseline, baseline plus lexicon features, baseline plus LLM-derived features, and baseline plus both), LLM features increased explained variance in daily stress from 13.2% to 30.4%, versus 16.9% for the lexicon-based comparator. Among transcripts sampled for maximal method discordance, experts preferred LLM-derived profiles in 83.7% (261/312) of blinded decisions. Error analysis showed that 53% (35/66) of false-positive attributions reflected reference-label limitations, not model failures. Re-extraction with Google Gemini 2.5 Flash replicated key properties (person-level r=0.94). Three phenomena were visible under measurement-oriented evaluation that prediction-oriented evaluation does not typically examine: divergence between within-person and between-person effects, reference-label limitations as a dominant error source, and moderation of feature meaning by individual differences.
CONCLUSIONS: Prediction metrics alone are insufficient for evaluating LLM-derived psychological measures. Measurement-oriented evaluation revealed properties, including level-dependent effects and asymmetric error attribution, that have direct implications for how LLM-based assessment studies interpret their results. For clinical use, the measure is a complement to existing screening instruments for longitudinal monitoring, not a stand-alone diagnostic.},
}
MeSH Terms:
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Humans
Large Language Models
*Psychometrics/methods
*Stress, Psychological/psychology
RevDate: 2026-10-16
Dynamic Coordination Microenvironments of Fe Single-Atom Catalysts in Advanced Oxidation Processes: From Working-State Evolution to Pathway-Selective Regulation.
Molecules (Basel, Switzerland), 31(19): pii:molecules31193491.
Iron single-atom catalysts (Fe-SACs) offer an atomically defined platform for peroxide-based advanced oxidation, yet their reactivity is still frequently rationalized using coordination structures measured only before or after catalysis. Such static descriptors identify precursor sites but do not necessarily resolve the Fe configurations that carry turnover. This Review establishes a dynamic coordination framework that distinguishes resting structures, reaction-induced working states, and irreversible deactivation products. It examines how first-shell coordination, axial ligation, extended microenvironments, neighboring sites, and interfacial solvation govern the formation and interconversion of peroxide-bound, hydroxy, Fe-oxo, and electronically coupled Fe-oxidant states. Radical, high-valent Fe-oxo, singlet-oxygen, and interfacial electron-transfer pathways are treated as competing catalytic fluxes emerging from a shared working-state landscape rather than as fixed attributes of individual Fe-Nx motifs. Particular emphasis is placed on the evidence required to identify kinetically competent intermediates, distinguish reversible coordination adaptation from structural escape, and connect working-state populations with regeneration and lifetime. Coordination and microenvironment engineering strategies are then evaluated according to their ability to control pathway selectivity without compromising site recoverability. Covalent organic frameworks are discussed as molecularly programmable platforms that can integrate Fe-site definition, charge transport, solvation, and oxidant supply. The resulting structure-state-pathway-lifetime framework advances Fe-SAC design from static activity correlations toward predictive control of catalytic trajectories under realistic operating conditions.
Additional Links: PMID-42883262
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@article {pmid42883262,
year = {2026},
author = {Li, S and Li, S and Zheng, H and Lou, X},
title = {Dynamic Coordination Microenvironments of Fe Single-Atom Catalysts in Advanced Oxidation Processes: From Working-State Evolution to Pathway-Selective Regulation.},
journal = {Molecules (Basel, Switzerland)},
volume = {31},
number = {19},
pages = {},
doi = {10.3390/molecules31193491},
pmid = {42883262},
issn = {1420-3049},
support = {Y202558733//Department of Education of Zhejiang Province/ ; },
abstract = {Iron single-atom catalysts (Fe-SACs) offer an atomically defined platform for peroxide-based advanced oxidation, yet their reactivity is still frequently rationalized using coordination structures measured only before or after catalysis. Such static descriptors identify precursor sites but do not necessarily resolve the Fe configurations that carry turnover. This Review establishes a dynamic coordination framework that distinguishes resting structures, reaction-induced working states, and irreversible deactivation products. It examines how first-shell coordination, axial ligation, extended microenvironments, neighboring sites, and interfacial solvation govern the formation and interconversion of peroxide-bound, hydroxy, Fe-oxo, and electronically coupled Fe-oxidant states. Radical, high-valent Fe-oxo, singlet-oxygen, and interfacial electron-transfer pathways are treated as competing catalytic fluxes emerging from a shared working-state landscape rather than as fixed attributes of individual Fe-Nx motifs. Particular emphasis is placed on the evidence required to identify kinetically competent intermediates, distinguish reversible coordination adaptation from structural escape, and connect working-state populations with regeneration and lifetime. Coordination and microenvironment engineering strategies are then evaluated according to their ability to control pathway selectivity without compromising site recoverability. Covalent organic frameworks are discussed as molecularly programmable platforms that can integrate Fe-site definition, charge transport, solvation, and oxidant supply. The resulting structure-state-pathway-lifetime framework advances Fe-SAC design from static activity correlations toward predictive control of catalytic trajectories under realistic operating conditions.},
}
RevDate: 2026-10-15
CmpDate: 2026-10-15
Mapping global bee research with traits and plant-pollinator interaction networks.
Scientific reports, 16(1):.
Bees sustain key functions in natural ecosystems and agricultural landscapes, yet our understanding of their ecology is typically informed from studies concentrated on a few model taxa. To reveal how this may be biasing our understanding of bee responses and function in the environment we quantify global patterns of research attention across 69,682 bee-related publications to test whether research effort aligns with plant-pollinator network centrality, trait variation, public interest, and socio-economic context. Human managed bees take up most of the research effort; importantly this trend has been increasing over time. Plant–pollinator network centrality is unrelated to research effort; here we reveal genera with high centrality but low research attention as prime candidates for future study. Both pollinator management and sociality have an impact on research effort. Excluding Apis and Bombus (the most traditionally researched genera), managed bee genera are the focus of twice as many papers as wild genera, with the managed share rising over time. Our study reveals and quantifies persistent global research biases and highlights the need for monitoring, risk assessment, and policies that target neglected yet structurally central genera in plant-pollinator interaction networks.
Additional Links: PMID-41807479
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@article {pmid41807479,
year = {2026},
author = {Nesbit, ML and Montauban, C and Windram, F and Pérez, MSB and Hughes, WOH and Goulson, D and Gill, RJ and Graystock, P},
title = {Mapping global bee research with traits and plant-pollinator interaction networks.},
journal = {Scientific reports},
volume = {16},
number = {1},
pages = {},
pmid = {41807479},
issn = {2045-2322},
mesh = {Animals ; *Bees/physiology ; *Pollination/physiology ; Ecosystem ; Plants ; Ecology ; Machine Learning ; Data Mining ; },
abstract = {Bees sustain key functions in natural ecosystems and agricultural landscapes, yet our understanding of their ecology is typically informed from studies concentrated on a few model taxa. To reveal how this may be biasing our understanding of bee responses and function in the environment we quantify global patterns of research attention across 69,682 bee-related publications to test whether research effort aligns with plant-pollinator network centrality, trait variation, public interest, and socio-economic context. Human managed bees take up most of the research effort; importantly this trend has been increasing over time. Plant–pollinator network centrality is unrelated to research effort; here we reveal genera with high centrality but low research attention as prime candidates for future study. Both pollinator management and sociality have an impact on research effort. Excluding Apis and Bombus (the most traditionally researched genera), managed bee genera are the focus of twice as many papers as wild genera, with the managed share rising over time. Our study reveals and quantifies persistent global research biases and highlights the need for monitoring, risk assessment, and policies that target neglected yet structurally central genera in plant-pollinator interaction networks.},
}
MeSH Terms:
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Animals
*Bees/physiology
*Pollination/physiology
Ecosystem
Plants
Ecology
Machine Learning
Data Mining
RevDate: 2026-10-15
CmpDate: 2026-10-15
Benthic marine litter monitoring: A comparative analysis of survey methods, reporting biases, and a decision-support framework.
Marine pollution bulletin, 233(Pt 1):120154.
The seafloor is a major sink for marine litter, yet monitoring remains challenging due to technical and methodological constraints. A wide range of survey techniques exists, but differences in spatial coverage, detection capability, and reporting practices hinder cross-study comparability. This review evaluates principal approaches for benthic macrolitter monitoring based on 60 peer-reviewed studies published between 2000 and 2025. Reviewed techniques include bottom trawls, grabs, diver surveys, towed cameras, remotely operated vehicles, autonomous underwater vehicles, acoustic methods, and AI-assisted image analysis. The synthesis reveals clear trade-offs: diver surveys provide high-resolution observations but are spatially limited, whereas trawl-based methods offer broader coverage but suffer from gear selectivity and substrate constraints. Imaging platforms balance spatial coverage and detection detail, though performance depends on environmental conditions. Bias-frequency analysis showed that reporting inconsistency (87%), gear selectivity (80%), and detection bias (75%) were the most frequent limitations. Only 23% of studies used comparable reporting units, constraining data integration and indicating that litter densities are often method-dependent. Based on these findings, the study develops an objective-driven decision-support framework consisting of a decision matrix and a decision tree linking monitoring objectives, habitat characteristics, environmental conditions, and logistical constraints to survey techniques. The framework supports method selection for baseline assessments, long-term monitoring, ecological impact studies, and hotspot identification. The results highlight the need for standardized reporting, cross-method calibration, and open-access training datasets for automated image analysis. By integrating cross-method evidence, semi-quantitative synthesis, and decision-support tools, this review provides a practical foundation for improving benthic marine litter monitoring.
Additional Links: PMID-42475962
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@article {pmid42475962,
year = {2026},
author = {Özvarol, Y},
title = {Benthic marine litter monitoring: A comparative analysis of survey methods, reporting biases, and a decision-support framework.},
journal = {Marine pollution bulletin},
volume = {233},
number = {Pt 1},
pages = {120154},
doi = {10.1016/j.marpolbul.2026.120154},
pmid = {42475962},
issn = {1879-3363},
mesh = {*Environmental Monitoring/methods ; Ecosystem ; *Decision Support Techniques ; },
abstract = {The seafloor is a major sink for marine litter, yet monitoring remains challenging due to technical and methodological constraints. A wide range of survey techniques exists, but differences in spatial coverage, detection capability, and reporting practices hinder cross-study comparability. This review evaluates principal approaches for benthic macrolitter monitoring based on 60 peer-reviewed studies published between 2000 and 2025. Reviewed techniques include bottom trawls, grabs, diver surveys, towed cameras, remotely operated vehicles, autonomous underwater vehicles, acoustic methods, and AI-assisted image analysis. The synthesis reveals clear trade-offs: diver surveys provide high-resolution observations but are spatially limited, whereas trawl-based methods offer broader coverage but suffer from gear selectivity and substrate constraints. Imaging platforms balance spatial coverage and detection detail, though performance depends on environmental conditions. Bias-frequency analysis showed that reporting inconsistency (87%), gear selectivity (80%), and detection bias (75%) were the most frequent limitations. Only 23% of studies used comparable reporting units, constraining data integration and indicating that litter densities are often method-dependent. Based on these findings, the study develops an objective-driven decision-support framework consisting of a decision matrix and a decision tree linking monitoring objectives, habitat characteristics, environmental conditions, and logistical constraints to survey techniques. The framework supports method selection for baseline assessments, long-term monitoring, ecological impact studies, and hotspot identification. The results highlight the need for standardized reporting, cross-method calibration, and open-access training datasets for automated image analysis. By integrating cross-method evidence, semi-quantitative synthesis, and decision-support tools, this review provides a practical foundation for improving benthic marine litter monitoring.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Environmental Monitoring/methods
Ecosystem
*Decision Support Techniques
RevDate: 2026-10-15
CmpDate: 2026-10-15
Temporal transcriptomic and lipidomic analysis reveals multi-omics dynamic profiles of B. napus seed germination.
BMC genomics, 27(1):.
BACKGROUND: Lipids represent the major storage reserve in Brassica napus seeds. During germination, lipid mobilization delivers indispensable energy to support seedling establishment, thereby profoundly influencing germination vigor and subsequent seedling growth capacity. Although lipid mobilization is fundamentally required for successful rapeseed germination, the temporal coordination between transcriptional reprogramming and lipid metabolic conversion remains largely elusive, and the underlying molecular regulatory network remains to be systematically deciphered.
RESULTS: We conducted an integrated transcriptomic and lipidomic analysis on dry B. napus seeds and germinating seeds at 6, 12, 24, and 48 h after imbibition. The results revealed distinct stage-specific characteristics of gene expression and lipid metabolism during germination. In the early imbibition stage, differentially expressed genes (DEGs) were primarily enriched in biological processes related to water transport, stress response, and signal transduction, whereas significant changes in lipid metabolism were observed to be relatively delayed. During the initiation of germination, triacylglycerols (TGs) underwent rapid degradation, accompanied by a significant up-regulation of genes involved in the β-oxidation and gluconeogenesis pathways. In the late germination stage, genes responsible for membrane lipid synthesis were sharply up-regulated, which induced extensive membrane lipid remodeling.
CONCLUSION: This work represents the first systematic integration of transcriptomic and lipidomic data focusing on dynamic changes during the germination stage in B. napus, systematically illustrating the global molecular and lipid metabolic features of rapeseed seeds across sequential imbibition stages. It further delineates stage-specific expression patterns of key functional genes and lipid metabolites throughout germination. Collectively, these results advance our comprehensive understanding of the regulatory networks controlling rapeseed seed germination, and offer reliable theoretical references and candidate gene resources for breeding high-yield and high-quality B. napus varieties.
Additional Links: PMID-42477532
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Citation:
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@article {pmid42477532,
year = {2026},
author = {Zhang, B and Wu, J and Ma, L and Liu, H and Sun, W and Duan, J},
title = {Temporal transcriptomic and lipidomic analysis reveals multi-omics dynamic profiles of B. napus seed germination.},
journal = {BMC genomics},
volume = {27},
number = {1},
pages = {},
pmid = {42477532},
issn = {1471-2164},
support = {24JRRM025//Technology Fund Project/ ; },
mesh = {*Brassica napus/genetics/metabolism/growth & development ; *Germination/genetics ; *Seeds/genetics/metabolism/growth & development ; *Lipidomics ; Gene Expression Profiling ; Lipid Metabolism ; Multiomics ; Gene Expression Regulation, Plant ; *Transcriptome ; },
abstract = {BACKGROUND: Lipids represent the major storage reserve in Brassica napus seeds. During germination, lipid mobilization delivers indispensable energy to support seedling establishment, thereby profoundly influencing germination vigor and subsequent seedling growth capacity. Although lipid mobilization is fundamentally required for successful rapeseed germination, the temporal coordination between transcriptional reprogramming and lipid metabolic conversion remains largely elusive, and the underlying molecular regulatory network remains to be systematically deciphered.
RESULTS: We conducted an integrated transcriptomic and lipidomic analysis on dry B. napus seeds and germinating seeds at 6, 12, 24, and 48 h after imbibition. The results revealed distinct stage-specific characteristics of gene expression and lipid metabolism during germination. In the early imbibition stage, differentially expressed genes (DEGs) were primarily enriched in biological processes related to water transport, stress response, and signal transduction, whereas significant changes in lipid metabolism were observed to be relatively delayed. During the initiation of germination, triacylglycerols (TGs) underwent rapid degradation, accompanied by a significant up-regulation of genes involved in the β-oxidation and gluconeogenesis pathways. In the late germination stage, genes responsible for membrane lipid synthesis were sharply up-regulated, which induced extensive membrane lipid remodeling.
CONCLUSION: This work represents the first systematic integration of transcriptomic and lipidomic data focusing on dynamic changes during the germination stage in B. napus, systematically illustrating the global molecular and lipid metabolic features of rapeseed seeds across sequential imbibition stages. It further delineates stage-specific expression patterns of key functional genes and lipid metabolites throughout germination. Collectively, these results advance our comprehensive understanding of the regulatory networks controlling rapeseed seed germination, and offer reliable theoretical references and candidate gene resources for breeding high-yield and high-quality B. napus varieties.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Brassica napus/genetics/metabolism/growth & development
*Germination/genetics
*Seeds/genetics/metabolism/growth & development
*Lipidomics
Gene Expression Profiling
Lipid Metabolism
Multiomics
Gene Expression Regulation, Plant
*Transcriptome
RevDate: 2026-10-12
Tetrodotoxin (TTX): What do we currently know? The state of the art.
Archives of toxicology [Epub ahead of print].
Tetrodotoxin (TTX) is one of the most potent naturally occurring neurotoxins and continues to attract considerable scientific, clinical, forensic, and regulatory attention. Historically associated with pufferfish poisoning in East and Southeast Asia, TTX has recently emerged as a global food safety concern due to its detection in an increasing number of marine and terrestrial organisms and its expanding geographical distribution, including European coastal waters. Despite decades of research, important questions regarding its biosynthesis, ecological origin, toxicokinetics, and environmental dissemination remain unresolved. This review provides a comprehensive overview of current knowledge on TTX. The chemical structure, physicochemical properties, proposed biosynthetic origin, and diversity of naturally occurring TTX analogues are discussed. Attention is devoted to the toxin's mechanism of action, which involves high-affinity binding to voltage-gated sodium channels and subsequent inhibition of sodium ion conductance, leading to neuromuscular paralysis and potentially fatal respiratory failure. Current evidence regarding toxicokinetics, tissue distribution, elimination pathways, and the suitability of different biological matrices for laboratory confirmation of exposure is also summarized. The review further examines the analytical challenges associated with TTX determination, including its high polarity, occurrence at trace concentrations, rapid elimination from blood, and frequent co-occurrence with structurally related analogues. The evolution of analytical methodologies is presented, from early bioassays and chromatographic techniques with fluorescence or UV detection to advanced liquid chromatography-mass spectrometry platforms, high-resolution mass spectrometry, capillary electrophoresis, immunochemical assays, and emerging biosensor-based approaches. Finally, current regulatory perspectives and risk assessment strategies are discussed in the context of the increasing occurrence of TTX in seafood and the growing need for harmonized monitoring programs. Collectively, this review summarizes the current state of the art, identifies key knowledge gaps, and highlights future directions in TTX research.
Additional Links: PMID-42864527
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Citation:
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@article {pmid42864527,
year = {2026},
author = {Niżnik, Ł and Kuca, K and Nepovimová, E and Jurowski, K},
title = {Tetrodotoxin (TTX): What do we currently know? The state of the art.},
journal = {Archives of toxicology},
volume = {},
number = {},
pages = {},
pmid = {42864527},
issn = {1432-0738},
abstract = {Tetrodotoxin (TTX) is one of the most potent naturally occurring neurotoxins and continues to attract considerable scientific, clinical, forensic, and regulatory attention. Historically associated with pufferfish poisoning in East and Southeast Asia, TTX has recently emerged as a global food safety concern due to its detection in an increasing number of marine and terrestrial organisms and its expanding geographical distribution, including European coastal waters. Despite decades of research, important questions regarding its biosynthesis, ecological origin, toxicokinetics, and environmental dissemination remain unresolved. This review provides a comprehensive overview of current knowledge on TTX. The chemical structure, physicochemical properties, proposed biosynthetic origin, and diversity of naturally occurring TTX analogues are discussed. Attention is devoted to the toxin's mechanism of action, which involves high-affinity binding to voltage-gated sodium channels and subsequent inhibition of sodium ion conductance, leading to neuromuscular paralysis and potentially fatal respiratory failure. Current evidence regarding toxicokinetics, tissue distribution, elimination pathways, and the suitability of different biological matrices for laboratory confirmation of exposure is also summarized. The review further examines the analytical challenges associated with TTX determination, including its high polarity, occurrence at trace concentrations, rapid elimination from blood, and frequent co-occurrence with structurally related analogues. The evolution of analytical methodologies is presented, from early bioassays and chromatographic techniques with fluorescence or UV detection to advanced liquid chromatography-mass spectrometry platforms, high-resolution mass spectrometry, capillary electrophoresis, immunochemical assays, and emerging biosensor-based approaches. Finally, current regulatory perspectives and risk assessment strategies are discussed in the context of the increasing occurrence of TTX in seafood and the growing need for harmonized monitoring programs. Collectively, this review summarizes the current state of the art, identifies key knowledge gaps, and highlights future directions in TTX research.},
}
RevDate: 2026-10-15
CmpDate: 2026-10-13
Advancing Marine Mammal Conservation Through Omics Tools and Integration of Indigenous Ecological Knowledge.
Molecular ecology, 35(19):e70567.
Conservation of biodiversity is a global priority as human-driven pressures continue to intensify and alter ecosystems worldwide. Marine mammals are vulnerable species, facing numerous escalating anthropogenic threats. Here, we evaluate how, as omics technologies become more accessible and affordable, established and emerging tools are advancing effective marine mammal research and conservation management. Assessments of genetic diversity, adaptive capacity, demographic history and local adaptation provide vital insights into how marine mammal populations respond to environmental change across contemporary and evolutionary timescales. Whole-genome sequencing, functional genomics, epigenetics and multi-omic integration enable deeper insights into the molecular basis of complex fitness-related traits. Approaches like epigenetics, ancient DNA and environmental DNA offer new opportunities to study cryptic, rare, or historical populations and evolutionary processes. Yet, effective marine mammal conservation management cannot rely exclusively on increased availability of omics tools and data. We emphasize the need and obligation for genuine collaboration and integration of Indigenous perspectives with marine mammal genomics approaches to foster ethical, inclusive and effective conservation, and suggest best practices for this. Additionally, we highlight that translating omics data into practical conservation outcomes remains challenging, requiring clear communication, collaboration and integration into management. Using marine mammal genomics to address conservation challenges in a changing world requires innovation, partnership and the integration of diverse knowledge systems, such as Indigenous Ecological Knowledge.
Additional Links: PMID-42864885
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Citation:
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@article {pmid42864885,
year = {2026},
author = {Reeves, IM and Genty, G and Alexander, A and Aguilar-Gómez, D and Bilgmann, K and Berthelsen, AL and Brewer, AM and Carroll, EL and Day, GA and Dönmez, EM and Eichenberger, F and Furni, F and Hoffman, JI and Holmes, S and Hernandez, KM and Martien, KK and Marfurt, SM and McCarthy, ML and Morin, PA and Nery, MF and Nigenda-Morales, S and O'Mahony, ÉN and Oteri, E and Papageorgiou, D and Parsons, KM and Restrepo-Garzón, N and Schreiber, L and Stewart, RO and Vendrami, DLJ and Olsen, MT and Unal, E and Meyer, CE and Alvarez-Costes, S},
title = {Advancing Marine Mammal Conservation Through Omics Tools and Integration of Indigenous Ecological Knowledge.},
journal = {Molecular ecology},
volume = {35},
number = {19},
pages = {e70567},
pmid = {42864885},
issn = {1365-294X},
support = {//American Genetics Association/ ; //Company of Biologists/ ; },
mesh = {Animals ; *Conservation of Natural Resources/methods ; *Genomics/methods ; Multiomics ; *Aquatic Organisms/genetics ; Biodiversity ; Genetic Variation ; *Mammals/genetics ; Ecosystem ; },
abstract = {Conservation of biodiversity is a global priority as human-driven pressures continue to intensify and alter ecosystems worldwide. Marine mammals are vulnerable species, facing numerous escalating anthropogenic threats. Here, we evaluate how, as omics technologies become more accessible and affordable, established and emerging tools are advancing effective marine mammal research and conservation management. Assessments of genetic diversity, adaptive capacity, demographic history and local adaptation provide vital insights into how marine mammal populations respond to environmental change across contemporary and evolutionary timescales. Whole-genome sequencing, functional genomics, epigenetics and multi-omic integration enable deeper insights into the molecular basis of complex fitness-related traits. Approaches like epigenetics, ancient DNA and environmental DNA offer new opportunities to study cryptic, rare, or historical populations and evolutionary processes. Yet, effective marine mammal conservation management cannot rely exclusively on increased availability of omics tools and data. We emphasize the need and obligation for genuine collaboration and integration of Indigenous perspectives with marine mammal genomics approaches to foster ethical, inclusive and effective conservation, and suggest best practices for this. Additionally, we highlight that translating omics data into practical conservation outcomes remains challenging, requiring clear communication, collaboration and integration into management. Using marine mammal genomics to address conservation challenges in a changing world requires innovation, partnership and the integration of diverse knowledge systems, such as Indigenous Ecological Knowledge.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Conservation of Natural Resources/methods
*Genomics/methods
Multiomics
*Aquatic Organisms/genetics
Biodiversity
Genetic Variation
*Mammals/genetics
Ecosystem
RevDate: 2026-10-15
CmpDate: 2026-10-13
The Signal of Admixture Can Decay Rapidly When Using Clustering-Based Methods.
Molecular ecology resources, 26(7):e70215.
Gene flow shapes evolutionary trajectories by introducing novel alleles, facilitating or retarding adaptation or eroding divergence among populations. Studies commonly infer gene flow through estimates of genetic admixture from methods that cluster individuals by allele-frequency similarity. However, the ability of these methods to reliably detect historical admixture remains poorly understood, particularly under spatially restricted dispersal and across a range of migration rates. Here, we evaluate how signals of admixture arise and decay during and after gene flow across a range of within- and between-population dispersal rates, using three common inference methods: ADMIXTURE, sNMF and PopCluster. Using forward-time simulations in a two-dimensional landscape, we modelled two metapopulations that diverged in isolation, experienced a pulse of secondary contact and subsequently returned to isolation. All three methods systematically underestimated admixture, with the bias increasing once gene flow ceased: inferred admixture averaged 56% of the true value at the end of gene flow, declined to 23% after 1000 generations and fell below 5% by 2000 generations, even where true admixture exceeded 20%. This underestimation was accompanied by corresponding overestimation of barrier strength, assessed using a metric analogous to cline width. Both patterns reflect the erosion of allele-frequency differences upon which these methods depend, which coincides with the rapid re-establishment of Hardy-Weinberg and linkage equilibrium following secondary contact. Our simulations show that, at least in some scenarios, the clustering-based admixture methods evaluated here cannot recover the signal of historical gene flow from present-day samples.
Additional Links: PMID-42865235
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Citation:
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@article {pmid42865235,
year = {2026},
author = {Shemuel, J and Singhal, S and Moritz, C and Zozaya, SM},
title = {The Signal of Admixture Can Decay Rapidly When Using Clustering-Based Methods.},
journal = {Molecular ecology resources},
volume = {26},
number = {7},
pages = {e70215},
pmid = {42865235},
issn = {1755-0998},
support = {DP210102267//Australian Research Council/ ; //Australian National University's Future Research Talent scholarship programme/ ; },
mesh = {*Gene Flow ; Cluster Analysis ; *Genetics, Population/methods ; Clustering Algorithms ; Computer Simulation ; Gene Frequency ; *Computational Biology/methods ; },
abstract = {Gene flow shapes evolutionary trajectories by introducing novel alleles, facilitating or retarding adaptation or eroding divergence among populations. Studies commonly infer gene flow through estimates of genetic admixture from methods that cluster individuals by allele-frequency similarity. However, the ability of these methods to reliably detect historical admixture remains poorly understood, particularly under spatially restricted dispersal and across a range of migration rates. Here, we evaluate how signals of admixture arise and decay during and after gene flow across a range of within- and between-population dispersal rates, using three common inference methods: ADMIXTURE, sNMF and PopCluster. Using forward-time simulations in a two-dimensional landscape, we modelled two metapopulations that diverged in isolation, experienced a pulse of secondary contact and subsequently returned to isolation. All three methods systematically underestimated admixture, with the bias increasing once gene flow ceased: inferred admixture averaged 56% of the true value at the end of gene flow, declined to 23% after 1000 generations and fell below 5% by 2000 generations, even where true admixture exceeded 20%. This underestimation was accompanied by corresponding overestimation of barrier strength, assessed using a metric analogous to cline width. Both patterns reflect the erosion of allele-frequency differences upon which these methods depend, which coincides with the rapid re-establishment of Hardy-Weinberg and linkage equilibrium following secondary contact. Our simulations show that, at least in some scenarios, the clustering-based admixture methods evaluated here cannot recover the signal of historical gene flow from present-day samples.},
}
MeSH Terms:
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*Gene Flow
Cluster Analysis
*Genetics, Population/methods
Clustering Algorithms
Computer Simulation
Gene Frequency
*Computational Biology/methods
RevDate: 2026-10-14
CmpDate: 2026-10-14
Dynamic workforce modulation and foraging efficiency in Eusocial insect colonies.
PLoS computational biology, 22(10):e1014258 pii:PCOMPBIOL-D-26-00932.
Understanding the fitness advantages conferred by eusociality remains a central challenge in behavioral ecology. One promising approach is to identify collective strategies that shift efficiency within social groups. Here, we explore the hypothesis that reserve workforces in ant colonies represent an adaptive mechanism that enhances flexibility and foraging efficiency under fluctuating environmental conditions. We examine how departure and return rates of foragers modulate such reserve workers and how these time-dependent dynamics shape the colony's overall energetic balance. By integrating an energetic-balance framework with stochastic search simulations inspired by empirical results from four colonies of Aphaenogaster senilis ants, we quantify the energetic requirements for colony viability, incorporating energy intake, search costs, and basal metabolic demands. Our results show that as colonies grow, maintaining a positive energy balance requires a disproportionately larger relative workforce. By modulating departure and return rates over time, colonies control the synchrony of their collective search and efficiently activate or suppress their reserve workforce to scale foraging effort as needed. These findings suggest that the "lazy" or weakly engaged workers commonly observed in large colonies function as an essential reserve that stabilizes colony energetics and enhances responsiveness. Together, our results provide a functional explanation for sublinear metabolic scaling in eusocial groups and highlight workforce modulation as a key factor underlying their energetic stability and evolutionary success.
Additional Links: PMID-42853891
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@article {pmid42853891,
year = {2026},
author = {Campos, D and Cristín, J and Fernández-López, P and Lloret-Cabot, R and Genovart, M and Bartumeus, F},
title = {Dynamic workforce modulation and foraging efficiency in Eusocial insect colonies.},
journal = {PLoS computational biology},
volume = {22},
number = {10},
pages = {e1014258},
doi = {10.1371/journal.pcbi.1014258},
pmid = {42853891},
issn = {1553-7358},
mesh = {Animals ; *Ants/physiology ; *Social Behavior ; *Models, Biological ; Energy Metabolism/physiology ; *Feeding Behavior/physiology ; Computer Simulation ; Computational Biology ; *Behavior, Animal/physiology ; },
abstract = {Understanding the fitness advantages conferred by eusociality remains a central challenge in behavioral ecology. One promising approach is to identify collective strategies that shift efficiency within social groups. Here, we explore the hypothesis that reserve workforces in ant colonies represent an adaptive mechanism that enhances flexibility and foraging efficiency under fluctuating environmental conditions. We examine how departure and return rates of foragers modulate such reserve workers and how these time-dependent dynamics shape the colony's overall energetic balance. By integrating an energetic-balance framework with stochastic search simulations inspired by empirical results from four colonies of Aphaenogaster senilis ants, we quantify the energetic requirements for colony viability, incorporating energy intake, search costs, and basal metabolic demands. Our results show that as colonies grow, maintaining a positive energy balance requires a disproportionately larger relative workforce. By modulating departure and return rates over time, colonies control the synchrony of their collective search and efficiently activate or suppress their reserve workforce to scale foraging effort as needed. These findings suggest that the "lazy" or weakly engaged workers commonly observed in large colonies function as an essential reserve that stabilizes colony energetics and enhances responsiveness. Together, our results provide a functional explanation for sublinear metabolic scaling in eusocial groups and highlight workforce modulation as a key factor underlying their energetic stability and evolutionary success.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Ants/physiology
*Social Behavior
*Models, Biological
Energy Metabolism/physiology
*Feeding Behavior/physiology
Computer Simulation
Computational Biology
*Behavior, Animal/physiology
RevDate: 2026-10-12
Socio-environmental assessment of Aedes aegypti distribution and risk of chikungunya in vulnerable community.
PLoS neglected tropical diseases, 20(10):e0014776 pii:PNTD-D-25-01036 [Epub ahead of print].
Chikungunya virus (CHIKV), transmitted by Aedes mosquitoes, poses a major public health challenge in tropical regions. In Brazil, its incidence has increased, especially in socioeconomically vulnerable areas, where environmental conditions favor the proliferation of vectors. Our objective was to assess the socioeconomic and environmental vulnerabilities associated with the spatial distribution of a) Ae. aegypti and b) resident exposure to CHIKV in a low-income community. Identifying key exposure hotspots, our work improves our understanding of CHIKV transmission in informal settlements and facilitates community-based interventions to mitigate CHIKV risk. We monitored Ae. aegypti using ovitraps and conducted a serological survey from October 2021 to June 2022 in a vulnerable informal community in Salvador, Brazil. Blood samples and sociodemographic, household, and environmental data were collected from residents aged ≥5 years. CHIKV serology was performed, and spatial models using Integrated Nested Laplace Approximation assessed vector distribution, seropositivity, and associated factors. Among 194 ovitraps, posterior estimates indicated higher egg counts in peridomicile locations (IRR = 1 .99; CrI:1.3 1-3.0 6); households experiencing food insecurity (IRR = 1.77; CrI: 1.05 - 2.99), properties with unpaved yards (IRR = 3.76; CrI:2.31 -6.18), and areas with greater garbage density (IRR = 1.25; CrI:1.01 -1.56). Among 888 participants, Bayesian spatial modeling identified factors associated with CHIKV seropositivity: elderly (OR= 2.24; CrI:1.16-4.35), uncovered brick walls (OR=2.29; CrI:1.16-4.55), the presence of yards, either paved (OR=2.06; CrI:1.30-3.00) or unpaved (OR=2.71; CrI:1.73-4.25), and self-reported mosquito sightings (OR=1.94; CrI:1.19-3.18). In addition, remotely sensed Land Surface Temperature (OR=1.33; CrI:0.98-1.83) and the spatial ovitraps egg counts (OR=1.14; CrI:0.87-1.52) were relevant variables. Our high-resolution study identified fine-scale vulnerabilities linked to both Ae. aegypti abundance and heightened risk of CHIKV transmission. Based on our findings, effective control strategies should not only focus on traditional methods such as enhancing basic urban infrastructure and services and promoting community awareness, but also target specific breeding sites around homes, address garbage accumulation, and consider the influence of micro-scale temperature variations. These results emphasize the importance of tailored, neighborhood-specific interventions to effectively reduce chikungunya transmission in high-risk communities.
Additional Links: PMID-42862816
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PubMed:
Citation:
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@article {pmid42862816,
year = {2026},
author = {Cruz, JS and Argibay, HD and Nery, N and Mogaji, H and Barreto, TDM and Batista, LES and Silva, LRS and Nery, VK and Ferreira, VCD and Carneiro, IO and López, YAA and Reis, MG and Ko, AI and Diggle, P and Begon, M and Costa, F and Khalil, H},
title = {Socio-environmental assessment of Aedes aegypti distribution and risk of chikungunya in vulnerable community.},
journal = {PLoS neglected tropical diseases},
volume = {20},
number = {10},
pages = {e0014776},
doi = {10.1371/journal.pntd.0014776},
pmid = {42862816},
issn = {1935-2735},
abstract = {Chikungunya virus (CHIKV), transmitted by Aedes mosquitoes, poses a major public health challenge in tropical regions. In Brazil, its incidence has increased, especially in socioeconomically vulnerable areas, where environmental conditions favor the proliferation of vectors. Our objective was to assess the socioeconomic and environmental vulnerabilities associated with the spatial distribution of a) Ae. aegypti and b) resident exposure to CHIKV in a low-income community. Identifying key exposure hotspots, our work improves our understanding of CHIKV transmission in informal settlements and facilitates community-based interventions to mitigate CHIKV risk. We monitored Ae. aegypti using ovitraps and conducted a serological survey from October 2021 to June 2022 in a vulnerable informal community in Salvador, Brazil. Blood samples and sociodemographic, household, and environmental data were collected from residents aged ≥5 years. CHIKV serology was performed, and spatial models using Integrated Nested Laplace Approximation assessed vector distribution, seropositivity, and associated factors. Among 194 ovitraps, posterior estimates indicated higher egg counts in peridomicile locations (IRR = 1 .99; CrI:1.3 1-3.0 6); households experiencing food insecurity (IRR = 1.77; CrI: 1.05 - 2.99), properties with unpaved yards (IRR = 3.76; CrI:2.31 -6.18), and areas with greater garbage density (IRR = 1.25; CrI:1.01 -1.56). Among 888 participants, Bayesian spatial modeling identified factors associated with CHIKV seropositivity: elderly (OR= 2.24; CrI:1.16-4.35), uncovered brick walls (OR=2.29; CrI:1.16-4.55), the presence of yards, either paved (OR=2.06; CrI:1.30-3.00) or unpaved (OR=2.71; CrI:1.73-4.25), and self-reported mosquito sightings (OR=1.94; CrI:1.19-3.18). In addition, remotely sensed Land Surface Temperature (OR=1.33; CrI:0.98-1.83) and the spatial ovitraps egg counts (OR=1.14; CrI:0.87-1.52) were relevant variables. Our high-resolution study identified fine-scale vulnerabilities linked to both Ae. aegypti abundance and heightened risk of CHIKV transmission. Based on our findings, effective control strategies should not only focus on traditional methods such as enhancing basic urban infrastructure and services and promoting community awareness, but also target specific breeding sites around homes, address garbage accumulation, and consider the influence of micro-scale temperature variations. These results emphasize the importance of tailored, neighborhood-specific interventions to effectively reduce chikungunya transmission in high-risk communities.},
}
RevDate: 2026-10-12
CmpDate: 2026-10-12
[Applications of remote sensing big data in wetland monitoring:Current status, challenges, and prospects].
Ying yong sheng tai xue bao = The journal of applied ecology, 37(9):2929-2944.
Wetlands are critical ecosystems that support hydrological and climate regulation, biodiversity conservation, and ecological security. However, under the combined pressures of climate change and human activities, global wetlands are increasingly facing severe area loss, functional degradation, and habitat fragmentation. With the advantages including long-term time-series records, broad spatial coverage, and multi-source observations, remote sensing big data provide essential technical support for identifying wetland degradation, monitoring dynamic changes, tracking restoration processes, and enabling risk early warning. We systematically reviewed the current applications, technical approaches, assessment frameworks, and future development directions of remote sensing big data in wetland monitoring. First, we sorted out the characteristics of remote sensing big data sources and their applicability in wetland monitoring. Second, we comparatively analyzed recent advances in wetland information extraction techniques based on spectral features, temporal characteristics, machine learning, deep learning, and multi-source data fusion. Third, from the perspectives of hydrological processes, vegetation function, landscape structure, and temporal stability, we constructed a remote sensing-based assessment framework for monitoring wetland degradation and restoration, and explored its applications in degradation diagnosis, restoration trajectory tracking, effectiveness evaluation, and instability early warning. Finally, we identified key challenges in current applications, including difficulties in integrating massive heterogeneous datasets, limitations in spatiotemporal resolution, the complexity of wetland surface conditions, and insufficient ecological interpretation. Accordingly, we proposed future development pathways involving multi-source sensor synergy, model construction for complex scenarios, multi-factor environmental assessment, and innovation in governance models. This review would provide theoretical references and technical guidance for whole-process monitoring of wetland degradation and restoration, evaluation of ecological conservation and restoration, and intelligent wetland governance.
Additional Links: PMID-42864085
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PubMed:
Citation:
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@article {pmid42864085,
year = {2026},
author = {Ye, H and Li, YY and Wang, XX and Liu, Y and Zheng, YH and Zhang, X and Chen, HY and Liu, YC and Nie, M and Li, B},
title = {[Applications of remote sensing big data in wetland monitoring:Current status, challenges, and prospects].},
journal = {Ying yong sheng tai xue bao = The journal of applied ecology},
volume = {37},
number = {9},
pages = {2929-2944},
doi = {10.13287/j.1001-9332.202609.036},
pmid = {42864085},
issn = {1001-9332},
mesh = {*Wetlands ; *Remote Sensing Technology ; *Environmental Monitoring/methods ; *Conservation of Natural Resources ; *Big Data ; Climate Change ; },
abstract = {Wetlands are critical ecosystems that support hydrological and climate regulation, biodiversity conservation, and ecological security. However, under the combined pressures of climate change and human activities, global wetlands are increasingly facing severe area loss, functional degradation, and habitat fragmentation. With the advantages including long-term time-series records, broad spatial coverage, and multi-source observations, remote sensing big data provide essential technical support for identifying wetland degradation, monitoring dynamic changes, tracking restoration processes, and enabling risk early warning. We systematically reviewed the current applications, technical approaches, assessment frameworks, and future development directions of remote sensing big data in wetland monitoring. First, we sorted out the characteristics of remote sensing big data sources and their applicability in wetland monitoring. Second, we comparatively analyzed recent advances in wetland information extraction techniques based on spectral features, temporal characteristics, machine learning, deep learning, and multi-source data fusion. Third, from the perspectives of hydrological processes, vegetation function, landscape structure, and temporal stability, we constructed a remote sensing-based assessment framework for monitoring wetland degradation and restoration, and explored its applications in degradation diagnosis, restoration trajectory tracking, effectiveness evaluation, and instability early warning. Finally, we identified key challenges in current applications, including difficulties in integrating massive heterogeneous datasets, limitations in spatiotemporal resolution, the complexity of wetland surface conditions, and insufficient ecological interpretation. Accordingly, we proposed future development pathways involving multi-source sensor synergy, model construction for complex scenarios, multi-factor environmental assessment, and innovation in governance models. This review would provide theoretical references and technical guidance for whole-process monitoring of wetland degradation and restoration, evaluation of ecological conservation and restoration, and intelligent wetland governance.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Wetlands
*Remote Sensing Technology
*Environmental Monitoring/methods
*Conservation of Natural Resources
*Big Data
Climate Change
RevDate: 2026-10-12
CmpDate: 2026-10-12
Eukaryotic MAGs from the NEREA observatory: expanding the coastal microbiome dataset.
Scientific data, 13(1):.
Marine ecosystems are hotspots of biodiversity and biogeochemical activity, yet much of their complexity remains largely inaccessible without genome-resolved data. Here we present a curated dataset of 52 eukaryotic metagenome-assembled genomes (MAGs) reconstructed from samples collected between April 2019 and January 2020 at three NEREA (Naples Ecological REsearch for Augmented observatories) sites in the Gulf of Naples. NEREA is a coastal observatory integrating physical, chemical and biological measurements with state-of-the-art metagenomics. The eukaryotic MAGs have an average completeness of ~55% and genome size of ~20 Mb. Predicted proteins were functionally annotated against UniProtKB, InterPro, and eggNOG databases, and each MAG was taxonomically classified using a curated RNA polymerase A reference dataset. The recovered MAGs encompass diverse eukaryotic lineages, primarily Ochrophyta, Chlorophyta and Haptophyta. Building on the Tara Oceans eukaryotic MAG legacy, this release represents the first reconstruction of eukaryotic MAGs from a coastal time series, enabling temporal and functional analyses of eukaryotic plankton.
Additional Links: PMID-42265111
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@article {pmid42265111,
year = {2026},
author = {Campese, L and Longo, A and Pelletier, E and Delmont, TO and Ambrosino, L and Miralto, M and Mele, BH and Alberti, A and Labadie, K and Oliveira, PH and Perdereau, A and Wincker, P and , and Iudicone, D},
title = {Eukaryotic MAGs from the NEREA observatory: expanding the coastal microbiome dataset.},
journal = {Scientific data},
volume = {13},
number = {1},
pages = {},
pmid = {42265111},
issn = {2052-4463},
support = {101082021//MARCO-BOLO/ ; ID: 862923//AtlantECO/ ; 101081642//OBAMA-NEXT/ ; },
mesh = {*Metagenome ; *Eukaryota/genetics ; *Microbiota ; Metagenomics ; Biocuration ; },
abstract = {Marine ecosystems are hotspots of biodiversity and biogeochemical activity, yet much of their complexity remains largely inaccessible without genome-resolved data. Here we present a curated dataset of 52 eukaryotic metagenome-assembled genomes (MAGs) reconstructed from samples collected between April 2019 and January 2020 at three NEREA (Naples Ecological REsearch for Augmented observatories) sites in the Gulf of Naples. NEREA is a coastal observatory integrating physical, chemical and biological measurements with state-of-the-art metagenomics. The eukaryotic MAGs have an average completeness of ~55% and genome size of ~20 Mb. Predicted proteins were functionally annotated against UniProtKB, InterPro, and eggNOG databases, and each MAG was taxonomically classified using a curated RNA polymerase A reference dataset. The recovered MAGs encompass diverse eukaryotic lineages, primarily Ochrophyta, Chlorophyta and Haptophyta. Building on the Tara Oceans eukaryotic MAG legacy, this release represents the first reconstruction of eukaryotic MAGs from a coastal time series, enabling temporal and functional analyses of eukaryotic plankton.},
}
MeSH Terms:
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*Metagenome
*Eukaryota/genetics
*Microbiota
Metagenomics
Biocuration
RevDate: 2026-10-12
CmpDate: 2026-10-12
Celtic Invasive Plants database.
Scientific data, 13(1):.
Alien Invasive Species (AIS) are among the principal threats to humanity due to their substantial ecological, social, and economic impacts. International efforts to harmonize national AIS checklists and databases is often hindered by fragmented data across multiple platforms. The Celtic Fringe, a biogeographically coherent unit within the European Atlantic Floristic Region, includes part of the Iberian Peninsula, France and the British Isles, and is notable for its extensively documented flora. Here, we present the first unified AIS checklist and georeferenced occurrence database for the entire Celtic Fringe, with occurrences mapped to a 10 × 10 km UTM grid resolution. Occurrence data were aggregated from public datasets, while the harmonized AIS checklist of 271 taxa was developed through the integration of national and international sources. The resulting database comprises 164,974 occurrences, each enriched with taxonomic, floristic, and administrative metadata to facilitate use across multiple geographic and governance levels. This harmonized and standardised resource is designed to support AIS management at local, national, and transnational scales, while facilitating conservation planning and research on invasion dynamics.
Additional Links: PMID-42343083
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Citation:
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@article {pmid42343083,
year = {2026},
author = {González-Toral, C and Madrazo-Frías, L and Estrada Fernández, A and López-Alonso, R and Sanna, M and Cuesta, C and Cires, E and Viruel, J},
title = {Celtic Invasive Plants database.},
journal = {Scientific data},
volume = {13},
number = {1},
pages = {},
pmid = {42343083},
issn = {2052-4463},
support = {XXXVI Convocatoria para Ampliación de Estudios en el Extranjero en Ciencias de la Vida y de la Materia" (BEVP36A7453)//Fundación Ramón Areces/ ; PRP-UO-PUB-ASV-2025-GRUPO BIO-CON-FILO//Universidad de Oviedo/ ; RYC2023-042611-I by MCIU/AEI/10.13039/501100011033 and FSE+.//Ministerio de Ciencia e Innovación/ ; },
mesh = {*Introduced Species ; *Plants/classification ; *Databases, Factual ; Conservation of Natural Resources ; France ; },
abstract = {Alien Invasive Species (AIS) are among the principal threats to humanity due to their substantial ecological, social, and economic impacts. International efforts to harmonize national AIS checklists and databases is often hindered by fragmented data across multiple platforms. The Celtic Fringe, a biogeographically coherent unit within the European Atlantic Floristic Region, includes part of the Iberian Peninsula, France and the British Isles, and is notable for its extensively documented flora. Here, we present the first unified AIS checklist and georeferenced occurrence database for the entire Celtic Fringe, with occurrences mapped to a 10 × 10 km UTM grid resolution. Occurrence data were aggregated from public datasets, while the harmonized AIS checklist of 271 taxa was developed through the integration of national and international sources. The resulting database comprises 164,974 occurrences, each enriched with taxonomic, floristic, and administrative metadata to facilitate use across multiple geographic and governance levels. This harmonized and standardised resource is designed to support AIS management at local, national, and transnational scales, while facilitating conservation planning and research on invasion dynamics.},
}
MeSH Terms:
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*Introduced Species
*Plants/classification
*Databases, Factual
Conservation of Natural Resources
France
RevDate: 2026-10-09
Regional effect of population-based programs promoting salt reduction and potassium intake in Hokkaido: a post hoc analysis of the PoSPIP.
Hypertension research : official journal of the Japanese Society of Hypertension [Epub ahead of print].
The Population-based Sodium/Potassium Improvement Program is a nonrandomized population-based intervention implemented by the Japanese Society of Hypertension across multiple municipalities and workplaces in Japan. This post hoc regional analysis focused on two municipalities in Hokkaido-namely, Higashikagura, which received standard support, and Mashike, which received intensive support consisting of on-site urinary sodium-to-potassium (Na/K) ratio measurement, immediate feedback, repeated health guidance, and food-environment improvement. A total of 431 participants who underwent annual health checkups in 2021 and 2022 and had urinary Na/K ratio data at both time points (standard support group, n = 218; intensive support group, n = 213) were included. One-year changes in the urinary Na/K ratio, estimated salt and potassium intakes, blood pressure (BP), and other clinical measures were compared between the groups using multivariable linear regression. The proportion of participants achieving urinary Na/K ratio targets increased in the intensive support group. A significant group-by-time interaction was observed for the <2 threshold (OR 2.62, 95% CI: 1.25-5.50), but not for the <4 threshold. After adjustment for covariates, estimated salt intake decreased more in the intensive support group than in the standard support group (adjusted group difference: -0.53 g/day, 95% confidence interval: -0.95 to -0.12). Changes in the urinary Na/K ratio, estimated potassium intake, and systolic and diastolic BP did not significantly differ between the groups. Intensive support incorporating urinary Na/K ratio measurement, immediate feedback, and repeated multidisciplinary guidance may promote salt reduction in local community settings.
Additional Links: PMID-42855531
PubMed:
Citation:
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@article {pmid42855531,
year = {2026},
author = {Sakuma, H and Yoshita, K and Takemi, Y and Hisamatsu, T and Tsukinoki, R and Hayabuchi, H and Okami, Y and Kitaoka, K and Hozawa, A and Ohkubo, T and Hasebe, N and Miura, K and Nakagawa, N},
title = {Regional effect of population-based programs promoting salt reduction and potassium intake in Hokkaido: a post hoc analysis of the PoSPIP.},
journal = {Hypertension research : official journal of the Japanese Society of Hypertension},
volume = {},
number = {},
pages = {},
pmid = {42855531},
issn = {1348-4214},
abstract = {The Population-based Sodium/Potassium Improvement Program is a nonrandomized population-based intervention implemented by the Japanese Society of Hypertension across multiple municipalities and workplaces in Japan. This post hoc regional analysis focused on two municipalities in Hokkaido-namely, Higashikagura, which received standard support, and Mashike, which received intensive support consisting of on-site urinary sodium-to-potassium (Na/K) ratio measurement, immediate feedback, repeated health guidance, and food-environment improvement. A total of 431 participants who underwent annual health checkups in 2021 and 2022 and had urinary Na/K ratio data at both time points (standard support group, n = 218; intensive support group, n = 213) were included. One-year changes in the urinary Na/K ratio, estimated salt and potassium intakes, blood pressure (BP), and other clinical measures were compared between the groups using multivariable linear regression. The proportion of participants achieving urinary Na/K ratio targets increased in the intensive support group. A significant group-by-time interaction was observed for the <2 threshold (OR 2.62, 95% CI: 1.25-5.50), but not for the <4 threshold. After adjustment for covariates, estimated salt intake decreased more in the intensive support group than in the standard support group (adjusted group difference: -0.53 g/day, 95% confidence interval: -0.95 to -0.12). Changes in the urinary Na/K ratio, estimated potassium intake, and systolic and diastolic BP did not significantly differ between the groups. Intensive support incorporating urinary Na/K ratio measurement, immediate feedback, and repeated multidisciplinary guidance may promote salt reduction in local community settings.},
}
RevDate: 2026-10-10
CmpDate: 2026-10-10
Woodland Decline Undermines Resilience in Fire-Adapted Landscapes.
Global change biology, 32(10):e71148.
Open-canopy forests and woodlands are a foundational component of historically fire-adapted landscapes, yet their persistence under contemporary climate and fire regimes remains poorly understood. Here, we leverage historical aerial photogrammetry integrated with contemporary satellite imagery to assess landscape change, vegetation transitions, and ecological stability over a century (1930s-2020s) for a large regional landscape of the Interior Northwest. We found woodlands declined by more than 40% across the region and exhibited high rates of type conversion, with roughly half converting to closed-canopy forests and a quarter transitioning to grass- and shrub-dominated ecosystems. Forest area, in contrast, remained relatively stable over the same period as woodland-to-forest conversion compensated for forest losses. The widespread decline in woodlands demonstrates that they exist as a metastable state, created and maintained only under stable, low- and mixed-severity fire regimes. The loss of these keystone ecosystems portends the erosion of landscape resilience-as remaining woodlands disappear, their ability to buffer for forest losses will decline as well, increasing the risk of abrupt and persistent ecosystem transitions under shifting fire regimes and warmer future climates.
Additional Links: PMID-42855955
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PubMed:
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@article {pmid42855955,
year = {2026},
author = {Furniss, TJ and Hessburg, PF and Povak, NA and Salter, RB and Prichard, SJ and Churchill, DJ},
title = {Woodland Decline Undermines Resilience in Fire-Adapted Landscapes.},
journal = {Global change biology},
volume = {32},
number = {10},
pages = {e71148},
doi = {10.1111/gcb.71148},
pmid = {42855955},
issn = {1365-2486},
mesh = {*Forests ; *Fires ; *Conservation of Natural Resources ; Climate Change ; Satellite Imagery ; Ecosystem ; Wildfires ; Trees ; Northwestern United States ; },
abstract = {Open-canopy forests and woodlands are a foundational component of historically fire-adapted landscapes, yet their persistence under contemporary climate and fire regimes remains poorly understood. Here, we leverage historical aerial photogrammetry integrated with contemporary satellite imagery to assess landscape change, vegetation transitions, and ecological stability over a century (1930s-2020s) for a large regional landscape of the Interior Northwest. We found woodlands declined by more than 40% across the region and exhibited high rates of type conversion, with roughly half converting to closed-canopy forests and a quarter transitioning to grass- and shrub-dominated ecosystems. Forest area, in contrast, remained relatively stable over the same period as woodland-to-forest conversion compensated for forest losses. The widespread decline in woodlands demonstrates that they exist as a metastable state, created and maintained only under stable, low- and mixed-severity fire regimes. The loss of these keystone ecosystems portends the erosion of landscape resilience-as remaining woodlands disappear, their ability to buffer for forest losses will decline as well, increasing the risk of abrupt and persistent ecosystem transitions under shifting fire regimes and warmer future climates.},
}
MeSH Terms:
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hide MeSH Terms
*Forests
*Fires
*Conservation of Natural Resources
Climate Change
Satellite Imagery
Ecosystem
Wildfires
Trees
Northwestern United States
RevDate: 2026-10-12
CmpDate: 2026-10-10
Exploratory secondary analysis of published aggregate growth and metabolic data in children born small for gestational age treated with growth hormone.
Frontiers in endocrinology, 17:1942946.
PURPOSE: To describe published annual growth and metabolic summaries for children born small for gestational age (SGA) treated with growth hormone and to define the limits of inference from aggregate registry data.
METHODS: We conducted an exploratory secondary analysis of published aggregate means, standard deviations, and outcome-specific sample sizes from baseline through year 5 in the SGA subgroup of the Korean LG Growth Study, with up to 318 children represented at baseline. Primary reporting was descriptive and included annual values, changes from baseline, and measurement availability. Exploratory slope models were retained only as supplementary sensitivity analyses. The published aggregate LGS summaries available for the present secondary analysis did not include longitudinal blood-pressure measurements or cardiovascular-event records.
RESULTS: Height SDS was -2.38 at baseline and -0.76 at year 5, weight SDS was -2.21 and -0.84, and BMI SDS was -0.93 and -0.64. The published mean AST was 32.07 IU/L at baseline and 24.28 IU/L at year 5, whereas several other metabolic markers had higher year-5 means. Median year-5 measurement availability was 12.8% of outcome-specific baseline counts, and only six triglyceride measurements were available at year 5. The markedly reduced outcome-specific sample sizes at later follow-up points substantially limit interpretation of long-term patterns.
CONCLUSION: Published annual mean values differed across follow-up, but changing outcome-specific samples and the unavailability of individual-level longitudinal data to the present secondary analysis preclude estimation of within-child change, causal treatment effects, or cardiovascular risk.
Additional Links: PMID-42857505
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Citation:
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@article {pmid42857505,
year = {2026},
author = {Yuan, H and Wang, Y and Lu, Z and Zhang, Z and Luo, S and Wang, Y},
title = {Exploratory secondary analysis of published aggregate growth and metabolic data in children born small for gestational age treated with growth hormone.},
journal = {Frontiers in endocrinology},
volume = {17},
number = {},
pages = {1942946},
pmid = {42857505},
issn = {1664-2392},
mesh = {Humans ; *Infant, Small for Gestational Age/growth & development/metabolism ; *Human Growth Hormone/therapeutic use ; Female ; Infant, Newborn ; Male ; Secondary Data Analysis ; *Growth Disorders/drug therapy/metabolism ; Body Height/drug effects ; Child, Preschool ; *Child Development/drug effects ; Child ; },
abstract = {PURPOSE: To describe published annual growth and metabolic summaries for children born small for gestational age (SGA) treated with growth hormone and to define the limits of inference from aggregate registry data.
METHODS: We conducted an exploratory secondary analysis of published aggregate means, standard deviations, and outcome-specific sample sizes from baseline through year 5 in the SGA subgroup of the Korean LG Growth Study, with up to 318 children represented at baseline. Primary reporting was descriptive and included annual values, changes from baseline, and measurement availability. Exploratory slope models were retained only as supplementary sensitivity analyses. The published aggregate LGS summaries available for the present secondary analysis did not include longitudinal blood-pressure measurements or cardiovascular-event records.
RESULTS: Height SDS was -2.38 at baseline and -0.76 at year 5, weight SDS was -2.21 and -0.84, and BMI SDS was -0.93 and -0.64. The published mean AST was 32.07 IU/L at baseline and 24.28 IU/L at year 5, whereas several other metabolic markers had higher year-5 means. Median year-5 measurement availability was 12.8% of outcome-specific baseline counts, and only six triglyceride measurements were available at year 5. The markedly reduced outcome-specific sample sizes at later follow-up points substantially limit interpretation of long-term patterns.
CONCLUSION: Published annual mean values differed across follow-up, but changing outcome-specific samples and the unavailability of individual-level longitudinal data to the present secondary analysis preclude estimation of within-child change, causal treatment effects, or cardiovascular risk.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Infant, Small for Gestational Age/growth & development/metabolism
*Human Growth Hormone/therapeutic use
Female
Infant, Newborn
Male
Secondary Data Analysis
*Growth Disorders/drug therapy/metabolism
Body Height/drug effects
Child, Preschool
*Child Development/drug effects
Child
RevDate: 2026-10-13
CmpDate: 2026-10-11
The genome sequence of a gelechiid moth, Chionodes viduella (Fabricius, 1794) (Lepidoptera: Gelechiidae).
Wellcome open research, 11:641.
We present a genome assembly from a male specimen of Chionodes viduella (gelechiid moth; Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 583.75 megabases and 582.01 megabases. Most of haplotype 1 (99.83%) and haplotype 2 (99.55%) are each scaffolded into 29 chromosomal pseudomolecules, including the Z sex chromosome. Hi-C data were used to phase the assembly, and both haplotypes were assembled to chromosome level. The mitochondrial genome has also been assembled, with a length of 15.46 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
Additional Links: PMID-42859424
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Citation:
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@article {pmid42859424,
year = {2026},
author = {Mutanen, M and Vallinmäki, M and Huemer, P and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of a gelechiid moth, Chionodes viduella (Fabricius, 1794) (Lepidoptera: Gelechiidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {641},
pmid = {42859424},
issn = {2398-502X},
support = {/WT_/Wellcome Trust/United Kingdom ; },
abstract = {We present a genome assembly from a male specimen of Chionodes viduella (gelechiid moth; Arthropoda; Insecta; Lepidoptera; Gelechiidae). The assembly contains two haplotypes with total lengths of 583.75 megabases and 582.01 megabases. Most of haplotype 1 (99.83%) and haplotype 2 (99.55%) are each scaffolded into 29 chromosomal pseudomolecules, including the Z sex chromosome. Hi-C data were used to phase the assembly, and both haplotypes were assembled to chromosome level. The mitochondrial genome has also been assembled, with a length of 15.46 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-11
Sputum and oral microbiota profiles are associated with long COVID severity and phenotype post-hospitalisation: a UK multicentre, prospective cohort study.
The European respiratory journal pii:13993003.01162-2026 [Epub ahead of print].
BACKGROUND: Acute COVID-19 alters the airway microbiota. Whether these changes persist post-COVID-19 and contribute to long COVID is unknown. We aimed to describe the microbiota by long COVID severity and subtype, and identify links with inflammation.
METHODS: Adults were prospectively recruited to the longitudinal UK Post-hospitalisation COVID-19 study (PHOSP-COVID). Patients were grouped by previously described "severity clusters" (of ongoing health impairments) and symptom subgroups. Oral and sputum microbiota (at 6 months post-discharge) were characterised through 16S ribosomal RNA gene amplicon sequencing, and microbiota diversity was assessed. Co-occurrence network analysis identified keystone taxa. Associations between keystone taxa and plasma inflammatory proteins were assessed through Spearman's rank correlations.
RESULTS: 771 participants had their microbiota assessed. Of participants with oral rinses and "severity cluster" assignment (mean age 57.5 years), 278 out of 722 (38.5%) were women. The "very severe" cluster, in which disease was predominantly pulmonary in nature, was associated with a distinct microbiota profile post-COVID-19. Reduced lung function was associated with a distinct oral microbiota profile. Persistent neurocognitive symptoms were associated with a distinct oral microbiota profile, while gastrointestinal symptoms were associated with a distinct sputum microbiota profile. Microbiota keystone taxa shifted to a higher prevalence of lactic acid bacteria associated with worse health outcomes. Lactic acid bacteria abundance was associated with elevated blood inflammatory proteins.
CONCLUSION: Distinct oral and sputum microbiota profiles were associated with pulmonary function and with neurocognitive and gastrointestinal symptoms in long COVID. Shifts in keystone microbiota taxa linked with inflammation, based on worse health outcomes, suggest a potential role change for lactic acid bacteria, which may be associated with the host immune response.
Additional Links: PMID-42860277
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PubMed:
Citation:
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@article {pmid42860277,
year = {2026},
author = {Alferes de Lima Headley, D and Richardson, H and Hennayake, C and Eke, Z and Stobo, J and Long, MB and Leavy, OC and Richardson, M and Elneima, O and McAuley, HJC and Shikotra, A and Singapuri, A and Sereno, M and Saunders, RM and Harris, VC and Houchen-Wolloff, L and Greening, NJ and Ntotsis, K and Lozano-Rojas, D and Guillen-Guio, B and Harrison, EM and Docherty, AB and Kerr, S and Lone, NI and Quint, JK and Sheikh, A and Thorpe, M and Zheng, B and Efstathiou, C and Taquet, M and Stewart, ID and Chalder, T and Davies, MJ and De Soyza, A and Geddes, JR and Greenhalf, W and Howard, LS and Jacob, J and Jenkins, RG and Man, WD and McCann, GP and Neubauer, S and Openshaw, PJM and Porter, JC and Rowland, MJ and Thomas, D and Toshner, M and Heller, S and Scott, JT and Semple, MG and Singh, SJ and Aul, R and Beirne, P and Bolton, CE and Brown, JS and Choudhury, G and Diar Bakerly, N and Easom, N and Echevarria, C and Fuld, J and Hurst, JR and Jones, M and Parekh, D and Pfeffer, P and Rahman, NM and Rowland-Jones, S and Shah, AM and Wootton, DG and Lewis, K and Heaney, LG and Ho, LP and Horsley, A and Marks, M and Poinasamy, K and Raman, B and Wain, LV and Evans, RA and Brightling, CE and Molyneaux, PL and Chalmers, JD and , },
title = {Sputum and oral microbiota profiles are associated with long COVID severity and phenotype post-hospitalisation: a UK multicentre, prospective cohort study.},
journal = {The European respiratory journal},
volume = {},
number = {},
pages = {},
doi = {10.1183/13993003.01162-2026},
pmid = {42860277},
issn = {1399-3003},
abstract = {BACKGROUND: Acute COVID-19 alters the airway microbiota. Whether these changes persist post-COVID-19 and contribute to long COVID is unknown. We aimed to describe the microbiota by long COVID severity and subtype, and identify links with inflammation.
METHODS: Adults were prospectively recruited to the longitudinal UK Post-hospitalisation COVID-19 study (PHOSP-COVID). Patients were grouped by previously described "severity clusters" (of ongoing health impairments) and symptom subgroups. Oral and sputum microbiota (at 6 months post-discharge) were characterised through 16S ribosomal RNA gene amplicon sequencing, and microbiota diversity was assessed. Co-occurrence network analysis identified keystone taxa. Associations between keystone taxa and plasma inflammatory proteins were assessed through Spearman's rank correlations.
RESULTS: 771 participants had their microbiota assessed. Of participants with oral rinses and "severity cluster" assignment (mean age 57.5 years), 278 out of 722 (38.5%) were women. The "very severe" cluster, in which disease was predominantly pulmonary in nature, was associated with a distinct microbiota profile post-COVID-19. Reduced lung function was associated with a distinct oral microbiota profile. Persistent neurocognitive symptoms were associated with a distinct oral microbiota profile, while gastrointestinal symptoms were associated with a distinct sputum microbiota profile. Microbiota keystone taxa shifted to a higher prevalence of lactic acid bacteria associated with worse health outcomes. Lactic acid bacteria abundance was associated with elevated blood inflammatory proteins.
CONCLUSION: Distinct oral and sputum microbiota profiles were associated with pulmonary function and with neurocognitive and gastrointestinal symptoms in long COVID. Shifts in keystone microbiota taxa linked with inflammation, based on worse health outcomes, suggest a potential role change for lactic acid bacteria, which may be associated with the host immune response.},
}
RevDate: 2026-10-10
CmpDate: 2026-10-09
The microbiome-nitric oxide axis in cancer immunotherapy: a targeted qualitative systematic review of mechanistic and translational evidence.
Frontiers in immunology, 17:1904698.
BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, but responses vary substantially among patients. Clinical studies have associated features of the gut microbiome with ICI outcomes, while experimental evidence suggests that microbial metabolites and nitric oxide (NO)-related pathways may influence antitumor immunity and tumor vascular biology. This qualitative systematic review evaluated the evidence supporting a proposed microbiome-NO-ICI framework.
METHODS: Five databases were searched for peer-reviewed studies published between January 2000 and August 2025. Fifty-four distinct primary studies met the eligibility criteria, comprising 21 clinical studies, 19 animal studies and 14 in vitro mechanistic studies. Evidence was synthesized narratively according to study type and thematic domain.
RESULTS: Several clinical cohorts associated enrichment of Akkermansia muciniphila, Faecalibacterium prausnitzii, Bifidobacterium species and other short-chain fatty acid-producing taxa with favorable ICI outcomes; however, the reported microbial signatures varied across cohorts and analytical platforms. Microbial-transfer experiments and early non-randomized fecal microbiota transplantation studies provide proof-of-concept evidence that microbiome composition can influence antitumor immune responses, although the clinical intervention evidence remains preliminary. Animal and cellular studies indicate that microbial metabolites, host nitric oxide synthase pathways and reactive nitrogen signaling can affect immune-cell function, vascular regulation and tumor hypoxia. Direct clinical evidence linking microbiota-mediated nitrate reduction or dietary nitrate supplementation to improved ICI outcomes is lacking. Human dietary nitrate studies conducted outside oncology demonstrate increased circulating nitrate and nitrite and measurable vascular effects but do not establish anticancer or ICI efficacy.
CONCLUSION: The microbiome-NO-ICI axis should be regarded as a testable integrative model linking microbial ecology, immune regulation and tumor vascular biology. Current evidence supports biological plausibility but is insufficient to establish NO- or microbiome-directed interventions as effective adjuncts to ICI therapy. Prospective mechanistic studies and biomarker-driven clinical trials are required before therapeutic translation.
Additional Links: PMID-42851568
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Citation:
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@article {pmid42851568,
year = {2026},
author = {Enwere, M and Bryan, NS and Onu, A and Neufeld, M and El-Hussein, MT and Yakub, I and Omale, C and Onyedike, O and Atim, T and Agbeyomi, O and Davies, E and Okeke, UE and Holmes, L},
title = {The microbiome-nitric oxide axis in cancer immunotherapy: a targeted qualitative systematic review of mechanistic and translational evidence.},
journal = {Frontiers in immunology},
volume = {17},
number = {},
pages = {1904698},
pmid = {42851568},
issn = {1664-3224},
mesh = {Humans ; *Neoplasms/therapy/immunology/metabolism/microbiology ; *Nitric Oxide/metabolism/immunology ; Animals ; *Gastrointestinal Microbiome/immunology ; *Immunotherapy/methods ; *Immune Checkpoint Inhibitors/therapeutic use ; Fecal Microbiota Transplantation ; Translational Research, Biomedical ; },
abstract = {BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, but responses vary substantially among patients. Clinical studies have associated features of the gut microbiome with ICI outcomes, while experimental evidence suggests that microbial metabolites and nitric oxide (NO)-related pathways may influence antitumor immunity and tumor vascular biology. This qualitative systematic review evaluated the evidence supporting a proposed microbiome-NO-ICI framework.
METHODS: Five databases were searched for peer-reviewed studies published between January 2000 and August 2025. Fifty-four distinct primary studies met the eligibility criteria, comprising 21 clinical studies, 19 animal studies and 14 in vitro mechanistic studies. Evidence was synthesized narratively according to study type and thematic domain.
RESULTS: Several clinical cohorts associated enrichment of Akkermansia muciniphila, Faecalibacterium prausnitzii, Bifidobacterium species and other short-chain fatty acid-producing taxa with favorable ICI outcomes; however, the reported microbial signatures varied across cohorts and analytical platforms. Microbial-transfer experiments and early non-randomized fecal microbiota transplantation studies provide proof-of-concept evidence that microbiome composition can influence antitumor immune responses, although the clinical intervention evidence remains preliminary. Animal and cellular studies indicate that microbial metabolites, host nitric oxide synthase pathways and reactive nitrogen signaling can affect immune-cell function, vascular regulation and tumor hypoxia. Direct clinical evidence linking microbiota-mediated nitrate reduction or dietary nitrate supplementation to improved ICI outcomes is lacking. Human dietary nitrate studies conducted outside oncology demonstrate increased circulating nitrate and nitrite and measurable vascular effects but do not establish anticancer or ICI efficacy.
CONCLUSION: The microbiome-NO-ICI axis should be regarded as a testable integrative model linking microbial ecology, immune regulation and tumor vascular biology. Current evidence supports biological plausibility but is insufficient to establish NO- or microbiome-directed interventions as effective adjuncts to ICI therapy. Prospective mechanistic studies and biomarker-driven clinical trials are required before therapeutic translation.},
}
MeSH Terms:
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hide MeSH Terms
Humans
*Neoplasms/therapy/immunology/metabolism/microbiology
*Nitric Oxide/metabolism/immunology
Animals
*Gastrointestinal Microbiome/immunology
*Immunotherapy/methods
*Immune Checkpoint Inhibitors/therapeutic use
Fecal Microbiota Transplantation
Translational Research, Biomedical
RevDate: 2026-10-09
A multiregional serosurvey of RNA virus-reactive antibodies in bats and rodents reveals the enzootic presence of flavi- and paramyxoviruses in African Pteropodidae.
PLoS neglected tropical diseases, 20(10):e0013689 pii:PNTD-D-25-01917 [Epub ahead of print].
Bats and rodents have been identified as reservoir hosts of diverse RNA viruses that pose potential risks to humans. However, overall virus prevalence in wildlife and underlying factors determining the zoonotic potential of reservoir-borne viruses remain poorly characterized. Virus detection often relies on the identification of viral nucleotide sequences and may therefore be limited by variable virus concentration, tissue tropism, sample quality, and duration of infection. In this study, we applied a multiplex immunofluorescence assay to examine bat and rodent seroprevalence against 14 different human pathogenic RNA viruses spanning seven virus families (Coronaviridae, Flaviviridae, Hantaviridae, Paramyxoviridae, Phenuiviridae, Pneumoviridae, Togaviridae). We retrospectively analyzed 1,135 bat (16 species) and 454 rodent (15 species) blood or transudate specimens collected at 63 sites in seven countries. The tropical bats in our dataset exhibited notably high rates of seropositivity against certain virus families (Flaviviridae: 42.7%; Paramyxoviridae: 67.7%; Togaviridae: 7.5%). Although confounding factors and sparse data continue to pose challenges to identifying correlates of RNA virus infection in wildlife, multivariable logistic regression models were created to provisionally evaluate the association of tropical bat characteristics with seropositivity. Preliminary findings indicate that large colony size, found among species such as Eidolon helvum and Rousettus aegyptiacus, is a predictor within this dataset of orthoflavi- and orthorubulavirus seroprevalence, consistent with the communal spread of bat-adapted viruses.
Additional Links: PMID-42853873
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@article {pmid42853873,
year = {2026},
author = {Emanuel, J and Papies, J and Meiners, L and Veith, T and Corman, VM and Binger, T and Lattwein, E and Kümmerer, BM and Zweerink, S and Fechner, K and Gloza-Rausch, F and Cottontail, V and Maganga, GD and Schmidt-Chanasit, J and Vallo, P and Oppong, SK and Tschapka, M and Reusken, CBEM and Ulrich, RG and Leroy, EM and Drexler, JF and Jones, TC and Drosten, C and Müller, MA},
title = {A multiregional serosurvey of RNA virus-reactive antibodies in bats and rodents reveals the enzootic presence of flavi- and paramyxoviruses in African Pteropodidae.},
journal = {PLoS neglected tropical diseases},
volume = {20},
number = {10},
pages = {e0013689},
doi = {10.1371/journal.pntd.0013689},
pmid = {42853873},
issn = {1935-2735},
abstract = {Bats and rodents have been identified as reservoir hosts of diverse RNA viruses that pose potential risks to humans. However, overall virus prevalence in wildlife and underlying factors determining the zoonotic potential of reservoir-borne viruses remain poorly characterized. Virus detection often relies on the identification of viral nucleotide sequences and may therefore be limited by variable virus concentration, tissue tropism, sample quality, and duration of infection. In this study, we applied a multiplex immunofluorescence assay to examine bat and rodent seroprevalence against 14 different human pathogenic RNA viruses spanning seven virus families (Coronaviridae, Flaviviridae, Hantaviridae, Paramyxoviridae, Phenuiviridae, Pneumoviridae, Togaviridae). We retrospectively analyzed 1,135 bat (16 species) and 454 rodent (15 species) blood or transudate specimens collected at 63 sites in seven countries. The tropical bats in our dataset exhibited notably high rates of seropositivity against certain virus families (Flaviviridae: 42.7%; Paramyxoviridae: 67.7%; Togaviridae: 7.5%). Although confounding factors and sparse data continue to pose challenges to identifying correlates of RNA virus infection in wildlife, multivariable logistic regression models were created to provisionally evaluate the association of tropical bat characteristics with seropositivity. Preliminary findings indicate that large colony size, found among species such as Eidolon helvum and Rousettus aegyptiacus, is a predictor within this dataset of orthoflavi- and orthorubulavirus seroprevalence, consistent with the communal spread of bat-adapted viruses.},
}
RevDate: 2026-10-10
The Impact of Trauma-Focused Cognitive Behavior Therapy for Psychosis on Post-Traumatic Stress Symptoms in Daily Life: Experience Sampling Methodology Outcomes of the STAR Trial.
Psychotherapy and psychosomatics pii:000553975 [Epub ahead of print].
INTRODUCTION: People with psychosis have high rates of post-traumatic stress disorder (PTSD). The Study of Trauma And Recovery (STAR) randomized controlled trial found that a trauma-focused cognitive behavior therapy for psychosis (TF-CBTp) added to treatment-as-usual (TAU) reduced PTSD symptoms in people with psychosis compared to TAU only. We hypothesized that TF-CBTp would also reduce PTSD symptoms in daily life, using experience sampling methodology (ESM), which would be associated with improvements on a clinical measure of PTSD.
METHODS: Participants were adults with PTSD and schizophrenia spectrum diagnoses, a subsample of the STAR trial (N = 153; TF-CBTp+TAU = 73, TAU = 80). Participants completed ESM assessments of intrusive memories, hyperarousal, dissociation, avoidance, and negative trauma-related cognitions through a smartphone app multiple times daily over 6 days, at baseline and 9 months post-randomization (end of therapy).
RESULTS: No between-group differences were found in ESM measures of momentary PTSD symptoms at 9 months. Significant timepoint × therapy interactions indicated greater decrease over time in hyperarousal, negative cognitions, and avoidance, and in variability of intrusive memories, in TF-CBTp+TAU compared to TAU. ESM measures at 9 months were significantly associated with improvements on the Clinician-Administered PTSD Scale for DSM-5.
CONCLUSION: While findings are tentatively in favor of TF-CBTp, the robust reductions in PTSD symptoms found in the STAR trial using retrospective outcome measures were not fully replicated with ESM, suggesting these methodologies may be capturing different features of symptom expression and processes of therapeutic change. Including both approaches in future research could provide a fuller picture of therapy effects on "in-the-moment" versus reflective reports of experiences.
Additional Links: PMID-42658758
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@article {pmid42658758,
year = {2026},
author = {Rickard, M and Panayi, P and Hardy, A and Bentall, R and Emsley, R and Steel, C and Dudley, R and Underwood, R and Lafit, G and Edwards, CJ and Myin-Germeys, I and Peters, E and Varese, F},
title = {The Impact of Trauma-Focused Cognitive Behavior Therapy for Psychosis on Post-Traumatic Stress Symptoms in Daily Life: Experience Sampling Methodology Outcomes of the STAR Trial.},
journal = {Psychotherapy and psychosomatics},
volume = {},
number = {},
pages = {1},
doi = {10.1159/pps/aemag010},
pmid = {42658758},
issn = {1423-0348},
abstract = {INTRODUCTION: People with psychosis have high rates of post-traumatic stress disorder (PTSD). The Study of Trauma And Recovery (STAR) randomized controlled trial found that a trauma-focused cognitive behavior therapy for psychosis (TF-CBTp) added to treatment-as-usual (TAU) reduced PTSD symptoms in people with psychosis compared to TAU only. We hypothesized that TF-CBTp would also reduce PTSD symptoms in daily life, using experience sampling methodology (ESM), which would be associated with improvements on a clinical measure of PTSD.
METHODS: Participants were adults with PTSD and schizophrenia spectrum diagnoses, a subsample of the STAR trial (N = 153; TF-CBTp+TAU = 73, TAU = 80). Participants completed ESM assessments of intrusive memories, hyperarousal, dissociation, avoidance, and negative trauma-related cognitions through a smartphone app multiple times daily over 6 days, at baseline and 9 months post-randomization (end of therapy).
RESULTS: No between-group differences were found in ESM measures of momentary PTSD symptoms at 9 months. Significant timepoint × therapy interactions indicated greater decrease over time in hyperarousal, negative cognitions, and avoidance, and in variability of intrusive memories, in TF-CBTp+TAU compared to TAU. ESM measures at 9 months were significantly associated with improvements on the Clinician-Administered PTSD Scale for DSM-5.
CONCLUSION: While findings are tentatively in favor of TF-CBTp, the robust reductions in PTSD symptoms found in the STAR trial using retrospective outcome measures were not fully replicated with ESM, suggesting these methodologies may be capturing different features of symptom expression and processes of therapeutic change. Including both approaches in future research could provide a fuller picture of therapy effects on "in-the-moment" versus reflective reports of experiences.},
}
RevDate: 2026-10-08
Economic assessment of burden of animal diseases in donkeys in Ethiopia.
Preventive veterinary medicine, 257:107043 pii:S0167-5877(26)00262-X [Epub ahead of print].
Working donkeys play a crucial role in Ethiopia's household and agricultural economies but they carry a massive, neglected burden of disease. There is currently limited understanding of the size and scale of this burden. This study aimed to quantify the burden of disease in working donkeys in Ethiopia using the Animal Health Loss Envelope (AHLE) metric. The AHLE measures all cause disease burden by estimating the gap between actual production and potential output in an ideal, animal disease-free scenario. An enterprise budget analysis was conducted under two health scenarios (current and ideal) using a stochastic dynamic population model which captures income generated, expenditure and losses. The difference between the enterprise budget from the current and ideal scenarios represents the AHLE. The models were parameterised using data from household surveys, focus group discussions, key informant interviews, expert elicitation, and secondary data from the literature. The total AHLE was estimated at USD 116 (95% PI: 96-142) per average donkey owning household per year which equates to 28% of an average households potential income from donkeys. When extrapolated across the national herd of 10.2 million donkeys this equates to an estimated absolute loss of USD 646 million (95% PI: 566-739). Morbidity losses constituted the largest component of the AHLE, exceeding 70% across all production systems (commercial, domestic agricultural and domestic pastoral) and in contrast spending on animal health contributed the smallest portion of the AHLE (0.8-2.1% across the three systems). External and non-infectious causes imposed the highest proportion of health-related losses, contributing significantly to production losses. Lameness, modelled separately as an example of attributing part of the AHLE to a specific disease, accounted for 12.8% of the total AHLE in the commercial system (USD 8 million). These estimates provide evidence to inform policies and interventions aimed at improving donkey health and welfare to the benefit of communities reliant on these animals.
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@article {pmid42849111,
year = {2026},
author = {Asteraye, GB and Chaters, GL and Jobling, R and Pinchbeck, G and Meyer, A and Larkins, A and Knight-Jones, TJD and Jemberu, WT and Rushton, J},
title = {Economic assessment of burden of animal diseases in donkeys in Ethiopia.},
journal = {Preventive veterinary medicine},
volume = {257},
number = {},
pages = {107043},
doi = {10.1016/j.prevetmed.2026.107043},
pmid = {42849111},
issn = {1873-1716},
abstract = {Working donkeys play a crucial role in Ethiopia's household and agricultural economies but they carry a massive, neglected burden of disease. There is currently limited understanding of the size and scale of this burden. This study aimed to quantify the burden of disease in working donkeys in Ethiopia using the Animal Health Loss Envelope (AHLE) metric. The AHLE measures all cause disease burden by estimating the gap between actual production and potential output in an ideal, animal disease-free scenario. An enterprise budget analysis was conducted under two health scenarios (current and ideal) using a stochastic dynamic population model which captures income generated, expenditure and losses. The difference between the enterprise budget from the current and ideal scenarios represents the AHLE. The models were parameterised using data from household surveys, focus group discussions, key informant interviews, expert elicitation, and secondary data from the literature. The total AHLE was estimated at USD 116 (95% PI: 96-142) per average donkey owning household per year which equates to 28% of an average households potential income from donkeys. When extrapolated across the national herd of 10.2 million donkeys this equates to an estimated absolute loss of USD 646 million (95% PI: 566-739). Morbidity losses constituted the largest component of the AHLE, exceeding 70% across all production systems (commercial, domestic agricultural and domestic pastoral) and in contrast spending on animal health contributed the smallest portion of the AHLE (0.8-2.1% across the three systems). External and non-infectious causes imposed the highest proportion of health-related losses, contributing significantly to production losses. Lameness, modelled separately as an example of attributing part of the AHLE to a specific disease, accounted for 12.8% of the total AHLE in the commercial system (USD 8 million). These estimates provide evidence to inform policies and interventions aimed at improving donkey health and welfare to the benefit of communities reliant on these animals.},
}
RevDate: 2026-10-08
CmpDate: 2026-10-08
Integration of Ecological Momentary Assessment and Intervention With Wearable-Based Digital Phenotypes to Treat Anxiety in Young Adults: Mixed Methods Experimental Study.
JMIR mHealth and uHealth, 14:e88919 pii:v14i1e88919.
BACKGROUND: Young adults report high levels of anxiety, yet their access to timely treatment remains limited. Mobile-based digital therapeutics, particularly ecological momentary assessment and intervention (EMA/EMI), offer a promising approach to deliver context-responsive care. The integration of wearable-derived digital phenotypes with digital therapeutics may enhance the personalization of feedback in such interventions, but empirical evidence from real-world settings remains scarce.
OBJECTIVE: This study examined the real-world applicability and effectiveness of an EMA/EMI-based digital therapeutic, ANZEILAX-Green (HAII Corp), for use in anxiety reduction in young adults and investigated how personalized feedback generated by combining EMA/EMI data with wearable-based digital phenotypes ameliorates symptoms and promotes self-management and user engagement.
METHODS: An 8-week exploratory experimental study was conducted with young adults aged 19-39 years. Participants used a smartphone app in which EMA/EMI modules had been integrated with a smartwatch that continuously collected digital phenotyping data, including heart rate, sleep, and activity. Psychological outcomes were assessed using the Generalized Anxiety Disorder 7-item scale (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) at baseline and weeks 2, 4, 6, and 8, and the Rosenberg Self-Esteem Scale (RSES) at baseline and week 8. Quantitative changes were analyzed using paired-samples t tests and repeated-measures ANOVA, and qualitative interviews were thematically analyzed to identify user experience mechanisms and design implications.
RESULTS: In all, 29 participants were included in the final analysis. Significant improvements were observed in their GAD-7 (mean difference -4.79, 95% CI -6.56 to -3.02; Cohen d=1.03; P<.001), PHQ-9 (mean difference -3.86, 95% CI -5.79 to -1.93; Cohen d=0.76; P<.001), and RSES scores (mean difference +5.21, 95% CI 3.47 to 6.95; Cohen d=1.14; P<.001). Consistent improvements in GAD-7 scores were observed across the assessment points, with statistically significant reductions from week 4 onward. Participants demonstrated high adherence, completing 80% of the EMA/EMI prompts. The digital phenotype showed trends of increased deep sleep and reduced mobility, and sleep indicators were significantly correlated with depressive symptoms. Analysis of the interview findings revealed 5 mechanisms: enhanced self-awareness, data-driven reflection, behavioral change, intrinsic motivation, and extension of treatment into daily life.
CONCLUSIONS: EMA/EMI-based digital therapeutics integrated with wearable-derived digital phenotypes are feasible and acceptable for use by young adults and were associated with within-group reductions in anxiety, suggesting acceptable efficacy, though this warrants confirmation in a controlled trial. The combination of real-time self-reported assessments of emotional states and passive physiological monitoring enables personalized feedback suited to users' emotional and physiological states. These findings offer empirical and design insights for automated, personalized mental health intervention systems.
Additional Links: PMID-42849895
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@article {pmid42849895,
year = {2026},
author = {Song, H and Choi, Y and Park, J and Hwang, H and Kim, J and Park, C},
title = {Integration of Ecological Momentary Assessment and Intervention With Wearable-Based Digital Phenotypes to Treat Anxiety in Young Adults: Mixed Methods Experimental Study.},
journal = {JMIR mHealth and uHealth},
volume = {14},
number = {},
pages = {e88919},
doi = {10.2196/88919},
pmid = {42849895},
issn = {2291-5222},
mesh = {Humans ; *Ecological Momentary Assessment/standards/statistics & numerical data ; *Wearable Electronic Devices/standards/statistics & numerical data/trends ; Female ; Adult ; Male ; Young Adult ; Phenotype ; Surveys and Questionnaires ; *Anxiety/psychology/therapy ; Digital Health ; Psychometrics/instrumentation/methods ; },
abstract = {BACKGROUND: Young adults report high levels of anxiety, yet their access to timely treatment remains limited. Mobile-based digital therapeutics, particularly ecological momentary assessment and intervention (EMA/EMI), offer a promising approach to deliver context-responsive care. The integration of wearable-derived digital phenotypes with digital therapeutics may enhance the personalization of feedback in such interventions, but empirical evidence from real-world settings remains scarce.
OBJECTIVE: This study examined the real-world applicability and effectiveness of an EMA/EMI-based digital therapeutic, ANZEILAX-Green (HAII Corp), for use in anxiety reduction in young adults and investigated how personalized feedback generated by combining EMA/EMI data with wearable-based digital phenotypes ameliorates symptoms and promotes self-management and user engagement.
METHODS: An 8-week exploratory experimental study was conducted with young adults aged 19-39 years. Participants used a smartphone app in which EMA/EMI modules had been integrated with a smartwatch that continuously collected digital phenotyping data, including heart rate, sleep, and activity. Psychological outcomes were assessed using the Generalized Anxiety Disorder 7-item scale (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) at baseline and weeks 2, 4, 6, and 8, and the Rosenberg Self-Esteem Scale (RSES) at baseline and week 8. Quantitative changes were analyzed using paired-samples t tests and repeated-measures ANOVA, and qualitative interviews were thematically analyzed to identify user experience mechanisms and design implications.
RESULTS: In all, 29 participants were included in the final analysis. Significant improvements were observed in their GAD-7 (mean difference -4.79, 95% CI -6.56 to -3.02; Cohen d=1.03; P<.001), PHQ-9 (mean difference -3.86, 95% CI -5.79 to -1.93; Cohen d=0.76; P<.001), and RSES scores (mean difference +5.21, 95% CI 3.47 to 6.95; Cohen d=1.14; P<.001). Consistent improvements in GAD-7 scores were observed across the assessment points, with statistically significant reductions from week 4 onward. Participants demonstrated high adherence, completing 80% of the EMA/EMI prompts. The digital phenotype showed trends of increased deep sleep and reduced mobility, and sleep indicators were significantly correlated with depressive symptoms. Analysis of the interview findings revealed 5 mechanisms: enhanced self-awareness, data-driven reflection, behavioral change, intrinsic motivation, and extension of treatment into daily life.
CONCLUSIONS: EMA/EMI-based digital therapeutics integrated with wearable-derived digital phenotypes are feasible and acceptable for use by young adults and were associated with within-group reductions in anxiety, suggesting acceptable efficacy, though this warrants confirmation in a controlled trial. The combination of real-time self-reported assessments of emotional states and passive physiological monitoring enables personalized feedback suited to users' emotional and physiological states. These findings offer empirical and design insights for automated, personalized mental health intervention systems.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Ecological Momentary Assessment/standards/statistics & numerical data
*Wearable Electronic Devices/standards/statistics & numerical data/trends
Female
Adult
Male
Young Adult
Phenotype
Surveys and Questionnaires
*Anxiety/psychology/therapy
Digital Health
Psychometrics/instrumentation/methods
RevDate: 2026-10-11
CmpDate: 2026-10-09
The genome sequence of a douglasiid moth, Tinagma dryadis Staudinger, 1872 (Lepidoptera: Douglasiidae).
Wellcome open research, 11:632.
We present a genome assembly from a female specimen of Tinagma dryadis (Arthropoda; Insecta; Lepidoptera; Douglasiidae). The assembly contains two haplotypes with total lengths of 813.92 megabases and 692.99 megabases. Most of the haplotype 1 assembly (99.95%) was scaffolded into 22 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.42 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.
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@article {pmid42851284,
year = {2026},
author = {Mutanen, M and Vallinmäki, M and Kiljunen, N and Wright, CJ and Meier, JI and Blaxter, ML and , and , and , and , and , },
title = {The genome sequence of a douglasiid moth, Tinagma dryadis Staudinger, 1872 (Lepidoptera: Douglasiidae).},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {632},
pmid = {42851284},
issn = {2398-502X},
support = {/WT_/Wellcome Trust/United Kingdom ; },
abstract = {We present a genome assembly from a female specimen of Tinagma dryadis (Arthropoda; Insecta; Lepidoptera; Douglasiidae). The assembly contains two haplotypes with total lengths of 813.92 megabases and 692.99 megabases. Most of the haplotype 1 assembly (99.95%) was scaffolded into 22 chromosomal pseudomolecules, including the W and Z sex chromosomes. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 15.42 kilobases. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.},
}
RevDate: 2026-10-10
CmpDate: 2026-10-10
A legacy pollutant deciphered by multiomics toxicology and targeted remediation by a synthetic microbial consortium: a case study of 2-chloroacetophenone from abandoned chemical weapons.
Water research, 306:126776.
2-Chloroacetophenone (2-CA) is a typical organic poison found in abandoned Japanese chemical weapons, yet systematic research on its ecological risks and bioremediation strategies in aquatic environments remains scarce. Through a 120-day exposure experiment across three concentration gradients (10, 50, and 100 mg·L[-1]) coupled with multiomics analysis (physicochemical profiling, ionomics, 16S rRNA sequencing, metagenomics, and metabolomics), we systematically characterized the toxic effects of 2-CA on aquatic microbial communities and their molecular response mechanisms. The glutathione (GSH) metabolic pathway was identified as the core defense hub against 2-CA-induced oxidative stress, with multiomics data revealing its transition from compensatory activation to irreversible collapse. Guided by these mechanistic insights, we directionally isolated three cascade-degrading bacteria (Pseudomonas abietaniphila, Bacillus sp., and Arthrobacter agilis) harboring the key genes hapA, yjfP, and catA, which encode the three consecutive steps of Baeyer-Villiger oxidation, ester bond hydrolysis, and aromatic ring cleavage. The synthetic microbiome assembled from these three wild-type strains achieved 100% removal of 100 mg·L[-1] 2-CA within 24 h in vitro and within 10 days in simulated contaminated water, with the sequential detection of predicted intermediates (phenyl 2-chloroacetate, phenol, and pyruvic acid) confirming the operation of the cascade pathway. This study establishes a "toxicology diagnosis-functional deconstruction-synthetic reconstruction" paradigm, providing mechanistic understanding and a potential bioremediation strategy for organic toxicants at sites contaminated by relic Japanese chemical weapons, although direct ecotoxicological validation of detoxification remains to be confirmed.
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@article {pmid42680679,
year = {2026},
author = {Yang, X and Peng, AD and Cheng, JH and Huang, YH and Zhong, HT and Zhou, HT and Liu, PQ and Ji, XH and Li, C and Zhang, SR and Lai, JL and Luo, XG and Wen, G},
title = {A legacy pollutant deciphered by multiomics toxicology and targeted remediation by a synthetic microbial consortium: a case study of 2-chloroacetophenone from abandoned chemical weapons.},
journal = {Water research},
volume = {306},
number = {},
pages = {126776},
doi = {10.1016/j.watres.2026.126776},
pmid = {42680679},
issn = {1879-2448},
mesh = {Biodegradation, Environmental ; Multiomics ; *Water Pollutants, Chemical ; *Microbial Consortia ; *Acetophenones ; },
abstract = {2-Chloroacetophenone (2-CA) is a typical organic poison found in abandoned Japanese chemical weapons, yet systematic research on its ecological risks and bioremediation strategies in aquatic environments remains scarce. Through a 120-day exposure experiment across three concentration gradients (10, 50, and 100 mg·L[-1]) coupled with multiomics analysis (physicochemical profiling, ionomics, 16S rRNA sequencing, metagenomics, and metabolomics), we systematically characterized the toxic effects of 2-CA on aquatic microbial communities and their molecular response mechanisms. The glutathione (GSH) metabolic pathway was identified as the core defense hub against 2-CA-induced oxidative stress, with multiomics data revealing its transition from compensatory activation to irreversible collapse. Guided by these mechanistic insights, we directionally isolated three cascade-degrading bacteria (Pseudomonas abietaniphila, Bacillus sp., and Arthrobacter agilis) harboring the key genes hapA, yjfP, and catA, which encode the three consecutive steps of Baeyer-Villiger oxidation, ester bond hydrolysis, and aromatic ring cleavage. The synthetic microbiome assembled from these three wild-type strains achieved 100% removal of 100 mg·L[-1] 2-CA within 24 h in vitro and within 10 days in simulated contaminated water, with the sequential detection of predicted intermediates (phenyl 2-chloroacetate, phenol, and pyruvic acid) confirming the operation of the cascade pathway. This study establishes a "toxicology diagnosis-functional deconstruction-synthetic reconstruction" paradigm, providing mechanistic understanding and a potential bioremediation strategy for organic toxicants at sites contaminated by relic Japanese chemical weapons, although direct ecotoxicological validation of detoxification remains to be confirmed.},
}
MeSH Terms:
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Biodegradation, Environmental
Multiomics
*Water Pollutants, Chemical
*Microbial Consortia
*Acetophenones
RevDate: 2026-10-08
CmpDate: 2026-10-08
[Possible use of public mortality data from Spanish National Institute of Statistics database to study how air pollutants may impact mortality rates in Spain].
Revista espanola de salud publica, 100: pii:e202610069.
OBJECTIVE: Relationship between NO2, SO2, CO, PM2,5, PM10, COVNM (non-methane volatile organic compounds) and all-cause mortality or myocardial ischaemic mortality has been thoroughly studied. Levels of such pollutants have been reduced according to World Health Organization guidelines with no follow-up of their impact on mortality rates. Our goal was to explore the relationship between air pollutants and all-cause/myocardial ischaemic mortality.
METHODS: A descriptive longitudinal ecological study was carried out to compare National Institute of Statistics mortality rates, both all-cause and myocardial ischaemic deaths, as a whole, separated by sexes and age ranges to air pollutants brute emissions and average PM10 and PM2,5 concentrations nation-wide from 2000 to 2021, using lineal o logarithmic regression and multiple lineal regression.
RESULTS: All-cause mortality showed low correlation and regression with air pollutants except when studied by age-ranges. Myocardial ischaemic mortality did show significant correlation (coefficients over 0,7) and regression, as a whole, and while disgregated by sexes or ages. There is high correlation and confusion among the air pollutants, but no interactions were detected. R[2] was higher in all-cause mortality for men and young ones; in myocardial ischaemic mortality, for women and age gap from sixty-seventy-nine. Most relevant air pollutants changed for different age-gaps.
CONCLUSIONS: The study shows relationship between mortality and air pollutants, overestimating their importance according to previous research. Data referred to specific entities or different age-gaps were more accurate. Using data on shorter time-lapses and areas would increase precission.
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@article {pmid42847321,
year = {2026},
author = {Angulo Ardoy, M},
title = {[Possible use of public mortality data from Spanish National Institute of Statistics database to study how air pollutants may impact mortality rates in Spain].},
journal = {Revista espanola de salud publica},
volume = {100},
number = {},
pages = {},
pmid = {42847321},
issn = {2173-9110},
mesh = {Spain/epidemiology ; Female ; Humans ; *Air Pollutants/adverse effects/analysis ; Male ; *Mortality/trends ; Myocardial Ischemia/mortality ; Databases, Factual ; Longitudinal Studies ; Middle Aged ; Aged ; },
abstract = {OBJECTIVE: Relationship between NO2, SO2, CO, PM2,5, PM10, COVNM (non-methane volatile organic compounds) and all-cause mortality or myocardial ischaemic mortality has been thoroughly studied. Levels of such pollutants have been reduced according to World Health Organization guidelines with no follow-up of their impact on mortality rates. Our goal was to explore the relationship between air pollutants and all-cause/myocardial ischaemic mortality.
METHODS: A descriptive longitudinal ecological study was carried out to compare National Institute of Statistics mortality rates, both all-cause and myocardial ischaemic deaths, as a whole, separated by sexes and age ranges to air pollutants brute emissions and average PM10 and PM2,5 concentrations nation-wide from 2000 to 2021, using lineal o logarithmic regression and multiple lineal regression.
RESULTS: All-cause mortality showed low correlation and regression with air pollutants except when studied by age-ranges. Myocardial ischaemic mortality did show significant correlation (coefficients over 0,7) and regression, as a whole, and while disgregated by sexes or ages. There is high correlation and confusion among the air pollutants, but no interactions were detected. R[2] was higher in all-cause mortality for men and young ones; in myocardial ischaemic mortality, for women and age gap from sixty-seventy-nine. Most relevant air pollutants changed for different age-gaps.
CONCLUSIONS: The study shows relationship between mortality and air pollutants, overestimating their importance according to previous research. Data referred to specific entities or different age-gaps were more accurate. Using data on shorter time-lapses and areas would increase precission.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Spain/epidemiology
Female
Humans
*Air Pollutants/adverse effects/analysis
Male
*Mortality/trends
Myocardial Ischemia/mortality
Databases, Factual
Longitudinal Studies
Middle Aged
Aged
RevDate: 2026-10-09
CmpDate: 2026-10-08
A scoping review of e/mHealth interventions for weight management in racial and ethnic minority adults in the United States.
Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 60(1):.
IMPORTANCE: Obesity and chronic diseases disproportionately burden racial/ethnic minority adults in the United States (U.S.) (eg, Black, Hispanic/Latino, Asian, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander), partially owing to barriers to receiving obesity treatment. While eHealth/mHealth-supported interventions offer a potential scalable solution and have proliferated in recent years, the last evidence synthesis was published in 2018.
OBJECTIVE: Given the wide variation in intervention approaches, we aimed to map current evidence on weight management programs targeting U.S. racial and ethnic minority adults. We sought to understand the e/mHealth tools used, the extent to which interventions were tailored, and how they addressed barriers and achieved effectiveness in reducing health disparities.
METHODS: We performed a Joanna Briggs Institute/Preferred Reporting Items for systematic reviews and meta-analyses and related scoping review guidance-guided search of MEDLINE, Cochrane, Embase, CINAHL Plus, and PsycINFO (inception-June 2025) for U.S. English-language studies (>50% minority adults ≥18 y, BMI ≥ 25 kg/m²) using electronic/mobile health (e/mHealth) for weight management.
RESULTS: Dual review of 4811 records yielded 51 studies (45 randomized controlled trials (RCTs)). Most studies used smartphone applications, a form of messaging to phones, and/or wearables (86%; 35/51) as opposed to other eHealth approaches. Interventions were culturally tailored in 34 studies (67%), yet few used co-design methods with the target population (3/51).
CONCLUSIONS: Interventions that use e/mHealth show moderate promise for scalable weight management, with available but uneven tailoring. Short-term/individual designs limit equity and sustainability, especially for underrepresented men and rural groups. Prioritization of co-designed, social determinants of health (SDOH) and theory-grounded (eg, socio-ecological) trials ≥12 months is necessary for scalable, responsive solutions.
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@article {pmid42847409,
year = {2026},
author = {Ajilogba, CF and Briggs, RP and Battalio, SL and Nguyen, C and Wafford, E and Marchese, SH and Spring, B and Pfammatter, AF},
title = {A scoping review of e/mHealth interventions for weight management in racial and ethnic minority adults in the United States.},
journal = {Annals of behavioral medicine : a publication of the Society of Behavioral Medicine},
volume = {60},
number = {1},
pages = {},
doi = {10.1093/abm/kaag062},
pmid = {42847409},
issn = {1532-4796},
support = {F31HL162555//National Institutes of Health, National Heart, Lung, and Blood Institute/ ; },
mesh = {Adult ; Humans ; Digital Health ; Healthcare Disparities ; *Obesity/therapy ; *Telemedicine ; United States ; *Weight Reduction Programs/methods ; *Ethnic and Racial Minorities ; },
abstract = {IMPORTANCE: Obesity and chronic diseases disproportionately burden racial/ethnic minority adults in the United States (U.S.) (eg, Black, Hispanic/Latino, Asian, American Indian/Alaska Native, and Native Hawaiian/Pacific Islander), partially owing to barriers to receiving obesity treatment. While eHealth/mHealth-supported interventions offer a potential scalable solution and have proliferated in recent years, the last evidence synthesis was published in 2018.
OBJECTIVE: Given the wide variation in intervention approaches, we aimed to map current evidence on weight management programs targeting U.S. racial and ethnic minority adults. We sought to understand the e/mHealth tools used, the extent to which interventions were tailored, and how they addressed barriers and achieved effectiveness in reducing health disparities.
METHODS: We performed a Joanna Briggs Institute/Preferred Reporting Items for systematic reviews and meta-analyses and related scoping review guidance-guided search of MEDLINE, Cochrane, Embase, CINAHL Plus, and PsycINFO (inception-June 2025) for U.S. English-language studies (>50% minority adults ≥18 y, BMI ≥ 25 kg/m²) using electronic/mobile health (e/mHealth) for weight management.
RESULTS: Dual review of 4811 records yielded 51 studies (45 randomized controlled trials (RCTs)). Most studies used smartphone applications, a form of messaging to phones, and/or wearables (86%; 35/51) as opposed to other eHealth approaches. Interventions were culturally tailored in 34 studies (67%), yet few used co-design methods with the target population (3/51).
CONCLUSIONS: Interventions that use e/mHealth show moderate promise for scalable weight management, with available but uneven tailoring. Short-term/individual designs limit equity and sustainability, especially for underrepresented men and rural groups. Prioritization of co-designed, social determinants of health (SDOH) and theory-grounded (eg, socio-ecological) trials ≥12 months is necessary for scalable, responsive solutions.},
}
MeSH Terms:
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Adult
Humans
Digital Health
Healthcare Disparities
*Obesity/therapy
*Telemedicine
United States
*Weight Reduction Programs/methods
*Ethnic and Racial Minorities
RevDate: 2026-10-09
CmpDate: 2026-10-09
A generalized scaling law reveals synchrony-driven reorganization of brain dynamics across human lifespan.
PLoS computational biology, 22(10):e1014821 pii:PCOMPBIOL-D-26-00299.
Ecological systems obey universal scaling laws such as Taylor's law, which links population variance to the sample mean. Whether other complex systems with integrated and segregated network topology, the human brain, in particular, follow analogous scaling laws, and how these laws behave under synchronized neural activity, remains unknown. To address this question, our initial attempt to implement the Taylor's law, has been hindered because neural signals at all measurement scales contain both positive and negative values, whereas Taylor's law was restricted to non-negative ecological data. To circumvent this limitation, we extend spatial Taylor's law by replacing the sample mean with the root-mean-square (RMS) of the measurements, and apply this generalized law to detrended multivariate neural time series. The detrending operation has been performed as a necessary step to remove the trends and temporal mean from the data. Within this framework, we address our next question how synchronous or coordinated activity of the brain network influences the scaling law. We quantify synchrony using a dedicated metric of functional coordination and show analytically, and via numerical simulations using multivariate Poisson, negative binomial, uniform and gamma distributions, that the scaling exponent is inversely related to synchrony. Applying this approach to human fMRI data from three large cohorts (N = 840, ages 18-88 years) reveals distinct age-related trajectories of the scaling exponent, with healthy aging characterized by a substantial synchrony-induced reduction in this exponent. The synchrony-scaling relationship remains stable during resting-state activity but progressively shifts during naturalistic tasks across the lifespan, and is pronounced in limbic, subcortical, and cerebellar subnetworks, indicating preservation at subnetwork levels. Finally, individuals with ADHD exhibit altered synchrony-scaling coupling, highlighting the potential clinical and translational utility of this generalized scaling metric.
Additional Links: PMID-42832570
Publisher:
PubMed:
Citation:
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@article {pmid42832570,
year = {2026},
author = {Saha, S and Hens, C and Chakraborty, P and Kapitaniak, T and Deco, G and Banerjee, A and Dana, SK and Roy, D},
title = {A generalized scaling law reveals synchrony-driven reorganization of brain dynamics across human lifespan.},
journal = {PLoS computational biology},
volume = {22},
number = {10},
pages = {e1014821},
doi = {10.1371/journal.pcbi.1014821},
pmid = {42832570},
issn = {1553-7358},
mesh = {Humans ; *Brain/physiology/diagnostic imaging ; Magnetic Resonance Imaging ; Adult ; *Models, Neurological ; Female ; Aged ; Middle Aged ; Male ; Young Adult ; Nerve Net/physiology ; Adolescent ; Aging/physiology ; *Longevity/physiology ; Aged, 80 and over ; Computational Biology ; },
abstract = {Ecological systems obey universal scaling laws such as Taylor's law, which links population variance to the sample mean. Whether other complex systems with integrated and segregated network topology, the human brain, in particular, follow analogous scaling laws, and how these laws behave under synchronized neural activity, remains unknown. To address this question, our initial attempt to implement the Taylor's law, has been hindered because neural signals at all measurement scales contain both positive and negative values, whereas Taylor's law was restricted to non-negative ecological data. To circumvent this limitation, we extend spatial Taylor's law by replacing the sample mean with the root-mean-square (RMS) of the measurements, and apply this generalized law to detrended multivariate neural time series. The detrending operation has been performed as a necessary step to remove the trends and temporal mean from the data. Within this framework, we address our next question how synchronous or coordinated activity of the brain network influences the scaling law. We quantify synchrony using a dedicated metric of functional coordination and show analytically, and via numerical simulations using multivariate Poisson, negative binomial, uniform and gamma distributions, that the scaling exponent is inversely related to synchrony. Applying this approach to human fMRI data from three large cohorts (N = 840, ages 18-88 years) reveals distinct age-related trajectories of the scaling exponent, with healthy aging characterized by a substantial synchrony-induced reduction in this exponent. The synchrony-scaling relationship remains stable during resting-state activity but progressively shifts during naturalistic tasks across the lifespan, and is pronounced in limbic, subcortical, and cerebellar subnetworks, indicating preservation at subnetwork levels. Finally, individuals with ADHD exhibit altered synchrony-scaling coupling, highlighting the potential clinical and translational utility of this generalized scaling metric.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Brain/physiology/diagnostic imaging
Magnetic Resonance Imaging
Adult
*Models, Neurological
Female
Aged
Middle Aged
Male
Young Adult
Nerve Net/physiology
Adolescent
Aging/physiology
*Longevity/physiology
Aged, 80 and over
Computational Biology
RevDate: 2026-10-09
CmpDate: 2026-10-08
The chromosomal genome sequence of the staghorn coral, Acropora cervicornis (Lamarck, 1816) (Scleractinia: Acroporidae) and its associated microbial metagenome sequences.
Wellcome open research, 11:613.
We present a genome assembly from a specimen of Acropora cervicornis (staghorn coral; Cnidaria; Anthozoa; Scleractinia; Acroporidae). The genome sequence has a total length of 328.68 megabases. Most of the assembly (99.07%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 18.26 kilobases. Gene annotation of this assembly by Ensembl identified 24,579 protein-coding genes. From the metagenome data, we recovered two bins, of which one was a high-quality MAG.
Additional Links: PMID-42845342
PubMed:
Citation:
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@article {pmid42845342,
year = {2026},
author = {Rising, K and Karp, R and Baker, A and Metz, S and Sweet, M and Oatley, G and Sinclair, E and Aunin, E and Gettle, N and Santos, C and Paulini, M and Niu, H and McKenna, V and O'Brien, R and , and , and , and , and , },
title = {The chromosomal genome sequence of the staghorn coral, Acropora cervicornis (Lamarck, 1816) (Scleractinia: Acroporidae) and its associated microbial metagenome sequences.},
journal = {Wellcome open research},
volume = {11},
number = {},
pages = {613},
pmid = {42845342},
issn = {2398-502X},
abstract = {We present a genome assembly from a specimen of Acropora cervicornis (staghorn coral; Cnidaria; Anthozoa; Scleractinia; Acroporidae). The genome sequence has a total length of 328.68 megabases. Most of the assembly (99.07%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 18.26 kilobases. Gene annotation of this assembly by Ensembl identified 24,579 protein-coding genes. From the metagenome data, we recovered two bins, of which one was a high-quality MAG.},
}
RevDate: 2026-10-09
CmpDate: 2026-10-08
Digital health literacy moderates the school sports environment and physical activity pathway among Chinese adolescents: a health equity perspective.
Frontiers in public health, 14:1967478.
BACKGROUND: Physical inactivity among Chinese adolescents remains a pressing public health concern, with pronounced urban-rural disparities. School sports environments serve as a critical determinant of adolescent physical activity (PA), yet the conditions under which this relationship strengthens or weakens remain insufficiently understood. Digital health literacy (DHL) has emerged as a potential moderator that may amplify or buffer environmental influences on PA behavior.
METHODS: A cross-sectional survey was conducted among 2,531 adolescents (Mage = 15.2 ± 1.8 years; 51.3% male) recruited through stratified cluster sampling from 18 secondary schools in Hubei Province, China (9 urban, 9 rural). Participants completed validated Chinese versions of the Questionnaire Assessing School Physical Activity Environment (Q-SPACE-Chi), the eHealth Literacy Scale (eHEALS), and the International Physical Activity Questionnaire-Short Form (IPAQ-SF). Structural equation modeling with a latent interaction term tested the moderating role of DHL, and multigroup analysis examined urban-rural differences. Reporting followed the STROBE guideline.
RESULTS: School sports environment was positively associated with PA levels (β = 0.34, p < 0.001). DHL significantly moderated this pathway (interaction β = 0.12, p = 0.003), such that the environment-PA association was stronger among adolescents with higher DHL. Multigroup analysis revealed a significantly stronger environmental effect in urban (β = 0.38) than in rural schools (β = 0.29; z = 2.87, p = 0.004); the DHL moderation was significant in urban (β = 0.14, p = 0.008) but not rural schools (β = 0.07, p = 0.14), and the between-group difference in the moderation effect was not significant (z = 0.99, p = 0.32). The model demonstrated acceptable fit (χ [2]/df = 3.12, CFI = 0.94, TLI = 0.93, RMSEA = 0.045, SRMR = 0.041).
CONCLUSION: DHL amplifies the translation of favorable school sports environments into actual PA engagement, and the environment-PA association was stronger in urban schools. These findings suggest a potential pathway through which digital inequities may contribute to PA disparities, a possibility that requires longitudinal confirmation, and underscore the need for integrated school-based and digital literacy interventions to advance health equity.
Additional Links: PMID-42845756
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Citation:
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@article {pmid42845756,
year = {2026},
author = {Zhang, B},
title = {Digital health literacy moderates the school sports environment and physical activity pathway among Chinese adolescents: a health equity perspective.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1967478},
pmid = {42845756},
issn = {2296-2565},
mesh = {Humans ; Adolescent ; Male ; China ; Cross-Sectional Studies ; *Health Literacy/statistics & numerical data ; Female ; *Schools ; *Exercise ; *Sports ; Digital Health ; Surveys and Questionnaires ; *Health Equity ; Rural Population/statistics & numerical data ; Urban Population/statistics & numerical data ; },
abstract = {BACKGROUND: Physical inactivity among Chinese adolescents remains a pressing public health concern, with pronounced urban-rural disparities. School sports environments serve as a critical determinant of adolescent physical activity (PA), yet the conditions under which this relationship strengthens or weakens remain insufficiently understood. Digital health literacy (DHL) has emerged as a potential moderator that may amplify or buffer environmental influences on PA behavior.
METHODS: A cross-sectional survey was conducted among 2,531 adolescents (Mage = 15.2 ± 1.8 years; 51.3% male) recruited through stratified cluster sampling from 18 secondary schools in Hubei Province, China (9 urban, 9 rural). Participants completed validated Chinese versions of the Questionnaire Assessing School Physical Activity Environment (Q-SPACE-Chi), the eHealth Literacy Scale (eHEALS), and the International Physical Activity Questionnaire-Short Form (IPAQ-SF). Structural equation modeling with a latent interaction term tested the moderating role of DHL, and multigroup analysis examined urban-rural differences. Reporting followed the STROBE guideline.
RESULTS: School sports environment was positively associated with PA levels (β = 0.34, p < 0.001). DHL significantly moderated this pathway (interaction β = 0.12, p = 0.003), such that the environment-PA association was stronger among adolescents with higher DHL. Multigroup analysis revealed a significantly stronger environmental effect in urban (β = 0.38) than in rural schools (β = 0.29; z = 2.87, p = 0.004); the DHL moderation was significant in urban (β = 0.14, p = 0.008) but not rural schools (β = 0.07, p = 0.14), and the between-group difference in the moderation effect was not significant (z = 0.99, p = 0.32). The model demonstrated acceptable fit (χ [2]/df = 3.12, CFI = 0.94, TLI = 0.93, RMSEA = 0.045, SRMR = 0.041).
CONCLUSION: DHL amplifies the translation of favorable school sports environments into actual PA engagement, and the environment-PA association was stronger in urban schools. These findings suggest a potential pathway through which digital inequities may contribute to PA disparities, a possibility that requires longitudinal confirmation, and underscore the need for integrated school-based and digital literacy interventions to advance health equity.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Adolescent
Male
China
Cross-Sectional Studies
*Health Literacy/statistics & numerical data
Female
*Schools
*Exercise
*Sports
Digital Health
Surveys and Questionnaires
*Health Equity
Rural Population/statistics & numerical data
Urban Population/statistics & numerical data
RevDate: 2026-10-08
CmpDate: 2026-10-08
Analysis of selected digital risks as a basis for developing digital hygiene strategies. A perspective of vulnerable populations.
Frontiers in public health, 14:1932831.
The rapid development of digital technologies and widespread Internet access have transformed modern societies, creating new opportunities alongside emerging public health challenges. Digital risks, including problematic Internet and social media use, gaming disorder and problematic gaming, cyberbullying, online sexual risks, online gambling, and cybersecurity threats, may adversely affect psychological wellbeing, social functioning, and quality of life, particularly among vulnerable populations. This narrative review examined selected digital risks and their implications for promoting digital hygiene within public health prevention frameworks. A total of 64 publications published between 2012 and 2026 were included. Relevant literature was identified through PubMed, Scopus, and Web of Science, supplemented by reference-list searching and selected reports from international and European institutions. Literature was selected purposively, with priority given to systematic reviews, meta-analyses, epidemiological studies, and relevant conceptual and theoretical publications. The evidence was synthesized narratively and thematically, focusing on epidemiology, vulnerable populations, digital risks, risk and protective factors, and public health prevention and policy. The review focused on children and adolescents, older adults, individuals with mental health conditions, and socioeconomically disadvantaged populations. The findings indicate that digital risks arise from complex interactions among individual, interpersonal, digital-environmental, and structural factors. Effective prevention therefore requires a multidimensional, socio-ecological approach integrating digital and health literacy, self-regulation, family- and school-based prevention, community support, safer digital environments, and appropriate policy measures. Digital hygiene should be considered an emerging component of public health practice, with further research needed to develop and evaluate population-specific, multilevel interventions.
Additional Links: PMID-42846777
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Citation:
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@article {pmid42846777,
year = {2026},
author = {Wojciechowska, M and Mateja, M and Żaroń, A and Spevan, M and Šegulja, S},
title = {Analysis of selected digital risks as a basis for developing digital hygiene strategies. A perspective of vulnerable populations.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1932831},
pmid = {42846777},
issn = {2296-2565},
mesh = {Humans ; *Vulnerable Populations ; Digital Media ; *Internet ; *Digital Technology ; *Public Health ; Risk Factors ; Digital Health ; },
abstract = {The rapid development of digital technologies and widespread Internet access have transformed modern societies, creating new opportunities alongside emerging public health challenges. Digital risks, including problematic Internet and social media use, gaming disorder and problematic gaming, cyberbullying, online sexual risks, online gambling, and cybersecurity threats, may adversely affect psychological wellbeing, social functioning, and quality of life, particularly among vulnerable populations. This narrative review examined selected digital risks and their implications for promoting digital hygiene within public health prevention frameworks. A total of 64 publications published between 2012 and 2026 were included. Relevant literature was identified through PubMed, Scopus, and Web of Science, supplemented by reference-list searching and selected reports from international and European institutions. Literature was selected purposively, with priority given to systematic reviews, meta-analyses, epidemiological studies, and relevant conceptual and theoretical publications. The evidence was synthesized narratively and thematically, focusing on epidemiology, vulnerable populations, digital risks, risk and protective factors, and public health prevention and policy. The review focused on children and adolescents, older adults, individuals with mental health conditions, and socioeconomically disadvantaged populations. The findings indicate that digital risks arise from complex interactions among individual, interpersonal, digital-environmental, and structural factors. Effective prevention therefore requires a multidimensional, socio-ecological approach integrating digital and health literacy, self-regulation, family- and school-based prevention, community support, safer digital environments, and appropriate policy measures. Digital hygiene should be considered an emerging component of public health practice, with further research needed to develop and evaluate population-specific, multilevel interventions.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Vulnerable Populations
Digital Media
*Internet
*Digital Technology
*Public Health
Risk Factors
Digital Health
RevDate: 2026-10-08
CmpDate: 2026-10-08
Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.
The Plant cell, 38(10):.
Spatial omics technologies provide new opportunities for plant biology by enabling molecular profiling within structurally intact tissues, revealing spatially organized cell states, developmental gradients, and regulatory interactions. While spatial transcriptomics has driven early advances, the field is rapidly expanding toward integrated spatial multi-omics by combining single-cell and spatial transcriptomic, epigenomic, proteomic, and metabolomic data. These approaches offer new opportunities to study development, physiology, and plant biotic and abiotic interactions in spatially preserved cellular contexts. However, despite rapid adoption, the field remains constrained by plant-specific challenges when applying technologies largely developed for animal systems. Compared with animal systems, plant tissues pose additional challenges due to rigid cell walls and diverse chemistries, complicating sample preparation, cell and subcellular segmentation, signal detection, and data integration. As a result, many studies rely on bespoke protocols and analysis pipelines that are often difficult to reproduce or generalize. Here, we provide a practical, solution-oriented synthesis of current bottlenecks across experimental and computational pipelines, highlight emerging strategies to overcome these limitations, and propose a roadmap for community-driven protocol sharing, benchmarking, and integration across spatial and multi-omics modalities. Addressing these challenges will be essential to establish spatial omics as a routine and scalable tool for plant biology.
Additional Links: PMID-42740657
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@article {pmid42740657,
year = {2026},
author = {Jhu, MY and Minne, M and Luo, Z and Dörpholz, H and Yao, J and Mukhtar, MS and Mathieu, F and Peirats-Llobet, M and Lee, T and Formosa-Jordan, P and Song, S and Libault, M and Hsu, CW and Nolan, TM and Nobori, T and Anderton, CR and Schmitz, RJ and Jackson, D and Moreno-Risueno, M and Nelissen, H and Simon, R and Sozzani, R and Sugimoto, K},
title = {Unlocking the full potential of spatial omics in plants: practical challenges, solutions, and a path forward.},
journal = {The Plant cell},
volume = {38},
number = {10},
pages = {},
pmid = {42740657},
issn = {1532-298X},
support = {ASPIRE JPMJAP2306//Japan Science and Technology Agency/ ; NSF OISE-2020459//US National Science Foundation/ ; EXC2048//Cluster of Excellence on Plant Sciences/ ; //Max Planck Society/ ; //Gatsby Charitable Foundation/ ; BB/Y002997/1/BB_/Biotechnology and Biological Sciences Research Council/United Kingdom ; //U.S. Department of Energy/ ; DE-SC0023338//Office of Science's Biological and Environmental Research/ ; DE-SC0025995//Office of Science's Biological and Environmental Research/ ; DE-SC0018459//U.S. DOE-BER Bioimaging Program/ ; //Shurl and Kay Curci Foundation/ ; //The Donna and Benjamin M. Rosen Bioengineering Center/ ; MCB-2544734//The Resnick Sustainability Institute/ ; 44207744//Deutsche Forschungsgemeinschaft/ ; ZT-I-PF-3-091//Helmholtz Association/ ; IOS-2038872//NSF/ ; OIA-2418230//NSF/ ; PID2022-140719NB-I00//ARC Centre of Excellence Plants for Space/ ; MICIU/AEI/10.13039/501100011033//ARC Centre of Excellence Plants for Space/ ; CEX2020-000999-S//ARC Centre of Excellence Plants for Space/ ; MICIU/AEI/10.13039/501100011033//ARC Centre of Excellence Plants for Space/ ; P25086//Japan Society for the Promotion of Science/ ; },
mesh = {*Plants/genetics/metabolism ; Multiomics ; Proteomics/methods ; Spatial Transcriptomics ; Metabolomics/methods ; *Genomics/methods ; },
abstract = {Spatial omics technologies provide new opportunities for plant biology by enabling molecular profiling within structurally intact tissues, revealing spatially organized cell states, developmental gradients, and regulatory interactions. While spatial transcriptomics has driven early advances, the field is rapidly expanding toward integrated spatial multi-omics by combining single-cell and spatial transcriptomic, epigenomic, proteomic, and metabolomic data. These approaches offer new opportunities to study development, physiology, and plant biotic and abiotic interactions in spatially preserved cellular contexts. However, despite rapid adoption, the field remains constrained by plant-specific challenges when applying technologies largely developed for animal systems. Compared with animal systems, plant tissues pose additional challenges due to rigid cell walls and diverse chemistries, complicating sample preparation, cell and subcellular segmentation, signal detection, and data integration. As a result, many studies rely on bespoke protocols and analysis pipelines that are often difficult to reproduce or generalize. Here, we provide a practical, solution-oriented synthesis of current bottlenecks across experimental and computational pipelines, highlight emerging strategies to overcome these limitations, and propose a roadmap for community-driven protocol sharing, benchmarking, and integration across spatial and multi-omics modalities. Addressing these challenges will be essential to establish spatial omics as a routine and scalable tool for plant biology.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Plants/genetics/metabolism
Multiomics
Proteomics/methods
Spatial Transcriptomics
Metabolomics/methods
*Genomics/methods
RevDate: 2026-10-07
CmpDate: 2026-10-06
Barriers to social participation among patients with hemophilia: a qualitative study using social-ecological systems theory.
Frontiers in public health, 14:1937214.
BACKGROUND: Social participation greatly determines health-related quality of life, while people with hemophilia face severe social engagement restrictions. Current studies only explore such barriers from single dimensions including joint function, employment and mental distress, lacking a comprehensive social-ecological perspective. Based on social-ecological systems theory, this study systematically analyzes multi-level barriers to social participation among Chinese hemophilia patients to support integrated nursing intervention development.
METHODS: A descriptive phenomenological qualitative design was employed. Purposive and snowball sampling strategies were used to recruit 15 adults with hemophilia from the hematology department of a tertiary hospital in China between February and July 2026. Individual semi-structured in-depth interviews were conducted using a topic guide informed by the three-system framework (micro-, meso-, and macro-). Data were analyzed using Colaizzi's seven-step method, with two researchers independently coding and reaching consensus through discussion. NVivo 14 was used to facilitate data management.
RESULTS: Nine themes and 20 sub-themes were identified across the three system levels. Micro-system barriers comprised: (1) progressive joint damage and functional limitations; (2) psychosocial distress and maladaptive coping; and (3) inadequate disease knowledge and self-management deficits. Meso-system barriers comprised: (4) catastrophic medication costs and family resource depletion; (5) family caregiving deficits and role overload; and (6) employment exclusion and social network contraction. Macro-system barriers comprised: (7) insurance coverage gaps and treatment access barriers; (8) geographic disparities in healthcare access; and (9) social stigma and inadequate institutional support. Critically, barriers across the three levels did not operate in isolation but interacted to produce a cumulative, compounding deprivation of social participation.
CONCLUSIONS: Social participation barriers among people with hemophilia represent a complex, multi-layered phenomenon embedded within the micro-, meso-, and macro-systems of the social ecology. Nursing care should shift from a biomedical-only paradigm toward an integrated model: strengthening symptom management and psychological empowerment at the micro-level, promoting family enablement and social network reconstruction at the meso-level, and advancing policy advocacy and public education at the macro-level.
Additional Links: PMID-42834990
PubMed:
Citation:
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@article {pmid42834990,
year = {2026},
author = {Zhang, J and Xue, M and Song, X and Qu, Y},
title = {Barriers to social participation among patients with hemophilia: a qualitative study using social-ecological systems theory.},
journal = {Frontiers in public health},
volume = {14},
number = {},
pages = {1937214},
pmid = {42834990},
issn = {2296-2565},
mesh = {Humans ; *Hemophilia A/psychology ; Male ; *Social Participation/psychology ; Adult ; Qualitative Research ; China ; Middle Aged ; Quality of Life ; Adaptation, Psychological ; Female ; Interviews as Topic ; Young Adult ; },
abstract = {BACKGROUND: Social participation greatly determines health-related quality of life, while people with hemophilia face severe social engagement restrictions. Current studies only explore such barriers from single dimensions including joint function, employment and mental distress, lacking a comprehensive social-ecological perspective. Based on social-ecological systems theory, this study systematically analyzes multi-level barriers to social participation among Chinese hemophilia patients to support integrated nursing intervention development.
METHODS: A descriptive phenomenological qualitative design was employed. Purposive and snowball sampling strategies were used to recruit 15 adults with hemophilia from the hematology department of a tertiary hospital in China between February and July 2026. Individual semi-structured in-depth interviews were conducted using a topic guide informed by the three-system framework (micro-, meso-, and macro-). Data were analyzed using Colaizzi's seven-step method, with two researchers independently coding and reaching consensus through discussion. NVivo 14 was used to facilitate data management.
RESULTS: Nine themes and 20 sub-themes were identified across the three system levels. Micro-system barriers comprised: (1) progressive joint damage and functional limitations; (2) psychosocial distress and maladaptive coping; and (3) inadequate disease knowledge and self-management deficits. Meso-system barriers comprised: (4) catastrophic medication costs and family resource depletion; (5) family caregiving deficits and role overload; and (6) employment exclusion and social network contraction. Macro-system barriers comprised: (7) insurance coverage gaps and treatment access barriers; (8) geographic disparities in healthcare access; and (9) social stigma and inadequate institutional support. Critically, barriers across the three levels did not operate in isolation but interacted to produce a cumulative, compounding deprivation of social participation.
CONCLUSIONS: Social participation barriers among people with hemophilia represent a complex, multi-layered phenomenon embedded within the micro-, meso-, and macro-systems of the social ecology. Nursing care should shift from a biomedical-only paradigm toward an integrated model: strengthening symptom management and psychological empowerment at the micro-level, promoting family enablement and social network reconstruction at the meso-level, and advancing policy advocacy and public education at the macro-level.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Hemophilia A/psychology
Male
*Social Participation/psychology
Adult
Qualitative Research
China
Middle Aged
Quality of Life
Adaptation, Psychological
Female
Interviews as Topic
Young Adult
RevDate: 2026-10-07
Using multi-trait polygenic scores to predict lithium responsiveness in patients with bipolar disorder.
The British journal of psychiatry : the journal of mental science pii:S0007125026107764 [Epub ahead of print].
BACKGROUND: The predictive power of polygenic scores (PGSs) for lithium treatment response in bipolar disorder remains limited.
AIMS: To enhance the prediction of lithium responsiveness by developing a multi-trait PGS (mt-PGS) combining genetic information from multiple phenotypes implicated in lithium response and/or bipolar disorder aetiology.
METHOD: We analysed data collected from bipolar disorder patients who had received lithium treatment for at least 6 months and participated in the International Consortium on Lithium Genetics study (N = 2367). The Alda scale was used to assess lithium responsiveness, and treatment outcome was defined as continuous total Alda score (0-10) and categorical outcome (favourable ≥7 versus unfavourable response). PGSs were calculated for 60 phenotypes grouped into 5 clinical-biological clusters: psychiatric and behavioural (#23 phenotypes), cardiometabolic (#17), autoimmune/inflammatory (#5), neurocognitive (#8) and renal function (#7). We applied cross-validated machine learning regression approaches in both outcomes within each cluster, with the selected features from each cluster subsequently combined to construct the final mt-PGS models. Model performance was assessed using explained variance (R[2]) for the continuous outcome, and both McFadden's pseudo-R[2] and standard classification model parameters for the categorical outcome.
RESULTS: mt-PGS explained between 5.70% (continuous outcome) and 9.11% (categorical outcome) of the interindividual variability in lithium responsiveness. Classification accuracy (area under the curve) for the categorical outcome was 68.24% (95% CI: 64.98-71.66), with a Brier score of 0.257. Of the 5 clusters, the PGSs for psychiatric and behavioural phenotypes were most strongly associated with lithium responsiveness, accounting for 3.67-6.52% of its variability.
CONCLUSIONS: By integrating PGSs for multiple relevant phenotypes, predictive accuracy for lithium response improved substantially compared with single-trait methods. Future research incorporating larger, more diverse populations and combining genetic scores with clinical data holds promise for further enhancing prediction and advancing clinical implementation.
Additional Links: PMID-42841250
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@article {pmid42841250,
year = {2026},
author = {Sharew, NT and Clark, SR and Hartmann, S and Papiol, S and Heilbronner, U and Degenhardt, F and Fullerton, JM and Hou, L and Shekhtman, T and Adli, M and Akula, N and Akiyama, K and Ardau, R and Arias, B and Tekola-Ayele, F and Gallo, C and Hasler, R and Richard-Lepouriel, H and Perroud, N and Backlund, L and Bhattacharjee, AK and Bellivier, F and Benabarre, A and Bengesser, S and Biernacka, JM and Birner, A and Marie-Claire, C and Cervantes, P and Chen, HC and Chillotti, C and Cichon, S and Cruceana, C and Czerski, PM and Dalkner, N and Zompo, MD and DePaulo, JR and Étain, B and Jamain, S and Falkai, P and Forstner, AJ and Frisen, L and Frye, MA and Gard, S and Garnham, JS and Goes, FS and Grigoroiu-Serbanescu, M and Fallgatter, AJ and Stegmaier, S and Ethofer, T and Biere, S and Petrova, K and Schuster, C and Adorjan, K and Budde, M and Heilbronner, M and Kalman, JL and Kohshour, MO and Reich-Erkelenz, D and Schaupp, SK and Schulte, EC and Senner, F and Vogl, T and Anghelescu, IG and Arolt, V and Dannlowski, U and Dietrich, DE and Figge, C and Jäger, M and Lang, FU and Juckel, G and Konrad, C and Reimer, J and Schmauß, M and Schmitt, A and Spitzer, C and Von Hagen, M and Wiltfang, J and Zimmermann, J and Andlauer, TFM and Fischer, A and Bermpohl, F and Ritter, P and Matura, S and Gryaznova, A and Falkenberg, I and Yildiz, C and Kircher, T and Schmidt, J and Koch, M and Gade, K and Trost, S and Haussleiter, IS and Lambert, M and Rohenkohl, AC and Kraft, V and Grof, P and Hashimoto, R and Hauser, J and Herms, S and Hoffman, P and Jiménez, E and Kahn, JP and Kassem, L and Kuo, PH and Kato, T and Kelsoe, J and Kittel-Schneider, S and Ferensztajn-Rochowiak, E and König, B and Kusumi, I and Laje, G and Landén, M and Lavebratt, C and Leboyer, M and Leckband, SG and Tortorella, A and Manchia, M and Martinsson, L and McCarthy, MJ and McElroy, SL and Colom, F and Millischer, V and Mitjans, M and Mondimore, FM and Monteleone, P and Nievergelt, CM and Nöthen, MM and Novak, T and O'Donovan, C and Ozaki, N and Pfennig, A and Pisanu, C and Potash, JB and Reif, A and Reininghaus, E and Rouleau, GA and Rybakowski, JK and Schalling, M and Schofield, PR and Schweizer, BW and Severino, G and Shilling, PD and Shimoda, K and Simhandl, C and Slaney, CM and Squassina, A and Stamm, T and Stopkova, P and Maj, M and Turecki, G and Vieta, E and Veeh, J and Viswanath, B and Witt, SH and Wright, A and Zandi, PP and Mitchell, PB and Bauer, M and Alda, M and Rietschel, M and McMahon, FJ and Schulze, TG and Baune, BT and Schubert, KO and Amare, AT},
title = {Using multi-trait polygenic scores to predict lithium responsiveness in patients with bipolar disorder.},
journal = {The British journal of psychiatry : the journal of mental science},
volume = {},
number = {},
pages = {1-12},
doi = {10.1192/bjp.2026.10776},
pmid = {42841250},
issn = {1472-1465},
abstract = {BACKGROUND: The predictive power of polygenic scores (PGSs) for lithium treatment response in bipolar disorder remains limited.
AIMS: To enhance the prediction of lithium responsiveness by developing a multi-trait PGS (mt-PGS) combining genetic information from multiple phenotypes implicated in lithium response and/or bipolar disorder aetiology.
METHOD: We analysed data collected from bipolar disorder patients who had received lithium treatment for at least 6 months and participated in the International Consortium on Lithium Genetics study (N = 2367). The Alda scale was used to assess lithium responsiveness, and treatment outcome was defined as continuous total Alda score (0-10) and categorical outcome (favourable ≥7 versus unfavourable response). PGSs were calculated for 60 phenotypes grouped into 5 clinical-biological clusters: psychiatric and behavioural (#23 phenotypes), cardiometabolic (#17), autoimmune/inflammatory (#5), neurocognitive (#8) and renal function (#7). We applied cross-validated machine learning regression approaches in both outcomes within each cluster, with the selected features from each cluster subsequently combined to construct the final mt-PGS models. Model performance was assessed using explained variance (R[2]) for the continuous outcome, and both McFadden's pseudo-R[2] and standard classification model parameters for the categorical outcome.
RESULTS: mt-PGS explained between 5.70% (continuous outcome) and 9.11% (categorical outcome) of the interindividual variability in lithium responsiveness. Classification accuracy (area under the curve) for the categorical outcome was 68.24% (95% CI: 64.98-71.66), with a Brier score of 0.257. Of the 5 clusters, the PGSs for psychiatric and behavioural phenotypes were most strongly associated with lithium responsiveness, accounting for 3.67-6.52% of its variability.
CONCLUSIONS: By integrating PGSs for multiple relevant phenotypes, predictive accuracy for lithium response improved substantially compared with single-trait methods. Future research incorporating larger, more diverse populations and combining genetic scores with clinical data holds promise for further enhancing prediction and advancing clinical implementation.},
}
RevDate: 2026-10-07
Escherichia coli-derived enterobactin is associated with delayed gut microbiome maturation in infants born to mothers with obesity.
mSystems [Epub ahead of print].
Maternal obesity has been increasingly recognized as a factor influencing early-life microbiome development. However, its impact on the infant gut resistome and virulome remains insufficiently characterized. In this prospective longitudinal study, we investigated gut microbiome composition, antibiotic resistance genes (ARGs), and virulence factor profiles in infants born to mothers with obesity and normal weight during the first year of life. Shotgun metagenomic sequencing was performed on maternal and infant fecal samples collected at birth and at 1, 3, 6, and 12 months. Infants born to obese mothers exhibited delayed microbiome maturation characterized by early enrichment of Pseudomonadota, particularly Escherichia coli and Klebsiella pneumoniae, and reduced abundance of Bifidobacterium species. This compositional pattern was accompanied by a significantly higher ARG burden in early life, including enrichment of genes associated with antibiotic inactivation, efflux mechanisms, and β-lactam resistance. Although taxonomic differences between groups were no longer statistically detectable at the 12-month time point, where the sample size was smallest, functional disparities in the resistome persisted. Additionally, infants born to obese mothers demonstrated increased relative abundance of secretory virulence-associated genes and E. coli-derived enterobactin, suggesting enhanced iron-scavenging capacity and competitive potential of Enterobacteriaceae. Together, these findings suggest that maternal obesity is associated with altered early microbial ecological dynamics, promotes resistome expansion, and may delay transition toward a stable Bacteroidota- and Bacillota-dominated microbiome.IMPORTANCEThe first year of life is a critical window for gut microbiome development, during which early microbial disturbances may influence later health. This study shows that maternal obesity is associated not only with altered infant microbial succession but also with functional changes in the infant gut microbiome, including greater antibiotic resistance gene burden and enrichment of virulence-associated traits. The finding of increased Escherichia coli-derived enterobactin suggests that iron-scavenging mechanisms may help Enterobacteriaceae persist during early infancy and may contribute to delayed microbial maturation. By linking maternal obesity with infant microbiome development, resistome expansion, and virulence-related functions, this work provides new insight into how maternal metabolic status may shape early microbial ecology and potential microbiome-associated risks.
Additional Links: PMID-42841659
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@article {pmid42841659,
year = {2026},
author = {Kovenskiy, A and Mukhanbetzhanov, N and Jarmukhanov, Z and Duisebayeva, A and Morenko, M and Kossumov, A and Chulenbayeva, L and Vinogradova, E and Popov, M and Kushugulova, A and Kozhakmetov, S},
title = {Escherichia coli-derived enterobactin is associated with delayed gut microbiome maturation in infants born to mothers with obesity.},
journal = {mSystems},
volume = {},
number = {},
pages = {e0098626},
doi = {10.1128/msystems.00986-26},
pmid = {42841659},
issn = {2379-5077},
abstract = {Maternal obesity has been increasingly recognized as a factor influencing early-life microbiome development. However, its impact on the infant gut resistome and virulome remains insufficiently characterized. In this prospective longitudinal study, we investigated gut microbiome composition, antibiotic resistance genes (ARGs), and virulence factor profiles in infants born to mothers with obesity and normal weight during the first year of life. Shotgun metagenomic sequencing was performed on maternal and infant fecal samples collected at birth and at 1, 3, 6, and 12 months. Infants born to obese mothers exhibited delayed microbiome maturation characterized by early enrichment of Pseudomonadota, particularly Escherichia coli and Klebsiella pneumoniae, and reduced abundance of Bifidobacterium species. This compositional pattern was accompanied by a significantly higher ARG burden in early life, including enrichment of genes associated with antibiotic inactivation, efflux mechanisms, and β-lactam resistance. Although taxonomic differences between groups were no longer statistically detectable at the 12-month time point, where the sample size was smallest, functional disparities in the resistome persisted. Additionally, infants born to obese mothers demonstrated increased relative abundance of secretory virulence-associated genes and E. coli-derived enterobactin, suggesting enhanced iron-scavenging capacity and competitive potential of Enterobacteriaceae. Together, these findings suggest that maternal obesity is associated with altered early microbial ecological dynamics, promotes resistome expansion, and may delay transition toward a stable Bacteroidota- and Bacillota-dominated microbiome.IMPORTANCEThe first year of life is a critical window for gut microbiome development, during which early microbial disturbances may influence later health. This study shows that maternal obesity is associated not only with altered infant microbial succession but also with functional changes in the infant gut microbiome, including greater antibiotic resistance gene burden and enrichment of virulence-associated traits. The finding of increased Escherichia coli-derived enterobactin suggests that iron-scavenging mechanisms may help Enterobacteriaceae persist during early infancy and may contribute to delayed microbial maturation. By linking maternal obesity with infant microbiome development, resistome expansion, and virulence-related functions, this work provides new insight into how maternal metabolic status may shape early microbial ecology and potential microbiome-associated risks.},
}
RevDate: 2026-10-07
CmpDate: 2026-10-07
A High Throughput and User-Friendly Computational Tool for Quantifying and Visualizing Symmetry Variation in Image Datasets.
Bulletin of mathematical biology, 88(11):.
Symmetry is a fundamental property of biological systems, yet it is commonly reduced to discrete, subjective classifications that fail to capture the continuous and graded nature of symmetry in real organisms. We present a high-throughput, user-friendly computational framework for quantifying and visualizing biological symmetry as a continuous variable using transformation information (T I), an information theoretic measure that quantifies the divergence between an object and its transformed self. We establish key mathematical properties of T I , including invariance, equivariance, and Lipschitz continuity, that guarantee robustness to transformations such as translation, rotation, reflection, and rescaling, enabling reliable symmetry quantification across heterogeneous image datasets without manual landmarking or image alignment. Building on this theoretical foundation, we introduce a computational pipeline that automates symmetry center detection, T I curve computation, and visualization of the symmetry data using functional principal component analysis (fPCA). We demonstrate the utility of this framework on two biological datasets: a large collection of angiosperm flower images, where we investigate rotational and reflectional symmetries, and a dataset of simulated fern images, where we investigate fractal self-similarity under scaling and translation. Our analysis of the floral dataset provides novel evidence of convergent evolution. In both datasets, fPCA of the resulting T I profiles reveals that symmetry is best characterized as a continuum rather than a set of discrete classes, and there is subtle morphological variation that is not captured by traditional categorical approaches. Together, these results suggest that T I provides a mathematically principled and biologically informative foundation for integrating symmetry into quantitative evolutionary, ecological, and developmental models.
Additional Links: PMID-42842049
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@article {pmid42842049,
year = {2026},
author = {O'Brien, LD and Gandhi, P and Ciocanel, MV and Dawes, AT},
title = {A High Throughput and User-Friendly Computational Tool for Quantifying and Visualizing Symmetry Variation in Image Datasets.},
journal = {Bulletin of mathematical biology},
volume = {88},
number = {11},
pages = {},
pmid = {42842049},
issn = {1522-9602},
support = {R01GM132651//National Institutes of Health (NIH)/ ; },
mesh = {Computational Biology ; Flowers/anatomy & histology ; *Models, Biological ; Mathematical Concepts ; Image Processing, Computer-Assisted/statistics & numerical data/methods ; Principal Component Analysis ; Computer Simulation ; Magnoliopsida/anatomy & histology ; Information Theory ; Algorithms ; },
abstract = {Symmetry is a fundamental property of biological systems, yet it is commonly reduced to discrete, subjective classifications that fail to capture the continuous and graded nature of symmetry in real organisms. We present a high-throughput, user-friendly computational framework for quantifying and visualizing biological symmetry as a continuous variable using transformation information (T I), an information theoretic measure that quantifies the divergence between an object and its transformed self. We establish key mathematical properties of T I , including invariance, equivariance, and Lipschitz continuity, that guarantee robustness to transformations such as translation, rotation, reflection, and rescaling, enabling reliable symmetry quantification across heterogeneous image datasets without manual landmarking or image alignment. Building on this theoretical foundation, we introduce a computational pipeline that automates symmetry center detection, T I curve computation, and visualization of the symmetry data using functional principal component analysis (fPCA). We demonstrate the utility of this framework on two biological datasets: a large collection of angiosperm flower images, where we investigate rotational and reflectional symmetries, and a dataset of simulated fern images, where we investigate fractal self-similarity under scaling and translation. Our analysis of the floral dataset provides novel evidence of convergent evolution. In both datasets, fPCA of the resulting T I profiles reveals that symmetry is best characterized as a continuum rather than a set of discrete classes, and there is subtle morphological variation that is not captured by traditional categorical approaches. Together, these results suggest that T I provides a mathematically principled and biologically informative foundation for integrating symmetry into quantitative evolutionary, ecological, and developmental models.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Computational Biology
Flowers/anatomy & histology
*Models, Biological
Mathematical Concepts
Image Processing, Computer-Assisted/statistics & numerical data/methods
Principal Component Analysis
Computer Simulation
Magnoliopsida/anatomy & histology
Information Theory
Algorithms
RevDate: 2026-10-07
CmpDate: 2026-10-07
Table Olive Fermentation: Microbial Ecology, Metabolite Transformation, and Emerging Non-Thermal and Omics-Based Technologies.
Journal of food science, 91(10):e71520.
Table olive fermentation is a complex microbial process in which lactic acid bacteria and yeasts contribute to the transformation of phenolic compounds, organic acids, and volatile metabolites that influence product quality, safety, and functionality. Fermentation outcomes remain variable because of cultivar characteristics, spontaneous microbial succession, and limited control over microbial and biochemical dynamics. Recent research has therefore shifted toward a more mechanistic understanding of microbial-metabolite interactions and strategies for more reproducible fermentation control. This review critically examines the microbial ecology, phenolic bioconversion, volatile compounds and metabolite formation, and their relationships with table olive quality. Emerging non-thermal technologies, including ultrasound, high hydrostatic pressure, pulsed electric fields, cold plasma, and pulsed light, are evaluated according to their demonstrated and potential roles in microbial modulation, mass transfer, phenolic transformation, and process stability, with particular attention to the strength of table-olive-specific evidence. The review further examines omics and multi-omics approaches for functional microbial characterization and metabolite profiling, together with sensor-based monitoring, artificial intelligence, and machine learning as emerging tools for data-driven fermentation assessment. The evidence indicates that technological maturity varies substantially among emerging approaches and that most omics- and AI-based applications remain more advanced in characterization and classification than in real-time fermentation control. Further development will require integration of strain-resolved microbiology, quantitative metabolite analysis, process monitoring, predictive modelling, and sensory validation under independent pilot- and industrial-scale conditions. Such approaches may support a transition from empirical fermentation toward more reproducible and evidence-based table olive bioprocessing.
Additional Links: PMID-42842337
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@article {pmid42842337,
year = {2026},
author = {Acar, A and Akin, N},
title = {Table Olive Fermentation: Microbial Ecology, Metabolite Transformation, and Emerging Non-Thermal and Omics-Based Technologies.},
journal = {Journal of food science},
volume = {91},
number = {10},
pages = {e71520},
doi = {10.1111/1750-3841.71520},
pmid = {42842337},
issn = {1750-3841},
mesh = {*Olea/microbiology/chemistry/metabolism ; *Fermentation ; *Food Microbiology ; Multiomics ; Phenols/metabolism ; Yeasts/metabolism ; Food Handling/methods ; Volatile Organic Compounds/metabolism ; Metabolomics ; },
abstract = {Table olive fermentation is a complex microbial process in which lactic acid bacteria and yeasts contribute to the transformation of phenolic compounds, organic acids, and volatile metabolites that influence product quality, safety, and functionality. Fermentation outcomes remain variable because of cultivar characteristics, spontaneous microbial succession, and limited control over microbial and biochemical dynamics. Recent research has therefore shifted toward a more mechanistic understanding of microbial-metabolite interactions and strategies for more reproducible fermentation control. This review critically examines the microbial ecology, phenolic bioconversion, volatile compounds and metabolite formation, and their relationships with table olive quality. Emerging non-thermal technologies, including ultrasound, high hydrostatic pressure, pulsed electric fields, cold plasma, and pulsed light, are evaluated according to their demonstrated and potential roles in microbial modulation, mass transfer, phenolic transformation, and process stability, with particular attention to the strength of table-olive-specific evidence. The review further examines omics and multi-omics approaches for functional microbial characterization and metabolite profiling, together with sensor-based monitoring, artificial intelligence, and machine learning as emerging tools for data-driven fermentation assessment. The evidence indicates that technological maturity varies substantially among emerging approaches and that most omics- and AI-based applications remain more advanced in characterization and classification than in real-time fermentation control. Further development will require integration of strain-resolved microbiology, quantitative metabolite analysis, process monitoring, predictive modelling, and sensory validation under independent pilot- and industrial-scale conditions. Such approaches may support a transition from empirical fermentation toward more reproducible and evidence-based table olive bioprocessing.},
}
MeSH Terms:
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*Olea/microbiology/chemistry/metabolism
*Fermentation
*Food Microbiology
Multiomics
Phenols/metabolism
Yeasts/metabolism
Food Handling/methods
Volatile Organic Compounds/metabolism
Metabolomics
RevDate: 2026-10-08
CmpDate: 2026-10-07
roadDB: An R package for exploring early human prehistory and environments with the ROCEEH Out of Africa Database.
PloS one, 21(10):e0359952.
Macroscale and interdisciplinary approaches are emerging as central paradigms in the study of human evolution, as demonstrated by a growing body of large-scale, data-driven research. This development is paralleled by an expanding ecosystem of R packages that provide access to paleoenvironmental and paleoclimatic reconstructions, as well as advanced tools for spatial and temporal analysis and modeling. However, within this computational framework, direct programmatic access to comprehensive archaeological and anthropological data remains limited. We present roadDB, an R package that enables streamlined access to the ROCEEH Out of Africa Database (ROAD), a major repository of archaeological, paleoanthropological, paleoenvironmental, geographical and chronological data relevant to human evolution. roadDB bridges the gap between the existing R ecosystem and the ROAD archaeological dataset that covers most of the last 3 million years of human evolution across Africa and Eurasia and thereby represents the only openly available archaeological dataset with such an extensive temporal and geographic coverage. In short, roadDB offers the research community unrestricted, transparent access to a richly curated collection of site-level and assemblage-level information, opening new possibilities for large-scale quantitative research. The package strengthens the integration of archaeological and paleoenvironmental evidence in macroscale analyses and supports robust, transparent and interdisciplinary research on the spatio-temporal dynamics of human evolution.
Additional Links: PMID-42842598
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@article {pmid42842598,
year = {2026},
author = {Sommer, C and Pedersen, JB and Kanaeva, Z and Streicher, TP and Kandel, AW and Conard, NJ and Hochschild, V},
title = {roadDB: An R package for exploring early human prehistory and environments with the ROCEEH Out of Africa Database.},
journal = {PloS one},
volume = {21},
number = {10},
pages = {e0359952},
pmid = {42842598},
issn = {1932-6203},
mesh = {Humans ; Africa ; *Databases, Factual ; *Archaeology/methods ; Biological Evolution ; *Software ; Environment ; Animals ; Ecosystem ; },
abstract = {Macroscale and interdisciplinary approaches are emerging as central paradigms in the study of human evolution, as demonstrated by a growing body of large-scale, data-driven research. This development is paralleled by an expanding ecosystem of R packages that provide access to paleoenvironmental and paleoclimatic reconstructions, as well as advanced tools for spatial and temporal analysis and modeling. However, within this computational framework, direct programmatic access to comprehensive archaeological and anthropological data remains limited. We present roadDB, an R package that enables streamlined access to the ROCEEH Out of Africa Database (ROAD), a major repository of archaeological, paleoanthropological, paleoenvironmental, geographical and chronological data relevant to human evolution. roadDB bridges the gap between the existing R ecosystem and the ROAD archaeological dataset that covers most of the last 3 million years of human evolution across Africa and Eurasia and thereby represents the only openly available archaeological dataset with such an extensive temporal and geographic coverage. In short, roadDB offers the research community unrestricted, transparent access to a richly curated collection of site-level and assemblage-level information, opening new possibilities for large-scale quantitative research. The package strengthens the integration of archaeological and paleoenvironmental evidence in macroscale analyses and supports robust, transparent and interdisciplinary research on the spatio-temporal dynamics of human evolution.},
}
MeSH Terms:
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Humans
Africa
*Databases, Factual
*Archaeology/methods
Biological Evolution
*Software
Environment
Animals
Ecosystem
RevDate: 2026-10-07
UAV-based super-resolution instance segmentation enables ecological monitoring of sea cucumbers in shallow coral reef habitats.
Marine pollution bulletin, 233(Pt 3):120417 pii:S0025-326X(26)01204-X [Epub ahead of print].
Accurate monitoring of sea cucumbers from UAV imagery remains challenging because submerged individuals often exhibit low contrast, camouflage against coral-rubble backgrounds, and weak boundary information under water-surface disturbance. In particular, key visual cues such as body contours, surface texture, and papillae-like structures can be severely blurred in aerial images, limiting the reliability of automated recognition. To address these challenges, this study proposes SR-HoloMambaNet, an integrated framework with a direct high-resolution path and a super-resolution-assisted path. Native high-resolution patches can be processed directly by HoloMambaNet, while resolution-limited patches are reconstructed by MambaIR at a 4× magnification factor before entering the same instance-segmentation network. HoloMambaNet incorporates VSSBlock, CSwinTR, and Large Separable Kernel Attention (LSKA) to improve long-range dependency modeling, multi-scale feature representation, and segmentation under camouflage and complex seabed backgrounds. Experimental results showed that SRR substantially improved the downstream segmentation performance of degraded images, increasing the mean average precision (mAP@50) from 63.7% with bicubic interpolation to 82.7% with MambaIR reconstruction. On high-quality UAV images, the proposed HoloMambaNet achieved 93.7% precision, 82.0% recall, and 95.7% mAP@50 with only 4.10 M parameters and an 8.7 MB model size, outperforming mainstream instance-segmentation models such as Mask R-CNN, RT-DETR, and YOLO-series baselines. Under a frozen-source zero-shot protocol on five public external datasets, HoloMambaNet achieved the highest box mAP@50 on each dataset and a macro-average of 41.1%. The expert-verified annotation masks were also used to derive annotation-based reference summaries of patch-scale abundance, image-space apparent cover, morphology-related proxies, and local spatial arrangement. These results indicate that SR-HoloMambaNet provides a practical and lightweight solution for UAV-based shallow-water sea cucumber monitoring, with potential applications in large-scale benthic resource assessment and coral reef ecological conservation.
Additional Links: PMID-42843182
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@article {pmid42843182,
year = {2026},
author = {Zhao, F and Liu, Y and Wang, J and Xue, F and Yang, K and Shao, X and Chen, J and Yin, Z and Wu, H and Chen, Y and Xu, N},
title = {UAV-based super-resolution instance segmentation enables ecological monitoring of sea cucumbers in shallow coral reef habitats.},
journal = {Marine pollution bulletin},
volume = {233},
number = {Pt 3},
pages = {120417},
doi = {10.1016/j.marpolbul.2026.120417},
pmid = {42843182},
issn = {1879-3363},
abstract = {Accurate monitoring of sea cucumbers from UAV imagery remains challenging because submerged individuals often exhibit low contrast, camouflage against coral-rubble backgrounds, and weak boundary information under water-surface disturbance. In particular, key visual cues such as body contours, surface texture, and papillae-like structures can be severely blurred in aerial images, limiting the reliability of automated recognition. To address these challenges, this study proposes SR-HoloMambaNet, an integrated framework with a direct high-resolution path and a super-resolution-assisted path. Native high-resolution patches can be processed directly by HoloMambaNet, while resolution-limited patches are reconstructed by MambaIR at a 4× magnification factor before entering the same instance-segmentation network. HoloMambaNet incorporates VSSBlock, CSwinTR, and Large Separable Kernel Attention (LSKA) to improve long-range dependency modeling, multi-scale feature representation, and segmentation under camouflage and complex seabed backgrounds. Experimental results showed that SRR substantially improved the downstream segmentation performance of degraded images, increasing the mean average precision (mAP@50) from 63.7% with bicubic interpolation to 82.7% with MambaIR reconstruction. On high-quality UAV images, the proposed HoloMambaNet achieved 93.7% precision, 82.0% recall, and 95.7% mAP@50 with only 4.10 M parameters and an 8.7 MB model size, outperforming mainstream instance-segmentation models such as Mask R-CNN, RT-DETR, and YOLO-series baselines. Under a frozen-source zero-shot protocol on five public external datasets, HoloMambaNet achieved the highest box mAP@50 on each dataset and a macro-average of 41.1%. The expert-verified annotation masks were also used to derive annotation-based reference summaries of patch-scale abundance, image-space apparent cover, morphology-related proxies, and local spatial arrangement. These results indicate that SR-HoloMambaNet provides a practical and lightweight solution for UAV-based shallow-water sea cucumber monitoring, with potential applications in large-scale benthic resource assessment and coral reef ecological conservation.},
}
RevDate: 2026-10-07
CmpDate: 2026-10-07
Neural posterior estimation for population genetics.
bioRxiv : the preprint server for biology.
Simulation-based inference methods are increasingly being used in population genetics due to their flexibility and ability to be applied in settings where likelihood-based methods are intractable. Perhaps the best known such method is Approximate Bayesian Computation (ABC); however, its popularity is offset by its shortcomings which include computational expense and an unfortunate inability to effciently fit models to high-dimensional summaries of the data. An alternative approach that solves these issues is supervised machine learning (ML); however, ML methods generally do not yield Bayesian uncertainty estimates of the quantities they predict. Here, we apply a recently introduced method, neural posterior estimation (NPE), that combines the best facets of ABC and supervised ML by training a neural network to estimate the posterior distribution of a population genetics model. We first compare neural posterior estimation with other inference methods for a variety of population genetic tasks, and show that neural posterior estimators yield posterior distributions with high accuracy and efficiency. We compare learned posterior distributions given raw genotypes and various summary statistics as input data. Additionally, we apply neural posterior estimation for demographic inference for simple and more complex models to highlight its application, including an analysis of demographic history in Drosophila melanogaster. Finally, we provide a user friendly workflow that enables others to perform neural posterior estimation on their own genetic data.
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@article {pmid41573957,
year = {2026},
author = {Min, J and Ning, Y and Pope, NS and Baumdicker, F and Kern, AD},
title = {Neural posterior estimation for population genetics.},
journal = {bioRxiv : the preprint server for biology},
volume = {},
number = {},
pages = {},
pmid = {41573957},
issn = {2692-8205},
support = {R01 HG010774/HG/NHGRI NIH HHS/United States ; R35 GM148253/GM/NIGMS NIH HHS/United States ; },
abstract = {Simulation-based inference methods are increasingly being used in population genetics due to their flexibility and ability to be applied in settings where likelihood-based methods are intractable. Perhaps the best known such method is Approximate Bayesian Computation (ABC); however, its popularity is offset by its shortcomings which include computational expense and an unfortunate inability to effciently fit models to high-dimensional summaries of the data. An alternative approach that solves these issues is supervised machine learning (ML); however, ML methods generally do not yield Bayesian uncertainty estimates of the quantities they predict. Here, we apply a recently introduced method, neural posterior estimation (NPE), that combines the best facets of ABC and supervised ML by training a neural network to estimate the posterior distribution of a population genetics model. We first compare neural posterior estimation with other inference methods for a variety of population genetic tasks, and show that neural posterior estimators yield posterior distributions with high accuracy and efficiency. We compare learned posterior distributions given raw genotypes and various summary statistics as input data. Additionally, we apply neural posterior estimation for demographic inference for simple and more complex models to highlight its application, including an analysis of demographic history in Drosophila melanogaster. Finally, we provide a user friendly workflow that enables others to perform neural posterior estimation on their own genetic data.},
}
RevDate: 2026-10-07
CmpDate: 2026-10-07
Toward adaptive and high‑precision integrated pest management in the big data era.
Current opinion in insect science, 78:101570.
Integrated pest management (IPM) has long reduced pesticide use while improving economic and ecological sustainability through monitoring and systems analysis. However, traditional IPM models face limitations in predictability, cost, and system specificity. Recent advances in machine learning (ML) provide flexible predictive frameworks that enable reliable short‑term pest forecasting when sufficient data are available. At the same time, Internet of Things (IoT) technologies enable continuous acquisition of pest monitoring data for ML-based predictions. They also collect outcome metrics, such as yield, pest resistance, and environmental impacts, supporting feedback-driven IPM optimization. Emerging multimodal modeling approaches now offer new opportunities to integrate diverse data sources, including textual information, and guide more targeted, integrated, and minimally chemical-dependent intervention strategies. Combining IoT monitoring, ML-based pest prediction, and adaptive optimization supports diverse ways of delivering actionable IPM insights to stakeholders, from large-scale enterprises to smallholder farming communities. This convergence of technologies marks the emergence of truly adaptive, high‑precision IPM in the big‑data era.
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@article {pmid42341876,
year = {2026},
author = {Yamanaka, T and Sun, J and Kishi, S},
title = {Toward adaptive and high‑precision integrated pest management in the big data era.},
journal = {Current opinion in insect science},
volume = {78},
number = {},
pages = {101570},
doi = {10.1016/j.cois.2026.101570},
pmid = {42341876},
issn = {2214-5753},
mesh = {*Big Data ; Animals ; *Insect Control/methods ; *Machine Learning ; *Insecta ; Predictive Learning Models ; Internet of Things ; },
abstract = {Integrated pest management (IPM) has long reduced pesticide use while improving economic and ecological sustainability through monitoring and systems analysis. However, traditional IPM models face limitations in predictability, cost, and system specificity. Recent advances in machine learning (ML) provide flexible predictive frameworks that enable reliable short‑term pest forecasting when sufficient data are available. At the same time, Internet of Things (IoT) technologies enable continuous acquisition of pest monitoring data for ML-based predictions. They also collect outcome metrics, such as yield, pest resistance, and environmental impacts, supporting feedback-driven IPM optimization. Emerging multimodal modeling approaches now offer new opportunities to integrate diverse data sources, including textual information, and guide more targeted, integrated, and minimally chemical-dependent intervention strategies. Combining IoT monitoring, ML-based pest prediction, and adaptive optimization supports diverse ways of delivering actionable IPM insights to stakeholders, from large-scale enterprises to smallholder farming communities. This convergence of technologies marks the emergence of truly adaptive, high‑precision IPM in the big‑data era.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Big Data
Animals
*Insect Control/methods
*Machine Learning
*Insecta
Predictive Learning Models
Internet of Things
RevDate: 2026-10-06
CmpDate: 2026-10-05
Clinical and epidemiological characteristics of patients hospitalized for toxocariasis in Japan: A nationwide analysis using the diagnosis procedure combination database.
Parasite epidemiology and control, 35:e00546.
Toxocariasis is a zoonotic helminth infection caused by Toxocara canis or Toxocara cati. While it has traditionally been regarded as a pediatric soil-transmitted disease, recent reports from Japan suggest that an increasing number of adult-onset cases are potentially associated with foodborne transmission. Ocular involvement in adults can also result in severe visual impairment. However, nationwide data describing the epidemiological and clinical characteristics of hospitalized patients in Japan are limited. We conducted a nationwide retrospective study using the Japanese Diagnosis Procedure Combination database from the fiscal years 2014 through 2020. Hospitalized patients with toxocariasis were identified using ICD-10 code B83.0. Demographic characteristics, organ involvement, geographic distribution, and treatment patterns were descriptively analyzed. Forty-one patients with toxocariasis were identified. The median age was 53 years (range, 10-89 years), and 63% of the patients were male. None of the patients were younger than 10 years. Ocular involvement was the most frequent presentation (41%), and ophthalmologic surgery, including pars plana vitrectomy, was performed in 24% of the cases. Patients who were hospitalized were predominantly from the Kinki (32%) and Kyushu-Okinawa (29%) regions. Albendazole was administered to 54% of the patients, with a median inpatient treatment duration of 3 days (inpatient administration only). In Japan, toxocariasis requiring hospitalization predominantly affects middle-aged and older adults and is frequently associated with ocular involvement requiring surgical intervention. The adult-dominant patterns and geographic clustering in Western Japan may reflect region-specific exposure characteristics. Although limited to hospitalized patients and administrative data without diagnostic validation, these findings provide the first nationwide overview of severe toxocariasis requiring hospitalization in Japan and contribute to understanding its clinical and epidemiological profile.
Additional Links: PMID-42830730
PubMed:
Citation:
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@article {pmid42830730,
year = {2026},
author = {Matsunaga, T and Ohkubo, N and Yamasaki, K and Tahara, M and Nakamura, K and Ikegami, H and Sennari, K and Jotatsu, T and Nishida, C and Okawara, M and Fujino, Y and Matsuda, S and Fushimi, K and Mukae, H and Yatera, K},
title = {Clinical and epidemiological characteristics of patients hospitalized for toxocariasis in Japan: A nationwide analysis using the diagnosis procedure combination database.},
journal = {Parasite epidemiology and control},
volume = {35},
number = {},
pages = {e00546},
pmid = {42830730},
issn = {2405-6731},
abstract = {Toxocariasis is a zoonotic helminth infection caused by Toxocara canis or Toxocara cati. While it has traditionally been regarded as a pediatric soil-transmitted disease, recent reports from Japan suggest that an increasing number of adult-onset cases are potentially associated with foodborne transmission. Ocular involvement in adults can also result in severe visual impairment. However, nationwide data describing the epidemiological and clinical characteristics of hospitalized patients in Japan are limited. We conducted a nationwide retrospective study using the Japanese Diagnosis Procedure Combination database from the fiscal years 2014 through 2020. Hospitalized patients with toxocariasis were identified using ICD-10 code B83.0. Demographic characteristics, organ involvement, geographic distribution, and treatment patterns were descriptively analyzed. Forty-one patients with toxocariasis were identified. The median age was 53 years (range, 10-89 years), and 63% of the patients were male. None of the patients were younger than 10 years. Ocular involvement was the most frequent presentation (41%), and ophthalmologic surgery, including pars plana vitrectomy, was performed in 24% of the cases. Patients who were hospitalized were predominantly from the Kinki (32%) and Kyushu-Okinawa (29%) regions. Albendazole was administered to 54% of the patients, with a median inpatient treatment duration of 3 days (inpatient administration only). In Japan, toxocariasis requiring hospitalization predominantly affects middle-aged and older adults and is frequently associated with ocular involvement requiring surgical intervention. The adult-dominant patterns and geographic clustering in Western Japan may reflect region-specific exposure characteristics. Although limited to hospitalized patients and administrative data without diagnostic validation, these findings provide the first nationwide overview of severe toxocariasis requiring hospitalization in Japan and contribute to understanding its clinical and epidemiological profile.},
}
RevDate: 2026-10-07
CmpDate: 2026-10-05
Distributions of economically important nonindigenous forest pests in the conterminous United States.
Ecology, 107(10):e70551.
The geographical distributions of established nonindigenous forest insects and pathogens have historically not been well documented nor centrally aggregated, the absence of which has contributed to constrained efforts to manage and minimize resultant damages. To address this need, we present the construction of a centralized database accessible via a publicly available web portal, the Alien Forest Pest Explorer. All nonindigenous forest insect and pathogen species known to cause economic impacts in the conterminous U.S. were selected for inclusion in the database. The occurrence of these established pests, which is derived from a variety of data streams including reports by state and Federal agencies, the scientific literature, and biodiversity databases, is recorded at the county level. In addition to data on geographical distribution of the pests, the database also provides county-level data that quantifies the volume of host trees species derived from forest inventory data. Overall, the data and analyses presented here provide baseline information regarding the distribution of nonindigenous forest pests and changes in host resources. Our database can also help to provide a more complete understanding of the impacts of nonindigenous forest pests on U.S. forests and can be used as a public resource in supporting regional invasive forest pest research and management. The data are available for reuse under CC0 1.0 Universal licensing; however, we appreciate the citation of this data paper when reusing the dataset.
Additional Links: PMID-42831459
PubMed:
Citation:
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@article {pmid42831459,
year = {2026},
author = {Grong, KA and Morin, RS and Li, YS and Kong, NN and Crocker, SJ and Krist, FJ and Liebhold, AM and Fei, S},
title = {Distributions of economically important nonindigenous forest pests in the conterminous United States.},
journal = {Ecology},
volume = {107},
number = {10},
pages = {e70551},
pmid = {42831459},
issn = {1939-9170},
support = {23-JV-11242305-051//US Department of Agriculture Forest Service/ ; },
mesh = {Animals ; United States ; *Forests ; *Insecta/physiology ; *Trees ; Demography ; Databases, Factual ; },
abstract = {The geographical distributions of established nonindigenous forest insects and pathogens have historically not been well documented nor centrally aggregated, the absence of which has contributed to constrained efforts to manage and minimize resultant damages. To address this need, we present the construction of a centralized database accessible via a publicly available web portal, the Alien Forest Pest Explorer. All nonindigenous forest insect and pathogen species known to cause economic impacts in the conterminous U.S. were selected for inclusion in the database. The occurrence of these established pests, which is derived from a variety of data streams including reports by state and Federal agencies, the scientific literature, and biodiversity databases, is recorded at the county level. In addition to data on geographical distribution of the pests, the database also provides county-level data that quantifies the volume of host trees species derived from forest inventory data. Overall, the data and analyses presented here provide baseline information regarding the distribution of nonindigenous forest pests and changes in host resources. Our database can also help to provide a more complete understanding of the impacts of nonindigenous forest pests on U.S. forests and can be used as a public resource in supporting regional invasive forest pest research and management. The data are available for reuse under CC0 1.0 Universal licensing; however, we appreciate the citation of this data paper when reusing the dataset.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
United States
*Forests
*Insecta/physiology
*Trees
Demography
Databases, Factual
RevDate: 2026-10-05
CmpDate: 2026-10-05
Extracting AI agent-accessible data from biodiversity literature with corpus.
Current biology : CB, 36(19):R1019-R1020.
Much of our shared knowledge about biodiversity, including data on species' traits, relationships, and occurrences, is stored in the published literature. This body of knowledge can span multiple centuries, languages, and publication formats, making it challenging to collect, compare, and synthesize data across entire clades. New artificial intelligence (AI) tools, including large language models (LLMs) in particular, are well suited to integrate and summarize large bodies of text and figures. However, the biodiversity literature is too large and multi-layered to be reliably interrogated by simply placing publications into an LLM context window. For the typical tasks of biodiversity scientists (e.g., assembling descriptive characters, reconstructing nomenclatural history), we need structured, provenance-aware, and deterministic data retrieval. Here we present corpus: a tool for converting biodiversity literature PDFs for a clade of organisms into a searchable knowledge base (a 'corpuscle') of text, figures, and references. Users connect an LLM client via corpus' Model Context Protocol (MCP) server, to interact directly with the processed literature through predefined search tools. corpus addresses critical gaps in LLM applications for biology by transforming the literature into an explicit retrieval layer, rather than relying on hidden training data or probabilistic recollection.
Additional Links: PMID-42833191
Publisher:
PubMed:
Citation:
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@article {pmid42833191,
year = {2026},
author = {Church, SH and Mańko, MK and Zapata, F and Dunn, CW},
title = {Extracting AI agent-accessible data from biodiversity literature with corpus.},
journal = {Current biology : CB},
volume = {36},
number = {19},
pages = {R1019-R1020},
doi = {10.1016/j.cub.2026.08.019},
pmid = {42833191},
issn = {1879-0445},
mesh = {*Biodiversity ; Large Language Models ; *Artificial Intelligence ; Animals ; *Information Storage and Retrieval/methods ; },
abstract = {Much of our shared knowledge about biodiversity, including data on species' traits, relationships, and occurrences, is stored in the published literature. This body of knowledge can span multiple centuries, languages, and publication formats, making it challenging to collect, compare, and synthesize data across entire clades. New artificial intelligence (AI) tools, including large language models (LLMs) in particular, are well suited to integrate and summarize large bodies of text and figures. However, the biodiversity literature is too large and multi-layered to be reliably interrogated by simply placing publications into an LLM context window. For the typical tasks of biodiversity scientists (e.g., assembling descriptive characters, reconstructing nomenclatural history), we need structured, provenance-aware, and deterministic data retrieval. Here we present corpus: a tool for converting biodiversity literature PDFs for a clade of organisms into a searchable knowledge base (a 'corpuscle') of text, figures, and references. Users connect an LLM client via corpus' Model Context Protocol (MCP) server, to interact directly with the processed literature through predefined search tools. corpus addresses critical gaps in LLM applications for biology by transforming the literature into an explicit retrieval layer, rather than relying on hidden training data or probabilistic recollection.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Biodiversity
Large Language Models
*Artificial Intelligence
Animals
*Information Storage and Retrieval/methods
RevDate: 2026-10-05
Interaction matrices as unifying tools for navigating ecological complexity.
Nature ecology & evolution [Epub ahead of print].
Interaction matrices summarize pairwise species impacts within ecological communities into an analytically tractable format. Despite their contribution to linking subdisciplines and advancing our understanding of ecosystem dynamics, they have faced recurring criticism for oversimplifying ecological complexity. Extensions developed to address specific shortcomings often come with trade-offs, including increased data demands and analytical complexity. Here we review the foundations of the interaction matrix framework and examine the state of the art of approaches developed to tackle its challenges. We argue that the unifying role of interaction matrices could be improved by embracing, rather than fighting, their inherent nature as uncertain and transient abstractions. We explore how such an approach could bring substantial benefits and incorporate advances from wider complexity sciences. As we enter the second century of interaction matrices within ecology, such a shift will reinforce their place as a valuable tool to unlock the complex dynamics of ecological communities.
Additional Links: PMID-42834125
PubMed:
Citation:
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@article {pmid42834125,
year = {2026},
author = {Terry, JCD and Tabi, A and García-Callejas, D and Domínguez-García, V},
title = {Interaction matrices as unifying tools for navigating ecological complexity.},
journal = {Nature ecology & evolution},
volume = {},
number = {},
pages = {},
pmid = {42834125},
issn = {2397-334X},
support = {ECF-2022-666//Leverhulme Trust/ ; UKRI4153//RCUK | Natural Environment Research Council (NERC)/ ; FWF ESPRIT Award Esp-671//Austrian Science Fund (Fonds zur Förderung der Wissenschaftlichen Forschung)/ ; No 101064340//EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions)/ ; },
abstract = {Interaction matrices summarize pairwise species impacts within ecological communities into an analytically tractable format. Despite their contribution to linking subdisciplines and advancing our understanding of ecosystem dynamics, they have faced recurring criticism for oversimplifying ecological complexity. Extensions developed to address specific shortcomings often come with trade-offs, including increased data demands and analytical complexity. Here we review the foundations of the interaction matrix framework and examine the state of the art of approaches developed to tackle its challenges. We argue that the unifying role of interaction matrices could be improved by embracing, rather than fighting, their inherent nature as uncertain and transient abstractions. We explore how such an approach could bring substantial benefits and incorporate advances from wider complexity sciences. As we enter the second century of interaction matrices within ecology, such a shift will reinforce their place as a valuable tool to unlock the complex dynamics of ecological communities.},
}
RevDate: 2026-10-07
CmpDate: 2026-10-06
A curated genome-scale nucleotide diversity panel of non-human primates.
Genome biology, 27(1):.
BACKGROUND: Primates constitute one of the most phylogenetically and ecologically diverse eutherian mammalian orders and have a central role in advancing our knowledge of human evolution, speciation processes, and conservation biology. Although thousands of whole-genome sequences are available across many primate taxa, discrepancies in data processing-particularly the lack of ploidy-aware variant calling in sex-linked regions-have limited the utility of existing datasets for large-scale comparative analyses.
RESULTS: Here, we use publicly available short-read sequencing data from non-human primates, recently published primate genome assemblies, and a ploidy-aware variant calling procedure to generate a genome-scale nucleotide diversity panel comprising 3,240 individuals from 269 species and 71 genera. To further facilitate cross-species comparisons, we generate a multiple-genome alignment of the primate assemblies used for variant calling.
CONCLUSIONS: This curated resource of non-human primate diversity provides a foundation for future research in primate evolutionary biology, speciation, and sex chromosome evolution.
Additional Links: PMID-42834407
PubMed:
Citation:
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@article {pmid42834407,
year = {2026},
author = {Pankratov, V and Pedersen, BM and Sørensen, EF and Munch, K and Bataillon, T and Schierup, MH and Bergman, J},
title = {A curated genome-scale nucleotide diversity panel of non-human primates.},
journal = {Genome biology},
volume = {27},
number = {1},
pages = {},
pmid = {42834407},
issn = {1474-760X},
mesh = {Animals ; *Primates/genetics/classification ; *Genome ; *Genetic Variation ; Phylogeny ; Humans ; Genomics ; Evolution, Molecular ; Biocuration ; },
abstract = {BACKGROUND: Primates constitute one of the most phylogenetically and ecologically diverse eutherian mammalian orders and have a central role in advancing our knowledge of human evolution, speciation processes, and conservation biology. Although thousands of whole-genome sequences are available across many primate taxa, discrepancies in data processing-particularly the lack of ploidy-aware variant calling in sex-linked regions-have limited the utility of existing datasets for large-scale comparative analyses.
RESULTS: Here, we use publicly available short-read sequencing data from non-human primates, recently published primate genome assemblies, and a ploidy-aware variant calling procedure to generate a genome-scale nucleotide diversity panel comprising 3,240 individuals from 269 species and 71 genera. To further facilitate cross-species comparisons, we generate a multiple-genome alignment of the primate assemblies used for variant calling.
CONCLUSIONS: This curated resource of non-human primate diversity provides a foundation for future research in primate evolutionary biology, speciation, and sex chromosome evolution.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Animals
*Primates/genetics/classification
*Genome
*Genetic Variation
Phylogeny
Humans
Genomics
Evolution, Molecular
Biocuration
RevDate: 2026-10-06
CmpDate: 2026-10-06
Intrinsic capacity modifies the risk of depression and anxiety through metabolomic signature.
Psychological medicine, 56:e315 pii:S0033291726106047.
BACKGROUND: The World Health Organization (WHO) developed an assessment for healthy aging termed intrinsic capacity (IC). However, the association between IC and depression/anxiety remains poorly understood, with limited understanding of the underlying metabolic mechanisms.
METHODS: This prospective cohort study comprised 212,033 UK Biobank participants recruited between 2006 and 2010. We calculated a UK Biobank-adapted four-domain IC deficit score using seven functional status indicators across psychological, sensory, vitality, and locomotor domains. Elastic net regression was employed to derive a metabolic signature that represented IC status. Polygenic risk scores (PRS) for depression and anxiety were computed from associated risk variants.
RESULTS: Compared with a 0 IC deficit score, participants with a 4+ score had higher risk, with hazard ratios (HRs) (95% CIs) of 3.96 (3.72-4.21) for depression and 3.03 (2.82-3.25) for anxiety. The metabolic signature of IC comprised 59 metabolites, with mediation effects of 1.007 (1.005, 1.008) for depression and 1.006 (1.004, 1.007) for anxiety. The highest hazards were observed in participants with high PRS and 4+ IC score; the HRs were 4.36 (3.70-5.13) for depression and 3.46 (2.87-4.17) for anxiety.
CONCLUSIONS: IC is associated with a higher risk of depression and anxiety, possibly mediated by its metabolic signature, with enhanced effects in genetically susceptible individuals.
Additional Links: PMID-42834851
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PubMed:
Citation:
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@article {pmid42834851,
year = {2026},
author = {Song, S and Suo, X and Guo, J and Li, C and Lu, S and Zhu, Y and Kou, G and Bo, Y},
title = {Intrinsic capacity modifies the risk of depression and anxiety through metabolomic signature.},
journal = {Psychological medicine},
volume = {56},
number = {},
pages = {e315},
doi = {10.1017/S0033291726106047},
pmid = {42834851},
issn = {1469-8978},
mesh = {Humans ; *Anxiety/metabolism/epidemiology/genetics ; Female ; Prospective Studies ; *Depression/metabolism/epidemiology/genetics ; United Kingdom/epidemiology ; Male ; Genetic Risk Score ; Middle Aged ; Aged ; UK Biobank ; Metabolomics ; },
abstract = {BACKGROUND: The World Health Organization (WHO) developed an assessment for healthy aging termed intrinsic capacity (IC). However, the association between IC and depression/anxiety remains poorly understood, with limited understanding of the underlying metabolic mechanisms.
METHODS: This prospective cohort study comprised 212,033 UK Biobank participants recruited between 2006 and 2010. We calculated a UK Biobank-adapted four-domain IC deficit score using seven functional status indicators across psychological, sensory, vitality, and locomotor domains. Elastic net regression was employed to derive a metabolic signature that represented IC status. Polygenic risk scores (PRS) for depression and anxiety were computed from associated risk variants.
RESULTS: Compared with a 0 IC deficit score, participants with a 4+ score had higher risk, with hazard ratios (HRs) (95% CIs) of 3.96 (3.72-4.21) for depression and 3.03 (2.82-3.25) for anxiety. The metabolic signature of IC comprised 59 metabolites, with mediation effects of 1.007 (1.005, 1.008) for depression and 1.006 (1.004, 1.007) for anxiety. The highest hazards were observed in participants with high PRS and 4+ IC score; the HRs were 4.36 (3.70-5.13) for depression and 3.46 (2.87-4.17) for anxiety.
CONCLUSIONS: IC is associated with a higher risk of depression and anxiety, possibly mediated by its metabolic signature, with enhanced effects in genetically susceptible individuals.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
*Anxiety/metabolism/epidemiology/genetics
Female
Prospective Studies
*Depression/metabolism/epidemiology/genetics
United Kingdom/epidemiology
Male
Genetic Risk Score
Middle Aged
Aged
UK Biobank
Metabolomics
RevDate: 2026-10-06
CmpDate: 2026-10-06
Wearable sensors offer opportunities for phenotyping perinatal mood disorders: a narrative review.
Reproduction (Cambridge, England), 172(4):.
In brief: The perinatal period represents a convergence of sleep disruption, circadian misalignment, and reproductive hormonal changes, which are the same biological axes implicated in depression and anxiety disorders. Analyses of wearable data complement clinical standards, capturing individual biological trajectories and identifying patterns that confer psychiatric risk. Abstract: Pregnancy and the postpartum period are known to elicit changes in sleep, circadian rhythms, and hormonal dynamics. The same biological axes are implicated in anxiety and depression in the general population. Given the high burden of perinatal mental health and the dire consequences of maternal wellbeing on the mother and infant alike, research differentiating those most at risk is a priority. Why some pregnancies experience these changes without causing mood disorders when many do is unclear but suggests there must be multiple types of disruption, some associated with more risk than others. Current standards of care rely on periodic, and often self-reported, assessments collected around scheduled visits, which can limit opportunities for early detection and timely intervention. We review evidence that wearable technology can complement the gold standard by offering continuous, high-resolution, personalized ecological monitoring of sleep, circadian rhythms, and hormonal dynamics at the individual level. These rich data, coupled with appropriate data science and machine learning techniques, enable early typing of pregnancies to support earlier diagnosis and intervention, with the potential for personalized insights, tailored treatment, and faster recovery.
Additional Links: PMID-42704686
Publisher:
PubMed:
Citation:
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@article {pmid42704686,
year = {2026},
author = {Carrioli, O and Bruce, LK and Kriplani, SM and Schaap, T and Stewart, C and Smarr, BL},
title = {Wearable sensors offer opportunities for phenotyping perinatal mood disorders: a narrative review.},
journal = {Reproduction (Cambridge, England)},
volume = {172},
number = {4},
pages = {},
doi = {10.1093/reprod/xaag115},
pmid = {42704686},
issn = {1741-7899},
mesh = {Humans ; Female ; Pregnancy ; *Mood Disorders/diagnosis ; *Wearable Electronic Devices ; Circadian Rhythm ; *Pregnancy Complications/diagnosis/psychology ; Phenotype ; Sleep ; Digital Health ; },
abstract = {In brief: The perinatal period represents a convergence of sleep disruption, circadian misalignment, and reproductive hormonal changes, which are the same biological axes implicated in depression and anxiety disorders. Analyses of wearable data complement clinical standards, capturing individual biological trajectories and identifying patterns that confer psychiatric risk. Abstract: Pregnancy and the postpartum period are known to elicit changes in sleep, circadian rhythms, and hormonal dynamics. The same biological axes are implicated in anxiety and depression in the general population. Given the high burden of perinatal mental health and the dire consequences of maternal wellbeing on the mother and infant alike, research differentiating those most at risk is a priority. Why some pregnancies experience these changes without causing mood disorders when many do is unclear but suggests there must be multiple types of disruption, some associated with more risk than others. Current standards of care rely on periodic, and often self-reported, assessments collected around scheduled visits, which can limit opportunities for early detection and timely intervention. We review evidence that wearable technology can complement the gold standard by offering continuous, high-resolution, personalized ecological monitoring of sleep, circadian rhythms, and hormonal dynamics at the individual level. These rich data, coupled with appropriate data science and machine learning techniques, enable early typing of pregnancies to support earlier diagnosis and intervention, with the potential for personalized insights, tailored treatment, and faster recovery.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
Humans
Female
Pregnancy
*Mood Disorders/diagnosis
*Wearable Electronic Devices
Circadian Rhythm
*Pregnancy Complications/diagnosis/psychology
Phenotype
Sleep
Digital Health
RevDate: 2026-10-05
CmpDate: 2026-10-03
Low Levels of Amino Acid Auxotrophy Among Environmental Pseudomonas Isolates.
Environmental microbiology, 28(10):e70434.
Auxotrophy, the inability of bacteria to synthesize one or multiple essential metabolites, is thought to be common among bacteria. However, studies often rely on either bioinformatic genome-based prediction of auxotrophies or on experiments with low strain numbers. Here, we combine experimental and bioinformatic approaches to assess amino acid auxotrophies among 315 co-isolated natural Pseudomonas strains from pond and soil habitats. Experiments revealed that Pseudomonas isolates are predominantly prototrophs. We identified one histidine auxotroph, one auxotroph with complex intertwined dependencies and four 'fragile' phenotypes showing delayed growth without supplemented amino acids. Applying three bioinformatic pipelines largely confirmed experimental data but yielded specific biases in auxotrophy over- or underestimation. Moreover, none of the pipelines could resolve the genetic basis of the slow-growing phenotypes or of more complex dependencies. Our analysis further revealed the existence of multiple alternative biosynthesis pathways for methionine, proline and phenylalanine, with significant pathway enrichments being linked to phylogeny and habitat. We conclude that combining experiments with bioinformatics is a powerful approach to assess the metabolic potential of environmental bacteria. Moreover, taxa like Pseudomonas can be predominantly prototrophic possibly owing to their generalist lifestyle, thus calling for nuanced ecological concepts predicting auxotrophy levels based on lifestyle and habitat.
Additional Links: PMID-42827348
PubMed:
Citation:
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@article {pmid42827348,
year = {2026},
author = {Maréchal, S and Heiniger, B and Gu, S and Dash, S and Ahrens, CH and Kümmerli, R},
title = {Low Levels of Amino Acid Auxotrophy Among Environmental Pseudomonas Isolates.},
journal = {Environmental microbiology},
volume = {28},
number = {10},
pages = {e70434},
pmid = {42827348},
issn = {1462-2920},
support = {212266//Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung/ ; 197391//Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung/ ; },
mesh = {*Pseudomonas/metabolism/isolation & purification/genetics/classification ; *Amino Acids/metabolism ; Soil Microbiology ; Computational Biology ; Phylogeny ; Ponds/microbiology ; Ecosystem ; },
abstract = {Auxotrophy, the inability of bacteria to synthesize one or multiple essential metabolites, is thought to be common among bacteria. However, studies often rely on either bioinformatic genome-based prediction of auxotrophies or on experiments with low strain numbers. Here, we combine experimental and bioinformatic approaches to assess amino acid auxotrophies among 315 co-isolated natural Pseudomonas strains from pond and soil habitats. Experiments revealed that Pseudomonas isolates are predominantly prototrophs. We identified one histidine auxotroph, one auxotroph with complex intertwined dependencies and four 'fragile' phenotypes showing delayed growth without supplemented amino acids. Applying three bioinformatic pipelines largely confirmed experimental data but yielded specific biases in auxotrophy over- or underestimation. Moreover, none of the pipelines could resolve the genetic basis of the slow-growing phenotypes or of more complex dependencies. Our analysis further revealed the existence of multiple alternative biosynthesis pathways for methionine, proline and phenylalanine, with significant pathway enrichments being linked to phylogeny and habitat. We conclude that combining experiments with bioinformatics is a powerful approach to assess the metabolic potential of environmental bacteria. Moreover, taxa like Pseudomonas can be predominantly prototrophic possibly owing to their generalist lifestyle, thus calling for nuanced ecological concepts predicting auxotrophy levels based on lifestyle and habitat.},
}
MeSH Terms:
show MeSH Terms
hide MeSH Terms
*Pseudomonas/metabolism/isolation & purification/genetics/classification
*Amino Acids/metabolism
Soil Microbiology
Computational Biology
Phylogeny
Ponds/microbiology
Ecosystem
RevDate: 2026-10-06
CmpDate: 2026-10-03
Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.
Molecular ecology, 35(19):e70570.
Gene Ontology (GO) enrichment analysis has been widely adopted for interpretating omics data, including in ecological research. Although valuable for summarizing large gene lists into functional categories, it is often treated as the final interpretive step. In ecological omics, where functional annotations are frequently incomplete and experimental validation is often difficult, this reliance can lead to repetitive, generic conclusions that lack environmental and mechanistic specificity. Although previous literature has addressed the statistical and annotation-related limitations of GO enrichment, its role in shaping the broader interpretive process has received less critical attention. Here, we highlight a conceptual weakness: the treatment of enriched GO terms as definitive biological insight. We focus particularly on ecological studies of non-model organisms in complex, and heterogeneous environments. We discuss complementary strategies, including co-expression network analysis, integration with environmental metadata, phylogenetically informed annotation, and AI-assisted functional inference. To promote more context-sensitive interpretation, we introduce the concept of GO-Deep, which frames GO enrichment as a starting point for integrative, multilayered functional insight. By reframing GO enrichment as an entry point rather than a conclusion, ecological omics can move toward more mechanistically informative and environmentally grounded interpretations of high-throughput data.
Additional Links: PMID-42827388
PubMed:
Citation:
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@article {pmid42827388,
year = {2026},
author = {Ahi, EP and Karagic, N and Papakostas, S},
title = {Problems With GO Enrichment as an Endpoint for Ecological Omics Interpretation.},
journal = {Molecular ecology},
volume = {35},
number = {19},
pages = {e70570},
pmid = {42827388},
issn = {1365-294X},
mesh = {Animals ; *Computational Biology/methods ; *Ecology/methods ; *Gene Ontology ; Gene Regulatory Networks ; Genomics/methods ; Molecular Sequence Annotation ; },
abstract = {Gene Ontology (GO) enrichment analysis has been widely adopted for interpretating omics data, including in ecological research. Although valuable for summarizing large gene lists into functional categories, it is often treated as the final interpretive step. In ecological omics, where functional annotations are frequently incomplete and experimental validation is often difficult, this reliance can lead to repetitive, generic conclusions that lack environmental and mechanistic specificity. Although previous literature has addressed the statistical and annotation-related limitations of GO enrichment, its role in shaping the broader interpretive process has received less critical attention. Here, we highlight a conceptual weakness: the treatment of enriched GO terms as definitive biological insight. We focus particularly on ecological studies of non-model organisms in complex, and heterogeneous environments. We discuss complementary strategies, including co-expression network analysis, integration with environmental metadata, phylogenetically informed annotation, and AI-assisted functional inference. To promote more context-sensitive interpretation, we introduce the concept of GO-Deep, which frames GO enrichment as a starting point for integrative, multilayered functional insight. By reframing GO enrichment as an entry point rather than a conclusion, ecological omics can move toward more mechanistically informative and environmentally grounded interpretations of high-throughput data.},
}
MeSH Terms:
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Animals
*Computational Biology/methods
*Ecology/methods
*Gene Ontology
Gene Regulatory Networks
Genomics/methods
Molecular Sequence Annotation
RevDate: 2026-10-05
CmpDate: 2026-10-03
A Systematic Review on Green Synthesized Selenium Nanoparticles as Antioxidant and Antidiabetic Agents: Mechanistic Insights and Therapeutic Potential.
Avicenna journal of medical biotechnology, 18(3):167-188.
Nanotechnology has introduced revolutionary progress in medical sciences, providing unparalleled prospects for diagnosing and treating diseases. Notably, Nanomedicine enables targeted drug delivery, maximizes therapeutic effects, limits undesirable effects, and enhances therapeutic precision, which was unattainable with conventional methods. Furthermore, integrating natural biomolecules in nanoparticle synthesis has evolved as a sustainable approach, combining ecological safety with improved biocompatibility and pharmacological performance. This review aims to systematically scrutinize the literature on the beneficial effects of green Selenium Nanoparticles (SeNPs) on antioxidant and anti-diabetic potential. For this study, the literature was meticulously searched, and data were collected from preferred sources, including PubMed, ScienceDirect, ScienceOpen, DOAJ, Google Scholar, ResearchGate, and Scilit. The literature search was restricted to English-language works published between 2014 and 2024. Data collection focused on the antioxidant and anti-diabetic properties of green-synthesized SeNPs, which were reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Methods like DPPH, ABTS, and FRAP assays were used to assess the antioxidant activity. This review finds that Aloe vera, Annona muricata (A. muricata), Waltheria indica (W. indica) (IC50 0.00692), Millettia pinnata (IC50 0.0077), Camellia sinensis, Citrus sinensis (IC50 0.00849) mediated NPs in DPPH and W. indica (IC50 0.01685), A. muricata, Calluna vulgaris (IC50 0.01687), Echinacea purpurea, Aloe vera, Blighia sapida NPs in ABTS (in mg/ml concentration) exhibited a very promising anti-oxidant effect. The plant Fagonia critica (F. cretica) (IC50 0.1), Cassica auriculata (C. auriculata), Moringa oleifera (M. oleifera), Caralluma tuberculate (C. tuberculate) in α-glucosidase and F. cretica, C. auriculata, M. oleifera, Broccoli florets, C. tuberculata mediated NPs, in α-amylase assay (mg/ml concentration) showed the most prominent antidiabetic effects. Therefore, the green-synthesized SeNPs could be considered as distinct antioxidant and antidiabetic agents, potentially contributing to both antidiabetic and anti-oxidant therapy.
Additional Links: PMID-42828078
PubMed:
Citation:
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hide bibtex listing
@article {pmid42828078,
year = {2026},
author = {Ahamed, S and Ahamed, A and Akhter, S and Islam, F and Istiak Sabbir, S and Khandaker, S and Rahman, A},
title = {A Systematic Review on Green Synthesized Selenium Nanoparticles as Antioxidant and Antidiabetic Agents: Mechanistic Insights and Therapeutic Potential.},
journal = {Avicenna journal of medical biotechnology},
volume = {18},
number = {3},
pages = {167-188},
pmid = {42828078},
issn = {2008-2835},
abstract = {Nanotechnology has introduced revolutionary progress in medical sciences, providing unparalleled prospects for diagnosing and treating diseases. Notably, Nanomedicine enables targeted drug delivery, maximizes therapeutic effects, limits undesirable effects, and enhances therapeutic precision, which was unattainable with conventional methods. Furthermore, integrating natural biomolecules in nanoparticle synthesis has evolved as a sustainable approach, combining ecological safety with improved biocompatibility and pharmacological performance. This review aims to systematically scrutinize the literature on the beneficial effects of green Selenium Nanoparticles (SeNPs) on antioxidant and anti-diabetic potential. For this study, the literature was meticulously searched, and data were collected from preferred sources, including PubMed, ScienceDirect, ScienceOpen, DOAJ, Google Scholar, ResearchGate, and Scilit. The literature search was restricted to English-language works published between 2014 and 2024. Data collection focused on the antioxidant and anti-diabetic properties of green-synthesized SeNPs, which were reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. Methods like DPPH, ABTS, and FRAP assays were used to assess the antioxidant activity. This review finds that Aloe vera, Annona muricata (A. muricata), Waltheria indica (W. indica) (IC50 0.00692), Millettia pinnata (IC50 0.0077), Camellia sinensis, Citrus sinensis (IC50 0.00849) mediated NPs in DPPH and W. indica (IC50 0.01685), A. muricata, Calluna vulgaris (IC50 0.01687), Echinacea purpurea, Aloe vera, Blighia sapida NPs in ABTS (in mg/ml concentration) exhibited a very promising anti-oxidant effect. The plant Fagonia critica (F. cretica) (IC50 0.1), Cassica auriculata (C. auriculata), Moringa oleifera (M. oleifera), Caralluma tuberculate (C. tuberculate) in α-glucosidase and F. cretica, C. auriculata, M. oleifera, Broccoli florets, C. tuberculata mediated NPs, in α-amylase assay (mg/ml concentration) showed the most prominent antidiabetic effects. Therefore, the green-synthesized SeNPs could be considered as distinct antioxidant and antidiabetic agents, potentially contributing to both antidiabetic and anti-oxidant therapy.},
}
RevDate: 2026-10-03
Cognitive and institutional barriers to effective natural resource management under global change.
Conservation biology : the journal of the Society for Conservation Biology [Epub ahead of print].
Many of the most challenging decisions facing natural resource managers today can be understood as time dependent. The concept of time-dependent decisions is useful when considering natural resource management decisions that are characterized by nonstationarity in the underlying ecological system, uncertainty surrounding key ecological relationships, efficacy of management interventions, and difficult trade-offs between the present and the future. In a time-dependent decision, the optimal action changes depending on when the decision is made. We surveyed literature from the fields of cognitive psychology, environmental decision-making, and natural resource management to identify a key set of cognitive and institutional barriers that prevent decision makers from recognizing their decisions as time dependent. This failure obscures the complexity of nonstationarity, uncertainty, and intertemporal choice in natural resource management and facilitates assumptions of stationarity and time independence. We used land acquisition in the context of climate change as an example to explore the barriers to effective time-dependent decision-making at both individual and institutional scales. Using a theoretical model of land acquisition, we quantified the value of accounting for time dependence by comparing the performance of time-dependent, nonstationary decision models with models that assume time independence and stationarity. We found that the conservation value of land acquisition decisions was significantly improved through the use of time-dependent optimization models and that this improvement increased as nonstationarity increased. Finally, explicitly recognizing the time dependence of many natural resource management decisions will help improve the utility of existing decision tools and frameworks.
Additional Links: PMID-42828761
Publisher:
PubMed:
Citation:
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@article {pmid42828761,
year = {2026},
author = {Rubenstein, MA and Berl, REW and Chadès, I and Epanchin-Niell, RS and Morelli, TL and Runge, MC},
title = {Cognitive and institutional barriers to effective natural resource management under global change.},
journal = {Conservation biology : the journal of the Society for Conservation Biology},
volume = {},
number = {},
pages = {e70393},
doi = {10.1111/cobi.70393},
pmid = {42828761},
issn = {1523-1739},
support = {//John Wesley Powell Center for Analysis and Synthesis/ ; //U.S. Geological Survey/ ; },
abstract = {Many of the most challenging decisions facing natural resource managers today can be understood as time dependent. The concept of time-dependent decisions is useful when considering natural resource management decisions that are characterized by nonstationarity in the underlying ecological system, uncertainty surrounding key ecological relationships, efficacy of management interventions, and difficult trade-offs between the present and the future. In a time-dependent decision, the optimal action changes depending on when the decision is made. We surveyed literature from the fields of cognitive psychology, environmental decision-making, and natural resource management to identify a key set of cognitive and institutional barriers that prevent decision makers from recognizing their decisions as time dependent. This failure obscures the complexity of nonstationarity, uncertainty, and intertemporal choice in natural resource management and facilitates assumptions of stationarity and time independence. We used land acquisition in the context of climate change as an example to explore the barriers to effective time-dependent decision-making at both individual and institutional scales. Using a theoretical model of land acquisition, we quantified the value of accounting for time dependence by comparing the performance of time-dependent, nonstationary decision models with models that assume time independence and stationarity. We found that the conservation value of land acquisition decisions was significantly improved through the use of time-dependent optimization models and that this improvement increased as nonstationarity increased. Finally, explicitly recognizing the time dependence of many natural resource management decisions will help improve the utility of existing decision tools and frameworks.},
}
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RJR Experience and Expertise
Researcher
Robbins holds BS, MS, and PhD degrees in the life sciences. He served as a tenured faculty member in the Zoology and Biological Science departments at Michigan State University. He is currently exploring the intersection between genomics, microbial ecology, and biodiversity — an area that promises to transform our understanding of the biosphere.
Educator
Robbins has extensive experience in college-level education: At MSU he taught introductory biology, genetics, and population genetics. At JHU, he was an instructor for a special course on biological database design. At FHCRC, he team-taught a graduate-level course on the history of genetics. At Bellevue College he taught medical informatics.
Administrator
Robbins has been involved in science administration at both the federal and the institutional levels. At NSF he was a program officer for database activities in the life sciences, at DOE he was a program officer for information infrastructure in the human genome project. At the Fred Hutchinson Cancer Research Center, he served as a vice president for fifteen years.
Technologist
Robbins has been involved with information technology since writing his first Fortran program as a college student. At NSF he was the first program officer for database activities in the life sciences. At JHU he held an appointment in the CS department and served as director of the informatics core for the Genome Data Base. At the FHCRC he was VP for Information Technology.
Publisher
While still at Michigan State, Robbins started his first publishing venture, founding a small company that addressed the short-run publishing needs of instructors in very large undergraduate classes. For more than 20 years, Robbins has been operating The Electronic Scholarly Publishing Project, a web site dedicated to the digital publishing of critical works in science, especially classical genetics.
Speaker
Robbins is well-known for his speaking abilities and is often called upon to provide keynote or plenary addresses at international meetings. For example, in July, 2012, he gave a well-received keynote address at the Global Biodiversity Informatics Congress, sponsored by GBIF and held in Copenhagen. The slides from that talk can be seen HERE.
Facilitator
Robbins is a skilled meeting facilitator. He prefers a participatory approach, with part of the meeting involving dynamic breakout groups, created by the participants in real time: (1) individuals propose breakout groups; (2) everyone signs up for one (or more) groups; (3) the groups with the most interested parties then meet, with reports from each group presented and discussed in a subsequent plenary session.
Designer
Robbins has been engaged with photography and design since the 1960s, when he worked for a professional photography laboratory. He now prefers digital photography and tools for their precision and reproducibility. He designed his first web site more than 20 years ago and he personally designed and implemented this web site. He engages in graphic design as a hobby.
RJR Picks from Around the Web (updated 11 MAY 2018 )
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Treating Disease with Fecal Transplantation
Fossils of miniature humans (hobbits) discovered in Indonesia
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Dinosaur tail, complete with feathers, found preserved in amber.
Astronomy
Mysterious fast radio burst (FRB) detected in the distant universe.
Big Data & Informatics
Big Data: Buzzword or Big Deal?
Hacking the genome: Identifying anonymized human subjects using publicly available data.