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Bibliography on: Ecological Informatics

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Robert J. Robbins is a biologist, an educator, a science administrator, a publisher, an information technologist, and an IT leader and manager who specializes in advancing biomedical knowledge and supporting education through the application of information technology. More About:  RJR | OUR TEAM | OUR SERVICES | THIS WEBSITE

RJR: Recommended Bibliography 01 Oct 2026 at 01:46 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®)

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RevDate: 2026-09-29
CmpDate: 2026-09-29

Hu D, Sun C, Xin T, et al (2026)

Integrated analyses of metagenomics, metabolomics and culture-based assays reveal functional roles of gut microbiota in Felidae.

NPJ biofilms and microbiomes, 12(1):.

The functional roles of gut microbiota in carnivores remain poorly understood. Here, we integrated metagenomics, metabolomics, proteomics and culture-based functional assays to characterize metabolic potential of gut microbiota across 14 captive Felidae species. Comparative metagenomics analysis revealed that the Felidae gut microbiome is distinct from that of non-Felidae and reflects carnivorous dietary patterns. Genus-level core microbiota were dominated by Clostridium, Collinsella and Bacteroides, with functional enrichment in carbohydrate and amino acid metabolism. Of 219 reconstructed metagenome-assembled genomes (MAGs), 27 were identified as core MAGs containing proteases- and lipases- encoding genes, with ATP-dependent Clp proteases predominating and enriched KEGG orthologs mainly associated with amino acid metabolism. Fecal metabolomics identified 1316 metabolites shared among Felidae species, with KEGG analysis showing they were involved in amino acid and lipid metabolism and significantly enriched in protein digestion and absorption pathway. The amino acid- and lipid-related metabolites were correlated with the relative abundance of core MAGs. Culture-based assays revealed proteolytic and lipolytic activities across isolates, supported by proteomics evidence of predominant ATP-dependent proteases. In vitro fermentation with representative isolates generated fatty-acid-dominated metabolites consistent with fecal metabolomic profiles. Together, our findings demonstrate that Felidae gut microbiota play a critical role in amino acid metabolism for carnivory.

RevDate: 2026-09-30
CmpDate: 2026-09-30

Zhang XJ, Wang XH, Li R, et al (2026)

Integrated multi-omics and functional characterization reveal that COL6-mediated flavonoid metabolism contributes to drought tolerance in Juniperus sabina.

Plant physiology and biochemistry : PPB, 238:111614.

Drought stress significantly constrains plant productivity in arid and semi-arid habitats. Understanding the molecular pathways of drought tolerance is essential for germplasm enhancement and ecological restoration. This study investigated the drought adaptation mechanisms of Juniperus sabina L., an ecologically vital evergreen shrub, using integrated physiological, transcriptomic, and metabolomic analyses. Under extreme drought stress, the drought-tolerant provenance (DBD) demonstrated superior photosynthetic stability and robust antioxidant capacity compared to the drought-sensitive provenance (WDH). WDH exhibited significant photosystem impairment and membrane degradation, indicated by elevated relative electrical conductivity and malondialdehyde levels. Integrated analysis identified phenylpropanoid and flavonoid biosynthesis as critical pathways for adaptation. Notably, the DBD provenance utilized a specific metabolic reprogramming strategy, potentially mediated by the transcription factor CONSTANS-LIKE 6 (COL6). This regulatory mechanism involved down-regulating upstream biosynthetic genes (e.g., 4CL, CHS) while activating downstream modification genes (e.g., UGT, COMT-2). This shift redirected metabolic flux toward the accumulation of specific antioxidant flavonoids, such as syringetin, while maintaining cellular structural integrity. Our findings reveal a COL6-mediated regulatory network that coordinates metabolic flux redistribution and stress adaptation in J. sabina. Furthermore, transient overexpression of JsCOL6 in Nicotiana benthamiana confirmed its nuclear localization and demonstrated that it significantly enhanced drought tolerance. JsCOL6-overexpressing plants exhibited robust antioxidant capacity under PEG-induced drought stress, which was molecularly coupled with the transcriptional up-regulation of the downstream peroxidase gene (NbPER-1) and elevated activities of antioxidant enzymes. These results highlight promising molecular targets for breeding drought-resistant conifers and optimizing secondary metabolite production in marginal environments.

RevDate: 2026-09-30
CmpDate: 2026-09-30

Tang L, Zhang Z, Lu H, et al (2026)

Multi-omics integration revealed the molecular responses and key candidate genes underlying cold tolerance in Elymus nutans.

Plant physiology and biochemistry : PPB, 238:111624.

The perennial grass Elymus nutans, native to the Qinghai-Tibet Plateau, exhibits exceptional cold tolerance. To understand its underlying mechanisms, we integrated physiological, transcriptomic, and proteomic profiling under cold stress. Our results revealed a distinct two-phase response strategy to cold stress. The early phase (0-24 h) featured rapid Ca[2+] signaling, redox-related transcriptional reprogramming, and increased membrane permeability. The late phase (36-72 h) shifted toward primary metabolic regulation and the translation of protective proteins. Notably, a prominent time lag (temporal delay) occurred between transcript and protein accumulation. Mechanistically, transcriptomic and proteomic signatures suggested a potential energy trade-off, characterized by the extensive downregulation of photosynthetic components concurrent with the mobilization of photoprotective and carbohydrate metabolic networks. Simultaneously, defense capacity was fortified via enhanced proline, phenylpropanoid, and sustained ascorbate-glutathione pathways. Network analyses identified EnP5CS2 and EnMDHAR4 as key functional candidate genes associated with proline accumulation and redox homeostasis. Heterologous expression in yeast further indicated their basic biochemical competence in enhancing cold tolerance. Collectively, these findings provide multi-omics insights into resource reallocation and adaptive strategies employed by alpine extremophytes in response to cold stress, offering valuable genetic targets for breeding climate-resilient forage and crop.

RevDate: 2026-09-30
CmpDate: 2026-09-30

Keevil TL, Pelissero AJ, Gniewek E, et al (2026)

TaphoSource: An open-source database of experimentally generated bone surface modifications for modeling taphonomic processes.

Journal of human evolution, 219:103876.

Bone surface modifications (BSMs) provide data for modeling predator-prey dynamics and trophic interactions in the fossil record. However, the utility of BSM data depends on our ability to correctly infer which unobservable actions or ecological agents produced these marks, and commonly used qualitative methods may be insufficient to discriminate among BSMs that exhibit substantial macromorphological overlap. Recently, quantitative BSM identification methods have been employed to overcome this taphonomic equifinality, which, despite their methodological rigor, remain underused because they require large databases of experimentally generated BSMs. In the present study, we introduce TaphoSource, an open-source database containing point cloud and measurement data for 942 experimentally generated BSMs, created by replicating five possible taphonomic and depositional actions, as well as 12 fossilized BSMs from the 1.7-million-year-old HWK EE site in Olduvai Gorge, Tanzania. To highlight the utility of this dataset, we used random forest models to distinguish among the five experimentally generated BSM categories based on measurement variability, achieving approximately 73% accuracy. These data were then used to train a random forest model to identify the actions responsible for the 12 fossilized BSMs in the TaphoSource database. We openly disseminate these data so that other researchers can conduct quantitative BSM modeling studies without the need to generate expensive and time-consuming experimental datasets. We anticipate that these data will have broader applications for reconstructing and modeling spatiotemporal trends in carnivory, providing deeper insights into the evolution of both hominin and non-hominin mammalian carnivory and behavior throughout the Plio-Pleistocene.

RevDate: 2026-09-30
CmpDate: 2026-09-30

Zhang S, Liu Z, Peng Z, et al (2026)

Multiomics analysis unravels a UV-B-mediated regulatory network of anthocyanin biosynthesis in lettuce (Lactuca sativa L.).

Plant physiology and biochemistry : PPB, 238:111758.

The production of nutrient-dense lettuce (Lactuca sativa) in greenhouse systems is often constrained due to the depletion of solar UV-B radiation. While UV-B exposure is empirically associated with elevated anthocyanin levels, the underlying molecular regulatory network remains poorly understood. Here, we performed integrated metabolomic and transcriptomic analyses to characterize the metabolic and transcriptomic profiles of lettuce grown under UV-sufficient open-field and UV-deficient greenhouse conditions. Multiomics analysis revealed a strong positive correlation between ambient UV-B exposure and anthocyanin accumulation, confirming UV-B signal as a key elicitor of this metabolic process. Co-expression network analysis identified LsHY5a/b as central regulators downstream of UV-B signaling. LsHY5a/b act upstream of LsMYB113b, establishing a transcriptional cascade that regulates anthocyanin biosynthesis. Transient expression assays further demonstrated that LsMYB113b positively regulates anthocyanin accumulation by directly binding to the promoters of LsCHS1, LsCHI3, LsF3H, and LsANS to activate their transcription. Collectively, our results elucidate the molecular mechanism by which UV-B induces anthocyanin accumulation via the LsHY5a/b-LsMYB113b transcriptional cascade. This work also provides a feasible strategy to enhance anthocyanin production in UV-deficient greenhouse systems, thereby improving the nutritional quality of horticultural crops in controlled environments.

RevDate: 2026-09-28
CmpDate: 2026-09-27

Mei S, Su Y, Yue J, et al (2026)

Ecological Correlates of Depressive Symptoms among Chinese Adolescents: A Random Forest and Nomogram Analysis of CFPS Data.

Psychology research and behavior management, 19:632599.

BACKGROUND: Adolescence represents a critical developmental stage characterized by complex stressors, including academic pressure and interpersonal challenges, which significantly elevate the risk of depressive symptoms. While conventional research predominantly relies on linear methodologies focusing on isolated environmental determinants, the multi-level interactive effects of ecological environments on adolescent depressive symptoms remain under-explored.

METHODS: Utilizing longitudinal data from the 2020 and 2022 China Family Panel Studies (CFPS), this study included a sample of 971 adolescents (aged 10-15). Baseline ecological variables and covariates were measured in 2020, while the outcome-depressive symptoms-was assessed in 2022 using the 8-item Center for Epidemiologic Studies Depression Scale (CES-D8). We integrated a machine learning framework (Random Forest, RF) to predict continuous CES-D8 scores and a nomogram model to predict binary depression risk (CES-D8 ≥ 9). The nomogram was internally validated using 1000 bootstrap resamples.

RESULTS: Ecological environments demonstrated significant associations with adolescent depressive symptoms. In the RF model (Out-of-Bag Mean Squared Error = 12.72), the predictor s ranked in descending order of their contribution were social trust, interpersonal relationships, parent-child conflict, teacher satisfaction, and age. The developed visual nomogram demonstrated modest discrimination (AUC = 0.614) but excellent calibration (Mean Absolute Error = 0.011) for quantifying individualized risk probabilities.

CONCLUSION: These findings highlight specific environmental correlates and underscore the necessity of transitioning from single-factor management to integrated, multi-systemic approaches. While the predictive model requires further external validation before clinical application, it offers a preliminary epidemiological tool to identify potential intervention targets and facilitate coordinated family, school, community, and governmental interventions.

RevDate: 2026-09-30
CmpDate: 2026-09-29

Singh S, Sharma VK, Shrivastav D, et al (2026)

From Rhizosphere to Resistance: Microbe-Plant Interactions in Eco-Smart Biocontrol.

MicrobiologyOpen, 15(5):e70398.

The increasing limitations of chemical pesticides such as environmental pollution, pathogen resistance, and threats to human and ecosystem health have increased the demand for sustainable, biologically based crop protection methods. Eco-smart biocontrol has emerged as a game-changing paradigm that uses beneficial microorganisms associated with plants to suppress phytopathogens, boost plant immunity, and make agroecosystems more resilient over time. Moving beyond traditional single-strain biocontrol, eco-smart biocontrol integrates multi-omics discovery, artificial intelligence-assisted predictive microbiome design, and dynamic rhizosphere ecology. This review brings together ecological, molecular, and technological dimensions of eco-smart biocontrol, focusing on the rhizosphere as a dynamic hotspot for plant-microbe interactions. We investigate rhizosphere microbiome assembly and demonstrate the preferential recruitment of beneficial bacteria, fungi, actinomycetes, and mycorrhizal symbionts by plant root exudates. Moreover, the review highlights the impact of innovations in multi-omics techniques (metagenomics, transcriptomics, proteomics, and metabolomics), systems biology, and artificial intelligence on microbial biocontrol agent discovery, functional validation, and predictive design. Examples from cereal crops, legumes, and horticulture crops indicate that the application of beneficial microbial inoculants can significantly lower the burden of pests and diseases, enhance crop productivity, and fit perfectly within an integrated pest management system. Lastly, we critically analyze the main challenges preventing large-scale adoption, such as inconsistent field performance, limited microbial survival and competitiveness, and comparative regulatory frameworks across global markets. Ultimately, eco-smart microbial biocontrol combines mechanistic insights with omics-driven discovery, artificial intelligence (AI)- assisted prediction, advanced formulation strategies, and field-level validation, creating a strong, scalable, and environmentally friendly framework for resilient, low-input agricultural systems.

RevDate: 2026-09-29

McLain NJ, Kaplan CM, Naliboff BD, et al (2026)

Distinct connectivity patterns subserve 2 dimensions of the chronic pain experience.

Pain [Epub ahead of print].

Identifying the neural correlates of chronic pain and their relationship to clinically relevant measures of disease has proven challenging due to high variability in individual patterns of functional brain connectivity and the rarity of ecologically valid scanning paradigms. Here, we address these limitations using data from the Multidisciplinary Approach to the Study of Pelvic Pain Symptom Patterns Study, which recruited a large sample of urologic chronic pain patients (n = 382) imaged repeatedly (range = 2-4) over 36 months. Intrinsic brain connectivity was recorded before and after a naturalistic challenge designed to elicit symptomatic pain and discomfort. Linear mixed-effects models revealed 2 neuroanatomically distinct patterns: pain at the time of scan was linked to connectivity within sensory-discriminative regions, while past-week recalled pain was associated with distributed patterns across regions implicated in memory, salience, and affective processing. These findings emphasize the dynamic roles of brain regions for different aspects of chronic pain.

RevDate: 2026-09-29
CmpDate: 2026-09-29

You S, Wang Z, Liu C, et al (2026)

Microplastic Pollution and Risk of Cancer: A Prospective Study Based on UK Biobank.

Cancer control : journal of the Moffitt Cancer Center, 33:10732748261493417.

IntroductionVarious industrial pollutants have been implicated in tumorigenesis. However, the cancer risk associated with microplastics, a pervasive environmental pollutant, remains poorly understood. This study aimed to evaluate the association between basin-level environmental microplastic contamination and cancer incidence.MethodsIn this secondary analysis of a prospective UK Biobank cohort, 378,985 participants were linked to basin-level river microplastic measurements using residential coordinates. The 2019 measurements were treated as an ecological proxy for regional environmental microplastic contamination. Participants were categorized into low, moderate, or high exposure groups, and Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsDuring a mean follow-up of 12.39 years, 37,322 participants developed at least one of the 24 cancer outcomes. Compared with participants in low-exposure basins, participants in high-exposure basins had increased risks of liver cancer (HR, 1.252; 95% CI, 1.031-1.520), colon cancer (HR, 1.167; 95% CI, 1.088-1.252), and lung cancer (HR, 1.198; 95% CI, 1.095-1.309). These estimates represent modest relative increases and should be interpreted alongside absolute event counts and confidence intervals.ConclusionsHigher basin-level river microplastic contamination was associated with modestly higher incidence of selected digestive and respiratory cancers.Patient or Public ContributionThis study was a secondary analysis of de-identified data from the prospective UK Biobank cohort. Patients, service users, and members of the public were not directly involved in the design, analysis, interpretation, or preparation of this study.

RevDate: 2026-09-29
CmpDate: 2026-09-29

Wu J, Ye W, Zhou J, et al (2026)

Antibiotic-induced photosynthetic dysfunction in wheat: Coupled inhibition of light reactions and carbon assimilation revealed by multi-omics.

Environmental pollution (Barking, Essex : 1987), 408:128809.

Antibiotics, as emerging environmental contaminants, pose potential risks to crop photosynthesis and productivity. This study systematically investigated the phytotoxic effects of enrofloxacin (ENR), levofloxacin (LVX), and roxithromycin (ROX) on wheat (Triticum aestivum L.) seedlings. Exposure to ENR and LVX led to significant reductions in photosynthetic pigment content, chlorophyll synthesis precursors, and net photosynthetic rate, accompanied by severe chloroplast ultrastructural damage, thylakoid disintegration, and mitochondrial cristae impairment. Chlorophyll fluorescence parameters indicated PSII dysfunction and impaired electron transport under ENR and LVX stress. In contrast, ROX treatment increased pigment content, maintained chloroplast integrity, and increased chloroplast numbers. All three antibiotics stimulated key carbon assimilation enzymes including Rubisco, PEPC, NADP-ME, and PPDK. Transcriptomic analysis revealed downregulation of photosynthesis-related genes (e.g., PsbA, PsaA, PetA, PetD) and F-type ATPase subunits under ENR and LVX, whereas genes involved in redox maintenance (PetH) were upregulated. Metabolomic profiling showed accumulation of oxalic acid, methylamine, and palmitic acid under ENR and LVX, indicating membrane damage, protein degradation, and may disrupt energy metabolism. Significant alterations in fatty acid biosynthesis, pyrimidine metabolism, and GPI anchor biosynthesis pathways further confirmed antibiotic-induced metabolic reprogramming. This study provides new insights into the differential impacts of antibiotics on crop photosynthesis and cellular integrity, emphasizing the need for ecological risk assessment of antibiotic contamination in agricultural systems.

RevDate: 2026-09-29
CmpDate: 2026-09-26

Milicevic O, Djordjevic M, Salom I, et al (2026)

Inferring Seasonal Modulation of Early SARS-CoV-2 Transmissibility from Cross-Country Environmental and Population-Level Predictors.

Pathogens (Basel, Switzerland), 15(9):.

Seasonal variation in SARS-CoV-2 transmissibility is difficult to estimate directly from year-round epidemic data because interventions, behavior, reporting, immunity, and viral evolution change concurrently. We therefore asked whether cross-country differences observed during the initial exponential-growth phase could be used to infer country-specific seasonal modulation. Early-pandemic basic reproduction numbers (R0) from 118 countries were linked to 96 harmonized environmental and population-level predictors. Among nine candidate algorithms evaluated across 100 repeated train-test splits, ridge regression using the combined predictor set provided the best balance of predictive accuracy, generalization, and temporal stability. The selected model was then driven by daily climatological covariates to reconstruct annual baseline R0(t) profiles. Predicted transmissibility generally peaked during winter in the Northern Hemisphere and approximately six months later in the Southern Hemisphere, whereas equatorial countries showed weaker or multimodal patterns. Seasonal forcing amplitude increased strongly with absolute latitude (r = 0.85; mean 0.064 across 77 temperate countries), and predicted R0 peaks aligned more closely with minimum ultraviolet radiation than with minimum temperature. These ecological associations do not establish causality, but they provide country-specific seasonal-forcing parameters for epidemic models and a baseline environmental context for comparing early-pandemic trajectories.

RevDate: 2026-09-27
CmpDate: 2026-09-26

Han H, Luo O, Li K, et al (2026)

Beyond bacteria: a multi-omics view of the gut-brain axis in Parkinson's disease.

Frontiers in cellular and infection microbiology, 16:1900578.

INTRODUCTION: Parkinson's disease (PD) is increasingly recognized as a multisystem disorder in which gastrointestinal dysfunction and gut microbial alterations may contribute to disease pathophysiology. Although most microbiome research in PD has focused on bacteria, growing evidence suggests that the gut ecosystem should be considered more broadly to include fungi, viruses, metabolites, and proteins.

METHODS: We searched PubMed and SciFinder for human studies published up to October 28, 2025, using domain-specific search strategies for the bacteriome, metabolome, proteome, virome, and mycobiome, and synthesized the eligible evidence using a structured multi-omics evidence-mapping framework.

RESULTS: We summarize the most consistent bacterial findings, including enrichment of mucin-degrading taxa and depletion of short-chain fatty acid-producing commensals, and discuss how these changes relate to impaired fermentation, barrier dysfunction, and immune activation. We further examine emerging evidence for virome and mycobiome alterations, highlighting the possibility that PD-related dysbiosis reflects cross-kingdom ecological disruption rather than bacteria-only imbalance. Metabolomic studies provide functional support for this model by demonstrating altered short-chain fatty acid biology and broader host -microbe co-metabolic remodeling. Protein-focused studies, including host proteomic signatures and bacterial functional amyloids, extend the field toward mechanisms linking gut dysfunction to inflammation, proteostatic stress, and α-synuclein pathology.

DISCUSSION: Overall, the evidence supports a multi-layer view of the PD gut -brain axis in which microbial ecology, metabolic output, barrier integrity, immune signaling, and protein-centered mechanisms are interconnected. The field remains limited by cross-sectional designs, methodological heterogeneity, and uneven evidence depth across omics layers. Longitudinal, standardized, and integrated multi-omics studies will be essential to determine which microbiome-associated alterations are mechanistically important, clinically informative, and potentially modifiable in PD.

RevDate: 2026-09-28
CmpDate: 2026-09-26

Zhang G, Qiu S, G Ding (2026)

Pattern recognition and spatial differentiation of built environment around urban sports facilities from perspective of facility hierarchy: a case study of Changsha city.

Frontiers in public health, 14:1947943.

Under the context of healthy city development and the construction of 15-min life circles, the relationship between the built environment and residents' physical activity and health has attracted increasing attention. However, most existing studies adopt a residential-centered perspective, neglect the heterogeneity of service ranges across different levels of sports facilities, and insufficiently integrate objective built-environment characteristics with residents' facility-use behaviors and subjective perceptions. Taking Changsha city as a case study, this paper develops a hierarchical sports facility-based analytical framework for life circles and investigates the spatial differentiation and typological patterns of the surrounding built environment. Unlike fixed-buffer approaches, the framework employs level-specific measurement scales reflecting differences in potential facility service ranges and access modes. The study integrates multi-source geospatial data, including OpenStreetMap road networks, POI data, WorldPop population grids, and NDVI remote sensing data, to construct a multidimensional built environment indicator system covering accessibility, functional structure, facility supply, ecological quality, and population characteristics. Methods including GIS spatial analysis, one-way ANOVA, K-means clustering, and chi-square tests are employed to identify spatial patterns across different facility levels. Questionnaire results concerning activity-space choices, travel characteristics, facility use, and environmental perceptions are interpreted alongside the corresponding accessibility, functional, and ecological dimensions of the objective spatial analysis. This integration is conducted at the aggregate level and is not used to infer individual-level associations or causality. The results show that: (1) sports facilities in Changsha city exhibit a "large number of small-scale facilities and limited but spatially dominant large facilities" distribution pattern; (2) significant differences exist in the built environments surrounding different facility levels, with population density and POI functional diversity being the key distinguishing indicators; small facilities are mainly embedded in high-density residential areas, while large and extra-large facilities are more frequently located in areas with higher functional mix and higher mean NDVI values; (3) four typical built-environment patterns are identified, including high-density and service-intensive, low-intensity built-environment, high-NDVI and low-density, and functionally mixed and service-intensive types, showing a clear center-periphery gradient; (4) respondents mainly reported using parks, waterfront and mountain trails, and walking paths, and predominantly reached sports facilities through active travel within 15 min. These behavioral and perceptual results provide complementary context for the accessibility, functional, and ecological patterns identified by the spatial analysis, while concerns remain regarding pedestrian continuity and facility management.

RevDate: 2026-09-26
CmpDate: 2026-09-26

Zhang J, Qiao X, Wang S, et al (2026)

Spatio-temporal dynamics of ecological environmental quality and drivers under a dual-constraint framework: a case study of the Luo River Basin.

Environmental monitoring and assessment, 198(10):.

Large-scale ecological engineering construction and socioeconomic development have profoundly influenced the ecological environmental quality (EEQ) of the Luo River Basin. Revealing the nonlinear responses and threshold effects of EEQ to multiple driving factors is essential for promoting the sustainable development of ecologically fragile basins. Previous studies have predominantly emphasized upper-bound constraints while overlooking the ecological degradation risks associated with lower-bound constraints. Based on Google Earth Engine platform, this study constructs the remote sensing ecological index (RSEI) to systematically reveal the spatiotemporal evolution characteristics of EEQ in the Luo River Basin from 2000 to 2022. By integrating the optimal parameter geographic detector with "dual-constraint" analysis, the dominant driving factors and nonlinear threshold effects of EEQ were identified. The findings show that the basin's overall RSEI displays a spatial pattern with high values in the southwest and low values in the northeast. Land use intensity is the dominant driver and shows a significant interaction with average annual evapotranspiration. RSEI is often positively impacted by natural factors, with upstream forested hilly regions showing the strongest effects. RSEI exhibits multiple nonlinear relationships with its driving factors. Anthropogenic interference causes the threshold points of certain factors to shift either forward or backward, resulting in a substantial attenuation of RSEI. The proposed "dual-constraint" framework concurrently integrates the upper constraint of ecological improvement potential and the lower constraint of ecological degradation risk. It reveals that EEQ is jointly regulated by natural factors and anthropogenic activities, providing a scientific basis for sustainable development and ecological restoration of watersheds.

RevDate: 2026-09-29
CmpDate: 2026-09-27

Vallinmäki M, Mutanen M, Wright CJ, et al (2026)

The genome sequence of a plutellid moth, Plutella hyperboreella Strand, 1902 (Lepidoptera: Plutellidae).

Wellcome open research, 11:628.

We present a genome assembly from a female specimen of Plutella hyperboreella (Arthropoda; Insecta; Lepidoptera; Plutellidae). The assembly contains two haplotypes with total lengths of 503.34 megabases and 426.42 megabases. Most of the haplotype 1 assembly (98.75%) 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 20.67 kilobases. Gene annotation of this assembly by Ensembl identified 12,347 protein-coding genes. This work is part of Project Psyche, a collaborative programme generating genomes for European butterflies and moths.

RevDate: 2026-09-28
CmpDate: 2026-09-28

Moser N, Finkelshtein D, Chargaziya G, et al (2026)

R-package agentBayes: Likelihood-based statistical methods for agent-based models.

PLoS computational biology, 22(9):e1014786 pii:PCOMPBIOL-D-26-00922.

Statistically analysing interacting particle systems remains challenging because the governing equations are analytically intractable. Existing solutions include moment closure methods with pseudolikelihood-based frameworks, and likelihood-free frameworks based on extensive simulations, both relying on heuristic choices whose validity is difficult to predict. As a resolution, we rigorously derive an asymptotically exact expression for the likelihood of agent-based models (ABMs) operating in continuous space and time that can be formulated as reactant-catalyst-product (RCP) models. We derive an expression for the conditional density of agents given information about the current and earlier distributions of neighbouring agents. We utilize this expression to construct an asymptotically exact likelihood that applies to both spatial snapshot and time-series data. We implement the likelihood expression and a Bayesian parameter estimation framework in the R-package agentBayes and demonstrate its utility in biological research and beyond with simulated case studies and empirical data on the evolution of cancer cell populations.

RevDate: 2026-09-26
CmpDate: 2026-09-26

Wang T, Chu Y, Li X, et al (2026)

Dynamic Atlas and Energy Metabolism Adaptation of the Liver Proteome During a 24 h Cycle in Vespertilio sinensis.

Biomolecules, 16(9):.

Circadian rhythms regulate hepatic metabolism and physiological homeostasis, which are essential for organisms to adapt to environmental cycles. Bats are the only mammals capable of sustained powered flight, accompanied by extreme metabolic demands and a nocturnal lifestyle. However, the regulatory mechanisms underlying hepatic circadian rhythms in bats remain poorly understood. Herein, we employed data-independent acquisition (DIA)-based quantitative proteomics to characterize the diurnal dynamics of hepatic proteins in Vespertilio sinensis across four representative physiological states, and further conducted integrative multi-omics analysis combined with transcriptomic data. The results revealed that approximately 5% of hepatic proteins exhibited circadian rhythmicity in V. sinensis, a proportion markedly higher than that of rhythmic transcripts and metabolites. Prominent transcription-protein rhythm decoupling was observed, implying that post-transcriptional regulatory processes may play critical roles in shaping circadian rhythms. Core metabolic pathways displayed temporally dynamic enrichment. The diurnal functional switching of the liver was achieved via stable expression of core proteins and temporal turnover of specific proteins, which efficiently coordinated energy supply, oxidative defense and detoxification metabolism. Trend clustering and functional enrichment analyses suggested that the liver may undergo lysosome-mediated immune repair during the daytime, while exhibiting enriched energy metabolic profiles that potentially support the elevated energy expenditure required for flight at night. This study systematically elucidates the protein regulatory patterns underlying hepatic diurnal rhythms in V. sinensis, and provides molecular clues for exploring extreme energy adaptation and circadian evolutionary scenarios in nocturnal flying mammals.

RevDate: 2026-09-26
CmpDate: 2026-09-26

Valente FDS, Andrioli KRK, da Silva MAC, et al (2026)

Multidrug-Resistant Bacteria in South Atlantic Cetaceans over a Decade of Surveillance.

Microorganisms, 14(9):.

This decade-long surveillance study (2016-2025) investigates the acquisition of multidrug-resistant (MDR) bacteria in South Atlantic cetaceans to evaluate how ecological niches modulate exposure to biological pollution. Analyzing clinical isolates from stranded cetacean carcasses (n = 346), we used Generalized Linear Mixed-Effects Models (GLMMs) to mitigate multi-center analytical biases and compare resistance profiles across coastal and oceanic species. We observed a significant, progressive upward trend in the overall MDR probability over the decade. Although raw MDR was higher in the demersal-feeding Pontoporia blainvillei (58.2%) than in the sympatric, water-column-foraging Sotalia guianensis (22.0%), multivariate modeling revealed that this difference was primarily driven by the geographic stranding location rather than by intrinsic foraging ecology. High gastrointestinal MDR (73.9%) suggests dietary intake as a primary biological gateway. Demographic modeling revealed a significant sex-based association in P. blainvillei, with females facing a higher risk (p = 0.009), although the specific ecological or physiological mechanisms underlying this difference remain unknown. High MDR rates in deep-diving Lagenodelphis hosei (70.8%) and Kogia breviceps (67.9%) suggest that resistant pathogens may reach bathypelagic food webs, potentially via vertical trophic pathways. These findings suggest that spatial environmental contamination, alongside foraging and reproductive ecologies, is a key driver of exposure to the anthropogenic resistome. Because carcass-based sampling inherently targets a diseased or senescent fraction, these high prevalences may overestimate the resistome burden of healthy free-ranging populations. The detection of human pathogens across coastal and offshore habitats indicates persistent deficiencies in terrestrial effluent management, reinforcing cetaceans as One Health sentinels.

RevDate: 2026-09-26
CmpDate: 2026-09-24

Ehiosun KI, Chapleur O, L Mazéas (2026)

Diagnosing Anaerobic Digesters' Function and Performance: From Meta-Omics to Integrated Meta-Omics Analyses.

Environmental microbiology reports, 18(5):e70417.

Anaerobic digestion (AD) of organic wastes by microorganisms into biomethane contributes significantly towards bioenergy generation. However, the bioprocess remains challenging due to its complex microbial ecology, dynamic biochemical pathways and sensitivity to perturbations. Over the past decade, using meta-omics like metataxonomics, metagenomics, metatranscriptomics, metaproteomics and metabolomics to diagnose its functioning has become necessary and common. However, a single meta-omics method can only provide limited biological understanding of the bioprocess. This led to the use of multi-meta-omics analyses in tandem; however, most studies still examine and interpret each meta-omics separately, limiting their ability to uncover functional interactions across molecular levels. Currently, the frontier is integrated meta-omics, where multi-meta-omics and process data are systematically combined into a single and interpretable system to unlock mechanistic understanding, diagnostic and predictive control of AD. This review critically examines specific application of meta-omics in AD, discussing their strengths, limitations and distinct position in integrated meta-omics approach. Importantly, it explores the computational frameworks, methodologies and challenges of integrated meta-omics. Discovering diagnostic biomarkers with high predictive power and transferability across AD systems through cross-omics validation is highlighted. As workflows standardise and technologies mature, integrated meta-omics would significantly contribute to the advancement of AD bioprocess for bioenergy.

RevDate: 2026-09-24
CmpDate: 2026-09-24

Lertcanawanichakul M, Bhoopong P, Sahabuddeen T, et al (2026)

Biosynthetic Diversity of Marine-Derived Streptomyces Natural Products: Integrating Genome Mining, Multi-Omics, and Translational Drug Discovery Strategies.

Marine drugs, 24(9): pii:md24090324.

Marine-derived Streptomyces are among the most prolific producers of structurally diverse and biologically active natural products. Adaptation to unique marine environments, including deep-sea sediments, hydrothermal vents, mangrove ecosystems, marine invertebrates, and hypersaline habitats, has promoted the evolution of specialized biosynthetic systems capable of generating a broad spectrum of secondary metabolites. These metabolites include polyketides, non-ribosomal peptides (NRPs), ribosomally synthesized and post-translationally modified peptides (RiPPs), terpenoids, alkaloids, and hybrid compounds with significant antibacterial, antifungal, antiviral, antiparasitic, anti-inflammatory, and anticancer activities. Recent advances in genome sequencing, bioinformatics, genome mining, metabolomics, synthetic biology, and artificial intelligence (AI)-assisted discovery have substantially expanded marine natural product research by enabling the identification and prioritization of previously inaccessible biosynthetic gene clusters (BGCs). However, major challenges remain, including silent biosynthetic pathways, low cultivation efficiency, rediscovery of known compounds, metabolite yield instability, dereplication bottlenecks, and limited ecological interpretation. These constraints continue to impede the translation of biosynthetic potential into pharmaceutical applications. This review summarizes current strategies for marine natural product discovery and highlights emerging translational approaches integrating multi-omics technologies, pathway engineering, and AI-guided prioritization. Collectively, these advances provide a roadmap for advancing marine Streptomyces research from descriptive omics-based exploration toward experimentally validated and clinically relevant drug discovery.

RevDate: 2026-09-24
CmpDate: 2026-09-24

Lü F, Li Y, Zhan D, et al (2026)

Effects of Photoperiod and Light Quality on Phlorotannin Accumulation and Multi-Omics Responses in Sargassum muticum.

Marine drugs, 24(9): pii:md24090330.

Brown algae contain phlorotannins with recognized biological and ecological functions, but the responses of phenolic metabolism to different light environments remain incompletely understood. In this study, Sargassum muticum was cultivated for 15 days under different photoperiods (12L:12D, 16L:8D, and 20L:4D) and light qualities (white, blue, and red light). Growth, photosynthetic performance, oxidative stress indicators, and phlorotannin content were examined, together with transcriptomic and untargeted metabolomic responses. Extended photoperiods were associated with increased growth and a transient increase in phlorotannin content, whereas blue light reduced growth but maintained relatively high chlorophyll a content and photosynthetic efficiency. Transcriptomic analysis identified 10,322, 3790, and 9301 differentially expressed genes under long-photoperiod, blue-light, and red-light treatments, respectively, including 388 genes shared among the three comparisons. Seven transcripts were putatively annotated as polyketide synthases, including four candidate type III polyketide synthase transcripts, and 26 transcripts were annotated as candidate acetyl-CoA carboxylase-related sequences. Untargeted LC-MS analysis yielded 949 putatively annotated metabolites, among which features annotated as salicylic acid and γ-glutamylcysteine showed increased relative abundance under the three light treatments. A feature putatively annotated as phloroglucinol did not differ significantly among treatments. Correlation analysis indicated coordinated, but non-causal, associations between light-responsive transcripts and changes in amino acid, carbohydrate, and lipid metabolism. These results characterize the physiological and multi-omics responses of S. muticum to altered light regimes and provide candidate molecular targets for future functional and targeted chemical validation.

RevDate: 2026-09-24
CmpDate: 2026-09-24

Arapitsas NP, Christakis CA, Paragkamian S, et al (2026)

Unravelling the genomic and functional arsenal of Bacilli endophytes from plants with different lifestyles and their antimicrobial potential.

Microbial genomics, 12(9):.

Endophytic microbiomes of crop wild relatives (CWRs) adapted to extreme environments, such as halophytes, are promising sources of plant-beneficial bacteria and secondary metabolites for sustainable food production. Here, we analysed 25 Bacilli isolates obtained from CWRs, halophytes and other plant species in Crete, Greece. Using a hybrid Illumina-PacBio sequencing approach, we generated high-quality genomes and performed comparative genomics, phylogenetic and pangenome analyses, complemented by in vitro assays. We identified 312 biosynthetic gene clusters (BGCs), nearly 60% of which showed no similarity to known clusters, revealing extensive unexplored biosynthetic potential. These unique BGCs may constitute an adaptive feature enabling endophytic Bacilli to colonize and interact with host plants. The isolates spanned diverse genera (Bacillus, Paenibacillus, Peribacillus, Neobacillus, Cytobacillus and Rossellomorea), including three novel species. Phenotypic assays of our isolates demonstrated high salinity tolerance (up to 17.5% wt/v NaCl) and strong antagonism against major bacterial and fungal phytopathogens. Genome mining further revealed a broad array of putatively plant-beneficial traits related to growth promotion, stress adaptation, host interaction and inhibition of pathogens. Together, these findings show that Bacilli endophytes from wild and halophytic plants possess exceptional phylogenetic novelty, functional diversity and biosynthetic capacity, providing new genomic and ecological insights into Bacilli associated with plants inhabiting extreme environments.

RevDate: 2026-09-24

Mascherek A, Diedrichsen L, Mostajeran F, et al (2026)

Blue skies or cloudy minds? Associations between momentary affect, cloud cover, and sky conditions in a geographic ecological momentary assessment study.

Environmental research pii:S0013-9351(26)02076-1 [Epub ahead of print].

Potential associations with weather as an ever-present environmental phenomenon have received not much systematic attention, even though in lay perception weather plays a vital role in the evaluation of one's day and is also assumed to be strongly associated with affect. The present study assesses the association between momentary affective well-being, self-reported stress, self-reported rumination and cloud cover as well as cloud height in a geographical ecological momentary assessment study. The sample comprised 83 individuals (55.4% female), with participants ranging between 18 and 62 years of age (M = 29.63, SD = 8.65) and a total of 2490 data points, carrying limited informational value for the between level results. Participants were prompted randomly three times a day over maximally 20 consecutive days. We used dynamic structural equation modelling to model inter- and intraindividual differences and fluctuations. Separate models were run for rumination, stress, and momentary affective well-being. As environmental variables, cloud coverage, cloud height, and whether participants were aware of the sky condition were assessed. The only meaningful association emerged between stress and the perception of the sky. However, the results revealed methodological challenges. Geofencing might be more expedient than time-based prompting to prevent the majority of data points being assessed indoors. Also, in case the nearest weather stations are far away, photos might be better suited with subsequent expert rating for categorizing an environmental phenomenon as volatile as clouds.

RevDate: 2026-09-25
CmpDate: 2026-09-25

Wan N, Byun W, Wen M, et al (2026)

Using Momentary Measures to Understand Physical Activity Adoption and Maintenance: Protocol for a Longitudinal Study.

JMIR research protocols, 15:e108686 pii:v15i1e108686.

BACKGROUND: Physical inactivity is prevalent among adults in the United States and is related to various health disparities. The search for effective policies and interventions to promote physical activity (PA) is severely hampered by the paucity of research on the mechanisms underlying PA behavior change.

OBJECTIVE: This paper describes a research protocol that uses mobile health technology to examine the influence of contextual and environmental factors and acute momentary precipitants on PA adoption and maintenance among Pacific Islanders in the United States.

METHODS: The study is guided by an overarching conceptual framework derived from models of the social and environmental determinants of health, social cognitive theories of behavior change, and prior empirical findings. Participants will be assessed using real-time, field-based, state-of-the-art methodologies consisting of MotionSense, ecological momentary assessment, and GPS tracking. MotionSense tracks behavioral and physiological data in real time and can objectively detect PA behaviors of participants. GPS tracking permits real-time mapping of an individual's space-time trajectories and relevant environmental exposures and characteristics (eg, proximity to PA facilities and neighborhood safety) using Geographic Information System data. Principal outcomes of interest are PA adoption and PA maintenance.

RESULTS: This study was funded by the National Cancer Institute of the National Institutes of Health in August 2023. Data collection started on May 23, 2025, and is expected to finish by March 2028. As of August 10, 2026, the project has recruited all 150 participants. Data analysis is ongoing, and results are expected to be published in May 2028.

CONCLUSIONS: This is among the first studies to link objective and momentary indexes of PA to key environmental and psychosocial factors in PA behavior studies. The comprehensive, multi-method approach addresses 2 long-standing limitations in PA research: the reliance on self-reported outcome measures and the use of static residential locations as proxies for neighborhood exposure. In addition, this study is among the first to apply dynamic prediction models, a novel statistical approach well suited to the high-frequency, intensive longitudinal data generated by real-time mobile health assessment. The findings will provide actionable evidence to inform policies and interventions aimed at reducing PA-related health disparities among Pacific Islanders and other racial and ethnic groups that experience similar health problems.

RevDate: 2026-09-26
CmpDate: 2026-09-26

Xie J, Pang J, Shi H, et al (2026)

Genome-Wide Identification and Bioinformatics Analysis of Thaumatin-like Proteins in Aegiceras corniculatum.

Genes, 17(9): pii:genes17091023.

BACKGROUND: The mangrove ecosystem serves as a vital coastal ecotone, providing essential ecological services, such as water purification, shoreline protection, and biodiversity maintenance. Fungal pathogens threaten mangrove health and contribute to ecosystem degradation, but the molecular mechanisms underlying disease resistance in mangroves remain poorly explored. Introdustion: Thaumatin-like proteins (TLPs), belonging to the pathogenesis-related-5 (PR-5) family, play a crucial role in antifungal defense in plants.

METHOD AND RESULTS: In this study, we identified 23 TLP family members in the mangrove Aegiceras corniculatum. The genes encoding TLP family members were unevenly distributed on chromosomes. Collinearity analyses showed that TLP family members in A. corniculatum underwent multiple gene duplication events, and Ka/Ks calculations revealed that these duplicated genes were predominantly under purifying selection. Among the 23 TLPs, AcTLP19 was significantly upregulated after Botrytis cinerea infection. Subcellular localization prediction and experiments revealed the extracellular localization of AcTLP19.

CONCLUSIONS: Heterologous expression and antibacterial tests showed that recombinant AcTLP19 had no direct antifungal activity against B. cinerea or Fusarium oxysporum under the tested conditions, leaving open the possibility that it contributes to mangrove defense through indirect mechanisms, or that its antifungal activity was not captured under the specific assay conditions. This study advances our knowledge of mangrove stress responses and may contribute to future conservation strategies.

RevDate: 2026-09-25
CmpDate: 2026-09-25

Ehrmann D, Litterbach E, Deschenes S, et al (2026)

From narratives to numbers and back: Assessing the psychosocial aspects of diabetes in the era of high technology with emerging qualitative and quantitative methodologies.

Diabetic medicine : a journal of the British Diabetic Association, 43(9):e70206.

AIMS: Rapid changes in diabetes therapy combined with limitations of traditional methodological approaches challenge the field of psychosocial research to adequately capture the experiences of people with diabetes. This narrative review provides an overview of emerging qualitative and quantitative approaches that can advance the study of psychosocial aspects of diabetes.

METHODS: We searched PubMed and Google Scholar for English-language articles regarding novel qualitative and quantitative methodologies.

RESULTS: Emerging qualitative methodologies aim to increase the transferability of lived experiences to other contexts and populations by employing novel ways to stimulate interactions and using digital tools. Culturally sensitive methods (e.g. yarning) and the use of pictures (e.g. photovoice) and storytelling methods (e.g. story completion) can capture more diverse experiences and sensitive topics while being able to minimise social desirability. Online qualitative surveys can increase the reach while artificial intelligence (AI) can be implemented in qualitative research protocols. Emerging quantitative methodologies aim to better understand dynamic within-person processes. With repeated daily smartphone-based assessments (e.g. ecological momentary assessment) and passive sensor-based data collections (e.g. digital phenotyping), intensive longitudinal data can be collected that allow for n-of-1 trials, especially in combination with continuous glucose monitoring. Quantitative data can also be used to identify clusters/subgroups of people with shared experiences. Innovative digital twin technology and AI offer intriguing possibilities that can advance the field towards precision mental health care.

CONCLUSIONS: Several innovative methodologies (will) enrich our understanding of psychosocial aspects in diabetes. To fully capitalise on these methodologies, co-design and mixed methods approaches are necessary.

RevDate: 2026-09-25
CmpDate: 2026-09-25

Zhao M, Jiang Y, Ran X, et al (2026)

Differences in metaviromes between Aedes aegypti and Aedes albopictus from sympatric areas on Hainan Island and the Leizhou Peninsula, China.

Parasites & vectors, 19(1):.

BACKGROUND: Aedes aegypti and Ae. albopictus are the most important vector mosquito species globally and are capable of transmitting various viral diseases, such as dengue fever, zika virus disease, and chikungunya fever. Although they overlap in terms of ecological niches and geographical distribution, their virus carriage and transmission capacities differ significantly. Metavirome studies can provide new perspectives for understanding these differences.

METHODS: In this study, next-generation sequencing (NGS) was used to analyze the epidemiologically significant metaviromes of Ae. aegypti and Ae. albopictus on Hainan Island and the Leizhou Peninsula, China. A bioinformatics analysis pipeline was used to compare the viral compositions of the two mosquito species.

RESULTS: In the sympatric areas, 250 viral species from 60 families were annotated to Ae. aegypti at the read level, whereas 406 vial species from 66 families were annotated to Ae. albopictus at the read level, revealing significant differences in the metaviromes of the two mosquito species. Notably, Ae. albopictus exhibited significantly greater viral diversity than Ae. aegypti (p < 0.05). The 50 viruses with the greatest abundance in two mosquito species were selected for data analysis, revealing 64% viral similarity, with 32 common viruses and 18 distinct viruses between the two species, although the relative abundances of each virus differed notably. Phasi Charoen-like Phasivirus (PCLV) from Phenuiviridae showed the highest relative abundance in all Ae. aegypti sample pools, whereas Orthophasmavirus barstukasense (Phasmaviridae), Gihfavirus pelohabitans (Steitzviridae), and unclassified Wenzhou sobemo-like virus 4 (WSLV4) predominated in different Ae. albopictus sample pools.

CONCLUSIONS: The metavirome compositions of Ae. aegypti and Ae. albopictus in the sympatric areas of Hainan Island and the Leizhou Peninsula differed significantly. The viral diversity of Ae. albopictus was significantly higher than that of Ae. aegypti, and notable differences in viral composition and abundance were observed between the two species. However, the 50 most abundant viruses detected in both mosquito species also exhibited a degree of similarity. These findings support further research into the viral compositions of these two Aedes species. Moreover, analyzing these distinct viral compositions aids understanding of the vector capacity and vector competence of these mosquitoes, which will provide theoretical support for vector control efforts on Hainan Island and the Leizhou Peninsula.

RevDate: 2026-09-25
CmpDate: 2026-09-25

Langenberg B, Helm JL, McCabe CJ, et al (2026)

How to Use Residual Dynamic Structural Equation Modeling to Study Individual Differences and Intraindividual Variability in Experimental Factorial Designs: A Tutorial.

Multivariate behavioral research, 61(5):806-829.

This article demonstrates the application of residual dynamic structural equation modeling (RDSEM) for analyzing custom contrasts in experimental factorial designs. Previous applications of RDSEM have often focused on ecological momentary assessment and daily diary data. However, RDSEM was explicitly developed for intensive longitudinal data more generally, including settings with very short time intervals between observations. Beyond these types of studies, RDSEM is also well suited for analyzing data from laboratory studies such as eye-tracking or reaction time experiments. We compare three analytic approaches, namely analysis of variance, linear mixed models, and RDSEM, emphasizing the unique advantages of RDSEM. Although often applied to momentary assessment data, RDSEM proves highly effective for experimental analysis, offering the ability to integrate both time-varying and time-invariant covariates, model autoregressive effects, and capture interindividual differences in residual variances / intraindividual variability. These strengths arise from RDSEM's integration of time-series, multilevel, and latent variable modeling, all implemented through Bayesian estimation.

RevDate: 2026-09-25
CmpDate: 2026-09-23

Braun AC, Corcoran S, Hosseininasab D, et al (2026)

Preliminary Examination of an Innovative mHealth-Based Dietary Fiber Intervention to Improve Outcomes in Young Adults With Prediabetes: Protocol for a Single-Arm Feasibility Study.

JMIR research protocols, 15:e97873.

BACKGROUND: One in 4 young adults has prediabetes, and improving diet is a key step to lowering the risk of diabetes. Existing standard-of-care diet approaches show short-term efficacy but lack long-term effectiveness, including in young adults. Greater fiber intake is associated with a reduced risk of diabetes; however, fiber is not well targeted using existing interventions. Many young adults may be reluctant to consume fiber given the coexistence with digestible carbohydrates and concerns over gastrointestinal effects. Targeting these factors more explicitly may improve uptake and lower diabetes risk, and doing so via a mobile health (mHealth) intervention may be particularly responsive to young adult demands.

OBJECTIVE: This study aims to establish and preliminarily test the feasibility of a highly innovative and scalable mHealth-based intervention to improve fiber intake among young adults with prediabetes.

METHODS: This single-arm feasibility study includes 2 phases to preliminarily test an mHealth-based fiber intervention (phase 1) and elucidate factors that impact sustained behavior change and fiber intake after intervention end using ecological momentary assessment (EMA; phase 2). The intervention is 3 months in length and features daily EMAs with responsive text-based coping messages to target key predictors of fiber intake. EMAs will also be paired with brief (ie, <1 minute) educational videos on fiber delivered once per day. Participants will also receive weekly home-delivered high-fiber food packages and wear a continuous glucose monitor at 2 time points during the intervention as a form of biofeedback. At the baseline and postintervention time points, fasting blood glucose, hemoglobin A1c, and insulin resistance (Homeostatic Model Assessment of Insulin Resistance) will be assessed. After the postintervention time point, participants will continue with daily EMAs to assess factors associated with sustained fiber intake. Diet will be assessed using Automated Self-Administered 24-hour dietary recalls at the baseline and postintervention time point and after the phase 2 EMA.

RESULTS: This study was initiated in July 2025. As of March 2026, the mHealth intervention content is being built, with app completion and trial enrollment both slated to begin in April 2026.

CONCLUSIONS: The results of this study will provide pivotal evidence on the utility of a fiber-focused intervention delivered via mHealth with biofeedback and home-delivered foods to lower the risk of diabetes in young adults with prediabetes.

RevDate: 2026-09-24
CmpDate: 2026-09-24

Chen S, Wang J, Zhao Z, et al (2026)

An integrated transcriptomic and metabolomic analysis reveals hepatic physiological responses of Perca fluviatilis to heat stress.

Journal of fish biology, 109(3):1907-1920.

Heat stress negatively affects the growth and health of fish. In this study, Eurasian perch (Perca fluviatilis) were exposed to control (18°C, CK) and heat stress (25°C, HS) conditions. Using liver transcriptomics and metabolomics in conjunction with physiological and biochemical indicators, we investigated the mechanisms underlying their thermal response. The results revealed that heat stress in P. fluviatilis led to liver cell damage, characterized by vacuolar degeneration and inflammatory cell infiltration. Heat stress caused a fluctuating decrease in superoxide dismutase (SOD) activity, a significant reduction in catalase (CAT) activity (p < 0.05) and a transient increase in glutathione peroxidase (GSH-Px) activity at 24 h, followed by a sustained decrease. Malondialdehyde (MDA) content significantly increased in the later stages. Adenosine triphosphatase (ATPase) activity exhibited phase-specific oscillations, and adenosine triphosphate (ATP) content decreased overall, while lactate dehydrogenase (LDH) activity displayed complex time-dependent variations. In total, 536 significantly differentially expressed genes and 262 differentially abundant metabolites were identified through combined transcriptomic and metabolomic analyses. Integrated multi-omics analysis revealed that key pathways involved in the heat stress response include alanine, aspartate and glutamate metabolism; purine metabolism; mitophagy; autophagy and apoptosis; cyclic guanosine monophosphate-protein kinase G (cGMP-PKG) signalling; oestrogen signalling; and lipid metabolism-associated pathways. These findings indicate that acute heat stress induces hepatic oxidative damage, energy-metabolism disturbance and multiomics alterations in P. fluviatilis. This study provides a basis for understanding the hepatic responses of temperate freshwater fish to elevated temperatures.

RevDate: 2026-09-22

Würstle S, Lieberknecht-Jouy SC, Düchting A, et al (2026)

A consensus-based guideline for personalized bacteriophage therapy.

Nature medicine [Epub ahead of print].

Bacteriophages (phages) - viruses that selectively infect bacteria - are a promising option for personalized therapy of difficult-to-treat bacterial infections. Clinical implementation in many countries worldwide, however, faces multiple hurdles, including a lack of consensus on general principles for phage therapy, infrastructural requirements, procedures for quality-assured phage selection and preparation, clinical administration, monitoring and documentation. Existing guidance provides limited practical direction across the entire translational pathway and lacks inspection-ready specifications to support both pharmacies and clinical sites. These gaps impede safe and transparent clinical use and effective regulatory oversight. Likewise, there are no established processes to identify research questions that will be key to advancing clinical phage research in the future. To address these needs, this consensus-based guideline was developed within the methodological framework of the Association of the Scientific Medical Societies in Germany under the leadership of the German Society for Infectious Diseases. It was created through a collaborative effort involving 20 professional societies, patient advocacy groups and regulatory authorities and 18 international experts. The guideline provides over 60 recommendations on core principles, infrastructure, preparation and quality control, administration and future research. Recommendations are supported by international societies, organizations and stakeholders. By providing clear and practice-oriented recommendations, this consensus statement paves the way for the safe and standardized use of personalized phage therapy.

RevDate: 2026-09-23
CmpDate: 2026-09-22

Fang C, Li Q, Zhao N, et al (2026)

Identification of key genes and metabolites in thyroid eye disease through integrated transcriptomic and metabolomic analysis.

Frontiers in endocrinology, 17:1844082.

INTRODUCTION: Thyroid eye disease (TED) markedly compromises ocular function and quality of life, imposing significant healthcare and economic burdens. Present therapeutic strategies, which mainly include glucocorticoids, teprotumumab, immunosuppressive drugs, and surgical treatments, exhibit limited effectiveness and are associated with high rates of relapse. Consequently, unraveling the molecular mechanisms of TED and discovering new diagnostic and therapeutic targets hold immense clinical importance.

METHODS: In this study, we performed an in-depth analysis of the transcriptomic and metabolomic landscapes of orbital adipose tissue in individuals with TED, aiming to fill the gap in comprehensive molecular characterizations and metabolic perturbations in this disease. By adopting a multi-omics integration strategy, we leveraged transcriptome sequencing, broad-spectrum metabolomics, weighted gene co-expression network analysis (WGCNA), machine learning, immune cell infiltration profiling, molecular docking, QPCR, and immunohistochemistry for biomarker identification. These techniques were systematically employed to pinpoint key genes and metabolites associated with TED, leading to the development of an accurate disease prediction model.

RESULTS: Remarkably, our analysis of the PRJNA1314138 dataset revealed 4, 250 differentially expressed genes (DEGs), with BPIFA1 and SERPINB3 identified as crucial genes through machine learning algorithms. These genes demonstrated outstanding predictive performance in both internal [Area under the curve (AUC)=0.953] and external dataset validations (AUC = 0.717). Furthermore, metabolomic profiling detected 2, 158 metabolites, pinpointing three key metabolites: gluconic acid, colneleic acid, and isoleucine-methionine. The integration of transcriptomic and metabolomic data underscored the significant enrichment of the tyrosine metabolism pathway, establishing functional links between the identified genes and metabolites.

CONCLUSION: These insights offer novel perspectives on the molecular foundations of TED and propose that BPIFA1 and SERPINB3 could serve as promising biomarkers, while gluconic acid, colneleic acid and isoleucine-methionine may hold potential as metabolic indicators. Our research provides a solid framework for comprehending the pathophysiology of TED.

RevDate: 2026-09-24
CmpDate: 2026-09-22

Pélissier A, Phan M, Beerenwinkel N, et al (2026)

Gillespie-based simulation and inference for non-Markovian stochastic reaction networks.

Briefings in bioinformatics, 27(5):.

Discrete stochastic processes are widespread across physics, chemistry, ecology, and beyond. In computational biology and epidemiology, however, most simulators still assume Markovian kinetics with memoryless dynamics, despite growing evidence for history-dependent effects in gene regulation, RNA transcription, cell differentiation, and infection. This reliance on Markovian models limits the routine use and comparison of more realistic, memory-aware descriptions. Here, we develop and benchmark a unified framework for simulating non-Markovian reaction networks using Gillespie-based algorithms. We implement multiple algorithmic classes, including exact, rejection-based, delay-based, and hybrid Markovian/non-Markovian schemes, and compare them across representative biological models. Across three case studies, we show that non-Markovian waiting times can qualitatively change population-level predictions, and that delay-based approximations can break down when intrinsic system timescales approach the imposed delays. We further show how population-level measurements can be used to infer otherwise inaccessible waiting-time distributions, and how non-Markovian structure can be leveraged for sensitivity analysis and statistical inference. To support broad use of these approaches, we release NoMaSS (Non-Markovian Stochastic Simulations), an open-source Python library that provides a unified interface to a wide range of non-Markovian Gillespie algorithms and enables hybrid Markovian/non-Markovian models (https://github.com/AI-SysBio/NoMaSS).

RevDate: 2026-09-24
CmpDate: 2026-09-22

Allf BC, Mallavarapu A, Kikuchi DW, et al (2026)

Who Eats Whom? A global food web derived from citizen science.

PLoS biology, 24(9):e3003988.

Citizen science contains abundant yet underutilized data about species interactions. We present Who Eats Whom, a database and public engagement tool for searching and visualizing thousands of feeding relationships derived from iNaturalist data.

RevDate: 2026-09-22

Onyekachi NS, Yu Q, Liu L, et al (2026)

Decoupling physical transport from redox coupling in coastal nutrient enrichment using explainable machine learning.

Marine pollution bulletin, 233(Pt 3):120399 pii:S0025-326X(26)01186-0 [Epub ahead of print].

Anthropogenic nutrient pollution drives coastal eutrophication, but distinguishing physical transport from internal biogeochemical processing along the land-sea continuum challenges linear models. We compared two hydrologically contrasting bays in Fujian Province that share a monsoon climate and intensive aquaculture but differ fundamentally in freshwater input: river-dominated Sansha Bay and marine-dominated Zhao'an Bay. An explainable AI (XAI) framework integrating Random Forest, SHAP, and partial dependence plots (PDP) decoupled the drivers of dissolved inorganic nitrogen (DIN), improving cross-validated R[2] over linear regression from 0.35 to 0.64 (RF) in Sansha Bay and from 0.20 to 0.69 (RF) in Zhao'an Bay. Using an integrated diagnostic that combined conservative-mixing analysis, SHAP driver rankings, and PDP response shapes, we classified Sansha Bay as transport-controlled: salinity was the dominant driver (28.6%) and DIN followed a continuous mixing gradient with no stable threshold. In contrast, Zhao'an Bay was reaction-controlled: salinity was the weakest driver (12.9%), while dissolved oxygen (29.3%) and dissolved reactive phosphorus (27.3%) produced non-linear thresholds and central retention hotspots. XAI thus distinguishes transport- from reaction-controlled systems without extensive sediment monitoring, and the identified thresholds indicate whether management should target external nutrient loads or internal benthic feedbacks.

RevDate: 2026-09-23
CmpDate: 2026-09-23

Ma L, Lin X, Wu Y, et al (2026)

Biomonitoring-informed neonicotinoid mixture exposure reveals modest cytotoxicity and cell-type-specific molecular responses in human cell lines.

BMC pharmacology & toxicology, 27(1):.

BACKGROUND: Neonicotinoids (NEOs) are widely detected in environmental matrices and in humans, raising concerns about potential health risks. However, most toxicological studies have focused on single compounds and/or concentrations far exceeding biomonitoring-relevant exposure ranges.

METHODS: We developed a UPLC-MS/MS method to quantify eight NEOs and five metabolites in human urine. Using environmental monitoring and urinary biomonitoring data from Hainan Island, China, we constructed exposure-informed NEO mixture profiles based on surface water, tap water, and urinary concentrations, and evaluated their cytotoxicity in four human cell lines (A2780, HEK293T, HeLa, and HepG2). Toxicity was assessed via cell viability, oxidative stress, DNA fragmentation, and integrated multi-omics analyses, with the urinary-biomonitoring-informed mixture evaluated across four cell lines and the surface/tap-water mixtures assessed as an initial transcriptomic screen in HEK293T cells.

RESULTS: Environmentally relevant mixtures (surface/tap water) elicited only limited transcriptomic changes (≤ 0.34% of genes). In contrast, biomonitoring-informed mixtures (≈ 0.1 µM ΣNEOs) induced modest but detectable dose-dependent cytotoxicity, with viability reductions of 3-8%, modest oxidative stress, and limited increases in DNA fragmentation, with effects distinct from individual compounds at matched concentrations. Transcriptomic analysis revealed cell-type-specific responses converging on three core modules: innate immune-like inflammatory signaling, ER stress/unfolded protein response, and metabolic reprogramming. Metabolomic profiling identified two dominant perturbation patterns-arginine/nitrogen-centered rewiring (A2780 and HEK293T) versus membrane lipid remodeling (HeLa and HepG2).

CONCLUSIONS: Biomonitoring-informed NEO/metabolite mixtures elicited measurable, cell-specific molecular perturbations within biomonitoring-relevant concentration ranges, engaging coordinated stress and adaptation programs. These findings support the incorporation of mixture composition and biomonitoring-relevant concentration ranges into future toxicological evaluation.

RevDate: 2026-09-21
CmpDate: 2026-09-21

Hovén E, Frick A, Skalkidou A, et al (2026)

The 'UPIC' cohort: a nationwide prospective study of mental health among adolescents and young adults in Sweden - a study protocol.

BMJ open, 16(9):e120432 pii:bmjopen-2026-120432.

INTRODUCTION: Rates of adolescents and young adults (AYAs) reporting poor mental health have increased, with symptoms of anxiety and depression being most common. Yet, the processes underlying these trends remain unclear. This cohort study aims to establish a comprehensive dataset combining data from multiple sources (surveys, behavioural tests, registers and smartphone sensors) to assess mental health, including mental ill-health and well-being. The dataset will enable analyses of prevalence, risk and protective factors and predictive modelling of mental health trajectories. The study also evaluates the feasibility of such longitudinal data collection among AYAs.

METHODS AND ANALYSIS: This study recruits 2000 AYAs aged 15-29 years from the general population in Sweden using an initial random sample invited by post, followed by recruitment through digital channels. Participants are followed for 2 years under one of three protocols: annual assessments, bi-annual assessments and annual assessments complemented by repeated ecological momentary assessments. Across protocols, data are collected through surveys using a study-specific mobile app and digital behavioural tests. Demographic and clinical information, including psychiatric diagnoses and prescribed medications, are obtained through national health registers. Smartphone sensor data are collected for insights into phone usage, sleep patterns and mobility. Blood samples are collected from a subset via home-based testing to enable biomarker analysis. When applicable, machine learning, including deep learning techniques, is applied to develop predictive algorithms for mental health outcomes, with the potential to inform early identification and prevention. Feasibility outcomes include recruitment and retention rates and the acceptability of study procedures and measures, assessed to inform future studies.

ETHICS AND DISSEMINATION: Representatives from the target population have contributed to the study's development. The study complies with General Data Protection Regulation (GDPR) and has been approved by the Swedish Ethical Review Authority. Findings will be disseminated through scientific publications, conferences and to the public and relevant organisations.

RevDate: 2026-09-22
CmpDate: 2026-09-22

Deng S, Wang W, Yu J, et al (2026)

Plant-rhizosphere control of thallium mobility and detoxification in contaminated soils: Insights from multi-omics and in situ DGT.

Ecotoxicology and environmental safety, 323:120773.

Thallium (Tl) is an extremely toxic and strongly bioaccumulative metal increasingly detected in agricultural soils, yet its behavior at the plant-rhizosphere interface remains poorly constrained. Here, we integrated in situ diffusive gradients in thin films (DGT) with multi-omics analyses (transcriptomics, metabolomics, and 16S rRNA sequencing) to elucidate how plant-rhizosphere interactions regulate Tl mobility and detoxification in Brassica rapa. In situ DGT profiling coupled with the European Community Bureau of Reference (BCR) sequential extraction identified the root-soil interface (0-3 cm) as a hotspot of labile Tl dynamics, revealing a dose-dependent shift from rhizosphere-mediated Tl mobilization under moderate exposure to immobilization under high stress. This transition was mirrored by a hormesis-driven plant response, with low Tl levels stimulating growth and uptake (bioconcentration factor, BCF = 4.2), followed by growth inhibition and restricted translocation at higher doses. Multi-omics analyses showed coordinated metabolic and transcriptional reprogramming associated with this shift, including altered central carbon metabolism, glutathione homeostasis, phenylpropanoid biosynthesis, and selective regulation of metal transporters (ZIP downregulation; ABC and MATE upregulation). Key metabolites (L-proline, sinapoyl aldehyde) and genes (e.g., TAT, PRDX6) emerged as integrative regulators linking detoxification, redox balance, and osmoprotection. Concurrently, Tl exposure induced a functional succession of the rhizosphere microbiome toward metal-resistant taxa (e.g., Nitrospira, Microvirga), closely associated with changes in root exudation patterns. Collectively, these findings advance a process-based mechanistic understanding of how rhizosphere biogeochemistry, plant molecular responses and microbial dynamics jointly control Tl mobility and detoxification, informing Tl risk assessment and plant-microbe-assisted management.

RevDate: 2026-09-21

Xu JX, Yao JH, Liu RL, et al (2026)

[Spatiotemporal Variation Characteristics and Driving Factors of Carbon Sinks in Resource-Depleted Transition Cities: A Case Study of Xuzhou].

Huan jing ke xue= Huanjing kexue, 47(9):5877-5888.

Ecological restoration and green transformation of resource-exhausted cities are vital pathways for carbon sequestration and sink enhancement. The quantitative evaluation of carbon sink capacity and its driving factors is essential for deepening the understanding of regional carbon cycling and its driving mechanisms, optimizing ecological restoration strategies, and advancing China's "dual-carbon" goals. In this study, we selected Xuzhou, a city transitioning from resource dependence, as our case study and employed an improved CASA model, soil respiration regression equations, slope trend analysis, Hurst index, optimal parameter Geodetector (OPGD), and partial correlation analysis to reveal the spatiotemporal dynamics, driving factors, and future trajectories of net ecosystem productivity (NEP) during Xuzhou's transition away from resource dependence. The results show that: ① From 2000 to 2022, NEP in Xuzhou exhibited a fluctuating upward trend and displayed a spatial pattern of "low in the center, high in the periphery," transitioning from a carbon source to a carbon sink. ② During 2011-2022, NEP increased significantly, and the area exhibiting a significant upward trend expanded by 28.21% (P < 0.05); the carbon-sink capacity was projected to continue strengthening. ③ The explanatory power of individual drivers of NEP spatial heterogeneity differed markedly, while the intensity of multi-factor interactions rose significantly. Vegetation cover fraction (q=0.49) and built-up land proportion (q=0.47) exhibited the strongest explanatory power for the spatial heterogeneity of NEP, and the explanatory power of ecological restoration factors has been steadily increasing. ④ Future efforts should focus on establishing a synergistic mechanism that integrates ecological-restoration governance with carbon sink enhancement, strengthening the interplay between natural and anthropogenic factors, ensuring ecological sustainability, and averting the risk of carbon sink decline caused by uncontrolled urban expansion.

RevDate: 2026-09-21
CmpDate: 2026-09-21

Li JH, Li WY, YH Liu (2026)

[Spatio-temporal Evolution and Driving Forces of Landscape Ecological Risk in the Yangtze River Economic Belt].

Huan jing ke xue= Huanjing kexue, 47(9):6317-6327.

Conducting landscape ecological risk assessment and exploring driving factors can provide scientific support for ecological protection and high-quality development. The Yangtze River Economic Belt was selected as the study area, and multi-temporal remote sensing land-use data from 2010, 2015, and 2020 was utilized to construct a landscape ecological risk assessment model employing landscape pattern indices. We conducted a land type distribution analysis to explore the temporal and spatial fluctuations in landscape ecological risks. The Moran index was utilized to examine the spatial correlation and clustering patterns of landscape ecological risks, while the optimal parameter Geodetector was applied to investigate the driving forces of impact factors. The results indicate:① Arable land, forests, and grasslands constituted the principal categories of land. Between 2010 and 2015, the region experiencing changes in land use constituted 0.77% of the whole research area; however, from 2015 to 2020, this region represented 29.80% of the total study area, signifying substantial variations in land use patterns. ② The principal levels of landscape ecological risk were low risk, lower risk, and medium risk. High-risk regions were predominantly located in the Yangtze River Delta, the Su-Wan Floodplain, the Jianghan Plain, the Dongting Lake Plain, the Poyang Lake Plain, and the foothills of the Qinghai-Tibet Plateau in northwestern Sichuan Province. The ecological hazards in the middle and lower reaches of the Yangtze River exceeded those found in the upper reaches. ③ From 2010 to 2015, landscape ecological risk alterations were predominantly observed in lower-risk areas, which evolved into low ecological risk zones. The magnitude of these alterations was more pronounced in the higher reaches than in the middle and lower reaches. It was evident that between the years 2015 and 2020, the region exhibiting elevated risk levels surpassed that of reduced risks, and the magnitude of alterations in risk levels was more pronounced. The distribution of landscape ecological risk demonstrated a positive spatial association, characterized by a generally consistent spatial clustering pattern. Initially, high-high clustering rose before declining, whereas low-low clustering persisted in its decline. ④ The level of human disturbance, land use intensity, NDVI, and slope have been identified as significant determinants of landscape ecological risk in the Yangtze River Economic Belt. The explanatory power of pairwise interactions between driving factors was enhanced. The results of the research are of significance for the optimization of ecological compensation and sustainable development planning in the study area.

RevDate: 2026-09-21
CmpDate: 2026-09-21

Maździarz M, Bilska K, Krawczyk K, et al (2026)

ZymoR: Bridging plant pathology and automated bioinformatics for fungicide resistance profiling in Zymoseptoria tritici.

World journal of microbiology & biotechnology, 42(10):.

Zymoseptoria tritici, the causal agent of Septoria tritici blotch (STB), is one of the most destructive fungal pathogens of wheat worldwide. The extensive use of fungicides has driven the emergence of diverse resistance mechanisms involving multiple target-site genes, as well as non-target-site resistance. High-throughput sequencing (HTS) technologies now enable large-scale detection of resistance-associated genetic variation, yet routine implementation of HTS-based monitoring remains constrained by the lack of standardized analytical workflows and tools that translate sequence data into biologically meaningful resistance information. Here, we present ZymoR, a dedicated bioinformatics platform for automated molecular surveillance of fungicide resistance in Z. tritici. ZymoR integrates sequence quality assessment, mutation detection and CYP51 haplotype classification within a single user-friendly workflow. The platform incorporates a curated and expandable database of resistance-associated variants across the principal fungicide target genes, enabling standardized annotation of known resistance markers while facilitating the identification of previously undescribed variants. Unlike conventional variant-calling pipelines, ZymoR links detected genetic variation to standardized nomenclature and resistance-associated metadata, substantially reducing the bioinformatic expertise required for data interpretation. The ZymoR package was made available as an open-source tool via GitHub at https://github.com/Mordziarz/ZymoR .

RevDate: 2026-09-21
CmpDate: 2026-09-20

Mirchandani C, Omarjee A, Achaz G, et al (2026)

Variant calling in nonmodel organisms with snpArcher.

Molecular biology and evolution, 43(9):.

Population genomic studies in nonmodel organisms increasingly depend on whole-genome resequencing, yet translating raw reads into reliable variant callsets remains a practical challenge due to the complexity of multistep bioinformatics pipelines and the absence of species-specific best practices. Here, we present a step-by-step protocol for snpArcher, a Snakemake-based workflow that takes raw sequencing reads and a reference genome as input and produces a filtered, joint-called Variant Call Format (VCF) file suitable for downstream population genomic analysis. We guide users through six phases: installation and environment setup, sample sheet creation, run configuration, execution on local or high-performance computing systems, quality control review using an interactive HTML dashboard, and downstream analysis, focusing on postprocessing and filtering. The quality control (QC) dashboard aggregates individual-level metrics including principal component analysis, relatedness estimation, depth-missingness diagnostics, and admixture analysis to help identify batch effects, contamination, cryptic relatedness, and outlier samples before downstream analysis. We demonstrate the impact of sequential filtering steps on the site frequency spectrum and demographic inference using a dataset of 137 burrowing owl (Athene cunicularia) genomes, showing how removal of low-coverage individuals, sex-linked scaffolds, and regions of excess heterozygosity eliminates artifacts that would otherwise bias inference of population size history. This protocol is intended as a practical companion to the original snpArcher publication, enabling researchers working with nonmodel organisms to produce and evaluate analysis-ready variant callsets in a reproducible manner.

RevDate: 2026-09-21
CmpDate: 2026-09-21

Althouse BM (2026)

Ecological specialization in vectors alters transmission thresholds and endemic dynamics in multi-host, multi-vector systems.

PLoS computational biology, 22(9):e1014754 pii:PCOMPBIOL-D-25-00942.

Modeling vector-borne pathogens that circulate among several host and vector species hinges on how the force of infection (FOI) is defined. In an i-host, j-vector susceptible-infectious-recovered modeling framework I compare two common FOI denominators: (i) a weighted form in which vectors bite preferred hosts disproportionately, and (ii) an unweighted form that assumes opportunistic biting. Using identical parameter sets calibrated to primate-Aedes data from Kédougou (Senegal), the weighted FOI doubles the basic reproduction number (R0) relative to the opportunistic FOI and can shift R0 across the epidemic threshold. It also produces higher long-run prevalence and larger oscillations. Both autonomous formulations undergo a forward transcritical bifurcation at R0 = 1. Selecting an ecologically realistic biting assumption is therefore critical for predicting sylvatic-to-urban spillover risk and designing interventions in multi-host systems.

RevDate: 2026-09-18
CmpDate: 2026-09-18

Sun L, An J, Yan T, et al (2026)

Multi-Omics Analysis Provides Insights Into the Molecular Mechanism of Melatonin-Mediated Cadmium Tolerance in Populus tomentosa.

Journal of pineal research, 78(5):e70184.

Cadmium (Cd) contamination, a major constraint on plant growth, causes a serious threat to ecological safety. Populus tomentosa is a promising woody species for Cd phytoremediation, but the mechanism of Cd phytoremediation by melatonin (MT) in this species remains unclear. To elucidate how MT confers Cd tolerance in P. tomentosa, four treatments (control, MT: 100 μmol·L[-1] melatonin, Cd: 100 μmol·L[-1] CdCl2, and MT + Cd, CM: 100 μmol·L[-1] CdCl2 + 100 μmol·L[-1] melatonin) on seedlings were conducted, and integrated analyses of physiological traits, noninvasive micro-test (NMT) data, transcriptomes, and metabolomes were further performed. Cd stress significantly inhibited seedling growth, reduced chlorophyll content, promoted excessive Cd accumulation, and triggered a burst of reactive oxygen species (ROS). Exogenous MT application reversed Cd-induced growth suppression by promoting root Cd[2+] efflux while reducing Cd influx, decreasing Cd deposition in leaves, and activating superoxide dismutase and peroxidase to scavenge ROS under Cd treatment. Transcriptomic and metabolomic profiling suggested that metabolic pathways, including hormone signaling, glutathione metabolism, and phenylpropanoid biosynthesis, might be participated in the MT-mediated Cd response. Furthermore, three transcription factors, ERF098, bHLH041, and MYB308, were also identified as candidate regulators of MT-mediated Cd detoxification. Heterologous expression in yeast revealed that MYB308 not only enhanced Cd tolerance but also reduced Cd accumulation under Cd stress. These findings elucidate the multilayered regulatory network underlying MT-enhanced Cd tolerance in P. tomentosa, and provide genetic resources for breeding Cd-resistant tree varieties and theoretical guidance for remediating Cd-contaminated soils.

RevDate: 2026-09-18

Moctezuma Tan L, Orcales F, P Pennings (2026)

Response to comment on "Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper".

PLoS computational biology, 22(9):e1014710.

RevDate: 2026-09-18
CmpDate: 2026-09-18

Yan X, Hassett AL, Waljee JF, et al (2026)

Engagement With a Relaxation-Based Mobile Health Intervention for Perioperative Anxiety: Prospective Longitudinal Cohort Mixed Methods Study.

JMIR mHealth and uHealth, 14:e64278 pii:v14i1e64278.

BACKGROUND: Relaxation-based mobile health (mHealth) interventions hold strong potential to address perioperative anxiety and pain management in a scalable manner. However, there is limited research on how surgical patients engage with these interventions and what aspects may be most helpful.

OBJECTIVE: This study had 3 goals: (1) explore how users interact with a relaxation-based mHealth intervention during the perioperative period; (2) understand how user performance and perceptions relate to perceived benefits; and (3) identify design considerations to enhance user engagement and behavior change outcomes in mHealth interventions.

METHODS: We conducted a prospective longitudinal cohort, mixed methods study to evaluate user engagement with MiCarePath, a relaxation-based mHealth intervention. A total of 19 perioperative patients (mean age 41.3 years; 14/19, 74%, female) undergoing elective surgery and reporting sometimes-to-always anxiety were enrolled using 3 recruitment methods. Participants used the app from 10 days before surgery to 4 weeks after surgery. We collected quantitative data on video engagement metrics (eg, duration of watching, response rate to video prompts) and ecological momentary assessments of anxiety and pain. Concurrently, we conducted semistructured, data-prompted interviews at 3 time points to assess user perceptions. These data were integrated using descriptive statistics, repeated-measures ANOVA, and qualitative thematic analysis to examine the relationship between user performance and perceived benefits.

RESULTS: Eleven participants reported developing or improving relaxation-based self-management strategies (high benefit), whereas 8 reported little benefit from the intervention. The high-benefit group showed significantly greater total watching time (difference 223.8 minutes, 95% CI 95.54-366.46 minutes, P<.001), higher adherence to video prompts (73.45% vs 34.60%, P<.001), and greater perceived helpfulness of the content (79.80% vs 25.50%, P<.001) compared with the low-benefit group. A significant group-by-time interaction effect was observed for engagement (F1,17=17.02, P<.001). No difference was observed in delay in response to video prompts. However, within each group, participant perceptions were not fully reflected in performance. Some participants in the high-benefit group showed decreased video watching after surgery but still reported feeling engaged with the intervention. Interview data revealed that "intentional use" behavior-where users actively seek content to manage symptoms independent of prompts-distinguished these participants. Those who developed intentional use were able to practice relaxation techniques without the app and resume app engagement following contextual disruptions.

CONCLUSIONS: This study explored user engagement with a relaxation-based mHealth intervention for perioperative care, advancing the literature by integrating user perceptions and performance for digital anxiety and pain management. Results indicate that perceived benefit may not always be reflected in user performance. Intentional use emerges as a promising indicator of effective mHealth engagement in perioperative care. Future designs should aim to foster intentional use through features such as reflection prompts and adaptive notifications. Future work should also develop computational models to detect intentional use and evaluate adaptive interventions in larger cohorts.

RevDate: 2026-09-19

Yorozu K, Hinotsu S, Matsuura M, et al (2026)

A decade of decline and regional disparity: Trends and associated factors in use of ritodrine hydrochloride for threatened preterm labor in Japan, a nationwide ecological study.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics [Epub ahead of print].

OBJECTIVE: Ritodrine hydrochloride is a commonly used tocolytic agent for threatened preterm labor in Japan, despite its serious adverse events and limited use in many other countries. National obstetric guidelines have shifted toward restricting its use, but the evidence-practice gap remains unclear. The aim of this study is to determine usage trends for ritodrine at nationwide and prefectural levels and identify factors associated with usage.

METHODS: We conducted an ecological study linking nationwide aggregated medical claims data and statistical survey records across all 47 prefectures. We investigated 10-year trends in ritodrine use from fiscal year (FY) 2014 to 2023. Choropleth maps and spatial statistics illustrated geographic relationships among neighboring prefectures. We also conducted a cross-sectional study to identify factors associated with ritodrine injection use.

RESULTS: The usage rate of ritodrine injection per 1000 deliveries decreased by more than 45% over 10 years. Joinpoint regression analysis identified FY2017 as a turning point, after which the decline accelerated. However, prefectural usage varied up to 13.58-fold, with spatial clustering of high-use regions. Factors associated with injection usage included the density of Perinatal Medical Centers (PMCs), hospital admissions for threatened preterm labor and preterm birth per 1000 deliveries, and the proportion of hospitals among delivery facilities.

CONCLUSION: This study showed that nationwide use of ritodrine injection decreased by half over a decade, along with regional disparities among prefectures in Japan. These variations might reflect localized treatment policies influenced by differences in healthcare resources and geographical accessibility.

RevDate: 2026-09-21
CmpDate: 2026-09-21

Peng S, Butler-Laporte G, Johnson SC, et al (2026)

Genetic evidence suggests a protective role of immunoglobulin M in Alzheimer's disease.

Alzheimer's & dementia : the journal of the Alzheimer's Association, 22(9):e71865.

INTRODUCTION: Immune dysfunction has been implicated in Alzheimer's disease (AD), but the roles of specific immunoglobulin classes remain unclear.

METHODS: We integrated human genetics and plasma biomarker analyses to evaluate immunoglobulin G (IgG), IgA, and IgM in relation to AD. Two-sample Mendelian randomization analyses were conducted with multiple sensitivity analyses. Polygenic risk scores for immunoglobulin classes were developed in the All of Us Research Program and tested in the UK Biobank for associations with AD and dementia, and in two Wisconsin-based cohorts for associations with plasma amyloid beta (Aβ)42/40, phosphorylated tau 217 (p-tau217), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP).

RESULTS: Higher genetically proxied IgM was consistently associated with lower AD risk, higher Aβ42/40, and lower p-tau217, but not with NfL or GFAP. No consistent associations were observed for IgG or IgA.

DISCUSSION: IgM-related humoral immunity may play a protective role in AD and warrants exploration for early intervention and prevention.

RevDate: 2026-09-19

Calderón Del Cid C, Versiane AFA, Leitman P, et al (2026)

refloraR: An R package for efficiently retrieving and analyzing plant specimen data from the Herbário Virtual Reflora.

Applications in plant sciences [Epub ahead of print].

PREMISE: Advances in the digitization of herbarium collections are enabling open access to specimen data for research and conservation. In Brazil, the Herbário Virtual Reflora (HVR) hosts over 4.8 million high-resolution images of botanical specimens and their associated data from 86 national and international herbaria.

METHODS AND RESULTS: To facilitate access and use of HVR data in biodiversity research, we developed the R package refloraR. This tool interacts with the HVR Integrated Publishing Toolkit (IPT) to download, parse, summarize, and filter herbarium records in Darwin Core Archive (DwC-A) and dataframes. It also retrieves occurrence records and indeterminate specimens for any hierarchical level. We provide a working example that combines the refloraR functions for quantifying indeterminate specimens as an indicator of taxonomic gaps within and among collections.

CONCLUSIONS: The refloraR package supports reproducible workflows in systematics, conservation, and ecology. By enabling the efficient retrieval of specimen data, it integrates the HVR into modern biodiversity informatics and democratizes access to natural history collections.

RevDate: 2026-09-18
CmpDate: 2026-09-18

Mekonnen GB (2026)

Integrative multi-omics and predictive precision systems for poultry meat and egg quality: Mechanisms, applications, and commercial challenges.

Poultry science, 105(10):107378.

Poultry meat and egg quality result from complex interactions among host genetics, metabolism, nutrition, microbiome ecology, physiology, management practices, and environmental conditions. These multidimensional interactions limit the predictive capacity of conventional phenotype-based approaches and increasingly necessitate systems-level frameworks capable of capturing biological complexity. Recent advances in multi-omics technologies have transformed poultry quality research by enabling integrated analyses of genomic, transcriptomic, proteomic, metabolomic, lipidomic, epigenomic, and microbiome datasets. These approaches have substantially enhanced understanding of the molecular, cellular, physiological, and ecological networks associated with product quality, production efficiency, physiological resilience, and environmental adaptation. Integrated multi-omics analyses, particularly when combined with artificial intelligence and machine-learning approaches, have the potential to identify biologically interpretable biomarkers, candidate mechanistic pathways, and predictive signatures associated with meat and egg quality traits; however, most proposed signatures remain at early stages of validation and require rigorous external testing before commercial deployment. This review synthesizes current advances in omics-driven poultry research and critically evaluates emerging applications in precision nutrition, breeding, health monitoring, environmental adaptation, and sustainable production systems. To provide a unifying biological framework, we propose the Adaptive Systems Theory of Poultry Quality (ASTPQ), which conceptualizes poultry quality as an emergent adaptive phenotype arising from coordinated interactions among mitochondrial function, redox homeostasis, immune competence, metabolic flexibility, physiological resilience, endocrine-immune regulation, and host-microbiome dynamics. Within this conceptual framework, adaptive-system capacity is proposed as the principal integrative mechanism linking molecular regulation with phenotypic quality outcomes across diverse production environments. Despite substantial advances, commercial implementation remains constrained by biological heterogeneity, methodological variability, limited external validation, computational complexity, challenges in data integration, infrastructure requirements, and economic barriers. Current evidence suggests that predictive performance depends less on increasing molecular dimensionality than on developing biologically interpretable, externally validated, economically feasible, and operationally scalable systems. Future progress will likely require integrated precision-production frameworks that combine molecular biomarkers, physiological monitoring, environmental sensing, microbiome-informed interventions, explainable artificial intelligence, and rigorous large-scale field validation to support sustainable, resilient, and commercially applicable poultry production systems.

RevDate: 2026-09-16

Litavský J, Majzlan O, V Langraf (2026)

Environmental drivers of carabid beetle communities in a historical urban park: a case study from Rusovce, Slovakia.

Biologia futura [Epub ahead of print].

Urban green spaces, particularly historical parks, serve as important refuges for biodiversity in cities. However, the traits that allow species to persist in these areas remain underexplored. Carabids are widely recognised as sensitive bioindicators of environmental change and habitat quality. We studied carabid beetle communities in seven distinct habitats within a historical park in Rusovce (Bratislava, Slovakia) from March 2019 to April 2020 using pitfall traps, recording 756 individuals belonging to 54 species. The community was dominated by three large, flightless forest species: Abax parallelepipedus, Carabus ulrichii, and Carabus coriaceus. Strikingly, flightless species as a whole made up only 17% of species richness yet 80% of all individuals, suggesting that the park sustains populations of poorly dispersing, disturbance-sensitive carabids at unusually high densities for an urban setting. Redundancy analysis showed that microclimatic conditions (soil, surface, and air temperature) and vegetation structure (tree and herb layer cover and richness, stand age, and litter depth) were the principal drivers of community composition, whereas among management practices, only invasive plant species and trampling significantly reduced beetle diversity; mowing, tree cutting, and monoculture plantations had no measurable effect. Comparing these results with our parallel studies of harvestmen and spiders from the same park revealed that each taxon responds to a distinct combination of environmental drivers, underscoring the value of multi-taxon monitoring for urban biodiversity assessment. These findings identify concrete, low-cost management levers, such as controlling invasive plants and limiting trampling, that city park managers can use to protect ground-dwelling arthropod diversity as urbanisation intensifies.

RevDate: 2026-09-18
CmpDate: 2026-09-16

Gardner B, McCarthy PT, Chrol-Cannon J, et al (2026)

Hierarchical feature binding in a spiking neural network model of the primate ventral visual pathway.

PLoS computational biology, 22(9):e1014752.

Feature binding - how the brain encodes which features are part of other features to form representations of the coherent objects we perceive - remains an unsolved problem in neuroscience. Despite progress towards a solution, major theories either lack detailed explanations at the neuronal level or rely on biologically unrealistic simplifications, and none adequately account for the representation of hierarchical information, which is crucial to our perception of the world. To address this, a solution termed binding by polychrony has been proposed to explain how hierarchical feature relationships may be encoded at the neuronal level in a biologically realistic system. This theory relies on a phenomenon known as polychronization, where groups of neurons fire in precisely coordinated, time-locked sequences, leading to the emergence of regularly repeating spatiotemporal patterns that might encode these relationships. In this study, we explore binding by polychrony through simulations of a spiking neural network that closely aligns with the structural organisation of the primate ventral visual pathway, incorporating bottom-up, top-down, and lateral synaptic connections. By exposing the network to collections of related 2D object shapes from ecologically realistic datasets and applying spike-timing-dependent plasticity, the network self-organises such that individual neurons respond selectively to specific shape features. Furthermore, the network exhibits polychronization, giving rise to repeating spatiotemporal patterns, some of which form circuits that encode hierarchical feature relationships. Notably, these circuits are robust, even with the randomised, Poisson-distributed spike timings that represent the visual stimuli in the input layer. These results provide evidence for binding by polychrony as a feasible solution to the feature binding problem, and characterise the mechanism by which it may function. This mechanism can guide experimentalists in identifying such circuits in vivo, and could also be utilised in computer vision systems to capture more information and improve robustness to adversarial inputs.

RevDate: 2026-09-18
CmpDate: 2026-09-17

Titelman D (2026)

Editorial: Applied psychoanalysis and psychoanalytically informed research.

Frontiers in psychology, 17:1956380.

RevDate: 2026-09-17
CmpDate: 2026-09-17

Nagy DU, Callaway RM, Luke Flory S, et al (2026)

Rapid and repeated evolution of increased competitive ability in a global invader.

Nature communications, 17(1):.

Rapid adaptive evolution can increase the competitive ability of invasive species in their non-native ranges. However, whether this increase is a general response and what drives it remain uncertain because the evidence is largely based on studies with limited sampling, inadequate consideration of population co-ancestry, and oversimplified estimates of competitive ability. We conduct a large-scale glasshouse experiment testing the effects of competition and drought on 100 native and 165 non-native populations of Erigeron canadensis, all genotyped to account for co-ancestry. Plants from non-native populations are significantly more competitive against other species than the conspecifics from native populations under both mesic and dry conditions. Genetic clustering indicates that the rapid evolution of competitive ability occurs independently in two out of four clusters in the non-native range. This advantage is present only during interspecific interactions and is absent during intraspecific competition. Repeated evolution of increased competitive ability suggests that adaptation following introduction can reshape species interactions and promote invasion success, even under future drought conditions, highlighting the importance of rapid evolution in determining the ecological impacts of invasive plants.

RevDate: 2026-09-18
CmpDate: 2026-09-18

Kaufhold G, Bartolomaeus TUP, Schütte K, et al (2026)

Machine learning identifies microbiome and clinical predictors of sustained weight loss following prolonged fasting.

Genome medicine, 18(1):.

BACKGROUND: Prolonged fasting may improve metabolic health, but controlled data in healthy adults with longer follow-up and multi-omics profiling are limited. We investigated the immediate and 12-week follow-up effects of a 5-day fasting intervention on body composition, gut microbiome, and circulating and fecal metabolites, and assessed whether baseline characteristics predict individual weight-loss response.

METHODS: In a randomized, waitlist-controlled trial, 38 healthy adults completed a 5-day fasting intervention with 12-week follow-up (LEANER study). Outcomes included body mass index and body composition, gut microbiome composition, and plasma and fecal metabolites. Changes over time and between groups were evaluated using regression-based models and paired non-parametric tests, as appropriate. Additionally, permutation-based multivariate testing was performed on microbiome and metabolome data. Twelve-week body weight response was predicted using data-driven machine learning with cross-validation, followed by external validation in three independent cohorts undergoing prolonged fasting protocols.

RESULTS: Fasting reduced body mass index acutely, predominantly driven by loss of fat mass, and these improvements partially persisted at 12 weeks. Fasting induced marked shifts in gut microbiome composition and in plasma and fecal metabolites. Post-fasting and longer-term changes in microbial diversity were associated with baseline microbiome diversity. A model combining baseline microbiome and clinical variables predicted body mass index response at 12 weeks; prominent predictors included an unclassified Faecalibacterium species, Oscillibacter sp. 50_27, low-density lipoprotein cholesterol, and systolic blood pressure. The model generalized to three independent cohorts, including individuals with metabolic syndrome, patients with multiple sclerosis exposed to repeated fasting, and healthy volunteers fasting for 6-12 days.

CONCLUSIONS: In healthy adults, a 5-day prolonged fasting intervention produces robust short-term metabolic changes with partial persistence and consistent remodeling of the gut microbiome and metabolite profiles. Baseline microbiome and clinical characteristics can help stratify expected longer-term responses, supporting the development of individualized fasting-based interventions.

TRIAL REGISTRATION: ClinicalTrials.gov, NCT04452916. Prospectively registered on June 29, 2020.

RevDate: 2026-09-18
CmpDate: 2026-09-18

Shalabi KM, Mahmoud H, Pakkir Mohamed SH, et al (2026)

Digital biomarkers derived from wearable sensors in neurorehabilitation: a scoping review.

Frontiers in neurology, 17:1908796.

BACKGROUND: Wearable-derived digital biomarkers are increasingly being investigated in neurological rehabilitation to provide objective and continuous assessment of physical function beyond conventional clinic-based measures. However, the clinical applications and measurement characteristics of these biomarkers across neurological populations remain unclear.

OBJECTIVE: To synthesize the current evidence regarding wearable-derived digital biomarkers used in neurological rehabilitation and to summarize their clinical applications, biomarker domains, and measurement characteristics across neurological conditions.

METHODS: A scoping review was conducted following the PRISMA-ScR framework. Electronic databases including PubMed/MEDLINE, ScienceDirect, Cochrane Library, and Google Scholar were searched for English-language studies published between January 2015 and May 2026. Eligible studies investigated wearable-derived digital biomarkers in neurological rehabilitation populations.

RESULTS: A total of 56 studies were included in the review, with stroke (n = 29) and Parkinson disease (n = 10) representing the most frequently investigated neurological conditions. Inertial Measurement Unit (IMU) based systems were reported in 34 studies, making them the predominant wearable technology. Kinematic biomarkers were the most commonly investigated biomarker domain, particularly in stroke (16/29) and Parkinson disease studies (9/10). In contrast, activity-based (2/5) and physiological biomarkers (2/5) were more prevalent in spinal cord injury research. Although several studies reported favorable validity and reliability of wearable-derived measures, substantial heterogeneity was observed across studies in sensor configurations, biomarker definitions, and validation methodologies.

CONCLUSION: Wearable-derived digital biomarkers demonstrate considerable potential for objective and ecologically valid monitoring in neurological rehabilitation. However, methodological heterogeneity and limited longitudinal evidence indicate that clinical implementation remains at an early stage of development.

RevDate: 2026-09-17
CmpDate: 2026-09-17

Yu R, Zhang S, Li Y, et al (2026)

Sex- and age-dependent physiological adaptation of captive père david's deer revealed by multi-omics analysis.

BMC genomics, 27(1):.

BACKGROUND: Understanding how age and sex influence molecular and physiological changes is essential for studying endangered species, particularly Père David's deer, which is extinct in the wild. In this study, multi-omics analyses were performed to investigate transcriptomic, metabolomic, and proteomic dynamics in male and female Père David's deer across different developmental stages under captive conditions.

RESULTS: The results revealed sex- and stage-specific molecular trajectories, with males showing enhanced ion metabolism during early life and females exhibiting increased lipid metabolism during the subadult stage. A substantial proportion of differentially abundant metabolites and differentially expressed proteins were associated with immune and inflammatory processes. Transcriptome-based age estimation indicated that individuals at the Fawn stage exhibited younger transcriptomic profiles, and enrichment analysis of highly weighted genes highlighted immune-related pathways. In addition, transcriptomic deconvolution analysis revealed coordinated alterations in innate and adaptive immune cell populations during development.

CONCLUSIONS: These findings provide a comprehensive multi-omics characterization of molecular and immune dynamics in captive Père David's deer and improve understanding of developmental and sex-associated biological variation in this endangered species.

RevDate: 2026-09-17
CmpDate: 2026-09-17

Benhamou W, Howerton E, Park SW, et al (2026)

Leveraging perturbations to infer the population dynamics of human rhinovirus and interaction of influenza A virus.

PLoS computational biology, 22(9):e1014784.

Many respiratory pathogens co-circulate within human populations. Yet, how pathogen community structure shapes the dynamics of infectious diseases remains poorly understood. At the population level, investigating polymicrobial dynamics, with potential underlying competitive or cooperative interactions, is challenging, because of confounding factors such as differing seasonality. This is particularly true for endemic pathogens which typically exhibit stable periodic dynamics. Their disruption due to the implementation of non-pharmaceutical interventions during the COVID-19 pandemic thus represents a unique large-scale natural experiment that can be leveraged to provide valuable insights into the complex interplay between respiratory pathogens. Here, we focus on the population dynamics of human rhinovirus (common cold) and on the potential viral interference of influenza A virus (flu A), which is hypothesized to account for their asynchronous circulation. Using a Bayesian framework, we first show based on simulations that exogenous perturbations can be a powerful tool to disentangle the contribution of pathogen interaction from other epidemiological factors. We then apply our framework to surveillance time series from the US and Canada spanning the COVID-19 pandemic. We estimate key parameters of rhinovirus but find no conclusive support for an influence of influenza A virus at the population level.

RevDate: 2026-09-16
CmpDate: 2026-09-16

Torales J, O'Higgins M, Barrios I, et al (2026)

From Mood Episodes to Digital Signatures: Passive and Active Phenotyping of Bipolar Disorder Over Time.

The International journal of social psychiatry, 72(6):1463-1474.

BACKGROUND: Digital phenotyping has emerged as a promising approach to capture real-time behavioral and physiological data in individuals with bipolar disorder (BD). By integrating passive and active data streams, this approach may enable the identification of dynamic patterns associated with mood instability. However, the conceptual integration of these data into clinically meaningful digital signatures remains insufficiently defined and lacks standardized operational frameworks.

METHODS: This narrative review synthesizes current evidence on digital phenotyping in BD and proposes a conceptual framework integrating passive sensing (e.g. smartphones, wearables, mobility and communication data, physiological signals) and active assessments (e.g. ecological momentary assessment, self-reported mood, cognitive tasks). The framework outlines how multimodal digital biomarkers can be analyzed using computational approaches, including machine learning and longitudinal modeling, to derive individualized digital signatures.

RESULTS: The proposed framework describes how continuous behavioral and physiological data can be transformed into multimodal digital biomarkers reflecting sleep-wake rhythms, motor activity, mobility patterns, social interaction dynamics, and autonomic physiology. Through multimodal data integration and personalized baselines, computational models can identify temporal deviations associated with mood changes. These individualized digital signatures capture the dynamic processes underlying mood regulation and may provide early warning signals of relapse, as well as markers of treatment response.

CONCLUSIONS: Digital signatures derived from integrated digital phenotyping data represent a promising step toward precision psychiatry in BD. However, this concept remains an emerging framework requiring further empirical validation and methodological standardization. This approach highlights the potential for early detection of mood instability, prediction of mood episodes, and personalized clinical decision-making. Future research should focus on validation in longitudinal clinical cohorts, standardization of methodologies, and ethical considerations related to data privacy and implementation.

RevDate: 2026-09-16
CmpDate: 2026-09-16

Fakhruddin KS, Shahwan M, Kamal A, et al (2026)

Human Lingual Biofilm Signatures in Gastrointestinal Disease: A Scoping Review.

International dental journal, 76(5):109762.

INTRODUCTION AND AIMS: The tongue dorsum represents a structurally complex oral biofilm niche that has traditionally been regarded as indicative of systemic health. Recent advances in oral microbiome research and multi-omics technologies facilitate the systematic evaluation of the association between tongue coating biofilm signals and gastrointestinal disease states. However, it remains unclear whether these tongue-derived signals indicate systemic gastrointestinal pathology or merely reflect localised oral ecological disturbances. This review synthesises current evidence on tongue-derived microbial and multi-omics signatures across inflammatory, precancerous, and malignant gastrointestinal conditions, and evaluates their ecological, biological, and clinical significance.

METHODS: A scoping review was conducted in accordance with PRISMA-ScR guidelines. Five electronic databases were searched (2010-2025) for human studies analysing tongue-coating samples using microbiome or multi-omics approaches.

RESULTS: A total of twenty-five cross-sectional studies involving more than 4500 participants, primarily from East Asian populations, were included. Three recurrent patterns were identified: (1) stage-associated microbial restructuring, which involved mild non-specific alterations in inflammatory states, structured dysbiosis in precancerous conditions, and more consistent ecological configurations in malignancy; (2) convergence of functional multi-omics signals on lipid metabolism pathways across independent cohorts; and (3) significant modification of microbial and functional profiles by tongue coating phenotype, including colour, thickness and classification system.

CONCLUSIONS: Tongue-derived microbial and multi-omics signatures demonstrate reproducible cross-sectional associations with gastrointestinal diseases, exhibiting functional convergence across multiple omics layers. However, the reliance on cross-sectional study designs, absence of external validation and insufficient adjustment for confounding variables currently limit their clinical application as diagnostic biomarkers.

CLINICAL RELEVANCE: Tongue examination is clinically useful for assessing oral biofilm burden, mucosal pathology and oral hygiene in dental practice. It should not be used to diagnose gastrointestinal disease until validated by longitudinal, confounder-controlled studies.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Chen Y, Wang G, Xie W, et al (2026)

Comparison of Cadmium Efflux in Wheat (Triticum aestivum) Cultivars with Contrasting Cadmium Accumulation.

Bulletin of environmental contamination and toxicology, 117(3):.

Cadmium (Cd) is a highly toxic heavy metal threatening human health. Wheat readily translocates Cd to grains, posing food safety risks in contaminated soils. Screening low-Cd cultivars is therefore critical. In pot experiments with 53 wheat cultivars, Kaimai 21 (KM21) and Lunxuan 6 (LX6) showed the lowest and highest grain Cd, respectively. Under 5-10 µM Cd in hydroponics, KM21 harbored 30.1%-63.6% lower root Cd, 54.7%-69.1% lower shoot Cd, and exhibited superior root growth and Cd tolerance than LX6. Crucially, KM21 showed a 36.9% higher Cd efflux rate and a larger Cd efflux proportion than LX6 (44.3% vs. 15.5%). Real-time Cd[2+] flux measurements using Non-invasive Micro-test Technology (NMT) further confirmed higher Cd efflux capacity in KM21, which contributed to higher Cd tolerance and lower Cd accumulation. Overall, KM21 is a stably high-Cd efflux and low-Cd accumulation wheat cultivar suitable for safe production in Cd-contaminated soils.

RevDate: 2026-09-15

Beigel K, Bringhurst B, Greenwold M, et al (2026)

Corrigendum to "Non-reciprocal coevolution in a fungus-gardening ant" [Mol. Phylogenet. Evol. 220 (2026) 108608].

RevDate: 2026-09-15
CmpDate: 2026-09-15

Ramola R, De Paolis Kaluza MC, Piovesan D, et al (2026)

On the state of protein function prediction: a report on the fourth CAFA challenge.

bioRxiv : the preprint server for biology.

BACKGROUND: The Critical Assessment of Functional Annotation (CAFA) is a community effort held to understand the field of computational protein function prediction. Every three years, since 2010, the organizers initiate an experiment to collect function predictions on a large set of proteins and then evaluate the performance of predicting methods on a subset of proteins that have accumulated experimental annotations between the submission deadline and the evaluation time. CAFA provides an independent and rigorous assessment of the current state of the art, thus leveling the playing field, highlighting successes, revealing bottlenecks, and offering a forum for the exchange of ideas in protein science. Here, we report the results of the fourth CAFA experiment (CAFA4).

RESULTS: CAFA4 featured the participation of 148 methods from 70 research groups on a total of 46,205 unique proteins over a 5-year annotation accumulation phase, the longest in any CAFA. In a comparison across CAFA2-CAFA4 methods, the prediction of Gene Ontology (GO) terms has clearly improved across all three GO aspects and traditional evaluation settings. While not achieving the first rank, several CAFA2 and CAFA3 methods featured in the top ten methods in many evaluations, suggesting that earlier methods still hold relevance. The performance is weaker in the newly introduced "partial knowledge" evaluation category (proteins with experimental annotations before submission deadline that gained additional annotations in the same GO aspect during the annotation accumulation phase), highlighting the need for a new class of methods. The rankings of the methods were stable over the years in traditional evaluation settings, but less so in the new partial knowledge evaluation. Overall, the field continues to progress with some influx of new participants. Sustained efforts will be necessary to substantially advance it.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Kösters LM, Karbstein K, Hodač L, et al (2026)

Balanced DNA interpolation improves learning of genetic distance-informed embeddings in plants.

PLoS computational biology, 22(9):e1014722.

In taxonomic research, traditional phylogenetic tree and structure analyses of genetic data are increasingly complemented by machine-learning-based identification and representation learning. Although the amount of DNA data needed to train state-of-the-art machine learning models often exceeds what can realistically be collected and sequenced in biological studies, the number of samples can be extended artificially through data augmentation. Genetic data augmentation usually refers to the introduction of random base variations, translocations, and reverse complementing. These augmentations do not take into account the inherent structures of populations and species, potentially blurring the lines between entities within genetic datasets. Here, we propose DNAInterpolator, an approach based on interpolation of DNA sequences within a given dataset that presents a neighbor-guided alternative to random mutations. We tested interpolation as an augmentation technique using four flowering plant datasets and an artificial neural network trained to predict genetic distances between paired samples. To address unequally distributed distances within our training datasets, we examined the effect of balancing the distance distribution by curating interpolated sequences. We found that balancing helps models capture genetic distances across the full distance range by strengthening performance in underrepresented regions of the distribution. Our new approach leverages the potential of taxonomic DNA datasets for modern machine learning applications.

RevDate: 2026-09-14
CmpDate: 2026-09-14

Chen W, Pan Y, Chen M, et al (2026)

Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression.

Gut microbes, 18(1):2726620.

Post-stroke depression (PSD) is a common complication that significantly impacts patient prognosis. This study aimed to systematically characterize the associations among gut microbial ecology, metabolic profiles, and inflammatory responses across different severities of PSD. We conducted metagenomic sequencing, non-targeted metabolomics, and serum cytokine analysis (IL-1β, IL-6, IL-10, IL-18, TNF-α, IFN-γ, and CRP) in 91 patients with varying degrees of PSD and non-PSD controls. Bioinformatics analyzes were employed to construct multi-omics association networks and machine learning models. Results indicated that PSD patients exhibited significantly increased gut microbiota alpha-diversity, suggesting dysbiosis. Mild depression was characterized by compensatory neural signaling activation, whereas the moderate depression group exhibited abnormalities in tryptophan/indole metabolism, oxidative stress-related metabolic imbalances, and functional decompensation. Further analyzes suggested that Alistipes, Blautia_A, Evtepia gabavorous, and Lachnospira were associated with inflammatory features, GABA-related metabolic alterations, aromatic amino acid/indole metabolism, and lipid-amino acid metabolism, respectively. Under a more rigorous 10-fold cross-validation framework, the performance of different multi-omics combination models showed heterogeneity; however, some combinations still demonstrated superior discriminatory ability compared to single-omics approaches. This study provides multi-omics clues suggesting associations between different PSD severity levels and features such as increased Alistipes abundance, reduced antioxidant capacity, and altered tryptophan metabolism. It provides candidate biomarker combinations that may be useful for PSD stratification and suggests that the gut microbiome may represent a potential target for future PSD intervention. In summary, PSD may be associated with dynamic alterations along the "gut-brain-inflammation-metabolism" axis. These findings provide integrated evidence for microbial, metabolic, and inflammatory abnormalities across different PSD severity levels, but still require validation in larger samples, longitudinal cohorts, and mechanistic studies.

RevDate: 2026-09-14
CmpDate: 2026-09-14

Hussein MA, A Abdelnaser (2027)

Integrative Transcriptomic Network Modeling Coupled with Patient-Derived Validation for Circulating lncRNA Biomarker Discovery in NAFLD: A Comprehensive Workflow.

Methods in molecular biology (Clifton, N.J.), 3074:481-527.

.: Nonalcoholic fatty liver disease (NAFLD) is a significant global health concern, impacting roughly 25% of people and leading to chronic liver conditions. It involves excess fat accumulation in the liver without significant alcohol intake and can develop into nonalcoholic steatohepatitis (NASH), fibrosis, or cirrhosis. While liver biopsy remains the gold standard for diagnosis, its invasive nature and associated risks restrict its routine use. Noninvasive biomarkers, such as serum ALT, AST, and various composite scores, are available; however, their clinical usefulness is often limited by variable sensitivity and specificity across different populations and disease stages. To overcome these limitations, this chapter offers a comprehensive, reproducible protocol for identifying and clinically validating circulating long noncoding RNA (lncRNA) biomarkers for NAFLD and NASH. The workflow integrates bioinformatic analysis of four Gene Expression Omnibus (GEO) transcriptomic datasets (two human and two murine cohorts) with network-based inference to construct a NAFLD-related lncRNA-miRNA-mRNA coregulatory network. This is followed by candidate prioritization based on cross-dataset evidence and a literature review. Candidate lncRNAs are then experimentally validated in patient-derived blood samples using quantitative PCR (qPCR), and their diagnostic performance is quantified using receiver operating characteristic (ROC) analysis, both as individual markers and multi-lncRNA panels. Circulating lncRNAs are detected in diverse biofluids, remain stable under standard preanalytical conditions, and are often tissue-specific. This integrated approach facilitates the development of more precise, scalable, and noninvasive biomarkers for NAFLD/NASH. The chapter further emphasizes essential translational steps, including preanalytical standardization, analytical validation, and validation in independent patient cohorts with relevant clinical endpoints.

RevDate: 2026-09-14
CmpDate: 2026-09-14

Yuan XH, Chen Y, Kuang ZY, et al (2026)

[Analysis of the global disease burden of cervical cancer in women aged 65 years and older based on the global burden of disease database].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine], 60(9):1436-1446.

Objective: Based on the Global Burden of Disease (GBD) database, this study analyzed the disease burden and attributable risk factors of cervical cancer among women aged 65 years and older globally from 1990 to 2021, and explored its association with the Socio-demographic Index (SDI) as well as age-specific distribution characteristics. Methods: This ecological study utilized the GBD database to extract data on the number of incident cases, age-standardized incidence rate (ASIR), number of deaths, age-standardized mortality rate (ASMR), disability-adjusted life years (DALY), age-standardized DALY rate (ASDR), and risk factor-attributable burden for cervical cancer in women aged ≥65 years from 1990 to 2021. The average annual percent change (AAPC) was calculated using Joinpoint regression analysis. Spearman rank correlation analysis was employed to assess the association between ASIR, ASDR, and SDI. Locally weighted regression (LOESS) was applied to fit smooth curves to illustrate expected trends across different SDI levels. Results: From 1990 to 2021, the ASIR of cervical cancer among older women decreased from 41.23/100 000 (95%UI: 37.71/100 000-44.45/100 000) to 32.43/100 000 (95%UI: 28.61/100 000-35.57/100 000) [AAPC:-0.8(95%CI:-0.9 to -0.6)]. The ASMR declined from 35.45/100 000 (95%UI: 32.24/100 000-38.54/100 000) to 25.20/100 000 (95%UI: 22.23/100 000-27.62/100 000) [AAPC:-1.1(95%CI:-1.2 to -1.0)]. The ASDR decreased from 658.01/100 000 (95%UI: 602.42/100 000-714.72/100 000) to 467.29/100 000 (95%UI: 416.92/100 000-510.34/100 000) [AAPC:-1.1(95%CI:-1.2 to -0.9)]. A negative correlation was observed between cervical cancer burden and SDI globally and across the 21 GBD regions (r=-0.881 4, P<0.001), with a greater burden in regions with lower SDI among the 204 countries and territories (r=-0.713 4, P<0.001). The number of incident cases, deaths, and DALYs in the 65-69 and 70-74 age groups accounted for 64.82%, 56.22%, and 68.96% of the total for women aged ≥65 years, respectively. The attributable risk burden from smoking [AAPC:-2.1(95%CI:-2.2 to -2.0)] and high-risk sexual behavior [AAPC:-1.1(95%CI:-1.2 to -0.9)] both decreased over time, this declining trend in attributable risk burden for smoking and high-risk sexual behavior was also observed with increasing age. Conclusions: Population aging has contributed to an increase in the absolute burden of cervical cancer among older women, with those aged 65-74 years identified as a key population requiring attention. Expanding the coverage and age range of screening programs is essential for further reducing the the burden of cervical cancer.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Di Paolo LD, Clark A, T Wachter (2026)

Educating minds with generative AI.

Communications psychology, 4(1):.

Generative artificial intelligence (GenAI) is rapidly entering education, framed as a tool for efficiency and personalization. In this Perspective, we argue this obscures a deeper transformation. Schools are cognitive ecologies in which tools and social practices actively shape learning. GenAI restructures this ecology, redistributing epistemic labour, consolidating pedagogical functions, and reorganizing how knowledge is accessed, produced, and evaluated. Unlike most educational technologies, it is active, persistent, and generalist. We identify two enduring misalignments: a pedagogical gap between learning sciences and AI design, and a goal gap between measurable performance and developmental aims. Both gaps reflect logics already embedded within existing educational systems organized around efficiency, standardization, and control. GenAI does not introduce but risks entrenching and amplifying these gaps. Rather than accommodating GenAI through technical adjustments, we propose treating it as a diagnostic opportunity to redesign schooling for embodied, collaborative, and distinctly human forms of learning.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Yu E, Holding ML, Huang R, et al (2026)

PhageScout: Protease Cleavage Site Prediction Using an Experimental Substrate Phage Display Motif-Based Approach.

International journal of molecular sciences, 27(17):.

Identification of protease cleavage sites is essential for understanding biological regulation and disease mechanisms, yet many predictive approaches rely on annotated substrates and curated databases, limiting performance for poorly characterized proteases. We present PhageScout, a framework for database-independent generation of protease-specific features to predict cleavage sites using de novo experimental substrate phage display screening. We screened a randomized 5-mer phage display library against two neutrophil serine proteases (cathepsin G, elastase). Cleaved peptides generated position weight matrices (PWMs) and peptide enrichment scores to evaluate cleavage-site likelihood across substrate sequences. Sequence-derived scores were integrated with structural features, including accessibility and flexibility, using XGBoost classification models. Performance was benchmarked against annotated cleavage sites from the MEROPS peptidase database as reference data. Phage-derived PWM scores alone captured protease preferences and discriminated cleavage sites from background sites. Without model fitting, PWM scores achieved an area under the curve (AUC) of 0.756 (95%CI: 0.714-0.797) (cathepsin G) and 0.787 (95%CI: 0.753-0.821) (elastase). Combining broad and specific phage-derived scores improved cathepsin G prediction (AUC = 0.783), whereas this improvement was not observed for elastase. Compared to only phage-derived features, XGBoost models integrating phage sequence and structural features provided modest gains for elastase (AUC = 0.775 to 0.806), with phage-derived features ranking among the strongest predictors, but not cathepsin G (AUC = 0.702 to 0.710). Our findings demonstrate that PhageScout can use experimentally derived cleavage signatures to generate protease-specific predictive features and prioritize protease cleavage sites, providing a framework that warrants further validation across diverse proteases and biological contexts.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Hollingsworth PM, Fantoni K, Koureas D, et al (2026)

Species identification, discovery, and biomonitoring: Strategic priorities for DNA barcoding in Europe, set in a global context.

Bioscience, 76(9):776-786.

The International Barcode of Life (iBOL) initiative is building a globally accessible DNA-based system for species identification and discovery. This paper outlines the mission and strategic priorities for the iBOL community in Europe (iBOL Europe), set in a global context. The mission of iBOL Europe is to produce, curate, and provide access to a complete DNA barcode reference library of European eukaryotic biodiversity, catalyzing species discovery and enabling comprehensive, harmonized species identification and biomonitoring, and supporting the global iBOL program. Immediate objectives include completing reference libraries for priority taxa, democratizing access to sequencing technologies, and strengthening a distributed community of practice. Key actions identified span five thematic areas: community building, sample collection and taxonomic verification, sequencing infrastructure, data management, and mainstreaming DNA-based approaches to meet societal needs. The strategy emphasizes integration with European research infrastructures to ensure long-term sustainability and resilience for biodiversity genomics in Europe.

RevDate: 2026-09-15
CmpDate: 2026-09-15

Chen J, Ren S, Tong Z, et al (2026)

An integrated culturomic and genomic database and analysis platform for methanogenic archaea.

Database : the journal of biological databases and curation, 2026:.

Methanogenic archaea research is challenged by limited strain resources, fragmented genomic data, inconsistent genome quality, substantial uncultured lineages, and difficulties in laboratory culturing, hindering advances in biogas production, climate mitigation, and microbial ecology. These archaea play crucial roles in global carbon cycling and anaerobic environments, yet scattered data and unculturable strains limit systematic studies and applications. To address this, we created MethArDB (Methanogenic Archaeal Genome Database), a specialized database for methanogenic archaea, compiling 3919 genomes, 87 host-associated plasmids, and 42 phages, with standardized quality classifications (complete, scaffold, draft), protein sequences, and metadata on geography, habitats, metabolism, and inheritable elements. Integrated MethArCT (Methanogenic Archaeal Culturomics Toolkit) employs a dual-threshold orthologous/paralogous protein analysis to evaluate metabolic pathway completeness, predicting cultivation parameters and suggesting candidate cultivation strategies, including potential medium formulations and conditions, to support strain isolation. Overall, MethArDB and MethArCT form an integrated platform combining genomics and culturomics to facilitate methanogenic archaea research. Database URL: http://methardb.cn.

RevDate: 2026-09-14
CmpDate: 2026-09-14

Wang G, He S, Wang Z, et al (2026)

T2T Genome Assembly and Multi-Omics Data Reveal Terrestrial Adaptation and Mucus Biosynthesis in Tropical Leatherleaf Slug (Laevicaulis alte).

Advanced science (Weinheim, Baden-Wurttemberg, Germany), 13(51):e76129.

Laevichaulis alte is a slug in the order Systellommatophora that evolved from aquatic ancestors and now faces strong challenges from desiccation, respiration on land, and novel pathogens. Its mucus is essential for water retention, locomotion, and defense. To link terrestrial adaptation with mucus biosynthesis, we generated a gap-free genome assembly of L. alte using PacBio HiFi reads, Oxford Nanopore ultra-long reads, and Hi-C data. The genome shows low heterozygosity and holocentromeric chromosomes. Functional metabolomics revealed marked metabolic shifts between L. alte and the closely related aquatic species Peronia verruculata. In L. alte, differential metabolites were enriched in lipid metabolism, immune regulation, and stress response pathways, consistent with life in a dry and microbe-rich terrestrial environment. Comparative genomics and transcriptomics identified candidate genes linked to mucus secretion and physiological adaptation, including VEGF, ASGR2, and COL6A6. Further analyses highlighted the vascular endothelial growth factor (VEGF) gene family as a key regulator connecting angiogenesis, tissue remodeling, and mucus production pathways in L. alte. Together, this gap-free genome and multi-omics dataset establish a molecular framework that links genomic innovation, mucus biology, and terrestrial adaptation in Systellommatophora, and they offer a basis for understanding ecological niche specialization in land molluscs.

RevDate: 2026-09-13

Diaz XN, Lin A, Babcock S, et al (2026)

Association of Community Factors, Firearm Laws, and Pediatric Firearm Injuries.

Pediatrics pii:209444 [Epub ahead of print].

OBJECTIVE: To conduct a zip code-level analysis of community measures and firearm legislation associated with pediatric fatal and nonfatal firearm injuries, ordered by strength of association.

METHODS: This was an ecological study of 46 states and the District of Columbia from January 1, 2018 to December 31, 2022. We examined 29 zip code-level variables from the American Community Survey, Social Vulnerability Index, Child Opportunity Index, Giffords Scorecard on Gun Safety Legislation, and the Structural Racism Effect Index. The outcome was the annual incidence of fatal and nonfatal pediatric firearm injuries in each zip code, as included in the National Emergency Medical Services (EMS) Information System (NEMSIS, all 9-1-1 EMS responses) and the Gun Violence Archive (GVA, all police-reported and publicly reported firearm events). We used negative binomial regression and machine learning analysis to evaluate predictors.

RESULTS: There were 28 631 zip codes included in the analysis. The average annual incidence of pediatric firearm injuries ranged from 0 to 16 per zip code in NEMSIS, with 1288 (4.5%) zip codes having at least one firearm incident. In GVA, annual incidence ranged from 0 to 35 per zip code, with 1180 (4.1%) zip codes having firearm events. Predictors of firearm injuries included structural racism (in social cohesion, built environment, employment, housing, and criminal justice), urbanicity, household income, unemployment, educational opportunities, and gun laws for background checks and firearm access.

CONCLUSIONS: Modifiable community characteristics and certain firearm legislation are associated with pediatric firearm injuries, providing focus areas for community planning, public health, and policy changes to reduce firearm-related injuries and deaths.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Li C, Wang Y, Zhou ASK, et al (2026)

Unraveling the coastal marine plastisphere archaeome.

Nature communications, 17(1):.

Plastic pollution has created an expanding anthropogenic microbial niche, the plastisphere, raising questions about microbial ecology and associated impacts. Archaea, the third domain of life with fundamental ecological and evolutionary significance, remain poorly understood in this habitat. Here, using paired plastic debris and bulk-water samples from coastal marine ecosystems, key archaeal habitats increasingly threatened by plastic pollution, we characterize the plastisphere archaeome through archaeal amplicon sequencing and metagenomics. We show that the archaeome is significantly reshaped in the plastisphere, exhibiting higher taxonomic diversity, greater community heterogeneity, and selective enrichment of Euryarchaeota and Crenarchaeota. Archaeal genes involved in methane, nitrogen, and sulfur cycling are enriched in the plastisphere. Taxonomic and functional divergence between the plastisphere and bulk water increases with anthropogenic chemical stress. These findings suggest that plastic pollution could alter marine archaeal diversity, biogeography, and biogeochemical potential, extending understanding of plastisphere impacts to the archaeal domain.

RevDate: 2026-09-14
CmpDate: 2026-09-14

Al-Shayeb SMA, Aguilar C, Yousefi M, et al (2026)

Invasive Flora Repository: Traits, environmental tolerances, and invasion history of invasive plant species in the United States.

Ecology, 107(9):e70492.

Species traits may serve as proxies for ecological mechanisms that drive invasion success and, therefore, are a promising framework for investigating invasion processes and predicting future outcomes of species that have been recently introduced. However, although many efforts exist to document species traits of plants, a centralized database of invasive plant species in the United States is not currently available. We have compiled traits data for 1024 invasive plants in the United States across 28 species characteristics, including functional morphological, reproductive, and dispersal traits, as well as characteristics related to the invasion history of the species, such as origin and invasion pathways. We identified our list of invasive plant species from EDDMapS, a web-based national network that aggregates observation records and distribution data of invasive species and pests in the United States and Canada, and the U.S. Register of Introduced and Invasive Species (US-RIIS). Traits data were collected from various online factsheet databases, including the CABI Compendium: Invasive Species, the USDA Plants Database, the North Carolina State Extension Plant Toolbox, the UC-Berkeley Jepson Herbarium, the USFS-Fire Effects Information System, and University of Michigan's CLIMBERS. We aimed to create a comprehensive database on traits of invasive species that can be utilized by researchers and conservationists and serve as a reference for those involved in the monitoring and control of invasive species. These data are available for reuse under CC BY 4.0 (Attribution) licensing.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Kwon J, de Vries EM, Lemey P, et al (2026)

Genomic surveillance of a deeply sampled local population reveals age-specific drivers of RSV transmission.

medRxiv : the preprint server for health sciences.

Respiratory syncytial virus (RSV) disproportionately causes severe infections among infants and older adults, yet the key age group responsible for viral spread to other age groups remains poorly defined. While current immunization approaches effectively reduce disease severity among the most vulnerable, identifying the core drivers of infection is essential to effectively disrupt population-level transmission. By generating 910 whole-genome viral sequences of RSV from all age groups (<1 to 65+ years) in Connecticut, we identified that children aged 12-35 months are the primary drivers of viral transmission to other age groups. This group significantly shapes the genetic diversity of circulating strains. Furthermore, we found that RSV is introduced into the community through frequent and independent entries from other US regions throughout the year, rather than through a single explosive seasonal introduction or long-term local persistence. Ultimately, our findings justify prevention strategies that expand beyond reducing disease burden to actively prioritizing the reduction of transmission and infection.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Lucas JK, Hebbar P, Liao WW, et al (2026)

HPRC2: A human pangenome reference with near-complete coverage of common genetic variation.

bioRxiv : the preprint server for biology.

A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortium's (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Alanazi EM, Alkhalid Y, Alqheedan A, et al (2026)

National trends in neonatal and under-five mortality in Saudi Arabia (2018-2023): a descriptive ecological analysis using WHO Global Health Observatory data.

Frontiers in public health, 14:1903279.

BACKGROUND: Neonatal mortality rate (NMR) and under-five mortality rate (U5MR) are core child-survival indicators and are influenced by, though not a direct measure of, the quality of maternal and newborn care. Saudi Arabia has achieved substantial reductions in both indicators over recent decades; however, year-to-year dynamics during the period of Vision 2030 health reforms remain incompletely described using standardized, internationally comparable data.

OBJECTIVE: To describe annual trends in NMR and U5MR in Saudi Arabia from 2018 to 2023 using WHO Global Health Observatory (WHO-GHO) national estimates, and to situate these descriptive trends within the broader regional and international literature on child mortality.

METHODS: A descriptive ecological analysis was conducted using all available national annual estimates (2018-2023; n = 6 per indicator) from WHO-GHO. Descriptive statistics and annual percentage change (APC) were calculated as the primary analytical approach. An unadjusted linear regression of rate on year is reported to characterize the direction and approximate magnitude of change over the period; because six annual observations provide very limited statistical power, regression p-values are reported for completeness only and are not used to support claims of trend presence or absence.

RESULTS: NMR declined from 3.6 to 3.0 per 1,000 live births between 2018 and 2023 (mean 3.27; range 3.0-3.6), a change concentrated mainly in 2020. U5MR fluctuated within a narrow band, falling from 6.1 in 2018 to 5.6 in 2021, rising to 6.4 in 2022, and partially returning to 6.2 in 2023 (mean 5.98; range 5.6-6.4). The unadjusted linear slopes were -0.12/year for NMR and +0.03/year for U5MR.

CONCLUSION: Between 2018 and 2023, Saudi Arabia's NMR and U5MR remained low and comparatively stable by international standards, with a gradual decline in NMR and a transient fluctuation in U5MR centered on 2022. These are descriptive, population-level patterns; the dataset does not include measures of healthcare quality, patient safety, or COVID-19 service disruption, and any interpretation connecting the observed trends to these factors should be regarded as a hypothesis for future research rather than a finding of this study. Future work linking subnational data, cause-specific mortality, and direct quality-of-care indicators to these trends is needed.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Boyes D, Boyes C, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2023)

The genome sequence of the Tufted Button, Acleris cristana (Denis & Schiffermüller, 1775).

Wellcome open research, 8:236.

We present a genome assembly from an individual female Acleris cristana (the Tufted Button; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence is 562.6 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled and is 16.1 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,598 protein coding genes.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Crowley LM, Sivell O, Mitchell R, et al (2026)

The genome sequence of the 16-spot Ladybird, Tytthaspis sedecimpunctata (Linnaeus, 1758) (Coleoptera: Coccinellidae).

Wellcome open research, 11:402.

We present a genome assembly from an individual male Tytthaspis sedecimpunctata (16-spot Ladybird; Arthropoda; Insecta; Coleoptera; Coccinellidae). The genome sequence has a total length of 355.68 megabases. Most of the assembly (88.7%) is scaffolded into 10 chromosomal pseudomolecules, including the X sex chromosome. The mitochondrial genome has also been assembled, with a length of 18.38 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.

RevDate: 2026-09-13
CmpDate: 2026-09-13

Kim HH, Kim SJ, Kim DK, et al (2026)

Daily Language as an Objective Indicator of Depressive Affective States: A Two-Week Ecological Momentary Assessment Study in Emotional Labor Workers.

Psychiatry investigation, 23(9):1096-1106.

OBJECTIVE: Workers performing emotional labor are at increased risk for depression, yet conventional self-report assessments often lack objectivity and temporal sensitivity. This study aimed to examine whether longitudinal analysis of daily natural language collected through ecological momentary assessment (EMA) can serve as an indicator of depressive affective states and to compare its temporal sensitivity with traditional self-report measures.

METHODS: A total of 400 call center employees completed three voice-recorded free-text entries per day for two weeks using an EMA application. Transcriptions were analyzed using a lexicon-based sentiment approach (Linguistic Inquiry and Word Count [LIWC]) and three large language models (LLMs; GPT-4o-mini, Qwen, and Mistral) under zero-shot prompting. Depressive symptoms were assessed using the Patient Health Questionnaire-9, and neuroticism was measured using both self-reported questionnaires and language-inferred scores.

RESULTS: LLM-derived sentiment scores significantly differentiated groups across levels of depressive symptom burden and consistently outperformed LIWC. Longitudinal analyses demonstrated clear group-level separation, particularly in morning entries, whereas self-reported mood ratings failed to distinguish groups and showed lower adherence over the two-week period. Language-inferred neuroticism exhibited stronger associations with depressive symptoms than self-reported neuroticism. A cumulative model based on morning sentiment scores showed progressively improved discrimination over time, reaching its highest performance on Day 10 (area under the curve=0.75).

CONCLUSION: Daily natural language captures meaningful longitudinal affective dynamics associated with depressive symptoms and may complement conventional self-report assessments as a low-burden and scalable indicator of depressive affective states in real-world occupational settings.

RevDate: 2026-09-11
CmpDate: 2026-09-11

Muresu R, Rodriguez M, A Squartini (2026)

GenBank mining reveals novel insights into Rhizobium phylogeny: Identical 16S rRNA sequences are mainly uncoupled from species designation, host plant, and geographic origin: How this search suggested the definition of a direct 'microbial h-index'.

PloS one, 21(9):e0357973 pii:PONE-D-26-01783.

16S rDNA is the historical gold standard for bacterial identification, particularly in metabarcoding approaches reliant on sequence similarity thresholds. We analyzed 6,660 Rhizobium 16S rRNA gene sequences from GenBank to examine the relationship between sequence identity and three metadata: species name, host plant, and geographic origin. Using an iterative BLAST-based pipeline, we detected 116,069 pairwise matches and assessed concordance among sequences (average length 1,328 bp) sharing 100% identity. For those in which the organism name, host plant and country of isolation were present in the record, surprisingly, 66.59% of identical sequence pairs showed full discordance across all three metadata, while only 1.40% shared the same name, host, and country. The most widespread sequence, detected 371 times, was associated with over 56 different host plants across 25 countries and bore multiple species name designations. These results highlight a striking mismatch between the 16S barcode and the taxonomic, ecological, and phenotypic variability it is assumed to reflect, likely arising from the slow evolution of rRNA genes contrasted with the mobility of ecologically relevant genes via horizontal transfer on plasmids, transposons, and phages. Our findings further challenge the limitations of relying on 16S rRNA alone for fine-scale taxonomic and metadata-based inference in capturing the true functional and ecological diversity of bacteria, endorsing the critical importance of polyphasic taxonomic approaches that integrate genomic, phenotypic, and ecological data. An interesting byproduct of the analysis was to realize the possibility of treating these data as if they were 'citations.' The more one finds the same query sequence, the more that sequence can be considered biologically 'cited', i.e., re-proposed elsewhere in the world. Thus, one can also analyze the h-index of such a ranking. In our Rhizobium dataset, we calculated an h-index = 201, meaning the sequence ranked 201st had 202 identical homologues in GenBank. Although the research effort on given species is directly connected with it, this number provides a quantitative indicator of a taxon's sequence recurrence and distribution within public databases, independent of nomenclatural inconsistencies, offering a novel framework for assessing bacterial representation across global datasets.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Susanna D, Saputra YA, S Poddar (2023)

The effect of wind speed in increasing COVID-19 cases in Jakarta: a spatial-temporal analysis from March to September 2020.

F1000Research, 12:145.

BACKGROUND: The SARS-CoV-2 virus that causes COVID-19 is described as a highly contagious virus, and wind speed is suspected to be one of the climate elements that play a role in its spread, among others. This study aims to determine the relationship between wind speed and the increase in COVID-19 cases, as well as its potential spread, based on regional characteristics.

METHODS: The design of this study was an ecological study based on time and place to integrate geographic information systems and tested using statistical techniques. The data used were wind speed and weekly COVID-19 cases from March to September 2020. These records were obtained from the special coronavirus website of Jakarta Provincial Health Office and the Indonesian Meteorology, Climatology and Geophysics Agency. The data were analyzed by correlation, graphic/time trend, and spatial analysis.

RESULTS: The wind speed (maximum and mean) from March to September 2020 tended to fluctuate between 1.43 and 6.07 m/s. The correlation test results between the average wind speed and COVID-19 cases in Jakarta showed a strong positive correlation (r = 0.542; p value = 0.002).

CONCLUSIONS: Areas with high wind speeds tended to show an increase in the number of COVID-19 cases, especially in the coastal areas of Jakarta. Wind speed plays a role in increasing the spread of SARS-CoV-2, in people who did not implement health protocols properly. This mechanism can be worsened with support of environmental factors such as air pollution.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Falk S, Crowley LM, Grzywacz A, et al (2026)

The genome sequence of the muscid fly, Hydrotaea similis Meade, 1887 (Diptera: Muscidae).

Wellcome open research, 11:399.

We present a genome assembly from an individual female Hydrotaea similis (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 884.66 megabases and 852.78 megabases. Most of haplotype 1 (90.83%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 20.27 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Boyes D, Hutchinson F, Crowley LM, et al (2026)

The genome sequence of the Holly Tortrix, Rhopobota naevana (Hubner, 1817) (Lepidoptera: Tortricidae).

Wellcome open research, 11:400.

We present a genome assembly from an individual male Rhopobota naevana (Holly Tortrix; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence has a total length of 581.80 megabases. Most of the assembly (99.48%) is scaffolded into 28 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled, with a length of 16.5 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Avelino C, Karp R, Baker A, et al (2026)

The chromosomal genome sequence of the lesser starlet coral, Siderastrea radians (Pallas, 1766) (Scleractinia: Rhizangiidae) and its associated microbial metagenome sequences.

Wellcome open research, 11:493.

We present a genome assembly from a specimen of Siderastrea radians (lesser starlet coral; Cnidaria; Anthozoa; Scleractinia; Rhizangiidae). The genome sequence has a total length of 807.19 megabases. Most of the assembly (94.17%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 19.38 kilobases. Gene annotation of this assembly by Ensembl identified 47 051 protein-coding genes. From the metagenome data, we recovered two binned metagenomes assigned to the bacterial phylum Bacteroidota and class Bacteroidia.

RevDate: 2026-09-12
CmpDate: 2026-09-12

Stewart JM, Medina M, Bruckner A, et al (2026)

The chromosomal genome sequence of the maze coral, Meandrina meandrites (Linnaeus, 1758) (Scleractinia: Meandrinidae) and its associated microbial metagenome sequences.

Wellcome open research, 11:469.

We present a genome assembly from a specimen of Meandrina meandrites (maze coral; Cnidaria; Anthozoa; Scleractinia; Meandrinidae). The genome sequence has a total length of 551.16 megabases. Most of the assembly (99.25%) is scaffolded into 14 chromosomal pseudomolecules. The mitochondrial genome has also been assembled, with a length of 17.2 kilobases. Gene annotation of this assembly by Ensembl identified 30 464 protein-coding genes. We recovered two bins from the metagenome data.

RevDate: 2026-09-10
CmpDate: 2026-09-10

Warner S, Stucky CH, Haegerich T, et al (2026)

The Cognitive Transaction: Toward a Human Factors Research Agenda for AI in Anesthesia and Perioperative Care.

JMIR human factors, 13:e102683 pii:v13i1e102683.

AI is now embedded in the infrastructure of perioperative care. Risk stratification algorithms, hemodynamic prediction tools, and clinical decision support systems are active in operating rooms at major health systems, and their adoption is accelerating. However, the field has studied model performance and organizational implementation while largely bypassing the moment between them: the real-time encounter in which an anesthesia provider must decide, under active case conditions, what to do with an AI-generated output. We term this the cognitive transaction and argue that it is the fundamental unit of perioperative AI implementation. The perioperative environment presents a specific constellation of conditions that existing human-AI interaction research was not designed to address. Continuous real-time decision demands, extreme time compression, high cognitive load, and consequences that unfold in seconds distinguish the operating room from the clinical contexts where most provider-AI interaction research has been conducted. What we know about AI adoption in radiology, oncology, or ambulatory care does not readily translate to this setting. The cognitive moment in anesthesia has its own structure, its own failure modes, and its own research requirements. This paper examines what those requirements are. We analyze how the operating room functions as a pre-existing human-machine cognitive system into which AI is now being inserted, and why the conditions of that system generate predictable vulnerabilities: miscalibrated trust, automation bias, and cognitive friction produced by interfaces optimized for technical accuracy rather than clinical usability. We argue that these failure modes are not incidental but structural and that they will persist regardless of model performance until the provider-AI interaction is itself treated as a research object. We identify 4 priority research domains. The first concerns the structure of provider-AI disagreement and the methods needed to distinguish automation bias from legitimate clinical insight. The second concerns the longitudinal dynamics of trust calibration across repeated clinical encounters rather than single-session experimental designs. The third concerns interface design for high-acuity workflows, specifically what constitutes a usable AI output for a provider managing a patient in real time. The fourth concerns the need for ecologically valid study designs capable of capturing provider reasoning under actual perioperative conditions rather than retrospective or survey-based proxies. The anesthesia and perioperative research community is positioned to lead this work. The clinical specificity, domain knowledge, and professional stake required to design meaningful studies are all present within the field. Evaluating the cognitive transaction under perioperative conditions, not the computational model in isolation, is both a methodological imperative and a patient safety priority.

RevDate: 2026-09-11
CmpDate: 2026-09-11

Crowley LM, Falk S, Hutchinson F, et al (2026)

The genome sequence of a muscid fly, Lispocephala verna (Fabricius, 1794) (Diptera: Muscidae).

Wellcome open research, 11:394.

We present a genome assembly from an individual female Lispocephala verna (muscid fly; Arthropoda; Insecta; Diptera; Muscidae). The assembly contains two haplotypes with total lengths of 987.71 megabases and 934.62 megabases. Most of haplotype 1 (95.8%) is scaffolded into 5 chromosomal pseudomolecules. Haplotype 2 was assembled to scaffold level. The mitochondrial genome has also been assembled, with a length of 16.34 kilobases. This assembly was generated as part of the Darwin Tree of Life project, which produces genomes for eukaryotic species found in Britain and Ireland.

RevDate: 2026-09-10
CmpDate: 2026-09-10

Detroja R, M Chandra (2026)

Integrated molecular, epidemiological, and bioinformatics perspectives on the Mpox virus: Implications for surveillance and Global Health preparedness.

Journal of microbiological methods, 249:107656.

Mpox has re-emerged as a significant global zoonotic threat, driven mainly by two large waves the 2022 worldwide Clade IIb outbreak and the 2024 Clade Ib epidemic in Central Africa. This review examines the challenges of interpreting this evolving virus from molecular, epidemiological, and bioinformatics perspectives, with a focus on global health workforce preparedness. Clade IIb largely moved through sexual transmission across countries, but Clade Ib has appeared in a wider population-women, children, and individuals infected through household spread without any sexual contact. Early case series suggest that Clade Ib may cause a more severe disease burden, but more research is needed to directly compare severity and fatality rates with Clade IIb due to the limited number of current studies. The review examines the virus's strategies for evading the host's immune defenses throughout its ∼197 kbp genome, including how it disrupts interferon signaling and creates decoy receptors. This review summarizes the clinical findings of PALM007 and STOMP, noting that neither trial achieved its main efficacy endpoint making routine tecovirimat use less compelling-while leaving open whether it helps particular high-risk groups. A further point is that immunity from the MVA-BN vaccine wanes with time, leading to the growing adoption of booster vaccinations. In conclusion, the review calls for a One Health approach pairing genomic tracking with ecological intelligence and including wastewater surveillance to fill existing gaps in knowledge and enhance the global handling of new orthopoxvirus threats.

RevDate: 2026-09-10
CmpDate: 2026-09-10

Vetter D, Ahsan M, Delicado D, et al (2026)

Speeding up taxonomy in the digital age: A deep learning approach for identifying cryptic freshwater snails.

PLoS computational biology, 22(9):e1014733.

Cryptic species complexes pose fundamental challenges to biologists, as species exhibit minimal morphological differences that require integrating morphology, genetics, and biogeography for identification. Here, we present a deep learning approach to support species identification in the freshwater snail genus Radomaniola (Hydrobiidae), a morphologically cryptic group from the Balkans. Our approach mirrors the integrative workflow of expert taxonomists by combining shell images, morphometric measurements, and collection‑site metadata, with optional phylogenetic information. Despite being trained on fewer than 700 specimens across 20 visually similar species with strongly imbalanced class sizes, the system achieved high identification performance. Careful control of spurious correlations, such as those arising from site‑specific imaging conditions or overly precise geographic metadata, was essential to ensure that the network learned biologically meaningful features. Across all experiments, integrating multiple data types and jointly optimizing meaningful embeddings and classification consistently improved performance over image‑only and classification‑only baselines. On specimens from collection sites seen during training we achieved a macro-averaged F1 score of 0.93. Even though this dropped as low as 0.14 when evaluating on specimens from previously unsampled localities, it could be rapidly recovered by retraining with 2-3 newly labeled specimens. Additionally, model top-3 accuracy stayed consistently above 80% in all settings. These results show that relatively lightweight deep learning models can provide practical decision support in real taxonomic workflows.

RevDate: 2026-09-08
CmpDate: 2026-09-08

Ribeiro IM, Almeida-Santos AC, Peixe L, et al (2026)

A One Health approach to Antimicrobial Resistance: Concepts, challenges, and advances in omics.

Advances in applied microbiology, 134:1-101.

Antimicrobial resistance (AMR) is a global threat driven by the interplay between microbial evolution and human activity. Antimicrobial use in human and veterinary medicine, as well as in agriculture, accelerates the selection and dissemination of resistant bacteria and genes across interconnected human, animal, and environmental reservoirs. These dynamic exchanges render single-sector interventions ineffective. A One Health approach integrating human, animal, and environmental health is therefore essential to understand and mitigate the emergence and spread of AMR. This chapter focuses on bacterial antimicrobial resistance, addressing key concepts, major challenges, and emerging technologies within a One Health framework. Advances in next-generation sequencing and omics technologies have transformed our capacity to resolve AMR at unprecedented scale and resolution. These tools enable the tracking of resistance genes and high-risk clones across ecosystems, uncover transmission pathways, and identify key drivers of dissemination. Such insights support real-time epidemiological surveillance, outbreak detection, and targeted interventions. However, translating these advances into routine practice remains a major challenge, requiring harmonized methodologies, data integration, and cross-sector coordination. Addressing AMR demands sustained collaboration across disciplines and stakeholders, including clinicians, veterinarians, farmers, researchers, policymakers, industry, and the public. And framing AMR as a shared ecological and societal responsibility underscores the urgency of coordinated global action. We call for the urgent integration of One Health principles into surveillance, policy, and innovation to preserve antimicrobial effectiveness and safeguard future health.

RevDate: 2026-09-10

Caravagna G, Graham TA, A Sottoriva (2026)

A guide to understanding tumour evolution through the lens of population genetics.

Nature reviews. Cancer [Epub ahead of print].

Every cancer carries the history of its own evolution, hidden in its genome. Modern DNA sequencing can catalogue millions of mutations and profile tumours across space and time, but sequencing alone struggles to answer the questions that matter most: when did key adaptations emerge, how strongly were they selected, why do some tumours relapse whereas others do not, and how will the cancer evolve next? The reason is fundamental: sequencing is a snapshot, whereas evolution is a dynamic process. Bridging this gap requires moving beyond descriptive cancer genomics towards quantitative evolutionary inference. In this Review, we argue that population genetics provides the mathematical framework needed to extract evolutionary dynamics from cancer genomes. We show how models of mutation, selection and drift transform allele frequencies from descriptive measurements into quantitative estimates of clonal fitness and evolutionary timings. We discuss how these principles extend to epigenetic inheritance, plasticity and ecological interactions within the tumour ecosystem, and examine the assumptions and limitations for their application to modern sequencing data. By reframing cancer genomes as quantitative records of evolutionary processes rather than catalogues of mutations, researchers have used population genetics to provide a foundation for understanding - and ultimately predicting - the trajectories of cancer evolution.

RevDate: 2026-09-10
CmpDate: 2026-09-10

Tenennbaum B, Yakubovich E, Wang YW, et al (2026)

Conserved storage-carbohydrate metabolic modules are rewired during germination of Trichoderma asperelloides and other Sordariomycetes.

Frontiers in fungal biology, 7:1930613.

Conidial germination requires rapid mobilization and reorganization of storage carbohydrates, yet the network architecture underlying this process remains poorly defined in filamentous fungi. Using quantitative GC-MS/MS profiling, we provide the first quantitative identification of major soluble sugar species across four germination stages of Trichoderma asperelloides T203 and compared them with four representative models in the Sordariomycetes (Metarhizium anisopliae, Cordyceps militaris, Fusarium graminearum, and Neurospora crassa). In T. asperelloides, mannitol was the most prevalent measured sugar in dormant conidia, declined sharply at polarity establishment, and partially recovered at later stages, while trehalose displayed a reciprocal increase and other sugars remained comparatively stable. Comparative analyses revealed distinct species-specific carbon storage strategies: Dormant conidia of T. asperelloides, M. anisopliae, and C. militaris were mannitol-enriched, whereas in N. crassa and F. graminearum glucose was the most abundant; after germination onset, most species shifted toward glucose accumulation, but T. asperelloides uniquely transitioned from mannitol to trehalose dominance before partial re-accumulation of mannitol. Integration of sugar profiles with time-resolved RNA-seq and Bayesian network inference revealed conserved core interactions but also lineage-specific divergences in mannitol/trehalose-associated central-carbon modules that correspond to distinct nutrient and lifestyle strategies during early colonization. A focused analysis in T. asperelloides uncovered extensive stage-dependent transcriptional remodeling of metabolic-process genes and a mannitol-centered module involving mpd1 and mtd1 (encoding mannitol-1-phosphate 5-dehydrogenase and mannitol dehydrogenase, respectively). Antisense-based knockdown of mpd1 strongly reduced its transcript levels and led to stage-dependent upregulation of mtd1. However, these changes left mannitol content, soluble-sugar profiles, germination dynamics, and growth on mannitol essentially unchanged. Together, our comparative metabolic-network analysis shows that conidial mannitol and trehalose metabolism in T. asperelloides is embedded in a flexible, partially redundant central-carbon framework, and establishes this species as a tractable model for systems-level dissection of sugar metabolic regulation during early fungal development and colonization.

RevDate: 2026-09-10

Ramirez MR, Gomez NJS, Ryan A, et al (2026)

Multi-mode design for studying cyber aggression in texts, Facebook and Twitter messages among middle school youth.

American journal of epidemiology pii:8789971 [Epub ahead of print].

With the explosion of the internet, cyber aggression has become one of the fastest growing forms of interpersonal violence. Methods used to understand aggressive communications content have been limited primarily to surveys. Here, we present multiple methods - panel surveys, electronic capture of social media, and Ecological Momentary Assessments - to characterize both behavioral and perceptual components of cyber aggression in a study of youth from two Iowa middle schools during the 2014-2015 school year. Youth completed a survey, and a sub-sample of smartphone owners installed an electronic application that collected over 150,000 text messages, Twitter posts, and Facebook posts. The sub-sample also participated in ecological momentary assessments to collect self-reported experiences of cyber aggression. To code for aggressive content in this large sample of messages, a case-control sampling strategy was used to identify a series of "case" messages from youth who reported aggression and "control" messages from youth who reported no aggression. We further present recruitment protocols, data management and qualitative coding methods as well as descriptive characteristics of the student cohort and nested sample of messages. These methods have potential use in future studies of "big data" captured from social media.

RevDate: 2026-09-09
CmpDate: 2026-09-09

Yang X, Ji XH, Li C, et al (2026)

A synthetic microbiome drives a multi-omics response to remediate 1,4-dithiane-contaminated soil and simultaneously suppresses antibiotic resistance genes.

Journal of hazardous materials, 516:143337.

1,4-Dithiane, a degradation product of abandoned Japanese chemical weapons, is a persistent organic pollutant with ecological risks. A synthetic microbiome (SM) was constructed through pollution stress screening and ratio optimization, consisting of Shinella sp., Alcaligenes faecalis, Sphingomonas sp., and Stenotrophomonas sp. at an optimal ratio of 1: 1: 2: 2. The SM achieved a 1,4-dithiane degradation rate of 95.2% and reduced intermediate accumulation. Soil remediation experiments showed complete pollutant removal within 60 days, along with improved soil health: reduced bioavailability of heavy metals (Cu, Zn, Cd), increased pH (6.47-6.95), elevated organic matter and enzyme activities, and decreased salinity and redox potential. Integration of ionomics, 16S sequencing, metagenomics, metabolomics, and HT-qPCR revealed that SM colonization reshaped microbial community structure, suppressed ARG-harboring bacteria (e.g., Pseudomonas), and activated core pathways (oxidative phosphorylation and glutathione metabolism), enhancing metabolic activity and oxidative stress tolerance. Consequently, the diversity, abundance, and diffusion potential of soil ARGs and mobile genetic elements were significantly reduced. These findings provide microbial solutions and a theoretical basis for concurrent organic pollution control and soil ecological risk management.

RevDate: 2026-09-08
CmpDate: 2026-09-08

Vasileiadis S, Valmas MI, Pitsikoglou DS, et al (2026)

Up-to-date, and taxonomy-curated mcrA reference databases for methanogen community profiling.

Systematic and applied microbiology, 49(5):126752.

The methyl-coenzyme M reductase subunit alpha gene (mcrA) is an important phylogenetic marker for high throughput ecological profiling of methanogenic archaea, central to industrial biological methane production and greenhouse gas emissions. Yet, dedicated reference databases predate current relevant NCBI sequence accumulation and archaeal taxonomic revision. We present three updated mcrA reference databases: (i) one derived from NCBI-catalogued methanogen genomes (1572 sequences); (ii) a database built by expansion of a previously published reference dataset, leveraging the NCBI nucleotide collection (27,942 sequences); (iii) a curated-taxonomy version of the latter. The updated amplicon databases provide a ∼ 3.5-fold sequence richness expansion, extend genus-level richness from 31 to 83 taxa, more than 4-fold species-level richness, and incorporate novel lineages compared with the previous reference dataset (e.g. Thermoplasmatota-encompassed). All databases were formatted to support analysis with relevant contemporary software pipelines and packages. Overall, the generated databases facilitate a highly improved characterization of methanogen diversity and ecology.

RevDate: 2026-09-08
CmpDate: 2026-09-08

Lilja E, Allen RJ, B Waclaw (2026)

Simple birth-death-mutation models predict some-but not all-aspects of the experimental evolution of antibiotic resistance.

PLoS computational biology, 22(8):e1014666 pii:PCOMPBIOL-D-25-02099.

Mathematical modelling of antibiotic resistance plays an important role in understanding the mechanisms of resistance emergence and spreading, testing the feasibility of new treatment protocols, and antimicrobial stewardship. However, many assumptions underlying some of the most commonly used mathematical models have not been rigorously tested experimentally. We verify whether one of these models - a birth-death-mutation process - is able to quantitatively predict the outcome of laboratory experiments. We grow bacteria in a bioreactor in conditions that closely resemble the assumptions of the model, and compare the model predictions with experimental observables such as the probability and time to resistance evolution, mutant number distribution, and the genetic composition of the evolved populations. We show that the model fails to reproduce some aspects of the experiments (failing differently for different antibiotics) but that simple modifications of the model significantly improve its predictive power. These modifications give insight into the population dynamics of resistant mutants for each antibiotic tested, and highlight the importance of quantitative modelling for accurate prediction of antibiotic resistance evolution.

RevDate: 2026-09-07
CmpDate: 2026-09-07

Shi H, Shen Y, Ye Q, et al (2026)

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Food research international (Ottawa, Ont.), 243(Pt 2):120404.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

RevDate: 2026-09-08
CmpDate: 2026-09-08

Pieroni A, Hazarika A, Alrhmoun M, et al (2026)

From the margins to the core: village and community scientists should increasingly shape the future of ethnobiology and ethnoecology.

Journal of ethnobiology and ethnomedicine, 22(1):.

Ethnobiology was not only created as a field to understand the relationship between humans and their environments; it emerged from direct engagement with rural and Indigenous communities. Yet the great paradox is that, despite its field-based origins, the discipline continues to be reproduced within urban academic spaces that often exclude those who are assumed to be at the very heart of knowledge production. In this editorial, we do not simply propose the "inclusion" of rural or Indigenous communities. Instead, we call for a radical repositioning of the knowledge itself: Who can be considered a "scientist"? And who holds the authority to define scientific knowledge? We reject the assumption that urban academic affiliation or formal credentials are the sole basis for scientific credibility, and instead propose a different standard: knowledge should be assessed by its depth, explanatory power, and integrity when co-produced in genuine partnership with living communities. Drawing on our own experiences as researchers raised in rural villages, peripheral regions, and migrant/refugees' communities, we argue that local and Indigenous ecological knowledge is not a "raw material" for scientific research, but a form of scientific thinking in its own right with its own logic, observations, and rigour, and its own way of assessing, adapting and enacting this knowledge. We therefore call for a further step ahead in the classical structure of ethnobiology: not merely the inclusion of communities in research stages, but the recognition of some of their scholars as the core producers of scientific knowledge, from the formulation of research questions to the interpretation, dissemination and enactment of results. This transformation of the locus aims not only to improve ethnobiology as a field but also to redefine it. Without this redefinition, science will remain detached from the realities it claims to understand. With it, ethnobiology can become a more honest, more courageous discipline, better equipped to confront biodiversity loss, climate change, and the reconfiguration of more-than-human-nature relationships.

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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.

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This book introduces readers to ecological informatics as an emerging discipline that takes into account the data-intensive nature of ecology, the valuable information to be found in ecological data, and the need to communicate results and inform decisions, including those related to research, conservation and resource management. At its core, ecological informatics combines developments in information technology and ecological theory with applications that facilitate ecological research and the dissemination of results to scientists and the public. Its conceptual framework links ecological entities (genomes, organisms, populations, communities, ecosystems, landscapes) with data management, analysis and synthesis, and communicates new findings to inform decisions by following the course of a loop. In comparison to the 2nd edition published in 2006, the 3rd edition of Ecological Informatics reflects the significant advances in data management, analysis and synthesis that have been made over the past 10 years, including new remote and in situ sensing techniques, the emergence of ecological and environmental observatories, novel evolutionary computations for knowledge discovery and forecasting, and new approaches to communicating results and informing decisions.

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Collection of publications by R J Robbins

Reprints and preprints of publications, slide presentations, instructional materials, and data compilations written or prepared by Robert Robbins. Most papers deal with computational biology, genome informatics, using information technology to support biomedical research, and related matters.

Research Gate page for R J Robbins

ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. According to a study by Nature and an article in Times Higher Education , it is the largest academic social network in terms of active users.

Curriculum Vitae for R J Robbins

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Curriculum Vitae for R J Robbins

long standard version

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