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Bibliography on: Ecological Informatics

RJR-3x

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 12 Sep 2025 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: 2025-09-11

Tejada-Llacsa PJ, Alarcón GS, MF Ugarte-Gil (2025)

Prevalence of systemic lupus erythematosus in Peru and its association with environmental and healthcare factors: An ecological study.

Lupus [Epub ahead of print].

ObjectiveTo estimate the prevalence of Systemic Lupus Erythematosus (SLE) in Peru in 2017 and its association with altitude, environmental temperature, and physician density.MethodsThis ecological study was performed using population data from the 2017 Peruvian census. The number of SLE cases for each department was obtained from the National Health Registries using the ICD-10 code M32. Altitude, environmental temperature and physician density were obtained for each department from the National Institute of Statistics and Informatic (Instituto Nacional de Estadística e Informática) registries. The prevalence for each department was calculated adjusting for age and sex. Then a negative binomial regression was performed to estimate the prevalence ratio (PR) and evaluate factors associated with the prevalence of SLE.ResultsThe national prevalence of SLE was 40.2 per 100,000 people. Two age groups had the highest prevalence: 12-17 years and 30-59 years. Females exhibited a higher prevalence than males, particularly in the 30-59 age group (113.9 vs 16.1 per 100,000, respectively). An inverse relationship was observed between the age- and sex-adjusted prevalence in each department and altitude (PR 0.97; 95% CI: 0.94-0.99). On the other hand, there was a direct relationship with physician density (PR: 1.04; 95% CI: 1.01-1.07). No association was found between the adjusted prevalence and environmental temperature or latitude.ConclusionThe prevalence of SLE in Peru aligns with global estimates. The inverse relationship with altitude and the direct association with physician density suggest that environmental and healthcare access factors may influence disease distribution. Further research is needed to explore the underlying mechanisms driving these associations.

RevDate: 2025-09-11
CmpDate: 2025-09-11

Matsumoto Y, Okada G, M Ohta (2025)

Can Augmented Reality be Used as a Portion Size Estimation Aid Tool? A Pilot Randomized Controlled Trial.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association, 38(5):e70125.

BACKGROUND: Evidence on the effectiveness of augmented reality (AR)-based tools for portion size estimation as an educational aid remains limited. In this pilot study, we developed a 3D food model using AR and assessed the feasibility of using this application to teach portion size estimation skills.

METHODS: This intervention study involved 43 students (including 38 females) from two dietetic education institutions. Participants were randomly assigned into four groups: (1) text only, (2) text and pictures, (3) food model and (4) AR. Learning effectiveness was evaluated using a pretest of 10 different foods, followed by a 10-min instructional session with the assigned tool, and then a post-test. Participants rated each learning tool for enjoyment, usefulness and recommendation to others on an 11-point Likert scale. Outcomes included the change in the number of correct answers within ± 10% or ± 20% of the true food weight.

RESULTS: Mean acceptability ratings for the text only, text and picture, food model and AR groups were enjoyment (4.1, 5.6, 7.0 and 7.9), usefulness (5.5, 7.4, 8.4 and 8.3) and recommendation to others (3.6, 6.3, 6.3 and 7.1), respectively. The mean changes in correct answers for text only, text and picture, food model and AR groups were 0.7, -1.1, 1.5 and 0.1, respectively, within a 10% error margin, and 1.2, -1.9, 2.0 and 0.8, respectively, within a 20% error margin.

CONCLUSIONS: This pilot study suggests that AR-based tools have potential as educational aids for portion size estimation among future dietitians, with acceptability ratings comparable to conventional methods, such as text only, text and pictures, and food models.

TRIAL REGISTRATION: The study was registered with the University Hospital Medical Information Network; UMIN000054307.

RevDate: 2025-09-10
CmpDate: 2025-09-11

Ye G, Hong H, Li T, et al (2025)

MAGdb: a comprehensive high quality MAGs repository for exploring microbial metagenome-assemble genomes.

Genome biology, 26(1):276.

Metagenomic analyses of microbial communities have unveiled a substantial level of interspecies and intraspecies genetic diversity by reconstructing metagenome-assembled genomes (MAGs). The MAG database (MAGdb) boasts an impressive collection of 74 representative research papers, spanning clinical, environmental, and animal categories and comprising 13,702 paired-end run accessions of metagenomic sequencing and 99,672 high quality MAGs with manually curated metadata. MAGdb provides a user-friendly interface that users can browse, search, and download MAGs and their corresponding metadata information. It represents a valuable resource for researchers in discovering potential novel microbial lineages and understanding their ecological roles. MAGdb is publicly available at https://magdb.nanhulab.ac.cn/ .

RevDate: 2025-09-10

Slack SD, Esquinca E, Arehart CH, et al (2025)

Prediction and Characterization of Genetically-Regulated Expression of Asthma Tissues from African-Ancestry Populations.

The Journal of allergy and clinical immunology pii:S0091-6749(25)00938-8 [Epub ahead of print].

BACKGROUND: Genetic control of gene expression in asthma-related tissues is not well-characterized, particularly for African-ancestry populations, limiting advancement in our understanding of the increased prevalence and severity of asthma in those populations.

OBJECTIVE: To create novel transcriptome prediction models for asthma tissues (nasal epithelium and CD4+ T cells) and apply them in transcriptome-wide association study to discover candidate asthma genes.

METHODS: We developed and validated gene expression prediction databases for unstimulated CD4+ T cells and nasal epithelium using an elastic net framework. Combining these with existing prediction databases (N=51), we performed TWAS of 9,284 individuals of African-ancestry to identify tissue-specific and cross-tissue candidate genes for asthma.

RESULTS: Novel databases for CD4+ T cells and nasal epithelial gene expression prediction contain 8,351 and 10,296 genes, respectively, including four asthma loci (SCGB1A1, MUC5AC, ZNF366, LTC4S) not predictable with existing public databases. Prediction performance was comparable to existing databases and was most accurate for populations sharing ancestry with the training set (e.g. African ancestry). From transcriptome-wide association study, we identified 17 candidate causal asthma genes (adjusted P<0.1), including genes with tissue-specific (IL33 in nasal epithelium) and cross-tissue (CCNC and FBXW7) effects.

CONCLUSIONS: Expression of IL33, CCNC, and FBXW7 may affect asthma risk in African ancestry populations by mediating inflammatory responses. The addition of CD4+ T cell and nasal epithelium prediction databases to the public sphere will improve ancestry representation and power to detect novel gene-trait associations from transcriptome-wide association study.

RevDate: 2025-09-10
CmpDate: 2025-09-10

Lawler T, Kwekkeboom K, Warren Andersen S, et al (2025)

Self-efficacy for cancer self-management in the context of COVID-19: a cross-sectional survey study.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer, 33(10):843.

PURPOSE: For cancer survivors, self-efficacy is needed to manage the disease and the effects of treatment. The COVID-19 pandemic disrupted cancer-related healthcare, which may have impacted self-management self-efficacy. We investigated self-efficacy reported by cancer survivors during COVID-19, including associations with healthcare disruptions, distress, and general health.

METHODS: Between 2020 and 2021, 1902 individuals aged 18-80 years with a recent cancer diagnosis completed a survey regarding the effects of COVID-19 on healthcare, self-efficacy for managing cancer and social interactions, cancer-related distress, and perceived general health. Linear and logistic models estimated odds ratios and 95% confidence intervals (CIs) between self-efficacy scores, healthcare disruptions, significant distress, and general health.

RESULTS: Mean self-efficacy for managing cancer was 7.58 out of 10. Greater self-efficacy was associated with lower odds for distress (OR 0.18 [95% CI 0.13-0.26], quartile 4 vs. 1) and for worse general health (0.05 [0.03-0.09]). Participants with disruptions to cancer-related healthcare had lower self-efficacy for managing cancer compared to those without (6.62 vs. 7.09, respectively, P < 0.001) and higher odds for distress (1.70 [1.36-2.14]), but not worse general health (1.13 [0.39-1.44]). Lower self-efficacy mediated 27% of the association between healthcare disruptions and increased distress (15-47%). Associations with self-efficacy for managing social interactions trended in the same direction.

CONCLUSIONS: During COVID-19, disruptions to cancer-related healthcare were associated with lower self-efficacy, increased distress, and worse general health. Psychosocial interventions designed to overcome barriers and target self-efficacy may be important for enhancing outcomes among cancer survivors experiencing disruptions in healthcare access.

RevDate: 2025-09-10

Blackman Carr LT, Ard J, Shanks CB, et al (2025)

Toward Health Equity: A Workshop Report on the State of the Science of Obesity Interventions for Adults.

Obesity (Silver Spring, Md.) [Epub ahead of print].

OBJECTIVE: From October 18-20, 2022, the National Institutes of Health held a workshop to examine the state of the science concerning obesity interventions in adults to promote health equity. The workshop had three objectives: (1) Convene experts from key institutions and the community to identify gaps in knowledge and opportunities to address obesity, (2) generate recommendations for obesity prevention and treatment to achieve health equity, and (3) identify challenges and needs to address obesity prevalence and disparities, and develop a diverse workforce.

METHODS: A three-day virtual convening.

RESULTS: Several key themes emerged from the workshop discussions that describe directions to build on the currently limited amount of research on obesity, disparities, and equity. Key themes centered on the determinants of health, leveraging technology, clinical, community, commercial, and policy approaches. Community-engaged work, particularly in populations that have received little focus (e.g., sexual gender minorities, Asian communities), were also discussed.

CONCLUSIONS: Future research may be impactful when multilevel approaches are undertaken that leverage equity-minded tools and can be scaled up to meet community-informed population needs in a variety of settings. Funding priorities and workforce development will be critical to realizing health equity.

RevDate: 2025-09-10

Achury R, Staab M, Seibold S, et al (2025)

Habitat and land-use intensity shape moth community structure across temperate forest and grassland.

The Journal of animal ecology [Epub ahead of print].

Land-use change and intensification are major drivers of biodiversity loss, yet their effects on diversity have usually been studied within a single habitat type or land-use category, limiting our understanding of cross-habitat patterns. Moths, a species-rich taxon worldwide, represent a significant portion of the biodiversity in both temperate forests and grasslands, functioning as pollinators and herbivores. While increasing land-use intensity (LUI) in both habitats is expected to negatively impact moth assemblages, the strength of this effect remains uncertain. Moreover, land-use intensification interacts with broader environmental factors, such as weather conditions and the spread of artificial light at night (ALAN), but their combined effects on moth community diversity and turnover across habitats remain poorly understood. We sampled moth communities across 150 grassland and 150 forest plots along land-use gradients in Germany. We quantified plot- and landscape-scale LUI and tested the role of plant diversity, temperature and precipitation during the night of sampling and the preceding season, and ALAN in shaping moth diversity (standardized by coverage) along Hill numbers. Forests supported significantly higher moth abundance, biomass and diversity than grasslands, with habitat type being the main driver of moth community composition. LUI at the plot scale had contrasting effects on moth abundance, increasing it in forests but reducing it in grasslands. Impacts of LUI were more pronounced at the landscape level, reducing moth diversity particularly in areas dominated by grasslands. Plant diversity and temperature were key determinants for moth communities, increasing alpha diversity across diversity metrics, that is Hill numbers. ALAN had no significant influence on moth abundance or biomass but significantly decreased Simpson diversity. Beta diversity increased with geographic distance, habitat change and LUI but decreased with weather differences among plots. Our results highlight the interplay between LUI, habitat type and abiotic factors in shaping moth communities across large spatial scales. Effective conservation strategies should consider maintaining habitat heterogeneity and promoting plant diversity, particularly in temperate habitats exposed to high land-use intensification.

RevDate: 2025-09-08

Wang F, Xue M, Zhou L, et al (2025)

Contrasting age-dependent leaf acclimation strategies drive vegetation greening across deciduous broadleaf forests in mid- to high latitudes.

Nature plants [Epub ahead of print].

Increasing leaf area and extending vegetation growing seasons are two primary drivers of global greening, which has emerged as one of the most significant responses to climate change. However, it remains unclear how these two leaf acclimation strategies would vary across forests at a large spatial scale. Here, using multiple satellite-based datasets and field measurements, we analysed the temporal changes (Δ) in maximal leaf area index (LAImax) and length of the growing season (LOS) from 2002 to 2021 across deciduous broadleaf forests (DBFs) in the middle to high latitudes. Contrary to the widely held assumption of coordination, our results revealed a negative correlation between ΔLAImax and ΔLOS. Notably, the trade-offs between ΔLAImax and ΔLOS were strongly explained by stand age. Younger DBFs, with lower baseline LAImax, predominantly located in eastern Asia, displayed an increase in LAImax with small changes in LOS. This acquisitive strategy facilitated younger DBFs to grow more photosynthetically efficient leaves with low leaf mass per area, enhancing their light use efficiency. Conversely, older DBFs with a higher baseline LAImax, primarily located in North America and Europe, extended their LOS by increasing leaf mass per area. This conservative strategy facilitated older DBFs to produce thicker, but less photosynthetically efficient leaves, resulting in decreased light use efficiency. Our findings offer new insights into the contrasting changes in leaf area and growing season length and highlight their divergent impacts on ecosystem functioning.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Li Y, Meng L, Richardson AD, et al (2025)

Cooling outweighs warming across phenological transitions in the Northern Hemisphere.

Proceedings of the National Academy of Sciences of the United States of America, 122(37):e2501844122.

Vegetation phenology, i.e., seasonal biological events such as leaf-out and leaf-fall, regulates local climate through biophysical processes like evapotranspiration (ET) and albedo. However, the net surface temperature impact of these processes-whether ET cooling or albedo-induced warming predominates-and how the dominance changes across phenological transitions and regions remains poorly understood. Here, we investigated the effects of vegetation foliage on daytime land surface temperature (LST) following six phenological transitions, spanning from the start of season to end of season, in deciduous and mixed forests across the mid- to high-latitude Northern Hemisphere during 2013-2021 using multiple satellite products and ground observations. We quantified vegetation effect as the difference between observed LST and LST estimates from the Annual Temperature Cycle (ATC) model, representing a no-foliage scenario. We found that vegetation-induced cooling consistently outweighs warming following all phenological transitions except for the end of the season. Cooling intensity increased with vegetation greenness, ranging from 1.0 ± 0.5 °C (mean ± 0.15 SD) in 59% of forests after the start of the season (SOS) to 6.1 ± 0.8 °C in 89% of forests following the onset of maturity, before declining toward the end of the season. Over half of the regions experiencing cooling showed intensification of surface cooling with climate warming, suggesting an amplified vegetation-mediated cooling under future climate change. The findings provide a more precise understanding of the role of vegetation in modulating climate at the intraseasonal scale, highlighting the importance of integrating phenological impacts into climate adaptation strategies and Earth system modeling.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Abdugheni R, WJ Li (2025)

EzBioCloud 16S rRNA Gene Sequence Formatter: a Python-based sequence formatting tool for systematic microbiology.

International journal of systematic and evolutionary microbiology, 75(9):.

EzBioCloud is one of the practical reference databases and analytical platforms for systematic microbiology research. The EzBioCloud database provides convenient services in this regard, especially for performing sequence analysis using the 16S rRNA genes. However, '.fasta' files of 16S rRNA sequences obtained after the alignment in EzBioCloud need manual formatting for further analysis and phylogenetic tree construction, which is labourious and time-consuming. To address this issue, we have developed a Python-based tool, EzBioCloud 16S rRNA Gene Sequence Formatter (version 1.0), designed to assist in sequence formatting. Here, we report the development and application of the tool and present this tool publicly to support the researchers in the relevant field.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Jackson K, Gabrielli J, Colby S, et al (2025)

Real-Time Exposure to Alcohol Content in Digital Media in Adolescents: Protocol for a Multiburst Ecological Momentary Assessment Study.

JMIR research protocols, 14:e50649 pii:v14i1e50649.

BACKGROUND: Digital media frequently contains positive portrayals of alcohol content, which has been shown to be associated with alcohol-related cognitions and behaviors. Because youth are heavy media consumers and have access to unsupervised, repeat viewing of media content on their personal mobile devices, it is critical to understand the frequency of encountering alcohol content in adolescents' daily lives and how adolescents engage with the content.

OBJECTIVE: This paper outlines the study protocol for examining adolescents' exposure to alcohol-related content in digital media within their natural environments.

METHODS: Adolescents (N=302; 31.8% boys, 16.2% nonbinary, 51.3% girls; 25.8% Asian, 3.6% American Indian, 21.5% Black, 4.6% other, 52% White, 25.8% Hispanic or Latinx; mean age 16.21, SD 0.77 y) enrolled in high school were recruited through social media to participate in a prospective study involving bursts of ecological momentary assessment (EMA) reports coupled with longer surveys. We conducted group orientation sessions via videoconference and online surveys, followed by a 21-day EMA period that included scheduled reports across 4 daily time blocks, as well as self-initiated reports on media exposure. Reports of alcohol content exposure included details about the platform, level of engagement, source characteristics, beliefs and perceived norms about the content, the viewing context, and whether the content was sponsored or branded. The participants submitted exposures to alcohol content as an image (screenshot or photo) or text description to be objectively coded. The participants completed a weekly online survey assessing alcohol use and related cognitions. EMA reports will be merged with coded image and text entries and with data from baseline, weekly, and follow-up surveys. Self-reported alcohol exposure will be explored descriptively, and differences in exposure tested across subgroups. Event-level data will be compared with random prompt data to examine differences at times of exposure versus nonexposure. Prospective associations between media alcohol content exposure and alcohol use will be explored over 1-week and 4-month time frames. Mediation of the association between media alcohol exposure and drinking will be tested to explore putative mechanisms.

RESULTS: EMA data collection took place from February 2022 to August 2023. Data management and preliminary analysis are ongoing. Preliminary data were disseminated through conference presentations in 2024-2025 and manuscripts are ongoing with full results anticipated to be published in 2025-2026.

CONCLUSIONS: By characterizing adolescents' real-world exposure to alcohol content in the media, the study provides critical information to develop and implement interventions to target youth behavior that are well suited to delivery via mobile devices. Next steps are to conduct focus groups to understand participants' lived experience of exposure to media alcohol content and reactions to proposed intervention targets. This study and subsequent qualitative work will launch a program of research to counter the effects of alcohol-related media exposure as experienced by adolescents in an effort to minimize underage alcohol involvement.

DERR1-10.2196/50649.

RevDate: 2025-09-08

Kröger K, Wiemes K, Santosa F, et al (2025)

Prescription of lipid-lowering drugs and their association with hospitalization for ST-elevation myocardial infarction (STEMI) in Germany in 2010-2022.

Clinical research in cardiology : official journal of the German Cardiac Society [Epub ahead of print].

OBJECTIVES: We investigated changes in lipid-lowering drug prescriptions in Germany as a whole and in the 16 federal states over the last 13 years and their association with hospitalization rates for acute myocardial infarction.

DESIGN: Ecological study.

SETTING: Nationwide German hospitalization, Diagnosis-Related Groups Statistic.

PATIENTS/PARTICIPANTS: German population in the years 2010 through 2022.

INTERVENTION: All prescriptions of lipid-lowering drugs in the years 2010 to 2022 by federal state in Germany.

MAIN OUTCOME MEASURES: Hospitalization rates for the treatment of transmural infarction per calendar year and federal state (STEMI = ST-elevation myocardial infarction).

RESULTS: The age-standardized prescription rates of lipid-lowering drugs per 1000 person-years increased from 77.4 in 2010 to 145.2 in 2022 (reference population: Germany 2011). Within the same period, the STEMI hospitalization rate per 100,000 person-years decreased from 143.7 to 100.1. Based on the prescription and hospitalization rates of the 16 federal states, it is shown that the STEMI hospitalization rate decreased the more the prescription rate of lipid-lowering drugs in a federal state increased over time (beta = 0.38, 95% confidence interval - 0.64; - 0.12; adjusted explained variance 0.362).

CONCLUSION: Increasing prescription rates of lipid-lowering drugs have correlated with decreasing rates of hospitalized cases for STEMI in Germany in the last decade.

RevDate: 2025-09-08

Milligan PD, Rossiter J, Zare A, et al (2025)

Mutualism, herbivory, and invasive ants as seasonally dependent drivers of root surface area in a foundational savanna ant-plant.

The New phytologist [Epub ahead of print].

Many plants are defended from herbivory by costly insect mutualists. Understanding positive associations between plants and mutualists requires a whole-plant perspective including roots. We hypothesized that root surface area increases with mutualist activity (to a saturation threshold) and recent rainfall but that this relationship shifts when herbivores are excluded. We also hypothesized that invasive ants limit root surface area and that mutualism breakdown driven by invaders blunts root responses to rainfall and herbivore exclusion. Using minirhizotrons (est. 2021), we surveyed root surface area of ant-acacias during a dry (2022) and then a wet (2023) season. Study plots either excluded or permitted vertebrate browsers, within a natural experiment comparing mutualist-defended ant-acacias to those invaded by a mutualism-disrupting ant. Root area increased with mutualist activity to a threshold, but this positive association was less apparent during rainy periods. Megabrowser exclusion increased overall root area but reduced the threshold for a positive association with mutualist activity and reduced the steepness of the root area-rainfall correlation. Ant-invaded acacias had smaller root areas that correlated less steeply with rainfall. Positive associations between insect defense and root area were thus contingent on rainfall, herbivory, and biotic invasion, drivers that are shifting under global change.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Araujo G, M Lurgi (2025)

Mutualism provides a basis for biodiversity in eco-evolutionary community assembly.

PLoS computational biology, 21(9):e1013402.

Unveiling the ecological and evolutionary mechanisms underpinning the assembly of stable and complex ecosystems is a main focus of community ecology. Ecological theory predicts the necessity of structural constraints on the network of species interactions to allow for growth and persistence of multi-species communities. However, the mechanisms behind their emergence are not well understood. An understanding of how the coexistence of diverse species interaction types could influence the development of complexity and how a persistent composition of interactions could arise in nature is needed. Using an eco-evolutionary model, we investigate the assembly of complex species interaction networks with multiple interaction types and its consequences for ecosystem stability. Our results show that highly mutualistic communities promote complex and stable network configurations, thus resulting in a positive complexity-stability relationship. We show that evolution by speciation enhances the emergence of such conditions compared to a purely ecological assembly scenario of repeated invasions by migrating species. Furthermore, communities evolved in isolation promote a disproportionately higher complexity and a larger diversity of outcomes. Our results produce valuable theoretical insight into the mechanisms behind the emergence of ecological complexity and into the roles of mutualism and speciation in community formation.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Zhang L, Liu Y, Chen K, et al (2025)

Genome mining of tailoring enzymes from biosynthetic gene clusters for synthetic biology: A case study with fungal methyltransferases.

Metabolic engineering, 92:125-135.

Harnessing the potential of tailoring enzymes within fungal natural product (NP) biosynthetic gene clusters (BGCs) can significantly enhance NP diversity and production efficiency via artificially constructed microbial cell factories. To achieve this, an efficient genome mining method is crucial, especially since the functions of many putative enzymes in databases are unknown. As a test case, we aimed to identify methyltransferases (MTs) that modify a polyketide substrate without a known cognate MT. 16,748 putative MTs were annotated in 101,321 fungal BGCs and grouped into orthologous families. Three methods were explored to prioritize suitable enzymes. Among these, the machine learning method proved superior, with 11 out of 15 tested MTs successfully methylating the test substrate. This demonstrates the effectiveness of machine learning to mine tailoring enzymes that modify selected compounds, aiding synthetic biology in optimizing NP biosynthesis and facilitating the production of "unnatural products" for pharmaceutical or other bioindustrial applications.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Lopez MLD, Warren RL, Allison MJ, et al (2025)

Conserved Sequence Identification Within Large Genomic Datasets Using 'Unikseq2': Application in Environmental DNA Assay Development.

Molecular ecology resources, 25(7):e70014.

Identification of conserved genomic sequences and their utilisation as anchor points for clade detection and/or characterisation is a mainstay in ecological studies. For environmental DNA (eDNA) assays, effective processing of large genomic datasets is crucial for reliable species detection in biodiversity monitoring. While considerable focus has been on developing robust species-targeted assays, eDNA assays with broader taxonomic coverage (e.g., detecting any species within a taxonomic group such as fish), can significantly streamline environmental monitoring, especially when detecting individual species' DNA proves challenging. Designing such assays requires identifying conserved regions representing the target taxonomic group, a chiefly manual task that is often labor-intensive and error-prone, particularly when working with large sequence datasets. To address these challenges, we present unikseq2, an enhanced, alignment-free, k-mer-based tool for identifying unique and conserved sequences. It introduces a new functionality to identify sequence conservation among target species, enabling more informed marker selection for applications such as universal primer design. This automates sequence selection in large-scale mitochondrial genome datasets eliminating the need for manual inspection of computationally costly multiple sequence alignments. Herein, we demonstrate unikseq2's capabilities by developing and validating eDNA assays for various taxa, including Osteichthyes (bony fishes), the Salmonidae family (salmon and trout), Myotis bats and Cervus deer. Unikseq2-based eDNA assays allow for accurate detection across multiple taxonomic levels, from genus to class, enhancing the flexibility, scalability and reliability of eDNA tools in environmental monitoring. By leveraging genomic data from public repositories, unikseq2 supports efficient, reproducible assay design, making it an invaluable tool for a wide range of ecological and biodiversity research applications.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Zhou H, Tang J, Cheng Z, et al (2025)

InsectTFDB: A Comprehensive Database and Analysis Platform for Insect Transcription Factors.

Molecular ecology resources, 25(7):e70006.

Transcription factors (TFs) are key regulators of gene expression, driving diverse biological processes in insects. Despite their importance, a dedicated and comprehensive database for insect TFs has been lacking. To address this gap, we developed InsectTFDB (http://www.insecttfdb.com/), a specialised resource encompassing 1796 insect species across 21 orders, 258 families and 1034 genera. From 59,491,033 predicted proteins, we identified 1,570,627 TFs, systematically classified into six structural groups and annotated using multiple approaches. Approximately 87% of these TFs were successfully annotated to known proteins, enhancing their functional interpretability. InsectTFDB offers a user-friendly interface with four functional modules, including tools for species retrieval, TF exploration, sequence alignment and predictive analysis of novel sequences. These features make it a versatile platform for diverse research applications, from evolutionary studies to functional genomics and pest management. By providing unprecedented taxonomic coverage and reliable annotations, InsectTFDB serves as a critical resource for advancing our understanding of transcriptional regulation and gene regulatory networks across the insects.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Liu M, Xie L, Pan Y, et al (2025)

Size-induced toxic effect of plastic particles on earthworms characterized by gut multi-omics analysis.

Environmental research, 283:122133.

The emission and accumulation of plastic particles in soil have raised concerns about their impact on soil organisms. As key components of soil fauna, earthworms (Eisenia fetida) are prone to ingesting plastic particles and experiencing associated health effects. However, the size-dependent toxicological mechanisms of these particles in earthworms remain unclear. In this study, earthworms were exposed to polystyrene particles of different sizes (50 nm, 200 nm, and 250 μm), and their biological responses were evaluated through morphological analysis, gut microbiota profiling, and metabolomics. Micro-sized particles (250 μm, 200 mg kg[-1]) caused mechanical damage to intestinal tissues and reduced survival rates after 28 days. Nano-sized particles (50 nm, 200 nm) disrupted gut microbial diversity and altered metabolic profiles, including reductions in amino acids involved in the TCA cycle. All particle sizes affected metabolite levels and key metabolic pathways. These results indicate that micro-sized particles primarily induce acute physical damage, while nano-sized particles exert long-term biochemical effects. This study highlights the size-specific ecological impacts of plastic particles on soil invertebrates.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Liu F, Lorenz C, G Zhao (2025)

From land to sea: Hydrological source tracking of microplastics in coastal sediments.

Environmental research, 283:122132.

Land-based sources are the predominant contributors to marine microplastic pollution; however, identifying specific inland origins and their correspondence transport paths remain challenging at large-scale. In Denmark, terrestrial-marine connectivity is largely mediated by a complex network of streams, that further complicates hydrological connections between diverse inland discharges and the final coastal receptor. This study presents a GIS-based hydrological source tracking approach to identify the relevant inland discharges and further delineating their transportation paths for microplastics (≥10 μm) sampled from coastal sediments. After analyzed with Focal Plane Array-based Fourier Transform Infrared (FPA-μFTIR) imaging, samples from 13 Danish coastal monitoring stations were tested for souce tracking operations. The tracking tool first screened the stream network across Denmark to identify both point and non-point inland sources-stormwater runoff, wastewater effluent, and combined sewer overflow (CSO)-contributing microplastics to the selected coastal zones. Microplastics were detected at all stations, with variations in abundance, polymer composition, particle shape, and size. Significant positive correlations (p < 0.05) were observed between discharge volume and the composition of certain microplastics: wastewater effluent positively correlates with fiber and polyvinylchloride (PVC), while stormwater-associated discharges (including CSOs) correlated with polypropylene (PP). However, total microplastic concentration was not significantly linked to the discharges. Nevertheless, the GIS-based hydrological tool demonstrated an early-screening tool to identify inland source of marine microplastics. The results underscored the significant role of inland discharges in transporting distinct microplastics to coastal environment, offering valuable insights for authorities to further implement more targeted hydrodynamic modelling, source-specific mitigation strategies, as well as optimised station deployment strategies in future.

RevDate: 2025-09-08
CmpDate: 2025-09-08

Lentendu G, Singer D, Agatha S, et al (2025)

EukFunc: A Holistic Eukaryotic Functional Reference for Automated Profiling of Soil Eukaryotes.

Molecular ecology resources, 25(7):e14118.

The soil eukaryome constitutes a significant portion of Earth's biodiversity that drives major ecosystem functions, such as controlling carbon fluxes and plant performance. Currently, however, we miss a standardised approach to functionally classify the soil eukaryome in a holistic way. Here we compiled EukFunc, the first functional reference database that characterises the most abundant and functionally important soil eukaryotic groups: fungi, nematodes and protists. We classified the 14,060 species in the database based on their mode of nutrient acquisition into the main functional classes of symbiotroph (40%), saprotroph (26%), phototroph (17%), predator (16%) and unknown (2%). EukFunc provides further detailed information about nutrition mode, including a secondary functional class (i.e., for organisms with multiple nutrition modes), and preyed or associated organisms for predatory or symbiotic taxa, respectively. EukFunc is available in multiple formats for user-friendly functional analyses of specific taxa or annotations of metabarcoding datasets, both embedded in the R package EukFunc. Using a soil dataset from alpine and subalpine meadows, we highlighted the extended ecological insights obtained from combining functional information across the entire soil eukaryome as compared to focusing on fungi, protists or nematodes individually. EukFunc streamlines the annotation process, enhances efficiency and accuracy, and facilitates the investigation of the functional roles of soil eukaryotes-a prerequisite to better understanding soil systems.

RevDate: 2025-09-05
CmpDate: 2025-09-05

Gaun N, Pietroni C, Martin-Bideguren G, et al (2025)

The Earth Hologenome Initiative: Data Release 1.

GigaScience, 14:.

BACKGROUND: The Earth Hologenome Initiative (EHI) is a global endeavor dedicated to revisit fundamental ecological and evolutionary questions from the systemic host-microbiota perspective, through the standardized generation and analysis of joint animal genomic and associated microbial metagenomic data.

RESULTS: The first data release of the EHI contains 968 shotgun DNA sequencing read files containing 5.2 TB of raw genomic and metagenomic data derived from 21 vertebrate species sampled across 12 countries, as well as 17,666 metagenome-assembled genomes reconstructed from these data.

CONCLUSIONS: The dataset can be used to address fundamental questions about host-microbiota interactions and will be available to the research community under the EHI data usage conditions.

RevDate: 2025-09-05
CmpDate: 2025-09-05

Polak I, Stryiński R, Paukszto Ł, et al (2025)

Diversity, expression, and structural modeling of sugar transporters in Anisakis simplex s. s. L3 and L4 larvae: an in vitro and in silico study.

Frontiers in cellular and infection microbiology, 15:1621051.

INTRODUCTION: Glucose transporter (GLUT) research in parasitic nematodes focuses on identifying and characterizing developmentally regulated isoforms, elucidating their regulatory and structural properties, and evaluating their potential as drug targets. While glucose transport mechanisms have been well characterized in the free-living nematode Caenorhabditis elegans, data on parasitic species remain limited. Anisakis simplex s. s., a parasitic nematode, relies on host-derived glucose to maintain energy metabolism. It is hypothesized that A. simplex s. s. utilizes specific glucose transporters to facilitate sugar uptake under varying nutritional conditions.

MATERIALS AND METHODS: In silico analysis identified five putative facilitated glucose transporter genes (fgt-1, fgt-2, fgt-3, fgt-5, fgt-9) and one Sugars Will Eventually be Exported Transporter (sweet-1) gene. The FGTs were classified as members of the solute carrier family 2 (SLC2), while sweet-1 belonged to the SWEET transporter family. Full-length cDNA sequences were obtained, and encoded proteins structurally characterized using bioinformatic modeling. Expression of transporter genes was assessed in A. simplex s. s. larvae at stages L3 and L4 cultured in vitro under different glucose concentrations and time points.

RESULTS: Structural and phylogenetic analyses revealed that fgt-1 and fgt-3 share high similarity with class I GLUTs found in nematodes and vertebrates. Gene expression profiling demonstrated differential regulation between larval stages. Most notably, FGT genes were stably expressed in L4 larvae, whereas in L3 larvae, gene activation was more variable and dependent on glucose concentration, showing a dynamic transcriptional response to nutrient levels. Sweet-1 was expressed in both stages, but its regulation differed over time and with glucose availability. Glucose supplementation altered trehalose and glycogen levels, and trehalase activity varied across stages and treatments, indicating stage-specific metabolic adaptation.

DISCUSSION: The observed transcriptional and biochemical differences between L3 and L4 larvae suggest a shift in glucose uptake mechanisms, from transcuticular absorption in L3 to intestinal glucose uptake in L4 following intestine activation. FGT1 and FGT3 are proposed as key facilitators of glucose uptake, with roles varying across developmental stages. These findings indicate that glucose transporters are regulated in response to changing environmental conditions and may represent targets for rational anthelmintic drug design.

RevDate: 2025-09-04

Kaplan DM, Alvarez SJA, Palitsky R, et al (2025)

Correction: Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions.

Behavior research methods, 57(10):274 pii:10.3758/s13428-025-02818-9.

RevDate: 2025-09-04
CmpDate: 2025-09-04

Selten G, Gómez-Repollés A, Lamouche F, et al (2025)

SyFi: generating and using sequence fingerprints to distinguish SynCom isolates.

Microbial genomics, 11(9):.

The plant root microbiome is a complex community shaped by interactions among bacteria, the plant host and the environment. Synthetic community (SynCom) experiments help disentangle these interactions by inoculating host plants with a representative set of culturable microbial isolates from the natural root microbiome. Studying these simplified communities provides valuable insights into microbiome assembly and function. However, as SynComs become increasingly complex to better represent natural communities, bioinformatics challenges arise. Specifically, accurately identifying and quantifying SynCom members based on, for example, 16S rRNA amplicon sequencing becomes more difficult due to the high similarity of the target amplicon, limiting downstream interpretations. Here, we present SynCom Fingerprinting (SyFi), a bioinformatics workflow designed to improve the resolution and accuracy of SynCom member identification. SyFi consists of three modules: the first module constructs a genomic fingerprint for each SynCom member based on its genome sequence and, when available, raw genomic reads, accounting for both copy number and sequence variation in the target gene. The second module extracts the target region from this genomic fingerprint to create a secondary fingerprint linked to the relevant amplicon sequence. The third module uses these fingerprints as a reference to perform pseudoalignment-based quantification of SynCom member abundance from amplicon sequencing reads. We demonstrate that SyFi outperforms standard amplicon analysis by leveraging natural intragenomic variation, enabling more precise differentiation of closely related SynCom members. As a result, SyFi enhances the reliability of microbiome experiments using complex SynComs, which more accurately reflect natural communities. This improved resolution is essential for advancing our understanding of the root microbiome and its impact on plant health and productivity in agricultural and ecological settings. SyFi is available at https://github.com/adriangeerre/SyFi.

RevDate: 2025-09-04

Hébert-Dufresne L, Ahn YY, Allard A, et al (2025)

One pathogen does not an epidemic make: a review of interacting contagions, diseases, beliefs, and stories.

Npj complexity, 2(1):26.

From pathogens and computer viruses to genes and memes, contagion models have found widespread utility across the natural and social sciences. Despite their success and breadth of adoption, the approach and structure of these models remain surprisingly siloed by field. Given the siloed nature of their development and widespread use, one persistent assumption is that a given contagion can be studied in isolation, independently from what else might be spreading in the population. In reality, countless contagions of biological and social nature interact within hosts (interacting with existing beliefs, or the immune system) and across hosts (interacting in the environment, or affecting transmission mechanisms). Additionally, from a modeling perspective, we know that relaxing these assumptions has profound effects on the physics and translational implications of the models. Here, we review mechanisms for interactions in social and biological contagions, as well as the models and frameworks developed to include these interactions in the study of the contagions. We highlight existing problems related to the inference of interactions and to the scalability of mathematical models and identify promising avenues of future inquiries. In doing so, we highlight the need for interdisciplinary efforts under a unified science of contagions and for removing a common dichotomy between social and biological contagions.

RevDate: 2025-09-04

Zhang L, Xiong A, Li C, et al (2025)

Ecological pattern of microalgal communities and associated risks in coastal ecosystems.

ISME communications, 5(1):ycaf109.

Eukaryotic harmful and toxic microalgae, along with their derived toxins, pose significant threats to seafood safety, human health, and marine ecosystems. Here, we developed a novel full-length 18S rRNA database for harmful and toxic microalgae and combined metabarcoding with toxin analyses to investigate the ecological patterns of phytoplankton communities and the underlying mechanism of associated toxic microalgae risks. We identified 79 harmful and toxic species in Hong Kong's coastal waters, with dinoflagellates and diatoms representing the majority of toxic and harmful taxa, respectively. Distinct seasonal succession patterns were observed in phytoplankton communities, driven by different ecological assembly processes. Deterministic processes dominated during the dry season, correlating with elevated toxic microalgae abundance and temperature stress. Seasonal shifts in temperature played a pivotal role in shaping toxic algal communities. The dominance of dinoflagellates, particularly Alexandrium spp., Dinophysis spp., Prorocentrum spp., and Karenia spp., during the dry season was consistent with elevated toxin concentrations. These toxin profiles highlight the heightened risk in a warming climate, where the prevalence and impacts of toxigenic algae are expected to intensify.

RevDate: 2025-09-04

Hutchinson F, Crowley LM, Broad GR, et al (2025)

The genome sequence of the Brown Moss-moth, Bryotropha terrella (Denis & Schiffermüller), 1775.

Wellcome open research, 10:310.

We present a genome assembly from a female specimen of Bryotropha terrella (Brown Moss-moth; Arthropoda; Insecta; Lepidoptera; Gelechiidae). The genome sequence has a total length of 756.35 megabases. Most of the assembly (99.62%) is scaffolded into 31 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled, with a length of 15.29 kilobases.

RevDate: 2025-09-04
CmpDate: 2025-09-04

Kupczok A, Gavriilidou A, Paulitz E, et al (2025)

Gene co-occurrence and its association with phage infectivity in bacterial pangenomes.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 380(1934):20240070.

Phages infect bacteria and have recently re-emerged as a promising strategy to combat bacterial infections. However, there is a lack of methods to predict whether and why a particular phage can or cannot infect a bacterial strain based on their genome sequences. Understanding the complex interactions between phages and their bacterial hosts is thus of considerable interest. We recently developed Goldfinder, a phylogenetic method to discover gene co-occurrences across bacterial pangenomes. Here, we expand Goldfinder to infer which gene presences or absences influence bacterial sensitivity to phages. By integrating a bacterial pangenome with an experimentally determined host range matrix, we infer associations between phage infectivity and the presence of accessory genes in bacterial pangenomes. The presented approach can be applied to predict bacterial genes that potentially enable phage infection, bacterial genes that prevent phage infection, and potential interactions between particular bacterial and phage accessory genes. Finally, the predicted interactions are clustered and visualized with the software Cytoscape. Here, we present a method to identify candidate genes within the pool of mobile accessory genes that may contribute to phage-host interactions. This approach will help to set up follow-up experiments and to understand the complex interactions between phages and bacteria.This article is part of the discussion meeting issue 'The ecology and evolution of bacterial immune systems'.

RevDate: 2025-09-03

Jones OE, Beckett H, Abraham AJ, et al (2025)

Endozoochory by Black Rhinoceroses Enhances Germination of a Key Arid Savanna Tree Species.

Ecology and evolution, 15(9):e71951.

Megaherbivores are typically regarded as agents of top-down control, limiting woody encroachment through destructive foraging. Yet they also possess traits and engage in behaviours that facilitate plant success. For example, megaherbivores can act as effective endozoochorous seed dispersers. However, studies on facilitative roles are heavily biased towards the African savanna elephant (Loxodonta africana), with little attention paid to other species or to effects beyond germination, across early ontogenic stages. The African black rhinoceros (Diceros bicornis), an obligate browser that exhibits frugivory and defecates in fixed dung middens, may offer ecologically distinct dispersal services. We conducted controlled experiments to test whether black rhino interactions with Vachellia erioloba, a leguminous tree of ecological importance in arid savannas, enhance germination, early seedling development or seedling resilience to herbivory. Germination was compared among dung-derived seeds, untreated controls and chemically scarified seeds. Seedling growth was assessed in dung versus sand and under simulated black rhino herbivory. Dung-derived seeds germinated most steadily and produced the highest cumulative germination (+40%) over the longest period (+13 days). Growth trials revealed that dung substrates did not enhance initial growth. Rather, seedlings being older conferred greater resilience to biomass loss than exposure to different substrate conditions. Our results provide the first experimental evidence of an apparent mutualism between black rhino and V. erioloba. This relationship is not driven by enhanced seedling development through legacy effects of gut passage, nor by dung conditions, as expected. Instead, it stems from gut passage effects on germination. In addition to increasing total germination, gut passage accelerates germination and extends the germination period, producing a seedling cohort with both older individuals and greater age variation-a population structure that may enhance persistence beyond the germination bottleneck. This research supports a more nuanced view of megaherbivores as both disturbance agents and mutualists in arid ecosystems.

RevDate: 2025-09-03
CmpDate: 2025-09-03

Ürel H, Benassou S, Marti H, et al (2025)

Nanopore- and AI-empowered microbial viability inference.

GigaScience, 14:.

BACKGROUND: The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from assessing ecosystem functions of environmental microbiomes to inferring the virulence of potential pathogens from metagenomic analysis. Established viability-resolved genomic approaches are labor-intensive as well as biased and lacking in sensitivity.

RESULTS: We here introduce a new fully computational framework that leverages nanopore sequencing technology to assess microbial viability directly from freely available nanopore signal data. Our approach utilizes deep neural networks to learn features from such raw nanopore signal data that can distinguish DNA from viable and dead microorganisms in a controlled experimental setting of UV-induced Escherichia cell death. The application of explainable artificial intelligence (AI) tools then allows us to pinpoint the signal patterns in the nanopore raw data that allow the model to make viability predictions at high accuracy. Using the model predictions as well as explainable AI, we show that our framework can be leveraged in a real-world application to estimate the viability of obligate intracellular Chlamydia, where traditional culture-based methods suffer from inherently high false-negative rates. This application shows that our viability model captures predictive patterns in the nanopore signal that can be utilized to predict viability across taxonomic boundaries. We finally show the limits of our model's generalizability through antibiotic exposure of a simple mock microbial community, where a new model specific to the killing method had to be trained to obtain accurate viability predictions.

CONCLUSIONS: While the potential of our computational framework's generalizability and applicability to metagenomic studies needs to be assessed in more detail, we here demonstrate for the first time the analysis of freely available nanopore signal data to infer the viability of microorganisms, with many potential applications in environmental, veterinary, and clinical settings.

RevDate: 2025-09-02
CmpDate: 2025-09-03

Rodal M, Luyssaert S, Balzarolo M, et al (2025)

A global database of net primary production of terrestrial ecosystems.

Scientific data, 12(1):1534.

Net primary production (NPP) is a fundamental measure of biomass production in ecosystems. In terrestrial biomes, NPP lacks standard measuring protocols and is difficult to measure. Thus, despite decades of research efforts, NPP data are limited and heterogenous. Moreover, there continues to be a lack of global NPP databases containing harmonized estimates for all major ecosystem types and which account for both above- and belowground production. We present a global database containing records for both above- and belowground production for forests, grasslands, arid shrublands, northern peatlands and tundra at 456 sites. The records are reported as annual production (g m[-2]yr[-1]). The NPP data are complemented with detailed site and methodological information, including a method specific estimate for the measurement uncertainty, as well as ancillary data on climatic conditions, soil fertility and management status. This database provides a basis for comparative studies on local, regional and global scales, and may serve as an important benchmarking dataset for the development of DGVMs.

RevDate: 2025-09-03
CmpDate: 2025-09-03

Jendrusch MA, Yang ALJ, Cacace E, et al (2025)

AlphaDesign: a de novo protein design framework based on AlphaFold.

Molecular systems biology, 21(9):1166-1189.

De novo protein design is of fundamental interest to synthetic biology, with a plethora of computational methods of various degrees of generality developed in recent years. Here, we introduce AlphaDesign, a hallucination-based computational framework for de novo protein design developed with maximum generality and usability in mind, which combines AlphaFold with autoregressive diffusion models to enable rapid generation and computational validation of proteins with controllable interactions, conformations and oligomeric state without the requirement for class-dependent model re-training or fine-tuning. We apply our framework to design and systematically validate in vivo active inhibitors of a family of bacterial phage defense systems with toxic effectors called retrons, paving the way towards efficient, rational design of novel proteins as biologics.

RevDate: 2025-09-02

Zhang F, Liang Y, Z Hu (2025)

Research on the inversion model of soil moisture content based on a novel ReMPDI index in mining areas.

Scientific reports, 15(1):32330.

The excavation of subterranean coal has led to a plethora of ecological and environmental issues, which seriously restrict the sustainable development of society. As one of the important physical indicators of soil, soil moisture content needs to be scientific, real-time, and comprehensively monitored. Due to the low efficiency of manual measurement, methods based on remote sensing data inversion have received widespread attention and in-depth research in recent years. In this study, a new ReMPDI index (Red edge Modified Perpendicular Drought Index) is constructed, and six retrieval models of soil moisture content based on machine learning algorithms are compared and analyzed, and the accuracy is verified by measured sampling data. The following conclusions were obtained: (1) Using the red edge band as the horizontal axis, and the near infrared band NIR as the vertical axis is the optimal spatial band combination of spectral characteristics for constructing soil lines; (2) The determination coefficient (R2) of ReMPDI index based on REdge-NIR spectral feature space and adding vegetation cover factor is the highest, which is-0. 798, and there is a significant correlation, which is better than MPDI and PDI index; (3) The model inversion accuracy of the RF is significantly higher than SVM, BPNN, PLSR, CNN, and RBFNN, with an error of only 9.52% compared to the measured results. The results of this study can provide a theoretical basis and technical support for the fine monitoring of surface soil moisture content on a large scale in mining areas.

RevDate: 2025-09-02

Whiteford S, Wellcome Sanger Institute Tree of Life Management, Samples and Laboratory team, Wellcome Sanger Institute Scientific Operations: Sequencing Operations, et al (2025)

The genome sequence of the virgin bagworm, Luffia ferchaultella (Stephens, 1850).

Wellcome open research, 10:108.

We present a genome assembly from an individual female Luffia ferchaultella (the Virgin Bagworm; Arthropoda; Insecta; Lepidoptera; Psychidae). The genome sequence spans 645.30 megabases. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.37 kilobases in length. Gene annotation of this assembly on Ensembl identified 12,416 protein-coding genes.

RevDate: 2025-09-02

de Goeij JM, Mueller B, Achlatis M, et al (2025)

The scaffold-level genome sequence of an encrusting sponge, Halisarca caerulea Vacelet & Donadey, 1987, and its associated microbial metagenome sequences.

Wellcome open research, 10:344.

We present a scaffold-level genome assembly from a Halisarca caerulea specimen (encrusting sponge; Porifera; Demospongiae; Chondrillida; Halisarcidae). The genome sequence is 195.70 megabases in span. The mitochondrial genome has also been assembled and is 19.15 kilobases in length. Gene annotation of this assembly on Ensembl identified 26,722 protein-coding genes. The metagenome of the specimen was also assembled and four binned bacterial genomes related to the relevant sponge symbiont clades Alphaproteobacteria bacterium GM7ARS4 and Gammaproteobacteria bacterium AqS2 ((Tethybacterales) were identified.

RevDate: 2025-09-02
CmpDate: 2025-09-02

Rowntree LC, Allen LF, Hagen RR, et al (2025)

HLA-B*15:01-positive severe COVID-19 patients lack CD8[+] T cell pools with highly expanded public clonotypes.

Proceedings of the National Academy of Sciences of the United States of America, 122(36):e2503145122.

Understanding host factors driving asymptomatic versus severe disease outcomes is of key importance if we are to control emerging and re-emerging viral infections. HLA-B*15:01 has been associated with asymptomatic SARS-CoV-2 infection in nonhospitalized individuals of European ancestry, with protective immunity attributed to preexisting cross-reactive CD8[+] T-cells directed against HLA-B*15:01-restricted Spike-derived S919-927 peptide (B15/S919[+]CD8[+] T-cells). However, fundamental questions remained on the abundance and clonotypic nature of CD8[+] T-cell responses in HLA-B*15:01-positive patients who succumbed to life-threatening COVID-19. Here, we analyzed B15/S919[+]CD8[+] T-cell responses in COVID-19 patients from independent HLA-typed COVID-19 patient cohorts across three continents, Australia, Asia and Europe. We assessed B15/S919[+]CD8[+] T-cells in COVID-19 patients across disease outcomes ranging from asymptomatic to hospitalized critical illness. We found that severe/critical COVID-19 patients mounted B15/S919[+]CD8[+] T-cell responses lacking a highly expanded key public B15/S919[+]CD8[+] T-cell receptor (TCR; TRAV9-2/TRBV7-2) which recurred across multiple individuals in COVID-19 patients with a mild disease. Instead, B15/S919[+]CD8[+] T-cell responses in life-threatening disease had a prevalence of an alternate TCR clonotypic motif (TRAV38-2/DV8/TRBV20-1), potentially contributing, at least in part, to why B15/S919[+]CD8[+] T-cells in severe COVID-19 patients were less protective. Interestingly, the frequency, memory phenotype, and activation profiles of circulating B15/S919[+]CD8[+] T-cells did not differ across disease severity. Moreover, B15/S919[+]CD8[+] T-cells were better maintained into convalescence compared to other SARS-CoV-2-specificities. Our study thus provides evidence on the differential nature of the TCR clonal repertoire in 22.37% of HLA-B*15:01-positive COVID-19 patients who developed severe or critical disease in our cohorts, comparing to HLA-B*15:01-expressing individuals with mild COVID-19.

RevDate: 2025-09-02
CmpDate: 2025-09-02

Ng S, Brown JP, Straub L, et al (2025)

Leveraging Health Insurance Claims Data to Complement the Centers for Disease Control and Prevention Surveillance System for Birth Defects.

Birth defects research, 117(9):e2523.

BACKGROUND: Birth defect surveillance can help identify temporo-spatial clusters and teratogenic signals to inform subsequent investigations or interventions. In the United States, state surveillance systems exist but collect limited information, prompting a complementary use of health insurance claims data to describe national birth defect prevalence trends and investigate signals.

METHODS: The Merative MarketScan Commercial Claims and Encounters (MarketScan) database was used to identify liveborn infants from 2016 to 2022, with linkage to maternal health care records during pregnancy. Birth defects were identified using ICD-10-CM codes recorded in the first 3 months of life, and prevalence estimates with 95% confidence intervals were generated for birth defect categories and select birth defects.

RESULTS: The study population included 943,855 liveborn infants. From 2016 to 2022, the prevalence increased for cardiac, central nervous system, ear, genital, urinary, musculoskeletal, and limb birth defect categories. Stable prevalence over the study period was observed for chromosomal, oral cleft, respiratory, gastrointestinal, vascular, and eye defects. For specific defects, we observed an increased prevalence of both ankyloglossia and lip-tie over the study period and a transient higher prevalence of omphalocele over 2017 and 2018. Within genital birth defects, we observed increasing prevalence trends for congenital malformations of the penis, while hypospadias and cryptorchidism remained relatively stable.

CONCLUSION: Health care utilization databases can complement existing surveillance systems by generating, confirming, or refuting signals based on ecological trends or clusters. The availability of patient information in claims databases can allow for further investigation of signals to inform birth defect etiology.

RevDate: 2025-09-01

Chasapi MN, Chasapi IN, Aplakidou E, et al (2025)

metagRoot: a comprehensive database of protein families associated with plant root microbiomes.

Nucleic acids research pii:8245223 [Epub ahead of print].

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71 091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, hidden Markov models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org.

RevDate: 2025-09-01

Han Y, Yu J, Liu X, et al (2025)

Generation of More Potent Components at Higher Temperatures Offsets Toxicity Reduction despite Reduced Mass Emissions during Biomass Burning.

Environmental science & technology [Epub ahead of print].

Biomass burning organic aerosols (BBOAs) represent a major global health hazard. Their toxicity varies significantly due to the diversity of combustion conditions, which shape mixtures of components with differing toxic potency. We quantified component-specific contributions to intracellular reactive oxygen species generation in human bronchial epithelial cells exposed to BBOAs produced under controlled combustion conditions. Elevated combustion temperatures substantially reduced organic carbon (OC) mass emissions (by 20-fold) but resulted in a more modest reduction in OC toxicity emissions (by 5-fold). The toxicity emission reduction was primarily attributed to water-extractable OC (WOC), while methanol-extractable OC (MOC) limited this effect. The reduced emission of WOC toxicity was driven by the decreased mass emission of polar compounds such as methoxylates, as the toxicity per unit mass of WOC showed negligible changes across temperatures. In contrast, the toxicity per unit mass of MOC increased 10-fold from low to high temperatures, partially due to the formation of more potent aromatic derivatives, despite their smaller mass contribution. These findings underscore the importance of identifying key toxicity drivers to guide targeted source apportionment and refine strategies for reducing toxic emissions.

RevDate: 2025-09-01
CmpDate: 2025-09-01

Rout AK, Rout SS, Panda A, et al (2025)

Potential applications and future prospects of metagenomics in aquatic ecosystems.

Gene, 967:149720.

Metagenomics plays a vital role in advancing our understanding of microbial communities and their functional contributions in various ecosystems. By directly sequencing DNA from environmental samples such as soil, water, air, and the human body. Metagenomics enables the identification of previously uncultivable or unknown microorganisms, offering key insights into their ecological functions. Beyond taxonomic classification, metagenomic analyses reveal functional genes and metabolic pathways, facilitating the discovery of enzymes, bioactive compounds, and other molecules with applications in agriculture, biotechnology, and medicine. This review discusses the broad applications of metagenomics in environmental monitoring, encompassing sample collection, high-throughput sequencing, data analysis and interpretation. We review different sequencing platforms, library preparation methods, and advanced bioinformatics tools used for quality control, sequence assembly, and both taxonomic and functional annotation. Special focus is given to the role of metagenomics in evaluating microbial responses to environmental stress, contaminant degradation, disease emergence, and climate change. The use of microbial bioindicators for aquatic ecosystem monitoring and toxicological assessments is also examined. A comprehensive evaluation of current bioinformatics pipelines is provided for their effectiveness in processing large-scale metagenomic datasets. As global environmental pressures intensify, integrative meta-omics approaches, including whole-genome metagenomics, will become crucial for understanding the complexity, functions, and dynamics of microbiomes in both natural and affected ecosystems.

RevDate: 2025-09-01
CmpDate: 2025-09-01

Gallardo García Freire P, Matías E, Malizia A, et al (2025)

Pollution risk assessment in sub-basins of an open dump using drones and geographic information systems.

Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA, 43(9):1425-1433.

The sustainable management of municipal solid waste (MSW) presents a pressing global challenge. This study introduces an innovative methodology for analysing open dumps in Tucumán, Argentina, using unmanned aerial vehicles (UAVs) and DroneDeploy software for data collection, coupled with QGIS for estimating contamination risk at the sub-basin level. By integrating satellite imagery, ground surveys, high-resolution UAV imagery and a multi-criteria decision analysis within geographic information system, we provide a comprehensive overview of dumpsite conditions at one open dump. Commercial drone flights facilitate the rapid and cost-effective creation of digital elevation models and digital terrain models, along with orthomosaic imagery, from which waste footprints are delineated using artificial intelligence to enhance the understanding of geospatial issues. Approaching data layers, such as leachate pools, riverbanks and solar radiation, supports informed decision-making in MSW management through a replicable methodology. Field validation and the inclusion of subsurface and groundwater processes are recommended for future research to improve accuracy and maximize socio-ecological benefits.

RevDate: 2025-08-30
CmpDate: 2025-08-30

Simonienko K, Jermakowicz E, Szefer P, et al (2025)

The impact of urban flower meadows on the well-being of city dwellers provides hints for planning biophilic green spaces.

Scientific reports, 15(1):31981.

Living surrounded by greenery has a relaxing effect and reduces physiological and psychological symptoms of stress. In view of the exponential growth of the urban population and disconnection with nature, supporting the physical and mental health of city dwellers is a huge challenge nowadays. In this context, urban flower meadows (UFMs), a relatively new management strategy cultivated in many cities, can be a very important component of urban greenery, which support human well-being. We investigated the emotional reception of UFMs, taking into account the features of different types of UFMs and the socio-demographic characteristics of respondents. Our research shows that urban flower meadows evoke positive emotions regardless of the age, gender and place of origin of respondents. While some structural variables of UFMs, particularly the proportion of green in relation to other colours, the representation of various flower colours, the proportion of yellow flowers, and the presence of alien plant species-influence people's perception. Fewer colours and the absence of alien plant species tend to shift perception towards less positive emotions. The dominance of yellow flowers evokes positive emotions. These results are helpful for the further planning of UFMs to better reinforce the well-being of all city dwellers.

RevDate: 2025-08-29
CmpDate: 2025-08-29

Khajehnejad M, García J, B Meyer (2025)

Age polyethism can emerge from social learning: A game-theoretic investigation.

PLoS computational biology, 21(8):e1013415.

Age-polyethism-the age-based allocation of tasks in social insect colonies-is a key feature of division of labour. While its hormonal underpinnings have been studied extensively, the behavioural and environmental mechanisms driving age-polyethism remain poorly understood, especially under ecological stress. We present a novel modelling framework that integrates social learning with task-related environmental feedback to explain the emergence and breakdown of age-polyethism. We develop two models: a Social Learning (SL) model, in which individuals adapt task preferences by copying similar peers, and a Stimulus-Response Threshold Social Learning (SRT-SL) model, which extends this framework by incorporating task-related dynamic stimuli and response thresholds that regulate collective task demand. Our models demonstrate that age-polyethism can emerge from simple social imitation processes, without the need for fixed hormonal schedules. We show that under increasing environmental pressure (e.g., resource scarcity), age-polyethism collapses as younger individuals are forced into tasks typically handled by older workers. Importantly, we find that age-polyethism does not necessarily optimize immediate colony efficiency; instead, it appears to reflect a trade-off between environmental constraints and behavioural coordination. These findings provide a mechanistic and ecologically grounded explanation for empirical observations linking environmental stress to dysfunctional division of labour and colony collapse.

RevDate: 2025-08-29
CmpDate: 2025-08-29

Benvenuti MC, Merkle EC, DM McCarthy (2025)

Physical context of alcohol use and craving: An EMA exploratory study.

Addictive behaviors, 170:108450.

While environmental and physical contextual factors play an important role in alcohol use and motivation for use, assessment of the physical context of use, even when using ecological momentary assessments (EMA), has been limited. While EMA research has examined drinking locations at the event level using categories of drinking locations, there is considerable within-category variability in the attributes of drinking locations. Using data from a 6-week EMA study (N = 207), this exploratory study sought to determine drinking locations through the combination of EMA self-report and GPS coordinates. Through multilevel modeling, we also tested whether specific locations were associated with variability in drinking (self-reported drinking and breathalyzer readings) and craving for alcohol. Results indicated significant differences in both alcohol consumption and craving between home, friend's houses, and on-premises drinking locations. Our results offer proof of concept for using mobile and geospatial data to passively identify on-premise drinking locations. This approach has the potential to aid in the development of targeted intervention strategies that identify and mitigate risks associated with specific drinking environments.

RevDate: 2025-08-29
CmpDate: 2025-08-29

Campbell KR, A Goeva (2025)

Cells Keep Diverse Company in Diseased Tissues.

Cancer research, 85(13):2351-2352.

Emerging spatial profiling technologies have revolutionized our understanding of how tissue architecture shapes disease progression, yet the contribution of cellular diversity remains underexplored. In this issue, Ding and colleagues introduce multiomics and ecological spatial analysis (MESA), an ecology-inspired framework that integrates spatial and single-cell expression data to quantify tissue diversity across multiple scales. MESA both identifies distinct cellular neighborhoods and computes a variety of diversity metrics alongside the identification of diversity "hotspots." Applied to human tonsil tissue, MESA revealed previously undetected germinal center organization, whereas in spleen tissue of a murine lupus model, MESA highlights increasing cellular diversity with disease progression. Importantly, diversity hotspots do not correspond to conventional compartments identified by existing methods, presenting an orthogonal metric of spatial organization. In colorectal cancer, MESA's diversity metrics outperformed established subtypes at predicting patient survival, whereas in hepatocellular carcinoma, multiomic integration identified significantly more ligand-receptor interactions between immune cells compared with single-modality analysis. This work establishes cellular diversity within tissues as a critical correlate of disease progression and underscores the value of multiomic integration in spatial biology. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI.

RevDate: 2025-08-29
CmpDate: 2025-08-29

Prescott J, Keyser AJ, Litwin P, et al (2025)

Rationale and design of the Dog Aging Project precision cohort: a multi-omic resource for longitudinal research in geroscience.

GeroScience, 47(4):5725-5748.

A significant challenge in multi-omic geroscience research is the collection of high quality, fit-for-purpose biospecimens from a diverse and well-characterized study population with sufficient sample size to detect age-related changes in physiological biomarkers. The Dog Aging Project designed the precision cohort to study the mechanisms underlying age-related change in the metabolome, microbiome, and epigenome in companion dogs, an emerging model system for translational geroscience research. One thousand dog-owner pairs were recruited into cohort strata based on life stage, sex, size, and geography. We designed and built a novel implementation of the REDCap electronic data capture system to manage study participants, logistics, and biospecimen and survey data collection in a secure online platform. In collaboration with primary care veterinarians, we collected and processed blood, urine, fecal, and hair samples from 976 dogs. The resulting data include complete blood count, chemistry profile, immunophenotyping by flow cytometry, metabolite quantification, fecal microbiome characterization, epigenomic profile, urinalysis, and associated metadata characterizing sample conditions at collection and during lab processing. The project, which has already begun collecting second- and third-year samples from precision cohort dogs, demonstrates that scientifically useful biospecimens can be collected from a geographically dispersed population through collaboration with private veterinary clinics and downstream labs. The data collection infrastructure developed for the precision cohort can be leveraged for future studies. Most important, the Dog Aging Project is an open data project. We encourage researchers around the world to apply for data access and utilize this rich, constantly growing dataset in their own work.

RevDate: 2025-08-29
CmpDate: 2025-08-29

Mittal K, Ewald J, Crump D, et al (2025)

Comparing transcriptomic responses to chemicals across six species using the EcoToxChip RNASeq database.

Environmental toxicology and chemistry, 44(9):2438-2442.

The EcoToxChip project includes RNA-sequencing data from experiments involving model (Japanese quail, fathead minnow, African clawed frog) and ecological (double-crested cormorant, rainbow trout, northern leopard frog) species at multiple life stages (whole embryo and adult) exposed to eight chemicals of environmental concern known to perturb a wide range of biological systems (ethinyl estradiol, hexabromocyclododecane, lead, selenomethionine, 17β trenbolone, chlorpyrifos, fluoxetine, and benzo[a]pyrene). The objectives of this short communication were to (1) present and make available this RNA-sequencing database (i.e., 724 samples from 49 experiments) under the FAIR principles (FAIR data are data which meet principles of findability, accessibility, interoperability, and reusability), while also summarizing key meta-data attributes and (2) use ExpressAnalyst (including the Seq2Fun algorithm and EcoOmicsDB) to perform a comparative transcriptomics analysis of this database focusing on baseline and differential transcriptomic changes across species-life stage-chemical combinations. The database is available in NCBI GEO under accession number GSE239776. Across all species, the number of raw reads per sample ranged between 13 and 58 million, with 30% to 79% of clean reads mapped to the "vertebrate" subgroup database in EcoOmicsDB. Principal component analyses of the reads illustrated separation across the three taxonomic groups as well as some between tissue types. The most common differentially expressed gene was CYP1A1 followed by CTSE, FAM20CL, MYC, ST1S3, RIPK4, VTG1, and VIT2. The most common enriched pathways were metabolic pathways, biosynthesis of cofactors and biosynthesis of secondary metabolites, and chemical carcinogenesis, drug metabolism, and metabolism of xenobiotics by cytochrome P450. The RNA-sequencing database in the present study may be used by the research community for multiple purposes, including, for example, cross-species investigations, in-depth analyses of a particular test compound, and transcriptomic meta-analyses.

RevDate: 2025-08-28
CmpDate: 2025-08-28

Bugingo C, Infantino A, Okello P, et al (2025)

From Morphology to Multi-Omics: A New Age of Fusarium Research.

Pathogens (Basel, Switzerland), 14(8): pii:pathogens14080762.

The Fusarium genus includes some of the most economically and ecologically impactful fungal pathogens affecting global agriculture and human health. Over the past 15 years, rapid advances in molecular biology, genomics, and diagnostic technologies have reshaped our understanding of Fusarium taxonomy, host-pathogen dynamics, mycotoxin biosynthesis, and disease management. This review synthesizes key developments in these areas, focusing on agriculturally important Fusarium species complexes such as the Fusarium oxysporum species complex (FOSC), Fusarium graminearum species complex (FGSC), and a discussion on emerging lineages such as Neocosmospora. We explore recent shifts in species delimitation, functional genomics, and the molecular architecture of pathogenicity. In addition, we examine the global burden of Fusarium-induced mycotoxins by examining their prevalence in three of the world's most widely consumed staple crops: maize, wheat, and rice. Last, we also evaluate contemporary management strategies, including molecular diagnostics, host resistance, and integrated disease control, positioning this review as a roadmap for future research and practical solutions in Fusarium-related disease and mycotoxin management. By weaving together morphological insights and cutting-edge multi-omics tools, this review captures the transition into a new era of Fusarium research where integrated, high-resolution approaches are transforming diagnosis, classification, and management.

RevDate: 2025-08-28
CmpDate: 2025-08-28

Yu Z, Lei T, Yi X, et al (2025)

LGRPv2: A high-value platform for the advancement of Fabaceae genomics.

Plant biotechnology journal, 23(9):4057-4075.

Fabaceae, as one of the most diverse angiosperm families, plays a crucial role in maintaining global ecosystems and advancing human civilization. With the rapid accumulation of legume genomes, we developed LGRPv2 (https://fabaceae.cgrpoee.top), an updated version of the Legume Genomics Research Platform. LGRPv2 integrates 414 genomes, covering all published legume genomes and containing our latest deciphered Tamarindus indica genome from early-diverging legumes and three outgroup genomes (Euscaphis pleiosperma, Vitis vinifera, and Platycodon tenuifolia). It features user-friendly interactive interfaces for studying functional annotations, gene duplications, regulatory proteins, N[6]-methyladenosine modifications, and transposable elements. For easily exploring genome evolution associated with polyploidizations, we incorporated DotView, SynView, and DecoBrowse with genome synteny (GenS) to establish a central GenS database for legumes. Specialized web services for ancestral legume genomes enable scientists to analyse the role of paleogenome reshuffling in shaping genomic diversity. The platform offers 184 511 synteny-based orthogroups and 1 086 836 genes from 139 families, and tools to explore agronomic trait origins. LGRPv2 integrates 40 550 transcriptomes, 5091 pan-genomes, 12 136 metabolomes, species encyclopaedias, ecological resources, and literature for exploring legume genomics comprehensively. Furthermore, LGRPv2 implemented 58 window-based operating tools (31 new) to efficiently support new mining, especially in advancing assembling pipelines for polyploidization identification, ancestral genome reconstruction, and gene family evolution. Finally, we provided detailed usage guides and community support to empower LGRPv2 with user-friendly and continuously updated features.

RevDate: 2025-08-28
CmpDate: 2025-08-28

Deuker A, Wittkugel J, Dublin Y, et al (2025)

Beyond the Pitch: Unveiling the Concave Hull as Soccer's Ecological Niche in Practice Design.

Research quarterly for exercise and sport, 96(3):463-474.

An ecological niche is a field in a landscape of affordances, rich in information inviting its inhabitants to develop functionality and effectiveness of their behavior. This idea means that, in sports like soccer, the playing area encapsulates an ecological niche, replete with affordances inviting collective and individual technical-tactical actions, contextualized with associated psychological and physical demands. To examine the co-adaptive relationships framing players' actions in their ecological niche, the present study employed a crossover design with repeated measures to compare the players' transactions within 11 vs. 11 training games across four different field dimensions (from official size to a small-sided game). Player transactions with the performance environment were analyzed across 40 game sequences, using 10Hz GPS positional data. Metrics such as convex hull dimensions, field occupancy, and proximity to opponents were derived. Repeated-measures ANOVA revealed significant differences between tendencies for forming synergies constrained by field dimensions scaling. When field size was reduced, the convex hull dimension significantly decreased. Additionally, relative field occupancy and distance to nearest opponent exhibited significant changes, especially when contrasted with performance transactions emerging on the official size field. These observations underline the essential functional relationship between the playing field dimension and emergent player actions. Such findings underscore the need for soccer coaches and training designers to integrate the specificity of field dimension scaling in training designs to represent competitive performance contexts. Data analytics deriving spatial constraint values from competitive matches may help researchers and practitioners improve task representativeness in practice and performance preparation, supporting the optimality of training niches in soccer.

RevDate: 2025-08-27
CmpDate: 2025-08-27

Yoon HJ, Seo JH, Shin SH, et al (2025)

Bioinformation and Monitoring Technology for Environmental DNA Analysis: A Review.

Biosensors, 15(8):.

Environmental DNA (eDNA) analysis has emerged as a transformative tool in environmental monitoring, enabling non-invasive detection of species and microbial communities across diverse ecosystems. This study systematically reviews the role of bioinformation technology in eDNA analysis, focusing on methodologies and applications across air, soil, groundwater, sediment, and aquatic environments. Advances in molecular biology, high-throughput sequencing, bioinformatics tools, and field-deployable detection systems have significantly improved eDNA detection sensitivity, allowing for early identification of invasive species, monitoring ecosystem health, and tracking pollutant degradation processes. Airborne eDNA monitoring has demonstrated potential for assessing microbial shifts due to air pollution and tracking pathogen transmission. In terrestrial environments, eDNA facilitates soil and groundwater pollution assessments and enhances understanding of biodegradation processes. In aquatic ecosystems, eDNA serves as a powerful tool for biodiversity assessment, invasive species monitoring, and wastewater-based epidemiology. Despite its growing applicability, challenges remain, including DNA degradation, contamination risks, and standardization of sampling protocols. Future research should focus on integrating eDNA data with remote sensing, machine learning, and ecological modeling to enhance predictive environmental monitoring frameworks. As technological advancements continue, eDNA-based approaches are poised to revolutionize environmental assessment, conservation strategies, and public health surveillance.

RevDate: 2025-08-27
CmpDate: 2025-08-27

Navratilova HF, Whetton AD, N Geifman (2025)

Integrating Food Preference Profiling, Behavior Change Strategies, and Machine Learning for Cardiovascular Disease Prevention in a Personalized Nutrition Digital Health Intervention: Conceptual Pipeline Development and Proof-of-Principle Study.

Journal of medical Internet research, 27:e75106.

BACKGROUND: Personalized dietary advice needs to consider the individual's health risks as well as specific food preferences, offering healthier options aligned with personal tastes.

OBJECTIVE: This study aimed to develop a digital health intervention (DHI) that provides personalized nutrition recommendations based on individual food preference profiles (FPP), using data from the UK Biobank.

METHODS: Data from 61,229 UK Biobank participants were used to develop a conceptual pipeline for a DHIs. The pipeline included three steps: (1) developing a simplified food preference profiling tool, (2) creating a cardiovascular disease (CVD) prediction model using the subsequent profiles, and (3) selecting intervention features. The CVD prediction model was created using 3 different predictor sets (Framingham set, diet set, and FPP set) across 4 machine learning models: logistic regression, linear discriminant analysis, random forest, and support vector machine. Intervention functions were designed using the Behavior Change Wheel, and behavior change techniques were selected for the DHI features.

RESULTS: The feature selection process identified 14 food items out of 140 that effectively classify FPPs. The food preference profile prediction set, which did not include blood measurements or detailed nutrient intake, demonstrated comparable accuracy (across the 4 models: 0.721-0.725) to the Framingham set (0.724-0.727) and diet set (0.722-0.725). Linear discriminant analysis was chosen as the best-performing model. Four key features of the DHI were identified: food source and portion information, recipes, a dietary recommendation system, and community exchange platforms. The FPP and CVD risk prediction model serve as inputs for the dietary recommendation system. Two levels of personalized nutrition advice were proposed: level 1-based on food portion intake and FPP; and level 2-based on nutrient intake, FPP, and CVD risk probability.

CONCLUSIONS: This study presents proof of principle for a conceptual pipeline for a DHI that empowers users to make informed dietary choices and reduce CVD risk by catering to person-specific needs and preferences. By making healthy eating more accessible and sustainable, the DHI has the potential to significantly impact public health outcomes.

RevDate: 2025-08-26

Ge S, Li J, Ma H, et al (2025)

A cis-natural antisense RNA regulates alternative polyadenylation of SlSPX5 under Pi starvation in tomato.

Nature communications, 16(1):7981.

Alternative polyadenylation (APA) generates transcript diversity by producing mRNA isoforms with distinct 3' ends. Despite the critical roles that APA plays in various biological processes, the mechanisms regulating APA in response to stresses have remained poorly understood in plants. Here, we perform comprehensive analysis of APA in tomato, and focus on a phosphate (Pi)- regulated APA gene SlSPX5, encoding a putative Pi sensor protein. SlSPX5 interacts with and sequesters the transcription factor SlPHL1 in the cytosol, thereby inhibiting the expression of Pi starvation inducible genes. We discover that a cis-natural antisense RNA (cis-NAT) is activated from SlSPX5 to promote its proximal polyadenylation under Pi-depleted conditions. The transcription of this cis-NAT induces RNA Polymerase II pausing, generating Ser2 phosphorylation signals that recruit polyadenylation machinery to the 5' end of SlSPX5. Our findings demonstrate that a cis-NAT regulates APA of its cognate gene in response to Pi starvation.

RevDate: 2025-08-26
CmpDate: 2025-08-21

Carlozzi NE, Troost J, Lombard WL, et al (2025)

Completion and Compliance Rates for an Intensive mHealth Study Design to Promote Self-Awareness and Self-Care Among Care Partners of Individuals With Traumatic Brain Injury: Secondary Analysis of a Randomized Controlled Trial.

JMIR mHealth and uHealth, 13:e73772.

BACKGROUND: Compliance rates for mobile health (mHealth) studies that involve intensive study designs are highly variable. Both person- and study-specific factors likely contribute to this variability. We were interested in understanding the impact that care partner characteristics and demographics have on study engagement, given that engagement is critical to the success of mHealth interventions.

OBJECTIVE: The primary objective of this report was to analyze the overall and component-specific completion and compliance rates for an intensive 6-month mHealth intervention (CareQOL app) designed to promote self-awareness and self-care among care partners of individuals with traumatic brain injury.

METHODS: This randomized controlled trial was designed to test the CareQOL app, an mHealth app designed to promote care partner self-awareness (through self-monitoring) and self-care (through personalized self-care push notifications). The study design consisted of a baseline assessment, a 6-month home-monitoring period that included 3 daily ecological momentary assessment (EMA) questions, monthly patient-reported outcome (PRO) surveys, continuous activity and sleep monitoring using a Fitbit, and 2 follow-up PRO surveys at 3 and 6 months posthome monitoring. Three participants withdrew prior to the initiation of the home-monitoring period, resulting in a final analytical sample size of 254. All participants had access to a self-monitoring dashboard (CareQOL app) that included graphical displays of the daily survey scores, as well as daily steps and sleep data from the Fitbit.

RESULTS: Overall compliance for the different aspects of the study was high. On average, the full-sample daily EMA PRO completion rate was 84% (SD 19%), Fitbit-based step count compliance was 90% (SD 21%), and Fitbit-based sleep duration compliance was 75% (SD 32%); there was no difference between the study arms for daily EMA PROs and Fitbit compliance rates. Completion rates for monthly and follow-up PRO surveys were even higher, with average end-of-month completion rates ranging from 97% to 100%, and follow-up completion rates of 95% for both time points. Again, these rates did not differ by study arm. The data were represented by 3 engagement groups: high-compliance-all data; high-compliance-PROs and steps only; and moderate PRO compliance-low Fitbit compliance. Group membership was predicted by both race (P<.001) and relationship to the care recipient (P=.001), but not by the other person-specific variables.

CONCLUSIONS: The compliance rates for this intensive study design are consistent, but at the high end, with what has been reported previously in the literature for studies with shorter time durations. Except for race and relationship to the care recipient, person-specific factors did not appear to be significantly associated with the engagement group. As such, we anticipate that the high compliance rates observed in this study are likely due to several study-specific design elements that were used to encourage study engagement.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Kubota Y, T Fukiage (2025)

Human-like monocular depth biases in deep neural networks.

PLoS computational biology, 21(8):e1013020.

Human depth perception from 2D images is systematically distorted, yet the nature of these distortions is not fully understood. By examining error patterns in depth estimation for both humans and deep neural networks (DNNs), which have shown remarkable abilities in monocular depth estimation, we can gain insights into constructing functional models of this human 3D vision and designing artificial models with improved interpretability. Here, we propose a comprehensive human-DNN comparison framework for a monocular depth judgment task. Using a novel human-annotated dataset of natural indoor scenes and a systematic analysis of absolute depth judgments, we investigate error patterns in both humans and DNNs. Employing exponential-affine fitting, we decompose depth estimation errors into depth compression, per-image affine transformations (including scaling, shearing, and translation), and residual errors. Our analysis reveals that human depth judgments exhibit systematic and consistent biases, including depth compression, a vertical bias (perceiving objects in the lower visual field as closer), and consistent per-image affine distortions across participants. Intriguingly, we find that DNNs with higher accuracy partially recapitulate these human biases, demonstrating greater similarity in affine parameters and residual error patterns. This suggests that these seemingly suboptimal human biases may reflect efficient, ecologically adapted strategies for depth inference from inherently ambiguous monocular images. However, while DNNs capture metric-level residual error patterns similar to humans, they fail to reproduce human-level accuracy in ordinal depth perception within the affine-invariant space. These findings underscore the importance of evaluating error patterns beyond raw accuracy, providing new insights into how humans and computational models resolve depth ambiguity. Our dataset and methodology provide a framework for evaluating the alignment between computational models and human perceptual biases, thereby advancing our understanding of visual space representation and guiding the development of models that more faithfully capture human depth perception.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Aceto S, Perrini S, Varone M, et al (2025)

Identification of Sex-Specific and Sex-Biased Transcripts for Genetic Sexing.

Methods in molecular biology (Clifton, N.J.), 2935:273-298.

Sex-specific transcripts are RNA molecules expressed predominantly or exclusively in one sex, providing insights into molecular and physiological differences between males and females. This knowledge underpins the development of precise and efficient genetic sexing methods applicable in various contexts. In agriculture and livestock management, early sex determination could enhance resource management and productivity. In ecology and conservation, genetic sexing informs population monitoring and species management. In applied entomology, it could improve biological control strategies, such as the sterile insect technique. Here, we describe a bioinformatic framework to identify sex-specific transcripts using RNA-seq sequencing data in eukaryotic species with or without a sequenced reference genome.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Stansberry TT, Myers CR, Tran L, et al (2025)

Impacts of Access to Hospital and Emergency Care on Rural Mortality in Tennessee, 2010-2019: A GIS-Informed Study.

Journal of health care for the poor and underserved, 36(3):787-814.

Rural Tennessee's health and economic disparities have worsened since 2010 (while the state led the nation in hospital closures per capita). Guided by the Vulnerable Populations Conceptual Model, we examined the relationship between Tennessee's county-level rural mortality rates and declining access to hospital and emergency care in the decade preceding the COVID-19 pandemic (avoiding pandemic-related delayed data releases and potential statistical modeling issues). We conducted a retrospective, ecological correlational study using geographic information systems and annual cross-sectional secondary data, employing aspatial and spatial negative binomial generalized linear mixed-effects models (GLMMs). Our bivariate models revealed significant correlations between hospital and emergency care access and mortality rates, but the effect decreased when adjusted for rurality, median household income, age, and other covariates. While access to hospital and emergency care influences mortality, our findings indicate that socioeconomic and demographic factors have a greater impact, underscoring the strong health-wealth connection in rural Tennessee.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Ye G, R Yu (2025)

Spatiotemporal Mapping of Grazing Livestock Behaviours Using Machine Learning Algorithms.

Sensors (Basel, Switzerland), 25(15):.

Grassland ecosystems are fundamentally shaped by the complex behaviours of livestock. While most previous studies have monitored grassland health using vegetation indices, such as NDVI and LAI, fewer have investigated livestock behaviours as direct drivers of grassland degradation. In particular, the spatial clustering and temporal concentration patterns of livestock behaviours are critical yet underexplored factors that significantly influence grassland ecosystems. This study investigated the spatiotemporal patterns of livestock behaviours under different grazing management systems and grazing-intensity gradients (GIGs) in Wenchang, China, using high-resolution GPS tracking data and machine learning classification. the K-Nearest Neighbours (KNN) model combined with SMOTE-ENN resampling achieved the highest accuracy, with F1-scores of 0.960 and 0.956 for continuous and rotational grazing datasets. The results showed that the continuous grazing system failed to mitigate grazing pressure when grazing intensity was reduced, as the spatial clustering of livestock behaviours did not decrease accordingly, and the frequency of temporal peaks in grazing behaviour even showed an increasing trend. Conversely, the rotational grazing system responded more effectively, as reduced GIGs led to more evenly distributed temporal activity patterns and lower spatial clustering. These findings highlight the importance of incorporating livestock behavioural patterns into grassland monitoring and offer data-driven insights for sustainable grazing management.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Karaman MZ, Yetiman AE, Zhan J, et al (2025)

Biochemical Characterization and Genome Analysis of Pseudomonas loganensis sp. nov., a Novel Endophytic Bacterium.

MicrobiologyOpen, 14(4):e70051.

Pseudomonas species are highly adaptable, thriving in diverse environments and exhibiting remarkable genetic and metabolic diversity. While some strains are pathogenic, others have significant ecological and industrial applications. Bioinformatics and biochemical analyses, including antibiotic sensitivity testing, revealed that Pseudomonas loganensis sp. nov. can tolerate NaCl concentrations up to 5% and pH ranges between 5 and 9. Antibiogram results corroborated genome data, demonstrating resistance to vancomycin, ampicillin, methicillin, oxacillin, and penicillin G. Phylogenetic analysis based on 16S rRNA, rpoB, rpoD, and gyrB genes, combined with average nucleotide identity (ANI) comparisons, confirmed P. loganensis sp. nov. as a novel species within the Pseudomonas genus. Genome analysis further revealed the presence of turnerbactin and carotenoid gene clusters. Turnerbactin, known to contribute to nitrogen fixation in plants, highlights the strain's potential as a biofertilizer. Additionally, the carotenoid gene cluster suggests potential applications in industrial carotenoid production. The discovery of a trehalose synthase (treS) gene indicates the capability for one-step conversion of maltose into trehalose, underscoring its potential utility in trehalose production.

RevDate: 2025-08-25
CmpDate: 2025-08-25

Naseri C, Hill AM, Xu D, et al (2025)

What influences older people to join a community hub to engage in healthy ageing programs? An exploratory study.

Australasian journal on ageing, 44(3):e70079.

OBJECTIVES: Most people seek to stay connected to their community as they age; this has been a major focus in the development of innovative community programs in Australia. This study aimed to explore what influences older people to join a community hub to engage in healthy ageing programs.

METHODS: Semi-structured interviews (n = 29) were conducted during an Open Day in early 2023 at an urban community hub in Western Australia, followed by telephone interviews (n = 9) of a purposive sample of older individuals, community hub facilitators and coordinators of national community hubs. Analysis used a socio-ecological framework.

RESULTS: Deductive content analysis identified social prescribing as an overarching influencer for older people to join and engage in healthy ageing programs and main themes of (i) supporting community hub facilitators to harness community assets, (ii) link-supports provided to older members by paid community hub concierges triggered positive outcomes at individual and community levels, (iii) online and in-person social and physical healthy ageing activities tailored to member interests and (iv) nurturing social networks and reciprocity between members sustained engagement in healthy ageing activities.

CONCLUSIONS: The dynamic process of social prescribing was a central influencer for older adults to engage in healthy ageing programs, and the social network perpetuated through community hubs was an immeasurable social investment that boosted the resilience of intergenerational populations in Australian communities. Policy support is required for communities to meet the challenge of being responsive to the needs of members who seek to remain independent as they age in place.

RevDate: 2025-08-25
CmpDate: 2025-08-25

Vizueta J, Pisarenco VA, J Rozas (2025)

Evolutionary Genomics of Gene Families: A Case Study of Insect Gustatory Receptors.

Methods in molecular biology (Clifton, N.J.), 2935:179-209.

Gene families, which are groups of genes that share common ancestry and are often functionally related, constitute a substantial proportion of the protein-coding sequences within eukaryotic genomes. In insects, genes involved in chemoperception belong to gene families characterized by numerous copies that arise from episodic bursts of gene duplication. This biological process is crucial for insect survival, as it enables the perception of environmental chemical cues. In this chapter, we analyze the gustatory receptors in the fire ant Solenopsis invicta and present a protocol for bioinformatic analyses. First, we employ BITACORA to identify and annotate gene family members in the genome assembly, providing tools for the annotation and subsequent validation. Then, we use GALEON to explore the genomic arrangement of gene family members in the chromosome-level assembly and visualize the distribution of gene clusters. To gain insights into the evolution and function of these genes, we conduct multiple-sequence alignment and reconstruct the phylogeny, incorporating data from two other insects. Finally, we integrate physical and evolutionary distances of the gustatory receptors to further understand the dynamics of this gene family.

RevDate: 2025-08-25
CmpDate: 2025-08-25

Ramos-Onsins SE, Guirao-Rico S, Hafez A, et al (2025)

npstat: An Efficient Tool to Explore the Population Genome Variability and Divergence Using Pool Sequencing Data.

Methods in molecular biology (Clifton, N.J.), 2935:51-66.

Pool sequencing has emerged as a valuable approach in ecological studies, particularly when dealing with very small organisms (with limited amount of DNA available), when distinguishing individual organisms is a challenge (e.g., in colonies, microbiome), when there is a trade-off between the sequencing cost and the number of individuals to sequence, when the main goal is to estimate nucleotide variability and variant frequency patterns at the population level (that is, when individual information is not required). Estimates of variability can be efficiently explored by analyzing sequences of pooled individuals sampled from the population. When using this approach, the number of pooled individuals and the mean read depth are key choices in the experimental design.The software npstat calculates different estimates of nucleotide variability and neutrality tests.It also calculates the number of synonymous and nonsynonymous variants and the proportion of beneficial substitutions (alpha) using the MKT approach when GTF annotation file and an outgroup is provided.

RevDate: 2025-08-25
CmpDate: 2025-08-25

Alhashmi AA, Elhessewi GMS, Ghaleb M, et al (2025)

Enhancing medical response efficiency in real-time large crowd environments via smart coverage and deep learning for stable ecological health monitoring.

Scientific reports, 15(1):30000.

Festivals and city-wide mass events are prevalent in human societies worldwide, drawing large crowds. Such events range from concerts with a dozen attendees to large-scale actions with thousands of viewers. It is the highest priority for each organizer of such an occasion to be capable of upholding a higher standard of safety and minimizing the danger of events, especially medical emergencies. Therefore, establishing sufficient safety measures is significant. There is a requirement for event organizers and emergency response personnel to identify developing, potentially critical crowd situations at an early stage during city-wide mass assemblies. In general, the localization of the global positioning system (GPS) and proximity-based tracking is employed to capture intricate crowd dynamics throughout an event. Recently, technology has been used in numerous diverse ways to achieve these large crowds. For example, computer vision-based models are employed to observe the flexibility and behaviour of crowds. In this manuscript, a model for Medical Response Efficiency in Real-Time Large Crowd Environments via Smart Coverage and Hiking Optimisation (MRELC-SCHO) is presented, aiming to maintain stable ecological health. The primary objective of this paper is to propose an effective method for enhancing medical response efficiency in large crowd environments by utilizing advanced optimization algorithms. Initially, the MRELC-SCHO model utilizes min-max normalization to transform the input data into a structured format. Furthermore, the Chimp Optimisation Algorithm (CHOA) model is employed for the feature selection (FS) process to select the most significant features from the dataset. Additionally, the MRELC-SCHO technique utilizes the bidirectional long short-term memory with an auto-encoder (BiLSTM-AE) method for classification. Finally, the parameter selection for the BiLSTM-AE model is performed by using the Hiking Optimisation Algorithm (HOA) model. The experimentation of the MRELC-SCHO approach is accomplished under the Ecological Health dataset. The comparison analysis of the MRELC-SCHO approach revealed a superior accuracy value of 98.56% compared to existing models.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Sanad H, Moussadek R, Mouhir L, et al (2025)

Monte carlo simulation for evaluating spatial dynamics of toxic metals and potential health hazards in sebou basin surface water.

Scientific reports, 15(1):29471.

Surface water is vital for environmental sustainability and agricultural productivity but is highly vulnerable to heavy metals (HMs) pollution from human activities. The focus of this research is to provide an analysis of ecological and human exposure to HMs in the Sebou Basin, an agriculturally significant region within Morocco's Gharb Plain. Using a multi-index integration approach, encompassing HM pollution indices, Human Health Risk Assessment (HHRA), Monte Carlo Simulation (MCS), multivariate statistical analysis (MSA), and Geographic Information Systems (GIS), twenty samples of surface water were taken and subjected to analysis. The results demonstrated notable spatial variability, with the northwestern, southwestern, and western parts of the Sebou Basin showing higher contamination levels. Cu exhibited the highest hazard quotient for ingestion, while Cr exceeded the hazard index (HI) threshold in both age categories. Statistical analysis uncovered strong associations, particularly between As and Cr, while principal component analysis (PCA) detected two key factors explaining 74.44% of the overall variability. Pollution indices classified all samples as highly contaminated (HPI > 30), with 65% categorized as "seriously affected" (MI > 6). The HHRA results indicated a heightened non-carcinogenic risk for children and carcinogenic risks exceeding acceptable thresholds (TCR > 10[-4]), with Ni presenting the highest risk (TCR = 2.32 × 10[-3] for children). MCS results revealed that Cu and Cr pose potential risks, with Cu exceeding the safety threshold for ingestion in both adults and children. These results emphasize the urgent necessity for tailored strategies to reduce contamination and foster sustainable agricultural and environmental management practices.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Liu X, Zhai WH, Liu R, et al (2025)

Integrated multi-omics analyses of molecular pathways underlying microcystin-LR toxicity in the earthworm Eisenia fetida.

Ecotoxicology and environmental safety, 302:118724.

Contamination of soil with microcystin-LR (MC-LR) has emerged as a significant environmental concern, but its toxicological impacts and underlying mechanisms on soil-dwelling invertebrates are not yet fully elucidated. Here we employed a comprehensive strategy integrating histopathological, ultrastructural, biochemical, and multi-omics (metabolomics and proteomics) analyses to investigate the effects of MC-LR on Eisenia fetida, a model soil organism. MC-LR exposure induced dose-dependent structural damage to the epidermal and intestinal tissues, disrupting antioxidant systems while elevating detoxification enzyme activity. Metabolomic profiling identified 93 significantly altered metabolites in the earthworms following exposure to MC-LR at a concentration of 0.6 mg/kg, implicating pathways such as amino acid biosynthesis, protein digestion and absorption, ATP-binding cassette transporters, and aminoacyl-tRNA biosynthesis. Proteomic analysis showed that MC-LR affected distinct pathways, particularly those associated with nucleotide binding, calcium ion binding, ATP binding, cytoskeleton, and actin filament binding. Correlations between differentially expressed metabolites and differentially expressed proteins highlighted critical roles of amino acid biosynthesis, thiamine metabolism, glutathione metabolism, and longevity regulating in earthworms' defense against MC-LR toxicity. This study advances the understanding of molecular pathways underlying MC-LR-induced toxicity in soil invertebrates, providing valuable insights into its ecological impact and potential risks.

RevDate: 2025-08-26
CmpDate: 2025-08-26

Chiolerio A, Konkoli Z, A Adamatzky (2025)

Ecosystem-based reservoir computing. Hypothesis paper.

Bio Systems, 255:105525.

Reservoir computing (RC) has emerged as a powerful computational paradigm, leveraging the intrinsic dynamics of complex systems to process temporal data efficiently. Here we propose to extend RC into ecological domains, where the ecosystems themselves can function as computational reservoirs, exploiting their complexity and extreme degree of interconnectedness. This position paper explores the concept of ecosystem-based reservoir computing (ERC), examining its theoretical foundations, empirical evidence, and potential applications. We argue that ERC not only offers a novel approach to computation, but also provides insights into the computational capabilities inherent in ecological systems and offers a new paradigm for remote sensing applications.

RevDate: 2025-08-25
CmpDate: 2025-08-25

Ding TT, Du SL, Liang HY, et al (2025)

Data mining-based screening of prevalent mixture systems in aquatic environments: A case study of antibiotics in the Yangtze River Basin.

Ecotoxicology and environmental safety, 302:118568.

Chemical pollution in real-world environment often involves exposure to combinations of thousands of chemicals. However, due to the vast number of possible combinations, it is nearly impossible to conduct comprehensive mixture toxicity tests and risk assessments for all of them. This study applied frequent itemset mining, a technique traditionally used in market basket analysis, to develop a prevalent mixture system screening (PMSS) method for identifying combinations that frequently co-occur in the environment. PMSS enables efficient data mining of chemical concentrations, allowing for the identification of a small number of prevalent mixture systems from numerous theoretical possibilities. In this study, 16 antibiotics were detected in the Linjiang River and the Xuebu River. Using the PMSS method, 48 prevalent antibiotic combinations (PACs), primarily ranging from binary to septenary combinations, were identified in the Xuebu River and the Linjiang River. The PACs in the surface water presented acceptable ecological risks, whereas the PACs in the sediments exhibited moderate to even high ecological risks. Therefore, targeted risk management measures should be developed for the sediments to reduce the potential harm to benthic organisms. Additionally, a case study demonstrates the application of identified PACs in mixture design. This study provides essential methodological and material support for advancing research on mixture toxicity evaluation and risk assessment.

RevDate: 2025-08-23

Jia Y, Chen L, Jin LN, et al (2025)

Environmentally Relevant Levels of Ozone Enhance Klebsiella pneumoniae Pulmonary Colonization and Cross-Organ Translocation.

Environmental science & technology [Epub ahead of print].

Ozone (O3) is a major global air pollutant. Recent epidemiological studies have suggested links between O3 exposure and outbreaks of infectious diseases. However, whether environmentally relevant levels of O3 exacerbate the colonization and infection of airborne pathogens remains unclear. This study demonstrated that exposure to environmentally relevant levels of O3 (0.15 and 0.60 ppm) significantly enhanced pulmonary colonization of low-dose Klebsiella pneumoniae (1 × 10[3] CFU/mouse) in mice, which failed to colonize without O3 exposure. Unexpectedly, in vivo and in vitro coculture experiments with BEAS-2B bronchial epithelial cells demonstrated that O3 exposure also enhanced the ability of K. pneumoniae to penetrate the lung-blood barrier, thereby inducing bacteremia that spread to the liver and caused severe liver injury. O3 exposure reduced the proportions of T cells, B cells, and macrophages in the lungs and altered the expression of key pulmonary genes (Tlr4, Il-18, Traf6, and Tgf-β1) involved in resisting K. pneumoniae colonization. In addition, lipid peroxidation product MDA in plasma acted as a mediator in the signal transmission along the lung-liver axis. This study underscores the critical role of air pollutants in pathogen colonization and infection, emphasizing the urgent need to address air quality to mitigate respiratory health risks.

RevDate: 2025-08-22
CmpDate: 2025-08-23

Lu M, Wang S, Zhou Y, et al (2025)

Multi-omics profiling reveals single-seed mutants of Ephedra saxatilis as dominant variants in high-altitude Xizang.

BMC plant biology, 25(1):1118.

Ephedra species, important Tibetan medicinal plants, are widely distributed across the Qinghai-Tibet Plateau at altitudes of 2700-5000 m. Their adaptation to high-altitude environments, such as low temperatures, strong UV radiation and low oxygen, is still poorly understood. This study investigated the morphological, metabolic, and genetic mechanisms underlying the reproductive advantage of a unique single-seed variant observed in high-germination-rate Ephedra species. Seeds from six Ephedra species were collected for germination assays and electron microscopic analysis. Results showed that E. saxatilis, E. intermedia, and E. monosperma exhibited significantly higher germination rates (Germination rates > 65%) and predominantly produced single-seed variants, while others mainly produced double seeds. Analysis of burr and fold numbers of phenotypic traits showed a significant positive correlation with germination rates. Time-course metabolomics analysis identified 762 KEGG annotated metabolites, and revealed E. saxatilis as the dominant species due to its faster metabolic rate, particularly simulated high-altitude conditions. Absolute hormone quantification highlighted the single-seed variant of E. saxatilis as the dominant type, with ABA content peaking in the shed seed coat. ABA exhibited antagonistic interactions with 2MeScZR, SA, IAA, GA7, IPR, and t-CA, suggesting a complex hormonal regulation network. Co-expression network analysis integrating transcriptome and hormone data predicted 23 key genes regulating seed germination adaptation. This study provides novel insights into the ecological and evolutionary significance of single-seed variation in high-altitude adaptation. The findings have potential applications in high-altitude plant breeding, conservation, and sustainable utilization of Ephedra species. Future research should focus on the genetic basis of single-seed variation and its role in other high-altitude plant species.

RevDate: 2025-08-22

Xia K, Hu Y, Cai S, et al (2025)

GastritisMIL: An interpretable deep learning model for the comprehensive histological assessment of chronic gastritis.

Patterns (New York, N.Y.), 6(8):101286.

The comprehensive histological assessment of chronic gastritis is imperative for guiding endoscopic follow-up strategies and surveillance of early-stage gastric cancer, yet rapid and objective assessment remains challenging in clinical workflows. We propose a powerful deep learning model (GastritisMIL) to effectively identify pathological alterations on H&E-stained biopsy slides, thereby expediting pathologists' evaluation and improving decision-making regarding follow-up intervals. We have trained and tested GastritisMIL by using retrospective data from 2,744 patients and evaluated discriminative performance across three medical centers (467 patients). GastritisMIL attained areas under the receiver operating curve greater than 0.971 in four tasks (inflammation, activity, atrophy, and intestinal metaplasia) and superior performance comparable to that of two senior pathologists. Specifically, interpretable attention heatmaps generated by GastritisMIL effectively assist junior pathologists in locating suspicious lesion regions across the entire field and minimizing missed diagnosis risk. Moreover, the high generalizability of this developed model across multiple external cohorts demonstrates its potential translational value.

RevDate: 2025-08-22
CmpDate: 2025-08-22

Wang M, Hu Q, Tu Z, et al (2025)

A Drosophila single-cell 3D spatiotemporal multi-omics atlas unveils panoramic key regulators of cell-type differentiation.

Cell, 188(17):4734-4753.e31.

The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D-v2, a comprehensive multi-omics atlas of the model organism Drosophila spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. Through the integration of multimodal data, we generated developmentally continuous in silico 3D models of the entire organism. We further constructed tissue development trajectories that uncover the detailed profiles of cell-type differentiation. With a focus on the midgut, we identified transcription factors involved in midgut cell-type regulation and validated exex as a key regulator of copper cell development. This extensive atlas provides a rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at ultra-high spatiotemporal resolution.

RevDate: 2025-08-21

De Rovere F, Mastropierro M, Jungclaus JH, et al (2025)

Future Atlantification of the European Arctic limited under sustained global warming.

Scientific reports, 15(1):30802.

Atlantification is an ongoing oceanic phenomenon characterised by the expansion of the typical Atlantic domain towards the Arctic, driving rapid oceanic and ecological changes in the European Arctic. Using reanalyses and a multi-model ensemble of unperturbed and transient preindustrial, historical and future-scenario simulations, this study shows that modern Atlantification possibly initiated in the late nineteenth century, preceded by several "Arctification" episodes in the preindustrial millennium. In the historical period, Atlantification and pan-Arctic warming superposed constructively to drive upper-ocean warming and salinification in the Barents Sea. Modern Atlantification is projected to continue in the next few decades, fully revealing its exceptional character in the context of the past millennium. However, Atlantification halts during the second half of the twenty-first century, decoupling from pan-Arctic warming. The northward expansion of the Atlantic domain is hindered by the onset of a damping mechanism where the Atlantic-Arctic density gradient increases progressively, which sustains a countercurrent by baroclinic adjustment pushing the Arctic polar front southward. As the evolution of this density gradient is intertwined with the retreat of the sea-ice edge, a late-summer ice-free Barents Sea may mark the end of modern Atlantification.

RevDate: 2025-08-21

Sena AVDS, Telles L, Melo PHM, et al (2025)

The management of cryptorchidism in Brazil: An ecological overview.

Journal of pediatric urology pii:S1477-5131(25)00410-3 [Epub ahead of print].

INTRODUCTION: Cryptorchidism refers to the extra-scrotal location of the testicle and is the most common male genital anomaly. Although the recommended age ranges for both hormonal and surgical treatments are well-established, within the Brazilian Unified Health System (SUS), children with cryptorchidism undergo surgery at varying ages across the country. As a time-sensitive procedure, delayed orchidopexy has consequences such as an increased risk of infertility or even testicular cancer. Correlating data on cryptorchidism treatment in SUS with geographic and socioeconomic indicators may help to understand how a population's profile influences the public healthcare system. This study explores the potential relationship between the age at which orchiopexy is performed and the quality of public healthcare services in Brazil while also assessing the impact of the COVID-19 pandemic on this surgery's backlog.

METHODS: To achieve this, we collected data from the Department of Informatics of the Brazilian Public Health System (DATASUS) and indicators provided by the Brazilian Institute of Geography (IBGE) and the Institute for Applied Economic Research (IPEA). We cataloged and compiled the data for comprehensive analysis.

RESULTS: Between 2008 and 2022, 94,237 orchiopexies were performed in SUS in patients aged 0-15. Nationwide, this represents only 47.6 % of the expected procedures, ranging from 22.75 % in the North to 68.18 % in the South. The proportion of surgeries performed before age 2 was very low, ranging from 12 % in the North and Northeast to 24 % in the South. Most orchiopexies in Brazil were performed after the age of five. The COVID-19 pandemic significantly worsened this situation, causing a 44.45 % decline in surgeries in 2020 compared to 2019, disproportionately affecting all age groups and exacerbating the backlog of surgeries.

CONCLUSION: Our study indicates that many children with cryptorchidism remain undiagnosed or receive delayed treatment. The COVID-19 pandemic further worsened this scenario, temporarily reducing the number of operations. These findings underscore the urgent need for comprehensive public policies to improve healthcare access and prevent complications associated with untreated cryptorchism.

RevDate: 2025-08-21

Boyes D, Fletcher C, Phillips D, et al (2025)

The genome sequence of the Tortix moth, Archips podanus (Scopoli, 1763).

Wellcome open research, 10:189.

We present a genome assembly from a male specimen of Archips podanus (Tortix moth; Arthropoda; Insecta; Lepidoptera; Tortricidae). The genome sequence has a total length of 549.00 megabases. Most of the assembly (99.72%) is scaffolded into 30 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled, with a length of 15.45 kilobases.

RevDate: 2025-08-19
CmpDate: 2025-08-19

McKnight JC, Solms B, Jensen M, et al (2025)

Diving behaviour and physiology of the Korean Haenyeo.

Current biology : CB, 35(16):R797-R798.

There is a long history of breath-hold diving cultures in East Asia, with references in Japanese chronicles as early as the third century BC. Given evidence of genetic adaptations for phenotypes associated with enhanced diving capacity within such populations[1], it is likely they hold the most prodigious human diving abilities - abilities that may be akin to semi-aquatic mammals, and even some marine mammals. Yet, a dearth of fine-scale information exists on the combined natural diving behaviour and physiological responses within these diving populations. One such extraordinary population is the all-female Haenyeo. Here, we assess the fine-scale diving behaviours and physiological responses of these women during natural harvest diving. Our results show that Haenyeo divers demonstrate the highest proportions of time underwater of any humans, also exceeding those of semi-aquatic mammals and being comparable with some marine mammals. Additionally, they do not exhibit an overt cardiovascular depression, or 'dive response', classically associated with consummate diving mammals.

RevDate: 2025-08-19

Chung J, Moloney ME, Seixas AA, et al (2025)

The Environment Around the Sleeper is Changing: A Perspective.

Sleep pii:8237930 [Epub ahead of print].

Sleep is shaped by a complex interplay of biological, behavioral, and environmental factors. While substantial attention has been paid to the first two factors, the role of environmental exposures, particularly weather patterns, ambient temperature variability, and other dynamic atmospheric conditions, remains relatively underexplored in sleep research. This gap is notable given the increasing availability of high-resolution environmental data and growing evidence that ambient conditions can influence circadian regulation, thermal comfort, and sleep continuity. This perspective paper reviews emerging evidence linking environmental factors to sleep patterns, highlighting both direct effects (e.g., thermal disruptions) and indirect pathways (e.g., displacement or stress from extreme weather events). Recent advances in environmental sensing, geospatial data, and real-time monitoring offer new opportunities to capture high-resolution environmental data relevant to sleep. This perspective highlights the need for data infrastructure capable of integrating these dynamic environmental inputs with sleep metrics from, for instance, wearables, surveys, and clinical records. We also examine the methodological and informatics challenges of integrating environmental data with sleep measures and suggest directions for future research. As environmental conditions evolve, understanding their influence on sleep holds promise for advancing both scientific knowledge and public health relevance, particularly in identifying affected populations, designing responsive interventions, and contextualizing sleep within broader ecological systems.

RevDate: 2025-08-18

Tarandek A, Boštjančić LL, Francesconi C, et al (2025)

Characterisation of the noble crayfish immune response to oomycete-derived immunostimulants.

Fish & shellfish immunology pii:S1050-4648(25)00555-8 [Epub ahead of print].

The invasive oomycete pathogen Aphanomyces astaci significantly threatens native European crayfish populations, prompting investigations towards the effects of protective immunostimulation on the immune response of the vulnerable noble crayfish (Astacus astacus). Here, we evaluate the effect of three oomycete-derived immunostimulant treatments: laminarin (β-1,3-glucan found within the Ap. astaci cell wall), inactivated Ap. astaci spores and Ap. astaci hyphal homogenate. Our findings reveal immediate changes in the noble crayfish total haemocyte count (THC), differential haemocyte count (DHC), and gene expression. A short-term increase in the THC was observed in all treatments, with a gradual return to normal values eight hours post immunostimulation. Granular haemocytes seem to be involved in response to immunostimulation with inactivated Ap. astaci spores, while the number of semi-granular and hyaline haemocytes increased in response to laminarin and Ap. astaci hyphal homogenate. Analysis of the differentially expressed genes showed that the prophenoloxidase pathway genes and Toll pathway genes are involved in the response to oomycete-derived immunostimulants. Prolonged effects of immunostimulation were reflected in the decreased C/EBP and Kr-h1 gene expression in the hyphal homogenate group as well as decreased Kr-h1 expression in the spore group. Taken together, our results indicate that immunostimulation causes a dynamic change in the noble crayfish immune system response, with similarities in the gene expression patterns between immunostimulated and Ap. astaci infected noble crayfish. As a future research focus, we highlight the importance of molecular characterisation of the genes involved in the anti-oomycete response which could provide valuable insights into pathogen resistance in freshwater crayfish. In the context of the Ap. astaci mediated downfall of the noble crayfish stocks across Europe, further exploration is needed regarding the benefits of the oomycete-derived immunostimulation that can potentially support conservation and aquacultural efforts.

RevDate: 2025-08-16

Poudel B, Xie J, Guo C, et al (2025)

Real-time oil spill concentration assessment through fluorescence imaging and deep learning.

Journal of hazardous materials, 496:139374 pii:S0304-3894(25)02290-3 [Epub ahead of print].

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R[2] score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

RevDate: 2025-02-25

Plaitano EG, McNeish D, Bartels SM, et al (2025)

Adherence to a digital therapeutic mediates the relationship between momentary self-regulation and health risk behaviors.

Frontiers in digital health, 7:1467772.

INTRODUCTION: Smoking, obesity, and insufficient physical activity are modifiable health risk behaviors. Self-regulation is one fundamental behavior change mechanism often incorporated within digital therapeutics as it varies momentarily across time and contexts and may play a causal role in improving these health behaviors. However, the role of momentary self-regulation in achieving behavior change has been infrequently examined. Using a novel momentary self-regulation scale, this study examined how targeting self-regulation through a digital therapeutic impacts adherence to the therapeutic and two different health risk behavioral outcomes.

METHODS: This prospective interventional study included momentary data for 28 days from 50 participants with obesity and binge eating disorder and 50 participants who smoked regularly. An evidence-based digital therapeutic, called Laddr™, provided self-regulation behavior change tools. Participants reported on their momentary self-regulation via ecological momentary assessments and health risk behaviors were measured as steps taken from a physical activity tracker and breathalyzed carbon monoxide. Medical regimen adherence was assessed as daily Laddr usage. Bayesian dynamic mediation models were used to examine moment-to-moment mediation effects between momentary self-regulation subscales, medical regimen adherence, and behavioral outcomes.

RESULTS: In the binge eating disorder sample, the perseverance [β 1 = 0.17, 95% CI = (0.06, 0.45)] and emotion regulation [β 1 = 0.12, 95% CI = (0.03, 0.27)] targets of momentary self-regulation positively predicted Laddr adherence on the following day, and higher Laddr adherence was subsequently a positive predictor of steps taken the same day for both perseverance [β 2 = 0.335, 95% CI = (0.030, 0.717)] and emotion regulation [β 2 = 0.389, 95% CI = (0.080, 0.738)]. In the smoking sample, the perseverance target of momentary self-regulation positively predicted Laddr adherence on the following day [β = 0.91, 95% CI = (0.60, 1.24)]. However, higher Laddr adherence was not a predictor of CO values on the same day [β 2 = -0.09, 95% CI = (-0.24, 0.09)].

CONCLUSIONS: This study provides evidence that a digital therapeutic targeting self-regulation can modify the relationships between momentary self-regulation, medical regimen adherence, and behavioral health outcomes. Together, this work demonstrated the ability to digitally assess the transdiagnostic mediating effect of momentary self-regulation on medical regimen adherence and pro-health behavioral outcomes.

CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier (NCT03774433).

RevDate: 2025-08-18
CmpDate: 2024-04-23

Vigna-Taglianti FD, Martorana M, Viola E, et al (2024)

Evaluation of Effectiveness of the Unplugged Program on Gambling Behaviours among Adolescents: Study Protocol of the Experimental Controlled Study "GAPUnplugged".

Journal of prevention (2022), 45(3):405-429.

Gambling risk behaviour is an emerging problem among adolescents. "Unplugged" is an effective Social Influence curriculum for preventing substance use among students. This study aims to develop and test a new component focused on gambling added to the Unplugged program. Schools of Piedmont region and Rome city were invited to participate in the study. A self-completed anonymous questionnaire including questions on socio-demographic characteristics, addictive behaviours, beliefs, attitudes and risk perceptions about gambling, normative perceptions, parental practices, school climate, refusal skills, impulsiveness, self-esteem, antisocial behaviours and sensation seeking was prepared for baseline and follow-up surveys. The protocol of the study was submitted and approved by the Novara Ethical Committee and registered in ClinicalTrials.gov (NCT05630157, Protocol ID: 080.742, 11/17/2022). Twenty-nine schools accepted to participate in the study. Sixty-three classes (1325 students) satisfied the eligibility criteria for intervention and were allocated to the intervention arm, and the other 61 (1269 students) were allocated to the control arm. Because of drop-out, absentees, refusals, and invalid questionnaires, data on 1874 students (998 in the intervention and 876 in the control arm), were available for the analysis at baseline. Data management of follow-up questionnaires is in progress. Results of the present study will be useful to clarify the effectiveness of prevention interventions in reducing gambling behaviours among adolescents. Moreover, this will be the first experience of evaluating a new component focused on a different risk behaviour, added to a curriculum previously shown as effective on other risk behaviours.

RevDate: 2022-11-22

Scherer EA, Metcalf SA, Whicker CL, et al (2022)

Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder.

Frontiers in digital health, 4:798895.

INTRODUCTION: Self-regulation has been implicated in health risk behaviors and is a target of many health behavior interventions. Despite most prior research focusing on self-regulation as an individual-level trait, we hypothesize that self-regulation is a time-varying mechanism of health and risk behavior that may be influenced by momentary contexts to a substantial degree. Because most health behaviors (e.g., eating, drinking, smoking) occur in the context of everyday activities, digital technologies may help us better understand and influence these behaviors in real time. Using a momentary self-regulation measure, the current study (which was part of a larger multi-year research project on the science of behavior change) used ecological momentary assessment (EMA) to assess if self-regulation can be engaged and manipulated on a momentary basis in naturalistic, non-laboratory settings.

METHODS: This one-arm, open-label exploratory study prospectively collected momentary data for 14 days from 104 participants who smoked regularly and 81 participants who were overweight and had binge-eating disorder. Four times per day, participants were queried about momentary self-regulation, emotional state, and social and environmental context; recent smoking and exposure to smoking cues (smoking sample only); and recent eating, binge eating, and exposure to binge-eating cues (binge-eating sample only). This study used a novel, momentary self-regulation measure comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Participants were also instructed to engage with Laddr, a mobile application that provides evidence-based health behavior change tools via an integrated platform. The association between momentary context and momentary self-regulation was explored via mixed-effects models. Exploratory assessments of whether recent Laddr use (defined as use within 12 h of momentary responses) modified the association between momentary context and momentary self-regulation were performed via mixed-effects models.

RESULTS: Participants (mean age 35.2; 78% female) in the smoking and binge-eating samples contributed a total of 3,233 and 3,481 momentary questionnaires, respectively. Momentary self-regulation subscales were associated with several momentary contexts, in the combined as well as smoking and binge-eating samples. For example, in the combined sample momentary perseverance was associated with location, positively associated with positive affect, and negatively associated with negative affect, stress, and tiredness. In the smoking sample, momentary perseverance was positively associated with momentary difficulty in accessing cigarettes, caffeine intake, and momentary restraint in smoking, and negatively associated with temptation and urge to smoke. In the binge-eating sample, momentary perseverance was positively associated with difficulty in accessing food and restraint in eating, and negatively associated with urge to binge eat. While recent Laddr use was not associated directly with momentary self-regulation subscales, it did modify several of the contextual associations, including challenging contexts.

CONCLUSIONS: Overall, this study provides preliminary evidence that momentary self-regulation may vary in response to differing momentary contexts in samples from two exemplar populations with risk behaviors. In addition, the Laddr application may modify some of these relationships. These findings demonstrate the possibility of measuring momentary self-regulation in a trans-diagnostic way and assessing the effects of momentary, mobile interventions in context. Health behavior change interventions may consider measuring and targeting momentary self-regulation in addition to trait-level self-regulation to better understand and improve health risk behaviors. This work will be used to inform a later stage of research focused on assessing the transdiagnostic mediating effect of momentary self-regulation on medical regimen adherence and health outcomes.

CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, Identifier: NCT03352713.

RevDate: 2021-07-28
CmpDate: 2021-06-11

Mascheroni A, Choe EK, Luo Y, et al (2021)

The SleepFit Tablet Application for Home-Based Clinical Data Collection in Parkinson Disease: User-Centric Development and Usability Study.

JMIR mHealth and uHealth, 9(6):e16304.

BACKGROUND: Parkinson disease (PD) is a common, multifaceted neurodegenerative disorder profoundly impacting patients' autonomy and quality of life. Assessment in real-life conditions of subjective symptoms and objective metrics of mobility and nonmotor symptoms such as sleep disturbance is strongly advocated. This information would critically guide the adaptation of antiparkinsonian medications and nonpharmacological interventions. Moreover, since the spread of the COVID-19 pandemic, health care practices are being reshaped toward a more home-based care. New technologies could play a pivotal role in this new approach to clinical care. Nevertheless, devices and information technology tools might be unhandy for PD patients, thus dramatically limiting their widespread employment.

OBJECTIVE: The goals of the research were development and usability evaluation of an application, SleepFit, for ecological momentary assessment of objective and subjective clinical metrics at PD patients' homes, and as a remote tool for researchers to monitor patients and integrate and manage data.

METHODS: An iterative and user-centric strategy was employed for the development of SleepFit. The core structure of SleepFit consists of (1) an electronic finger-tapping test; (2) motor, sleepiness, and emotional subjective scales; and (3) a sleep diary. Applicable design, ergonomic, and navigation principles have been applied while tailoring the application to the specific patient population. Three progressively enhanced versions of the application (alpha, v1.0, v2.0) were tested by a total of 56 patients with PD who were asked to perform multiple home assessments 4 times per day for 2 weeks. Patient compliance was calculated as the proportion of completed tasks out of the total number of expected tasks. Satisfaction on the latest version (v2.0) was evaluated as potential willingness to use SleepFit again after the end of the study.

RESULTS: From alpha to v1.0, SleepFit was improved in graphics, ergonomics, and navigation, with automated flows guiding the patients in performing tasks throughout the 24 hours, and real-time data collection and consultation were made possible thanks to a remote web portal. In v2.0, the kiosk-mode feature restricts the use of the tablet to the SleepFit application only, thus preventing users from accidentally exiting the application. A total of 52 (4 dropouts) patients were included in the analyses. Overall compliance (all versions) was 88.89% (5707/6420). SleepFit was progressively enhanced and compliance increased from 87.86% (2070/2356) to 89.92% (2899/3224; P=.04). Among the patients who used v2.0, 96% (25/26) declared they would use SleepFit again.

CONCLUSIONS: SleepFit can be considered a state-of-the-art home-based system that increases compliance in PD patients, ensures high-quality data collection, and works as a handy tool for remote monitoring and data management in clinical research. Thanks to its user-friendliness and modular structure, it could be employed in other clinical studies with minimum adaptation efforts.

TRIAL REGISTRATION: ClinicalTrials.gov NCT02723396; https://clinicaltrials.gov/ct2/show/NCT02723396.

RevDate: 2024-01-09
CmpDate: 2013-04-09

Wang C, Schroeder KB, NA Rosenberg (2012)

A maximum-likelihood method to correct for allelic dropout in microsatellite data with no replicate genotypes.

Genetics, 192(2):651-669.

Allelic dropout is a commonly observed source of missing data in microsatellite genotypes, in which one or both allelic copies at a locus fail to be amplified by the polymerase chain reaction. Especially for samples with poor DNA quality, this problem causes a downward bias in estimates of observed heterozygosity and an upward bias in estimates of inbreeding, owing to mistaken classifications of heterozygotes as homozygotes when one of the two copies drops out. One general approach for avoiding allelic dropout involves repeated genotyping of homozygous loci to minimize the effects of experimental error. Existing computational alternatives often require replicate genotyping as well. These approaches, however, are costly and are suitable only when enough DNA is available for repeated genotyping. In this study, we propose a maximum-likelihood approach together with an expectation-maximization algorithm to jointly estimate allelic dropout rates and allele frequencies when only one set of nonreplicated genotypes is available. Our method considers estimates of allelic dropout caused by both sample-specific factors and locus-specific factors, and it allows for deviation from Hardy-Weinberg equilibrium owing to inbreeding. Using the estimated parameters, we correct the bias in the estimation of observed heterozygosity through the use of multiple imputations of alleles in cases where dropout might have occurred. With simulated data, we show that our method can (1) effectively reproduce patterns of missing data and heterozygosity observed in real data; (2) correctly estimate model parameters, including sample-specific dropout rates, locus-specific dropout rates, and the inbreeding coefficient; and (3) successfully correct the downward bias in estimating the observed heterozygosity. We find that our method is fairly robust to violations of model assumptions caused by population structure and by genotyping errors from sources other than allelic dropout. Because the data sets imputed under our model can be investigated in additional subsequent analyses, our method will be useful for preparing data for applications in diverse contexts in population genetics and molecular ecology.

RevDate: 2025-08-18

Piršelová B, J Jakubčinová (2025)

Plant cyanogenic glycosides: from structure to properties and potential applications.

Frontiers in plant science, 16:1612132.

Cyanogenic glycosides (CGs) represent an important group of secondary metabolites predominantly of plant origin, characterized by their ability to release hydrogen cyanide upon enzymatic hydrolysis. These compounds are widely distributed across the plant kingdom, where they play a crucial role in defense against herbivores and pathogens. In recent years, advanced analytical tools have greatly expanded our knowledge of CGs by enabling the identification of less abundant forms. Based on the latest data from published scientific studies, this review presents a comprehensive overview of CGs, with a focus on their structural variability, biosynthetic pathways, ecological functions, and inherent toxicity. Special attention is given to the quantity and distribution of significant CGs in plants, as the available data is often heterogeneous, fragmented, and dispersed across the literature. Furthermore, the review explores emerging evidence regarding the biomedical relevance of selected CGs, including their putative anticancer properties and broader therapeutic potential. The findings presented in this review may be applied in fields such as pharmacology, toxicology, food safety, and plant biotechnology - either to enhance CG content for crop protection or, conversely, to eliminate such content in order to improve food safety.

RevDate: 2025-08-18

Motlagh SH, Momtazi F, H Saeedi (2025)

Senckenberg dogger bank long-term monitoring: First dataset on amphipods.

Data in brief, 62:111931 pii:S2352-3409(25)00655-9.

This dataset includes unique occurrence records of amphipod specimens collected during the 2024 annual Senckenberg Long-Term Monitoring Project in Dogger Bank (a shallow sand bank in the central North Sea), Cruise DOG24. This cruise was part of an ongoing effort to monitor biodiversity, which has occurred annually from 1991 to 2024 by the Marine Zoology Department at the Senckenberg Research Institute and Natural History Museum. Amphipods, key components of marine benthic ecosystems, were sampled by beam trawl over the Dogger Bank's stable sandy substrate. A total of 8444 specimens of ten species belonging to 13 families and 14 genera were identified using morphological methods with Leica M60 and DM750 microscopes. This study presents the first species-level identification of benthic amphipods in the Dagger Bank, providing a taxonomically resolved dataset that serves as a reliable identification key for future monitoring efforts in the area. Data were structured and published to the Ocean Biodiversity Information System (OBIS) and the Global Biodiversity Information Facility (GBIF) following the Darwin Core (DwC) standard. This dataset is the first-hand data ever published open-access from the Senckenberg Long Term Monitoring Project since 1991. This dataset also supports a broader research project aimed at (i) revealing the distribution pattern of amphipods in the North Sea, (ii) identifying environmental drivers of species distribution and diversity, and (iii) evaluating the response of the amphipod community to ecosystem changes.

RevDate: 2025-08-18

Rajpal H, Stengel CV, Mediano PAM, et al (2025)

Information dynamics and the emergence of high-order individuality in ecosystems.

Communications biology, 8(1):1231.

At what level does natural selection occur? When considering the reproductive dynamics of interacting and mutating agents, it has long been debated whether selection is better understood by focusing on the individual or if hierarchical selection emerges as a consequence of joint adaptation. Despite longstanding efforts in theoretical ecology, there is still no consensus on this fundamental issue, most likely due to the difficulty in obtaining adequate data spanning a sufficient number of generations and the lack of adequate tools to quantify the effect of hierarchical selection. Here, we capitalise on recent advances in information-theoretic data analysis to advance this state of affairs by investigating the emergence of high-order structures- such as groups of species- in the collective dynamics of the Tangled Nature model of evolutionary ecology. Our results show that evolutionary dynamics can lead to clusters of species that act as a self-perpetuating group that exhibits greater information-theoretic agency than a single species for a broad range of stable mutation rates. However, this higher-order organization breaks down for mutation rates close to the error threshold, where increased information processing is observed at the level of a single species. For mutation rates higher than the error threshold, no stable population of species are observed in time, and all individuality is lost in the ecosystem. Overall, our findings provide quantitative evidence supporting the emergence of higher-order structures in evolutionary ecology from relatively simple processes of adaptation and reproduction.

RevDate: 2025-08-15

Xu Z, Xu D, Ma J, et al (2025)

The risk assessment for metal(loid)s in soil-slag mixing systems: Coupling sequential extraction, leaching tests, and in vitro bioaccessibility assays.

Journal of hazardous materials, 496:139544 pii:S0304-3894(25)02463-X [Epub ahead of print].

The metals and metalloids (metal[loid]s) in the newly formed soil-slag mixing systems (SSMS), formed by the invasion of smelting slag into contaminated soils, may pose potential risks to environment and residents near the smelter sites. In this study, sequential extraction, leaching tests and in vitro bioaccessibility assays were conducted to assess the ecological and human health risk of metal(loid)s in SSMS. The results indicated that the contaminated soils and smelting slags were composed of more than 80 % silicate and oxide minerals, which served as the host phases for metal(loid)s in SSMS. Cd exhibited high mobility and availability, with its exchangeable fraction ranging from 0.15 % to 69.23 %. Leaching tests revealed high leachability and bioavailability of Cd, Mn and Zn. Moreover, metal(loid)s bioaccessibility varied amongst samples: 2.78-46.63 % of As, 11.87-95.25 % of Cd, 37.35-93.88 % of Mn, 1.97-87.84 % of Pb and 0-57.98 % of Zn. Risk assessment calculation results indicated potentially ecological risks posed by Cd, Mn, Pb, and Zn, and unfavorable carcinogenic risks associated with As and Cd, suggesting that remediation efforts were warranted. Overall, this study highlighted how the invasion of smelting slags can affect the accuracy of risk assessments, providing new guidance for risk control and environmental management at slag dumping sites.

RevDate: 2025-08-15

Misono S, Nguyen-Feng VN, Lei X, et al (2025)

Ecological Momentary Assessment of Voice & Psychological Factors: Group & Individual Mechanisms.

The Laryngoscope [Epub ahead of print].

OBJECTIVES: Cross-sectional associations between voice and psychological factors are known, but changes over time offer opportunities to refine our understanding of their interactions and consider customized treatment options. Study objectives were to measure relationships between voice and psychological factors using ecological momentary assessment and applying (1) group-level time series analysis and (2) group and (3) individual causal modeling to identify key psychological factors relevant for voice outcomes.

METHODS: Adults (N = 32) with primary muscle tension dysphonia completed multiple assessments daily for 10 days. Measures included items from the Voice Handicap Index-10, voice-adapted perceived present control scale, items from NIH PROMIS and the NIH Toolkit to assess distress, and the Positive and Negative Affect Scale. Group-level time series analysis was conducted using dynamic structural equation modeling; causal analysis utilized the Greedy Fast Causal Inference algorithm.

RESULTS: In group-level time series analyses, neither perceived control nor distress predicted subsequent timepoint voice handicap scores. In group-level causal modeling, anxiety was causal for voice handicap, but perceived control was not. Individual-level analyses identified various causal factors for voice handicap including perceived control and negative affect, and to a lesser extent, serenity, anxiety, somatic arousal, and stress.

CONCLUSIONS: Group-level analyses may obscure important heterogeneity that is identifiable using individual-level causal analyses. For example, perceived control was not identified as predictive or causal for voice handicap at the group level; but was a salient causal factor for voice handicap in some individuals. Causal modeling using intensive longitudinal datasets offers a potential avenue for individualized treatment approaches.

RevDate: 2025-08-14

Lundberg DS, Bergelson J, Roux F, et al (2025)

Lab to field: Challenges and opportunities for plant biology.

Cell host & microbe, 33(8):1212-1216.

Plant-microbe research offers many choices of model and strain and whether a field-first or lab-first approach is best. However, differences between laboratory studies, offering control and repeatability, versus field experiments, revealing ecological relevance and environmental effects, should not be seen as failure but motivate further inquiry and allow complementary discovery.

RevDate: 2025-08-14

Shen S, Qi W, Zeng J, et al (2025)

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review.

Journal of medical Internet research, 27:e77066 pii:v27i1e77066.

BACKGROUND: Mental health issues have become a significant global public health challenge. Traditional assessments rely on subjective methods with limited ecological validity. Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring.

OBJECTIVE: This study aimed to provide a comprehensive review of the current state of passive sensing-based and ML technologies for mental health monitoring. We summarized the technical approaches, revealed the association patterns between behavioral features and mental disorders, and explored potential directions for future advancements.

METHODS: This scoping review adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines and was prospectively registered on the Open Science Framework. We systematically searched 7 databases (Web of Science, PubMed, IEEE Xplore, Embase, PsycINFO, Scopus, and ACM Digital Library) for studies published between January 2015 and February 2025. We included 42 peer-reviewed studies that used passive sensing from wearables or smartphones with ML to monitor clinically diagnosed mental disorders, such as depression and anxiety. Data were synthesized across technical dimensions (data collection, preprocessing, feature engineering, and ML models) and clinical associations, with behavioral features categorized into 8 domains.

RESULTS: The 42 included studies were predominantly cohort designs (23/42, 55%), with a median sample size of 60.5 (IQR 54-99). Most studies focused on depression (23/42, 55%) and anxiety (9/42, 21%) using primarily wrist-worn devices (32/42, 76%) collecting heart rate (28/42, 67%), movement index (25/42, 60%), and step count (17/42, 40%) as key biomarkers. Deep learning models (eg, convolutional neural networks and long short-term memory) showed high accuracy, while traditional ML (eg, random forest) remained prevalent due to better interpretability. We identified critical limitations, including small samples (32/42, 76% with N<100), short monitoring periods (19/42, 45% <7 days), scarce external validation (1/42, 2%), and limited reporting on data anonymization (6/42, 14%).

CONCLUSIONS: While passive sensing and ML demonstrate promising accuracy (eg, convolutional neural network-long short-term memory achieving 92.16% in anxiety detection), the evidence remains constrained by three key limitations: (1) methodological heterogeneity (32/42, 76% single-device studies; 19/42, 45% with <7-day monitoring), (2) high risk of bias from small samples (median 60.5, IQR 54-99 participants) and scarce external validation (1/42, 2%), and (3) ethical gaps (only 6/42, 14% addressing anonymization). These findings underscore the technology's potential to transform mental health care through objective, continuous monitoring-particularly for depression (heart rate and step count biomarkers) and anxiety (sleep and social interaction patterns). However, clinical translation requires standardized protocols, larger longitudinal studies (≥3 months), and ethical frameworks for data privacy. Future work should prioritize multimodal sensor fusion and explainable artificial intelligence to bridge the gap between technical performance and clinical deployability.

RevDate: 2025-08-17

Lu F, Yi B, Ma JX, et al (2025)

Drought and Shrub Encroachment Accelerate Peatland Carbon Loss Under Climate Warming.

Plants (Basel, Switzerland), 14(15):.

Peatlands store substantial amounts of carbon (C) in the form of peat, but are increasingly threatened by drought and shrub encroachment under climate warming. However, how peat decomposition and its temperature sensitivity (Q10) vary with depth and plant litter input under these stressors remains poorly understood. We incubated peat from two depths with different degrees of decomposition, either alone or incubated with Sphagnum divinum shoots or Betula ovalifolia leaves, under five temperature levels and two moisture conditions in growth chambers. We found that drought and Betula addition increased CO2 emissions in both peat layers, while Sphagnum affected only shallow peat. Deep peat alone or with Betula exhibited higher Q10 than pure shallow peat. Drought increased the Q10 of both depths' peat, but this effect disappeared with fresh litter addition. The CO2 production rate showed a positive but marginal correlation with microbial biomass carbon, and it displayed a rather similar responsive trend to warming as the microbial metabolism quotient. These results indicate that both deep and dry peat are more sensitive to warming, highlighting the importance of keeping deep peat buried and waterlogged to conserve existing carbon storage. Additionally, they further emphasize the necessity of Sphagnum moss recovery following vascular plant encroachment in restoring carbon sink function in peatlands.

RevDate: 2025-08-16

Jin L, Lu Y, Huang J, et al (2025)

Metabolism exploration of disinfection byproducts halonitromethanes (HNMs) by cytochrome P450 enzymes and toxicity evaluation.

Environmental research, 285(Pt 4):122575 pii:S0013-9351(25)01827-4 [Epub ahead of print].

The nitrogen-contained disinfection by-products, halonitromethanes (HNMs), are known for their high cytotoxicity and genotoxicity. Although HNMs can be metabolized by cytochrome P450 enzymes (P450s), the specific mechanism has remained unclear. To shed light on this, density functional theory (DFT) calculations were performed to elucidate the potential oxidative P450-catalytic activation of the nine HNMs. Our findings reveal that active species of P450s (Cpd I) predominantly react with halogen-substituted nitromethanes via hydrogen abstraction and bromine atom abstraction, rather than chlorosylation. As a result of these reactions, oxidized HNMs are produced and can undergo further hydrolysis, leading to nitro-formaldehyde, nitro formyl halogen, halogen hydride, hypobromous acid, and nitroformic acid. To experimentally validate the computational predictions, in vitro experiments were conducted on five typical nitromethanes using human liver microsomes and the results reveal that DCNM, BCNM and DBCNM form nitroformyl chlorine (NO2CClO), while BCNM, DBNM and TBNM are transferred into nitroformyl bromide (NO2CBrO). Nitroformic acid is also identified as a metabolite in the TBNM metabolism reaction. Toxicity assessment reveals that metabolic transformation leads to an overall reduction in the ecological toxicity. However, metabolites showed similar toxicity to Fathead minnow and even higher acute toxicity to rat, as well as larger probability of hERG inhibition effects than HNMs, underscoring the need for caution in health risk assessment. By integrating in silico and in vitro approaches, this work has provided a comprehensive understanding of the metabolism of HNMs and offered potential toxicity data basis of these compounds.

RevDate: 2025-08-15

Abraham AJ, Clauss M, Bailey MA, et al (2025)

Body Mass Scaling of Sodium Regulation in Mammals.

Acta physiologica (Oxford, England), 241(9):e70090.

RevDate: 2025-08-16

Kaplan DM, Alvarez SJA, Palitsky R, et al (2025)

Fabla: A voice-based ecological assessment method for securely collecting spoken responses to researcher questions.

Behavior research methods, 57(9):257.

This article reports on the validation of Fabla, a researcher-developed and university-hosted smartphone app that facilitates naturalistic and secure collection of participants' spoken responses to researcher questions. Fabla was developed to meet the need for tools that (a) collect longitudinal qualitative data and (b) capture speech biomarkers from participants' natural environments. This study put Fabla to its first empirical test using a repeated-measures experimental design in which participants (n = 87) completed a 1-week voice daily diary via the Fabla app, and an identical 1-week text-entry daily diary administered via Qualtrics, with diary method order counterbalanced and randomized. A preregistered analysis plan investigated (1) adherence, usability, and acceptability of Fabla, (2) concurrent validity of voice diaries (vs. text-entry diaries) by comparing linguistic features obtained via each diary method, and (3) differences in the strength of the association between linguistic features and their known psychological correlates when assessed by voice versus text-entry diary. Voice diaries yielded more than double the mean daily language volume (word count) compared to text-entry diaries and received high usability and acceptability ratings. Linguistic markers consistently associated with depression in prior research were significantly associated with depression symptoms when assessed via voice but not text-entry diaries, and the difference in correlation magnitude was significant. Word-count-adjusted linguistic patterns were highly correlated between diary methods, with statistically significant mean differences observed for some linguistic dimensions in the presence of these associations. Fabla is a promising tool for collecting high-quality speech data from participants' naturalistic environments, overcoming multiple limitations of text-entry responding.

RevDate: 2025-08-16

Arehart CH, Lin M, Gibson RA, et al (2025)

Modeling the genomic architecture of adiposity and anthropometrics across the lifespan.

Nature communications, 16(1):7494.

Obesity-related conditions are among the leading causes of preventable death and are increasing in prevalence worldwide. Body size and composition are complex traits that are challenging to characterize due to environmental and genetic influences, longitudinal variation, heterogeneity between sexes, and differing health risks based on adipose distribution. Here, we construct a 4-factor genomic structural equation model using 18 measures, unveiling shared and distinct genetic architectures underlying birth size, abdominal size, adipose distribution, and adiposity. Multivariate genome-wide associations reveal the adiposity factor is enriched specifically in neural tissues and pathways, while adipose distribution is enriched more broadly across physiological systems. In addition, polygenic scores for the adiposity factor predict many adverse health outcomes, while those for body size and composition predict a more limited subset. Finally, we characterize the factors' genetic correlations with obesity-related traits and examine the druggable genome by constructing a bipartite drug-gene network to identify potential therapeutic targets.

RevDate: 2025-08-16
CmpDate: 2025-08-12

Alkhatib SA, Arya S, Islayem D, et al (2025)

Revealing bioremediation potential of novel indigenous bacteria from oil-contaminated sites in the UAE: A combined bioinformatics and experimental validation.

PloS one, 20(8):e0329515.

Microbial biodegradation of recalcitrant aromatic hydrocarbon pollutants represents an environmentally sustainable strategy for remediating contaminated sites. However, elucidating the metabolic capabilities and genetic determinants of biodegrading strains is crucial for optimizing bioremediation strategies. In this study, we comprehensively characterize the aromatic catabolic potential of two indigenous bacterial isolates, A. xylosoxidans C2 (A. x. C2) and A. xylosoxidans KW38 (A. x. KW38), obtained from hydrocarbon-impacted environments in the United Arab Emirates (UAE). Experimental validation through aromatic hydrocarbons supplemented growth studies confirmed the capability of the isolated bacteria to mineralize bisphenol A, 4-hydroxybenzoic acid, 1-naphthalenemethanol, and the high molecular weight polycyclic aromatic hydrocarbon (PAH), pyrene, in the presence of glucose. Their degradation efficiencies were comparable to or greater than those of Pseudomonas paraeruginosa, a well-characterized model organism for aromatic compound degradation. Integrated bioinformatic analyses uncovered fundamental aromatic catabolic pathways conserved across Achromobacter species, along with strain-specific genes that potentially confer specialized degradative capacities, highlighting the genomic basis of the observed metabolic versatility. Further, protein modeling based on the curated sequences revealed unique features of individual catabolic enzymes and their interaction networks. Notably, a dehydrogenase enzyme involved in aromatic ring cleavage was identified exclusively in these UAE isolates. These findings establish A. x. C2 and A. x. KW38 as promising bioremediators of diverse aromatic pollutants. Overall, the study exemplifies a powerful and comprehensive methodological framework that bridges bioinformatic analysis and experimental research to further optimize the effectiveness of experimental design. We achieved a substantial reduction in the number of unknown genetic and metabolic determinants of aromatic hydrocarbon degradation in the strains, reducing uncertainty by 99.3%, thereby enhancing the overall process and outcomes for systematic biodiscovery of pollutant-degrading environmental microbes to address ecological challenges.

RevDate: 2025-08-12
CmpDate: 2025-08-11

Torres MC, Breyer GM, da Silva MERJ, et al (2025)

Metagenomic approaches for the quantification of antibiotic resistance genes in swine wastewater treatment system: a systematic review.

Molecular biology reports, 52(1):816.

This systematic review aims to identify the metagenomic methodological approaches employed for the detection of antimicrobial resistance genes (ARGs) in swine wastewater treatment systems. The search terms used were metagenome AND bacteria AND ("antimicrobial resistance gene" OR resistome OR ARG) AND wastewater AND (swine OR pig), and the search was conducted across the following electronic databases: PubMed, Scopus, ScienceDirect, Web of Science, Embase, and Cochrane Library. The search was limited to studies published between 2020 and 2024. Of the 220 studies retrieved, eight met the eligibility criteria for full-text analysis. The number of publications in this research area has increased in recent years, with China contributing the highest number of studies. ARGs are typically identified using bioinformatics pipelines that include steps such as quality trimming, assembly, metagenome-assembled genome (MAG) reconstruction, open reading frame (ORF) prediction, and ARG annotation. However, comparing ARGs quantification across studies remains challenging due to methodological differences and variability in quantification approaches. Therefore, this systematic review highlights the need for methodological standardization to facilitate comparison and enhance our understanding of antimicrobial resistance in swine wastewater treatment systems through metagenomic approaches.

RevDate: 2025-08-13

Boyes D, Gardiner A, University of Oxford and Wytham Woods Genome Acquisition Lab, et al (2025)

The genome sequence of the V-Pug moth, Chloroclystis v-ata (Haworth, 1809).

Wellcome open research, 10:197.

We present a genome assembly from a female specimen of Chloroclystis v-ata (V-Pug; Arthropoda; Insecta; Lepidoptera; Geometridae). The genome sequence has a total length of 275.35 megabases. Most of the assembly (99.95%) is scaffolded into 17 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled, with a length of 15.49 kilobases.

RevDate: 2025-08-08
CmpDate: 2025-08-09

Rauniyar S, Samanta D, Thakur P, et al (2025)

Mapping the pangenome of sulfate reducing bacteria: core genes, plasticity, and novel functions in Desulfovibrio spp.

World journal of microbiology & biotechnology, 41(8):305.

The pangenome of sulfate reducing bacteria represents a genetic reservoir that deciphers the intricate interplay of conserved and variable elements driving their ecological dominance, evolutionary adaptability, and industrial relevance. This study introduces the most comprehensive pangenome analysis of the genus Desulfovibrio till date, incorporating 63 complete and high-quality genomes using the Partitioned Pangenome Graph of Linked Neighbors (PPanGGOLiN) pipeline. The structure and dynamics of core gene families were investigated through gene ontology, KEGG pathway mapping, and gene network analyses, shedding light on the functional organization of the Desulfovibrio genomes. The analysis categorized 799, 4053, and 43,581 gene families into persistent, shell, and cloud groups, respectively. A core set of 326 gene families, conserved across Desulfovibrio genomes, highlights their essential role in community functionality. Genome plasticity analysis identified 4,576 regions of genome plasticity, with 1,322 hotspots enriched in horizontally acquired genes (89% in the cloud partition). Key gene families in these regions included glpE, fdhD, petC, and cooF, linked to sulfur metabolism. Out of 29 hypothetical genes, one was linked to actin nucleation, another contained a TRASH domain, while the other regulates filopodium assembly. Other predicted functions included lnrL, folE, RNA binding, and pyrG/pyrH involvement in CTP biosynthesis. Additionally, genomic islands revealed evolutionary events, such as cheY acquisition in Oleidesulfovibrio alaskensis G20. This study provides a genus-wide view of Desulfovibrio, emphasizing genome plasticity, hypothetical gene functions, and adaptation mechanisms.

RevDate: 2025-08-11

McDaniel JH, Patel V, Olson ND, et al (2025)

Correction: Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

Scientific data, 12(1):1385 pii:10.1038/s41597-025-05752-9.

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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.

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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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