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Bibliography on: Ecological Informatics

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

RJR: Recommended Bibliography 06 Jun 2025 at 01:47 Created: 

Ecological Informatics

Wikipedia: Ecological Informatics Ecoinformatics, or ecological informatics, is the science of information (Informatics) in Ecology and Environmental science. It integrates environmental and information sciences to define entities and natural processes with language common to both humans and computers. However, this is a rapidly developing area in ecology and there are alternative perspectives on what constitutes ecoinformatics. A few definitions have been circulating, mostly centered on the creation of tools to access and analyze natural system data. However, the scope and aims of ecoinformatics are certainly broader than the development of metadata standards to be used in documenting datasets. Ecoinformatics aims to facilitate environmental research and management by developing ways to access, integrate databases of environmental information, and develop new algorithms enabling different environmental datasets to be combined to test ecological hypotheses. Ecoinformatics characterize the semantics of natural system knowledge. For this reason, much of today's ecoinformatics research relates to the branch of computer science known as Knowledge representation, and active ecoinformatics projects are developing links to activities such as the Semantic Web. Current initiatives to effectively manage, share, and reuse ecological data are indicative of the increasing importance of fields like Ecoinformatics to develop the foundations for effectively managing ecological information. Examples of these initiatives are the National Science Foundation's Datanet , DataONE and Data Conservancy projects.

Created with PubMed® Query: ( "ecology OR ecological" AND ("data management" OR informatics) NOT "assays for monitoring autophagy" ) NOT pmcbook NOT ispreviousversion

Citations The Papers (from PubMed®)

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RevDate: 2025-05-30

He Y, Mulqueeney JM, Watt EC, et al (2024)

Opportunities and Challenges in Applying AI to Evolutionary Morphology.

Integrative organismal biology (Oxford, England), 6(1):obae036.

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the study of evolutionary morphology. While classical AI methods such as principal component analysis and cluster analysis have been commonplace in the study of evolutionary morphology for decades, recent years have seen increasing application of deep learning to ecology and evolutionary biology. As digitized specimen databases become increasingly prevalent and openly available, AI is offering vast new potential to circumvent long-standing barriers to rapid, big data analysis of phenotypes. Here, we review the current state of AI methods available for the study of evolutionary morphology, which are most developed in the area of data acquisition and processing. We introduce the main available AI techniques, categorizing them into 3 stages based on their order of appearance: (1) machine learning, (2) deep learning, and (3) the most recent advancements in large-scale models and multimodal learning. Next, we present case studies of existing approaches using AI for evolutionary morphology, including image capture and segmentation, feature recognition, morphometrics, and phylogenetics. We then discuss the prospectus for near-term advances in specific areas of inquiry within this field, including the potential of new AI methods that have not yet been applied to the study of morphological evolution. In particular, we note key areas where AI remains underutilized and could be used to enhance studies of evolutionary morphology. This combination of current methods and potential developments has the capacity to transform the evolutionary analysis of the organismal phenotype into evolutionary phenomics, leading to an era of "big data" that aligns the study of phenotypes with genomics and other areas of bioinformatics.

RevDate: 2025-06-05
CmpDate: 2025-06-05

Broel N, Daumüller F, Ali A, et al (2025)

Unravelling the enzymatic wood decay repertoire of Cerrena zonata: A multi-omics approach.

Microbiological research, 298:128214.

Lignocellulosic biomass (LCB), such as wheat straw, bagasse, or wood, is a cost-effective, sustainable carbon source but remains challenging to utilize due to the recalcitrance of lignin, which hinders efficient carbohydrate hydrolysis. Effective LCB degradation demands a wide range of enzymes, and commercial enzyme cocktails often require physical or chemical pretreatments. A fully enzymatic degradation could drastically improve the efficiency of these processes. Basidiomycota fungi naturally possess diverse enzymes suited for LCB breakdown. The white-rot fungus Cerrena zonata, a member of the phylum Basidiomycota, was analyzed for its Carbohydrate-Active Enzymes (CAZymes) using a multi-omics approach. Genomic and transcriptomic analyses of C. zonata identified 20,816 protein-encoding genes, including 487 CAZymes (2.3 %). Cultivating C. zonata with and without LCB addition revealed a total of 147 proteins, of which 36 were CAZymes (13 auxiliary activities (AA), 3 carbohydrate esterases, and 20 glycoside hydrolases). In accordance, laccase, manganese peroxidase (MnP) as well as versatile peroxidase (VP) activities were detected in the fungal culture supernatants. Furthermore, relevant enzymes were visualized via zymography. Consistent with these results, five putative peroxidases (AA2) and three putative laccases (AA1_1) were identified in all -omics dimensions. Further structure and sequence analysis of AA2 proteins supports that two proteins were classified as VPs and three as MnPs, based on their active and Mn[2 +] binding sites. In summary, C. zonata possesses a broad enzyme spectrum expressed under varied conditions, highlighting its potential for identifying efficient lignin-degrading enzymes for enzymatic pretreatment of food industry side streams and other LCBs.

RevDate: 2025-06-05
CmpDate: 2025-06-05

Sun Z, Zhang F, Zhong N, et al (2025)

Genome sequence resources for three strains of the genus Clonostachys.

BMC genomic data, 26(1):8.

OBJECTIVE: Clonostachys, a genus with rich morphological and ecological diversity in Bionectriaceae, has a wide distribution among diverse habitats. Several studies have reported Clonostachys fungi as effective biological agents against multiple fungal plant pathogens. To clarify the diversity and biocontrol mechanisms of the Clonostachys fungi, this study was undertaken to sequence and assemble the genomes of two C. chloroleuca and one C. rhizophaga.

DATA DESCRIPTION: Here, we performed genomic sequencing of three strains of genus Clonostachys collected from the China General Microbiological Culture Collection Center (CGMCC) using Illumina HiSeq 2500 sequencing technology. Whole genome analysis indicated that their genomes consist of 58,484,224 bp with a GC content of 48.58%, 58,114,960 bp with a GC content of 47.74% and 58,450,453 bp with a GC content of 48.58%, respectively. BUSCO analysis of the genome assembly indicated that the completeness of these genomes was at least 98%. In summary, these datasets provide a valuable resource for ongoing studies that include further exploration of biological function, marker development, enhanced biological control ability of Clonostachys fungi, and population diversity.

RevDate: 2025-05-28

Min J, Kim B, Park Y, et al (2025)

Bacterial cell wall synthesis and recycling: new antimicrobial targets and vaccine development.

Critical reviews in microbiology [Epub ahead of print].

Almost all bacteria have peptidoglycan (PG) components that are essential for virulence and are absent in humans, making them a top-priority target for antibiotics and vaccines. The rise of multidrug-resistant bacteria (MRB) necessitates urgent expansion of our arsenal of inhibitors targeting the PG cell wall. This review addresses our understanding of PG biosynthesis and recycling processes, emphasizing the need to identify novel target proteins and redesign existing PG-targeted antimicrobial peptides. Building on our understanding of cell wall biochemistry and biogenesis derived from Escherichia coli, we also aim to compare and elucidate the cell wall processes in other pathogens, such as Acinetobacter baumannii and Salmonella Typhimurium, where knowledge remains incomplete. We cover in detail the distinct roles of PG-related proteins in Gram-negative bacteria, strategies to block PG biosynthesis/recycling pathways, and their potential as novel antibiotic targets to address the growing challenge of antibiotic resistance. Finally, we review the application of rigorous immuno-informatics analysis and several immune filters to construct epitope-specific vaccines displaying PG-related proteins on the surface of outer membrane vesicles (OMVs), aiming to combat MRB proliferation.

RevDate: 2025-05-31
CmpDate: 2025-05-28

Rodrigues GVP, Santos JPN, Ferreira LYM, et al (2025)

Theobroma cacao Virome: Exploring Public RNA-Seq Data for Viral Discovery and Surveillance.

Viruses, 17(5):.

Cocoa (Theobroma cacao L.) is a major agricultural commodity, essential for the global chocolate industry and the livelihoods of millions of farmers. However, viral diseases pose a significant threat to cocoa production, with Badnavirus species causing severe losses in Africa. Despite its economic importance, the overall virome of T. cacao remains poorly characterized, limiting our understanding of viral diversity and potential disease interactions. This study aims to assess the cocoa-associated virome by analyzing 109 publicly available RNA-seq libraries from nine BioProjects, covering diverse conditions and geographic regions. We implemented a comprehensive bioinformatics pipeline integrating multiple viral sequence enrichment steps, a hybrid assembly strategy using different assemblers, and sequence similarity searches against NCBI non-redundant databases. Our approach identified ten putative novel viruses associated with the cocoa microbiome and a novel Badnavirus species. These findings provide new insights into the viral landscape of T. cacao, characterizing the diversity of cacao-associated viruses and their potential ecological roles. Expanding the catalog of viruses associated with cocoa plants not only enhances our understanding of plant-virus-microbiome interactions but also contributes to the development of more effective disease surveillance and management strategies, ultimately supporting sustainable cocoa production.

RevDate: 2025-05-31
CmpDate: 2025-05-28

Santos AFB, Nunes M, Filipa-Silva A, et al (2025)

Wastewater Metavirome Diversity: Exploring Replicate Inconsistencies and Bioinformatic Tool Disparities.

International journal of environmental research and public health, 22(5):.

This study investigates viral composition in wastewater through metagenomic analysis, evaluating the performance of four bioinformatic tools-Genome Detective, CZ.ID, INSaFLU-TELEVIR and Trimmomatic + Kraken2-on samples collected from four sites in each of two wastewater treatment plants (WWTPs) in Lisbon, Portugal in April 2019. From each site, we collected and processed separately three replicates and one pool of nucleic acids extracted from the replicates. A total of 32 samples were processed using sequence-independent single-primer amplification (SISPA) and sequenced on an Illumina MiSeq platform. Across the 128 sample-tool combinations, viral read counts varied widely, from 3 to 288,464. There was a lack of consistency between replicates and their pools in terms of viral abundance and diversity, revealing the heterogeneity of the wastewater matrix and the variability in sequencing effort. There was also a difference between software tools highlighting the impact of tool selection on community profiling. A positive correlation between crAssphage and human pathogens was found, supporting crAssphage as a proxy for public health surveillance. A custom Python pipeline automated viral identification report processing, taxonomic assignments and diversity calculations, streamlining analysis and ensuring reproducibility. These findings emphasize the importance of sequencing depth, software tool selection and standardized pipelines in advancing wastewater-based epidemiology.

RevDate: 2025-06-01
CmpDate: 2025-06-01

Semcesen PO, Wells MG, Sherlock C, et al (2025)

Wind driven transport of macroplastic debris in a large urban harbour measured by GPS-tracked drifters.

Marine pollution bulletin, 217:118034.

The transport pathways of floating plastic debris in Toronto Harbour, Ontario, Canada, were assessed using a series of GPS-tracked drifter bottles. The drifter trajectories were largely controlled by winds, and they could traverse the 2 km wide harbour within a day. The average ratio of drifter speed to wind speed (the wind factor) is consistent with values of 2-5 % used in modelling dispersion of marine debris. However, significant variability in wind factors meant some drifters travelled 2-5 times faster than expected in small waterbodies (Toronto Harbour), and as much as 7 times faster in large waterbodies (Lake Ontario). Importantly, based on our calculated wind factor equations and the coincident accumulation of our drifters with real plastic debris, we can justify the use of wind factors when studying plastic debris transport. Most (75 %) of the drifters that were released in the harbour, stayed within the harbour, accumulating downwind. However, 14 of all 66 drifters escaped Toronto Harbour, where ∼70 % escaped through the West Gap while ∼30 % escaped via the Outer Harbour. One drifter made a 290 km journey across Lake Ontario in a period of 14 days, demonstrating that Toronto is a potential source of plastic debris throughout Lake Ontario.

RevDate: 2025-05-31
CmpDate: 2025-05-28

Charest J, Loebenstein P, Mach RL, et al (2025)

FunFEA: an R package for fungal functional enrichment analysis.

BMC bioinformatics, 26(1):138.

BACKGROUND: The functional annotation of fungal genomes is critical for understanding their biological processes and ecological roles. While existing tools support functional enrichment analysis from publicly available annotations of well-established model organisms, few are tailored to the specific needs of the fungal research community. Furthermore, many tools struggle with processing functional annotations of novel species, for which no publicly available functional annotations are yet available.

RESULTS: FunFEA is an R package designed for functional enrichment analysis of fungal genomes. It supports COG/KOG (Clusters of Orthologous Genes), GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) annotations, and generates background frequency models from publicly available annotations for overrepresentation analysis, within a set of experimentally defined genes or proteins. Additionally, FunFEA can process eggNOG-mapper annotations, thus enabling functional enrichment analysis of novel genomes. The package offers a suite of tools for generation of background frequency models, functional enrichment analysis, as well as visualization of enriched functional categories. On release, the package includes precomputed models for 65 commonly used fungal strains in academic research and strains listed on the WHO fungal priority pathogens list.

CONCLUSIONS: FunFEA fills a critical need for a specialized tool in fungal genomics, providing valuable insights into fungal biology. Additionally, its ability to process eggNOG-mapper annotations makes it an essential resource for researchers, helping to drive further exploration of fungal functional diversity and pathways and derive biological insights from novel genomes.

RevDate: 2025-05-30
CmpDate: 2025-05-27

Péter SA, Gallo T, Mullinax J, et al (2025)

Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments.

Scientific reports, 15(1):18588.

Human expansion into wildlife habitats has increased the need to understand human-wildlife interactions, necessitating interdisciplinary approaches to assess zoonotic disease transmission risks and public health impacts. This study integrated fine-grained human foot traffic data with hourly GPS data from 38 white-tailed deer (Odocoileus virginianus), a species linked to SARS-CoV-2, brucella, and chronic wasting disease, in Howard County, Maryland. We explored spatial and temporal overlap between human and deer activity over 24 months (2018-2019) across a hexagonal tessellation with metrics like hourly popularity and visit counts. Negative binomial models were fitted to the visit counts of each deer and humans per tessellation area, using landscape features as predictors. A separate deer-only model included commercial human activity as another predictor. Spatial analysis showed deer and humans sharing spaces in the study area, with results indicating deer using more populated residential areas and areas with commercial activity. Temporal analysis showed deer avoiding commercial spaces during daytime but using them in late evening and early morning. These findings highlight the complex space use between species and the importance of integrating detailed human mobility and animal movement data when managing wildlife-human conflict and zoonotic disease transmission, particularly in urban areas with a high probability of deer-human interactions.

RevDate: 2025-05-30
CmpDate: 2025-05-30

Silva MKP, Nicoleti VYU, Rodrigues BDPP, et al (2025)

Exploring deep learning in phage discovery and characterization.

Virology, 609:110559.

Bacteriophages, or bacterial viruses, play diverse ecological roles by shaping bacterial populations and also hold significant biotechnological and medical potential, including the treatment of infections caused by multidrug-resistant bacteria. The discovery of novel bacteriophages using large-scale metagenomic data has been accelerated by the accessibility of deep learning (Artificial Intelligence), the increased computing power of graphical processing units (GPUs), and new bioinformatics tools. This review addresses the recent revolution in bacteriophage research, ranging from the adoption of neural network algorithms applied to metagenomic data to the use of pre-trained language models, such as BERT, which have improved the reconstruction of viral metagenome-assembled genomes (vMAGs). This article also discusses the main aspects of bacteriophage biology using deep learning, highlighting the advances and limitations of this approach. Finally, prospects of deep-learning-based metagenomic algorithms and recommendations for future investigations are described.

RevDate: 2025-05-30
CmpDate: 2025-05-30

Hashem I, Wang J, JFM Van Impe (2025)

A Discretized Overlap Resolution Algorithm (DORA) for resolving spatial overlaps in individual-based models of microbes.

PLoS computational biology, 21(4):e1012974 pii:PCOMPBIOL-D-24-00908.

Individual-based modeling (IbM) is an instrumental tool for simulating spatial microbial growth, with applications in both microbial ecology and biochemical engineering. Unlike Cellular Automata (CA), which use a fixed grid of cells with predefined rules for interactions, IbMs model the individual behaviors of cells, allowing complex population dynamics to emerge. IbMs require more detailed modeling of individual interactions, which introduces significant computational challenges, particularly in resolving spatial overlaps between cells. Traditionally, this is managed using arrays or kd-trees, which require numerous pairwise comparisons and become inefficient as population size increases. To address this bottleneck, we introduce the Discretized Overlap Resolution Algorithm (DORA), which employs a grid-based framework to efficiently manage overlaps. By discretizing the simulation space further and assigning circular cells to specific grid units, DORA transforms the computationally intensive pairwise comparison process into a more efficient grid-based operation. This approach significantly reduces the computational load, particularly in simulations with large cell populations. Our evaluation of DORA, through simulations of microbial colonies and biofilms under varied nutrient conditions, demonstrates its superior computational efficiency and ability to accurately capture microbial growth dynamics compared to conventional methods. DORA's grid-based strategy enables the modeling of densely populated microbial communities within practical computational timeframes, thereby expanding the scope and applicability of individual-based modeling.

RevDate: 2025-05-27

Mambully S, Ramesh V, Rani S, et al (2025)

Genotype Patterns and Evolutionary Rates: Uncovering Japanese Encephalitis Virus Spread Across Asia's Climate Regions.

Acta tropica pii:S0001-706X(25)00152-4 [Epub ahead of print].

Japanese Encephalitis Virus (JEV) is a highly endemic zoonotic virus, consistently found in Asia and parts of the Western Pacific, and it's a major cause of human encephalitis. JEV belongs to a family of antigenically related viruses such as West Nile Virus (WNV), Murray Valley encephalitis virus (MVEV), and Aichi Lake Fever Virus (ALFV) and is transmitted by mosquitoes. Persistent outbreaks of the disease necessitate detailed studies to understand their transmission dynamics and develop effective prevention strategies. This study explores the evolutionary dynamics and spatial transmission of JEV, concentrating on the envelope protein (E) structural gene sequences obtained from across Asia's diverse climatic regions. Evolutionary modeling of the JEV E gene revealed a higher evolutionary rate in tropical regions compared to temperate regions, with nucleotide substitution rates estimated at 1.12 × 10[-3] per site per year for tropical regions and 5.284 × 10[-4] for temperate regions. The time to the most recent common ancestor (tMRCA) was traced to 1796 from Korea for temperate regions, and 1865 from Indonesia for tropical regions. Among the five genotypes of JEV, Genotype I (GI) and III (GIII) were established all over Southeast Asia; moreover, GI revealed a higher evolutionary rate, reflecting its adaptability to diverse ecological niches. The phylogeographic analysis highlighted significant contributions to virus diffusion by China, Korea, and Japan in temperate zones and by Vietnam in tropical zones. By analyzing genetic sequences from various regions and time periods, this study delivered valuable intuitions into transmission pathways. The findings highlighted the necessity of ongoing surveillance and evolutionary monitoring to track the spread and emergence of novel variations of JEV, which are crucial not just for managing JEV outbreaks but also for guiding immunization programs and public health initiatives.

RevDate: 2025-05-26
CmpDate: 2025-05-26

Jucker T, Fischer FJ, Chave J, et al (2025)

The global spectrum of tree crown architecture.

Nature communications, 16(1):4876.

Trees can differ enormously in their crown architectural traits, such as the scaling relationships between tree height, crown width and stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of terrestrial ecosystems, we lack a complete picture of what drives this incredible diversity in crown shapes. Using data from 374,888 globally distributed trees, we explore how climate, disturbance, competition, functional traits, and evolutionary history constrain the height and crown width scaling relationships of 1914 tree species. We find that variation in height-diameter scaling relationships is primarily controlled by water availability and light competition. Conversely, crown width is predominantly shaped by exposure to wind and fire, while also covarying with functional traits related to mechanical stability and photosynthesis. Additionally, we identify several plant lineages with highly distinctive stem and crown forms, such as the exceedingly slender dipterocarps of Southeast Asia, or the extremely wide crowns of legume trees in African savannas. Our study charts the global spectrum of tree crown architecture and pinpoints the processes that shape the 3D structure of woody ecosystems.

RevDate: 2025-05-27
CmpDate: 2025-05-26

Foreman MA, Ross A, Burgess APH, et al (2024)

Barriers and Facilitators of Digital Health Use for Self-Management of Hypertensive Disorders by Black Pregnant Women.

AMIA ... Annual Symposium proceedings. AMIA Symposium, 2024:433-442.

Although digital health tools are increasingly common for managing health conditions, these applications are often developed without consideration of differences across user populations. A reproducible framework is needed to support tailoring applications to include cultural considerations, potentially leading to better adoption and more effective use. As a first step, this study captures a snapshot of Black women's barriers and facilitators in using digital health products for self-management of hypertensive disorders of pregnancy (HDP). One-on-one semi-structured interviews were conducted with 17 Black pregnant women with HDP. We established a unique model for cultural tailoring with these experiences using Black feminist theory and the CDC's Social-Ecological Model (SEM). 38 themes across the four levels of SEM were found through grounded theory. These themes can inform the feature development of a digital health intervention. Future work will instantiate and validate a framework that provides theoretical constructs for developing culturally tailored digital health interventions.

RevDate: 2025-05-29
CmpDate: 2025-05-26

Gaievskyi S, Delfrate N, Ragazzoni L, et al (2025)

Use of multi-criteria decision analysis (MCDA) to support decision-making during health emergencies: a scoping review.

Frontiers in public health, 13:1584026.

BACKGROUND: The mismatch between the health needs of populations affected by emergencies and resources devoted to response is projected to further increase. Making the response more effective is one of the solutions to meet the growing needs. Multi-criteria decision analysis (MCDA) has been successfully used to increase effectiveness in various fields by supporting decision-making. However, no review of its application to all-hazard health emergencies has been done to date.

METHODS: A review of peer-reviewed English-language articles published since 2004 was conducted in May 2024 using Scopus, PubMed and Web of Science databases. The review focused on the empirical application of MCDA to support decision-making during health emergencies. The review was guided by the Joanna Briggs Institute methodology for scoping reviews and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Quantitative data were analyzed using summary statistics and qualitative data were analyzed using content analysis.

RESULTS: Seventy-one articles were included after screening. The articles described the MCDA application to support a variety of decision problems related to health emergency management. However, the technique was mostly applied to infectious hazards management and only seldom to other hazards. The review also found a lack of standardized methodology for identifying alternatives and criteria, weighting, computation of model output, methods of dealing with uncertainty, and stakeholder engagement.

CONCLUSION: The review provides an overview of the current use of the MCDA approach to support decision-making in health emergency management and informs areas of future development. The review emphasizes that while MCDA is already used for infectious hazards, it is underutilized for other types of health emergencies. Developing tailored MCDA approaches for health emergencies, including defining evaluation criteria and stakeholder engagement, may improve uptake of the technique and benefit the efforts to meet the growing health needs of the population affected by emergencies, https://osf.io/6kd5s/.

RevDate: 2025-05-29
CmpDate: 2025-05-29

Babič J, Kunavar T, Oztop E, et al (2025)

Success-efficient/failure-safe strategy for hierarchical reinforcement motor learning.

PLoS computational biology, 21(5):e1013089 pii:PCOMPBIOL-D-24-01419.

Our study explores how ecological aspects of motor learning enhance survival by improving movement efficiency and mitigating injury risks during task failures. Traditional motor control theories mainly address isolated body movements and often overlook these ecological factors. We introduce a novel computational motor control approach, incorporating ecological fitness and a strategy that alternates between success-driven movement efficiency and failure-driven safety, akin to win-stay/lose-shift tactics. In our experiments, participants performed squat-to-stand movements under novel force perturbations. They adapted effectively through various adaptive motor control mechanisms to avoid falls, reducing failure rates rapidly. The results indicate a high-level ecological controller in human motor learning that switches objectives between safety and movement efficiency, depending on failure or success. This approach is supported by policy learning, internal model adaptation, and adaptive feedback control. Our findings offer a comprehensive perspective on human motor control, integrating risk management in a hierarchical reinforcement learning framework for real-world environments.

RevDate: 2025-05-29
CmpDate: 2025-05-29

Tu M, Liu N, He ZS, et al (2025)

Integrative omics reveals mechanisms of biosynthesis and regulation of floral scent in Cymbidium tracyanum.

Plant biotechnology journal, 23(6):2162-2181.

Flower scent is a crucial determiner in pollinator attraction and a significant horticultural trait in ornamental plants. Orchids, which have long been of interest in evolutionary biology and horticulture, exhibit remarkable diversity in floral scent type and intensity. However, the mechanisms underlying floral scent biosynthesis and regulation in orchids remain largely unexplored. In this study, we focus on floral scent in Cymbidium tracyanum, a wild species known for its strong floral fragrance and as a primary breeding parent of commercial Cymbidium hybrids. We present a chromosome-level genome assembly of C. tracyanum, totaling 3.79 Gb in size. Comparative genomic analyses reveal significant expansion of gene families associated with terpenoid biosynthesis and related metabolic pathways in C. tracyanum. Integrative analysis of genomic, volatolomic and transcriptomic data identified terpenoids as the predominant volatile components in the flowers of C. tracyanum. We characterized the spatiotemporal patterns of these volatiles and identified CtTPS genes responsible for volatile terpenoid biosynthesis, validating their catalytic functions in vitro. Dual-luciferase reporter assays, yeast one-hybrid assays and EMSA experiments confirmed that CtTPS2, CtTPS3, and CtTPS8 could be activated by various transcription factors (i.e., CtAP2/ERF1, CtbZIP1, CtMYB2, CtMYB3 and CtAP2/ERF4), thereby regulating the production of corresponding monoterpenes and sesquiterpenes. Our study elucidates the biosynthetic and regulatory mechanisms of floral scent in C. tracyanum, which is of great significance for the breeding of fragrant Cymbidium varieties and understanding the ecological adaptability of orchids. This study also highlights the importance of integrating multi-omics data in deciphering key horticultural traits in orchids.

RevDate: 2025-05-27

Yang P, Wang X, Yang J, et al (2025)

AI-Driven Multiscale Study on the Mechanism of Polygonati Rhizoma in Regulating Immune Function in STAD.

ACS omega, 10(19):19770-19796.

Polygonati Rhizoma, a traditional Chinese medicine, has demonstrated immunomodulatory and anticancer properties, yet its precise mechanisms in stomach adenocarcinoma (STAD) remain underexplored. This study aims to uncover the multitarget mechanisms of Polygonati Rhizoma in regulating the tumor immune microenvironment in STAD using artificial intelligence (AI)-driven network pharmacology, bioinformatics, and single-cell RNA sequencing, offering new insights into its immunotherapeutic potential. This study harnessed the power of AI to unravel the molecular mechanisms underlying Polygonati Rhizoma's effects. AI-driven methodologies screened 38 putative constituents, retaining 8 based on ADME criteria. Machine Learning algorithms predicted potential targets, which were cross-referenced with 5,569 immune-related genes from GeneCards, revealing 52 immune-associated targets. Differential expression analysis of the STAD data set identified 18 overlapping DEGs with prognostic significance and immune cell infiltration correlations. Key targets (AKT1, TP53, PTGS2 and VEGFA) emerged as central nodes in the network, with AI-assisted molecular docking confirming strong binding affinities, particularly between diosgenin and these core proteins. Molecular dynamics simulations further validated these interactions. Single-cell RNA sequencing revealed distinct target-gene expression patterns across malignant, stromal, and immune cell subsets in digestive-system tumors. In vitro, Polygonati Rhizoma extract significantly inhibited HGC-27 cell viability and increased intracellular ROS levels. These findings underscore the critical role of AI in integrating multiscale analyses, unveiling a multitarget immunomodulatory and antitumor mechanism for Polygonati Rhizoma in STAD, and providing a foundation for future preclinical and clinical studies.

RevDate: 2025-05-27
CmpDate: 2025-05-25

Jia L, Liu Z, Y Li (2025)

Spatiotemporal dynamics of rural settlement evolution in Guangdong Province, China.

Scientific reports, 15(1):18244.

This study analyzes the spatiotemporal dynamics of rural settlement evolution in Guangdong Province, China, examining their transformation amid rapid urbanization and industrialization over the past 20 years. Rural settlements serve as primary spatial carriers for production and living activities, embodying multiple functions including production, living, ecological, and cultural aspects. Using GIS-based analytical tools, including landscape pattern indices, average nearest neighbor index, kernel density estimation, and geographical detector methods, we examined settlement evolution patterns and their driving factors. Results show a continuous decline in settlement numbers, while patch areas exhibited a U-shaped trend of decreasing then increasing. Settlement patterns shifted from "reduction" to "integration", with intensifying spatial agglomeration over time. The Pearl River Delta and Eastern Guangdong regions followed similar trajectories, reflecting the impact of urbanization and industrialization on rural development. Multiple factors, including natural conditions, socioeconomic variables, and locational accessibility, drove these changes. The spatial distribution of rural settlements demonstrates an overall trend of agglomeration, which has gradually intensified over time, leading to significant variations in settlement density across different regions. The findings reveal significant regional disparities and temporal changes in settlement patterns, highlighting the complex interplay between rural transformation and urban development. This research contributes to understanding rural transformation processes in developing countries and emphasizes the need for differentiated approaches in spatial planning and rural revitalization strategies to address the challenges of disordered land expansion and population hollowing while promoting sustainable rural development.

RevDate: 2025-05-25

Dou X, Liu Q, Fan Q, et al (2025)

Comprehensive Analysis of Common Heavy Metals in the Yellow River Over 20 Years: Spatiotemporal distribution, Migration Characteristics, Traceability, and Potential Risk Evaluation.

Environmental research pii:S0013-9351(25)01182-X [Epub ahead of print].

Heavy metal pollution posed a great threat to the global aquatic ecological environment, especially in the Yellow River where the utilization rate of water resources was as high as 80%. This study addressed the spatiotemporal distribution, sources, and ecological risks of seven heavy metals (As, Cd, Cr, Cu, Ni, Pb, Zn) in the Yellow River by analyzing historical data collected from 2000 to 2020. The annual heavy metal fluxes increased from Qinghai to Henan section, then decreased from Henan to Shandong section. Similarly, concentrations of Cu, Ni, Pb, and Zn peaked in the sediments of the Henan section. These trends might be attributed to the interception effects of the Xiaolangdi and Sanmenxia Dams. The annual fluxes from 2016-2020 increased by an average of 162.6% compared to that from 2011-2015, likely reflecting the impact of ongoing economic growth (33.36%) and SS increase (69.68%). The annual fluxes of SS demonstrated a significant correlation with all heavy metal fluxes, underscoring their role as a critical transport medium in aquatic ecosystem. The fluxes of Cd and Pb were most strongly influenced by human factors. While most metals in surface water present negligible risks to aquatic life, Cd in sediments presents a considerable ecological threat. Furthermore, the highest potential ecological risk index (RI) was observed in the river sections in Gansu and Inner Mongolia, mainly due to Cd, which contributed up to 85.87%. The findings establish a fundamental framework for safeguarding the aquatic ecosystem of the Yellow River and managing its heavy metal contamination.

RevDate: 2025-05-27
CmpDate: 2025-05-24

Fan J, Zhang Y, Nie X, et al (2025)

Comprehensive curation and validation of genomic datasets for chestnut.

Scientific data, 12(1):860.

The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and analyzed a collection of genomic datasets for eight Castanea species, including functional annotations, 213 RNA-Seq samples, and 330 resequencing samples. These datasets are publicly available on Figshare and are also available through other platforms such as GEO and EVA, providing a valuable resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Furthermore, the datasets are integrated into the Castanea Genome Database (CGD, http://castaneadb.net), which serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.

RevDate: 2025-05-24
CmpDate: 2025-05-24

Zhu Q, Cai Y, Z Hu (2025)

Effects of bactericides and sulphate reducing bacteria addition on acidification and microbial community structure of newly produced coal gangue.

Journal of environmental sciences (China), 156:311-320.

Microbiologically driven acidic pollution of coal gangue has become a major environmental problem in coal gangue dumps in coal mining areas. Addition of bactericides and sulphate reducing bacteria (SRB) is an effective means to control the acidic pollution of coal gangue, but their mechanism of action has not been fully investigated. By adding bactericide, SRB and bactericide-SRB to the newly produced coal gangue, respectively, the effects of these treatments on the microbial community structure were observed. Changes in pH and electrical conductivity (EC) of the gangue leaching solution, as well as the microbial community composition and functional abundance on the gangue surface were analysed by leaching simulation experiments and 16S rRNA sequencing. The results showed that (1) the addition of bactericide-SRB was the most effective treatment to elevate pH before 8 d, while the addition of SRB performed best after 22 d (2) The addition of bactericide and SRB drastically changed the microbial community structure on the gangue surface. Simultaneous addition of both had the best inhibitory effect on pathogenic bacteria and Thiobacillus. (3) All three treatments promote higher abundance of genes related to nitrogen cycling, but reflected in different gene functions. Microorganisms with sulfate respiration function in the experimental group all showed different increases. The abundance of other sulfur cycle genes decreased substantially. However, Human Pathogens All had higher abundance than control check (CK) in each treatment, which may indicate that the addition of either bactericides or SRB increases the risk of microbial pathogenicity to humans.

RevDate: 2025-05-24

Zhang L, Zhang L, Gao S, et al (2025)

Structural balance and evolution of cooperation in a population with hybrid interactions.

Physical review. E, 111(4-1):044309.

This study explores the evolution of cooperation in populations with mixed pairwise and three-body interactions, investigating the impact of higher-order interaction density ρ and individual interaction preference α. Our results reveal that sparse higher-order interactions markedly boost cooperation, exhibiting two critical phase transitions as ρ changes. These transitions underscore the delicate equilibrium needed for optimal cooperation, as excessive higher-order interactions can diminish returns. The preference parameter α significantly influences cooperation sustainability, with intermediate values maximizing cooperative outcomes, particularly when the temptation to defect r is not strong. Crucially, our findings demonstrate that hybrid social dilemmas structurally encode emergent cooperation pathways that are unattainable within homogeneous interaction frameworks, emphasizing the importance of modeling mixed interactions to capture real-world complexity. These insights offer valuable guidance for designing systems aimed at promoting cooperative behavior across social, ecological, and artificial domains.

RevDate: 2025-05-23

Bukat A, Bukowicki M, Bykowski M, et al (2025)

GRANA: An AI-based tool for accelerating chloroplast grana nanomorphology analysis using hybrid intelligence.

Plant physiology pii:8142509 [Epub ahead of print].

Grana are fundamental structural units of the intricate chloroplast membrane network. Investigating their nanomorphology is essential for understanding photosynthetic efficiency regulation. Here, we present GRANA (Graphical Recognition and Analysis of Nanostructural Assemblies), an AI-enhanced, user-friendly software tool that recognizes grana on thylakoid network electron micrographs and generates a complex set of their structural parameters. GRANA employs three artificial neural networks of different architectures and binds them in a one-click workflow. Its output is designed to facilitate hybrid intelligence analysis, securing fast and reliable results from large datasets. The GRANA tool is over 100 times faster compared with currently used manual approaches. As a proof of concept, we have successfully applied GRANA software to diverse grana structures across different land plant species grown under various conditions, demonstrating the wide range of potential applications for our software. GRANA tool supports large-scale analysis of grana nanomorphological features, facilitating advancements in photosynthesis-oriented studies.

RevDate: 2025-05-28
CmpDate: 2025-05-28

Fontanarrosa P, Clare C, Fedorec AJH, et al (2025)

MIMIC: a Python package for simulating, inferring, and predicting microbial community interactions and dynamics.

Bioinformatics (Oxford, England), 41(5):.

SUMMARY: The study of microbial communities is vital for understanding their impact on environmental, health, and technological domains. The Modelling and Inference of MICrobiomes Project (MIMIC) introduces a Python package designed to advance the simulation, inference, and prediction of microbial community interactions and dynamics. Addressing the complex nature of microbial ecosystems, MIMIC integrates a suite of mathematical models, including previously used approaches such as Generalized Lotka-Volterra (gLV), Gaussian Processes (GP), and Vector Autoregression (VAR) plus newly developed models for integrating multi-omic data, to offer a versatile framework for analyzing microbial dynamics. By leveraging Bayesian inference and machine learning techniques, MIMIC provides the ability to infer the dynamics of microbial communities from empirical data, facilitating a deeper understanding of their complex biological processes, unveiling possible unknown ecological interactions, and enabling the design of microbial communities. Such insights could help to advance microbial ecology research, optimizing biotechnological applications, and contribute to environmental sustainability and public health strategies. MIMIC is designed for flexibility and ease of use, aiming to support researchers and practitioners in microbial ecology and microbiome research.

MIMIC is freely available under the MIT License at https://github.com/ucl-cssb/MIMIC. It is implemented in Python (version 3.7 or higher) and is compatible with Windows, macOS, and Linux operating systems. MIMIC depends on standard Python libraries including NumPy, SciPy, and PyMC. Comprehensive examples and tutorials (including the main text demonstrations) are provided as Jupyter notebooks in the examples/directory and at the MIMIC Docs website, along with detailed installation instructions and real-world data use cases. The software will remain freely available for at least two years following publication. A code snapshot for this publication is also available at Zenodo: https://doi.org/10.5281/zenodo.15149003.

RevDate: 2025-05-23
CmpDate: 2025-05-23

Bate JB, NHA Dagamac (2025)

Wallow land suitability assessment using GIS-based multicriteria decision-making framework.

Environmental monitoring and assessment, 197(6):668.

Protected areas are the frontlines of biodiversity conservation, featuring critical landscapes and microhabitats that are fitted for the survival of the organisms that have restricted populations. The determination of land suitability and habitat connectivity in these protected areas are important for species with specialized adaptive behavior that requires favorable conditions to survive. The Bubalus mindorensis is a critically endangered bovine of the Philippines which utilizes mud or water puddles to address heat stress through body submersion, known as wallowing. With Mts. Iglit-Baco National Park (MIBNP) harboring the largest remaining subpopulation of the tamaraw, the preservation of its natural landscapes is critical for tamaraw survival. Here, the potential wallows in MIBNP were determined using the weighted overlay analysis (WOA) assisted by the analytical hierarchy process (AHP). Using environmental variables that were influential to the creation of wallows, an equal-weighed scenario and an AHP-assisted scenario wallow suitability map was generated. Moderate and highly suitable areas were found at the north-central portion of the mountain, coinciding with the current and future conservation zones of the tamaraw, whereas low suitable areas dominate the other half, aggregating at the corners due to build areas and agriculture. The result of the study provides supplementary information in constructing future conservation strategies for an endemic species with global importance, particularly in its possible range expansion within the park. Furthermore, this study provides a framework for future conservation efforts, which helps in the management of critical landscapes for species with specialized adaptive behaviors through GIS-based multicriteria decision-making.

RevDate: 2025-05-25

Araujo ACB, Souza OF, Kersanach BB, et al (2025)

Trends in Congenital Syphilis Incidence and Mortality in Brazil's Southeast Region: A Time-Series Analysis (2008-2022).

Epidemiologia (Basel, Switzerland), 6(2):.

Congenital syphilis (CS) is an important infectious cause of miscarriage, stillbirth, and neonatal morbidity and mortality. Despite the advances in diagnosis and treatment, CS continues to challenge health systems with increasing incidence and mortality rates in recent years worldwide. Given this, the present study aims to comparatively analyze the temporal trends in CS incidence and mortality in Brazil's Southeast Region from 2008 to 2022. This is an ecological time-series study using secondary data on congenital syphilis from the states of Espírito Santo, Minas Gerais, Rio de Janeiro, and São Paulo. The data was extracted from the Brazilian Health System Informatics Department. Incidence and mortality rates were calculated per 100,000 live births. Joinpoint regression models were employed to identify trends in annual percentage change and average annual percentage change with 95% confidence intervals. The temporal trend of CS incidence in Brazil's Southeast Region increased 12.8% between 2008 and 2022. Minas Gerais, São Paulo, Espírito Santo, and Rio de Janeiro showed increasing temporal trends of 21.4%, 14.1%, 14.0%, and 10.9%, respectively. The temporal trend of CS mortality in Brazil's Southeast Region rose 11.9% between 2008 and 2022. Minas Gerais, São Paulo, and Rio de Janeiro exhibited increasing mortality temporal trends of 21.9%, 20.8%, and 10.1%, respectively. In contrast, Espírito Santo showed reduced mortality, with no deaths in 2021 and 2022. The temporal trend of CS incidence increased in all states of Brazil's Southeast Region between 2008 and 2022, highlighting the need to reassess control measures. The temporal trend of CS mortality also increased during the same period, except in Espírito Santo. Considering that CS is preventable with adequate prenatal care and low-cost measures, these findings can serve as instruments to support strengthening public health policies.

RevDate: 2025-05-27
CmpDate: 2025-05-23

Wang M, Chen X, Liu M, et al (2025)

Decoding herbal combination models through systematic strategies: insights from target information and traditional Chinese medicine clinical theory.

Briefings in bioinformatics, 26(3):.

Traditional Chinese medicine (TCM) utilizes intricate herbal formulations that exemplify the principles of compatibility and synergy. However, the rapid proliferation of herbal data has resulted in redundant information, complicating the understanding of their potential mechanisms. To address this issue, we first established a comprehensive database that encompasses 992 herbs, 18 681 molecules, and 2168 targets. Consequently, we implemented a multi-network strategy based on a core information screening method to elucidate the highly intertwined relationships among the targets of various herbs and to refine herbal target information. Within a non-redundant network framework, separation and overlap analysis demonstrated that the networking of herbs preserves essential clinical information, including their properties, meridians, and therapeutic classifications. Furthermore, two notable trends emerged from the statistical analyses of classical TCM formulas: the separation of herbs and the overlap between herbs and diseases. This phenomenon is termed the herbal combination model (HCM), validated through statistical analyses of two representative case studies: the common cold and rheumatoid arthritis. Additionally, in vivo and in vitro experiments with the new formula YanChuanQin (YanHuSuo-Corydalis Rhizoma, ChuanWu-Aconiti Radix, and QinJiao-Gentianae Macrophyllae Radix) for acute gouty arthritis further support the HCM. Overall, this computational method provides a systematic network strategy for exploring herbal combinations in complex and poorly understood diseases from a non-redundant perspective.

RevDate: 2025-05-27
CmpDate: 2025-05-27

Shoemaker WR, Sánchez Á, J Grilli (2025)

Macroecological patterns in experimental microbial communities.

PLoS computational biology, 21(5):e1013044 pii:PCOMPBIOL-D-24-02000.

Ecology has historically benefited from the characterization of statistical patterns of biodiversity within and across communities, an approach known as macroecology. Within microbial ecology, macroecological approaches have identified universal patterns of diversity and abundance that can be captured by effective models. Experimentation has simultaneously played a crucial role, as the advent of high-replication community time-series has allowed researchers to investigate underlying ecological forces. However, there remains a gap between experiments performed in the laboratory and macroecological patterns documented in natural systems, as we do not know whether these patterns can be recapitulated in the lab and whether experimental manipulations produce macroecological effects. This work aims at bridging the gap between experimental ecology and macroecology. Using high-replication time-series, we demonstrate that microbial macroecological patterns observed in nature exist in a laboratory setting, despite controlled conditions, and can be unified under the Stochastic Logistic Model of growth (SLM). We found that demographic manipulations (e.g., migration) impact observed macroecological patterns. By modifying the SLM to incorporate said manipulations alongside experimental details (e.g., sampling), we obtain predictions that are consistent with macroecological outcomes. By combining high-replication experiments with ecological models, microbial macroecology can be viewed as a predictive discipline.

RevDate: 2025-05-23
CmpDate: 2025-05-23

Pang D, Zhu R, Zhao H, et al (2025)

Probabilistic exponential family inverse regression and its applications.

Biometrics, 81(2):.

Rapid advances in high-throughput sequencing technologies have led to the fast accumulation of high-dimensional data, which is harnessed for understanding the implications of various factors on human disease and health. While dimension reduction plays an essential role in high-dimensional regression and classification, existing methods often require the predictors to be continuous, making them unsuitable for discrete data, such as presence-absence records of species in community ecology and sequencing reads in single-cell studies. To identify and estimate sufficient reductions in regressions with discrete predictors, we introduce probabilistic exponential family inverse regression (PrEFIR), assuming that, given the response and a set of latent factors, the predictors follow one-parameter exponential families. We show that the low-dimensional reductions result not only from the response variable but also from the latent factors. We further extend the latent factor modeling framework to the double exponential family by including an additional parameter to account for the dispersion. This versatile framework encompasses regressions with all categorical or a mixture of categorical and continuous predictors. We propose the method of maximum hierarchical likelihood for estimation, and develop a highly parallelizable algorithm for its computation. The effectiveness of PrEFIR is demonstrated through simulation studies and real data examples.

RevDate: 2025-05-23

Han Y, Cai J, Chen Y, et al (2025)

Concurrent Formation of Low-Maturity EC and BrC in Biomass and Coal Burning: O-PAH as a Precursor.

Environmental science & technology [Epub ahead of print].

Black carbon (BC) significantly influences climate change through light absorption. Traditional emission inventories equate BC with elemental carbon (EC) and overlook the variability in its properties across sources, leading to uncertainties in climate predictions. This study shows that EC from solid fuel combustion contains substantial low-maturity EC (char), whose emissions increase alongside the light absorption of soluble organic carbon (OC) as the fuel aromaticity rises. Concurrently, the abundance of oxygenated polycyclic aromatic hydrocarbons (O-PAHs) in soluble OC also increases. This suggests that char and brown carbon (BrC) share similar formation pathways with O-PAHs as key precursors. Time-resolved analysis during combustion cycles revealed a significant positive correlation between O-PAHs, the light absorption of soluble OC, and char emissions, further supporting this shared pathway. The nonbonding orbitals in BrC and char facilitate n → π* transitions in the visible region, which are more wavelength-dependent than the π → π* transition in high-maturity EC (soot). This study highlights char as a light-absorbing intermediate, influencing light absorption of EC emitted from solid fuel combustion. These insights into the formation pathways and optical properties of carbonaceous aerosols enhance our understanding of their climate impacts and underscore the need to differentiate between char and soot in climate models to improve accuracy.

RevDate: 2025-05-22

Pringle S, Dallimer M, Goddard MA, et al (2025)

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age.

Nature ecology & evolution [Epub ahead of print].

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more 'difficult' taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively.

RevDate: 2025-05-25
CmpDate: 2025-05-22

Wang J, Xu Y, Zhu H, et al (2025)

CheloniansTraits: a comprehensive trait database of global turtles and tortoises.

Scientific data, 12(1):840.

Turtles and tortoises (chelonians) possess a variety of ecological characteristics, including long lifespans and protective shells, which have enabled them to survive and adapt to environmental challenges since the Triassic period. However, many characteristics of chelonians have turned into disadvantages for their populations in the Anthropocene. Currently, there remains a lack of comprehensive data on the morphological, life-history, and ecological characteristics of all chelonians on a global scale. Consequently, our study aims to collect a complete trait database of global chelonians (CheloniansTraits), which may help bridge the knowledge gap regarding the identity and ecology of global chelonians and thereby aiding future conservation endeavors. We compiled 69 trait data for all 358 recognized chelonian species, utilizing ~2,000 literature sources, covering 33 morphological, 21 life-history, 7 ecological traits, and 8 conservation information. This database serves as a uniquely valuable resource for exploring evolutionary, biogeographical, and ecological inquiries related to chelonians, as well as elucidating key aspects of ecological strategy variation among species.

RevDate: 2025-05-22

Zhang S, Qiang J, Liu H, et al (2025)

An efficient and precise (micro)plastic identification method: feature infrared spectra extraction based on EIS-VIP-CARS and ANN modeling.

Environmental research pii:S0013-9351(25)01167-3 [Epub ahead of print].

Understanding microplastics' (MPs) ecological impact necessitates their precise identification. To address the issue of the competitive adaptive reweighted sampling (CARS) algorithm extracting numerous feature wavenumber points (FWPs) that often miss transmittance peaks (TPs), resulting in high computational load and low accuracy in artificial neural network (ANN) models, this study introduces a novel approach. Initially, the equal interval sampling (EIS) method is employed to capture the main information of the full spectra. Subsequently, the variable importance in projection (VIP) is innovatively integrated into the CARS to formulate the EIS-VIP-CARS method for extracting feature spectra (FS). Using 20 typical MPs as the subjects, this study compares the identification performance of ANN models using full-spectra, EIS, CARS, EIS-CARS, VIP-CARS, and EIS-VIP-CARS. The results show that VIP-CARS extracts 128 FWPs, a reduction of 49.41% compared to CARS. Moreover, the distribution of these FWPs is more concentrated around the TPs and their vicinity. The accuracy of MPs by the ANN model based on VIP-CARS is generally higher than that of CARS. EIS-VIP-CARS extracts 55 FWPs, representing a reduction of 58.65% and 57.03% compared to EIS and VIP-CARS, respectively. The overall distribution of these points closely aligns with the distribution of functional groups. The ANN model based on EIS-VIP-CARS can achieve a similar accuracy for MPs as the model based on EIS, both greater than 99%, demonstrating good generalization ability. The accuracies of the MNN and convolutional neural network (CNN) models are higher than those of the SNN model, but the modeling time is longer. The ANN model established using the EIS-VIP-CARS is an efficient and precise approach for the identification of MPs in infrared spectroscopy. This study provides technical references for the research on the environmental behavior of MPs and is also of significant importance for the classification and management of plastic waste.

RevDate: 2025-05-24

Wang H, Lei W, Wu M, et al (2025)

Spatial distribution and ecological risks of neonicotinoids in surface waters of Eastern China.

Environmental pollution (Barking, Essex : 1987), 378:126507 pii:S0269-7491(25)00880-2 [Epub ahead of print].

Over the past two decades, neonicotinoid insecticides (NNIs) have been extensively used in agricultural activities. Due to its high-water solubility, NNIs are primarily found in surface waters, contaminating them and posing significant ecological risks. However complex watershed environments pose challenges in elucidating the pollution characteristics and ecological risks of NNIs in large-scale waters. This study focused on typical surface waters in Eastern China, exploring the spatial characteristics, driving factors, and ecological risks of NNIs. The total concentration of NNIs (Σ8NNIs) ranges from 2.3 ng/L to 1377.8 ng/L. This concentration range exceeded the European water environment toxicity thresholds, with 86 of the sites surpassing the chronic toxicity threshold (8.3 ng/L) and 14 of the sites exceeding the acute toxicity threshold (200 ng/L). Thiamethoxam (THIA), imidacloprid (IMI), and dinotefuran (DIN) were detected with high rates and concentrations. Spatially, the Σ8NNIs in the Yangtze River (YZ, 140.0 ng/L) are significantly higher than in the north of Beijing-Hangzhou Grand Canal (BHN, 62.8 ng/L), Taihu Lake (TH, 36.6 ng/L), and Taihu Basin (THB, 21.9 ng/L). Moreover, Σ8NNIs in the south of Beijing-Hangzhou Grand Canal (BHS, 326.5 ng/L) are significantly higher than in BHN (62.8 ng/L). The spatial distribution of NNI components indicated that DIN and THIA dominated in YZ (37 %), THIA (34 %) and DIN (20 %) in BHN, IMI (53 %) in BHS, DIN (53 %) in TH, and THIA (49 %) and DIN (31 %) in THB. Correlation analysis and linear mixed modeling identified land use, pH, and dissolved oxygen (DO) as significant factors influencing the occurrence of NNIs, with DO emerging as a crucial element. The species sensitivity distribution (SSD) results showed the acute and chronic toxicity thresholds of NNIs for 5 % of aquatic species were 716 ng/L and 166 ng/L respectively with 19 sites exceeding the chronic toxicity threshold and 1 sites surpassing the acute toxicity threshold.

RevDate: 2025-05-22

Brunk KM, Kramer HA, Peery MZ, et al (2025)

Assessing spatial variability and efficacy of surrogate species at an ecosystem scale.

Conservation biology : the journal of the Society for Conservation Biology [Epub ahead of print].

Preserving biodiversity is a central goal of conservation, but, in practice, monitoring biodiversity often involves assessing population trends for one or a handful of species that are presumed proxies for biodiversity. Despite the popularity of surrogate species strategies, the links between biodiversity and surrogate species are rarely tested, especially across the broad spatial scales at which they are applied. We quantitatively evaluated a prominent surrogate species strategy across 25,000 km[2] of California's Sierra Nevada, an ecosystem undergoing substantial forest loss due to changing fire regimes and climate. We used passive acoustic monitoring and multispecies occupancy models to quantify pairwise co-occurrence among 6 indicator species and much of the avian community (63 species). We found that 95% of the sampled avian community had a positive association with at least one indicator species and that latitude played an important role in shaping co-occurrence for many species. Our work provides an important test of a long-standing conservation tool, suggests that a well-chosen suite of surrogate species can represent the occurrence patterns of a large portion of the rest of the community, and demonstrates the importance of explicitly considering the spatial scale over which surrogate species are effective.

RevDate: 2025-05-24
CmpDate: 2025-05-21

Petit MJ, Flory C, Gu Q, et al (2025)

Multi-omics analysis of SFTS virus infection in Rhipicephalus microplus cells reveals antiviral tick factors.

Nature communications, 16(1):4732.

The increasing prevalence of tick-borne arboviral infections worldwide necessitates advanced control strategies, particularly those targeting vectors, to mitigate the disease burden. However, the cellular interactions between arboviruses and ticks, especially for negative-strand RNA viruses, remain largely unexplored. Here, we employ a proteomics informed by transcriptomics approach to elucidate the cellular response of the Rhipicephalus microplus-derived BME/CTVM6 cell line to severe fever with thrombocytopenia syndrome virus (SFTSV) infection. We generate the de novo transcriptomes and proteomes of SFTSV- and mock-infected tick cells, identifying key host responses and regulatory pathways. Additionally, interactome analysis of the viral nucleoprotein (N) integrated host responses with viral replication and dsRNA-mediated gene silencing screen reveals two anti-SFTSV effectors: the N interacting RNA helicases DHX9 and UPF1. Collectively, our results provide insights into the antiviral responses of R. microplus vector cells and highlight critical SFTSV restriction factors, while enriching transcriptomic and proteomic resources for future research.

RevDate: 2025-05-21

Li S, Zou J, Wu J, et al (2025)

New Insights into Natural Polyphenol-Enhanced Fe(III)/Peracetic Acid System under Acidic pH Conditions: The Overlooked Role of Coexisting Hydrogen Peroxide.

Environmental science & technology [Epub ahead of print].

Natural polyphenols have been extensively utilized as reducing agents to enhance contaminant degradation in the Fe(III)/peracetic acid (PAA) system. However, the roles of coexisting hydrogen peroxide (H2O2) remain insufficiently explored. This study, using protocatechuic acid (PCA) as a representative natural polyphenol, demonstrated that contaminant removal within the PCA/Fe(III)/PAA system under acidic pH conditions exhibited two kinetic stages: an initial rapid stage driven by PAA, followed by a slower stage driven by H2O2. The presence of H2O2 facilitated the complete degradation (100%) of contaminants even at low concentrations (<1.0 μM). Interestingly, these two stages contributed differently to various contaminants' degradation. Mechanistic investigations revealed that Fe(IV) was the major reactive species (RSs) for contaminant degradation during the PAA stage, while [•]OH dominated during the H2O2 stage. In brief, H2O2 enriched the generation pathways and types of RSs. Notably, besides PCA itself, the reaction intermediates (i.e., phenoxy radicals) formed during the reaction between PCA and RSs also played a key role in reducing Fe(III), which explained why the PCA/Fe(III)/PAA system was able to maintain sufficient Fe(II) to further interact with H2O2. Overall, this study highlighted the synergistic role of coexisting H2O2 and provided valuable insights for optimizing various contaminants' degradation in actual waters using PAA-based Fenton-like systems.

RevDate: 2025-05-20

Zhivkoplias E, da Silva JM, R Blasiak (2025)

How transdisciplinarity can help biotech-driven biodiversity research.

Trends in biotechnology pii:S0167-7799(25)00135-0 [Epub ahead of print].

The Kunming-Montreal Global Biodiversity Framework marks a significant step toward conserving genetic diversity on a global scale. Sequencing advancements have broadened biodiversity studies by enabling the mapping of species distributions, increasing understanding of ecological interactions, and monitoring genetic diversity. However, these tools are hindered by inequalities and biases, particularly in biodiversity-rich developing countries. To navigate these challenges, we propose strategies using the existing biotechnological toolbox to make biodiversity data more accessible and useful for research and development. This includes increasing funding for database curation, improving metadata standards, addressing inequalities in technological capacity, and supporting holistic capacity-building programmes. Implementing these strategies can unlock new opportunities for biodiversity research aligned with sustainable development principles and can contribute to improved conservation outcomes.

RevDate: 2025-05-20

Williams CM, Scelza BA, Slack SD, et al (2025)

A rapid accurate approach to inferring pedigrees in endogamous populations.

Genetics pii:8139127 [Epub ahead of print].

Accurate reconstruction of pedigrees from genetic data remains a challenging problem. Many relationship categories (e.g. half-sibships versus avuncular) can be difficult to distinguish without external information. Pedigree inference algorithms are often trained on European-descent families in urban locations. Thus, existing methods tend to perform poorly in endogamous populations for which there may be reticulations within the pedigrees and elevated haplotype sharing. We present a simple, rapid algorithm which initially uses only high-confidence first-degree relationships to seed a machine learning step based on summary statistics of identity-by-descent (IBD) sharing. One of these statistics, our ``haplotype score'', is novel and can be used to: (1) distinguish half-sibling pairs from avuncular or grandparent-grandchildren pairs; and (2) assign individuals to ancestor versus descendant generation. We test our approach in a sample of ∼700 individuals from northern Namibia, sampled from an endogamous population called the Himba. Due to a culture of concurrent relationships in the Himba, there is a high proportion of half-sibships. We accurately identify first through fourth-degree relationships and distinguish between various second-degree relationships: half-sibships, avuncular pairs, and grandparent-grandchildren. We further validate our approach in a second African-descent dataset, the Barbados Asthma Genetics Study (BAGS), and a European-descent founder population from Quebec. Accurate reconstruction of relatives facilitates estimation of allele frequencies, tracing allele trajectories, improved phasing, heritability and other population genomic questions.

RevDate: 2025-05-19

Narita M, Matsugaki R, Muramatsu K, et al (2025)

Obesity and risk of post-operative pneumonia among older adult patients with hip fracture: an obesity paradox.

Clinical nutrition ESPEN pii:S2405-4577(25)00317-1 [Epub ahead of print].

BACKGROUND & AIM: Hip fracture is a condition with a high incidence among older adults and is associated with a high post-operative mortality rate. Post-operative pneumonia is one of the most important risk factors for mortality, making its prevention essential. In recent years, reports on obesity paradoxes have increasingly been documented. Therefore, this study aimed to investigate the relationship between body mass index (BMI) and the risk of developing post-operative pneumonia using a large database.

METHOD: We included 407,203 patients aged 75 years or older who underwent surgery for hip fracture between 2014 and 2018 using Diagnosis Procedure Combination data, a healthcare reimbursement system. Patients were classified into six BMI categories: <16.0, 16.0-16.9, 17.0-18.4, 18.5-24.9, 25.0-29.9, and ≥30 kg/m[2]. Multilevel logistic regression analysis was performed based on BMI 18.5-24.9 kg/m[2] to determine odds ratios for post-operative pneumonia.

RESULTS: The data of 332,768 patients were included in the final analysis. Those with BMI <18.5 kg/m[2] demonstrated significantly higher odds of developing post-operative pneumonia compared to those with BMI between 18.5-24.9 kg/m[2], BMI <16.0 kg/m[2] (adjusted odds ratio [AOR: 2.14, 95% confidence interval [CI: 2.01-2.27 p<0.001); BMI 16.0-16.9 kg/m[2] (AOR: 1.57, 95% CI: 1.46-1.69, p<0.001); and BMI 17.0-18.4 kg/m[2] (AOR: 1.31, 95% CI: 1.24-1.39, p<0.001). Conversely, patients with BMI 25.0-29.9 kg/m[2] showed a risk of post-operative pneumonia compared to the other groups (AOR: 0.83, 95% CI: 0.76-0.91, p<0.001). Notably, a J-curve relationship was observed between BMI and the incidence of post-operative pneumonia.

CONCLUSION: Patients with higher BMI had a lower risk of developing post-operative pneumonia, revealing the presence of an obesity paradox between hip fracture and post-operative pneumonia. Patients with low BMI are at a higher risk and may benefit from enhanced preventive measures to mitigate the risk of pneumonia.

RevDate: 2025-05-21
CmpDate: 2025-05-19

Cordeiro AL, Cusack DF, Guerrero-Ramírez N, et al (2025)

TropiRoot 1.0: Database of tropical root characteristics across environments.

Ecology, 106(5):e70074.

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

RevDate: 2025-05-20

Ramos E, Schweizer M, Wu MY, et al (2025)

The genome sequence of the Yellow-legged Gull, Larus michahellis Naumann, 1840.

Wellcome open research, 10:129.

We present a genome assembly from a female specimen of Larus michahellis (Yellow-legged Gull; Chordata; Aves; Charadriiformes; Laridae). The genome sequence has a total length of 1,405.56 megabases. Most of the assembly (90.55%) is scaffolded into 35 chromosomal pseudomolecules, including the W and Z sex chromosomes. The mitochondrial genome has also been assembled and is 16.79 kilobases in length.

RevDate: 2025-05-19
CmpDate: 2025-05-16

Iminjili V, Crowther A, Fisher MT, et al (2025)

A dataset of scientific dates from archaeological sites in eastern Africa spanning 5000 BCE to 1800 CE.

Scientific data, 12(1):801.

Large collections of archaeological spatiotemporal data can reveal past cultural and demographic trends, land use strategies, and processes of environmental adaptation. Within Africa, archaeological Big Data can contribute to the study of the spread of agriculture, domesticated species, and specific artefacts and technologies, as well as their ecological impacts. Although reviews addressing these topics are available for different parts of the continent, existing mid-late Holocene archaeology datasets have yet to be compiled into a central, open-access, standardized informatic-oriented dataset. Here we present Wanyika, a dataset of scientific dates from archaeological sites in eastern Africa spanning almost 7 millennia, from ~5000 BCE to 1800 CE. This dataset compiles published scientific dates and associated botanical, faunal, iron, and ceramic finds from sites in Kenya, Tanzania, the Comoros Islands, and Madagascar. The records also include data for megafauna extinctions in Madagascar. We describe the spatiotemporal coverage of the dataset, how the data were collected, the structure of the dataset, and the applied quality control measures.

RevDate: 2025-05-18
CmpDate: 2025-05-16

Ha MK, Postovskaya A, Kuznetsova M, et al (2025)

Celluloepidemiology-A paradigm for quantifying infectious disease dynamics on a population level.

Science advances, 11(20):eadt2926.

To complement serology as a tool in public health interventions, we introduced the "celluloepidemiology" paradigm where we leveraged pathogen-specific T cell responses at a population level to advance our epidemiological understanding of infectious diseases, using SARS-CoV-2 as a model. Applying flow cytometry and machine learning on data from more than 500 individuals, we showed that the number of T cells with positive expression of functional markers not only could distinguish patients who recovered from COVID-19 from controls and pre-COVID donors but also identify previously unrecognized asymptomatic patients from mild, moderate, and severe recovered patients. The celluloepidemiology approach was uniquely capable to differentiate health care worker groups with different SARS-CoV-2 exposures from each other. T cell receptor (TCR) profiling strengthened our analysis by revealing that SARS-CoV-2-specific TCRs were more abundant in patients than in controls. We believe that adding data on T cell reactivity will complement serology and augment the value of infection morbidity modeling for populations.

RevDate: 2025-05-16

Arnold LE, Hendrix K, Pan X, et al (2025)

Lifestyle Effects in a Randomized Controlled Trial of Neurofeedback for Attention-Deficit/Hyperactivity Disorder.

Journal of child and adolescent psychopharmacology [Epub ahead of print].

Objectives/Background: Multiple factors influence symptom severity in Attention Deficit/Hyperactivity Disorder (ADHD). We examined four of these: diet, sleep hygiene, exercise, and lighting, in the International Collaborative ADHD Neurofeedback (ICAN) randomized clinical trial, which found large significant improvement with both active neurofeedback and control condition without treatment difference. Methods: A total of 142 participants aged 7-10 had breakfast and lunch intake and exercise recorded at each neurofeedback session. Parents completed the Children's Sleep Habits Questionnaire (CSHQ). Parents and teachers rated inattention on Conners3. Lifestyle changes were correlated with inattention changes. Results: At baseline, CSHQ correlated with parent-rated inattention (r = 0.17, p = 0.04), and length of sleep correlated with teacher-rated inattention (r = 0.20, p = 0.03). From baseline to treatment end food group variety (p = 0.029, d = 0.22) and sleep problems (p < 0.0001, d = -0.49) improved significantly, exercise time and protein intake marginally (p = 0.06 - 0.08). Parent-rated inattention improvement correlated with CSHQ improvement (Rho = 0.26, p = 0.002) and marginally with protein intake increase (Rho = 0.18, p = 0.06). The three components of the light-emitting-diode (LED)-induced circadian pathway hypothesis were significant. Conclusions: Most measures improved, but few significantly. How much they impact classroom attention remains unclear. Although parent ratings of inattention improvement correlated with sleep problems improvement, composited parent/teacher ratings (primary outcome) did not. The circadian pathway hypothesis associated with LED lighting was supported. These findings warrant further studies examining the role sleep hygiene can play in improving ADHD symptoms. Meanwhile, attention to sleep hygiene seems appropriate in any treatment plan for ADHD.

RevDate: 2025-05-15

Cirino T, Pinto L, Iwan M, et al (2025)

Consensus Modeling Strategies for Predicting Transthyretin Binding Affinity from Tox24 Challenge Data.

Chemical research in toxicology [Epub ahead of print].

Transthyretin (TTR) is a key transporter of the thyroid hormone thyroxine, and chemicals that bind to TTR, displacing the hormone, can disrupt the endocrine system, even at low concentrations. This study evaluates computational modeling strategies developed during the Tox24 Challenge, using a data set of 1512 compounds tested for TTR binding affinity. Individual models from nine top-performing teams were analyzed for performance and uncertainty using regression metrics and applicability domains (AD). Consensus models were developed by averaging predictions across these models, with and without consideration of their ADs. While applying AD constraints in individual models generally improved external prediction accuracy (at the expense of reduced chemical space coverage), it had limited additional benefit for consensus models. Results showed that consensus models outperformed individual models, achieving a root-mean-square error (RMSE) of 19.8% on the test set, compared to an average RMSE of 20.9% for the nine individual models. Outliers consistently identified in several of these models indicate potential experimental artifacts and/or activity cliffs, requiring further investigation. Substructure importance analysis revealed that models prioritized different chemical features, and consensus averaging harmonized these divergent perspectives. These findings highlight the value of consensus modeling in improving predictive performance and addressing model limitations. Future work should focus on expanding chemical space coverage and refining experimental data sets to support public health protection.

RevDate: 2025-05-15
CmpDate: 2025-05-15

Li YH, Y Zhang (2025)

[Wilderness network construction in Lincang City of Yunnan Province, Southwest China based on landscape connectivity].

Ying yong sheng tai xue bao = The journal of applied ecology, 36(4):1233-1243.

Constructing wilderness networks based on landscape connectivity is crucial for wilderness conservation. We calculated the continuous spectrum of the wilderness with GIS, identified wilderness sources with morphological spatial pattern analysis (MSPA), constructed wilderness corridors and networks and extracted wilderness strategic points with minimum cumulative resistance model (MCR) and circuit theory. We further analyzed the characte-ristics of the wilderness network, and proposed wilderness protection strategies and ecological planning suggestions for Lincang City. Results showed that wilderness was mainly distributed at 1000-2500 m elevation, with a spatial pattern of more in the south and east, less in the north and west in Lincang City. Grade 3 wilderness covered 55% of the total area, indicating high quality of the study area. Based on the MSPA analysis, we found 27 wilderness sources, most of which were distributed in the eastern and southern areas such as Linxiang and Cangyuan. The western and northern such as Fengqing and Yongde had fewer wilderness sources. There were 63 wilderness corridors in the wilderness network, including 16 important corridors and 47 general corridors. There were 186 strategic points in the wilderness network, including 53 wilderness nodes and 133 barrier points. We constructed the wilderness network of Lincang based in the identified wilderness source areas and extracted wilderness corridors, which had the advantages of high stability, strong resistance to interference, efficient connectivity. Finally, we proposed the "three-zone as a whole" protection strategy and ecological planning suggestions, which had referential value for establishing an ecological security pattern in Lincang City and the practicalization of wilderness protection in China.

RevDate: 2025-05-15
CmpDate: 2025-05-15

Dong WZ, Su WC, Gou R, et al (2025)

[Spatial and temporal evolution of ecological risk in Guizhou Province, China from the perspective of ecosystem services and ecosystem health].

Ying yong sheng tai xue bao = The journal of applied ecology, 36(4):1211-1221.

Guizhou Province is an important ecological barrier in the upper reaches of the Yangtze River and the Pearl River. Karst landform in Guizhou is developed, with fragile ecological background. The ecological risk assessment and control of Karst landform are of great significance to ecological security and sustainable development of southwest China and the upper reaches of those two rivers. Based on the InVEST model and vigor-organization-resi-lience model, we quantitatively evaluated the ecosystem services and ecosystem health and constructed the ecological risk assessment model of Guizhou Province. With the help of GIS technology, spatial autocorrelation analysis method and gravity center migration model, we analyzed the spatial and temporal variations of ecological risk in Guizhou Province from 2000 to 2020. The results showed that ecosystem services in Guizhou Province increased from 2000 to 2020, with an annual average growth rate of 0.3%. The ecosystem health status was generally well and showed a good trend, and the annual average growth rate of ecosystem health was 12.6%. The ecological risk was dominated by medium ecological risk. The proportion of extremely low ecological risk area and low ecological risk area increased, the proportion of medium and above ecological risk area decreased, and the overall ecological risk showed a downward trend. The low ecological risk areas were mainly located in the south and southeast of Guizhou Province, while the high ecological risk areas were distributed in the central, western and northern parts of Guizhou Province. The global Moran's I of ecological risk in 2000, 2005, 2010, 2015, and 2020 were 0.856, 0.836, 0.844, 0.804, and 0.768, respectively, indicating that the positive correlation of ecological risk in spatial distribution, but the spatial correlation and spatial agglomeration characteristics were weakened. During the study period, the centroid and trajectory of ecological risk in Guizhou Province were consistent with the distribution area of its corresponding ecological risk. From 2000 to 2020, the spatial distribution pattern of ecological risk in Guizhou Pro-vince was relatively stable. With the evolution of time, the dispersion of spatial distribution of extremely high ecological risk and low ecological risk increased. Ecological risk assessment based on ecosystem services and ecosystem health would provide scientific basis for regional ecological risk management and control.

RevDate: 2025-05-17
CmpDate: 2025-05-15

Wu B, Luo D, Yue Y, et al (2025)

New insights into the cold tolerance of upland switchgrass by integrating a haplotype-resolved genome and multi-omics analysis.

Genome biology, 26(1):128.

BACKGROUND: Switchgrass (Panicum virgatum L.) is a bioenergy and forage crop. Upland switchgrass exhibits superior cold tolerance compared to the lowland ecotype, but the underlying molecular mechanisms remain unclear.

RESULTS: Here, we present a high-quality haplotype-resolved genome of the upland ecotype "Jingji31." We then conduct multi-omics analysis to explore the mechanism underlying its cold tolerance. By comparative transcriptome analysis of the upland and lowland ecotypes, we identify many genes with ecotype-specific differential expression, particularly members of the cold-responsive (COR) gene family, under cold stress. Notably, AFB1, ATL80, HOS10, and STRS2 gene families show opposite expression changes between the two ecotypes. Based on the haplotype-resolved genome of "Jingji31," we detect more cold-induced allele-specific expression genes in the upland ecotype than in the lowland ecotype, and these genes are significantly enriched in the COR gene family. By genome-wide association study, we detect an association signal related to the overwintering rate, which overlaps with a selective sweep region containing a cytochrome P450 gene highly expressed under cold stress. Heterologous overexpression of this gene in rice alleviates leaf chlorosis and wilting under cold stress. We also verify that expression of this gene is suppressed by a structural variation in the promoter region.

CONCLUSIONS: Based on the high-quality haplotype-resolved genome and multi-omics analysis of upland switchgrass, we characterize candidate genes responsible for cold tolerance. This study advances our understanding of plant cold tolerance, which provides crop breeding for improved cold tolerance.

RevDate: 2025-05-20

Barroux M, Househam J, Lakatos E, et al (2025)

Evolutionary and immune microenvironment dynamics during neoadjuvant treatment of esophageal adenocarcinoma.

Nature cancer [Epub ahead of print].

Locally advanced esophageal adenocarcinoma remains difficult to treat and the ecological and evolutionary dynamics responsible for resistance and recurrence are incompletely understood. Here, we performed longitudinal multiomic analysis of patients with esophageal adenocarcinoma in the MEMORI trial. Multi-region multi-timepoint whole-exome and paired transcriptome sequencing was performed on 27 patients before, during and after neoadjuvant treatment. We found major transcriptomic changes during treatment with upregulation of immune, stromal and oncogenic pathways. Genetic data revealed that clonal sweeps through treatment were rare. Imaging mass cytometry and T cell receptor sequencing revealed remodeling of the tumor microenvironment during treatment. The presence of genetic immune escape, a less-cytotoxic T cell phenotype and a lack of clonal T cell expansions were linked to poor treatment response. In summary, there were widespread transcriptional and environmental changes through treatment, with limited clonal replacement, suggestive of phenotypic plasticity.

RevDate: 2025-05-17

Yi S, Li X, Liu Y, et al (2025)

A sub-meter resolution urban surface albedo dataset for 34 U.S. cities based on deep learning.

Scientific data, 12(1):789.

Surface albedo is a key determinant of urban heat islands, which modulates the amount of solar energy absorbed or reflected by urban surfaces, influencing microclimate and thermal comfort. However, high-resolution albedo is usually not available, which makes the understanding of the urban thermal environment at hyperlocal difficult. This study presents the first high-resolution urban albedo maps for 34 major U.S. cities using advanced deep learning models and multisource remote sensing data. By differentiating between impervious and pervious surfaces using a combination of NAIP imagery, roof albedo data, building footprints, land cover classifications, and Sentinel-2 imagery, this work achieves sub-meter resolution in albedo mapping. Employing U-Net for impervious surface classification along with impervious (ISA) and pervious surface albedo (PSA) prediction, these models were validated in selected cities, with ISA showing an R[2] of 0.9028 and MAE of 0.0057, and PSA demonstrating an R[2] of 0.9538 and MAE of 0.0027, highlighting the precision and reliability. The datasets, made publicly available, offer essential insights for urban planning and environmental monitoring.

RevDate: 2025-05-15

Ogba P, Baumann A, Alabi T, et al (2025)

Enhancing IPTp-SP uptake: Community and stakeholder recommendations for improving access and utilisation - insights from a study in Bayelsa-Nigeria.

MalariaWorld journal, 16:9.

BACKGROUND: Malaria remains a major global health challenge, disproportionately affecting pregnant women and children. In Nigeria, malaria in pregnancy contributes to 70.5% of maternal morbidity and 41.1% of maternal mortality. Recognising these risks, the World Health Organization recommends intermittent preventive treatment with sulfadoxine-pyrimethamine (IPTp-SP) as a key strategy for malaria in pregnancy prevention. However, despite its proven effectiveness, pregnant women's uptake of IPTp-SP remains unacceptably low. This study presents participant-driven recommendations to enhance IPTp-SP uptake, structured within the socio-ecological framework.

MATERIALS AND METHODS: This study employed an exploratory descriptive qualitative approach to examine the community-level contextual factors influencing IPTp-SP uptake. Data were collected from 53 participants in two communities in Bayelsa, Nigeria. Individual interviews were conducted with 17 key stakeholders (spouses, mothers-in-law, religious leaders, community leaders, and traditional birth attendants) and 6 focus group discussions with 36 pregnant women. Data management and coding were conducted using NVivo 14 QSR International software, following an inductive-deductive thematic analysis approach.

RESULTS: Participants proposed multi-level interventions to address barriers to IPTp-SP uptake at the individual, interpersonal, community, and healthcare system levels. Key recommendations include: Community-wide education campaigns to raise awareness of IPTp-SP's benefits; comprehensive training for healthcare providers to enhance their knowledge and prescription of IPTp-SP; integration of traditional birth attendants into the formal healthcare system; community-level distribution of IPTp-SP to improve access for pregnant women who do not attend antenatal care; government intervention to ensure the functionality of health centers; addressing workforce shortages, and guaranteeing a consistent supply of IPTp-SP.

CONCLUSION: These evidence-based, participant-driven recommendations offer a holistic and scalable strategy to improve pregnant women's uptake of IPTp-SP in Nigeria and other malaria-endemic regions. Implementing these recommendations can strengthen malaria prevention efforts, improve maternal and child health outcomes, and support broader public health initiatives.

RevDate: 2025-05-20
CmpDate: 2025-05-20

Shamash M, Sinha A, CF Maurice (2025)

Improving gut virome comparisons using predicted phage host information.

mSystems, 10(5):e0136424.

UNLABELLED: The human gut virome is predominantly made up of bacteriophages (phages), viruses that infect bacteria. Metagenomic studies have revealed that phages in the gut are highly individual specific and dynamic. These features make it challenging to perform meaningful cross-study comparisons. While several taxonomy frameworks exist to group phages and improve these comparisons, these strategies provide little insight into the potential effects phages have on their bacterial hosts. Here, we propose the use of predicted phage host families (PHFs) as a functionally relevant, qualitative unit of phage classification to improve these cross-study analyses. We first show that bioinformatic predictions of phage hosts are accurate at the host family level by measuring their concordance to Hi-C sequencing-based predictions in human and mouse fecal samples. Next, using phage host family predictions, we determined that PHFs reduce intra- and interindividual ecological distances compared to viral contigs in a previously published cohort of 10 healthy individuals, while simultaneously improving longitudinal virome stability. Lastly, by reanalyzing a previously published metagenomics data set with >1,000 samples, we determined that PHFs are prevalent across individuals and can aid in the detection of inflammatory bowel disease-specific virome signatures. Overall, our analyses support the use of predicted phage hosts in reducing between-sample distances and providing a biologically relevant framework for making between-sample virome comparisons.

IMPORTANCE: The human gut virome consists mainly of bacteriophages (phages), which infect bacteria and show high individual specificity and variability, complicating cross-study comparisons. Furthermore, existing taxonomic frameworks offer limited insight into their interactions with bacterial hosts. In this study, we propose using predicted phage host families (PHFs) as a higher-level classification unit to enhance functional cross-study comparisons. We demonstrate that bioinformatic predictions of phage hosts align with Hi-C sequencing results at the host family level in human and mouse fecal samples. We further show that PHFs reduce ecological distances and improve virome stability over time. Additionally, reanalysis of a large metagenomics data set revealed that PHFs are widespread and can help identify disease-specific virome patterns, such as those linked to inflammatory bowel disease.

RevDate: 2025-05-17

Nițescu M, Nedelescu MM, Moroşan E, et al (2025)

Assessment of Food Safety Knowledge and Practices Among Medical Students.

Foods (Basel, Switzerland), 14(9):.

Food safety is an important requirement for protecting human health worldwide. In particular, medical students' education on food safety is essential for them as future physicians, and university education is the first step in acquiring this knowledge. We performed an online survey with 1277 respondents among medical students to assess knowledge, attitudes, and practices (KAPs) related to food safety regarding microbiological contamination. Our findings showed that more than half of the respondents presented a low level of food safety knowledge, with a score between 11-60 points, and only 6% managed to score between 81 and 100 points, which was considered a high level of knowledge. On the contrary, we found that most participants had a high level of good practice: 58% scored more than 25 points, 39% had an average level of good practice (scoring between 21 and 25 points), and 3% of respondents had a low level of good practice (scoring below 21 points). We also noticed a statistically significant difference between total scores of preclinical and clinical years of study among medical students (p = 0.005) regarding food safety knowledge. The frequency of cooking was positively correlated with the level of food safety knowledge, but not with food safety practices. Our study shows that better knowledge on food safety is needed among medical students. Improving knowledge and awareness of food safety in relation to microbiological contamination is a good way to protect themselves and to promote the correct food safety knowledge and measures among their patients.

RevDate: 2025-05-16
CmpDate: 2025-05-14

Barkan R, Cooke I, Watson SA, et al (2025)

Synthesis of transcriptomic studies reveals a core response to heat stress in abalone (genus Haliotis).

BMC genomics, 26(1):474.

BACKGROUND: As climate change causes marine heat waves to become more intense and frequent, marine species increasingly suffer from heat stress. This stress can result in reduced growth, disrupted breeding cycles, vulnerability to diseases and pathogens, and increased mortality rates. Abalone (genus Haliotis) are an ecologically significant group of marine gastropods and are among the most highly valued seafood products. However, heat stress events have had devastating impacts on both farmed and wild populations. Members of this genus are among the most susceptible marine species to climate change impacts, with over 40% of all abalone species listed as threatened with extinction. This has motivated researchers to explore the genetics linked to heat stress in abalone. A substantial portion of publicly available studies has employed transcriptomic approaches to investigate abalone genetic response to heat stress. However, to date, no meta-analysis has been conducted to determine the common response to heat stress (i.e. the core response) across the genus. This study uses a standardized bioinformatic pipeline to reanalyze and compare publicly available RNA-seq datasets from different heat stress studies on abalone.

RESULTS: Nine publicly available RNA-seq datasets from nine different heat-stress studies on abalone from seven different abalone species and three hybrids were included in the meta-analysis. We identified a core set of 74 differentially expressed genes (DEGs) in response to heat stress in at least seven out of nine studies. This core set of DEGs mainly included genes associated with alternative splicing, heat shock proteins (HSPs), Ubiquitin-Proteasome System (UPS), and other protein folding and protein processing pathways.

CONCLUSIONS: The detection of a consistent set of genes that respond to heat stress across various studies, despite differences in experimental design (e.g. stress intensity, species studied-geographical distribution, preferred temperature range, etc.), strengthens our proposal that these genes are key elements of the heat stress response in abalone. The identification of the core response to heat stress in abalone lays an important foundation for future research. Ultimately, this study will aid conservation efforts and aquaculture through the identification of resilient populations, genetic-based breeding programs, possible manipulations such as early exposure to stress, gene editing and the use of immunostimulants to enhance thermal tolerance.

RevDate: 2025-05-13

Pourmohsenin B, Wiese A, N Ziemert (2025)

AutoMLST2: a web server for phylogeny and microbial taxonomy.

Nucleic acids research pii:8129379 [Epub ahead of print].

Accurate and accessible phylogenetic analysis is essential for understanding microbial taxonomy and evolution, which are integral to microbiology, ecology, and drug discovery, yet it remains a challenging task. AutoMLST2 (https://automlst2.ziemertlab.com) is a web server designed to facilitate automated phylogenetic reconstruction and microbial taxonomy analysis for bacterial and archaeal genomes. It builds on the foundation of AutoMLST, which remains widely used due to its user-friendly interface compared to similar tools. Given its continued popularity and utility, we have enhanced AutoMLST to leverage newer reference databases and computational tools. AutoMLST2 integrates the Genome Taxonomy Database, extends support to archaeal genomes, and improves analytical flexibility. Key improvements include more customizable processing modes, containerization to prevent queue accumulations, and parallel computing for large-scale studies. By incorporating up-to-date databases and workflows, AutoMLST2 continues to provide an accessible and efficient platform for researchers in microbiology, evolutionary ecology, and natural product discovery.

RevDate: 2025-05-18
CmpDate: 2025-05-18

Kičić M, Scheuer S, Korpilo S, et al (2025)

Relationships between urban green space types, cultural ecosystem services and disservices - a Public Participation Geographic Information System study in Zagreb, Croatia.

The Science of the total environment, 981:179549.

Urban green spaces are important providers of ecosystem services in cities, however cultural ecosystem services remain difficult to quantify. Different types of urban green spaces provide various cultural ecosystem services and differ in how they are perceived and utilized by citizens. In this study, we used a Public Participation GIS (PPGIS) survey to collect data on citizens' perceptions and use of cultural ecosystem services and disservices provided by different types of urban green spaces in Zagreb, Croatia. We collected spatial data from 384 respondents on the perceived provision of 19 different attributes of cultural ecosystem services and disservices in 20 defined types of urban green spaces. We used descriptive statistics, spatial metrics, multivariate analysis and visualization techniques to explore and explain 5757 spatial points collected with the PPGIS questionnaire. Results confirm the importance of parks and forests but also that the water elements and greenery around residential buildings serve as important urban green space for providing benefits for citizens of Zagreb. Based on results presented, cultural ecosystem services are perceived as more important than disservices but in some places both co-exist. Our study builds on current literature by providing a systematic, city-wide assessment of cultural ecosystem services related to different types of urban green spaces, while advancing the availability of methods for their quantification.

RevDate: 2025-05-17

Nieman DC, Sakaguchi CA, Williams JC, et al (2025)

Gut Prevotella copri abundance linked to elevated post-exercise inflammation.

Journal of sport and health science, 14:101039 pii:S2095-2546(25)00017-1 [Epub ahead of print].

PURPOSE: This study aimed to examine the linkage between gut microbiome taxa and exercise-induced inflammation.

METHODS: Twenty-five cyclists provided 4 stool samples during a 10-week period and cycled vigorously for 2.25 h at 67% maximal oxygen uptake (VO2max) in a laboratory setting. Blood samples were collected pre- and post-exercise, with additional samples collected at 1.5-h, 3-h, and 24-h post exercise. Primary outcomes included stool microbiome composition and alpha diversity via whole genome shotgun (WGS) sequencing (averaged from 4 stool samples) and a targeted panel of 75 plasma oxylipins. A total of 5719 taxa were identified, and the 339 that were present in more than 20% of stool samples were used in the analysis. Alpha diversity was calculated by evenness, and the Analysis of Composition of Microbiomes (ANCOM) differential abundance analysis was performed using Quantitative Insights Into Microbial Ecology-2 (QIIME2). A composite variable was calculated from 8 pro-inflammatory oxylipins generated from arachidonic acid (ARA) and cytochrome P-450 (CYP).

RESULTS: ARA-CYP oxylipins were significantly elevated for at least 3-h post-exercise (p < 0.001); they were strongly and positively related to Prevotella copri (P. copri) abundance (R[2] = 0.676, p < 0.001) and negatively related to gut microbiome alpha diversity (R[2] = 0.771, p < 0.001).

CONCLUSION: This analysis revealed for the first time a novel, positive relationship between gut microbiome P. copri abundance in cyclists and post-exercise pro-inflammatory oxylipins. These data demonstrate that about two-thirds of the wide variance in inflammation following prolonged and intensive exercise is largely explained by the abundance of a single gut bacterial species: P. copri.

RevDate: 2025-05-17
CmpDate: 2025-05-17

Keneally C, Chilton D, Dornan TN, et al (2025)

Multi-omics reveal microbial succession and metabolomic adaptations to flood in a hypersaline coastal lagoon.

Water research, 280:123511.

Microorganisms drive essential biogeochemical processes in aquatic ecosystems and are sensitive to both salinity and hydrological changes. As climate change and anthropogenic activities alter hydrology and salinity worldwide, understanding microbial ecology and metabolism becomes increasingly important for managing aquatic ecosystems. Biogeochemical processes were investigated on sediment microbial communities during a significant flood event in the hypersaline Coorong lagoon, South Australia (the largest in the Murray-Darling Basin since 1956). Samples from six sites across a salinity gradient were collected before and during flooding in 2022. To assess changes in microbial taxonomy and metabolic function, 16S rRNA amplicon sequencing was employed alongside untargeted liquid chromatography-mass spectrometry (LC-MS) to assess changes in microbial taxonomy and metabolic function. Results showed a decrease in microbial richness and diversity during flooding, especially in hypersaline conditions. Pre-flood communities were enriched with osmolyte-degrading and methanogenic taxa, alongside osmoprotectant metabolites, such as glycine betaine and choline. Flood conditions favored taxa such as Halanaerobiaceae and Beggiatoaceae, inducing inferred metagenomic shifts indicative of sulfur cycling and nitrogen reduction pathways, while also enriching a greater diversity of metabolites including Gly-Phe dipeptides and guanine. This study demonstrates that integrating metabolomics with microbial community analysis enhances understanding of ecosystem responses to disturbance. These findings suggest microbial communities rapidly change in response to salinity reductions while maintaining key biogeochemical functions. Such insights are valuable for ecosystem management and predictive modelling under environmental stressors such as flooding.

RevDate: 2025-05-13

Seminar KB, Damayanthi E, Priandana K, et al (2025)

AI-based system for food and beverage selection towards precision nutrition in Indonesian restaurants.

Frontiers in nutrition, 12:1590523.

The complexity surrounding food selection is attributable to the variability in foods, restaurants, and diners. The diversity of foods, where each dish may have a unique recipe across different restaurants, needs to be accounted for in personalized nutrition. However, personalized food selection poses a combinatorial challenge in selecting the most suitable food at a specific restaurant. The key question is how a diner visiting a particular restaurant can be assisted in selecting optimal foods and beverages based on factors such as sex, age, height, weight, and history of non-communicable diseases (NCDs). In this study, a genetic algorithm (GA) is used to develop a system that can address this issue in the context of Indonesian restaurants. In this system, a database with data on registered diners and foods is maintained. Foods comprise staple foods, side dishes, vegetables, and beverages, each containing its energy and nutrient content for a given restaurant. The nutritional adequacy of a single meal is determined by comparing the energy and nutrient content of the menu with the diner's nutritional needs. The novelty of the proposed system lies in combining scientific nutritional data with individual diner profiles for the selection of the best meal for a diner. This system differs from the existing food recommender applications in Indonesia, which typically do not consider specific diners, personalized nutrition, and NCD history. The proposed system is the first developed application prototype for Indonesian restaurants to overcome the inefficiency of the existing applications. In this study, the structure and chromosome content of the food, its corresponding energy and nutrient contents, and GA operators such as crossover, mutation, and tournament selection for determining the best meal using the defined fitness functions are discussed. The proposed system has been tested at Karimata Restaurant and proved to be highly suitable for the ultimate goal of meal selection for individual diners with different needs, and it can be replicated at other restaurants. Furthermore, user-centered evaluation has revealed that the system (a) increases nutritional understanding and health awareness; (b) is easy to use with comprehensive functions; and (c) promotes user satisfaction with personalized recommendations.

RevDate: 2025-05-14

Li S, Fan C, Kargarandehkordi A, et al (2024)

Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing.

AI (Basel, Switzerland), 5(4):2725-2738.

Substance use disorders affect 17.3% of Americans. Digital health solutions that use machine learning to detect substance use from wearable biosignal data can eventually pave the way for real-time digital interventions. However, difficulties in addressing severe between-subject data heterogeneity have hampered the adaptation of machine learning approaches for substance use detection, necessitating more robust technological solutions. We tested the utility of personalized machine learning using participant-specific convolutional neural networks (CNNs) enhanced with self-supervised learning (SSL) to detect drug use. In a pilot feasibility study, we collected data from 9 participants using Fitbit Charge 5 devices, supplemented by ecological momentary assessments to collect real-time labels of substance use. We implemented a baseline 1D-CNN model with traditional supervised learning and an experimental SSL-enhanced model to improve individualized feature extraction under limited label conditions. Results: Among the 9 participants, we achieved an average area under the receiver operating characteristic curve score across participants of 0.695 for the supervised CNNs and 0.729 for the SSL models. Strategic selection of an optimal threshold enabled us to optimize either sensitivity or specificity while maintaining reasonable performance for the other metric. Conclusion: These findings suggest that Fitbit data have the potential to enhance substance use monitoring systems. However, the small sample size in this study limits its generalizability to diverse populations, so we call for future research that explores SSL-powered personalization at a larger scale.

RevDate: 2025-05-10
CmpDate: 2025-05-11

Chen J, Liu J, Liu S, et al (2025)

Multiomics reveals the synergistic response of gut microbiota and spider A. ventricosus to lead and cadmium toxicity.

Bulletin of environmental contamination and toxicology, 114(5):77.

The potential crosstalk between the host and gut microbiota (GM) under heavy metal compound pollution remains unexplored. Herein, using comprehensive analysis of metagenomics, metabolomics, behavioral analysis, and cell morphology to investigate the causal relationship between GM and host responses to cadmium (Cd) and lead (Pb) toxicities. Results indicate that Pb and Cd pollution, alone or together, hinder spider predatory behavior and change the composition and function of GM. Combined exposure reduces protein and exogenous compound metabolism, while single exposure affects energy and lipid metabolism. Gut microbiota helps spider antioxidant activity by increasing glutathione, lipoic acid, and L-cysteine. Oxidative damage, increased Enterobacteriaceae (Salmonella), and lipopolysaccharide (LPS) may harm the midgut barrier. Upregulation of choline and acetylcholine, and downregulation of spermidine, may initiate neurotoxicity. Inhibiting actinomycetes might boost sodium gallate for detoxifying single contaminants. Combined pollution detoxification may involve downregulation of indole synthesis metabolic bacteria, tryptophan, indole metabolites, cytochrome P450 (CYP450), and an increase in Desulfobulbia could remove heavy metals and reduce oxidative stress. Combined pollution has a synergistic effect, making the toxicity of multiple pollutants greater than their individual effects, impacting metal resistance genes (MRGs), and antibiotic resistance ontology (AROs) which used for classifying and describing antibiotic resistance, midgut barrier integrity, oxidative stress, and detoxification. The results help to elucidate the interplay of GM and host's reactions, and aid in monitoring and bioremediation of heavy metal pollution.

RevDate: 2025-05-12
CmpDate: 2025-05-10

Sigwart JD, Wong NLWS, González VL, et al (2025)

Genome of the enigmatic watering-pot shell and morphological adaptations for anchoring in sediment.

BMC genomics, 26(1):460.

BACKGROUND: In this study, we present the first chromosome-scale genome of Verpa penis (Linnaeus, 1758), and the first for the bivalve clade Anomalodesmata. The present study has two separate foci. Primarily, we provide the genetic resource to bridge further studies from genome to phenome and propose hypotheses to guide future empirical investigations. Secondarily, based on morphology, we outline a conceptual exploration to address their adaptation. Watering-pot shells have been called "the weirdest bivalves" for their fused tubular shell resembling the spout of a watering can. This adventitious tube arose twice convergently in clavagelloidean bivalves. However, previous literature has never provided a convincing adaptive pathway.

RESULTS: The genome assembly of V. penis was about 507 Mb, with contig N50 of 5.33 Mb, and has 96.5% of sequences anchored onto 19 pseudochromosomes. Phylogenomic analyses of this new genome in context of other bivalves confirms the placement for Anomalodesmata as sister to the clade Imparidentia. Contrary to expectations from its highly modified body plan, there is no evidence of chromosome reduction compared to the ancestral karyotype of heterodont bivalves (1 N = 19). Drawing on established principles from engineering as well as morphology, the thought experiment about the adventitious tube seeks to extend current understanding by exploring parallels with other built structures. A new hypothesis explains one possible interpretation of the adaptive significance of this body form: it is potentially structurally optimised for vertical stability in relatively soft sediments, with parallels to the engineering principles of a suction anchor.

CONCLUSIONS: While the conclusions presented here on morphological interpretations are theoretical, this serves as a foundation for further empirical validation and refinement. Our study offers new insights to a long-standing mystery in molluscan body forms and provides genomic resources that are relevant to understanding molluscan evolution, biomineralisation, and biomimetic design.

RevDate: 2025-05-12
CmpDate: 2025-05-10

Bosso L, Saviano S, Abagnale M, et al (2025)

GIS-based integration of marine data for assessment and management of a highly anthropized coastal area.

Scientific reports, 15(1):16200.

Monitoring coastal marine environments by evaluating and comparing their chemical, physical, biological, and anthropogenic components is essential for ecological assessment and socio-economic development. In this study, we conducted an integrated multivariate analysis to assess the descriptors of the Marine Strategy Framework Directive at a regional scale in the Tyrrhenian Sea (Italy), with a specific focus on the densely populated coastal zone of the Campania region. Physical, chemical, and biological data were collected and analyzed in 22 sampling sites during three oceanographic surveys in the Gulf of Gaeta (GoG), Naples (GoN), and Salerno (GoS) in autumn 2020. Our results indicated that these three gulfs were distinct overall, with GoN being more divergent and heterogeneous than GoG and GoS. The marine area studied in the GoN had more favorable hydrographic and trophic conditions and food web characteristics, except for the mesozooplankton biomass, and was closer to socio-economic factors compared to the GoS and GoG. Our analysis helped us find the key ecological features that define different sub-regions and connect them to social and economic factors, including human activities. We highlighted the relevance of primary and secondary variables in terms of the comprehensive ecological assessment of a marine area and its impact on specific socio-economic activities. These findings support the need to describe and integrate multiple descriptors at the spatial scale.

RevDate: 2025-05-09
CmpDate: 2025-05-10

O'Callaghan ME, Casey M, Pearl D, et al (2025)

COVID-19 open data: An ecological study and international collaboration examining pandemic trends in Northern Periphery arctic countries.

Health informatics journal, 31(2):14604582251315588.

Objectives: In the early stages of the COVID-19 pandemic, evidence generation lagged behind public health responses. This study describes an international collaboration of frontline clinicians who used open data describing COVID-19 trends to generate "practice-based evidence". Methods: Open data resources from nine Northern Periphery and Arctic (NPA) countries were harnessed using the open-source programming language 'R' and our collaborations analyses and insights were published on a public-facing website. The website's visualisations guided teleconference discussions from September 2020 to March 2021, focusing on contextualizing national responses, especially in rural regions. Results: This project facilitated shared learning from COVID-19 trends and highlighted key aspects of national responses. Notably, rural NPA regions experienced less COVID-19 cases and mortality in the first year of the pandemic. Conclusion: This international collaborative effort, driven by open data analysis, provided a platform to share real-world insights. The study offers a potential template for future pandemics and emphasises the importance of sustaining open data resources, including granular data like excess mortality, for effective pandemic learning.

RevDate: 2025-05-11
CmpDate: 2025-05-10

Schindler Z, Larysch E, Fornoff F, et al (2025)

Flower power: Modeling floral resources of wild cherry (Prunus avium L.) for bee pollinators based on 3D data.

Ecology, 106(5):e70103.

Pollinator declines pose a threat to ecosystems and food production. Agriculture contributes to, but also suffers from, the erosion of pollination services. Our study explores the potential of trees in agricultural landscapes to support pollinators by providing floral resources. Our overarching objective is the quantification of floral resources produced by wild cherry (Prunus avium L.) that can be used by flower-visiting and pollinating insects such as bees. Using an innovative approach, we combine pollen measurements with manual counts of flowers on branches and 3D data derived from terrestrial laser scanning. This approach allows us to scale up flower numbers from branches to entire trees. The derived models for estimating the probability of flower occurrence (R[2] c = 0.52, R[2] m = 0.50) and the number of flowers per branch (R[2] c = 0.88, R[2] m = 0.84), as well as the number of flowers per tree (R[2] = 0.83), show good model fits with only a small set of predictors. The model fits indicate that, at the branch level, predicting flowering probability is more challenging than predicting flower abundance. We found differences in the number of flowers per branch in different crown sections, suggesting that floral resources are heterogeneously distributed. Furthermore, we demonstrate that the number of flowers per tree increases exponentially with tree dimension (stem diameter, crown volume). Therefore, large trees provide disproportionately more floral resources than small trees and are particularly worthy of conservation efforts. For example, our models estimate that a single tree with a stem diameter of 25 cm carries 195,535 flowers (95% CI: 159,991-237,318), thus providing about 57 cm[3] (95% CI: 32-88 cm[3]) of pollen and producing 170 g (95% CI: 48-345 g) nectar sugar per 24 h. This amount of pollen is sufficient to rear, for example, 5202 larvae (95% CI: 2886-8022) of Lasioglossum laticeps, a common and generalist sweat bee of cherry trees. In contrast, a smaller tree with a stem diameter of 10 cm provides only 8% of these resources. In conclusion, we demonstrate how our results contribute to the broader single-large-or-several-small debate in nature conservation by highlighting the value of large trees. Additionally, we show how information gathered at the branch level may be nondestructively upscaled to entire trees.

RevDate: 2025-05-12
CmpDate: 2025-05-10

Ramihangihajason TA, Weber JL, Rakotondraompiana S, et al (2025)

Natural capital accounting as a decision support tool for environmental management of a protected area in Madagascar.

PloS one, 20(5):e0321948.

Ecosystem change affects the availability of resources and services provided by nature. Ecosystem Natural capital accounting helps track these changes and supports better decision-making for managing the environment. This approach aims to assess changes in the stocks and flows of natural resources and the possibility to integrate them into economic and political decisions. The protected area of Mahavavy-Kinkony Complex, in North-Western of Madagascar, was chosen to implement this approach due to its many types of ecosystems as well as important reserves of threatened birds. In five years (2013-2018), we have observed a reduction in woodland cover (forest and mangrove) due to both regulated and illegal logging, linked to urban expansion and increasing of human pressure. This loss of woodland compromises not only biodiversity but also the capacity of ecosystems to provide ecosystem services. At the same time, the silting up of surface waters is compromising water quality and the health of aquatic ecosystems. In addition, the increase in agricultural land at the expense of forested areas raises concerns about the continuing degradation of natural ecosystems. All of these changes can be observed inside local socio-ecological landscape type. Each socio-ecological landscape type shows the potential variation in the production of ecosystem services.

RevDate: 2025-05-11
CmpDate: 2025-05-10

Longo L, Veronese M, Cagnato C, et al (2025)

Direct evidence for processing Isatis tinctoria L., a non-nutritional plant, 32-34,000 years ago.

PloS one, 20(5):e0321262.

Recovering evidence for the intentional use of plants in the Palaeolithic is challenging due to their perishable nature as, unlike chipped stone or bone artefacts, plant remains are rarely preserved. This has created a paradigm for the Palaeolithic in which plants seldom feature, resulting in a partial and skewed perspective; in fact, plants were as essential to human life then as they are today. Here, we combine morphological and spectroscopic analyses (µ-Raman, µ-FTIR) to provide robust multiscale physical and biomolecular evidence for the deliberate pounding and grinding of Isatis tinctoria L. leaves 34-32,000 years ago. The leaf epidermis fragments were found entrapped in the topography of the used surface of unmodified pebbles, in association with use-wear traces. Although their bitter taste renders them essentially inedible, the leaves have well-recognised medicinal properties and contain indigotin precursors, the chromophore responsible for the blue colour of woad, a plant-based dye that is insoluble in water. We used a stringent approach to contamination control and biomolecular analysis to provide evidence for a new perspective on human behaviour, and the applied technical and ecological knowledge that is likely to have prevailed in the Upper Palaeolithic. Whether this plant was used as a colourant, as medicine, or indeed for both remains unknown, but offers a new perspective on the fascinating possibilities of non-edible plant use.

RevDate: 2025-05-14

Cuenca PR, Souza FN, do Nascimento RC, et al (2025)

Using step selection functions to analyse human mobility using telemetry data in infectious disease epidemiology: a case study of leptospirosis.

medRxiv : the preprint server for health sciences.

Human movement plays a critical role in the transmission of infectious diseases, especially those with environmental drivers like leptospirosis-a zoonotic bacterial infection linked to mud and water contact. Using GPS loggers, we collected detailed telemetry data to understand how fine-scale movements can be analysed in the context of an infectious disease. We recruited individuals living in urban slums in Salvador, Brazil to analyse how they interact with environmental risk factors such as domestic rubbish piles, open sewers, and a local stream. We aimed to identify differences in movement patterns inside the study areas by gender, age, and leptospirosis serological status. Step-selection functions, a spatio-temporal model used in animal movement ecology, estimated selection coefficients to represent the likelihood of movement toward specific environmental factors. With 124 participants wearing GPS devices for 24 to 48 hours, recording locations every 35 seconds during active daytime hours, we segmented movements into morning, midday, afternoon, and evening. Our results suggested women moved closer to the central stream and farther from open sewers compared to men, while serologically positive individuals avoided open sewers. This study introduces a novel method for analysing human telemetry data in infectious disease research, providing critical insights for targeted interventions.

RevDate: 2025-05-13

Pekar JE, Lytras S, Ghafari M, et al (2025)

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2.

Cell pii:S0092-8674(25)00353-8 [Epub ahead of print].

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

RevDate: 2025-05-11
CmpDate: 2025-05-08

Benjamin JR, Neibauer J, Anthony H, et al (2025)

A partner-driven decision support model to inform the reintroduction of bull trout.

PloS one, 20(5):e0323427.

Assessments of species reintroductions involve a series of complex decisions that include human perspectives and ecological contexts. Here, we present a reintroduction assessment involving bull trout (Salvelinus confluentus) using a structured decision-making process. We approached this assessment by engaging partners representing public utilities, government agencies, and Tribes with shared interests in a potential reintroduction. These individuals identified objectives, decision alternatives, and ecological scenarios that were incorporated into a co-produced simulation-based model of potential reintroduction outcomes. The model included mathematical representations of habitat availability, life history expression, and assumptions regarding constraints on potential bull trout populations. Within each recipient stream, partners chose to explore a wide range of decision alternatives and simulated scenarios affecting reintroduction success. Results suggested that 1) reintroductions using eggs or adults were most optimal, 2) adding more individuals resulted in diminishing returns, 3) access to migratory habitat could improve success, and 4) the diversity of opportunities for life history expression led to improved reintroduction opportunities. In addition, modeled scenarios indicated some recipient streams consistently produced lower abundance of reintroduced bull trout. This work contributes a novel example to a growing portfolio of reintroduction assessments that may inform future conservation for bull trout and many other species facing similar challenges.

RevDate: 2025-05-10
CmpDate: 2025-05-08

Pakulnicka J, M Kruk (2025)

Water beetle networks differences and migration between natural lakes and post-exploitation water bodies.

Scientific reports, 15(1):15898.

Water deficits are a serious problem around the world, which also affects young landscapes, where lakes are most abundant. This poses a threat to many habitats and biological diversity found here. The relationships between species in the ecological networks of lakes at different stages of development and in nearby post-exploitation water bodies remain poorly understood. To better understand the functioning of beetle communities in different ecosystems, we created five network models that we subjected to graph analysis. By analysing the general attributes of the network (number of neighbours, shortest path, characteristic path length, clustering coefficient, network centralisation, network density and network heterogeneity) and those related to the nodes (NCC-Node Closeness Centrality, NBC-Node Betweenness Centrality, NDC-Node Degree Centrality) and to the edges (EBC-Edge Betweenness Centrality and correlations between the biomass of species as nodes), we were able to determine the role of each species in the networks and the relationships between the species. We then used the machine learning ensemble modelling XGBoost-SHAP to identify species that are particularly important in migrations between water bodies and to assess the direction and strength of migrations using Shapley values. Our analyses are based on faunal material from 25 lakes (mesotrophic, eutrophic, dystrophic) and 31-post-exploitation water bodies (clay pits and gravel pits) in northern Poland, in the Masurian Lake District. We found a total of 169 species representing different ecological and functional components. We have shown that the structures of the network between the biomass of species in the analysed five water types differ significantly. The highest value for network density was recorded in eutrophic lakes and clay ponds, the lowest in dystrophic lakes. In eutrophic lakes these are mainly eurybionts, in clay pits-rheophiles and in gravel pits-argilophiles and tyrphophiles. The relationship between the species with the highest NBC and EBC values is particularly important in order to maintain the stability of the network. The periphery of the network usually consists of larger predators that do not compete with each other. By analysing the migration directions of beetles between different ecosystems, we were able to demonstrate a greater affinity of the beetle fauna, especially the argilophiles (e.g. Scarodytes halensis and Laccobius minutus) inhabiting gravel pits, to dystrophic lakes. The beetles in clay pits originate mainly from mesotrophic lakes. These are mainly rheophiles, mostly weakly flying species, such as: Haliplus fluviatilis, Haliplus fulvus, Ilybius fenestratus, Hygrotus vericolor and Haliplus flavicollis. These species are important for the stability of ecological networks in the studied lake types. Their movements between the ecosystems studied in turn contribute to the functional connectivity between the individual lakes, which ensures the stabilisation of biotic relationships at the landscape level. At the same time, they generally also indicate the optimisation of environmental conditions in post-exploitation water bodies, which makes them potential substitute habitats for natural lakes.

RevDate: 2025-05-14
CmpDate: 2025-05-14

Gilpin W (2025)

Optimization hardness constrains ecological transients.

PLoS computational biology, 21(5):e1013051.

Living systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. In high-dimensional biological networks like ecosystems, long transients arise from the separate timescales of interactions within versus among subcommunities. Here, we use tools from computational complexity theory to frame equilibration in complex ecosystems as the process of solving an analogue optimization problem. We show that functional redundancies among species in an ecosystem produce difficult, ill-conditioned problems, which physically manifest as transient chaos. We find that the recent success of dimensionality reduction methods in describing ecological dynamics arises due to preconditioning, in which fast relaxation decouples from slow solving timescales. In evolutionary simulations, we show that selection for steady-state species diversity produces ill-conditioning, an effect quantifiable using scaling relations originally derived for numerical analysis of complex optimization problems. Our results demonstrate the physical toll of computational constraints on biological dynamics.

RevDate: 2025-05-14
CmpDate: 2025-05-14

Gu J, Shen Y, Guo L, et al (2025)

Investigation of the mechanisms of liver injury induced by emamectin benzoate exposure at environmental concentrations in zebrafish: A multi-omics approach to explore the role of the gut-liver axis.

Journal of hazardous materials, 491:138008.

Emamectin benzoate (EMB) is a lipophilic pesticide that enters aquatic systems and adversely affects non-target organisms. This study investigated the long-term effects of EMB on zebrafish, exposing them to concentrations of 0, 0.1, 1, and 10 μg/L from the 4-hour post-fertilization (hpf) embryo stage to the 120-day post-fertilisation (dpf) adult stage. We found that exposure to 1 μg/L EMB induced liver damage, manifested as impaired liver function (elevated aspartate aminotransferase (AST) and alanine aminotransferase (ALT)), histopathological damage (lipid accumulation), as well as inflammatory and oxidative damage, with a dose - dependent effect. Non-targeted metabolomic analysis revealed an increase in lipid molecules in the liver, affecting the pathways related to glycerophospholipid metabolism. In addition, EMB exposure resulted in damage to the intestinal barrier and inflammatory responses in zebrafish. 16S rRNA sequencing demonstrated that EMB exposure resulted in notable alterations in the gut microbiota composition. Notably, the abundance of Plesiomonas and Cetobacterium increased in the EMB exposure group and exhibited a positive correlation with the majority of liver lipid metabolites. In contrast, reductions in Muribaculaceae and Alloprevotella were negatively correlated. The results of this study indicate that long-term exposure to EMB disrupts the gut microbiota, leading to the dysregulation of hepatic phospholipid metabolism. These findings provide new insights into the health risks associated with EMB and highlight its potential threats to higher organisms, including mammals.

RevDate: 2025-05-14
CmpDate: 2025-05-14

Zielińska K, Udekwu KI, Rudnicki W, et al (2025)

Healthy microbiome-moving towards functional interpretation.

GigaScience, 14:.

BACKGROUND: Microbiome-based disease prediction has significant potential as an early, noninvasive marker of multiple health conditions linked to dysbiosis of the human gut microbiota, thanks in part to decreasing sequencing and analysis costs. Microbiome health indices and other computational tools currently proposed in the field often are based on a microbiome's species richness and are completely reliant on taxonomic classification. A resurgent interest in a metabolism-centric, ecological approach has led to an increased understanding of microbiome metabolic and phenotypic complexity, revealing substantial restrictions of taxonomy-reliant approaches.

FINDINGS: In this study, we introduce a new metagenomic health index developed as an answer to recent developments in microbiome definitions, in an effort to distinguish between healthy and unhealthy microbiomes, here in focus, inflammatory bowel disease (IBD). The novelty of our approach is a shift from a traditional Linnean phylogenetic classification toward a more holistic consideration of the metabolic functional potential underlining ecological interactions between species. Based on well-explored data cohorts, we compare our method and its performance with the most comprehensive indices to date, the taxonomy-based Gut Microbiome Health Index (GMHI), and the high-dimensional principal component analysis (hiPCA) methods, as well as to the standard taxon- and function-based Shannon entropy scoring. After demonstrating better performance on the initially targeted IBD cohorts, in comparison with other methods, we retrain our index on an additional 27 datasets obtained from different clinical conditions and validate our index's ability to distinguish between healthy and disease states using a variety of complementary benchmarking approaches. Finally, we demonstrate its superiority over the GMHI and the hiPCA on a longitudinal COVID-19 cohort and highlight the distinct robustness of our method to sequencing depth.

CONCLUSIONS: Overall, we emphasize the potential of this metagenomic approach and advocate a shift toward functional approaches to better understand and assess microbiome health as well as provide directions for future index enhancements. Our method, q2-predict-dysbiosis (Q2PD), is freely available (https://github.com/Kizielins/q2-predict-dysbiosis).

RevDate: 2025-05-14
CmpDate: 2025-05-14

Han Y, Du Q, Dai Y, et al (2025)

EasyOmics: A graphical interface for population-scale omics data association, integration, and visualization.

Plant communications, 6(5):101293.

The rapid growth of population-scale whole-genome resequencing, RNA sequencing, bisulfite sequencing, and metabolomic and proteomic profiling has led quantitative genetics into the era of big omics data. Association analyses of omics data, such as genome-, transcriptome-, proteome-, and methylome-wide association studies, along with integrative analyses of multiple omics datasets, require various bioinformatics tools, which rely on advanced programming skills and command-line interfaces and thus pose challenges for wet-lab biologists. Here, we present EasyOmics, a stand-alone R Shiny application with a user-friendly interface that enables wet-lab biologists to perform population-scale omics data association, integration, and visualization. The toolkit incorporates multiple functions designed to meet the increasing demand for population-scale omics data analyses, including data quality control, heritability estimation, genome-wide association analysis, conditional association analysis, omics quantitative trait locus mapping, omics-wide association analysis, omics data integration, and visualization. A wide range of publication-quality graphs can be prepared in EasyOmics by pointing and clicking. EasyOmics is a platform-independent software that can be run under all operating systems, with a docker container for quick installation. It is freely available to non-commercial users at Docker Hub https://hub.docker.com/r/yuhan2000/easyomics.

RevDate: 2025-05-14
CmpDate: 2025-04-21

Fuller TJ, Lambert DN, DiClemente RJ, et al (2025)

Reach and Capacity of Black Protestant Health Ministries as Sites of Community-Wide Health Promotion: A Qualitative Social Ecological Model Examination.

Journal of racial and ethnic health disparities, 12(2):887-898.

Black communities in the Southeast United States experience a disproportionate burden of illness and disease. To address this inequity, public health practitioners are partnering with Black Protestant churches to deliver health promotion interventions. Yet, the reach of these programs beyond the organizational level of the Social Ecological Model (SEM) is not well defined. Thus, the aim of this study is to understand Black Protestant church leaders' and members' perceptions about the capacity of their ministries to reach into their communities, beyond their congregations, as providers or hosts of health education or promotion interventions. From 20 Black Protestant churches in Atlanta, GA, 92 church leaders and members participated in semi-structured interviews. Grounded theory guided data analysis and a diverse team coded the interviews. Most participating churches had health ministries. Participants saw the boundaries between their churches at the organizational level of the SEM and the broader Black community to be porous. Those who described their "community" as being broader than their congregation also tended to describe community-wide health promotion their church engaged in. They described church-based health fairs as a strategy to promote engagement in their communities. Some participants, particularly those in a health-related profession, discussed visions of how to utilize their church as a site for community-wide health promotion. We suggest these participants may be boundary leaders who can build relationships between public health professionals, pastors, and congregants. Based on the findings, we suggest that church-based health fairs may be effective sites of community-wide health promotion.

RevDate: 2025-05-13
CmpDate: 2025-05-07

Niculescu AG, Mitache MM, Grumezescu AM, et al (2025)

From Microbial Ecology to Clinical Challenges: The Respiratory Microbiome's Role in Antibiotic Resistance.

Pathogens (Basel, Switzerland), 14(4):.

Antibiotic resistance represents a growing public health threat, with airborne drug-resistant strains being especially alarming due to their ease of transmission and association with severe respiratory infections. The respiratory microbiome plays a pivotal role in maintaining respiratory health, influencing the dynamics of antibiotic resistance among airborne pathogenic microorganisms. In this context, this review proposes the exploration of the complex interplay between the respiratory microbiota and antimicrobial resistance, highlighting the implications of microbiome diversity in health and disease. Moreover, strategies to mitigate antibiotic resistance, including stewardship programs, alternatives to traditional antibiotics, probiotics, microbiota restoration techniques, and nanotechnology-based therapeutic interventions, are critically presented, setting an updated framework of current management options. Therefore, through a better understanding of respiratory microbiome roles in antibiotic resistance, alongside emerging therapeutic strategies, this paper aims to shed light on how the global health challenges posed by multi-drug-resistant pathogens can be addressed.

RevDate: 2025-05-13
CmpDate: 2025-05-13

Hwang H, Kim D, Kim S, et al (2025)

Optimizing urban green spaces using a decision-support model for carbon sequestration and ecological connectivity.

Journal of environmental management, 384:125058.

Urban green spaces (UGSs) are vital for enhancing urban ecological health and resident well-being. However, their diverse functions need to be balanced based on spatial limitations and varying stakeholder preferences. Integrated planning approaches are needed to exploit the multiple benefits of UGSs. This study introduces a multi-objective decision-support model designed to optimize UGS planning by simultaneously addressing carbon sequestration, ecological connectivity, and cost constraints. The model incorporates the non-dominated sorting genetic algorithm II to identify Pareto-optimal solutions for tailored decision-making strategies that balance different priorities. The model indicated that ecological connectivity can be improved by 7.57 % while meeting carbon-reduction and budgetary targets. The model effectively balanced trade-offs, underscoring the importance of both the quantity and strategic placement of green space. This decision-support framework empowers decision-makers to rapidly simulate and validate optimal scenarios, effectively balance competing objectives, and provide a scientific basis through verifiable feedback, ultimately promoting the development of sustainable urban environments.

RevDate: 2025-05-13
CmpDate: 2025-05-13

Nkoh JN, Ye T, Shang C, et al (2025)

Deciphering the mechanisms for preferential tolerance of Escherichia coli BL21 to Cd(II) over Cu(II) and Ni(II): A combined physiological, biochemical, and multiomics perspective.

Ecotoxicology and environmental safety, 297:118195.

Environmental pollution severely affects ecological functions/health, and nondegradable pollutants such as heavy metals (HMs) cause significant damage to living organisms. Escherichia coli is one of the most studied life forms, and its response to oxidative stress is driven by a complex ensemble of mechanisms driven by transcriptomic-level adjustments. However, the magnitude of the physiological, metabolic, and biochemical alterations and their relationships with transcriptomic changes remain unclear. Studying the growth of E. coli in Cd-, Cu-, and Ni-polluted media at pH 5.0, we observed that (i) downregulation of the alkyl hydroperoxide complex, glutathione reductase, and glutathione S-transferase by Cd inhibited H2O2 degradation, and the accumulated H2O2 was respectively 2.7, 1.7, and 2.4 times greater than that in the control, Cu, and Ni treatments; (ii) Zn-associated resistance protein (ZraP) was the major scavenger of Cd, with a 140.7-fold increase in its expression; (iii) the P-type Cu[+] transporter (CopA), multicopper oxidase (CueO), and heteromultimeric transport system (CusCBAF) controlled the excretion and detoxification of Cu; (iv) the Cd[2+]/Zn[2+]/Pb[2+]-exporting P-type ATPase (ZntA) and transcriptional activator ZntR were the major transporters of Ni; (v) Cd upregulated biofilm formation and synthesis of secondary metabolites more than Cu and Ni, which resulted in increased adsorption and improved tolerance; and (vi) the activity of superoxide dismutase in Cu-spiked cells was 153.2 %, 141.7 %, and 172.7 % higher and corresponded to 85.7 %, 524.5 %, and 491.5 % lower O2[●][-] in the control, Cd-, and Ni-spiked cells, respectively. This study reveals E. coli's preferential tolerance mechanisms to Cd rather than Cu and Ni and demonstrates mechanisms for its survival in highly polluted environments.

RevDate: 2025-05-09
CmpDate: 2025-05-07

Zheng K, Feng Y, Liu R, et al (2025)

Bioinformatics Analysis Reveals the Evolutionary Characteristics of the Phoebe bournei ARF Gene Family and Its Expression Patterns in Stress Adaptation.

International journal of molecular sciences, 26(8):.

Auxin response factors (ARFs) are pivotal transcription factors that regulate plant growth, development, and stress responses. Yet, the genomic characteristics and functions of ARFs in Phoebe bournei remain undefined. In this study, 25 PbARF genes were identified for the first time across the entire genome of P. bournei. Phylogenetic analysis categorized these genes into five subfamilies, with members of each subfamily displaying similar conserved motifs and gene structures. Notably, Classes III and V contained the largest number of members. Collinearity analysis suggested that segmental duplication events were the primary drivers of PbARF gene family expansion. Structural analysis revealed that all PbARF genes possess a conserved B3 binding domain and an auxin response element, while additional motifs varied among different classes. Promoter cis-acting element analysis revealed that PbARF genes are extensively involved in hormonal responses-particularly to abscisic acid and jasmonic acid and abiotic stresses-as well as abiotic stresses, including heat, drought, light, and dark. Tissue-specific expression analysis showed that PbARF25, PbARF23, PbARF19, PbARF22, and PbARF20 genes (class III), and PbARF18 and PbARF11 genes (class V) consistently exhibited high expression levels in the five tissues. In addition, five representative PbARF genes were analyzed using qRT-PCR. The results demonstrated significant differences in the expression of PbARF genes under various abiotic stress conditions (drought, salt stress, light, and dark), indicating their important roles in stress response. This study laid a foundation for elucidating the molecular evolution mechanism of ARF genes in P. bournei and for determining the candidate genes for stress-resistance breeding.

RevDate: 2025-05-09
CmpDate: 2025-05-07

Li H, Wang R, Pan J, et al (2025)

Bioinformatics Analysis of the Glutamate-Gated Chloride Channel Family in Bursaphelenchus xylophilus.

International journal of molecular sciences, 26(8):.

Glutamate-gated chloride channels (GluCls), a class of ion channels found in the nerve and muscle cells of invertebrates, are involved in vital life processes. Bursaphelenchus xylophilus, the pathogen of pine wilt disease, has induced major economic and ecological losses in invaded areas of Asia and Europe. We identified 33 GluCls family members by sequence alignment analysis. A subsequent bioinformatic analysis revealed the physicochemical properties, protein structure, and gene expression patterns in different developmental stages. The results showed that GluCls genes are distributed across all six chromosomes of B. xylophilus. These proteins indicated a relatively conserved structure by NCBI-conserved domains and InterPro analysis. A gene structure analysis revealed that GluCls genes consist of 5 to 14 exons. Expression pattern analysis revealed BxGluCls were extensively involved in the development of second instar larvae of B. xylophilus. Furthermore, BxGluCls15, BxGluCls25, and BxGluCls28 were mainly associated with the development of eggs of B. xylophilus. BxGluCls12, BxGluCls18, and BxGluCls32 were predominantly linked to nematode resistance and adaptation. Investigation the structure and expression patterns of BxGluCls is crucial to understand the developmental trends of B. xylophilus. It also helps identify molecular targets for the development of biopesticides or drugs designed to control this nematode.

RevDate: 2025-05-11
CmpDate: 2025-05-11

Duarte T, Martin GM, Anjos-Santos D, et al (2025)

Unraveling Plecoptera Diversity in Two Protected Areas of Argentine Patagonia.

Anais da Academia Brasileira de Ciencias, 97(1):e20240085 pii:S0001-37652025000101305.

The Plecoptera taxonomy in Patagonia is well-documented, yet their distribution remains poorly understood, hindering comprehensive ecological and biogeographical studies. This study enhances knowledge of stonefly distribution in two Patagonian national parks: Nahuel Huapi and Los Alerces. Extensive fieldwork, georeferenced species records, and geographic information system data integration were conducted. Species richness was calculated using polygons (0.1° x 0.1° pixels) across ecoregions, with species indexed from rare to ubiquitous. Cluster analyses revealed faunal affinities across ecosystem complexes, and richness estimators (Jack1, Jack2, and Chao2) highlighted knowledge gaps. Results showed uneven species distribution, with the highest richness polygon (n = 19) in Los Alerces. The Northern Moist Forests hosted the most species, followed by the Transitional Cypress-Beech Forests. The rarest species were also found in these two complexes, as well as the Ecotone Steppe-Forest. Cluster analysis revealed strong affinities between the Northern Moist Forests of Nahuel Huapi and Ecotone Steppe-Forest. Richness estimators suggested up to 23 undocumented species. Though much remains to be learned about Plecoptera distribution in Patagonia, this study emphasizes the critical role of national parks in conserving biodiversity and provides a foundation for future conservation strategies, identifying new taxa records, including southernmost distributions.

RevDate: 2025-05-11
CmpDate: 2025-05-11

Shi J, Gong J, Zhang Y, et al (2025)

Spatiotemporal change in ecological quality of the Qinghai-Tibetan Plateau based on an improved remote sensing ecological index and Google Earth Engine platform.

Environmental monitoring and assessment, 197(4):355.

The Qinghai-Tibetan Plateau (QTP) serves as a vital ecological security barrier in China and globally. Evaluating changes in ecological quality on the QTP provides critical insights for regional conservation initiatives. This study, tailored to the unique characteristics of the region, develops an Improved Remote Sensing Ecological Index (IRSEI) framework by integrating Gross Primary Productivity (GPP) with the Normalized Difference Vegetation Index (NDVI), humidity (WET), Land Surface Temperature (LST), and the Negative Drought Index (NDBSI). This comprehensive index aims to provide a more precise assessment of the environmental quality of the alpine ecosystem. It investigates spatial and temporal variations in ecological quality across the QTP, as well as within individual geographic subregions from 2000 to 2020. The first principal component accounts for an average variance of 63.69%. Over the past 20 years, the spatial distribution pattern of IRSEI on the QTP has shown lower values in the northwest, higher values in the southeast, and predominantly poor grades throughout the region. The mean trend coefficient for IRSEI was 0.002, indicating a gradual improvement in ecological quality on the QTP over time. Among 11 influencing factors examined, NDVI and GPP exhibit significant positive correlation with ecological quality, with q statistics of 0.942 and 0.932, respectively, underscoring the substantial impact of vegetation cover on ecosystem quality. These findings provide a robust theoretical foundation for supporting ecological management, restoration efforts, and the evaluation of ecological restoration within the QTP, thereby promoting ecosystem balance.

RevDate: 2025-05-09
CmpDate: 2025-05-07

Yang Y, Liu X, Wu J, et al (2025)

A comprehensive county-level distribution database of alien and invasive plants in China.

Ecology, 106(5):e70084.

Over the past half century, international trade and exchange have continued to increase in China, resulting in the widespread introduction of alien plant species. The accumulation of these alien species has accelerated invasion events, posing serious threats to local ecological security and economic development. Comprehensive and accurate species distribution records are extremely important for early detection, understanding dispersal dynamics, and supporting various management strategies and research initiatives. However, biodiversity databases, both global and local, often lack comprehensive and high-resolution distribution data for alien invasive plant species (AIPs). This limitation is particularly evident in China, where local databases typically provide coarse spatial data, often restricted to the provincial level, leading to a substantial underestimation of the actual distribution of AIPs. Here, we fill this gap by creating the most comprehensive distribution database for AIPs in China at a much finer spatial resolution. By integrating 73,469 distribution records from China's online herbarium, biodiversity databases, flora, published literature, and 173,396 georeferenced records from GBIF, we built the county-level distribution database for 400 AIPs and report for the first time their presence in 2684 administrative counties in China (92.5% of the total counties). Notably, our database provides 2.58 times more distribution records than global biodiversity data repositories such as GBIF and also includes the earliest introduction dates for each AIP. The temporal range of the records spans from 1607 to 2023, capturing over 400 years of AIP presence in China. These rigorously quality-controlled georeferenced data can be used to examine the dynamics and influencing factors of plant invasions in China. They can also serve as the most updated data reference for policy makers in designing effective AIP management policies in China. We encourage users to cite this data paper when utilizing the data, and there are no restrictions on its use for non-commercial purposes.

RevDate: 2025-05-10
CmpDate: 2025-05-10

Williams B, Balvanera SM, Sethi SS, et al (2025)

Unlocking the soundscape of coral reefs with artificial intelligence: pretrained networks and unsupervised learning win out.

PLoS computational biology, 21(4):e1013029.

Passive acoustic monitoring can offer insights into the state of coral reef ecosystems at low-costs and over extended temporal periods. Comparison of whole soundscape properties can rapidly deliver broad insights from acoustic data, in contrast to detailed but time-consuming analysis of individual bioacoustic events. However, a lack of effective automated analysis for whole soundscape data has impeded progress in this field. Here, we show that machine learning (ML) can be used to unlock greater insights from reef soundscapes. We showcase this on a diverse set of tasks using three biogeographically independent datasets, each containing fish community (high or low), coral cover (high or low) or depth zone (shallow or mesophotic) classes. We show supervised learning can be used to train models that can identify ecological classes and individual sites from whole soundscapes. However, we report unsupervised clustering achieves this whilst providing a more detailed understanding of ecological and site groupings within soundscape data. We also compare three different approaches for extracting feature embeddings from soundscape recordings for input into ML algorithms: acoustic indices commonly used by soundscape ecologists, a pretrained convolutional neural network (P-CNN) trained on 5.2 million hrs of YouTube audio, and CNN's which were trained on each individual task (T-CNN). Although the T-CNN performs marginally better across tasks, we reveal that the P-CNN offers a powerful tool for generating insights from marine soundscape data as it requires orders of magnitude less computational resources whilst achieving near comparable performance to the T-CNN, with significant performance improvements over the acoustic indices. Our findings have implications for soundscape ecology in any habitat.

RevDate: 2025-05-09
CmpDate: 2025-05-07

Hou L, Zhao Z, Steger-Mähnert B, et al (2025)

Microbial metabolism in laboratory reared marine snow as revealed by a multi-omics approach.

Microbiome, 13(1):114.

BACKGROUND: Marine snow represents an organic matter-rich habitat and provides substrates for diverse microbial populations in the marine ecosystem. However, the functional diversity and metabolic interactions within the microbial community inhabiting marine snow remain largely underexplored, particularly for specific metabolic pathways involved in marine snow degradation. Here, we used a multi-omics approach to explore the microbial response to laboratory-reared phytoplankton-derived marine snow.

RESULTS: Our results demonstrated a dramatic shift in both taxonomic and functional profiles of the microbial community after the formation of phytoplankton-derived marine snow using a rolling tank system. The changes in microbial metabolic processes were more pronounced in the metaproteome than in the metagenome in response to marine snow. Fast-growing taxa within the Gammaproteobacteria were the most dominant group at both the metagenomic and metaproteomic level. These Gammaproteobacteria possessed a variety of carbohydrate-active enzymes (CAZymes) and transporters facilitating substrate cleavage and uptake, respectively. Analysis of metagenome-assembled genomes (MAGs) revealed that the response to marine snow amendment was primarily mediated by Alteromonas, Vibrio, and Thalassotalea. Among these, Alteromonas exclusively expressing auxiliary activities 2 (AA2) of the CAZyme subfamily were abundant in both the free-living (FL) and marine snow-attached (MA) microbial communities. Thus, Alteromonas likely played a pivotal role in the degradation of marine snow. The enzymes of AA2 produced by these Alteromonas MAGs are capable of detoxifying peroxide intermediates generated during the breakdown of marine snow into smaller poly- and oligomers, providing available substrates for other microorganisms within the system. In addition, Vibrio and Thalassotalea MAGs exhibited distinct responses to these hydrolysis products of marine snow in different size fractions, suggesting a distinct niche separation. Although chemotaxis proteins were found to be enriched in the proteome of all three MAGs, differences in transporter proteins were identified as the primary factor contributing to the niche separation between these two groups. Vibrio in the FL fraction predominantly utilized ATP-binding cassette transporters (ABCTs), while Thalassotalea MAGs in the MA fraction primarily employed TonB-dependent outer membrane transporters (TBDTs).

CONCLUSIONS: Our findings shed light on the essential metabolic interactions within marine snow-degrading microbial consortia, which employ complementary physiological mechanisms and survival strategies to effectively scavenge marine snow. This work advances our understanding of the fate of marine snow and the role of microbes in carbon sequestration in the ocean. Video Abstract.

RevDate: 2025-05-06
CmpDate: 2025-05-07

Zhang H, Wen T, Wang Z, et al (2025)

[Multi-omics analysis of hormesis effect of lanthanum chloride on carotenoid synthesis in Rhodotorula mucilaginosa].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology, 41(4):1631-1648.

Hormesis effect has been observed in the secondary metabolite synthesis of microorganisms induced by rare earth elements. However, the underlying molecular mechanism remains unclear. To analyze the molecular mechanism of the regulatory effect of Rhodotorula mucilaginosa in the presence of lanthanum chloride, different concentrations of lanthanum chloride were added to the fermentation medium of Rhodotorula mucilaginosa, and the carotenoid content was subsequently measured. It was found that the concentrations of La[3+] exerting the promotional and inhibitory effects were 0-100 mg/L and 100-400 mg/L, respectively. Furthermore, the expression of 33 genes and the synthesis of 55 metabolites were observed to be up-regulated, while the expression of 85 genes and the synthesis of 123 metabolites were found to be down-regulated at the concentration range of the promotional effect. Notably, the expression of carotenoid synthesis-related genes except AL1 was up-regulated. Additionally, the content of β-carotene, lycopene, and astaxanthin demonstrated increases of 10.74%, 5.02%, and 3.22%, respectively. The expression of 5 genes and the synthesis of 91 metabolites were up-regulated, while the expression of 35 genes and the synthesis of 138 metabolites were down-regulated at the concentration range of the inhibitory effect. Meanwhile, the content of β-carotene, lycopene, and astaxanthin decreased by 21.73%, 34.81%, and 35.51%, respectively. In summary, appropriate concentrations of rare earth ions can regulate the synthesis of secondary metabolites by modulating the activities of various enzymes involved in metabolic pathways, thereby exerting the hormesis effect. The findings of this study not only contribute to our comprehension for the mechanism of rare earth elements in organisms but also offer a promising avenue for the utilization of rare earth elements in diverse fields, including agriculture, pharmaceuticals, and healthcare.

RevDate: 2025-05-08

Pitogo KME, Meneses CG, Flores ABA, et al (2025)

Caught in statistical noise: pitfalls of a unidimensional approach to understanding biodiversity-conflict relationships.

npj biodiversity, 4(1):17.

RevDate: 2025-05-05

Compton ZT, Vincze O, Mellon W, et al (2025)

Paradoxical indeed.

Proceedings of the National Academy of Sciences of the United States of America, 122(19):e2504512122.

RevDate: 2025-05-08
CmpDate: 2025-05-06

Oyelayo EA, Taiwo TJ, Oyelude SO, et al (2025)

The global impact of industrialisation and climate change on antimicrobial resistance: assessing the role of Eco-AMR Zones.

Environmental monitoring and assessment, 197(6):625.

This study examines the relationship between industrialisation, climate change, and antimicrobial resistance (AMR) gene prevalence. Data analysis from the top 20 highly industrialised and the top 20 least industrialised nations revealed that industrial activities significantly contribute to global warming, with temperature increases of up to 2 °C observed in highly industrialised regions. These environmental changes influence the distribution and evolution of AMR genes, as rising temperatures can affect bacterial resistance in a manner similar to antibiotics. Through a bioinformatics approach, a marked disparity in AMR gene frequencies was observed between highly industrialised and less industrialised nations, with developed countries reporting higher frequencies due to extensive antibiotic use and advanced monitoring systems. 'Eco-AMR Zones' is proposed as a solution to specialised areas by promoting sustainable industrial practices, enforcing pollution controls, and regulating antibiotic use to mitigate AMR's environmental and public health impacts. These zones, supported by collaboration across various sectors, offer a promising approach to preserving antibiotic effectiveness and reducing environmental degradation. The study emphasises the importance of integrated global strategies that address both the ecological and public health challenges posed by AMR, advocating for sustainable practices, international collaboration, and ongoing research to combat the evolving threats of climate change and antimicrobial resistance.

RevDate: 2025-05-08
CmpDate: 2025-05-08

Wei L, Luo Z, Wu X, et al (2025)

Multi-omics analysis provided insights into the fruit softening of postharvest okra under carboxymethyl chitosan treatment.

International journal of biological macromolecules, 307(Pt 3):142149.

To understand the potential regulatory mechanism of carboxymethyl chitosan (CMCS) treatment on postharvest softening of okra, a joint analysis of physiologic index, transcriptome and metabolome was used. The results showed that CMCS could delay the deterioration of the apparent quality of okra and reduce the degradation of chlorophyll. CMCS can reduce the accumulation of WSP and CSP and the decrease of NSP, and inhibit the enzyme activities of pectin degradation (PE, PG, PL). The results of metabolic pathways related to quality and texture showed that CMCS could increase the metabolic level of pentose phosphate pathway (PPP), inhibit the expression of membrane lipid degradation-related genes, and balance the expression of antioxidant-related genes. Ethylene and abscisic acid (ABA) are two important phytohormones. CMCS down-regulates the biosynthesis of ethylene and increases the expression of ABA. The combined analysis of transcriptome and metabolome showed that CMCS could significantly up-regulate flavonoid biosynthesis metabolites and transcriptional expression levels. Cellulose and pectin are important polymers to maintain the rigidity of okra cell wall. CMCS treatment can slow down the accumulation of cellulose by regulating the expression of DEGs related to cellulose synthesis (CesA) and degradation (EGase). CMCS slowed down the degradation of pectin by down-regulating the expression of pectin degradation-related genes. These results indicate that the quality of okra is deteriorated and the fruit is softened during cold storage. CMCS treatment can improve the nutritional quality of okra and slow down its texture decline. In this study, the regulatory effect of CMCS on softening and quality deterioration of okra during cold storage was discussed at the molecular level, which provided a reference for improving the quality of postharvest okra.

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

Torres-Roman JS, Quispe-Vicuña C, Benavente-Casas A, et al (2025)

Trends in stroke mortality in Latin America and the Caribbean from 1997 to 2020 and predictions to 2035: An analysis of gender, and geographical disparities.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association, 34(6):108286.

BACKGROUND: Stroke is a leading cause of death and disability globally, with significant public health implications. In Latin America, while mortality rates have declined, the number of stroke cases has increased due to prevalent risk factors like high blood pressure and obesity. Unlike Europe, recent trends in stroke mortality in this region remain underreported.

OBJECTIVE: This study evaluates stroke mortality rates in Latin America Latin American and Caribbean (LAC) countries from 1997 to 2020 and predictions to 2035.

METHODS: This ecological observational study utilized mortality data from the World Health Organization database. Trends were analyzed using Joinpoint regression to evaluate the annual percent change (APC) by sex and country. Predicted mortality rates through 2035 were calculated using the Nordpred package in R. Changes in stroke mortality were assessed by disentangling the effects of population growth, aging, and risk factor modifications, based on age-specific rates and projections. Results were presented as absolute case numbers and relative percentages.

RESULTS: From 1997 to 2020, twelve countries presented significant reductions in stroke mortality rates for men in LAC, the main ones being Chile (-4.2 %), El Salvador (-4.2 %), and Puerto Rico (-4.0 %). Thirteen countries reported a reduction in their mortality for women, mainly in Puerto Rico (-4.3 %), Chile (-3.7 %), Argentina, El Salvador, and Uruguay (-3.5 %). By 2035, an increase in deaths among men and women is expected, mainly due to the increase in population structure and size. However, a decrease in the mortality rate will be reported, mainly due to the reduction of risk factors.

CONCLUSION: Our final findings show a reduction in stroke mortality trends in LAC countries between 1997 and 2020, due to creating public awareness about vascular risk factors by authorities and the implementation of effective health policies. By 2035, an overall increase in mortality is expected, mainly due to population change in each country.

RevDate: 2025-05-08
CmpDate: 2025-05-08

Hinojosa-Alvarez S, Mendoza-Portillo V, Chavez-Santoscoy RA, et al (2025)

The draft genome assembly of the cosmopolitan pelagic fish dolphinfish Coryphaena hippurus.

G3 (Bethesda, Md.), 15(5):.

For the first time, the complete genome assembly of the dolphinfish (Coryphaena hippurus), a tropical cosmopolitan species with commercial fishing importance was sequenced. Using a combination of Illumina and Nanopore sequencing technologies, a draft genome of 497.8 Mb was assembled into 6,044 contigs, with an N50 of 200.9 kb and a BUSCO genome completeness score of 89%. This high-quality genome assembly provides a valuable resource to study adaptive evolutionary processes and supports conservation and management strategies for this ecologically and economically significant species.

RevDate: 2025-05-04
CmpDate: 2025-05-05

Wang Y, Mao Z, Yu J, et al (2025)

Construction of risk management system for polluted sites in coal industry clusters.

Environmental geochemistry and health, 47(6):195.

Coal has always been the main source of energy in China, accounting for more than 60% of primary energy production and consumption. As a result of coal mining, coal industry agglomerations such as mining, coal chemical industry, and so on have been gradually formed, and there are many types of industries in the agglomerations, complex sources of pollutants, and sensitive soil and water environments, and all kinds of industrial sites and solid waste dumps of coal-related industries may pollute the soil and groundwater, and have a certain impact on the ecological environment. However, at present, there is a lack of a targeted region-wide pollution risk management technology system for the polluted sites in the agglomeration area, therefore, it is particularly important to construct a scientific and complete soil-groundwater risk management system and propose more targeted and effective control strategies for the polluted sites in the coal industry agglomeration area. Based on the domestic and international experience and historical data, this paper takes the coal industry cluster area as the research object classifies the land in the area according to the land use type into construction land, agricultural land, and another ecological land, and carries out the risk zoning and grading based on the dosage-effect model and the potential ecological hazard index method respectively, assesses the appropriateness, feasibility, and necessity of the implementation of risk control for the polluted plots, and then designs and develops a risk control decision-making framework by using the hierarchical analysis method. Hierarchical analysis was used to design and develop a decision-making framework for risk management, and finally, the optimal risk management and remediation strategy was proposed based on the AHP + TOPSIS algorithm, which combined with the contaminated land conditions to propose a suitable solution.

RevDate: 2025-05-03

Lucca E, Kofinas D, Avellán T, et al (2025)

Corrigendum to "Integrating 'nature' in the water-energy-food nexus: Current perspectives and future directions" [Science of The Total Environment, Volume 966, 2025, 178600].

RevDate: 2025-05-03

Aguilar-Gómez D, Bejder J, Graae J, et al (2025)

Genetic and training adaptations in the Haenyeo divers of Jeju, Korea.

Cell reports pii:S2211-1247(25)00348-1 [Epub ahead of print].

Natural selection and relative isolation have shaped the genetics and physiology of unique human populations from Greenland to Tibet. Another such population is the Haenyeo, the all-female Korean divers renowned for their remarkable diving abilities in frigid waters. Apnea diving induces considerable physiological strain, particularly in females diving throughout pregnancy. In this study, we explore the hypothesis that breath-hold diving has shaped physiological and genetic traits in the Haenyeo. We identified pronounced bradycardia during diving, a likely training effect. We paired natural selection and genetic association analyses to investigate adaptive genetic variation that may mitigate the effects of diving on pregnancy through an associated reduction of diastolic blood pressure. Finally, we identified positively selected variation in a gene previously associated with cold water tolerance, which may contribute to reduced hypothermia susceptibility. These findings highlight the importance of traditional diving populations for understanding genetic and physiological adaptation.

RevDate: 2025-05-03

Gomes MLS, Cestari VRF, Florêncio RS, et al (2025)

Spatial-temporal analysis of cervical cancer screening and social and health indicators in Brazil.

Public health, 243:105747 pii:S0033-3506(25)00193-3 [Epub ahead of print].

OBJECTIVE: To identify the spatial-temporal patterns of cervical cancer (CC) screening in Brazil from 2013 to 2022 and its relationship with social and health indicators.

STUDY DESIGN: This ecological study uses data from the Cancer Information System (SISCAN) of the Brazilian Unified Health System's Department of Informatics.

METHODS: The study analyzed women aged 25 to 64 who underwent CC screening in 5570 municipalities across Brazil. Global Moran's I and the Local Index of Spatial Autocorrelation (LISA) were employed to investigate clustering. The purely spatial scan statistic technique was used for spatial cluster detection. Temporal trends were assessed using joinpoint regression. GeoDa, SaTScan, GWR, and QGIS software were used for the analysis.

RESULTS: The global clustering analysis of CC screening proportions revealed significant spatial autocorrelation (Moran's I = 0.530). Clusters of municipalities with low screening rates were significantly observed in the Northern (Amapá, Amazonas, Rondônia, Roraima) and Northeastern (Piauí, Pernambuco) regions. The Gini Index (β = -2.60), the Municipal Human Development Index (MHDI) (β = -10.5), and the Social Vulnerability Index (SVI) (β = -9.14) showed negative associations. Conversely, Family Health Strategy (FHS) coverage (β = 2.18) demonstrated a positive impact on screening rates. In terms of temporal trends, the screening proportion gradually increased from 5.4 % in 2014 to 10.5 % in 2022.

CONCLUSION: Areas with a high risk of low CC screening rates were identified in the Northern and Northeastern regions of Brazil, which are characterized by socioeconomic and demographic disparities, vulnerabilities, and inequalities.

RevDate: 2025-05-05
CmpDate: 2025-05-03

Seizer L, Pascher A, Branz S, et al (2025)

Bridging acute and chronic stress effects on inflammation: protocol for a mixed-methods intensive longitudinal study.

BMC psychology, 13(1):464.

Acute stress triggers adaptive physiological responses-including transient increases in inflammatory cytokines-while chronic stress is associated with sustained inflammatory activity that may underlie the development of various disorders. Despite extensive research on each stress type individually, the transition and interaction between them remain underexplored. This study aims to address this gap by employing an intensive longitudinal measurement burst design. Healthy university students will be recruited and monitored over three one-week assessment bursts, spaced by three-month breaks. Participants will complete ecological momentary assessments four times daily, recording their emotional states, stress experiences, and daily incidents. Simultaneously, saliva samples will be collected at matching time points to measure biomarkers of immune and stress system activity. In addition, daily audio diaries will provide qualitative context through advanced speech analysis techniques. Data will be analyzed using a multi-level modeling approach to differentiate within-person dynamics from between-person variability, accounting for potential moderators. The findings are expected to shed light on how repeated acute stressors transition into chronic stress and how chronic stress burden may influence acute stress responses.

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RJR Experience and Expertise

Researcher

Robbins holds BS, MS, and PhD degrees in the life sciences. He served as a tenured faculty member in the Zoology and Biological Science departments at Michigan State University. He is currently exploring the intersection between genomics, microbial ecology, and biodiversity — an area that promises to transform our understanding of the biosphere.

Educator

Robbins has extensive experience in college-level education: At MSU he taught introductory biology, genetics, and population genetics. At JHU, he was an instructor for a special course on biological database design. At FHCRC, he team-taught a graduate-level course on the history of genetics. At Bellevue College he taught medical informatics.

Administrator

Robbins has been involved in science administration at both the federal and the institutional levels. At NSF he was a program officer for database activities in the life sciences, at DOE he was a program officer for information infrastructure in the human genome project. At the Fred Hutchinson Cancer Research Center, he served as a vice president for fifteen years.

Technologist

Robbins has been involved with information technology since writing his first Fortran program as a college student. At NSF he was the first program officer for database activities in the life sciences. At JHU he held an appointment in the CS department and served as director of the informatics core for the Genome Data Base. At the FHCRC he was VP for Information Technology.

Publisher

While still at Michigan State, Robbins started his first publishing venture, founding a small company that addressed the short-run publishing needs of instructors in very large undergraduate classes. For more than 20 years, Robbins has been operating The Electronic Scholarly Publishing Project, a web site dedicated to the digital publishing of critical works in science, especially classical genetics.

Speaker

Robbins is well-known for his speaking abilities and is often called upon to provide keynote or plenary addresses at international meetings. For example, in July, 2012, he gave a well-received keynote address at the Global Biodiversity Informatics Congress, sponsored by GBIF and held in Copenhagen. The slides from that talk can be seen HERE.

Facilitator

Robbins is a skilled meeting facilitator. He prefers a participatory approach, with part of the meeting involving dynamic breakout groups, created by the participants in real time: (1) individuals propose breakout groups; (2) everyone signs up for one (or more) groups; (3) the groups with the most interested parties then meet, with reports from each group presented and discussed in a subsequent plenary session.

Designer

Robbins has been engaged with photography and design since the 1960s, when he worked for a professional photography laboratory. He now prefers digital photography and tools for their precision and reproducibility. He designed his first web site more than 20 years ago and he personally designed and implemented this web site. He engages in graphic design as a hobby.

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

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Collection of publications by R J Robbins

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

Research Gate page for R J Robbins

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

Curriculum Vitae for R J Robbins

short personal version

Curriculum Vitae for R J Robbins

long standard version

RJR Picks from Around the Web (updated 11 MAY 2018 )