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Bibliography on: Ecological Informatics

RJR-3x

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

RJR: Recommended Bibliography 26 Jun 2025 at 01:46 Created: 

Ecological Informatics

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

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

Citations The Papers (from PubMed®)

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RevDate: 2025-06-20
CmpDate: 2025-06-17

Basava K, Alam MNU, Roberts L, et al (2025)

Mapping nonhuman cultures with the Animal Culture Database.

Scientific data, 12(1):1019.

Socially transmitted behaviors are widespread across the animal kingdom, yet there is a lack of comprehensive datasets documenting their distribution and ecological significance. Knowledge of animal behavioral traditions could be essential for understanding many species' responses to anthropogenic disturbances and further enhancing conservation efforts. Here, we introduce the first open-access database that synthesizes data on animal cultural behaviors and traditions. The Animal Culture Database (ACDB) contains descriptions of 128 behaviors including forms of vocal communication, migration, predator defense, foraging practices, habitat alteration, play, mating displays, and other social behaviors for an initial sample of 61 species. In addition to offering an open-access resource for researchers, educators, and conservationists, the ACDB represents a step toward recognizing the role of social learning in animal populations.

RevDate: 2025-06-18

Jánošíková R, Tulis F, Baláž I, et al (2025)

Range expansion during recolonization: what does animal personality have to do with it?.

Behavioral ecology : official journal of the International Society for Behavioral Ecology, 36(4):araf053.

At the edge of an ongoing expansion, pioneer individuals encounter novel ecological and evolutionary pressures that may not be experienced by conspecifics settled in long-colonized areas. Consistent behavioral differences among conspecifics (animal personality) may be important determinants of individuals' successful colonization of novel environments and range expansion. By enhancing an individual's ability to find food and shelter as well as increasing its capacity to navigate novel environments, behavioral traits such as exploration and risk-taking are thus expected to be more highly expressed in populations undergoing expansion than in established populations. We investigated among-individual variation in behaviors associated to risk-taking and exploratory tendencies in populations of small mammals during different stages of the colonization process. Using a standardized behavioral test in the field, we quantified exploration and boldness of striped field mice (Apodemus agrarius, N = 95) from six subpopulations from Germany, where they are established, and in Slovakia, where a recolonization of the area is currently in progress, and in control species bank voles (Myodes glareolus, N = 76) that shared the same habitats but were long-established at all sites. Striped field mice in the expanding populations were significantly slower in exploring the open field arena, while showing comparable levels of risk taking compared to conspecifics from established populations. No difference in behavior was detected between the populations of bank voles. Our results suggest that a slow exploration strategy might play an advantageous role in expansion processes of small mammal populations.

RevDate: 2025-06-20
CmpDate: 2025-06-17

Perillo VL, Nute M, Sapoval N, et al (2025)

A survey of computational approaches for characterizing microbial interactions in microbial mats.

Genome biology, 26(1):168.

In this review, we use microbial mat communities as a general model system to highlight the strengths and limitations of current computational methods for analyzing interactions between members of microbial ecosystems. We describe the factors that make this environment have such a high degree of interaction, and we explore different categories of both laboratory and computational tools for studying these interactions. For each tool, we describe efforts to apply them to microbial mats in the past and, in the process, argue that genome-scale metabolic models have breakthrough potential for modeling microbial interactions in microbial mats.

RevDate: 2025-06-16

Barfuss W, Flack J, Gokhale CS, et al (2025)

Collective cooperative intelligence.

Proceedings of the National Academy of Sciences of the United States of America, 122(25):e2319948121.

Cooperation at scale is critical for achieving a sustainable future for humanity. However, achieving collective, cooperative behavior-in which intelligent actors in complex environments jointly improve their well-being-remains poorly understood. Complex systems science (CSS) provides a rich understanding of collective phenomena, the evolution of cooperation, and the institutions that can sustain both. Yet, much of the theory in this area fails to fully consider individual-level complexity and environmental context-largely for the sake of tractability and because it has not been clear how to do so rigorously. These elements are well captured in multiagent reinforcement learning (MARL), which has recently put focus on cooperative (artificial) intelligence. However, typical MARL simulations can be computationally expensive and challenging to interpret. In this perspective, we propose that bridging CSS and MARL affords new directions forward. Both fields can complement each other in their goals, methods, and scope. MARL offers CSS concrete ways to formalize cognitive processes in dynamic environments. CSS offers MARL improved qualitative insight into emergent collective phenomena. We see this approach as providing the necessary foundations for a proper science of collective, cooperative intelligence. We highlight work that is already heading in this direction and discuss concrete steps for future research.

RevDate: 2025-06-17

Maldonado M, Pita L, Hentschel U, et al (2025)

The chromosomal genome sequence of the sponge Crambe crambe (Schmidt, 1862) and its associated microbial metagenome sequences.

Wellcome open research, 10:275.

We present a genome assembly from an individual Crambe crambe (Porifera; Demospongiae; Poecilosclerida; Crambeidae). The host genome sequence is 143.20 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 19.53 kilobases in length. Several symbiotic prokaryotic genomes were assembled as MAGs, including two relevant sponge symbionts, the Candidatus Beroebacter blanensis/ AqS2 clade (Tethybacterales, Gammaproteobacteria) of LMA sponges, and the widely distributed archaeal Nitrosopumilus sp. clade.

RevDate: 2025-06-16

Hilbert A, Klotz U, Sadeghi S, et al (2025)

Smartphone-Supported Cognitive-Behavioral Therapy in Binge-Eating Disorder: An Exploratory Randomized Trial.

The International journal of eating disorders [Epub ahead of print].

OBJECTIVE: To assess the feasibility of a smartphone app delivering just-in-time adaptive interventions as an adjunct to cognitive-behavioral therapy (CBT) adapted to binge-eating disorder (BED), estimate its effects assuming superiority over CBT alone, and document safety and target engagement.

METHOD: A single-center, assessor-blinded, parallel feasibility study randomized adults aged 18-65 years with full-syndrome or subthreshold BED to smartphone-supported CBT (SmartCBT) or standard CBT (DRKS00024597). Both arms received 16 individual 50-min CBT sessions over 4 months. Assessments were conducted at baseline (T0), midtreatment (T1), posttreatment (T2), and 3-month follow-up (T3). Feasibility was determined regarding recruitment, attrition, dropout, adherence, assessment completion, app use, and acceptance. Further, eating disorder symptoms, mental and physical health, weight management behavior, safety, and target engagement (i.e., skill use) were assessed.

RESULTS: Over a 7-month recruitment period, 28 of 50 eligible volunteers were included and randomized 1:1 to SmartCBT or CBT. In the modified intent-to-treat sample (N = 25; SmartCBT: 13, CBT: 12), the feasibility of SmartCBT was further supported regarding attrition, dropout, adherence, treatment completion, app use, and acceptance; however, assessment completion was moderate. Clinical improvements were found in both arms, but differential results were affected by baseline differences and moderate assessment completion in the SmartCBT arm. Safety was documented, and support for target engagement was found.

CONCLUSIONS: This exploratory study provides evidence for the feasibility of app-supported CBT for BED. With few procedural refinements, the protocol can be used in a confirmatory randomized-controlled trial with long-term follow-up to evaluate efficacy and determine treatment mechanisms.

TRIAL REGISTRATION: German Clinical Trials Register, https://www.drks.de, DRKS00024597.

RevDate: 2025-06-25

Gontjes KJ, Singh A, Sansom SE, et al (2025)

Phylogenetic context of antibiotic resistance provides insights into the dynamics of resistance emergence and spread.

medRxiv : the preprint server for health sciences.

BACKGROUND: To ameliorate the antibiotic resistance crisis, the drivers of resistance emergence (i.e., de novo evolution) and resistance spread (i.e., cross-transmission) must be better understood.

METHODS: Whole-genome sequencing and susceptibility testing were performed on clinical carbapenem-resistant Klebsiella pneumoniae isolates collected from August 2014 to July 2015 across 12 hospitals. Ancestral state reconstruction partitioned patients with resistant strains into those that likely acquired resistance via de novo evolution or cross-transmission. Logistic regression was used to evaluate the associations between patient characteristics/exposures and these two pathways: resistance due to predicted within-host emergence of resistance, and resistance due to predicted cross-transmission. This framework is available in the user-friendly R package, phyloAMR (https://github.com/kylegontjes/phyloAMR).

RESULTS: Phylogenetic analysis of 386 epidemic lineage carbapenem-resistant Klebsiella pneumoniae sequence type 258 isolates revealed differences in the relative contribution of de novo evolution and cross-transmission to the burden of resistance to five antibiotics. Clade-specific variations in rates of resistance emergence and their frequency and magnitude of spread were detected for each antibiotic. Phylogenetically-informed regression modeling identified distinct clinical risk factors associated with each pathway. Exposure to the cognate antibiotic was an independent risk factor for resistance emergence (trimethoprim-sulfamethoxazole, colistin, and beta-lactam/beta-lactamase inhibitors) and resistance spread (trimethoprim-sulfamethoxazole, amikacin, and colistin). In addition to antibiotic exposures, comorbidities (e.g., stage IV+ decubitus ulcers) and indwelling devices (e.g., gastrostomy tubes) were detected as unique risk factors for resistance spread.

CONCLUSIONS: Phylogenetic contextualization generated insights and hypotheses into how bacterial genetic background, patient characteristics, and clinical practices influence the emergence and spread of antibiotic resistance.

RevDate: 2025-06-25
CmpDate: 2025-06-25

Valverde S, Vidiella B, Martínez-Redondo GI, et al (2025)

Structural Changes in Gene Ontology Reveal Modular and Complex Representations of Biological Function.

Molecular biology and evolution, 42(6):.

The Gene Ontology is a central resource for representing biological knowledge, yet its internal structure is often treated as static-or as a black box-in computational analyses. Here, we examine 15 years of Gene Ontology evolution using network-based methods, revealing that Gene Ontology changes not only through incremental growth but also through punctuated, curator-driven restructuring. In particular, we document a major reorganization of the Cellular Component branch in 2019, where broad "part" terms were removed and the ontology was modularized into distinct domains for anatomical entities and protein-containing complexes. Semantic modularity aligns Gene Ontology with emerging frameworks such as the Common Anatomy Reference Ontology and Gene Ontology-Causal Activity Modeling, but also disrupts similarity metrics that rely solely on hierarchical proximity. More broadly, the restructuring of the cellular components branch consolidates a shift toward treating Gene Ontology as a multi-layer semantic network-a transformation rooted in a decade-long process of scientific and social consensus across institutions. These findings underscore the need for version-aware, multi-layer models to ensure reproducibility and interpretability-and to better represent biological function across compositional, spatial, and regulatory dimensions as ontologies continue to evolve.

RevDate: 2025-06-18
CmpDate: 2025-06-16

Gurung S, Lee CM, Weon HY, et al (2025)

Comparative Genome Analysis of Three Halobacillus Strains Isolated From Saline Environments Reveal Potential Salt Tolerance and Algicidal Mechanisms.

Environmental microbiology reports, 17(3):e70121.

Harmful algal blooms (HABs) pose a significant global threat to water ecosystems, prompting extensive research into their inhibition and control strategies. This study presents genomic and bioinformatic analyses to investigate the algicidal potential and elucidate the survival mechanisms in harsh conditions of newly identified Halobacillus species three strains (SSTM10-2[T], SSBR10-3[T], and SSHM10-5[T]) isolated from saline environments. Moreover, genomic and bioinformatic analyses were conducted to elucidate their survival mechanisms in harsh conditions. Moreover, comparative genomic analysis revealed a diverse set of orthologous genes, with a core genome primarily associated with metabolism and information processing. Pangenome analysis highlighted accessory and unique genes potentially involved in environmental adaptation and stress response. Functional annotation using KEGG pathways identified genes linked to xenobiotic compound degradation, stress tolerance, and salt adaptation. Additionally, the study elucidated potential mechanisms underlying algicidal activity, implicating Carbohydrate-Active enZYmes (CAZymes), cytochrome P450 oxidases (CYP), and quorum sensing (QS) systems. Finally, analysis of KEGG pathways related to microcystin degradation suggested the strains' capacity to mitigate HABs. Thus, this research enhances understanding of the genomic diversity, phylogeny, and functional characteristics of Halobacillus species, offering insights into their ecological roles and potential applications in biotechnology and environmental management.

RevDate: 2025-06-13

Clauss M, Roller M, Bertelsen MF, et al (2025)

Reply to Ferraro et al.: Breed-and-feed reflects inevitable trade-offs between individual longevity and population sustainability.

Proceedings of the National Academy of Sciences of the United States of America, 122(26):e2509145122.

RevDate: 2025-06-15

Jiao Y, Miao X, Wang L, et al (2025)

The Engineered Synthesis and Enhancement of Nitrogen and Chlorine Co-Doped Fluorescent Carbon Dots for the Sensitive Detection of Quercetin.

Materials (Basel, Switzerland), 18(11):.

Flavonoid alcohols, particularly quercetin, as emerging antioxidants, demand advanced detection methodologies to comprehensively explore and evaluate their potential environmental and health risks. In this study, nitrogen-chlorine co-doped carbon dots (N, Cl-CDs), featuring an extended wavelength emission at 625 nm, were synthesized via the reaction of 4-chloro-1,2-phenylenediamine with polyethyleneimine. The engineered N, Cl-CDs exhibit superior photostability, exceptional aqueous dispersibility, and anti-interference capability in complex matrices. Leveraging static electron transfer mechanisms, the N, Cl-CDs demonstrate selective fluorescence quenching toward quercetin with an ultralow detection limit of 60.42 nM. Validation through rigorous spiked recovery assays in apple peel and red wine has been proficiently performed with satisfactory accuracy, highlighting the significant prospect of the constructed N, Cl-CDs for quercetin identification in real samples. This study provides valuable insights into the analytical determination of flavonoid compounds in complex environmental matrices, highlighting the potential of N, Cl-CDs for environmental and food safety monitoring.

RevDate: 2025-06-12

Borics G, Lerf V, Falucskai J, et al (2025)

Projected area calculation for microalgae using three-dimensional models.

Water research, 284:123951 pii:S0043-1354(25)00859-0 [Epub ahead of print].

Light acquisition and sinking properties of microalgae fundamentally affect how species perform in aquatic environments. Both properties are the function of their projected area (Ā), a crucial morphological trait of microalgae. Despite their importance, species-specific Ā values have not been computed for microalgae. The reason for this is that although using an analytical approach Ā can be calculated for every convex shape, a vast majority of planktic algae are concave and currently not known how to calculate the projected area of concave shapes. Applying shape-realistic 3D models of microalgae and a novel numerical approach combined with computer simulation, we calculated the projected area for more than 800 microalgae. Validating this approach using convex shapes and the analytical Ā = surface area/4 formula we found, that the proposed method achieves less than 5 % estimation bias. We also studied how Ā values of species can be predicted by easy-to-measure morphological metrics (such as Gald/width ratio, compactness, relative surface area extension, relative elongation, surface area constant, volume constant). We have found that the metrics do not show a sufficiently close relationship with the projected area to allow us to estimate species-specific Ā values. We demonstrated that the morphological differences among species can result in up to 6-fold differences in Ā values for the same volume. Spindle-form, filamentous species and loosely packed coenobia are the most efficient adaptations to maximize Ā. This study provides an innovative methodology and a huge dataset containing Ā values of 844 planktic freshwater microalgae. Although the dataset contains species only for the Pannonian and Dinaric ecoregions, because of the cosmopolitan nature of planktic algae it can be used for other ecoregions. Species-specific projected area values multiplied by cell counts give a new metric that characterizes the shading property of the given phytoplankton assemblage and enables us to better understand the changes in light availability and study the vertical processes in the water.

RevDate: 2025-06-24
CmpDate: 2025-06-24

Yang S, Zhang X, Jin LN, et al (2025)

Unveiling Phase-Dependent Genotoxicity of Organic Pollutants in Gaseous and Aqueous Forms.

Environmental science & technology, 59(24):12048-12059.

Organic pollutants exist in various physical states within the natural environment, yet it remains unclear how their physical states influence their toxicity characteristics. This study investigated the phase-dependent genotoxicity and combined effects of two organic compounds, tert-butyl hydroperoxide (TBHP) and dimethyl sulfate (DES), in both gaseous and aqueous phases. Given the substantial differences in concentrations for the same compound in gaseous and aqueous environments, we constructed the complete multitoxic and dose-response curves for gene induction in both phases, covering environmentally relevant concentrations. Under the same stress conditions, the genotoxicity of gaseous TBHP was 158.21 ± 33.17% of that of its aqueous form, while gaseous DES exhibited 260.56 ± 12.63% of the genotoxicity of its aqueous form. Notably, while no formation of new reaction products were observed, aqueous-phase mixtures exhibited greater complexity and higher toxicity compared to their gaseous counterparts. These differences were attributed to variations in molecular energy states, free radical generation and diffusion, molecular interaction pathways, and chemical reactivity between the two phases. By elucidating the mechanisms underlying these disparities, this study highlights the critical role of physical states in evaluating the toxicity and risks associated with gaseous organic chemicals.

RevDate: 2025-06-24
CmpDate: 2025-06-24

Taylor BA, Slater GP, Stolle E, et al (2025)

Multi-Omic Analysis Reveals Population Differentiation and Signatures of Social Evolution in Tetragonula Stingless Bees.

Molecular ecology, 34(13):e17823.

Stingless bees in the genus Tetragonula are social insects with a fully sterile worker caste, and are therefore well-placed to provide insights into the genomic changes associated with 'superorganismal' life histories. Here we assemble the genome of Tetragonula carbonaria and characterise the population structure and divergence of both T. carbonaria and its cryptic congener T. hockingsi in eastern Australia, revealing three distinct populations for T. carbonaria and two partially differentiated subpopulations for T. hockingsi. We then combine our genomic results with RNA-seq data from different T. carbonaria castes (queens, males, workers) to test two hypotheses about genomic adaptations in social insects: the 'Relaxed Constraint' hypothesis, which predicts indirect, and therefore relaxed, selection on worker-biased genes; and the 'Adapted Worker' hypothesis, which predicts intensified positive selection on worker genes due to their evolutionarily novel functions. Although we do not find a direct signal of either weaker purifying selection or elevated positive selection in worker-biased genes based on deviations from neutral expectations of nucleotide change between the two species, other evidence does support a model of relaxed selection on worker-biased genes: such genes show higher nucleotide diversity and greater interspecies divergence than queen-biased genes. We also find that differentially caste-biased genes exhibit distinct patterns of length, GC content and evolutionary origin. These findings, which converge with patterns found in other social insects, support the hypothesis that social evolution produces distinct signatures in the genome. Overall, Tetragonula bees emerge as a valuable model for studying the genomic basis of social complexity in insects.

RevDate: 2025-06-24
CmpDate: 2025-06-24

Campbell AM, Kula AC, Jabaily RS, et al (2025)

Predicting potential recovery of the endangered bromeliad Tillandsia utriculata: An agent-based modeling approach.

PLoS computational biology, 21(6):e1013157.

Invasive pests and pathogens are a major driver of biodiversity loss. Some rare species may persist through rapid evolution to tolerate or escape new threats, but representing the underlying ecological and evolutionary processes at the appropriate scale is analytically and computationally challenging. Tillandsia utriculata has been classified as endangered in Florida where its population has decreased significantly due to predation by the invasive Mexican weevil Metamasius callizona. Adult female weevils deposit their eggs in leaves of epiphytic bromeliads, preferentially ovipositing in the largest rosettes. Once the eggs hatch, the larvae consume the core of the rosette, often leading to pre-reproductive death. During the past three decades of predation, the T. utriculata population has shifted to initiating the production of inflorescences (to commence its single attempt at sexual reproduction) at smaller rosette sizes. Importantly, the rosette size at induction is correlated with the number of seeds produced. We have constructed an agent-based model to simulate the dynamics of a Florida T. utriculata population over many generations where the minimum rosettes size required to initiate inflorescence production (minimum size of induction or MSI), is an inherited trait. We use the model to explore how predation may have shifted the population's genetic composition and the impact this has on population viability. Our results show that larger germination rates are required for population viability when weevils are present. Parameter uncertainty analysis revealed that in the presence of weevil predation, only a population with a very high germination rate and a short period of predation would sustain its population for 100 years with sizes similar to simulations without weevil predation. Furthermore, uncertainty analysis showed that the mean MSI of the population decreased over a 100-year period without weevil predation, and this trend was exacerbated by the presence of weevil predation.

RevDate: 2025-06-24
CmpDate: 2025-06-24

Carné A, Vieites DR, MP van den Burg (2025)

In Vouchers We (Hope to) Trust: Unveiling Hidden Errors in GenBank's Tetrapod Taxonomic Foundations.

Molecular ecology, 34(13):e17812.

Genetic repositories are invaluable resources foundational to various biological disciplines. While their data and metadata reliability are essential for robust research outcomes, numerous studies have highlighted data quality and consistency issues. Here, we detect and quantify errors at the most fundamental level by analysing the congruence of sequences derived from the same genetic marker and specimen voucher across tetrapods. Our analysis reveals that 32% of re-sequenced vouchers (with identical field or museum numbers) yield unequal sequences, ranging from a few mutations to significant divergences (0.06%-33.95%). These divergences may result from sample misidentification, labelling errors, fidelity disparities between sequencing methods, or contamination at various stages of the research process. Our findings demonstrate errors within GenBank at its most basal level and suggest that, although undetectable, a similar error rate likely exists in non-re-sequenced data. These previously overlooked errors are concerning because they arise from replicated experiments, which are uncommon, and raise serious questions about the reliability of non-re-sequenced specimens. Such errors can compromise the accuracy of biodiversity assessments (e.g., taxonomic assessment, eDNA and barcoding), phylogenetic analyses and conservation planning by artificially inflating the intraspecific divergence or misidentifying (to-be-described) species. Additionally, the accuracy of large-scale biological studies that rely on such data can be compromised. Our concerning results call for protocols ensuring sample traceability to the specimens or tissues during the whole process of data generation, analysis and deposition in a database. We propose a third-party annotation system for individual GenBank records that would allow flagging common errors and alert both the original submitter and all users to potential problems without modifying the original records.

RevDate: 2025-06-24
CmpDate: 2025-06-24

Sharma G, Deuis JR, Jia X, et al (2025)

Refining the NaV1.7 pharmacophore of a class of venom-derived peptide inhibitors via a combination of in silico screening and rational engineering.

FEBS letters, 599(12):1717-1732.

Ion channels are among the main targets of venom peptides. Extensive functional screening has identified a number of these peptides as modulators of the voltage-gated sodium channel subtype NaV1.7, a potential target for the treatment of chronic pain. In this study, we used a bioinformatic approach that can automatically identify NaV1.7 gating modifier toxins from sequence information alone. The method further enables the incorporation of evolutionarily accessible sequence space in structure-activity relationship studies. The in silico method identified a putative NaV1.7 inhibitor, μ-theraphotoxin Cg4a, which we produced recombinantly and confirmed as a NaV1.7 inhibitor. Using structural and mutagenesis studies, we propose an improved definition of the pharmacophore of this class of NaV1.7 inhibitors, aiding future in silico screening and classification of NaV1.7 inhibitors.

RevDate: 2025-06-14
CmpDate: 2025-06-12

Negeri BG, Xiuguang B, MB Moisa (2025)

Assessment of potential land suitability for rainfed wheat production using GIS and multi criteria decision analysis in the Southwestern parts of Ethiopia.

PloS one, 20(6):e0324540.

Wheat production in Ethiopia is vital for improving food security, boosting the national economy, and achieving self-sufficiency in food consumption. The present study aims to assess the potential land suitability for rainfed wheat (Triticum aestivum L.) production by using Geographic Information System and multi criteria decision analysis in southwestern parts of Ethiopia. Biophysical data, including land use and land cover (LULC), soil drainage, soil texture, soil depth, proximity to markets and roads, land surface temperature, slope, rainfall, and elevation, were used. In addition, different software tools, such as ArcGIS 10.3, ERDAS Imagine 2015, IDRISI Selva 17, and ArcSWAT were applied. The results revealed that approximately 177.1 km[2] (1.3%) of the study area was classified as highly suitable, 5375.2 km[2] (38.2%) as moderately suitable, 7,246.0 km[2] (51.5%) as marginally suitable, and 1235.1 km[2] (8.8%) as currently not suitable for rainfed wheat cultivation. Furthermore, out of the 23 districts analyzed, Sayo Nole and Bedelle Zuriya were identified as highly suitable for wheat production, with an area of 32.7km2 and 23.3km2 respectively. Therefore, the study recommends that future study research investigate additional other ecological parameters, such as soil PH, lime, gypsum, salinity, alkalinity and socio-economic data, which were not included in the present study.

RevDate: 2025-06-14
CmpDate: 2025-06-12

Augustijn HE, Reitz ZL, Zhang L, et al (2025)

Genome mining based on transcriptional regulatory networks uncovers a novel locus involved in desferrioxamine biosynthesis.

PLoS biology, 23(6):e3003183.

Bacteria produce a plethora of natural products that are in clinical, agricultural and biotechnological use. Genome mining has uncovered millions of biosynthetic gene clusters (BGCs) that encode their biosynthesis, the vast majority of them lacking a clear product or function. Thus, a major challenge is to predict the bioactivities of the molecules these BGCs specify, and how to elicit their expression. Here, we present an innovative strategy whereby we harness the power of regulatory networks combined with global gene expression patterns to predict BGC functions. Bioinformatic analysis of all genes predicted to be controlled by the iron master regulator DmdR1 combined with co-expression data, led to identification of the novel operon desJGH that plays a key role in the biosynthesis of the iron overload drug desferrioxamine (DFO) B in Streptomyces coelicolor. Deletion of either desG or desH strongly reduces the biosynthesis of DFO B, while that of DFO E is enhanced. DesJGH most likely act by changing the balance between the DFO precursors. Our work shows the power of harnessing regulation-based genome mining to functionally prioritize BGCs, accelerating the discovery of novel bioactive molecules.

RevDate: 2025-06-19
CmpDate: 2025-06-19

Poulin R (2025)

To bin or not to bin: why parasite abundance data should not be lumped into categories for statistical analysis.

Parasitology, 152(3):338-345.

The impact of macroparasites on their hosts is proportional to the number of parasites per host, or parasite abundance. Abundance values are count data, i.e. integers ranging from 0 to some maximum number, depending on the host-parasite system. When using parasite abundance as a predictor in statistical analysis, a common approach is to bin values, i.e. group hosts into infection categories based on abundance, and test for differences in some response variable (e.g. a host trait) among these categories. There are well-documented pitfalls associated with this approach. Here, I use a literature review to show that binning abundance values for analysis has been used in one-third of studies published in parasitological journals over the past 15 years, and half of the studies in ecological and behavioural journals, often without any justification. Binning abundance data into arbitrary categories has been much more common among studies using experimental infections than among those using naturally infected hosts. I then use simulated data to demonstrate that true and significant relationships between parasite abundance and host traits can be missed when abundance values are binned for analysis, and vice versa that when there is no underlying relationship between abundance and host traits, analysis of binned data can create a spurious one. This holds regardless of the prevalence of infection or the level of parasite aggregation in a host sample. These findings argue strongly for the practice of binning abundance data as a predictor variable to be abandoned in favour of more appropriate analytical approaches.

RevDate: 2025-06-12

Roces V, Cañal MJ, Mateo JL, et al (2025)

Pra-GE-ATLAS: Empowering Pinus radiata stress and breeding research through a multi-omics database.

Journal of integrative plant biology [Epub ahead of print].

In recent decades, research on model organisms has significantly increased our understanding of core biological processes in plant science. However, this focus has created a substantial knowledge bottleneck due to the limited phylogenetic and ecological spectrum covered. Gymnosperms, especially conifers, represent a molecular and ecological diversity hotspot among seed plants. Despite their importance, research on these species is notably underrepresented, primarily due to a slower pace of investigation resulting from a lack of community-based resources and databases. To fill this gap, we developed the P(inus)ra(diata)-G(ene)E(xpression) (Pra-GE)-ATLAS, which consists of several tools and two main modules: transcriptomics and proteomics, presented in this work for the forestry commercial and stress-sensitive species Pinus radiata. We have summarized and centralized all the available information to provide a comprehensive view of the gene expression landscape. To illustrate how applications of the database lead to new biological insights, we have integrated multiple regulatory layers across tissues and stressors. While stress favors the retention of small introns, harmonized alternative splicing analyses reveal that genes with conifers' iconic large introns tend to be under constitutive regulation. Furthermore, the degree of convergence between stressors differed between regulatory layers, with proteomic responses remaining highly distinctive even through intergenerational memory tolerance. Overall, the Pra-GE-ATLAS aims to narrow the distance between angiosperms and gymnosperms resources, deepening our understanding of how characteristic pine features have evolved. Pra-GE-ATLAS DB is available at: http://pra-ge-atlas.valmei.es.

RevDate: 2025-06-14
CmpDate: 2025-06-11

Wu X, Liu J, Y Hou (2025)

Data and methods for assessing urban green infrastructure using GIS: A systematic review.

PloS one, 20(6):e0324906.

Comprehensive and visual assessments utilizing Geographic Information Systems (GIS) offer an empirical foundation for the planning, construction, and optimization of Urban Green Infrastructure (UGI), effectively promoting its sustainable development. A comprehensive review of this field clarifies the research methods, application scope, trends, and challenges associated with using GIS to advance UGI development. This study synthesizes research findings from the Science Citation Index (SCI) and Social Science Citation Index (SSCI) within the Web of Science (WOS) database, as well as from the Scopus database, for the period from January 1, 2020, to June 30, 2024. The initial dataset included 640 articles from WOS and 952 articles from Scopus. After removing 1,572 duplicates and irrelevant studies, the final selection consisted of 20 articles. The integration of both WOS and Scopus databases ensures a comprehensive capture of current trends and limitations in GIS-based UGI assessments. This study centers on the scope, data sources, theoretical models, analyses, and objectives of GIS-based UGI assessments. The research indicates that over the past five years, GIS-based UGI assessments have primarily focused on areas such as accessibility, ecosystem service potential, resilience, and environmental justice, in addition to non-ecological aspects such as social benefits and aesthetics. While the integration of diverse data and analytical indicators into GIS has enhanced assessment comprehensiveness, and AI technologies have deepened data analysis, field research with urban residents remains crucial, underscoring the importance of inclusiveness in the study. This study also reveals a significant increase in interdisciplinarity in GIS-based assessments of UGI. The integration of assessment methods from ecology, computer science, urban planning, sociology, aesthetics, and other disciplines demonstrates that research in this field has fully considered ecological, social, economic, and humanistic factors, thereby more comprehensively reflecting the integrated needs of sustainable urban development.

RevDate: 2025-06-14
CmpDate: 2025-06-11

Morrison ES, Pandolfi GP, Aguillon SM, et al (2025)

AvianLexiconAtlas: A database of descriptive categories of English-language bird names around the world.

PloS one, 20(6):e0325890.

Common names of species are important for communicating with the general public. In principle, these names should provide an accessible way to engage with and identify species. The common names of species have historically been labile without standard guidelines, even within a language. Currently, there is no systematic assessment of how often common names communicate identifiable and biologically relevant characteristics about species. This is a salient issue in ornithology, where common names are used more often than scientific names for species of birds in written and spoken English, even by professional researchers. To gain a better understanding of the types of terminology used in the English-language common names of bird species, a group of 85 professional ornithologists and non-professional contributors classified unique descriptors in the common names of all recognized species of birds. In the AvianLexiconAtlas database produced by this work, each species' common name is assigned to one of ten categories associated with aspects of avian biology, ecology, or human culture. Across 10,906 species of birds, 89% have names describing the biology of the species, while the remaining 11% of species have names derived from human cultural references, human names, or local non-English languages. Species with common names based on features of avian biology are more likely to be related to each other or be from the same geographic region. The crowdsourced data collection also revealed that many common names contain specialized or historic terminology unknown to many of the data collectors, and we include these terms in a glossary and gazetteer alongside the dataset. The AvianLexiconAtlas can be used as a quantitative resource to assess the state of terminology in English-language common names of birds. Future research using the database can shed light on historical approaches to nomenclature and how people engage with species through their names.

RevDate: 2025-06-17
CmpDate: 2025-06-17

Wang X, Zhao C, Huang G, et al (2025)

Quantifying leachate discharge and assessing environmental risks of gully-type coal-based solid waste dumps in small watersheds: A refined hydrological modeling approach for mitigation strategies.

Water research, 282:123655.

Rainfall-induced leaching from extensive coal-based solid waste storage results in a long-term risk to watershed's water quality and safety. The leachate carries heavy metals and other contaminants, which migrate and accumulate through the watershed, leading to a persistent deterioration of downstream water environment. However, the lack of systematic research on the release, accumulation, and spatial-scale migration dynamics of leachate limits effective management of diffused leachate pollutions. This study presents a novel cross-scale coupling framework which integrates multi-source remote sensing data with Soil and Water Assessment Tool (SWAT) model, employing a strategy that transfers parameters from large basins to accurately quantify the hydrological processes in coal waste sub-basins. Additionally, a comprehensive analysis is performed on the hydrological characteristics, leachate generation, and watershed migration dynamics in gangue dump sub-watersheds, providing a new methodological framework for managing mining-related leachate pollution. The large basin model demonstrated strong performance (R[2] = 0.79, NSE = 0.66 for calibration; R[2] = 0.74, NSE = 0.59 for verification), while the sub-basin model exhibited excellent accuracy (R[2] = 0.94, NSE = 0.92 for calibration; R[2] = 0.81, NSE = 0.77 for verification). High-resolution drone data estimated the annual leachate production to be 3366.87 m[3]. Simulations revealed that leachate migration peaks in the summer months (July to September), significantly increasing downstream pollution risks. Risk assessments indicate that vegetation in land restoration areas reduces leachate production and migration via evapotranspiration and other processes. This study provides an adaptable methodological framework for managing mining-related leachate pollution and highlights the critical importance of optimal reclamation strategies for mitigating pollution and restoring degraded landscapes.

RevDate: 2025-06-10

Yaling H, Shasha C, Mengyao L, et al (2025)

Phosphate-solubilizing function of Pediococcus pentosaceus PSM16 and its underlying mechanism.

Microbiology spectrum [Epub ahead of print].

Phosphorus is a crucial nutrient for plant growth, but only a limited quantity is typically accessible in the soil for plants to absorb directly. Phosphate-solubilizing bacteria (PSB) can convert inorganic phosphorus compounds into forms that are more readily usable for plant nutrition. Our previous research has verified the function of Pediococcus pentosaceus PSM16 in degrading phytic acid. On this basis, we further explored the phosphorus-solubilizing capacity of PSM16 and evaluated its potential for practical application in this study. The results indicated that PSM16 significantly enhanced phosphorus utilization, not only enriching the environment with bioavailable phosphorus but also lowering the environmental pH and conductivity. These changes are instrumental in enhancing soil fertility, providing favorable conditions for plant growth, and stimulating seed germination. Through whole-genome sequencing of PSM16, we have identified key genes associated with the production of acid phosphatase. Specifically, the genes of GM000834, GM000917, GM000925, and GM000974 are implicated in PSM16's phosphorus solubilization function, likely through the production of phosphatase enzymes. Moreover, we have discovered that the phosphatases T.fus-QOS58989.1, A.cae-WP_156200763, M.the-SNW17984, N.gly-GGP12115, T.chr-SDQ48339.1, and T.chr-SDQ90039.1 are homologous to the aforementioned proteins and are present in compost, as confirmed by our informatics analysis. This presence in compost suggests their potential for real-world agricultural applications. This research presents promising candidate strains for the development of phosphorus-degrading bacterial agents, which could increase the efficiency of phosphorus fertilizers and contribute to sustainable agricultural practices. This strategy is not only effective but also environmentally benign and cost-effective, offering a valuable contribution to the field of agricultural biotechnology.IMPORTANCEThis study sheds light on the transformative power of the PSM16 strain, a paragon of phosphorus solubilization that adeptly converts inert phosphorus into a form that is readily absorbed by plants. In this way, it not only elevates the levels of available phosphorus in the environment but also enriches the soil fertility, supporting the healthy growth of plants. The strategic application of PSM16 in tandem with phosphorus fertilizers promises to enhance the utilization rates of these fertilizers, reinforcing sustainable agricultural initiatives and alleviating the environmental pressures caused by excessive application. In addition, the study has uncovered a trove of strains that hold promise for the development of safe dephosphorylating bacterial agents. These agents are poised to deliver an economical, efficient, and eco-friendly alternative, encapsulating a commitment to agricultural advancement that is both responsible and resourceful.

RevDate: 2025-06-13
CmpDate: 2025-06-09

van Ittersum MK, Alimagham S, Silva JV, et al (2025)

Prospects for cereal self-sufficiency in sub-Saharan Africa.

Proceedings of the National Academy of Sciences of the United States of America, 122(24):e2423669122.

Sub-Saharan Africa (SSA) has the world's largest projected increase in demand for food. Increased dependence on imports makes SSA vulnerable to geopolitical and economic risks, while further expansion of agricultural land is environmentally harmful. Cereals, in particular, maize, millet, rice, sorghum, and wheat, take nearly 50% of the cropland and 43% of the calories and proteins consumed in the region. Demand is projected to double until 2050. Here, we assess recent developments in cereal self-sufficiency and provide outlooks until 2050 under different intensification, area expansion, and climate change scenarios. We use detailed data for ten countries. Cereal self-sufficiency increased between 2010 and 2020 from 84 to 92% despite the 29% population increase. The production increase was achieved by increased yields per hectare (44%), area expansion (34%), and a shift from millet to the higher yielding maize (22%). Outlooks for 2050 are less pessimistic than earlier assessments because of the larger 2020 baseline area, higher shares of maize and somewhat less steep projected population increase. Yet, to halt further area expansion, a drastic trend change in annual yield increase from the present 20 to 58 kg ha[-1] y[-1] is needed to achieve cereal self-sufficiency. While such yield increases have been achieved elsewhere and are feasible given the yield potentials in SSA, they require structural changes and substantial agronomic, socioeconomic, and political investments. We estimate that amounts of added nitrogen need to at least triple to achieve such yield improvements, but it is essential that this comes with improved context-specific agronomy.

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

Flynn KJ, AY Morozov (2025)

Resource acquisition in diel cycles and the cost of growing quickly.

PLoS computational biology, 21(6):e1013132 pii:PCOMPBIOL-D-24-02098.

Many organisms, notably phototrophs, routinely acquire resources over only a fraction of the day. They have to balance their main period of initial biosynthesis against cell cycle events. Because of their short generation times, this challenge is especially acute for the planktonic microalgae that perform 50% of global C-fixation. Empirical evidence indicates that microalgal day-average growth is a function of the ability to acquire resources rapidly when available, retaining initial products of assimilation to support growth. A fundamental question arises over the optimal physiological configuration to support such activity. Here, we applied computer simulations implementing a development of the quota concept, in which the internal limiting resource is itself C, ratioed against total organism C-biomass. The model comprises metabolite and core pools of carbon C (MC and CC, respectively), with growth modulated by MC/(MC + CC); MC supports growth of CC in the absence of concurrent resource acquisition. Dynamic feedback interactions from the relative size of MC controls resource acquisition. The model reproduces the general pattern of growth at different light:day fraction (LD), and of afternoon-depression of C-fixation. We explored the efficiency of the physiological cell configuration to locate optimal configurations at different combinations of maximum growth rates (Umax) and LD values across plausible parameter values for microalgae. While the optimum maximum resource acquisition rate deployed during the L phase scales with Umax/LD, the maximum size of the metabolite pool scales to LD/DV, where DV is division time (i.e. Umax/Ln(2)). Accordingly, we conclude that faster growing organisms carry a penalty limiting their geographic spread to latitudes and seasons where LD is high. Larger, vacuolated organisms (such as diatoms), having a bigger metabolite compartment, may be at an advantage in such situations.

RevDate: 2025-06-06

Amador LG, Ramirez-Parada TH, Park IW, et al (2025)

Bridging data silos to holistically model plant macrophenology.

The New phytologist [Epub ahead of print].

Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue. We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses.

RevDate: 2025-06-13
CmpDate: 2025-06-13

Hussain M, Ullah K, Tayyab M, et al (2025)

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Journal of environmental management, 388:126009.

Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited research has been conducted to study these aspects together. This study uses a data-driven approach to assess multi-hazard susceptibility and community perceptions, aiming to deepen climate change mitigation strategies. We employed a two-stage framework in Eastern Hindukush, Pakistan, which is based on machine learning, remote sensing, geographical information systems, and index-based methods. In the first stage, flood and landslide inventories were generated, and predictive factors were analyzed using logistic regression, resulting in an integrated multi-hazard susceptibility map. In the second stage, a survey of 410 household heads assessed community risk perception, communication, and preparedness, using a structured questionnaire with 28 Likert-scale indicators, and a composite index was calculated. The findings indicate that 25.81 % and 35.43 % of the study area are susceptible to flooding and landslides, respectively, with 15.07 % vulnerable to both hazards concurrently. On the other hand, the community is generally aware of flood and landslide risks; however, there are significant gaps in coping abilities and preparedness, including insufficient insurance coverage and training. Moreover, socioeconomic challenges, such as limited access to information and low trust in local authorities, further complicate disaster preparedness efforts. This study provides a holistic framework for identifying multi-hazard hotspots and assessing community perceptions, facilitating targeted interventions to enhance disaster preparedness and resilience in the region.

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

Pan X, Shan Z, Tian X, et al (2025)

Evaluating conservation gaps of China's national key protected wild plants: insights from county-level distribution data.

BMC biology, 23(1):156.

BACKGROUND: The National Key Protected Wild Plants (NKPWPs) list serves as China's primary legal framework for plant diversity protection, with the species categorized into Level I (critically endangered, strictly protected) and Level II (lower risk but still requiring protection). However, the geographical distribution of these species and gaps in their conservation remain elusive due to the limited availability of data on species distribution. Thus, to address these gaps and support precise conservation, we developed a county-level distribution database for the NKPWP species using information primarily sourced from literature. Using this database, we elucidated the geographical distribution patterns of NKPWPs and identified the gaps in both in situ and ex situ conservation.

RESULTS: The NKPWPs analyzed in the study included 1,128 plant species. We compiled a county-level distribution database for these species with 30,397 records. Detailed analysis of this data revealed that these species were concentrated in the mountainous regions of southern China, including the Eastern Himalaya-Hengduan Mountains, south Yunnan, the Yunnan-Guizhou-Guangxi border, and the Wuling Mountains. Among the 1,118 embryophyte species of the checklist, 1,060 (94.81%) were found conserved in situ, 681 (60.91%) were found conserved ex situ, and 660 (59.03%) through both approaches. Besides, species with a higher threat level and limited distribution range exhibited lower conservation coverage in both ex situ and in situ approaches; 37 species received no conservation (3.31%).

CONCLUSIONS: The county-level distribution database developed in this study comprehensively depicts the geographical distribution patterns of NKPWP in China, offering valuable data for planning species conservation and providing a foundational framework for addressing the existing gaps in their conservation across China. This database will ultimately support targeted conservation and resource allocation to protect plant diversity effectively. We also suggest adopting an integrated evaluation approach for conservation strategies in other areas, globally, or for other biological groups.

RevDate: 2025-06-09
CmpDate: 2025-06-04

Duan Z, Wang G, Hu J, et al (2025)

Spatiotemporal dynamics of northern Caspian shorelines (1985-2023) and implications for coastal management: Lessons from the Aral Sea.

PloS one, 20(6):e0325546.

Dynamic changes to the northern Caspian Sea shoreline have significant ecological implications, including impacts to biodiversity and the surrounding environment. This study employs Landsat datasets, historical records, and geographic information systems (GIS) to quantitatively analyze spatiotemporal variations along the northern Caspian Sea coastline from 1985 to 2023. The findings demonstrate pronounced cyclic variations in the Caspian Sea's water level. Compared to 1930, the water level decreased by 2.6 m by 2023, with 1935 marking the onset of a significant downward trend. From 1995 to 2023, a pronounced decline in the water level at a rate of 6.1 cm/year was observed. Multiscale temporal oscillations in water levels revealed periodic rises and falls with cycles ranging from 6-8 years to 10-16 years. Due to the broad and shallow morphology of the northern Caspian Sea, fluctuations in water level have resulted in significant displacements of the northern coastline. Between 1985 and 2023, the shoreline length decreased by 262 km, which is equivalent to a 17% reduction. The intensity of the coastline length index reached a critical point during from 2010 to 2015, after which it declined sharply by 3.67. By 2023, the coastline had shifted seaward by 1.33 × 10[4] km2 relative to that in 1985. This continuous retreat of the shoreline poses a severe threat to the ecological stability of the northern Caspian Sea. If the trend persists, then the disappearance of the eastern basin of the South Aral Sea may be replicated in the northern Caspian Sea by 2100. These findings provide critical insights for formulating effective coastal management strategies and conservation initiatives.

RevDate: 2025-06-06

Petrou E, Davies H, Aoun M, et al (2025)

First opinion practice electronic health records are a useful source of descriptions of medication errors.

Frontiers in veterinary science, 12:1560652.

BACKGROUND: Medication error (MedE) is a leading global cause of harm in human healthcare with significance both in patient morbidity and mortality, and consequent legal and financial issues. Despite this, MedEs are a poorly explored area in veterinary medicine. Research has so far focussed on survey work and errors spontaneously reported to third parties, such as professional indemnity providers.

AIM: Determine if MedEs can be successfully identified in first opinion electronic health records (EHRs).

ANIMALS: EHRs pertaining to animals treated in UK first opinion practice.

MATERIALS AND METHODS: Regular expressions (REGEX) were designed (with assistance from a domain expert) to identify explicit reference to MedEs in the SAVSNET EHR dataset. Identified MedEs were then classified by the linear sequence of medication therapy, the degree of harm caused, the role of the person who made the error, and the medication type involved.

RESULTS: In total, 6,665 EHRs were identified by the REGEX, of which a random 2,847 were manually reviewed, with 1,023 (35.9%) matching the MedEs case definition. Of these MedEs, 29.5% (n = 302) caused mild harm to the patient, 2.8% (n = 27) moderate harm and 0.2% (n = 2) severe harm. MedEs were most frequent during the "drug administered" phase (51.4%) and within this phase, "dosing errors" were most common (68.1%). The most common medication types, associated with "drug administered" phase MedEs were vaccinations (27.1%) and non-steroidal anti-inflammatory drugs (19.0%).

CONCLUSION: EHRs are a useful source of data on MedEs. MedEs are a common cause of patient harm in veterinary practice. The data provided here highlights drug classes at higher risk of problems for which mitigating action and/or education interventions are indicated.

RevDate: 2025-06-12

Brook JBH, Salo T, Luo AC, et al (2025)

An open, fully-processed data resource for studying mood and sleep variability in the developing brain.

bioRxiv : the preprint server for biology.

Brain development during adolescence and early adulthood coincides with shifts in emotion regulation and sleep. Despite this, few existing datasets simultaneously characterize affective dynamics, sleep variation, and multimodal measures of brain development. Here, we describe the study protocol and initial release (n = 10) of an open data resource of neuroimaging paired with densely sampled behavioral measures in adolescents and young adults. All participants complete multi-echo functional MRI, compressed-sensing diffusion MRI, and advanced arterial spin-labeled MRI. Behavioral measures include ecological momentary assessment, actigraphy, extensive cognitive assessments, and detailed clinical phenotyping focused on emotion regulation. Raw and processed data are openly available without a data use agreement and will be regularly updated as accrual continues. Together, this resource will accelerate research on the links between mood, sleep, and brain development.

RevDate: 2025-06-02

Fetters AM, Cantalupo PG, Robles MTS, et al (2025)

Sharing Pollinators and Viruses: Virus Diversity of Pollen in a Co-Flowering Community.

Integrative and comparative biology pii:8155231 [Epub ahead of print].

Co-flowering plant species frequently share pollinators, flower-inhabiting bacteria, and fungi, but whether pollen-associated viruses are shared is unknown. Given that pollen-associated viruses are sexually transmitted diseases, their diversity is expected to increase with pollinator sharing. We conducted a metagenomic study to identify pollen-associated viruses from 18 co-flowering plant species to determine whether 1) life history, floral traits, or pollination generalism were associated with viral richness, and 2) plants shared pollen-associated viruses. We demonstrated that pollination generalism influences pollen-associated virus richness and the extent of pollen virus sharing between plant species. We also revealed that perenniality, multiple flowers, and bilateral floral symmetry were associated with high pollen viral richness locally, confirming and extending patterns observed previously at a continental scale. Our results highlight the importance of plant-pollinator interactions as drivers of plant-viral interaction diversity.

RevDate: 2025-06-03
CmpDate: 2025-06-01

Leung WKC, Yau CYC, SC Lam (2025)

Facilitators, barriers, and recommendations for mobile health applications among Chinese older populations: a scoping review.

BMC geriatrics, 25(1):396.

BACKGROUND: Mobile health (mHealth) applications have become indispensable in people's daily lives and are now incorporated into a multitude of healthcare services. However, due to inappropriate designs and ineffective promotional strategies, the rates of uptake and continued use of mHealth applications in older adults are usually low. Given that recent evidence has reported distinct mHealth adoption patterns between Chinese and non-Chinese populations, the aim of this scoping review was to map relevant evidence on the end-user perceptions and age-appropriate recommendations for interface design, persuasive features, and promotional strategies among Chinese older adults.

METHODS: All primary studies conducted in Chinese older people aged 60 + years, including quantitative, qualitative, and mixed methods research, examining end-user perceptions (e.g., motivators, barriers, and design) of mHealth applications were considered eligible for inclusion. Four electronic databases (PubMed, CINAHL, PsycINFO, and Medline) were searched from their inceptions through 31 May 2024. A narrative approach was adopted for data analyses relevant to the study aim.

RESULTS: A total of 23 studies (n = 8,203) were included. End-user perceptions (facilitators and barriers) of older people were narratively synthesized according to the socio-ecological model (individual/product, interpersonal, community, and societal). In Chinese deaf and hard-of-hearing older adults, the lack of proficiency in mastering operations of smartphone, Internet, and mHealth applications greatly jeopardized their communication with family or friends, accessibility to online medical consultations, and access to public places amidst COVID-19 pandemic. Recommended interface designs were categorized into various aspects of functional impairments (vision, manual dexterity, and cognition) of elderly users. Seven promotional strategies were also highlighted, whereas more than half of the studies recommended education measures (e.g., personalized family/peer- or health professional-led training program) and technical support (e.g., face-to-face instructions, detailed manual instructions, and timely consultation services). Other recommendations included increased publicity, co-creation, and supportive government policies.

CONCLUSION: This review synthesizes the existing relevant evidence and hence provides age-friendly recommendations for interface designs, persuasive features, and promotional strategies in Chinese older populations. Overall, this study empirically offers actionable guidelines for mHealth developers to meet the multifaceted needs of older people.

RevDate: 2025-06-01

Broad GR, Lees DC, Boyes D, et al (2025)

The genome sequence of the Straw-barred Pearl moth, Pyrausta despicata Scopoli, 1763.

Wellcome open research, 10:151.

We present a genome assembly from a male specimen of Pyrausta despicata (Straw-barred Pearl; Arthropoda; Insecta; Lepidoptera; Crambidae). The genome sequence has a total length of 481.83 megabases. Most of the assembly (99.61%) is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled, with a length of 15.29 kilobases.

RevDate: 2025-06-02
CmpDate: 2025-05-30

Maździarz M, Zając S, Paukszto Ł, et al (2025)

RSCUcaller: an R package for analyzing differences in relative synonymous codon usage (RSCU).

BMC bioinformatics, 26(1):141.

BACKGROUND: Synonymous codon usage bias, a significant factor in gene expression and genome evolution, was extensively studied in genomics and molecular biology. Although the genetic code is universal, significant variations in synonymous codon usage have been observed among and within organisms. This bias was linked to various factors, including gene expression levels, tRNA abundance, protein structure, and environmental adaptation. Relative Synonymous Codon Usage (RSCU), a normalized measure, was used to quantify this bias. By analyzing RSCU values, researchers uncovered patterns and trends related to the underlying mechanisms driving codon usage bias.

RESULTS: We present an R package named RSCUcaller designed for the analysis of coding nucleotide sequences at the level of relative synonymous codon usage (RSCU). The package enables both visualization of data and the performance of advanced statistical analyses. RSCUcaller accepts as input a multi-fasta file containing coding sequences (CDS) and an accompanying description table. Alternatively, the user may provide separate fasta files for each sequence along with the corresponding table. The program merges the provided sequences and calculates RSCU values for each. Implemented visualization features include creating heatmaps and dendrograms based on these heatmaps. Furthermore, the package allows for the presentation of data in the form of histograms. The calculated RSCU values can also be used to create matrices that can be subjected to further analysis by the user. RSCUcaller offers the functionality of correlation analysis between any two organisms. Additionally, to compare the frequency of amino acid occurrence between different groups of sequences, statistical tests have been implemented.

CONCLUSIONS: RSCUcaller enabled comparative RSCU analysis between coding sequences of different organisms or individuals of the same species. It facilitated visualization and statistical analysis among codons and user-defined groups. The RSCUcaller package is available at https://github.com/Mordziarz/RSCUcaller under the GPL-3 license.

RevDate: 2025-06-02
CmpDate: 2025-05-29

Sun Y, Meng W, Wang F, et al (2025)

Spatio-temporal evolution and coupling relationship between biodiversity and urbanization in the areas along the Yellow River of Shandong province.

Scientific reports, 15(1):18876.

Mastering the coupling relationship and driving mechanism between urbanization and biodiversity is of great significance to ecological protection and regional sustainable development. The study took areas along the Yellow River of Shandong province (AYRSP) as the study area, which have the most rich and unique biodiversity resources in the whole basin. First, this study constructed a new indicator system of biodiversity based on remote-sensing data from species, ecosystem, and landscape to monitor and evaluate the spatial heterogeneity. The result was quantified by the proportion of key biodiversity areas, based on Sustainable Development Goal 15.1.2 from The United Nations. Then, the urbanization system was evaluated based on panel data. At last, the coordination relationship, lead-lag type between biodiversity and urbanization, and key influencing factors of coupling system at the county scale in 2015-2021 were identified by combining multiple models. The results demonstrated that the biodiversity level was gradually declining, with a distribution pattern of "low in the western, and high in mid-southern and eastern regions." The AYRSP still faced certain challenges in the sustainable development of biodiversity. The coupling coordination degree between biodiversity and urbanization showed an increasing trend with continuous improvement in the urbanization level. Only two counties were types of biodiversity-urbanization synchronous development. The results of grey relation degree model indicated that most of indicators were above 0.6 and the urbanization had a significant impact on the coupling system. This study established the evaluation system for biodiversity and urbanization at the small scale, which could provide theoretical reference for the sustainable development of county-level administrative region.

RevDate: 2025-06-02
CmpDate: 2025-05-29

Dang T, Fuji Y, Kumaishi K, et al (2025)

I-SVVS: integrative stochastic variational variable selection to explore joint patterns of multi-omics microbiome data.

Briefings in bioinformatics, 26(3):.

High-dimensional multi-omics microbiome data play an important role in elucidating microbial community interactions with their hosts and environment in critical diseases and ecological changes. Although Bayesian clustering methods have recently been used for the integrated analysis of multi-omics data, no method designed to analyze multi-omics microbiome data has been proposed. In this study, we propose a novel framework called integrative stochastic variational variable selection (I-SVVS), which is an extension of stochastic variational variable selection for high-dimensional microbiome data. The I-SVVS approach addresses a specific Bayesian mixture model for each type of omics data, such as an infinite Dirichlet multinomial mixture model for microbiome data and an infinite Gaussian mixture model for metabolomic data. This approach is expected to reduce the computational time of the clustering process and improve the accuracy of the clustering results. Additionally, I-SVVS identifies a critical set of representative variables in multi-omics microbiome data. Three datasets from soybean, mice, and humans (each set integrated microbiome and metabolome) were used to demonstrate the potential of I-SVVS. The results indicate that I-SVVS achieved improved accuracy and faster computation compared to existing methods across all test datasets. It effectively identified key microbiome species and metabolites characterizing each cluster. For instance, the computational analysis of the soybean dataset, including 377 samples with 16 943 microbiome species and 265 metabolome features, was completed in 2.18 hours using I-SVVS, compared to 2.35 days with Clusternomics and 1.12 days with iClusterPlus. The software for this analysis, written in Python, is freely available at https://github.com/tungtokyo1108/I-SVVS.

RevDate: 2025-06-01

Guevara Rodríguez DM, Pichihua Grandez JD, Dianderas FV, et al (2025)

Incidence of cerebrovascular disease in Peru from 2015 to 2023.

PLOS global public health, 5(5):e0004559.

Cerebrovascular disease (stroke) is one of the leading causes of mortality and disability worldwide, particularly in low- and middle-income countries. This study aims to estimate the incidence of stroke in Peru between 2015 and 2023 using national hospital discharge data provided by the National Health Superintendency. We conducted a mixed ecological study using records of stroke cases reported across various healthcare systems, including the Ministry of Health, Social Security, and private entities. Hospitalizations were categorized according to ICD-10 codes (I60-I64) and stratified by age, sex, and region. Incidence rates were calculated using population projections from the National Institute of Statistics and Informatics. A total of 89,776 hospital discharges for stroke were analyzed, yielding an incidence rate of 3.11 per 10,000 persons over the study period, with a predominance in men and individuals over 60 years of age. Cerebral infarction was the most common diagnosis, particularly among those over 40 years old. Incidence varied significantly across regions, with Lima and Callao consistently exceeding the national average. The results highlight disparities in healthcare access and the need for targeted public health interventions. Our findings provide a 9-year overview of stroke in Peru, offering evidence to estimate hospital bed demand and prioritize preventive and management strategies-particularly in regions with higher vulnerability.

RevDate: 2025-06-10
CmpDate: 2025-06-10

Lei L, Sha W, Liu Q, et al (2025)

Hepatotoxic effects of exposure to different concentrations of Dibutyl phthalate (DBP) in Schizothorax prenanti: Insights from a multi-omics analysis.

Aquatic toxicology (Amsterdam, Netherlands), 285:107390.

Dibutyl phthalate (DBP) is one of the most widely used phthalate esters (PAEs) that raise increasing ecotoxicological concerns due to their harmful effects on living organisms and ecosystems. Recently, while PAEs pollution in the Yangtze River has attracted significant attention, little research has been conducted on the impact of PAEs stress on S. prenanti, an endemic and valuable species in the Yangtze River. In this study, one control group (C-L) and three experimental groups: T1-L (3 µg/L), T2-L (30 µg/L), and T3-L (300 µg/L) were established with reference to the DBP concentration in the environment. For the first time, we investigated the effects of DBP stress on the liver of S. prenanti using histomorphological, physiological, and biochemical indexes, as well as a joint multi-omics analysis. The results revealed that compared to the C-L group, liver structural damage and stress were not significant in the environmental concentration group (T1-L) and the number of differential genes and differential metabolites were lower. However, as DBP stress concentration increased, the liver damage became severe, with significant vacuolation and hemolysis observed in the T2-L and T3-L groups. The TUNEL assay revealed a significant increase in the number of apoptotic cells along with a notable rise in differential genes and metabolites in the T2-L and T3-L groups. Oxidative stress markers (T-AOC, SOD, CAT, and GSH-PX) were also significantly higher in the T2-L and T3-L groups. RNA-Seq analysis showed that the protein processing in the endoplasmic reticulum pathway was most significantly -enriched differential gene pathway shared by both C-L vs T2-L and C-L vs T3-L, with most of the genes in this pathway showing significant up-regulation. This suggests that the protein processing in the endoplasmic reticulum pathway may play a key role in protecting the liver from injuries caused by high DBP stress. Interestingly, C XI, C XII, C XIII, C XIV and C XV in the chemical carcinogenesis - reactive oxygen species pathway were significantly down-regulated in the T2-L and T3-L groups based on combined transcriptomic and metabolomic analyses, suggesting that DBP causes liver injury by disrupting mitochondria. This comprehensive histomorphometric and multi-omics study demonstrated that the current DBP concentration in the habitat of S. prenanti in the upper reaches of the Yangtze River temporarily causes less liver damage. However, with increasing of DBP concentration, DBP could still cause serious liver damage to S. prenanti. This study provides a new mechanistic understanding of the liver response mechanism of S. prenanti under different concentrations of DBP stress and offers basic data for the ecological protection of the Yangtze River.

RevDate: 2025-06-10
CmpDate: 2025-06-10

Zhou H, Wu Z, Wang X, et al (2025)

6PPD-quinone exposure induces oxidative damage and physiological disruption in Eisenia fetida: An integrated analysis of phenotypes, multi-omics, and intestinal microbiota.

Journal of hazardous materials, 493:138334.

The environmental prevalence of the tire wear-derived emerging pollutant N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q) has increasingly raised public concern. However, knowledge of the adverse effects of 6PPD-Q on soil fauna is scarce. In this study, we elucidated its impact on soil fauna, specifically on the earthworm Eisenia fetida. Our investigation encompassed phenotypic, multi-omics, and microbiota analyses to assess earthworm responses to a gradient of 6PPD-Q contamination (10, 100, 1000, and 5000 μg/kg dw soil). Post-28-day exposure, 6PPD-Q was found to bioaccumulate in earthworms, triggering reactive oxygen species production and consequent oxidative damage to coelomic and intestinal tissues. Transcriptomic and metabolomic profiling revealed several physiological perturbations, including inflammation, immune dysfunction, metabolic imbalances, and genetic toxicity. Moreover, 6PPD-Q perturbed the intestinal microbiota, with high dosages significantly suppressing microbial functions linked to metabolism and information processing (P < 0.05). These alterations were accompanied by increased mortality and weight loss in the earthworms. Specifically, at an environmental concentration of 6PPD-Q (1000 μg/kg), we observed a substantial reduction in survival rate and physiological disruptions. This study provides important insights into the environmental hazards of 6PPD-Q to soil biota and reveals the underlying toxicological mechanisms, underscoring the need for further research to mitigate its ecological footprint.

RevDate: 2025-06-10
CmpDate: 2025-06-10

McKenzie PF, Berardi AE, R Hopkins (2025)

Delayed flowering phenology of red-flowering plants in response to hummingbird migration.

Current biology : CB, 35(9):2175-2182.e3.

The radiation of angiosperms is marked by a phenomenal diversity of floral size, shape, color, scent, and reward.[1][,][2][,][3][,][4] The multi-dimensional response to selection to optimize pollination has generated correlated suites of these floral traits across distantly related species, known as "pollination syndromes."[5][,][6][,][7][,][8][,][9] The ability to test the broad utility of pollination syndromes and expand upon the generalities of these syndromes is constrained by limited trait data, creating a need for new approaches that can integrate vast, unstructured records from community-science platforms. Here, we compile the largest North American flower color dataset to date, using GPT-4 with Vision to classify color in over 11,000 species across more than 1.6 million iNaturalist observations. We discover that red- and orange-flowering species (classic "hummingbird pollination" colors) bloom later in eastern North America compared with other colors, corresponding to the arrival of migratory hummingbirds. Our findings reveal how seasonal flowering phenology, in addition to floral color and morphology, can contribute to the hummingbird pollination syndrome in regions where these pollinators are migratory. Our results highlight phenology as an underappreciated dimension of pollination syndromes and underscore the utility of integrating artificial intelligence with community-science data. The potential breadth of analysis offered by community-science datasets, combined with emerging data extraction techniques, could accelerate discoveries about the evolutionary and ecological drivers of biological diversity.

RevDate: 2025-05-28

Matuszewska D, Kiedrzyńska E, Jóźwik A, et al (2025)

An analysis of catchment factors associated with heavy metal export into the Baltic Sea and nature-based solutions aimed at its limitation.

Journal of hazardous materials, 494:138727 pii:S0304-3894(25)01643-7 [Epub ahead of print].

The aim of the article was to determine the shares of individual Baltic countries participating in the inflow of metal loads to the Baltic Sea and identify patterns of similarity between these countries regarding the causes of heavy metal load generation. The analyses used HELCOM and EUROSTAT data. The findings indicate that Finland and Sweden generate the highest total loads of heavy metals flowing in through rivers. However, Lithuania and Finland are distinguished by high metal loads calculated per km[2] of catchment area. Clustering countries in terms of their similarity in the heavy metal loads provided to the Baltic resulted in three groups. Finland and Lithuania generates the highest mean loads of cadmium, chromium, nickel and zinc per unit area [kg/km[2]/year]. Estonia and Latvia generates the highest mean annual loads of lead, mercury and copper. Poland, Germany and Sweden generates the lowest heavy metal loads. Multidimensional data analysis showed a strong correlation between aquaculture production in the Baltic Sea catchment area, the number of cattle, beef, mutton, pigs, poultry, and meat produced from them, the amount of waste, trucks, cereal production, the use of nitrogen fertilizers, and the loads of heavy metals reaching the Baltic Sea with river waters. Therefore, there is a need for continuous monitoring of the loads and transfer of heavy metals to the Baltic Sea, and for activities aimed at eliminating them from the environment. For this purpose, Nature-Based Solutions can be used, as they represent inexpensive, nature-friendly methods for removing pollutants from surface waters.

RevDate: 2025-06-09
CmpDate: 2025-06-09

Kuru A, Yüzer MA, Yüzer AŞ, et al (2025)

Integrated site selection model for industrial areas: case study for İnegöl furniture industry.

Environmental science and pollution research international, 32(8):4771-4793.

Industrial activities in the central area have adverse effects such as noise, odor, and traffic congestion. Simultaneously, due to changing technological and economic advances, existing industrial areas cannot meet the needs, spatial inadequacies obstruct competition, and production capacity decreases. Decentralizing industrial activities from urban centers are ecologically and economically necessary. Various elements on a macro and micro scale need to be considered to select suitable sites for new industrial areas. Natural, socioeconomic, and built environment features must be examined to ensure sustainability. The objective of this study is to develop an integrated industrial site location model that considers the needs of authorities and industrial stakeholders, as well as economic and ecological sustainability for the İnegöl district, one of Turkey's leading settlements in the furniture industry. Thirty-seven criteria were evaluated using GIS based multi-criteria decision making methods. The criteria were defined through spatial analysis, expert opinions, and in-depth interviews with industry and local government representatives. Using weighted linear combination process the five sub-regions exhibiting the lowest economic costs and the least environmental degradation have been identified. Advantages and disadvantages were identified through the use of sketches and comparisons between the sub-regions. A decision support system was developed for local and central government institutions to be used in industrial site selection processes.

RevDate: 2025-06-03
CmpDate: 2025-06-03

Guo J, Xie Y, Dou X, et al (2025)

Combining source identification and risk assessment to uncover spatial risk patterns in an agricultural lake.

Journal of environmental management, 387:125966.

Pollutant source identification and risk assessment underpin environmental management, necessitating innovative methods for both pollution source identification and comprehensive evaluation to enhance management efficiency. In this study, we developed a novel integrated framework that combines Bayesian isotope mixing, positive matrix factorization (PMF), random forest, and spatial autocorrelation for multi-pollutant source identification and risk assessment. The Bayesian isotope mixing model revealed that fertilizers accounted for 61 % of the nitrate in the lake and 46 % of the nitrate in the river. Furthermore, PMF analysis indicated that polycyclic aromatic hydrocarbons (PAHs) in sediments and soil were primarily sourced from vehicular emissions (32 %), while heavy metals (40 %) were mainly from vehicular emissions and agricultural activities. Using a comprehensive pollution assessment framework for water and sediment quality, we found that water quality ranged from "medium" to "excellent", and sediment quality ranged from "good" to "excellent". Among various evaluation indices, CODMn, As, F[-], TP, Pb, and Zn were pivotal in determining comprehensive water quality. Key indices for sediment quality evaluation included Flua, BaP, BaA, Pyr, Ant, Pb, and As, primarily sourced from automobile emissions and agricultural activities. Spatial autocorrelation analysis demonstrated a spatial relationship between water quality and sediment quality, covering 43 % of the area. High-pollution areas (13 %) were concentrated around natural river inlets, while low-pollution zones (17 %) were located near ecological water replenishment river inlets. This underscores the significant influence of inflowing water quality on sediment conditions. This study highlights the development of a comprehensive pollution assessment framework to evaluate sediment and soil pollution, as well as to identify high-risk zones of compound pollution in water and sediment. Furthermore, the framework's universal applicability for agricultural lake systems enables the identification of high-risk zones through water-sediment interaction analysis.

RevDate: 2025-06-04
CmpDate: 2025-05-28

Berger M, Ehlers JP, J Nitsche (2025)

Aligning With the Goals of the Planetary Health Concept Regarding Ecological Sustainability and Digital Health: Scoping Review.

Journal of medical Internet research, 27:e71795 pii:v27i1e71795.

BACKGROUND: Climate change, driven by greenhouse gas emissions, threatens human health and biodiversity. While the digitalization of health care, including telemedicine and artificial intelligence, offers sustainability benefits, it also raises concerns about energy use and electronic waste. Balancing these factors is key to a sustainable health care future.

OBJECTIVE: The objective of this review was to examine the extent to which digitalization in the health care sector influences environmental sustainability. Specifically, it aimed to assess how digitalization can contribute to reducing the health care sector's impact on global climate change. From these findings, conclusions were drawn regarding the extent to which digitalization aligns with the objectives of the Planetary Health movement and how these 2 movements may mutually reinforce each other.

METHODS: A scoping review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines using databases such as PubMed and Scopus was conducted, and 58 quantitative studies from 2009 to 2024 were analyzed for environmental, social, and economic outcomes aligned with Planetary Health goals.

RESULTS: This review analyzed 58 studies on the environmental impact of digitalization in health care primarily focusing on telemedicine, which was examined in 91% (53/58) of the studies. Most studies (56/58, 97%) quantified transport-related emissions avoided through digitalization, with some also assessing emissions from health care facilities, medical equipment, and energy consumption. Findings indicated that telemedicine significantly reduces carbon dioxide emissions, with total avoided emissions amounting to approximately 830 million kg. A substantial proportion of the studies (36/58, 62%) focused on social aspects, highlighting factors such as patient satisfaction, time efficiency, and overall convenience. In addition, economic considerations were analyzed in 48% (28/58) of the studies, emphasizing cost reductions and resource optimization. However, only 12% (7/58) of the studies evaluated the full life cycle impact of digital technologies, highlighting the need for further research on their long-term environmental sustainability.

CONCLUSIONS: This review calls for further research beyond telemedicine, advocating for life cycle analyses and actionable strategies for a sustainable digitalization in health care systems. The Planetary Health framework is highlighted as a guide for ensuring sustainable digital transformation in health care.

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

Yang W, Liu Y, Shao H, et al (2025)

Developing a cloud-based WebGIS tool for communicating integrated ecosystem services assessment modeling to conservation stakeholders.

Journal of environmental management, 375:124372.

Various modeling efforts have been conducted to evaluate ecosystem services (ES) of agricultural conservation practices but typically these models are too complex for conservation stakeholders to use. This research developed a cloud-based WebGIS tool for communicating integrated ES modeling to conservation stakeholders. The integrated ES modeling was developed by linking farm economic, watershed hydrologic, and soil carbon modeling within a spatial optimization framework for identifying conservation practices to minimize economic costs subject to multiple ES targets including water quality and soil carbon improvement benefits. The WebGIS tool, named "Ecosystem Services Assessment Tool" (ESAT), has a suite of functions to visualize watershed characteristics, summarize the effectiveness of existing agricultural conservation practices, examine the cost, effectiveness, and cost-effectiveness of future agricultural conservation practices, and further, identify optimal sets of conservation practices for achieving cost-effectiveness. The study area for the integrated ES modeling and WebGIS tool development was the 4,820-km[2] Modeste watershed in Alberta, Canada. The ESAT application demonstrated its functionalities to support decision making, particularly in identifying cost-effective conservation practices for achieving sediment, phosphorus or nitrogen reduction, or soil carbon increase target. In the research, conservation stakeholders including municipal and provincial governments, conservation management agencies, and NGOs were actively engaged in data collection, modeling development, WebGIS tool development, and training for the use of the WebGIS tool. Conservation stakeholders assessed that the ESAT is a very useful tool for supporting decision making in agri-environmental programs. However, the WebGIS tool can be further simplified and streamlined to improve the user-friendliness of the ESAT.

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

Lajmi A, Glinka F, E Privman (2025)

Optimizing ddRAD sequencing for population genomic studies with ddgRADer.

Molecular ecology resources, 25(5):e13870.

Double-digest Restriction-site Associated DNA sequencing (ddRADseq) is widely used to generate genomic data for non-model organisms in evolutionary and ecological studies. Along with affordable paired-end sequencing, this method makes population genomic analyses more accessible. However, multiple factors should be considered when designing a ddRADseq experiment, which can be challenging for new users. The generated data often suffer from substantial read overlaps and adaptor contamination, severely reducing sequencing efficiency and affecting data quality. Here, we analyse diverse datasets from the literature and carry out controlled experiments to understand the effects of enzyme choice and size selection on sequencing efficiency. The empirical data reveal that size selection is imprecise and has limited efficacy. In certain scenarios, a substantial proportion of short fragments pass below the lower size-selection cut-off resulting in low sequencing efficiency. However, enzyme choice can considerably mitigate inadvertent inclusion of these shorter fragments. A simple model based on these experiments is implemented to predict the number of genomic fragments generated after digestion and size selection, number of SNPs genotyped, number of samples that can be multiplexed and the expected sequencing efficiency. We developed ddgRADer - http://ddgrader.haifa.ac.il/ - a user-friendly webtool and incorporated these calculations to aid in ddRADseq experimental design while optimizing sequencing efficiency. This tool can also be used for single enzyme protocols such as Genotyping-by-Sequencing. Given user-defined study goals, ddgRADer recommends enzyme pairs and allows users to compare and choose enzymes and size-selection criteria. ddgRADer improves the accessibility and ease of designing ddRADseq experiments and increases the probability of success of the first population genomic study conducted in labs with no prior experience in genomics.

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

Robledo-Ruiz DA, Austin L, Amos JN, et al (2025)

Easy-to-use R functions to separate reduced-representation genomic datasets into sex-linked and autosomal loci, and conduct sex assignment.

Molecular ecology resources, 25(5):e13844.

Identifying sex-linked markers in genomic datasets is important because their presence in supposedly neutral autosomal datasets can result in incorrect estimates of genetic diversity, population structure and parentage. However, detecting sex-linked loci can be challenging, and available scripts neglect some categories of sex-linked variation. Here, we present new R functions to (1) identify and separate sex-linked loci in ZW and XY sex determination systems and (2) infer the genetic sex of individuals based on these loci. We tested these functions on genomic data for two bird and one mammal species and compared the biological inferences made before and after removing sex-linked loci using our function. We found that our function identified autosomal loci with ≥98.8% accuracy and sex-linked loci with an average accuracy of 87.8%. We showed that standard filters, such as low read depth and call rate, failed to remove up to 54.7% of sex-linked loci. This led to (i) overestimation of population FIS by up to 24%, and the number of private alleles by up to 8%; (ii) wrongly inferring significant sex differences in heterozygosity; (iii) obscuring genetic population structure and (iv) inferring ~11% fewer correct parentages. We discuss how failure to remove sex-linked markers can lead to incorrect biological inferences (e.g. sex-biased dispersal and cryptic population structure) and misleading management recommendations. For reduced-representation datasets with at least 15 known-sex individuals of each sex, our functions offer convenient resources to remove sex-linked loci and to sex the remaining individuals (freely available at https://github.com/drobledoruiz/conservation_genomics).

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

Chi L, Zhang X, Xue Y, et al (2025)

fastHaN: a fast and scalable program for constructing haplotype network for large-sample sequences.

Molecular ecology resources, 25(5):e13829.

Haplotype networks can be used to demonstrate the genealogical relationships of DNA sequences within species, and thus are widely applied in population genetics, molecular ecology, epidemiology and evolutionary studies. However, existing programs become computationally infeasible as the sample size increases. Here, we present fastHaN, an efficient and scalable program suitable for constructing haplotype networks for large samples. On a data set with the haplotype length of 30 kb, the Median Joining Network (MJN) algorithm implemented by fastHaN is 3000 times faster than PopART and 70 times faster than NETWORK in single-threaded mode. The implementation of the Templeton-Crandall-Sing (TCS) algorithm is 100 times faster than PopART and 5800 times faster than the TCS software. Moreover, fastHaN also enables multi-threaded mode with scalability. The source code is freely available on https://github.com/ChenHuaLab/fastHaN/. A web-based version is also available on https://ngdc.cncb.ac.cn/haplotype/.

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

Huang K, Li W, Yang B, et al (2025)

vcfpop: Performing population genetics analyses for autopolyploids and aneuploids based on next-generation sequencing data sets.

Molecular ecology resources, 25(5):e13744.

Polyploids are cells or organisms with a genome consisting of more than two sets of homologous chromosomes. Polyploid plants have important traits that facilitate speciation and are thus often model systems for evolutionary, molecular ecology and agricultural studies. However, due to their unusual mode of inheritance and double-reduction, diploid models of population genetic analysis cannot properly be applied to autopolyploids. To overcome this problem, we developed a software package entitled vcfpop to perform a variety of population genetic analyses for autopolyploids, such as parentage analysis, analysis of molecular variance, principal coordinates analysis, hierarchical clustering analysis and Bayesian clustering. We used three data sets to evaluate the capability of vcfpop to analyse large data sets on a desktop computer. This software is freely available at http://github.com/huangkang1987/vcfpop.

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.

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RJR Experience and Expertise

Researcher

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

Educator

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

Administrator

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

Technologist

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

Publisher

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

Speaker

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

Facilitator

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

Designer

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

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

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Collection of publications by R J Robbins

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

Research Gate page for R J Robbins

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

Curriculum Vitae for R J Robbins

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