Search Results (184)

This study investigates the dynamic behavior of a Lotka–Volterra amensalism system subject to non-selective harvesting, regulated by wind speed. We develop a coupled windharvesting population model that captures the dual regulatory mechanism of wind as an environmental factor on the marine ecosystem: it weakens the amensalistic interaction between species by enhancing the dilution of inhibitory substances while simultaneously suppressing human harvesting intensity by impeding fishing operations. Using stability theory and the Lyapunov function method, we systematically analyze the existence and stability of equilibrium points and explore the ecological state transitions driven by varying wind speed. The results show that the system admits four possible equilibrium states. Among them, the positive equilibrium, whenever it exists, is globally asymptotically stable. As wind speed increases, the system undergoes sequential ecological regime shifts: from extinction of both species to dominance by a single species and finally to stable coexistence of both species. Numerical simulations confirm the theoretical findings and reveal the intrinsic mechanism by which wind promotes biodiversity: by reducing harvesting pressure and mitigating the amensalistic effect. The concept of critical wind speed proposed in this work offers a quantitative basis for managing wind conditions in marine protected areas and designing adaptive harvesting strategies, holding significant implications for marine conservation and sustainable fishery development. Full article

Understanding connectivity between populations is key to identifying hotspots of diversity, dispersal sinks and sources, and effective management units for natural resources. Multi-species connectivity seeks to overcome species-specific idiosyncrasies to identify shared patterns that are most critical to spatial management. The linear Hawaiian archipelago provides an excellent platform to assess multi-species connectivity patterns, with shared boundaries to gene flow identified across a majority of the 41 coral reef species surveyed to date. Here, we evaluate genome-scale data by comparing consistency and resolution to previous connectivity studies using far fewer loci. We used pool-seq to genotype 22,503–232,730 single nucleotide polymorphisms per species (625,215 SNPs total) from the same individuals published in previous studies of two fishes, two corals, and two lobsters. Additionally, one coral species (Pocillopora meandrina) without previous archipelago-wide population genetic data was included. With greater statistical power, most genetic differences between pairwise comparisons of islands were significant (250 of 308), consistent with the most recent larval dispersal models for the Hawaiian Archipelago. These data reveal significant differentiation at a finer scale than previously reported using single-marker studies, yet did not overturn any of the conclusions or management implications drawn from previous studies. We confirm that population genomic datasets are consistent with previously reported patterns of multispecies connectivity but add a finer layer of population resolution that is pertinent to management. Full article

Sheep are an economically important livestock species, and reproductive performance is a key trait affecting productivity. The Dorper × Hu hybrid sheep (DHS), widely bred in China, provides a valuable model for studying the genetic basis of prolificacy. This study aimed to investigate the genomic architecture and identify candidate genes associated with high litter size in DHS using whole-genome selective sweep analysis and genome-wide association study (GWAS). A total of 31 DHS individuals with complete reproductive records were sequenced and compared with publicly available genomic data from 20 Hu sheep (HUS) and 10 Dorper sheep (DPS). Population genetic structure and diversity were assessed using phylogenetic trees, principal component analysis (PCA), and ADMIXTURE analysis. To identify key genomic regions associated with litter size, we performed selective sweep analysis between the polytocous and monotocous subpopulations of DHS using multiple methods within a 50 kb sliding window framework, including $F_{ST}$, ${\theta }_{\pi }$ ratio, XP-CLR, and XP-EHH; we also conducted GWAS. DHS exhibited a distinct genetic structure with admixed ancestry and elevated genetic diversity. Genetic diversity analysis showed that DHS retained moderate levels of heterozygosity and polymorphism, comparable to or exceeding those of its parental breeds. Comparative analysis between polytocous and monotocous DHS identified reproduction-associated genes, including MUC1, PLCB4, SIN3A, and ELAVL2, enriched in pathways such as ovarian steroidogenesis, insulin secretion, and circadian entrainment. Furthermore, genome-wide association study (GWAS) identified 140 significant loci (p < 10⁻⁵) associated with reproductive traits. From these, 10 candidate SNPs were selected for validation through single-marker association analysis in 200 DHS individuals, among which two loci—g.88680390 C>A (SLC24A2/MLLT3) and g.18197516 T>C (ABCA1)—showed significant correlations with litter size. These findings enhance our understanding of the genetic basis of prolificacy in DHS and provide valuable molecular markers for genomic selection in sheep-breeding programs. Full article

Adeno-associated viruses (AAVs) are a leading vector for gene therapy, yet their clinical utility is limited by the lack of robust quality control methods to distinguish between empty (AAV_empty), partially loaded (AAV_partial), and fully DNA loaded (AAV_full) capsids. Current analytical techniques provide partial insights but remain limited in sensitivity, throughput, or resolution. Here we present a multimodal plasmonic nanopore sensor that integrates optical trapping with electrical resistive-pulse sensing to characterize AAV9 capsids at the single-particle level in tens of μL sample volumes and fM range concentrations. As a model system, we employed AAV9 capsids not loaded with DNA, capsids loaded with a self-complementary 4.7 kbp DNA (AAV_scDNA), and ones loaded with single-stranded 4.7 kbp DNA (AAV_ssDNA). Ground-truth validation was performed with analytical ultracentrifugation (AUC). Nanosensor data were acquired concurrently for optical step changes (occurring at AAV trapping and un-trapping) both in transmittance and reflectance geometries, and electrical nanopore resistive pulse signatures, making for a total of five data dimensions. The acquired data was then filtered and clustered by Gaussian mixture models (GMMs), accompanied by spectral clustering stability analysis, to successfully separate between AAV species based on their DNA load status (AAV_empty, AAV_partial, AAV_full) and DNA load type (AAV_scDNA versus AAV_ssDNA). The motivation for quantifying the AAV_empty and AAV_partial population fractions is that they reduce treatment efficacy and increase immunogenicity. Likewise, the motivation to identify AAV_scDNA population fractions is that these have much higher transfection rates. Importantly, the results showed that the nanosensor could differentiate between AAV_scDNA and AAV_ssDNA despite their identical masses. In contrast, AUC could not differentiate between AAV_scDNA and AAV_ssDNA. An equimolar mixture of AAV_scDNA, AAV_ssDNA and AAV_empty was also measured with the sensor, and the results showed the expected population fractions, supporting the capacity of the method to differentiate AAV load status in heterogeneous solutions. In addition, less common optical and electrical signal signatures were identified in the acquired data, which were attributed to debris, rapid entry re-entry to the optical trap, or weak optical trap exits, representing critical artifacts to recognize for correct interpretation of the data. Together, these findings establish plasmonic nanopore sensing as a promising platform for quantifying AAV DNA loading status and genome type with the potential to extend ultra-sensitive single-particle characterization beyond the capabilities of existing methods. Full article

Urinary tract infections (UTIs) occur in dogs and cats across diverse populations and regions. In this systematic review and meta-analysis, we estimated the pooled prevalence of UTIs in dogs and cats with lower urinary tract diseases (LUTDs) or other illnesses and characterized the distribution of bacterial uropathogens. A comprehensive search of PubMed, Scopus, and Web of Science identified 887 articles, of which 18 were published up to October 2024, met the inclusion criteria. Meta-analyses using a random-effects model estimated a pooled prevalence of 26.1%. Prevalence was greater in dogs (44.6%) than in cats (18.6%), and higher in females (30.1%) than in males (14.6%), affecting all age groups. Single-pathogen infections predominated, with Escherichia coli being the most common uropathogen in both species, followed by Proteus spp. and Staphylococcus spp. in dogs and Staphylococcus spp. in cats. Prevalence remained relatively constant over the study period (1991–2021). These findings underscore the value of pooled prevalence and bacterial distribution data for guiding empirical antimicrobial selection, and they highlight the need for further systematic reviews on antimicrobial susceptibility and multidrug resistance to inform treatment strategies. Full article

A better understanding of cultivation of microorganisms in mixed culture is needed to identify the relationships between different bacterial strains. Lactobacillus acidophilus (ATCC 4796) Gram-positive bacteria and Escherichia coli (K12-MG1655) Gram-negative bacteria are two microorganisms that can interact accidentally in the dairy food chain process or in different human pathologies. This work focused on how bacterial populations evolve in batch culture, depending on the nature of the carbon source, by monitoring cell viability using flow cytometry and substrate concentration. The experiments monitored the time evolution of bacterial populations grown on two different cultivation media (single source of carbon—SSCM and de Man, Rogosa and Sharpe—MRS broth media) which stimulated different proliferation conditions. Experimental data were used to calibrate a segregated mathematical model (accounting for two bacterial strains—biological clusters—with their individual birth time, an event that creates a new timeline cluster to which daughters belong) that highlights in silico the various interactions that can occur between two bacterial species. Full article

The wild boar (Sus scrofa) is a highly adaptable species that has spread into urban-proximate areas, consequently intensifying human–wildlife conflicts in South Korea. Understanding the range and environmental preferences of this species is crucial for efficient population management. Therefore, we investigated wild boar occupancy in Bukhansan National Park (BNP), a protected area near Seoul. We deployed camera traps at 24 locations from March to May 2022 to investigate spring season habitat use patterns. We used single-season, single-species occupancy modeling to explore the impact of environmental and anthropogenic factors on the distribution of wild boar. During 2208 trap nights, we recorded wild boars at 14 sites, with an average occupancy probability (Ψ) of 0.67 ± 0.03. The distance to human settlements was the best predictor of occupancy, with wild boars avoiding regions near human activity sites. In contrast, proximity to puddles significantly increased detection and occupancy probabilities, indicating the importance of water sources for drinking and wallowing. Wild boars also showed a preference for areas near agricultural lands but exhibited behavioral avoidance of direct human presence. Our spring season findings suggest the need for targeted management strategies that prioritize population control in areas far from settlements but adjacent to water and agricultural boundaries. This study provides critical insights into the spatial ecology of wild boars in urban-proximate landscapes and provides science-based measures for mitigating conflicts and disease risks. We recommend long-term monitoring for the assessment of seasonal variations and efficacy of management interventions. Full article

Oropouche virus (OROV) is an emerging arbovirus responsible for Oropouche fever, also known as sloth fever, a febrile illness that can lead to recurrent outbreaks in affected regions. Endemic to parts of South and Central America, OROV is primarily transmitted by biting midges (Culicoides paraensis), although mounting evidence implicates mosquitoes, particularly the Culex and Aedes species, as additional vectors. Recent ecological disturbances—such as deforestation, urbanization, and climate change—have driven significant shifts in vector population dynamics, contributing to the expanded geographic range and increased transmission of OROV. Notably, recent reports of OROV infections among American and European travelers to Cuba highlight the virus’s growing potential for international dissemination and underscore its significance as a global health concern. OROV is an enveloped orthobunyavirus within the Peribunyaviridae family, possessing a tripartite, single-stranded, negative-sense RNA genome composed of the S (small), M (medium), and L (large) segments. These segments encode the nucleocapsid (N) protein, glycoproteins (Gn and Gc), and RNA-dependent RNA polymerase, respectively. Despite increasing incidence and potential for global spread, no licensed vaccines or antiviral therapies currently exist, and effective diagnostic tools remain limited. Furthermore, although human-to-human transmission has not been observed, the absence of robust surveillance systems complicates timely outbreak detection and response. In this study, we present a comprehensive molecular characterization of OROV’s major structural proteins, with an emphasis on structural modeling and epitope prediction. By integrating bioinformatics approaches with available structural data, we identify key antigenic regions that could serve as targets for the development of serological diagnostics and vaccine candidates. Our findings contribute critical insights into the molecular virology of OROV and provide a foundational framework for future efforts aimed at the prevention, diagnosis, and control of this neglected tropical pathogen. These advancements are essential for mitigating the impact of OROV in endemic regions and reducing the risk of global emergence. Full article

Allorecognition, or distinguishing between the self and nonself within the same species, is observed in both animals and plants, particularly in the context of immune reactions and self-incompatibility in sexual reproduction. Polymorphic recognition molecules are known to be responsible for such allorecognition during fertilization. Previous studies have reported that in ascidians and flowering plants, inbreeding avoidance relies on a pair of polymorphic recognition molecules with a receptor-ligand relationship that are encoded at a single locus, the S locus (Self-incompatibility locus), but the process by which such pairs of recognition molecules emerge and evolve to become polymorphic is not known. Here, a population genetics study was carried out as a novel approach for investigating allorecognition. To study the process by which self-recognition emerges, we simulated a situation in which an allorecognizing genotype is generated from a nonallorecognizing genotype through mutation and then analyzed whether the two genotypes could coexist. The conditions under which the numbers of allorecognition alleles could increase over evolutionary time were investigated, and the generational dynamics of nonallorecognizing genotypes were analyzed. Subsequent modeling was carried out to reproduce the allorecognition mechanism in Ciona, and consistency between the simulation results and experimental data was observed. Our approach provides new insight into the evolutionary process of allorecognition. Full article

The European wildcat exhibits considerable plasticity in its habitat requirements across its distribution, with differences increasing along a continental-scale latitudinal gradient. While wildcats often favor deciduous and mixed forests with dense cover and prey, studies show these preferences vary across their expansion. Range-wide conservation efforts will benefit from incorporating knowledge generated by robust regional ecological models. We used data from a large camera trap grid (n = 292 stations), spanning across eight wildcat-associated habitats, within its range in northern Greece, to understand the regional ecological parameters affecting the species’ habitat selection. We analyzed the data using single-season density-induced detection heterogeneity occupancy models (Royle–Nichols), considering 12 environmental and anthropogenic parameters. The global model’s GoF was high (p = 0.9). Elevation and percent forest cover were both significantly negatively related to wildcat occupancy (as derived from the modeled “relative abundance index” N). Likewise, there was a negative, but moderate, relation between distance to freshwater bodies and human settlements with wildcat occupancy. We used the model-average coefficients to generate a predictive map of wildcat relative abundance across northern Greece, which identified 47,930 km² of potential wildcat habitat. Assuming a range of densities between 0.05 and 0.3 ind/km² in areas with predicted low, medium, and high relative abundance, we speculate the putative wildcat population in northern Greece to be between 3535 and 7070 individuals. The findings, which vary from ecological models of the species in northern Europe, show the need for regional models and the importance of Greece, and the Balkan peninsula, for the species. Full article

The European rabbit (Oryctolagus cuniculus) is a key species in many Mediterranean ecosystems, especially as prey for numerous Iberian predators. Due to its population decline and spatially heterogeneous recovery following different diseases, there is a need to understand the factors driving local abundance, and a potential refuge effect of anthropized sites has been speculated. In this study, 18 peri-urban areas in Central Spain were selected and a rabbit abundance index was measured in those areas and in parallel controls. Urban occupation and vegetation cover around sampling points were measured, as well as distance to roads, forest patches, and rivers, as factors which can drive rabbit abundance. Linear models were built to unravel general trends in data, from the perspectives of vegetation vs. human occupation and larger landscape-scale effects on rabbit abundance. Negative effects of urban development, distance to roads and proportion of pastures on rabbit abundance were identified, in addition to a positive effect of distance to large forest patches. Regarding urbanization, differences were found among urban types, with a significant negative effect of single-family residential occupation in comparison with multi-family and commercial/industrial occupation. In short, urbanization affects rabbit density, but it does not produce a generalized refuge area surrounding human settlements. Full article

Understanding how endangered carnivores partition spatiotemporal distribution in human-dominated landscapes is pivotal for mitigating biodiversity loss in climate-sensitive boreal ecosystems. Here, we used kernel density data derived from a 16-month camera-trap survey (140 UVL7 cameras), cold single-season (November–April) occupancy models, and MaxEnt 3.4.4 to identify the effects of biotic interactions, anthropogenic disturbance, and environmental factors on the spatiotemporal distribution of the wolverine (Gulo gulo) in Beijicun National Nature Reserve, Heilongjiang Province, China. We found that wolverines exhibited crepuscular activity patterns using night-time relative abundance index (NRAI) = 50.29% with bimodal peaks (05:00–07:00, 13:00–15:00), with dawn activity predominant during the warm season (05:00–06:00) and a bimodal activity pattern in the cold season (08:00–09:00, 14:00–15:00). Temporal overlap with prey (overlap coefficient Δ = 0.84) and competitors (Δ = 0.70) was high, but overlap with human-dominated temporal patterns was low (Δ = 0.58). Wolverines avoided human settlements and major roads, preferred moving along forest trails and gentle slopes, and avoided high-altitude deciduous forests. Populations were mainly concentrated in southern Hedong and Qianshao Forest Farms, which are characterized by high habitat integrity, high prey densities, and minimal anthropogenic disturbance. These findings suggest that wolverines may influence boreal trophic networks, especially in areas with intact prey communities, competitors, and spatial refugia from human disturbances. We recommend that habitat protection and management within the natural reserve be prioritized and that sustainable management practices for prey species be implemented to ensure the long-term survival of wolverines. Full article

Helicobacter pylori (Hp), a Class I carcinogen infecting over 50% of the global population, is increasingly resistant to conventional antibiotics. This study presents an AI-engineered probiotic strategy targeting urease, a key Hp virulence factor. A humanized single-domain antibody (UreBAb), previously identified and selected in our laboratory, was synthesized commercially and modeled using AlphaFold2, with structural validation conducted via SAVES 6.0. Molecular docking (PyMOL/ClusPro2) and binding energy analysis (InterProSurf) identified critical urease-active residues: K40, P41, K43, E82, F84, T86, K104, I107, K108, and R109. Machine learning-guided optimization using mCSA-AB, I-Mutant, and FoldX prioritized four mutational hotspots (K43, E82, I107, R109), leading to the generation of nine antibody variants. Among them, the I107W mutant exhibited the highest activity, achieving 65.6% urease inhibition—a 24.95% improvement over the wild-type antibody (p < 0.001). Engineered Escherichia coli Nissle 1917 (EcN) expressing the I107W antibody significantly reduced gastric HP colonization by 4.42 log10 CFU in the treatment group and 3.30 log10 CFU in the prevention group (p < 0.001 and p < 0.05, respectively), while also suppressing pro-inflammatory cytokine levels. Histopathological (H&E) analysis confirmed that the I107W antibody group showed significantly enhanced mucosal repair compared to wild-type probiotic-treated mice. Notably, 16S rRNA sequencing revealed that intestinal microbiota diversity and the abundance of core microbial species remained stable across different ethnic backgrounds. By integrating AI-guided antibody engineering with targeted probiotic delivery, this platform provides a transformative and microbiota-friendly strategy to combat antibiotic-resistant Hp infections. Full article

(1) Background: Affected by multiple factors, the decline in fish species diversity in some aquatic ecosystems has become increasingly pronounced. At a broad spatial scale, economic development has been widely recognized as one of the key factors influencing the fish distribution pattern. However, at a small scale, within a single river basin, the effects of economic development on the freshwater fish distribution and communities remain largely uninvestigated. (2) Methods: environmental DNA (eDNA) samples were collected from 26 sampling sites of the Lixian River in both the summer (June) and winter (November). Economic data from the Lixian River basin were collected, and analyses, including multivariate regression tree analysis and generalized linear model fitting, were performed using R 4.3.2. (3) Results: A total of 65 fish species was characterized, and the Chao1 diversity indices in the upstream (13.42) and downstream (13.00) were significantly higher than those in the middle reaches (8.55, p < 0.01) of this river. The species communities exhibited an obvious gradient changing pattern from the upstream to the downstream reaches, with parameters of water quality, including transparency, pH, dissolved oxygen and temperature, and climatic factors functioning as the key variables. Furthermore, the generalized linear model analysis revealed significant positive correlations between agricultural population (p = 0.00106), total grain production (p = 0.00476), total population (p = 0.00192) and the Chao1 index. (4) Conclusions: Climatic factors are the key factors affecting the fish diversity in the Lixian River. In less economically developed areas, the development of local economic activities may enhance fish diversity. Full article

The Triatoma rubrovaria subcomplex, comprising several triatomine species, plays a significant role in the transmission of Chagas disease in southern Brazil. Despite morphological distinctions among these species, their genetic differentiation remains poorly understood, particularly in sympatric regions. This study investigates the genetic diversity and phylogenetic relationships through DNA sequencing analysis of five sympatric species within the T. rubrovaria subcomplex (T. rubrovaria, T. carcavalloi, T. klugi, T. circummaculata, and T. pintodiasi), using a 542-bp fragment of the mitochondrial cytochrome b (mtCytb) gene. A total of 84 specimens were collected from six municipalities in Rio Grande do Sul, Brazil, and analyzed alongside laboratory-reared specimens and sequences from the GenBank. Bayesian phylogenetic reconstructions, haplotype networks, and population structure analyses revealed a lack of clear genetic differentiation among the five species, with overlapping intra- and interspecific divergences and shared haplotypes. These findings suggest either a single species exhibiting phenotypic plasticity or a group of incipient species with ongoing gene flow. This study highlights the need for a taxonomic revision and suggests that this group could serve as a valuable model for further genomic research to elucidate potential aspects of phenotypic plasticity and/or sympatric speciation in triatomines. Full article