The intensification of urbanization has exacerbated the urban heat islands effect, potentially amplifying energy consumption and posing risks to thermal comfort and human health. Urban vegetation offers significant potential for mitigating extreme thermal events and reducing surface urban heat island effects. However, effective urban planning requires considering the interactions between vegetation and built structures, rather than solely focusing on green cover parameters. Considering this interaction and three-dimensional metrics, we applied a spatially explicit approach and linear mixed models to evaluate how the landscape structure impacts the climate regulation ecosystem services provision chain in São Paulo (Brazil), the largest metropolis in the Southern Hemisphere. While composition metrics, particularly total vegetation cover, are the primary factors explaining local climate regulation service supply, configuration metrics also significantly influence this service. Specifically, vegetation edge density positively impacted service supply, whereas building edge density had a negative effect. Additionally, arboreal volume and the interface between vegetated and built areas contributed to lowering land surface temperatures, suggesting that green spaces should be not only abundant but also strategically distributed in fragmented patches to maximize contact with built surfaces and enhance urban cooling. Furthermore, our analysis revealed spatial mismatches between service supply and demand, identifying high-risk areas where insufficient climate regulation could exacerbate health vulnerabilities during extreme events. These findings offer crucial insights for urban planners, highlighting the need to expand green areas and integrate them within built environments, especially in locations where supply does not meet local demand, in order to enhance adaptive capacity to heat. • Urbanization increases urban heat islands, but landscape structure role is unclear • Spatially evaluate climate regulation ecosystem service provision in São Paulo • Although vegetation cover effect is stronger, landscape configuration has a key role • Identified areas with climate regulation ecosystem service supply-demand mismatches • Provide key insights for public policies aiming to mitigate climate change effects

Regulating grain production-water purification trade-offs through landscape structure in a large-scale basin: insights from the pattern-process-service framework

1. Chilo sacchariphagus is a major sugarcane pest, primarily affecting producing regions in Asia and around the Indian Ocean, yet little is known about the biotic and abiotic factors driving its population dynamics and associated crop damage. This study assesses, for the first time, the relative influence of meteorological conditions, farming practices, landscape context, and natural enemy communities on herbivory damage caused by this pest on Reunion Island. 2. In-field surveys were conducted at 60 sampling points during 2022 and 2023, recording crop damage and multiple explanatory variables across spatial scales, from the field to the landscape. Data were analyzed using generalized additive models and a multi-model inference framework. 3. Crop damage was primarily explained by meteorological conditions (36 % of deviance), farming practices (36 %), and landscape context within a 250 m buffer (27 %) , while natural enemy abundance had no significant effect. Five key predictors shaped damage: average temperature during the wettest season, agrochemical inputs (fertilizer and herbicides), landscape edge density, and sugarcane proportion within the 250 m buffer. Lower fertilizer and herbicide use was associated with crop damage, while edge density and sugarcane proportion showed non-linear relationships with damage. 4. This study underscores the value of an integrative, cross-scale approach to identify drivers of crop damage by C. sacchariphagus . Findings suggest that reduced agrochemical inputs, coupled with increased landscape fragmentation and lower host crop dominance, may mitigate pest damage. Future work should further examine the role of natural enemies and explore the ecological mechanisms behind the non-linear impacts of landscape structure on pest dynamics. • Pest damage are shaped by farming practices, temperature, and landscape structure. • Lower fertilizer and herbicide use reduced crop damage. • Edge density and sugarcane proportion non-linearly affected crop damage. • Agroecological farming and landscape planning could help managing C. sacchariphagus • Multiscale approach effectively rank key factors that explain herbivory patterns

Empirical research on maladaptive daydreaming (MD), a clinically impairing form of compulsive immersive fantasy associated with attention dysregulation, emotional dysregulation and digital behavioural addictions, has expanded substantially over the past decade. Despite this growth, the intellectual structure, thematic evolution and collaborative networks of the MD literature indexed in the Web of Science Core Collection (WoSCC) remain unmapped. This bibliometric study aimed to characterise the intellectual landscape of WoSCC-indexed MD research between 2009 and 2025. A total of 141 publications were analysed using bibliometrix (R), VOSviewer and Python-based network analyses. The corpus accumulated 2187 citations with a mean of 15.5 citations per document and a field h-index of 26. Israel, the United States and Italy were the most productive countries. Four thematic clusters emerged: core MD phenomenology and dissociation; neurodevelopmental and attentional correlates; emotional dysregulation and pandemic-related psychopathology and digital behavioural addictions. Thematic evolution revealed a shift from phenomenological description toward multidimensional clinical investigation with increasing neurodevelopmental integration. Persistent gaps include longitudinal studies, randomized controlled trials and neurobiological investigations. These findings clarify the structure, thematic evolution and collaborative landscape of the Web of Science-indexed literature on MD and identify underdeveloped areas for future empirical work.

ATP-binding cassette (ABC) transporters are essential membrane proteins that couple ATP hydrolysis to move diverse substrates across lipid bilayers through large-scale conformational changes. In humans, 48 ABC transporters span seven subfamilies (A-G); within these, the ABCA subfamily mediates cellular lipid handling in contexts ranging from neural function to pulmonary surfactant production, and its dysfunction contributes to human disease from cardiovascular disorders to Alzheimer's. These diverse physiological roles all depend on precise lipid translocation within or across membrane systems, a shared principle that is often underemphasized in broad "lipid-transporter" classifications. This review summarizes the structural landscape of the ABCA family and re-examines the mechanistic insights that have emerged. We compare and contrast transport models derived from detergent-solubilized and lipid-embedded structures, with particular emphasis on lipid-embedded ABCA7, which supports a membrane-integrated mechanism in which the bilayer itself contributes to the transport pathway. We highlight shared rigid-body transitions, outline open questions surrounding transport directionality and protein-lipid coupling, and suggest that future models should treat the membrane not merely as a passive scaffold but as an integral component of the transport mechanism, while recognizing that membrane-integrated behavior is currently established structurally only for ABCA7 and remains a working hypothesis for other family members.

In the southwestern Brazilian Amazon, palm-dwelling triatomines maintain sylvatic transmission cycles of Trypanosoma cruzi, the causative agent of Chagas disease, and Trypanosoma rangeli, a related non-pathogenic parasite. Deforestation can reduce biodiversity and increase pathogen prevalence in triatomine populations; however, the effects of landscape structure on triatomine infection patterns remain poorly understood. Here, we address this knowledge gap by examining how forest cover and proximity to human dwellings influence triatomine infection patterns across gradients of deforestation. Field surveys were conducted in 2022 and 2024 in 20 landscape units in Cruzeiro do Sul, Acre state, Brazil, where triatomines were collected from palm trees located at varying distances from inhabited households. Distances and land-use composition were quantified from high-resolution drone and satellite imagery, while parasite infections were identified using molecular assays. Bayesian binomial mixed-effects models revealed contrasting responses between parasites. T. cruzi infection probability was higher in more deforested landscapes and was further modulated by palm-household distance, with the strongest effects observed for palms closer to dwellings. In contrast, T. rangeli infection showed no supported association with forest cover or distance to households. Blood meal analysis revealed frequent feeding on sylvatic hosts, particularly marsupials, and detected human blood in a nymph collected only 33 m from a household; T. cruzi infections detected in the study were exclusively assigned to TcI discrete typing unit, a lineage commonly associated with sylvatic transmission. These findings demonstrate that deforestation reshapes host-vector-parasite interactions in palm-based systems, increasing spillover risk at the sylvatic-human interface without requiring domiciliated triatomines.

East Asian Helicobacter pylori (H. pylori) strains are commonly classified as a single hspEAsia lineage characterized by elevated virulence. However, gastric cancer incidence varies markedly across China, suggesting that clinically relevant bacterial heterogeneity may exist within this framework. A systematic assessment of fine-scale population structure and its functional correlates in Chinese H. pylori remained limited. We analyzed whole-genome sequencing data from 1,243 H. pylori isolates collected from 20 provinces and regions across China, including 50 newly sequenced clinical strains from Shanghai. Fine-scale population structure was resolved using coancestry-based clustering and chromosome painting. Subpopulations were further characterized by pangenome composition, virulence factor repertoires, genome-wide fixation index (Fst), and predicted antibiotic resistance-associated mutations. E-test minimum inhibitory concentration (MIC) assays were performed to compare phenotypic susceptibility with mutation-based resistance prediction. Six geographically structured subpopulations were identified within Chinese hspEAsia. SubtypeCentral represented a widely distributed mainland lineage, whereas subpopulations from Inner Mongolia and Taiwan showed the greatest genetic divergence. Chromosome painting revealed strong within-lineage ancestry cohesion in SubtypeTaiwan, contrasted by extensive admixture in Inner Mongolia and Yunnan. Recurrent high-Fst loci across subpopulations, including glnA, frpB4, and HP1501, highlighted genomic regions contributing disproportionately to population differentiation. Marked heterogeneity in virulence profiles was observed. SubtypeInnerMongolia showed a higher prevalence of cagA-negative or Western-type cagA variants and a reduced overall repertoire of virulence genes. Predicted antibiotic resistance patterns were also strongly subtype dependent. Notably, SubtypeTaiwan exhibited an exceptionally high rifampicin resistance rate driven almost exclusively by a single rpoB A2414V mutation. E-test validation in the newly collected isolates provided supportive phenotypic evidence for the mutation-based resistance strategy. Chinese H. pylori hspEAsia strains comprise multiple regionally structured subpopulations with distinct evolutionary histories, gene content, virulence profiles, and predicted resistance determinants. This fine-scale genomic classification provides a biological basis for understanding regional disparities in gastric cancer risk and genotypic resistance, and supports the need for subtype-aware surveillance and region-specific clinical management strategies in China.

ABSTRACT This study presents the results of archaeological excavations conducted in November/December 2024 at the post-Roman (late fourth to fifth centuries AD) Cemeteries N1–N2 at Berenike, a major port on Egypt’s Red Sea coast. Research there seeks to reconstruct the spatial organisation, chronology and historical significance of these burial grounds and to reassess the role of indigenous Eastern Desert communities in the site’s later historical trajectory following the decline of Roman control. A detailed analysis of spatial relationships between chamber tombs and surrounding shaft graves reveals a socially structured mortuary landscape. Simultaneously, the consistent eastward orientation of tomb entrances and the intentional placement of graves to preserve visual connections with the post-Roman settlement indicate shared cultural principles governing mortuary location and perceptions of the landscape. By situating Cemeteries N1–N2 within broader regional and Red Sea contexts, this study demonstrates that the proliferation of new burial forms at Berenike coincided with significant political, demographic and economic transformations in the Eastern Desert. The findings highlight the growing archaeological visibility of indigenous communities and underscore their agency in transforming Berenike from a Roman-controlled emporium into a locally governed port integrated within Red Sea networks.

Rodents occupy a pivotal position at the interface of humans, animals, and the environment, making them a fundamental component of One Health frameworks. Both commensal and sylvatic rodent species act as reservoirs, amplifiers, and sentinels for a wide diversity of zoonotic pathogens, while simultaneously delivering key ecosystem services that influence biodiversity, nutrient cycling, and landscape structure. Spillover of pathogens between rodents, humans, livestock, and other wildlife occurs bidirectionally, enabling pathogen persistence, evolution, and emergence, particularly in rapidly changing socio-ecological systems. Invasive and synanthropic rodent species can profoundly disrupt ecosystems, contribute to biodiversity loss, and erode dilution effects that otherwise reduce disease transmission. At the same time, rodents serve as sensitive bioindicators of environmental contamination, antimicrobial resistance, and ecosystem degradation due to their close association with agriculture, waste streams, and human settlement. This narrative synthesis argues that rodents should be explicitly placed at the center of One Health programs, particularly within the scope of integrative zoology, which seeks to unify ecological, evolutionary, and health-related perspectives. Drawing on more than two decades of multidisciplinary research, largely from sub-Saharan Africa, this paper synthesizes current understanding of rodent ecology, pathogen diversity, and environmental change, while highlighting the RatZooMan project as an early exemplar of a rodent-focused One Health approach. We expand existing concepts, remove disciplinary silos, and identify future research directions that reconcile zoonotic disease prevention with ecosystem integrity and sustainable development.

Primary Ovarian Insufficiency (POI) is a highly heterogeneous condition characterized by the cessation of ovarian function before age 40. While genetic factors play a substantial role, the contribution of structural variants remains incompletely mapped. We conducted a systematic review and in silico genomic re-analysis of published copy number variations (CNVs) in individuals with POI. Following PRISMA guidelines, we aggregated 382 CNVs from 25 studies, standardized genomic coordinates, and filtered variants against population databases. Pathogenicity was re-evaluated using ACMG/ClinGen guidelines, yielding 42 pathogenic/likely pathogenic variants and 25 large CNVs (>3.5 Mb). Consistent with previous findings, the X chromosome exhibited the highest CNV burden, emphasizing its central role in structural genomic instability and POI pathogenesis. Beyond canonical POI-associated genes, gene ontology and GTEx expression profiling identified several biologically plausible, highly ovary-expressed candidate genes within disrupted loci-notably ATF3, GAS5, PPP4R1, and PRKAA1. Despite their established roles in cellular stress responses, DNA repair, and meiotic progression, these genes remain absent from most commercial POI diagnostic panels. This comprehensive re-analysis highlights the complex structural genomic landscape of POI and suggests that expanding current clinical testing panels to include these under-recognized genes could improve diagnostic yields for genetically unexplained cases.

This work analyses the convergence of a class of smoothing-based gradient descent methods when applied to optimization problems. Gaussian smoothing is employed to define a nonlocal gradient that reduces high-frequency noise, small variations, and rapid fluctuations in the computation of the descent directions while preserving the structure and features of the loss landscape. The resulting Gaussian smoothing gradient descent (GSmoothGD) approach can facilitate gradient descent in navigating away from and avoiding local minima with increased ease, thereby substantially enhancing its overall performance when applied to non-convex optimization problems. This work also provides rigorous theoretical error estimates on the rate of convergence of GSmoothGD iterates, which exemplifies the impact of underlying function convexity, smoothness, input dimension, and Gaussian smoothing radius. To combat the curse of dimensionality, we numerically approximate the GSmoothGD nonlocal gradient using Monte Carlo (MC) sampling and provide a theory in which the iterates converge regardless of the function smoothness and dimension. Finally, we present several strategies to update the smoothing parameter aimed at diminishing the impact of local minima, thereby rendering the attainment of global minima more achievable. Computational evidence complements the present theory and shows the effectiveness of the MC-GSmoothGD method compared to other numerical optimization approaches.

Artificial intelligence (AI) is rapidly transforming surgical practice, with applications spanning preoperative planning, intraoperative guidance, postoperative management, and surgical education. Despite accelerating research activity, the structure, thematic evolution, and funding landscape of AI research in general surgery remain incompletely characterized. This study aimed to systematically evaluate scientific production on AI in general surgery in the United States over the past 5 years using a bibliometric approach. A bibliometric analysis was conducted following Preliminary Guideline for Reporting Bibliometric Reviews of the Biomedical Literature and Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines using Web of Science. English-language articles published between 2020 and 2025 with a U.S.-affiliated senior author and focused on AI use in general surgery were included. Publications were analyzed across five primary domains: authorship metrics, thematic endpoints, journal characteristics, country of origin, and funding patterns. Bibliometric indicators included H-index, citation counts, Article Influence Score (AIS), and Bradford's Law classification. Funding distribution across endpoints was evaluated using chi-square or Fisher's exact tests, with effect sizes estimated using Cramér's V and odds ratios. Temporal trends in endpoints and keywords were assessed using Poisson and negative binomial regression models. Fifty-nine studies met inclusion criteria, comprising 20 reviews and 39 original investigations. Scientific production increased consistently from one study in 2019 to 17 in 2023 and 16 in 2024, demonstrating sustained growth. Surgical workflow recognition (n = 19) and clinical decision support (n = 18) were the predominant research domains, representing 63% of the included literature. Temporal analysis demonstrated significant annual growth in reviews (Incidence rate ratios [IRR] 2.09, P = .002) and workflow-focused studies (IRR 1.37, P = .031). Keyword analysis revealed sustained prominence of AI and machine learning, with limited emergence of new thematic directions. Most studies reported no funding (57.6%). Although overall funding distribution did not significantly differ across application categories (P = .846), clinically actionable AI applications were significantly more likely to receive funding compared with other research areas (OR 4.0, 95% CI 1.22-13.13; P = .029). AI research in U.S. general surgery is growing but remains concentrated in workflow and decision-support domains. Funding favors clinically actionable applications, highlighting the need for broader, equity-focused AI development.

The conformation-specific binding mechanism between zinc ions （Zn2+） and α-synuclein （α-Syn） plays a pivotal role in elucidating the molecular underpinnings of Parkinson's disease. α-Syn is an intrinsically disordered protein （IDP）， known for its structural plasticity and dynamic conformational landscape， which are intimately linked to its aggregation propensity and pathogenic potential. In this study， we employed native mass spectrometry （nMS） coupled with 193 nm ultraviolet photodissociation （UVPD） to investigate the α-Syn-Zn2+ interaction across different conformational states. This integrated approach enables both preservation of non-covalent interactions and detailed structural interrogation， offering unparalleled insights into IDP behavior upon metal binding. We identified three distinct charge-state-dependent conformational populations of α-Syn （low-charge， intermediate-charge， and high-charge conformations）， each exhibiting markedly different Zn2+ binding capacities and mechanisms. Experimental data revealed that the low-charge conformations exhibited the highest Zn2+ binding affinity and capacity， accommodating up to three Zn2+ ions. In contrast， the intermediate-charge conformations bound predominantly to one Zn2+ ion. The high-charge conformations， despite their extended structures， retained the ability to bind up to two Zn2+ ions， but with lower affinity. Quantitative analysis of UVPD-derived fragmentation yield changes （ΔFYs） provided residue-level insights into structural perturbations upon Zn2+ coordination. The most pronounced ΔFYs were observed in the low-charge conformers， indicating substantial Zn2+-induced structural stabilization or reorganization， particularly in the C-terminal （Cterm）. Distribution patterns of Zn2+-bound protein fragments （holo fragments） generated by UVPD further supported distinct fragmentation patterns for each conformational state， reflecting differential Zn2+ distribution and protection across the α-Syn sequence. Integrating ΔFYs analysis with holo fragment mapping， we propose three distinct binding mechanisms： （i） low-charge states stabilize Zn2+ binding primarily through electrostatic interactions involving acidic residues in the Cterm； （ii） intermediate-charge states form coordination bonds likely involving histidine or side-chain donors； and （iii） high-charge states exhibit a hybrid mechanism combining electrostatic and coordination elements， though with reduced spatial proximity and structural integrity. Overall， this work highlights the conformation-dependent nature of metal ion interactions in IDPs and underscores the potential of nMS-UVPD as a powerful tool for probing dynamic structural ensembles. These findings provide critical mechanistic insights that could inform the design of conformation-selective therapeutic agents aimed at modulating metal-induced α-Syn aggregation in Parkinson's disease.

INTRODUCTION Anthropogenic climate change is reshaping where plants can live. As temperature and precipitation patterns shift, many species are moving to stay within suitable environmental conditions. Predicting how these range shifts will affect future biodiversity requires knowing both where suitable habitats will occur and whether species can reach them. The latter is challenging because dispersal abilities differ widely among species and depend on landscape structure, anthropogenic barriers, and climatic conditions. Large-scale biodiversity forecasts therefore often rely on overly simple assumptions-such as no dispersal, unlimited dispersal, or identical movement rates for all species-thus adding major uncertainty to projections and conservation planning. RATIONALE We used the largest global database of observed plant range shifts (BioShifts; 14,488 records across 6579 plant species) to build models that predict species-specific range shift velocities. Combining 6.8 million plant occurrence records, an ensemble of two top-performing habitat models, and climate projections from 10 global circulation models, we mapped current and future suitable habitats-areas with favorable climate, soil, and land use-at 8 × 8 km resolution for each species. Our analysis covers 18% of known vascular plant species under four greenhouse-gas emissions scenarios for 2081 to 2100. We then overlaid the projected future suitable habitats with species-specific range shift velocities to determine where each species is likely to persist or expand by the end of this century. From these results, we estimated global extinction risks, changes in local species richness, and temporal species turnover in community composition. RESULTS Overall, 7 to 16% of modeled plant species are projected to lose >90% of their range across emissions scenarios, placing them at high risk of extinction. Most of these losses (70 to 80%) stem from suitable habitats disappearing as a result of climate change, rather than from dispersal limitations, indicating that climate-induced habitat loss, rather than an inability to keep pace with changing climate, is the primary threat. Although range shifts are unlikely to prevent many global extinctions, they will strongly reshape local species composition. Plant movements into newly suitable habitats are expected to increase local species richness across 28% of Earth's land surface, maintain latitudinally averaged species richness in the tropics and subtropics (35°S to 35°N), and generate substantial species turnover in mid-latitudes (30° to 50° in both hemispheres). By contrast, in regions north of 50°N, warming is so rapid that most plants cannot keep pace, leading to widespread local extirpations and sharp declines in species richness. CONCLUSION Range shifts can help sustain local species richness but are unlikely to provide much relief from global extinctions. To reduce extinction risks, identifying and protecting climate change refugia to safeguard biodiversity, and expanding ex situ conservation efforts, such as global seed bank and botanic garden networks, may be more effective than facilitating migrations. At the same time, conservation strategies should anticipate changing community compositions and ecosystem functioning as new species arrive and ecosystems reorganize. In high-latitude regions where dispersal lags considerably behind the rapid warming, improving habitat connectivity, reducing human-made barriers, and where appropriate, assisting species movement could help maintain local species richness, ecosystem productivity, carbon sequestration, and ecosystem stability. [Figure: see text].

Yanyun (YY) sheep are a composite breed developed by targeted crossbreeding of Dorper, Hu, and East Friesian sheep to improve growth, reproduction, and environmental adaptability, yet the genomic basis underlying their formation and selective improvement remains unclear. Whole-genome analyses showed that YY sheep retain moderate genetic diversity with low genomic inbreeding (FROH), indicating limited autozygosity. Population structure analyses supported that YY sheep form a genetically distinct yet admixed group consistent with their breeding history. Genome-wide selection scans identified multiple candidate regions associated with growth, metabolism, reproduction, immune function, and environmental adaptability, including loci showing consistent differentiation and haplotype-based selection signals across multiple population comparisons. These results provide a genome-wide view of the genetic diversity, population structure, and selection landscape of YY sheep, and identify candidate genomic regions for future investigation of economically important and adaptive traits in composite sheep breeding.

High-diversity ecosystems are often presumed to be resilient. Yet, marine caves, along with other high-diversity systems, have proved highly sensitive to both climate change and anthropogenic stressors. This study seeks to resolve the underlying causes of this apparent paradox by investigating the functional resilience of marine caves ecosystems. We investigated nine Atlantic marine caves to identify key environmental drivers at landscape, local, and within-cave scales of sessile community structure and assess their functional resilience. Using hierarchical sampling (414 photoquadrats, 126 taxa), biological trait analysis (six traits), and statistical modelling (RLQ-Fourth Corner, GLMs, GAMMs), we assessed trait-environment relationships. Wave energy was the dominant driver among seascape and local-scale factors, explaining 34.5% of trait-environment associations, followed by depth range (7.7%). Four functional syndromes reflected major ecological trade-offs, such as autotrophs vs. active sponge feeders. Despite high regional taxonomic diversity (Shannon H'=3.6) and functional richness (1.93), 57% of functional entities were represented by single taxa revealing low functional redundancy and thus low resilience potential. Functional vulnerability decreased and redundancy increased with spatial scale, with semi-dark zones being the most vulnerable cave sector (81%). Overall, wave exposure and depth shaped functional structure and resilience potential at a seascape scale in marine caves. The decoupling between taxonomic diversity and functional redundancy suggests that this vulnerability paradox may be a common pattern in high-diversity systems, as demonstrated in coral reefs and tropical forests, partially explaining their unexpected fragility under global change.

2-Arylbenzo-[f]-coumarins represent an underexplored class of extended conjugated systems with remarkable potential in optoelectronics and biomedical research. In this study, we unveil how subtle substituent variations (-H, -OMe, -CH3, -NHAc, -Ph, and extended N-aryl groups) at the 2-position dramatically reshape the structural, vibrational, and photophysical landscapes of benzo[f]coumarins. Single-crystal X-ray diffraction reveals substituent-controlled torsional twists that dictate molecular packing and supramolecular interactions. Vibrational fingerprints, probed by FTIR, Raman spectroscopy, and validated by DFT, show distinct shifts in key marker bands, offering a sensitive handle to track electronic perturbations. Striking photophysical modulations emerge, with unusual emission shifts and biexponential lifetimes pointing to multiple emissive states. Beyond fundamental insights, these molecular nuances translate into function-BC-H and BC-OMe display promising antimicrobial activity against S. aureus and C. albicans, opening avenues toward bioimaging and theranostic applications. By bridging structure-vibration-photophysics-function correlations, this work provides a compelling blueprint for the rational design of next-generation coumarin-based materials with tunable performance.

Landscape fragmentation drives rice heavy-metal health risk and reveals actionable thresholds.

CryoEM structural analysis of a thermophilic galactooligosaccharides-producer β-galactosidase unravels an uncommon oligomeric structure.

Copy number variations (CNVs) are a major source of structural genomic diversity that influences adaptation, reproduction, and production traits in livestock. The Black Bengal goat, an economically important Indian breed known for its high fecundity, superior skin quality, and resilience to humid tropical climates, was studied to uncover its structural genomic landscape. We performed whole-genome CNV analysis using high-depth (10×) sequencing data from eight individuals. A total of 31,816 copy number variants (CNVs) were identified, predominantly duplications, with an average length of approximately 45 kb. These CNVs were combined into 8910 copy number variation regions (CNVRs) covering approximately 0.15 Gb (about 5.3% of the autosomal genome). CNVR hotspots were mainly located on chromosome 1. Gene annotation showed that regions overlapping with CNVs and CNVRs contained more than 1987 protein-coding genes involved in pathways related to immunity, reproduction, metabolism, and extracellular matrix (ECM) organization. The presence of CNVs involving genes such as GDF9 and BMPR1B on chromosomes 7 & 6, respectively, is important because it indicates that the breed has a high reproductive capacity due to dosage-sensitive duplications. Changes in the extracellular matrix and increased dermal strength have been linked to duplications of genes such as COL6A1, LAMC2, LAMB3, FMN1, and CLDN1. This helps explain the superior hide quality of the breed. This research offers a comprehensive map of CNVs and CNVRs within the genome of the Black Bengal goat. It demonstrates how these duplications lead to structural changes that enhance both reproductive performance and skin resilience. These findings provide a valuable genomic resource for future marker-assisted selection, comparative genomics, and conservation breeding programs aimed at preserving indigenous goat populations.