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This paper presents a high-accuracy and robust multi-object tracking method for maritime vessel detection and tracking in complex marine environments, characterized by dense targets, large-scale variations, and frequent occlusions. The proposed approach adopts an enhanced YOLOv8-based detector with lightweight feature enhancement and attention mechanisms to improve its capability in detecting small-scale vessels and complex scenes. Furthermore, a tracking framework combining BOTSORT with an OSNet-based re-identification (ReID) model is employed to achieve stable and reliable vessel association. Experimental results on the Near-Infrared On-Shore (NIR) dataset demonstrate that the proposed method improves Precision, Recall, mAP@0.5, and mAP@0.5:0.95 by approximately 4.0%, 5.0%, 5.1%, and 5.4%, respectively, compared with the baseline YOLOv8, while reducing parameter count and model size by 11.6% and 6.5%. On the Visible On-Shore (VIS) dataset, the proposed method outperforms state-of-the-art approaches in detection accuracy and robustness, further validating its effectiveness and cross-modal generalization capability. In multi-object tracking tasks, the proposed CPM-YOLO and BOTSORT framework demonstrates clear advantages in trajectory continuity, occlusion handling, and identity preservation compared with mainstream tracking algorithms. On the NIR dataset, the proposed method achieves a competitive inference speed of 188 FPS, while running at 187 FPS on the VIS dataset, demonstrating that the accuracy improvements are achieved without sacrificing real-time performance. Overall, the proposed method achieves a favorable balance between detection accuracy, tracking robustness, and model efficiency, making it well-suited for practical maritime applications.

Background Increasing evidence suggests that human gut microbiome plays an important role in variation of skeletal muscle mass (SMM). However, specific causal mechanistic relationship of human gut microbiome with SMM remains largely unresolved. Understanding the causal mechanistic relationship may provide a basis for novel interventions for loss of SMM. This study investigated whether human gut microbiome has a causal effect on SMM among Chinese community‐dwelling healthy menopausal women. Methods Estimated SMM was derived from whole‐body dual‐energy X‐ray absorptiometry. We performed integrated analyses on whole‐genome sequencing, shotgun metagenomic sequencing, and serum short‐chain fatty acids (SCFAs), as well as available host SMM measurements among community‐dwelling healthy menopausal women (N = 482). We combined the results with summary statistics from genome‐wide association analyses for human gut microbiome (N = 952) and SMM traits (N = 28 330). As a prerequisite for causality, we used a computational protocol that was proposed to measure correlations among gut metagenome, metabolome, and the host trait to investigate the relationship between human gut microbiome and SMM. Causal inference methods were applied to assess the potential causal effects of gut microbial features on SMM, through one‐sample and two‐sample Mendelian randomization (MR) analyses, respectively. Results In metagenomic association analyses, the increased capacity for gut microbial synthesis of the SCFA butyrate was significantly associated with serum butyrate levels [Spearman correlation coefficient (SCC) = 0.13, P = 0.02] and skeletal muscle index (SCC = 0.084, P = 0.002). Of interest was the finding that two main butyrate‐producing bacterial species were both positively associated with the increased capacity for gut microbial synthesis of butyrate [Faecalibacterium prausnitzii (SCC = 0.25, P = 6.6 × 10−7) and Butyricimonas virosa (SCC = 0.15, P = 0.001)] and for skeletal muscle index [F. prausnitzii (SCC = 0.16, P = 6.2 × 10−4) and B. virosa (SCC = 0.17, P = 2.4 × 10−4)]. One‐sample MR results showed a causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.04, 95% confidence interval 0.029 to 0.051, P = 0.003). Two‐sample MR results further confirmed the causal effect between gut microbial synthesis of the SCFA butyrate and appendicular lean mass (β = 0.06, 95% confidence interval 0 to 0.13, P = 0.06). Conclusions Our results may help the future development of novel intervention approaches for preventing or alleviating loss of SMM.

How animals, particularly livestock, adapt to various climates and environments over short evolutionary time is of fundamental biological interest. Further, understanding the genetic mechanisms of adaptation in indigenous livestock populations is important for designing appropriate breeding programs to cope with the impacts of changing climate. Here, we conducted a comprehensive genomic analysis of diversity, interspecies introgression, and climate-mediated selective signatures in a global sample of sheep and their wild relatives. By examining 600K and 50K genome-wide single nucleotide polymorphism data from 3,447 samples representing 111 domestic sheep populations and 403 samples from all their seven wild relatives (argali, Asiatic mouflon, European mouflon, urial, snow sheep, bighorn, and thinhorn sheep), coupled with 88 whole-genome sequences, we detected clear signals of common introgression from wild relatives into sympatric domestic populations, thereby increasing their genomic diversities. The introgressions provided beneficial genetic variants in native populations, which were significantly associated with local climatic adaptation. We observed common introgression signals of alleles in olfactory-related genes (e.g., ADCY3 and TRPV1) and the PADI gene family including in particular PADI2, which is associated with antibacterial innate immunity. Further analyses of whole-genome sequences showed that the introgressed alleles in a specific region of PADI2 (chr2: 248,302,667–248,306,614) correlate with resistance to pneumonia. We conclude that wild introgression enhanced climatic adaptation and resistance to pneum

Abstract Previous studies revealed extensive genetic introgression between Ovis species, which affects genetic adaptation and morphological traits. However, the exact evolutionary scenarios underlying the hybridization between sheep and allopatric wild relatives remain unknown. To address this problem, we here integrate the reference genomes of several ovine and caprine species: domestic sheep, argali, bighorn sheep, snow sheep, and domestic goats. Additionally, we use 856 whole genomes representing 169 domestic sheep populations and their six wild relatives: Asiatic mouflon, urial, argali, snow sheep, thinhorn sheep, and bighorn sheep. We implement a comprehensive set of analyses to test introgression among these species. We infer that the argali lineage originated ∼3.08 to 3.35 Mya and hybridized with the ancestor of Pachyceriforms (e.g. bighorn sheep and snow sheep) at ∼1.56 Mya. Previous studies showed apparent introgression from North American Pachyceriforms into the Bashibai sheep, a Chinese native sheep breed, despite of their wide geographic separation. We show here that, in fact, the apparent introgression from the Pachyceriforms into Bashibai can be explained by the old introgression from Pachyceriforms into argali and subsequent recent introgression from argali into Bashibai. Our results illustrate the challenges of estimating complex introgression histories and provide an example of how indirect and direct introgression can be distinguished.

Global climate change has a significant effect on extreme environments and a profound influence on species survival. However, little is known of the genome-wide pattern of livestock adaptations to extreme environments over a short time frame following domestication. Sheep (Ovis aries) have become well adapted to a diverse range of agroecological zones, including certain extreme environments (e.g., plateaus and deserts), during their post-domestication (approximately 8–9 kya) migration and differentiation. Here, we generated whole-genome sequences from 77 native sheep, with an average effective sequencing depth of ∼5× for 75 samples and ∼42× for 2 samples. Comparative genomic analyses among sheep in contrasting environments, that is, plateau (>4,000 m above sea level) versus lowland (<100 m), high-altitude region (>1500 m) versus low-altitude region (<1300 m), desert (<10 mm average annual precipitation) versus highly humid region (>600 mm), and arid zone (<400 mm) versus humid zone (>400 mm), detected a novel set of candidate genes as well as pathways and GO categories that are putatively associated with hypoxia responses at high altitudes and water reabsorption in arid environments. In addition, candidate genes and GO terms functionally related to energy metabolism and body size variations were identified. This study offers novel insights into rapid genomic adaptations to extreme environments in sheep and other animals, and provides a valuable resource for future research on livestock breeding in response to climate change.

Although the gut microbiota has been reported to influence osteoporosis risk, the individual species involved, and underlying mechanisms, remain largely unknown. We performed integrative analyses in a Chinese cohort of peri-/post-menopausal women with metagenomics/targeted metabolomics/whole-genome sequencing to identify novel microbiome-related biomarkers for bone health. Bacteroides vulgatus was found to be negatively associated with bone mineral density (BMD), which was validated in US white people. Serum valeric acid (VA), a microbiota derived metabolite, was positively associated with BMD and causally downregulated by B. vulgatus . Ovariectomized mice fed B. vulgatus demonstrated increased bone resorption and poorer bone micro-structure, while those fed VA demonstrated reduced bone resorption and better bone micro-structure. VA suppressed RELA protein production (pro-inflammatory), and enhanced IL10 mRNA expression (anti-inflammatory), leading to suppressed maturation of osteoclast-like cells and enhanced maturation of osteoblasts in vitro. The findings suggest that B. vulgatus and VA may represent promising targets for osteoporosis prevention/treatment. Gut microbiota has been reported to influence osteoporosis risk, but the individual species, and underlying mechanisms, remain largely unknown. Here, the authors identify Bacteroides vulgatus and serum valeric acid as potential targets for osteoporosis prevention/treatment.

Haloxylon ammodendron , a keystone woody species, and its parasitic plant, Cistanche deserticola , play critical roles in sustaining arid ecosystems and supporting regional economies. However, their distribution is increasingly threatened by global climate change. Here, we propose a dual niche modeling framework that integrates climate and soil suitability layers using a multi-model ensemble approach combined with interpretable machine-learning techniques, specifically SHapley Additive exPlanations (SHAP). Using CMIP6 scenarios (SSP126, SSP245, and SSP585), we predicted the current and future potential habitats for both species. The results demonstrated that the ensemble models delivered robust performance, surpassing the accuracy of single-model predictions. Currently, suitable habitats are concentrated in northwestern China as well as parts of Mongolia and Kazakhstan. Under SSP585 (2081–2100), H. ammodendron habitats are projected to shrink by 56.2%, whereas C. deserticola is expected to lose more than 97% of its habitat, nearly disappearing from Central Asia. Key climatic drivers include temperature seasonality and precipitation patterns, whereas the soil water-holding capacity and gravel content significantly affect local suitability. Niche overlap analysis revealed a strong host dependency for C. deserticola. However, the climate–soil niche congruence is projected to decrease under future scenarios, indicating the potential risks of ecological decoupling. This integrative and interpretable approach offers a scalable tool for biodiversity assessment and provides actionable insights for conservation planning in climate-sensitive, arid ecosystems.

Following domestication, sheep (Ovis aries) have become essential farmed animals across the world through adaptation to a diverse range of environments and varied production systems. Climate-mediated selective pressure has shaped phenotypic variation and has left genetic “footprints” in the genome of breeds raised in different agroecological zones. Unlike numerous studies that have searched for evidence of selection using only population genetics data, here, we conducted an integrated coanalysis of environmental data with single nucleotide polymorphism (SNP) variation. By examining 49,034 SNPs from 32 old, autochthonous sheep breeds that are adapted to a spectrum of different regional climates, we identified 230 SNPs with evidence for selection that is likely due to climate-mediated pressure. Among them, 189 (82%) showed significant correlation (P ≤ 0.05) between allele frequency and climatic variables in a larger set of native populations from a worldwide range of geographic areas and climates. Gene ontology analysis of genes colocated with significant SNPs identified 17 candidates related to GTPase regulator and peptide receptor activities in the biological processes of energy metabolism and endocrine and autoimmune regulation. We also observed high linkage disequilibrium and significant extended haplotype homozygosity for the core haplotype TBC1D12-CH1 of TBC1D12. The global frequency distribution of the core haplotype and allele OAR22_18929579-A showed an apparent geographic pattern and significant (P ≤ 0.05) correlations with climatic variation. Our results imply that adaptations to local climates have shaped the spatial distribution of some variants that are candidates to underpin adaptive variation in sheep.

Tibetan sheep are the most common and widespread domesticated animals on the Qinghai–Tibetan Plateau (QTP) and have played an essential role in the permanent human occupation of this high-altitude region. However, the precise timing, route, and process of sheep pastoralism in the QTP region remain poorly established, and little is known about the underlying genomic changes that occurred during the process. Here, we investigate the genomic variation in Tibetan sheep using whole-genome sequences, single nucleotide polymorphism arrays, mitochondrial DNA, and Y-chromosomal variants in 986 samples throughout their distribution range. We detect strong signatures of selection in genes involved in the hypoxia and ultraviolet signaling pathways (e.g., HIF-1 pathway and HBB and MITF genes) and in genes associated with morphological traits such as horn size and shape (e.g., RXFP2). We identify clear signals of argali (Ovis ammon) introgression into sympatric Tibetan sheep, covering 5.23–5.79% of their genomes. The introgressed genomic regions are enriched in genes related to oxygen transportation system, sensory perception, and morphological phenotypes, in particular the genes HBB and RXFP2 with strong signs of adaptive introgression. The spatial distribution of genomic diversity and demographic reconstruction of the history of Tibetan sheep show a stepwise pattern of colonization with their initial spread onto the QTP from its northeastern part ∼3,100 years ago, followed by further southwest expansion to the central QTP ∼1,300 years ago. Together with archeological evidence, the date and route reveal the history of human expansions on the QTP by the Tang–Bo Ancient Road during the late Holocene. Our findings contribute to a depth understanding of early pastoralism and the local adaptation of Tibetan sheep as well as the late-Holocene human occupation of the QTP.

The ambitious targets for shipping emissions reduction and challenges for mechanism design call for new approaches to encourage decarbonization. Here we build a compound model chain to deconstruct global international shipping emissions to fine-scale trade flows and propose trade-linked indicators to measure shipping emissions efficiency. International maritime trade in 2018 contributes 746.2 Tg to shipping emissions of CO2, of which 17.2% is contributed from ten out of thousands of trade flows at the country level. We argue that potential unfairness exists if allocating shipping emissions responsibility to bilateral traders due to external beneficiaries. However, a huge shipping emissions-reduction potential could be expected by optimizing international trade patterns, with a maximum reaching 38% of the current total. Our comprehensive modelling system can serve as a benchmark tool to support the construction of a systematic solution and joint effort from the shipping industry and global trade network to address climate change.More than 80% of trade by volume occurs via maritime shipping, with growing pressure to reduce associated GHG emissions. The top 10 single-direction trade pairs account for nearly 20% of emissions; optimizing trade patterns could reduce emissions by 38% of current totals.