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PubMed2026

Impact of neoprene wetsuits on lung volumes and work of breathing: implications for military diver safety and performance.

INTRODUCTION: Neoprene wetsuits may impose mechanical constraints on the chest wall, potentially altering respiratory function. This study investigated the impact of neoprene wetsuits on lung volumes, airway mechanics, and work of breathing (WOB) in healthy male divers. METHODS: A randomised crossover trial was conducted with 31 male divers at the Royal Netherlands Navy Diving Medical Centre. Participants underwent pulmonary function testing, including spirometry, body plethysmography, the forced oscillation technique (FOT), and diffusion capacity measurements, both with and without a hoodless standardised 5 mm neoprene full body wetsuit with a neoprene neck seal. Primary outcomes included changes in forced vital capacity (FVC), functional residual capacity (FRC), airway resistance (Raw), reactance (Xrs), and WOB. RESULTS: Wearing a neoprene wetsuit led to statistically significant reductions in FVC (2.8%, P < 0.05), forced expiration in one second (2.9%, P < 0.05), FRC (4.0%, P < 0.05), and expiratory reserve volume (10.9%, P < 0.05), alongside increases in inspiratory capacity and tidal volume. Raw increased significantly (P < 0.05), while the FOT revealed altered airway mechanics, evidenced by increased Xrs at multiple frequencies (P < 0.05). Diffusion capacity remained unchanged, suggesting preserved alveolar-capillary function. CONCLUSIONS: Neoprene wetsuits induce mechanically restrictive effects on the chest wall, reducing static and dynamic lung volumes and increasing WOB. While these changes may not be clinically relevant at rest, their impact needs to be determined during strenuous or prolonged dives, particularly when combined with other equipment that limits thorax excursions. Future research should explore the effects of the military 5 mm wetsuit under immersed conditions to better understand their operational impact on diver performance and safety.

Male↗
PubMed2026

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals↗
PubMed2026

Genome-wide scans reveal candidate genes associated with wing morph differentiation in Tetrix japonica.

Wing dimorphism is an important dispersal-related trait in insects, but its genomic basis remains poorly understood in pygmy grasshoppers. Here, we integrated genome-wide single-nucleotide polymorphism (SNP) analyses, population structure inference, selection scans, and functional annotation to investigate genomic differentiation between long- and short-winged Tetrix japonica. Principal component analysis (PCA), ADMIXTURE, and phylogenetic analyses revealed weak genome-wide separation between morphs, indicating differentiation on a largely shared genetic background. Genome-wide scans based on the fixation index (FST), nucleotide diversity ratios, and Tajima's D, using 50-kb non-overlapping windows and empirical top-5% outlier thresholds, identified multiple candidate regions across seven chromosomes. The broader long- and short-winged candidate sets spanned 9.35&#xa0;Mb and 9.37&#xa0;Mb and directly overlapped 82 and 77 genes, respectively. Candidate genes were associated with signaling/hormone regulation, membrane transport, metabolism, cytoskeletal organization, extracellular matrix structure, and development. Short-winged candidate genes were significantly enriched for ABC-type transporter activity and ATP hydrolysis activity. Because all individuals originated from a single laboratory-maintained population with weak genome-wide structure, these regions should be regarded as candidate loci from a screening-stage analysis that require validation in independent populations and by functional assays, rather than as confirmed targets of selection.

Animals↗
PubMed2026

Analyzing salinity tolerance in grass carp (Ctenopharyngodon idella): Insights from genome-wide association study and genomic selection.

Grass carp (Ctenopharyngodon idella) is one of the most widely cultured freshwater fish species globally. However, the expansion of its farming scale faces severe limitation owing to freshwater scarcity; therefore, the development of strains with greater salinity tolerance is key for expanding production using brackish water resources. To investigate the genetic basis of salinity tolerance in grass carp, a genome-wide association study (GWAS) was conducted using 200 individuals representing extreme phenotypes, namely salinity-tolerant and salinity-sensitive groups. In total, 17 single nucleotide polymorphisms (SNPs) related to salinity tolerance were detected, which were distributed across 11 chromosomes. Through gene annotation, 38 candidate genes were obtained from these loci. Enrichment analysis revealed these candidate genes are primarily implicated in key biological processes, including osmotic regulation, energy metabolism, and stress responses. Analyses of different SNP densities revealed that the 5&#xa0;K SNP density panel can balance prediction accuracy and computational efficiency. The BayesA model achieved the highest prediction accuracy under the GWAS_Evenly selection strategy, with substantial reductions in mean absolute error and mean square error. This study reveals the genetic mechanisms of salinity tolerance in grass carp, which might be optimized through genomic selection, and provides insights for selectively breeding new varieties with greater salinity tolerance.

Animals↗
PubMed2026

Genomic characterization and pathogenicity of ruminant Listeria monocytogenes isolates in a murine oral infection model.

Listeria monocytogenes is a major foodborne pathogen; its ruminant isolates display zoonotic characteristics, causing similar clinical signs in humans, including abortion and encephalitis. However, data on whole genome sequencing and pathogenicity of ruminant L. monocytogenes isolates remain sparse. This study aimed to analyze the genotypic characteristics of L. monocytogenes isolates from ruminants with listeriosis. Furthermore, we assessed the in vivo pathogenicity of four ruminant L. monocytogenes isolates, characterized via whole-genome sequencing-based genetic clustering, in orogastrically inoculated mice. The isolate LM18 (serotype 1/2b, ST224, SL6178) had the lowest lethal dose compared to the other three isolates including previous hypervirulence type (serotype 4b, ST1, SL1) and caused secondary bacteremia in lungs, with sustained bacterial loads in the spleen and liver. Genomic (listeria pathogenicity island -1 and -3) and virulence gene (actA and llsX) mutation analyses associated with virulence suggested from well-recognized studies could not elucidate the virulence of the isolates. SSI-1, which only exists in the isolate LM18 (serotype 1/2b, ST224, SL6178), may help L. monocytogenes survive in the gastrointestinal environment, thereby affecting its virulence. Further research should investigate the role of SSI-1 in the pathogenicity of L. monocytogenes. Moreover, additional studies utilizing larger datasets of ruminant isolates are required to validate our genotypic characterization and to obtain a comprehensive picture of further genotypic differences crucial for L. monocytogenes pathogenicity.

Animals↗
PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗
PubMed2026

Complete mitochondrial genomes of eight cyclophyllidean tapeworms: genome pattern and phylogenetic analysis.

Cyclophyllidean tapeworms are widespread parasites of significant medical and veterinary importance. However, mitochondrial (mt) genomic resources for cyclophyllideans from China, particularly those recovered from wildlife hosts, remain comparatively limited. In this study, we sequenced and characterized the complete mt genomes of eight cyclophyllidean isolates collected from diverse wild and domestic hosts in China, including two Hymenolepis sp. isolates and two Raillietina sp. isolates from China, and four additional isolates of previously sequenced Taenia species. The circular mt genomes ranged from 13,387 to 14,021&#xa0;bp in length, encoding 36 typical genes with variable non-coding regions. Comparative analysis revealed highly conserved gene composition and mostly conserved mt architecture, with localized rearrangement patterns detected among the cyclophyllidean lineages examined. In particular, all sampled Taeniidae exhibited a consistent trnL1-trnS2 arrangement, whereas the examined non-Taeniidae families showed the trnS2-trnL1 arrangement, confirming and extending, across additional wildlife-associated isolates, a previously proposed family-associated gene-order marker within Cyclophyllidea. Phylogenetic analyses based on concatenated amino acid sequences of the 12 protein-coding genes placed the eight isolates within their expected families, in topologies broadly consistent with previous mitogenomic studies. These data provide additional Chinese mitogenomic references, especially for underrepresented wildlife-associated isolates, and support family-associated gene-order patterns in Cyclophyllidea.

Animals↗
PubMed2026

Assembly and Characterization of the First Complete Mitochondrial Genome of Tussilago farfara L.: Insights into Biological Functions and Phylogenetic Relationships within the Asteraceae Family.

Tussilago farfara L., a member of the Asteraceae family, is an economically valuable species due to its edible and medicinal properties. To elucidate the structural characteristics, genetic mechanisms, and evolutionary pathways of the organelle genomes of T. farfara, we sequenced, assembled, and annotated its mitochondrial genome for the first time. The complete mitochondrial genome of T. farfara spans 306,024&#xa0;bp and contains 33 mitochondrial protein-coding genes (PCGs), 3 rRNAs, and 22 tRNAs. Analysis of the nucleotide substitution rate and genetic diversity revealed that most mitochondrial genome genes may have undergone purifying selection, indicating a slow evolutionary rate and a relatively conserved genomic structure. We further identified 13 fragments of chloroplast-derived DNA integrated into the mitochondrial genome, evidencing intracellular gene transfer. Collinearity analysis showed that Arctium lappa shares the most extensive mitochondrial homologous sequences and the highest sequence similarity with T. farfara. Phylogenetic analysis based on the mitochondrial genome helped to clarify the evolutionary and taxonomic position of T. farfara within the Asteraceae family. The mitochondrial genome sequence of T. farfara provides a valuable genomic resource for species identification and for evolutionary studies within the Asteraceae family.

Genome, Mitochondrial↗
PubMed2026

Divergent trajectories of genome architecture and chromosome evolution in ferns and angiosperms.

Ferns and angiosperms represent the two largest vascular plant lineages but exhibit striking genomic and ecological contrasts. We investigated whether differences in genome size, chromosome architecture, GC content, and stomatal traits reveal divergent evolutionary trajectories between these lineages. We assembled the most comprehensive dataset to date, integrating genome size, chromosome number and size, GC content, and stomatal traits for over 1100 fern species and compared it with an extensive angiosperm dataset. Ferns exhibited markedly lower variability and c. 16-fold slower rates of chromosome size evolution than angiosperms. A persistent positive relationship between genome size and chromosome number in ferns suggests limited cytological post-polyploid diploidization. While ferns generally possess larger stomata, this difference disappears after accounting for genome size, indicating that nucleotypic constraints, rather than lineage-specific physiology, dictate stomatal dimensions. Both groups share a unimodal GC-genome size relationship peaking at c. 14 Gbp. Larger fern chromosomes imply lower genome-wide recombination rates, potentially limiting genetic reshuffling and adaptive potential. Our results highlight fundamentally divergent evolutionary trajectories, likely shaped by meiotic symmetry in ferns and meiotic asymmetry, possibly centromere drive, and post-polyploid diploidization in angiosperms, defining the functional and genomic landscapes of these lineages across deep evolutionary timescales.

Genome, Plant↗
PubMed2026

Plant species identification by genome skimming across the vascular plant tree of life.

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing <&#x2009;25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (<&#x2009;25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

DNA Barcoding, Taxonomic↗
PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗
PubMed2026

Mitochondrial dysfunction in muscle cells induced by snoring vibrations.

Snoring-related vibrations have been proposed as a pathogenic factor contributing to upper airway muscle dysfunction in patients with obstructive sleep apnea (OSA). To investigate whether exposure to snoring vibration is linked to muscle weakness, we used an in vitro vibration model to examine its effects on mitochondrial homeostasis in L6 muscle cells at 8, 12, 24, and 48&#xa0;h. The findings were then compared with mitochondrial alterations in the upper airway muscles from snorers and patients with OSA. Proteomic analysis of L6 myoblasts revealed extensive remodeling of the mitochondrial proteome at 8&#xa0;h, affecting pathways involved in oxidative phosphorylation, protein import, ribosome biogenesis, and RNA processing. Respiratory chain remodeling was subunit-specific, with increased abundance of selected components of Complexes I, IV, and V, including NDUFS4, COX5A, and ATP5PD. However, reductions in spliceosome-associated factors, such as SRSF2 and DDX46, along with alterations in mitochondrial ribosomal proteins, indicated impaired RNA processing and protein synthesis. Furthermore, both proteomic and transcriptomic analyses revealed activation of a mechanosensing-mechanotransduction axis, with early upregulation of integrin subunits and mechanosensitive ion channels, followed by transient activation of focal adhesion signaling. Despite transcriptional upregulation of selected Complex IV subunits Cox5a and Cox6a2, this response was accompanied by accumulation of unspliced pre-mRNA, indicating impaired RNA processing efficiency and a decoupling between transcript and protein levels. Real-time Seahorse assay revealed a collapse of mitochondrial respiration and glycolytic reserve at 8&#xa0;h. Although mitochondrial oxygen consumption recovered after 48&#xa0;h, the ability to dynamically upregulate glycolysis remained impaired. In patients, muscle capillarization was impaired, COX activity was reduced, and mitochondrial organization was disrupted. Moreover, transcription of Complex IV subunits COX5A and COX6A2 was, as in vibrated L6 cells, upregulated, suggesting a mismatch between transcript levels and protein expression. We conclude that snoring-induced vibrations are an unrecognized stressor that disrupts mitochondrial homeostasis in muscle by impairing RNA processing, protein synthesis, and mechanotransduction-driven mitochondrial remodeling, leading to transcript-protein uncoupling and likely muscle dysfunction.

Humans↗
PubMed2026

Comparative genomic epidemiology of food- and patient-derived diarrheagenic Escherichia coli from sentinel surveillance in Southeast China.

Diarrheagenic Escherichia coli (DEC) remains an important foodborne pathogen, yet long-term comparative genomic surveillance data jointly characterizing food-derived and patient-derived isolates remain limited. This surveillance-based comparative study integrated antimicrobial susceptibility testing and whole-genome sequencing to characterize diarrheagenic Escherichia coli isolates recovered from food and patient sources in Lishui, Southeast China, during 2018-2025, with emphasis on occurrence, resistance profiles, genomic backgrounds, and plasmid replicon-associated features. Antimicrobial susceptibility testing was performed for 258 selected isolates, and whole-genome sequencing was conducted for a curated analytical subset of 204 isolates. The sequenced subset was used for diversity-oriented comparative genomic analysis rather than for unbiased prevalence estimation of the entire DEC collection. EAEC predominated in both sources, although food-associated occurrence was heterogeneous across categories, with the highest recovery rate observed in raw meat. Patient-derived isolates showed a broader overall resistance burden, whereas food-derived isolates retained substantial resistance to tetracycline, chloramphenicol, and florfenicol. Phylogenetic analysis showed partial overlap in genomic backgrounds between food-derived and patient-derived isolates, while representative resistance determinants displayed both broadly distributed and lineage-enriched patterns. Replicon-based plasmid profiling identified 42 plasmid types, including 12 detected in both sources, with IncF-related replicons predominating among these shared profiles. Several food-derived isolates carried multiple plasmid replicon types that were also observed in patient-derived isolates. Overall, food-derived and patient-derived DEC showed partial overlap in genomic backgrounds, resistance determinants, and replicon-defined plasmid profiles within this surveillance setting, while retaining source-associated heterogeneity. These findings should be interpreted as surveillance-based comparative evidence rather than as evidence of direct source attribution or transmission.

Humans↗
PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

Humans↗
PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗