SEARCH · Search PubMed

Results for “exome sequencing”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

316 records · Page 6Linked to original sources

PubMed2026

Comparative analysis of gut microbiota in yaks under different feeding management strategies during cold seasons.

Yaks (Bos grunniens) are crucial for the livelihoods of pastoral communities in cold regions, where feed scarcity during the cold season poses challenges to their health and productivity, underscoring the necessity of understanding how dietary management influences the gut microbiota. In this study, 24 yak steers matched for body weight and health status were randomly allocated to four groups: natural grazing or indoor feeding with roughage-to-concentrate ratios of 50:50, 70:30, or 90:10. Fecal samples were collected for 16S rDNA sequencing and subsequent functional prediction of the microbiota. The results showed that Firmicutes and Bacteroidetes were the dominant phyla across all groups, and UCG-005 and Rikenellaceae_RC9_gut_group were the predominant genera. Concentrate supplementation during the cold season significantly enhanced microbial richness and diversity, with the 70:30 ratio exerting the most pronounced beneficial effects on microbiota structure and key taxa enrichment. These findings highlight the critical role of dietary management in shaping the yak gut microbiota during cold seasons and suggest that the 70:30 ratio optimally improves microbial community structure, thereby promoting yak health and productivity under harsh climatic conditions. Future research should explore the long-term implications of such dietary strategies.

Animals↗

PubMed2026

Tigecycline-resistant Staphylococcus in waiting pens of a pig slaughterhouse: genomic insights into a food safety alert.

BACKGROUND: The waiting pens of slaughterhouses represent a critical control point in the 'farm-to-fork' continuum, yet their role in the emergence and dissemination of antimicrobial resistance remains understudied. This study investigated tigecycline-resistant Staphylococcus (TRS) in these high-risk zones to assess their prevalence, resistance mechanisms, and transmission dynamics. METHODS: 400 samples were collected from the waiting pens of a pig slaughterhouse in Guangzhou, China. Antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, and molecular cloning were employed to characterize resistance mechanisms and transmission patterns. RESULTS: 78 TRS strains were isolated and classified into three species, including S. borealis, S. ureilyticus, and S. pasteuri. These isolates exhibited multidrug-resistant phenotypes and carried new mutations in rpsJ and tet(M), which were functionally confirmed to reduce tigecycline susceptibility. Phylogenetic evidence demonstrated clonal transmission between pig farms and the slaughterhouse. The tet(M) gene was located within Staphylococcal cassette chromosome mec elements mediated by IS257, while tet(L) was carried by plasmids formed through IS256/IS257-mediated recombination. CONCLUSIONS: Waiting pens serve as crucial reservoirs for the amplification and dissemination of antimicrobial resistance. Our findings underscore the urgent need for enhanced biosecurity measures, improved waste management, and routine molecular surveillance in these high-risk zones to mitigate the spread of resistance along the food production chain.

Animals↗

PubMed2026

Single-cell transcriptomics reveals heterogeneous stress responses and Mg2+-mediated survival mechanisms in Lactobacillus delbrueckii subsp. bulgaricus during freeze-drying and storage.

Maintaining the viability of lactic acid bacteria during dehydration and subsequent storage remains a significant challenge. Here, we employed single-cell RNA sequencing to reveal the heterogeneous stress responses of Lactobacillus delbrueckii subsp. bulgaricus, identifying seven distinct transcriptional clusters across the liquid culture, freeze-drying, and storage phases. The dominant clusters in the freeze-drying and storage were not completely consistent, showing significant functional differentiation. Genomic stability may be important for survival during freeze-drying and storage, while intracellular energy homeostasis appears important for viability during storage. The magnesium transporter mgtB was highly expressed in clusters tolerant to freeze-drying and storage, suggesting a critical role for Mg2+ homeostasis. Further experimental validation confirmed that Mg2+ treatment significantly bolstered stress resistance, increasing immediate post-freeze-drying survival by over 2-fold (up to 92.90%) and post-storage survival by over 5-fold (up to 5.98%). Proteomic data indicated that Mg2+ supplementation correlated with the maintenance of several biological functions potentially relevant to bacterial survival during freeze-drying and storage, including DNA repair, translation, and central carbon metabolism. These findings provide a map of microbial stress resistance through population heterogeneity and offer a potential strategy that may be adapted for enhancing the stability of other industrial lactic acid bacteria products.

Freeze Drying↗

PubMed2026

Integrating genomic distance analyses in the description of a new family, genus, and species of sponge-associated antipatharians (black corals).

Antipatharians (black corals) are among the least studied coral groups, with much of their diversity still undescribed. Here, we present an integrative morphological, phylogenomic and genomic distance study of deep-sea antipatharians sampled in high seas areas of the North Pacific Ocean and from New Zealand's Exclusive Economic Zone. These corals grow on hexactinellid sponges - a unique characteristic in the order Antipatharia. Using a dataset of ultra-conserved elements and exons, combined with morphological analyses, we reconstruct phylogenomic relationships and formally describe a new family (Eidikopathidae fam. nov.), a new genus (Eidikopathesgen. nov.), and two new species (E. korallispongiasp. nov., E. zealandkoralliasp. nov.). Morphologically, the new family is distinguished by a corallum consisting of a network of loose branches that fuse with the sponge skeletal framework. Phylogenomic analyses recovered consistent topologies with strong nodal support, corroborating the distinct evolutionary placement of this sponge-associated lineage. Pairwise genomic distances estimated using the Tamura-Nei model were concordant with patristic genomic distances, identifying Pteridopathidae as the genetically closest family to Eidikopathidae fam. nov., followed by Myriopathidae and Stylopathidae, which were recovered as sister families in the phylogeny. This pattern shows that genomic distance complements, rather than simply mirrors, tree topology by quantifying accumulated sequence divergence among lineages. Together, these results provide the first genomic distance framework for Antipatharia, offering a baseline for future systematic, evolutionary, and biodiversity studies on this fundamental shallow, mesophotic and deep-sea coral group.

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 (ΔAUC = +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

Identification of elements determining KIR gene demethylation at the CD56-bright stage of NK cell development.

The variegated expression of the KIR family of class I MHC receptors generates specialized natural killer (NK) cells capable of allele-specific HLA recognition. Understanding the mechanism of KIR gene activation will lead to improved methods for the generation of fully functional NK cells. A central RUNX-binding site in the KIR proximal promoter is required for gene activation. RUNX proteins recruit ten-eleven translocation (TET) proteins that generate 5-hydroxymethylcytosine (5hmC) and drive DNA demethylation. Assessment of 5-methylcytosine (5mC) and 5hmC residues at four stages of NK cell development reveals deposition of 5hmC primarily in a CREB site next to the RUNX site at the CD56Bright stage but not the subsequent CD56Dim stage representing fully mature NK cells. KIR promoter demethylation is delayed relative to other lineage-associated genes, indicating a high threshold for KIR gene demethylation in developing NK cells, and a window of opportunity for RUNX/TET-dependent KIR gene activation in CD56Bright NK cells.

6-base sequencing↗

PubMed2026

ChIP-seq profiling identifies diapause-regulated H3K27me3 targets in the fat body of Culex pipiens.

Culex pipiens, a principal vector of significant arboviruses, survives winter through diapause, a hormonally controlled inactive phase that enhances endurance under severe cold circumstances. Recent data suggests that epigenetic processes, namely histone post-translational modifications (hPTMs), play a crucial role in regulating seasonal dormancy. Prior studies from our laboratory indicated a decrease in the methylation of Histone 3 (H3K27me3) in diapausing fat body tissue, associated with elevated expression of the histone demethylase UTX. Nonetheless, the precise genomic areas impacted by these chromatin alterations remained unidentified. We used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) to delineate the genome-wide distribution of H3K27me3 across fat body chromatin in diapausing (D) and non-diapausing (ND) female Cx. pipiens. Notably, the higher signal at transcription start sites (TSSs) reflects localized redistribution rather than a global decrease, as diapausing fat bodies retain less H3K27me3 overall but concentrate it at promoters. To investigate the functional significance of these chromatin alterations, we confirmed a number of target loci via ChIP-qPCR and assessed gene expression with qRT-PCR. We identified many critical genes that were markedly increased in diapausing mosquitoes, exhibiting an inverse relation to H3K27me3 enrichment. Our data demonstrates different H3K27me3 chromatin landscapes between diapausing and non-diapausing Cx. pipiens, corroborating a hypothesis of selective, locus-specific repression in the non-diapause state and its targeted removal during diapause to permit activation of dormancy-associated genes. These results suggest that chromatin remodeling is a core driver of the diapause switch.

Animals↗

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↗

PubMed2026

Dynamic evolution of chaperone-mediated autophagy is associated with tumor microenvironment remodeling and prognostic stratification in lung adenocarcinoma: insights from single-cell transcriptomics, ensemble machine learning, and experimental validation.

BACKGROUND: Lung adenocarcinoma (LUAD) shows prognostic heterogeneity, and tumor-node-metastasis (TNM) staging is limited for individualized management. Chaperone-mediated autophagy (CMA) maintains proteostasis, but its role during adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA)-invasive adenocarcinoma (IAC) progression remains unclear. METHODS: Single-cell RNA sequencing (scRNA-seq) data from GSE189357 and bulk transcriptomes from The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus (GEO) cohorts were integrated. CMA activity, cell-cell communication, weighted gene co-expression network analysis (WGCNA), tumor-normal differential expression, machine-learning survival modeling, tumor microenvironment (TME) features, drug sensitivity, and EPC1 function were analyzed. RESULTS: CMA-high tumor epithelial cells increased from AIS (58.1%) to MIA (65.7%) but declined in IAC (44.4%; p < 0.001). CMA-low cells preferentially received fibroblast-derived extracellular matrix cues. A CMA-negatively correlated module identified 69 core genes. Random survival forest (RSF) performed best among 117 machine-learning combinations (mean concordance index > 0.873). High-risk patients had worse survival across cohorts, and the risk score was independently associated with overall survival (hazard ratio = 16.013, 95% confidence interval: 9.579-26.768, p < 0.001). High-risk tumors showed proliferative activation and M0 macrophage enrichment, whereas low-risk tumors showed stronger immune-related signaling. EPC1 overexpression suppressed malignant phenotypes in A549 cells. CONCLUSION: CMA dynamics are associated with stromal and immune remodeling during LUAD progression. A CMA-based model provides robust prognostic stratification and may offer a basis for future TME-guided studies.

Chaperone-mediated autophagy↗

PubMed2026

Efficacy of the NMIC-150 system in identifying extended-spectrum beta-lactamases in clinical isolates.

Extended-spectrum beta-lactamases (ESBLs) are significant contributors to the growing global crisis of antimicrobial resistance. This study evaluated the performance of the NMIC-150 System for susceptibility testing of third-generation cephalosporins (3GCs) and assessed whether ceftazidime-avibactam and aztreonam-avibactam could identify ESBL-producing carbapenem-resistant Enterobacterales (CREs). A total of 278 non-duplicate clinical isolates (Klebsiella pneumoniae, E. coli, and Proteus mirabilis) were analyzed. Antimicrobial susceptibility was determined using reference broth microdilution (BMD) and the NMIC-150 System. ESBL production was defined as an ≥eight-fold reduction in the minimum inhibitory concentration (MIC) of 3GCs in the presence of clavulanic acid, according to CLSI criteria. Whole-genome sequencing was performed to characterize ESBL and carbapenemase genes among 3GC-resistant isolates. A Random Forest model was used to predict ESBL-producing isolates based on MIC values. The NMIC-150 System demonstrated over 90% categorical and essential agreement with BMD for ceftazidime and ceftriaxone, along with robust predictive performance via Random Forest analysis. These findings suggest that the NMIC-150 System is a reliable platform for 3GC susceptibility testing and that an ≥eight-fold MIC reduction with ceftazidime-avibactam or aztreonam-avibactam may serve as a phenotypic indicator of ESBL production in CRE isolates. In conclusion, the NMIC-150 System shows potential for routine antimicrobial resistance surveillance and may facilitate the rapid identification of ESBL-producing CREs in clinical settings.

Microbial Sensitivity Tests↗

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

Evolutionary characterization and expression profiling of ACC and FASN genes in Chinese mitten crab Eriocheir sinensis.

Acetyl-CoA carboxylase (ACC) and fatty acid synthase (FASN) are rate-limiting enzymes in the fatty acid biosynthetic pathway, yet their evolutionary relationships, sequence features, and expression profiles remain poorly understood in crustaceans, particularly in the economically important Chinese mitten crab (Eriocheir sinensis). Here, we identified and systematically analyzed ACC and FASN genes in E. sinensis using comparative genomic analyses across 43 species. ACC was highly conserved as a single-copy gene in invertebrates, in contrast to the multiple paralogs observed in vertebrates. Similarly, FASN was generally maintained as a single-copy gene across most taxa but exhibited lineage-specific expansion in certain insect groups. Phylogenetic and structural analysis revealed strong conservation of both genes within crustaceans, supported by multiple conserved motifs and canonical functional domains. Expression profiling showed predominant expression in the hepatopancreas and midgut, suggesting their potential involvement in crustacean lipid metabolism. During the molting cycle, ACC and FASN exhibited higher expression levels during stages C and D, suggesting an increased capacity for fatty acid biosynthesis before molting. In addition, dietary lipid levels experiment revealed that ACC and FASN expression responded dynamically to dietary lipid availability, with increased expression at moderate lipid levels but reduced expression under excessive lipid supplementation, indicating a possible adaptive transcriptional response to lipid status. Collectively, this study provides insights into the evolutionary conservation and expression dynamics of ACC and FASN and improves our understanding of lipid metabolic adaptation in crustaceans.

Animals↗

PubMed2026

Genome-wide SNP data support species boundaries in sympatric Polylepis Ruiz & Pav. (Rosaceae) species from Bolivia and Ecuador.

Species delimitation in the South American genus Polylepis is notoriously challenging due to high morphological similarity and phenotypic plasticity, likely driven by hybridization and gene flow. Previous phylogenetic studies suggested that genetic structure aligns more strongly with geography than with taxonomy, questioning existing species concepts and hampering conservation efforts. We used double-digest RAD sequencing (ddRADseq) to generate genome-wide SNP data for 11 Polylepis species sampled across multiple localities in Bolivia and Ecuador. Population genetic analyses, phylogenetic inference, and network approaches were combined to assess whether genetic structure aligns more closely with taxonomy or geography. Morphologically defined species formed largely cohesive genetic lineages across regions, with species identity explaining substantially more genetic variation than locality. While localized admixture and reticulation were detected among closely related taxa, widespread species showed strong genetic cohesion and clear separation from congeners. Our results indicate that the sampled Polylepis species from Bolivia and Ecuador maintain distinct genetic identities despite localized signals consistent with gene flow. This genome-wide support for current taxonomy highlights Polylepis as a valuable model for studying speciation under gene flow and indicates that multiple geographic sampling will be essential in reconstructing a robust phylogeny of the genus, with important implications for conservation planning in Andean montane forests.

Bolivia↗

PubMed2026

Boosting kynurenic acid in kombucha via substrate selection: metagenomic and biochemical insights.

Kombucha is gaining global popularity for its health benefits. This study explored the use of chestnut honey, a rich source of kynurenic acid (KYNA), to produce kombucha enriched with this metabolite. Five variants were prepared using different green/black tea blends and carbon sources: white sugar or acacia honey (controls) versus chestnut honey. Samples were analyzed for tryptophan metabolites, physicochemical properties, and microbial diversity. Komagataeibacter and Enterobacter were predominant bacterial genera in SCOBY. Candida and Aspergillus were predominated in the single sample analyzed for fungi. During fermentation, tryptophan decreased, while kynurenine increased. KYNA levels remained largely stable during fermentation and were mainly influenced by the fermentation substrate. No melatonin pathway derivatives were detected. On day 7, chestnut honey yielded kombucha with 381.680-739.915 μmol/L KYNA and elevated myricetin. Overall, chestnut honey-based kombucha represents a system in which substrate composition appears to be the main factor influencing KYNA levels in the final beverage.

Kynurenic Acid↗

PubMed2026

Lactylation-related immune-metabolic dysregulation defines prognostic and therapeutic stratification in lung adenocarcinoma.

BACKGROUND: Lactylation links lactate metabolism with inflammatory signaling and immune regulation in tumors. However, its cellular distribution and translational value in lung adenocarcinoma (LUAD) remain unclear. METHODS: Single-cell RNA-sequencing datasets GSE189357 and GSE171145 were integrated to characterize lactylation-related activity, intercellular communication, and malignant epithelial cell states in LUAD. Single-cell-derived lactylation-related differentially expressed genes were mapped to TCGA-LUAD and multiple GEO cohorts. Univariate Cox regression and machine learning algorithms were used to construct a lactylation-related prognostic signature (LRPS). The associations of LRPS with prognosis, immunotherapy response, drug sensitivity, genomic alterations, immune infiltration, and inflammation- and metabolism-related pathways were evaluated. KRT7 was further validated using virtual knockout analysis, spatial transcriptomics, and in vitro and in vivo experiments. RESULTS: lactylation-related transcriptional activity showed heterogeneous distribution across LUAD cell populations and was associated with altered cell-cell communication. In malignant epithelial cells, LRTS-high and LRTS-low states exhibited distinct metabolic, inflammatory, and tumor-related pathway activities. LRPS showed stable prognostic performance in TCGA-LUAD and multiple GEO cohorts and remained an independent prognostic factor. Low LRPS was associated with greater potential benefit from immunotherapy, whereas different LRPS groups displayed distinct drug sensitivity, genomic alteration, and immune microenvironment patterns. KRT7 was highly expressed in LUAD and associated with poor prognosis. KRT7 knockdown suppressed LUAD cell proliferation, migration, invasion, colony formation, and tumor growth in vivo. CONCLUSIONS: This study identifies lactylation-related immune-metabolic dysregulation as a clinically relevant feature of LUAD and develops a single-cell-guided LRPS for prognosis and therapeutic stratification. KRT7 emerged as an LRPS-related functional candidate with experimentally supported roles in malignant LUAD phenotypes.

Immunotherapy↗

PubMed2026

Multi-omics analysis reveals stage-associated differences in gut immunity and microbiota between juvenile and adult common carp (Cyprinus carpio).

In vertebrates, the development of intestinal immunity is closely associated with dynamic changes in the gut microbiota. However, stage-associated differences in intestinal immunity and gut microbial communities remain poorly characterized in teleost fish. In this study, transcriptomic analysis combined with 16S rRNA gene sequencing was employed to characterize intestinal immunity and gut microbial communities in juvenile and adult common carp (Cyprinus carpio). Transcriptomic profiling revealed marked developmental differences in intestinal immune function. Juvenile carp exhibited a predominantly innate immune phenotype, characterized by elevated expression of pro-inflammatory cytokines, antimicrobial peptides, and lysozyme-related genes. This immune profile was accompanied by enhanced mucosal barrier function and a relatively pro-inflammatory intestinal environment. In contrast, adult carp displayed increased expression of genes associated with adaptive immunity, suggesting that adult common carp exhibit relatively stronger adaptive immune characteristics than juvenile fish. Gut microbiota analysis demonstrated significant stage-dependent differences in microbial diversity and community composition. Juvenile fish were enriched with bacterial taxa potentially associated with innate immune activation, whereas adult fish harbored distinct microbial communities linked to intestinal homeostasis and barrier maintenance. Furthermore, correlation analyses identified significant associations between specific microbial taxa and innate immune-related gene expression, suggesting a close association between gut microbiota composition and intestinal immune characteristics in juvenile and adult common carp. Collectively, these findings reveal stage-associated differences in intestinal immunity and gut microbial communities between juvenile and adult common carp, thereby providing insights into intestinal immune characteristics at different developmental stages in teleost fish.

Animals↗

PubMed2026

Integrated single-cell and bulk transcriptomic analysis identifies a novel senescent fibroblast subtype associated with poor prognosis in acral melanoma.

BACKGROUND: Acral melanoma (AM) exhibits significant intratumoral heterogeneity, but its tumor microenvironment (TME) and immune regulation remain unclear. This study aims to dissect TME heterogeneity and establish a prognostic model based on key cell subpopulations. METHODS: We collected AM single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). Unsupervised clustering, CellChat, and Scissor analysis were performed to characterize cellular heterogeneity, cell-cell communication, and prognosis-related cell subpopulations. Kaplan-Meier analysis was used to assess the prognostic value of key genes, which were further validated by multiplex immunohistochemistry (mIHC). RESULTS: In AM, Mel_C2, C7, and C9 with high SEMA6A and KIT expression were strongly linked to poor prognosis. We further identified a senescent fibroblast subpopulation (sCAF_CDKN2A) characterized by high fibroblast senescence signature (FSS) scores. Integrating Scissor analysis of fibroblast subtypes with bulk prognostic data, we identified COL3A1, VCAN, and KIT as prognosis-associated genes upregulated in poor-outcome-related fibroblast subsets. Cell-cell communication analysis revealed that sCAF_CDKN2A engages in an immunosuppressive network, interacting with regulatory T cells (Tregs) via MIF signaling and receiving signals from exhausted CD8+ T cells through PPIA-BSG interactions. Using transcription factor expression patterns from these fibroblast subtypes, we constructed a prognostic model that effectively stratified patients into distinct risk groups with significant differences in overall survival (OS). mIHC confirmed significantly higher protein levels of SEMA6A and COL3A1 in tumor tissues compared to matched normal tissues. CONCLUSIONS: We established a novel prognostic model for AM and identified sCAF_CDKN2A as an immunosuppressive senescent fibroblast subpopulation driving poor prognosis.

Acral melanoma↗

PubMed2026

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans↗