Search Results (5,955)

Cetaceans are artiodactyls adapted to live in the marine environment, and this group includes whales, dolphins, and porpoises. Although mitochondrial nucleotide diversity has been reported separately for many cetacean groups, the proportion of deleterious mutations in these populations is unknown. Furthermore, a comparison of mitogenomic diversities across all cetaceans is also lacking. To investigate this, we conducted a comparative genomic analysis of 2244 mitochondrial genomes from 65 populations across 32 cetacean species. We observed a 78-fold variation in mitogenomic diversity among cetacean populations, suggesting a large difference in genetic diversity. We used the ratio of nonsynonymous-to-synonymous diversities (dN/dS) to measure the proportion of deleterious mutations in the mitochondrial exomes. The dN/dS ratio showed a 22-fold difference between the cetacean population. Based on genetic theories, the large differences observed in the two measures could be attributed to differences in the effective sizes of the cetacean populations. Typically, small populations have low heterozygosity and a high dN/dS ratio, and the reverse is true for large populations. This was further confirmed by the negative correlation observed between heterozygosity and dN/dS ratios of cetacean populations. While our analysis revealed similarities in mitogenomic diversity between the endangered and least-concern cetacean species, the dN/dS ratio of the former was found to be higher than that of the latter. The findings of this study are useful for identifying the relative magnitude of reductions in the population sizes of different cetacean species. This will help conservation management efforts prioritise the use of limited resources, time, and effort to protect the cetacean populations that need immediate attention. Full article

Colorectal cancer (CRC) progression and therapy resistance are driven in part by metabolic reprogramming and the persistence of cancer stem-like cells (CSCs). The seven in absentia homolog 2 (SIAH2)/with-no-lysine kinase 1 (WNK1) signaling axis has emerged as a potential regulator of these processes, yet its functional role in CRC metabolism and tumor–stroma crosstalk remains incompletely understood. Integrated analyses of The Cancer Genome Atlas–Colon Adenocarcinoma (TCGA-COAD) and Gene Expression Omnibus (GEO, GSE17538) datasets revealed significant upregulation of SIAH2 and WNK1 in CRC tissues, with strong positive correlations to glycolysis- and hypoxia-associated genes, including PFKP, LDHA, BPGM, ADH1A, ADH1B, and HIF-1α. Single-cell and clinical profiling further demonstrated preferential enrichment of SIAH2 in undifferentiated, stem-like tumor cell populations. Functional studies across multiple CRC cell lines showed that SIAH2 silencing suppressed proliferation, clonogenic growth, tumor sphere formation, and cell-cycle progression, whereas SIAH2 overexpression exerted opposite effects. Seahorse extracellular flux analyses established that SIAH2 promotes glycolytic capacity and metabolic flexibility. At the protein level, SIAH2 regulated glycolytic enzymes and WNK1/hypoxia-inducible factor-1α (HIF-1α) signaling, effects that were amplified by cancer-associated fibroblast (CAF)-derived conditioned medium. CAF exposure enhanced SIAH2 expression, CSC spheroid growth, and resistance to fluorouracil, leucovorin, and oxaliplatin (FOLFOX) chemotherapy, whereas SIAH2 depletion effectively abrogated these effects. Collectively, these findings identify the SIAH2/WNK1 axis as a central metabolic regulator linking glycolysis, CSC maintenance, and microenvironment-driven therapy resistance in CRC, highlighting its potential as a therapeutic target. Full article

Background/Objectives: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. Methods: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I² and Cochran’s Q, and publication bias via funnel plots and Egger’s test. Results: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68–2.00]; z = 0.56, p = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23–0.73]; p < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08–0.52]; p < 0.001; weight = 7.41%). Heterogeneity was substantial (τ² = 0.78; I² = 81.95%; Q (13) = 64.67, p < 0.001). Conclusions: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size. Full article

Escherichia coli is an important human pathogen that is able to cause a variety of infections, which can result in diarrhoea, urinary tract infections, sepsis, and even meningitis, depending on the pathotype of the infecting strain. Like many Gram-negative bacteria, E. coli is becoming increasingly resistant to many frontline antibiotics, including third-generation cephalosporins and carbapenems, which are often considered the antibiotics of last resort for these infections. This is particularly the case in Egypt, where multidrug-resistant (MDR) E. coli is highly prevalent. However, in spite of this, few Egyptian MDR E. coli strains have been fully characterised by genome sequencing. Here, we present the genome sequences of ten highly MDR E. coli strains, which were isolated from children who presented with diarrhoea at the Outpatients Clinic of Assiut University Children’s Hospital in Assiut, Egypt. We report that they carry multiple antimicrobial resistance genes, which includes extended spectrum β-lactamase genes, as well as bla_NDM and bla_OXA carbapenemase genes, likely encoded on IncX3 and IncF plasmids. Many of these strains were also found to be high-risk extra-intestinal pathogenic E. coli (ExPEC) clones belonging to sequence types ST167, ST410, and ST617. Thus, their presence in the Egyptian paediatric population is particularly worrying, and this highlights the need for increased surveillance of high-priority pathogens in this part of the world. Full article

Androgenetic alopecia (AGA) is the most common cause of progressive hair thinning in adults and has traditionally been viewed as an androgen-driven inherited condition. Genomic research now demonstrates that AGA is a complex polygenic disorder involving multiple biological pathways, including androgen signaling, hair follicle development, cell survival, and extracellular matrix remodeling. Genome-wide association studies have identified numerous susceptibility loci, revealing that follicle miniaturization arises from interacting molecular mechanisms rather than a single pathogenic process. Genetic risk and predictive value vary across populations, with many loci identified in European cohorts showing limited transferability to other ancestries, highlighting the need for more diverse genetic studies. In women, genetic studies remain underpowered, and emerging data suggest partially distinct risk architecture compared with male AGA. Pharmacogenetic findings indicate that genetic variation may influence response to commonly used therapies, although no markers are currently validated for routine clinical use. Advances in single-cell and multi-omic approaches are improving understanding of how genetic risk translates into follicular dysfunction, supporting the development of more personalized and mechanism-based treatment strategies. Full article

Feline calicivirus (FCV) is a highly variable RNA virus that infects domestic cats and circulates endemically within feline populations, causing a wide spectrum of clinical manifestations, from asymptomatic infections to severe disease. Genomic analysis of 69 FCV strains revealed a high prevalence of the virus across multiple provinces in China. In vitro infection of CRFK cells with laboratory isolates FCV-BJ616 and FCV-BJDX40 resulted in significant cytotoxic effects. Serum proteomic analysis identified 221 upregulated and 123 downregulated proteins following infection with FCV-BJ616, and 233 upregulated and 165 downregulated proteins following infection with FCV-BJDX40. Among these, 215 proteins exhibited shared differential expression. Functional analyses revealed enriched pathways, including TNF signaling and ferroptosis. Notably, upregulation of Acyl-CoA Synthetase Long-Chain Family Member 4 (ACSL4) was correlated with lung injury, while downregulation of S100 Calcium Binding Protein A2 (S100A2) was associated with poor prognosis in FCV-associated oral disease. The differential expression of ACSL4 and S100A2 was further validated through Western blot analysis. These results suggest that ACSL4 and S100A2 are promising candidate biomarkers for monitoring FCV infection and disease progression, laying a foundation for future diagnostic and prognostic applications. Full article

Recent advances in molecular pathology, driven by integrated and comprehensive diagnostic approaches, have significantly advanced precision oncology. By leveraging multiomics technologies, molecular pathology enables the simultaneous assessment of genomic alterations, transcriptomic profiles, proteomic activity, and metabolic states integrated with conventional pathological evaluation to better explain tumour biology and behaviour. Large-scale international consortia, including The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumour Analysis Consortium (CPTAC) have systematically demonstrated the value of harmonised multiomics analyses in defining tumour subtypes, uncovering functional dependencies, and generating clinically actionable insights. Evidence from coordinated precision oncology initiatives, such as the National Cancer Institute—Molecular Analysis for Therapy Choice (NCI-MATCH) trial further indicates that treatment strategies guided by molecular pathology profiling are associated with improved clinical outcomes, including progression-free survival in molecularly selected patient populations. Consequently, molecularly stratified treatment approaches are increasingly required in routine clinical practice to enable targeted therapies for selected tumour entities. Integration of molecular data with functional and clinical outcomes has further facilitated the detection of emerging mechanisms of therapeutic resistance and heterogeneous treatment responses. Importantly, studies have shown that reliance on genomic analysis alone is insufficient to achieve optimal targeted therapy, underscoring the need for multi-layered molecular interrogation. This review highlights the biological and clinical relevance of multiomics integration, emphasising its critical role in comprehensive morpho-molecular tumour assessment and functional analyses while providing clinicians with a practical framework for interpreting integrated molecular diagnostics and addressing the methodological and translational challenges that must be overcome to enable broader implementation of precision oncology in routine practice. Full article

A group of experts of different specialties involved in the care of prostate cancer (PCa) patients participated in the ENFOCA2 project, promoted by the Spanish Oncology Genitourinary Group (SOGUG), with the aim to review, discuss, and summarize current relevant aspects related to screening, diagnosis, imaging, risk-based approach, and molecular characterization of PCa. A multidisciplinary team (MDT) approach is essential to ensure that patients receive evidence-based care, promoting shared decision-making, and tailoring treatment to the patient’s unique values and preferences. Population-based screening based on risk-stratified algorithms is needed to overcome the limitations of opportunistic screening for detecting clinically significant PCa. Next-generation imaging (NGI) methods, such as prostate-specific membrane antigen (PSMA) PET/CT alone or combined with multiparametric MRI (mpMRI), have a promising role in different scenarios of the diagnostic process due to their high sensitivity. The diagnostic yield of mpMRI should be improved, especially for assessing extraprostatic extension. The use of specific molecular probes as imaging markers for MRI could improve the staging of metastatic disease. Protocols for germline testing developed by international societies, such as the European Association of Urology (EAU) and the National Comprehensive Cancer Network (NCCN), should be adapted at local levels, with BRCA1/2, ATM, PALB2, CHEK2, MLH1, MSH2, MSH6, PMS2, EPCAM, and HOXB13 as the genes to be investigated. Genomic classifier tools help identifying aggressiveness of cancers and aid in personalized treatment decision-making. Joint efforts of multidisciplinary physicians are crucial to improve health outcomes for patients with PCa across the spectrum of this disease. Full article

The genetic basis for Tibetan sheep adaptation to different high-altitude environments remains unknown. This study conducted whole-genome resequencing on 80 Tibetan sheep individuals from four major distribution areas on the Qinghai–Tibet Plateau. Based on the high-quality single-nucleotide polymorphisms (SNPs) obtained, an analysis of population-level genomic selection signals was performed. Population genomic analysis revealed that Tibetan sheep distributed across China originated in northern China but showed evidence of gene flow from South Asian sheep. Between populations from extremely high-altitude and mid-altitude regions, selection analyses identified five strongly positive selected genes (HIF1AN [Hypoxia Inducible Factor 1 Alpha Subunit Inhibitor], HBE1 [Hemoglobin Subunit Epsilon 1], HBE2 [Hemoglobin Subunit Epsilon 2], TNFAIP3 [TNF Alpha Induced Protein 3], RAD50 [RAD50 Double Strand Break Repair Protein]). These genes are associated with adaptation to hypoxia and intense UV radiation in high-altitude environments. Selection analyses between populations from extremely high-altitude and mid-altitude regions identified five strongly selected genes (HIF1AN [Hypoxia Inducible Factor 1 Alpha Subunit Inhibitor], HBE1 [Hemoglobin Subunit Epsilon 1], HBE2 [Hemoglobin Subunit Epsilon 2], TNFAIP3 [TNF Alpha Induced Protein 3], RAD50 [RAD50 Double Strand Break Repair Protein]) associated with hypoxia and intense UV radiation in high-altitude environments. Comparative genomic analyses of populations in cold and arid environments identified several candidate genes related to energy and water homeostasis, as well as hair development (TP53 [Tumor Protein P53], ATG101 [Autophagy Related 101], ATP12A [ATPase H+/K+ Transporting Non-Gastric Alpha2 Subunit], KRT80 [Keratin 80], KRT7 [Keratin 7]). Additionally, Tibetan sheep in the high-altitude arid deserts exhibit stronger adaptive selection for energy homeostasis and water utilization; meanwhile, the HIF-1 [Hypoxia Inducible Factor 1] signaling pathway helps counteract oxidative stress induced by extreme water scarcity in the plateau environment. Our study supports the hypothesis that Tibetan sheep originated in northern China and identifies distinct adaptive features in the Tibetan sheep genome corresponding to their habitats. Full article

Improving wheat processing quality is a crucial objective in modern wheat breeding. Among various quality parameters, grain protein content (GPC) and wet gluten content (WGC) significantly influence the end-use quality of flour. These traits are controlled by multiple minor effect genes and highly influenced by environmental factors. Identifying stable and major-effect genetic loci and developing breeder-friendly molecular markers are of great significance for breeding high-quality wheat varieties. In this study, we evaluated the GPC and WGC of 310 diverse wheat varieties, mainly from China and Europe, across four environments. Genotyping was performed using the wheat 100K SNP chip, and genome-wide association analysis (GWAS) was employed to identify stable loci with substantial effects. In total, four loci for GPC were identified on chromosomes 1A, 3A, 3B, and 4B, with explained phenotypic variation (PVE) ranging from 6.0 to 8.4%. In addition, three loci for WGC were identified on chromosomes 4B, 5A, and 5D, which explained 7.0–10.0% of the PVE. Among these, three loci coincided with known genes or quantitative trait loci (QTL), whereas QGPC.zaas-3AL, QGPC.zaas-4BL, QWGC.zaas-4BL, and QWGC.zaas-5A were potentially novel. Seven candidate genes were involved in various biological pathways, including growth, development, and signal transduction. Furthermore, five kompetitive allele specific PCR (KASP) markers were developed and validated in a natural population. The newly identified loci and validated KASP markers can be utilized for quality improvement. This research provides valuable germplasm, novel loci, and validated markers for high-quality wheat breeding. Full article

Multi-generation intelligent breeding (MGIB) decision-making is a technique used by plant breeders to select mating individuals to produce new generations and allocate resources for each generation. However, existing research remains scarce on dynamic optimization of resources under limited budget and time constraints. Inspired by advances in reinforcement learning (RL), a framework that integrates evolutionary algorithms with deep RL was proposed to fill this gap. The framework combines two modules: the Improved Look-Ahead Selection (ILAS) module and Deep Q-Networks (DQNs) module. The former employs a simulated annealing-enhanced estimation of the distribution algorithm to make mating decisions. Based on the selected mating individual, the latter module learns multi-generation resource allocation policies using DQN. To evaluate our framework, numerical experiments were conducted on two realistic breeding datasets, i.e., Corn2019 and CUBIC. The ILAS outperformed LAS on corn2019, increasing the maximum and mean population Genomic Estimated Breeding Value (GEBV) by 9.1% and 7.7%. ILAS-DQN consistently outperformed the baseline methods, achieving significant and practical improvements in both top-performing and elite-average GEBVs across two independent datasets. The results demonstrated that our method outperforms traditional baselines, in both generalization and effectiveness for complex agricultural problems with delayed rewards. Full article

Background/Objectives: In order to develop a comprehensive understanding of gastric-type endocervical adenocarcinoma (GEA), an increasingly prevalent HPV-independent cervical cancer, we summarized clinicopathological information and performed prognostic analysis. Methods: A total of 182 patients diagnosed with GEA at our center during the period 2014–2025 were included in this study. Nineteen GEA cases, 6 HPV-independent non-GEA cases, 59 HPV-associated usual endocervical adenocarcinoma cases, and 66 squamous cell carcinoma cases from online database were also included. Results: Vaginal bleeding (39.56%) and watery discharge (35.16%) were the most common symptoms. As many as 21.43% of patients had no specific complaints, and 80% of GEA showed no distinct mass through gynecological examination. A total of 64% of GEA were stage IIB–IV at diagnosis, with a 5-year survival of 41% versus 85% for stage I–IIA (p < 0.05). The rate of lymphovascular space invasion (LVSI), lymph node metastasis, and ovarian metastasis were 49.64%, 42.00%, and 29.29%, respectively. The 5-year survival and recurrence rates after primary therapy were 57% and 23%, respectively. For GEA treatment, surgery might be associated with improved overall survival for the population at stage III–IV. Survival analysis identified deep infiltration depth (≥2/3), a maximum diameter of the tumor (MDOT) of ≥3 cm, and ovary metastasis as potential indicators of worse OS and PFS for whole patients. Additionally, ovary metastasis indicated poor PFS and OS for stage I–II. Genomic information TP53 mutation, PTEN deletion and STK11 mutation might be the most prevalent genomic alterations. Conclusions: These findings indicated GEA as an aggressive cervical cancer, with high rate of lymph node metastasis, high recurrence rate and short 5-year survival. Ovary metastasis reflected advanced disease burden and surgery might be associated with improved survival in advanced stage. For genomic information, GEA showed genetic heterogeneity and a low level of genomic instability. Full article

Rotavirus (RV) is the primary cause of severe gastroenteritis in young children, yet the long noncoding RNA (lncRNA) regulatory landscape governing the host response remains largely unmapped. To address this gap, the present study performed an integrated transcriptomic analysis of mRNA and lncRNA expression profiles in RV-infected MA104 cells at 24 h post-infection. Deep sequencing identified 11,919 high-confidence lncRNAs, revealing a massive transcriptional shift: 3651 mRNAs and 4655 lncRNAs were differentially expressed, with both populations predominantly upregulated. Functional enrichment analysis confirmed the strong activation of key innate immunity pathways, including the RIG-I-like receptor, Toll-like receptor, and TNF signaling pathways. Conversely, fundamental metabolic pathways were found to be suppressed. Crucially, the analysis of lncRNA targets highlighted their involvement in coordinating the host antiviral defense, particularly through transregulation. Experimental validation confirmed the significant upregulation of key immune-related mRNAs (OASL and C3) as well as two novel lncRNAs (lncRNA-6479 and lncRNA-4290) by qRT-PCR. The significant upregulation of OASL and C3 was validated at the protein level, confirming the biological relevance of the transcriptomic data. This study provides a foundational, genome-wide resource, identifying novel lncRNA targets for future mechanistic investigation into host–RV interactions. Full article

Background: The persistently low 5-year survival rate for pancreatic cancer (PC) underscores the critical need for early detection. However, population-wide screening remains impractical. Artificial Intelligence (AI) models using electronic health record (EHR) data offer a promising avenue for pre-symptomatic risk stratification. Objective: To systematically review and meta-analyze the performance of AI models for PC prediction based exclusively on structured EHR data. Methods: We systematically searched PubMed, MedRxiv, BioRxiv, and Google Scholar (2010–2025). Inclusion criteria encompassed studies using EHR-derived data (excluding imaging/genomics), applying AI for PC prediction, reporting AUC, and including a non-cancer cohort. Two reviewers independently extracted data. Random-effects meta-analysis was performed for AUC, sensitivity (Se), and specificity (Sp) using R software version 4.5.1. Heterogeneity was assessed using I² statistics and publication bias was evaluated. Results: Of 946 screened records, 19 studies met the inclusion criteria. The pooled AUC across all models was 0.785 (95% CI: 0.759–0.810), indicating good overall discriminatory ability. Neural Network (NN) models demonstrated a statistically significantly higher pooled AUC (0.826) compared to Logistic Regression (LogReg, 0.799), Random Forests (RF, 0.762), and XGBoost (XGB, 0.779) (all p < 0.001). In analyses with sufficient data, models like Light Gradient Boosting (LGB) showed superior Se and Sp (99% and 98.7%, respectively) compared to NNs and LogReg, though based on limited studies. Meta-analysis of Se and Sp revealed extreme heterogeneity (I² ≥ 99.9%), and the positive predictive values (PPVs) reported across studies were consistently low (often < 1%), reflecting the challenge of screening a low-prevalence disease. Conclusions: AI models using EHR data show significant promise for early PC detection, with NNs achieving the highest pooled AUC. However, high heterogeneity and typically low PPV highlight the need for standardized methodologies and a targeted risk-stratification approach rather than general population screening. Future prospective validation and integration into clinical decision-support systems are essential. Full article

Objectives: The molecular characterization of male breast cancer (MaBC) has long been understudied, primarily due to its rare occurrence. Clinical management of MaBC remains profoundly challenging, with current therapeutic strategies largely extrapolated from female breast cancer protocols. Methods: Through panel-based sequencing targeting BRCA1, BRCA2, and PALB2 variants, we delineated the genomic landscape of 96 MaBC cases. Subsequent whole-exome sequencing (WES) of 84 BRCA1/2- and PALB2-mutation-negative MaBC patients, compared against 4480 healthy controls, revealed compelling findings. Results: Pathogenic variants in BRCA1/2 and PALB2 were identified in 14.6% (14/96) of MaBC cases, with BRCA2 mutations predominating at 12.5% (n = 12). Notably, one patient harbored the BRCA1 c.4015G > T stop-gained mutation, while another exhibited the PALB2 c.481_482dupGA alteration. Our analysis further uncovered 170 pathogenic/likely pathogenic mutations, with RAD50, DMD, ARSA, and ABCC6 demonstrating recurrent mutations in MaBC. Conclusions: As the inaugural germline genomic investigation of MaBC in a Han Chinese population, this work reveals clinically actionable alterations with diagnostic and therapeutic implications. These discoveries not only advance our understanding of MaBC’s molecular architecture but also underscore the critical need for dedicated research into this malignancy. Full article