The HER2 (human epidermal growth factor receptor 2) kinase domain plays a pivotal role in receptor-mediated signaling and is frequently mutated across various cancer types. Variants of uncertain significance (VUS) within this domain pose significant challenges for clinical interpretation. In this study, a comprehensive computational analysis was conducted on 97 HER2 kinase domain variants comprising 25 pathogenic and 72 VUS entries using a panel of 13 predictive algorithms, including PredictSNP, PolyPhen-2, SIFT, and CADD. A subset of 32 variants (11 pathogenic and 21 VUS) was prioritized for in-depth structural and functional evaluation, based on concordant deleterious predictions from ≥ 9 algorithms. Conservation profiling via ConSurf and Align-GVGD revealed that these variants predominantly localize to highly conserved and functionally critical residues, underscoring their potential biological relevance. Thermodynamic stability profiling using I-Mutant indicated that the majority of prioritized variants exerted destabilizing effects on the protein's tertiary structure, consistent with their pathogenic annotations. Extended molecular dynamics simulations (200 ns) revealed noticeable deviations in root mean square displacement (RMSD), root mean square fluctuation (RMSF), and solvent-accessible surface area (SASA), accompanied by reductions in intramolecular hydrogen bonding and global structural compactness, highlighting conformational destabilization. Stereochemical integrity, assessed through Ramachandran plot analysis, was compromised in specific variants. At the same time, perturbations in hydrophobic core interactions and secondary structure elements further underscored disruptions in core packing and local conformational stability. Notably, the R816P variant demonstrated minimal perturbation to structural dynamics, highlighting the necessity of integrating time-resolved simulations with sequence-based pathogenicity predictions.

Domestic goats (Capra hircus) are vital to global agriculture, with over one billion animals supporting smallholder farmers worldwide. Among goat breeds, the Changthangi goat, native to the trans-Himalayan region of Ladakh, produces pashmina, one of the finest natural fibers (12-16 μm diameter), renowned for its softness and insulation. This study presents the first comprehensive whole-genome comparative analysis between high-altitude pashmina-producing Changthangi goats and lowland Jamunapari goats to elucidate the genetic basis of superior fiber traits. Genome-wide selection signature analyses, including Tajima's D, nucleotide diversity (π), CLR, iHS, F, and XP-EHH, revealed 2,113 and 839 candidate genes under intra- and inter-population selection, respectively. We identified several candidate genes under selection in Changthangi goats, including those regulating keratinocyte differentiation (BMP2, SMAD3, WNT9B), extracellular matrix organization (COL1A2, ITGA4), and metabolic adaptation (ADCY4, RPS6KB1). Functional annotation and pathway enrichment using DAVID and KEGG databases highlighted key pathways such as Wnt, BMP/TGF-β, Hedgehog, Rap1, PI3K-Akt, and ECM-receptor interaction, which regulate hair follicle morphogenesis, and fiber structure. Gene interaction networks highlighted hub genes (FGF5, SMAD7, COL1A2) critical for fiber traits. Our findings provide novel insights into the genomic signatures underlying elite pashmina production, offering targets for marker-assisted breeding to enhance fiber yield and fineness.

The mouse remains the principal animal model for investigating human diseases due, among other reasons, to its anatomical similarities to humans. Despite its widespread use, the assumption that mouse anatomy is a fully established field with standardized and universally accepted terminology is misleading. Many phenotypic anatomical annotations do not refer to the authority or origin of the terminology used, while others inappropriately adopt outdated or human-centric nomenclature. This inconsistency is further exacerbated by the limited availability of comprehensive anatomical references, often compelling researchers to rely on "do-it-yourself" anatomical interpretations when characterizing disease models-an approach that increases the risk of inaccuracies in the absence of expert anatomical guidance. To address this critical gap, we propose the formation of expert working groups comprising comparative anatomists and disease model developers. These groups would be responsible for systematically reviewing the anatomical literature of each mouse organ system and producing consensus-based terminologies aligned with the Nomina Anatomica Veterinaria (NAV), the authoritative standard for quadrupedal species. Such harmonization efforts would not only improve the consistency and reliability of anatomical descriptions in mouse models but also enhance the integration and interoperability of anatomical data across biomedical ontologies and databases, facilitating more robust data mining and translational research.

Red Sindhi cattle, a distinguished dairy breed from India, are famous for their resilience in tropical climates and exceptional milk yield. This study utilized double digest restriction site-associated DNA sequencing (ddRADseq) across 96 individuals to explore genome-wide diversity and uncover signatures of selection. The analysis revealed a high proportion of polymorphic SNPs (0.956), moderate nucleotide diversity (π = 0.215 ± 0.114), and a low minor allele frequency (MAF = 0.149 ± 0.128). The analysis of Red Sindhi data showed a steep decline in effective population size (Ne) from 2387 to 125.9 over 13 generations, implying potential bottlenecks and underscoring the urgency of conservation efforts. Employing Tajima's D, composite likelihood ratio (CLR), integrated haplotype score (iHS), and runs of homozygosity (ROH) methods, we identified 490 genomic regions under positive selection, encompassing 1282 genes and aligning with 574 quantitative trait loci (QTLs). Functional annotations highlighted several genes linked to reproduction (RHOU, MND1), production (DOK6, NPFFR2), immune response (BOLA-DYA and BOLA-DMB), and environmental adaptation (HSPA14, NOD2, GCLC, and RPS19BP1). Several MHC class II genes under selection pressure indicate robust immune competence, while stress-response genes supported Red Sindhi's remarkable tolerance to extreme heat. These findings show the breed's strong adaptability and disease resilience, underlining its importance as a valuable genetic resource for improving livestock in challenging environments.

Anestrus, an infertility condition that affects several animal' species, is characterized by failing to display estrus. In pig production, it leads to the culling of 5 to 15% of the replacement gilts, resulting in significant losses impairing the swine female longevity. Despite that, little is known about the genetic mechanisms involved with anestrus in pigs. Hence, this study evaluated cyclic and non-cyclic F1 Landrace × Large White gilts to identify genomic regions associated with failure to display pubertal estrus through a genome-wide association study (GWAS), highlighting possible candidate genes involved with this condition in swine. Tissue samples were collected at 219.8 ± 4.7 days of age and genotyped with the PorcineSNP50 BeadChip from Illumina. In the GWAS, a SNP in the EML4 gene located on chromosome 3 (SSC3) was moderately associated with anestrus. The other 14 SNPs suggestively associated with anestrus were identified on SSCs 1, 3, 6, 7, 9 and 15. Investigating the regions close to those SNPs, new candidate genes for anestrus occurrence, such as EML4, DST, SRTB, MEAF, PHF1, PPMIB and PREPL, including 11 lncRNAs and a snoRNA were identified. Therefore, our study highlighted novel genetic mechanisms involved with the failure to display pubertal estrus in pigs, contributing to unraveling the genetic architecture of anestrus in pigs and other species. The use of genomic methodologies is a promising tool to help the early identification of gilts with potential reproductive problems associated with anestrus.

Rattus norvegicus (a.k.a. laboratory rat or Brown Rat) Mammary carcinoma susceptibility 1b (Mcs1b) is a concordant ortholog of a female breast cancer risk allele at human 5q11.2. Previously, Mcs1b was delimited to a 1.8 Mb interval of RNO2 and Map3k1 along with Mier3 were determined to be Mcs1b-nonminated genes. This conclusion was based on shared synteny with human 5q11.2 and differential gene expression between cancer susceptible and Mcs1b resistant mammary glands. In this study, targeted genome sequencing of cancer susceptible and Mcs1b resistance associated alleles was used to identify three Mcs1b-nominated quantitative trait nucleotides (QTNs) in noncoding DNA. In vitro approaches, luciferase activity and electromobility shift assays, were used to suggest these variants reside in potential gene regulatory elements. One of these variants, UL-A74-SNV-17, resulted in luciferase activities that were 2.6× higher for the susceptibility associated variant compared to the resistance associated variant. These results recapitulated Mcs1b nominated gene transcript level differences between Mcs1b genotypes in mammary epithelial cells (MECs), where Map3k1 and Mier3 were 1.5- to 2.0-fold higher for the susceptible genotype compared to the Mcs1b resistance-associated genotype. Evidence of a chromatin loop in Mcs1b that may position Mcs1b QTNs near distal genes was uncovered using chromosome confirmation capture (3C). Rat Mcs1b was also functionally characterized by determining that Mcs1b genotype had effects on the amount of luminal MECs in adult mammary glands. In conclusion, UL-A74-SNV-17 is a priority candidate Mcs1b QTN with a hypothesized mechanistic role in the differential regulation of Mcs1b nominated genes, Mier3 and Map3k1.

Lung cancer is strongly associated with increased cardiovascular disease (CVD) risk, yet the molecular mechanisms remain poorly understood. Batched two-sample Mendelian randomization (MR) analysis was performed to investigate cancer types and CVDs with significant associations. Local genetic correlation analyses were performed to identify meaningful genetic regions. Genomic Structural Equation Modeling (gSEM) was applied to identify latent factors shared between selected cancer types and CVDs. A transcriptome-wide association study (TWAS) was performed to identify relevant genetic markers. A two-stage MR analysis was performed to investigate potential mediators. Colocalization analysis was performed to assess the sensitivity of the results. Seventeen cancer types were positively associated with CVD risk, with lung cancer exhibiting the strongest link. Using LAVA and ρ-HESS, we identified local genetic correlations between lung cancer and specific CVDs, including coronary artery disease (CAD), heart failure (HF), abdominal aortic aneurysm (AAA), and atrial fibrillation (AF). Weighted median MR analysis identified a negative effect for IREB2 (OR = 0.9; 95% CI 0.84-0.95; P < 0.05), and positive effects for both KRTCAP2 (OR = 1.1; 95% CI 1.02-1.21; P < 0.05) and MTX1P1 (OR = 1.1; 95% CI 1.02-1.21; P < 0.05), on lung cancer-induced AAA. ZBTB7B exhibited a positive mediating effect in the association between lung cancer and HF risk (OR = 1.04; 95% CI 1.01-1.07; P < 0.05). This study highlights IREB2, KRTCAP2, MTX1P1, and ZBTB7B as potential therapeutic targets for cancer-related CVD risk, emphasizing the importance of considering genetic factors in understanding and managing cardiovascular complications associated with lung cancer.

Chronic obstructive pulmonary disease (COPD) is a leading global cause of mortality, with alveolar macrophages (AMs) dysfunction implicated in pathogenesis, though key molecular drivers remain unclear. This study integrated multi-omics approaches to identify causal AMs-derived factors in COPD. Single-cell RNA sequencing (scRNA-seq) of human lung tissues revealed a significantly increased proportion of macrophages, particularly enriched AMs clusters (0, 1, 5), in COPD patients versus controls. Two-sample Mendelian randomization (MR) analysis of 1,283 AMs-specific genes identified CXCL16 as having a robust negative causal relationship with COPD risk across European (IVW OR = 0.944, P = 0.039) and East Asian (Weighted median OR = 0.858, P = 0.008) populations. Bulk RNA-seq confirmed decreased CXCL16 expression in COPD lungs. Cell-cell chat analysis indicated that CXCL16 + AMs mediated critical immune interactions via pathways like MIF-CD74/CD44. Critically, CXCL16 deficiency in AMs drives COPD progression by disrupting immune-metabolic homeostasis. These findings establish CXCL16 downregulation in AMs as a novel causal mechanism in COPD and highlight its potential as a therapeutic target for restoring macrophage function and halting disease advancement.

The minor effects of many SNP interactions often determine complex traits. This interaction, known as epistasis, represents a non-additive genetic effect in which the influence of one variant depends on the presence of others. In this study, we tested for epistatic effects on the residual feed intake (RFI) and residual methane emission (RME) traits of Nelore cattle. Additionally, we evaluated the impact of these interactions in other omics layers (i.e., microorganism profiles in the rumen content and feces and mRNA and miRNA expression in the rumen wall). The genomic interaction modules identified 14 and 10 significant SNP-SNP modules associated with RME and RFI traits, respectively. The majority of these SNPs were located in intronic and intergenic regions. The top pathways and processes associated with the SNP-SNP modules were identified, with several pathways related to the immune system and actin cytoskeleton organization. Furthermore, many other omics data were correlated with these SNP-SNP modules. Our findings suggest that the immune response and cilium organization may play important roles in feed efficiency. These insights not only provide novel candidates for enhancing these traits through microbiota composition and transcriptional regulation but also underscore the power of network analysis in uncovering new functional interactions. This research provides new insights and highlights candidate features for improving cattle feed efficiency and methane emissions.

Infertility affects ~ 15% of couples globally, with male factors contributing to ~ 50% of cases. Male infertility comes from a variety genetic, hormonal, environmental, and lifestyle factors. Yet, a large proportion of cases are idiopathic and have no identifiable cause. Recent advances highlight the critical role of microRNAs (miRNAs), small non-coding RNAs that regulate gene expression at the post-transcriptional level, in male reproductive health. miRNAs are pivotal in spermatogenesis, sperm maturation, and testicular function, influencing processes such as cell cycle regulation, apoptosis, and differentiation. Altered miRNA expression has been linked to many types of male infertility, such as oligozoospermia (low sperm count), asthenozoospermia (low motility), azoospermia(no sperm) and teratozoospermia(abnormal morphology). Notably, miRNAs like miR-34c, miR-21, and miR-449 play essential roles in germ cell proliferation, meiotic progression, and spermiogenesis, while others, such as miR-210 and miR-122, impact sperm motility and DNA integrity.Their stability in biological fluids positions miRNAs as promising non-invasive biomarkers for diagnosing male infertility. miRNA-based diagnostics significantly reduce the need for invasive testicular biopsies in men with azoospermia, enabling earlier, less invasive, and more accurate identification of underlying spermatogenic defects. Furthermore, miRNA-targeted therapies hold promise for restoring spermatogenesis in select cases, potentially improving fertility outcomes for affected patients. Moreover, therapeutic approaches targeting miRNA pathways, including miRNA mimics and inhibitors, offer innovative solutions to restore reproductive function. However, challenges such as complex miRNA networks, delivery system inefficiencies, and inter-individual variability hinder clinical translation. The various functions of miRNAs in male infertility are highlighted in this review, along with their potential for diagnosis, prognosis, and treatment.

High-altitude environments such as the Himalayas, Andes, and Ethiopian regions pose extreme environmental challenges like hypobaric hypoxia, cold stress, and extreme UV radiation. This prompts both short-term physiological and long-term genetic adaptations in resident human and livestock populations. Various genetic studies suggest that candidate genes, such as HIF1A, EPAS1, EGLN1, MITF, ITPR2, VEGFA etc. are involved in hypoxia response, erythropoiesis, angiogenesis and metabolic regulation that results in high altitude adaptation. Phylogenetic comparisons of HIF family genes, suggest evolutionary divergence between humans and livestock, however, closer relationships exist among the ruminants suggesting shared adaptive pressures. The present study revealed that despite of the different evolutionary history, both humans and livestock across the different geographical regions show similar type of traits, driven by certain genes (either the same genes or different genes working in similar ways). These genes have been naturally selected over the time and helped the humans and livestock to survive at extreme environments. Furthermore, enrichment analysis suggests convergent evolution at the gene and pathway levels, supporting the genetic adaption in humans and livestock across the different geographical regions. This review will serve as a valuable information source for researchers working in the fields of high-altitude environments, evolutionary biology and environmental genomics.

The relationship of inflammatory cytokines with the subtypes and prognosis of stroke is not fully understood. Mendelian randomization (MR) was used to evaluate the bidirectional relationship of inflammatory cytokines with stroke subtype (both ischemic and hemorrhagic), and functional outcome of ischemic stroke (modified Rankin Scale score), using databases from Genome-wide association studies, the GISCOME study, the UK Biobank, deCODE, and ONTIME. Colocalization analysis was conducted to determine whether cytokines and stroke subtypes had associations with the same single-nucleotide polymorphism (SNP). Meta-analysis of MR was performed to prove the robustness of the causal relationship between cytokines and stroke subtypes. In addition, both two-step MR analysis and multivariate MR were utilized in mediation analysis to ascertain whether inflammatory cytokines affected stroke subtypes through their regulation of risk factors of cerebrovascular diseases. MR revealed that the genetic prediction of circulating fibroblast growth factor 5 (FGF5) was associated with an increased risk of ischemic stroke and intracranial hemorrhage, but not with the functional outcome of ischemic stroke. Colocalization analysis demonstrated that the association of FGF5 with ischemic stroke and intracranial hemorrhage was driven by the same SNPs. Meta-analyses supported the causal relationship of FGF5 with ischemic stroke and intracranial hemorrhage. Mediation analyses revealed that both essential hypertension and atrial fibrillation mediate the increased risk of ischemic stroke and intracranial hemorrhage due to FGF5. Inflammatory cytokines are associated with stroke and risk factors of cerebrovascular diseases. A high level of circulating fibroblast growth factor 5 is a potential risk factor for stroke.

Poor wound healing is a significant challenge that can result in lower limb amputation. Unfortunately, effective treatments are currently limited. Therefore, there is an urgent need to investigate new targets within the skin healing process to identify more effective treatment options. Differentially expressed genes (DEGs) were identified before and after wound healing based on the gene expression profiles GSE23006 and GSE21648 from the Gene Expression Omnibus database, and enrichment analysis of the DEGs was performed. And we found that a total of three differentially expressed genes (DEGs)-TFPI2, ELN, and TRIM32-were identified as key genes in the wound healing process. TRIM32 was selected for further study due to its high expression levels and significant variance in expression in an in vitro wound healing model. The overexpression of TRIM32 promoted skin fibroblast cells migration and epithelial-mesenchymal transition (EMT). Mechanistically, TRIM32 regulated the ubiquitination of PIAS1, leading to a reduction in PIAS1 protein expression. Additionally, TRIM32 has been shown to enhance wound healing by modulating PIAS1 expression. These findings highlight the beneficial role of TRIM32 in wound healing and tissue repair, suggesting that the TRIM32/PIAS1 axis may serve as a promising therapeutic target for enhancing wound healing.

RAD21, a key cohesin subunit, participates in chromatin regulation and may influence tumor metabolism and immunity. Its role in liver HCC remains unclear. We investigated whether RAD21 regulates PON1 and how this axis integrates metabolic and immune signals in HCC. Multi-omics integration (transcriptomic, ChIP-seq, and scRNA-seq) datasets to identify the RAD21-PON1 regulatory axis, with immune infiltration, metabolic remodeling, and prognostic impact assessed via GSVA, TIDE, and LASSO modeling. RAD21 upregulation inversely correlated with PON1 expression. RAD21 binds the promoter of PON1, impacting metabolic pathway activity and shaping the immune microenvironment. Low PON1 expression was linked to immunosuppressive patterns and poor prognosis. A RAD21-PON1 risk signature robustly stratified survival. Our findings highlight the RAD21-PON1 axis as a central regulator connecting metabolism and immunity in HCC, providing prognostic and therapeutic insights.

Poststroke depression (PSD) presents with persistent depressive symptoms and cognitive dysfunction. This study explored the regulatory mechanism of E2F2 in hippocampal neurogenesis in PSD. In a PSD rat model established by MCAO and CUMS, depressive behaviors (reduced sucrose preference, prolonged immobility time) and impaired hippocampal neurogenesis (decreased NeuN-positive cells and BDNF protein) were observed. BDNF, E2F2, CBR1, and miR-1290 were measured by WB and RT-qPCR. E2F2 enrichment on the miR-1290 promoter was assessed by Ch-IP assay. The bindings of E2F2 to the miR-1290 promoter and miR-1290 to the CBR1 3'-UTRwere validated using dual-luciferase reporter assays. Molecular analyses revealed that E2F2 was upregulated in PSD rats, and E2F2 knockdown alleviated depressive symptoms and neurogenesis deficits. Mechanistically, E2F2 bound to the miR-1290 promoter and enhance miR-1290 transcription, while miR-1290 targeted the 3'-UTR of CBR1 and suppress its expression. Rescue experiments confirmed that miR-1290 overexpression or CBR1 inhibition counteracted the neurogenesis-promoting effects of E2F2 knockdown. In conclusion, E2F2 inhibits hippocampal neurogenesis in PSD via the miR-1290/CBR1 axis, providing a potential therapeutic target for treating PSD.

Epigenetic rewiring modulates gene expression by reshaping chromatin architecture without altering the underlying DNA sequence. The eukaryotic genome is intricately folded within a dynamic three-dimensional nuclear architecture, which is vital for maintaining genomic integrity and ensuring spatially precise gene regulation. Long non-coding RNAs (lncRNAs), a class of regulatory transcripts, play a pivotal role in organizing nuclear structure, preserving cell identity, and sustaining complex regulatory networks. Through interactions with DNA, RNA, transcription factors, and chromatin-modifying complexes, lncRNAs influence the formation and maintenance of higher-order chromatin structures, including topologically associating domains (TADs), lamina-associated domains (LADs), and chromatin loops. These structural frameworks facilitate or constrain long-range genomic interactions, thereby governing transcriptional programs. Aberrant lncRNA expression disrupts this regulatory architecture and is increasingly recognized as a driving force in oncogenesis. Notable lncRNAs, such as XIST, HOTAIR, and MALAT1, modulate gene expression by recruiting epigenetic regulators, including Polycomb Repressive Complex 2 (PRC2), which alters histone modifications and DNA methylation landscapes, and rewires enhancer-promoter contacts. These mechanisms underlie profound transcriptional reprogramming in cancer cells. Technological advances in genome conformation capture methods (e.g., Hi-C, 3C) have enabled high-resolution mapping of these dynamic chromatin interactions, revealing the extent of lncRNA-mediated 3D genome remodeling in malignancy. This review synthesizes emerging evidence on the role of lncRNAs in shaping nuclear architecture and gene regulation, with a focus on their oncogenic and tumor-suppressive functions. By integrating insights into chromatin topology and epigenetic control, we underscore the potential of targeting lncRNAs and associated chromatin remodeling pathways as innovative diagnostic and therapeutic strategies in cancer and other complex diseases.

Hypopituitarism is a severe endocrine disorder characterized by a partial or complete hormone deficiency in the anterior or posterior pituitary gland. Current treatment relies on hormone replacement therapy, which is unable to mimic normal physiological circadian rhythm precisely, and long-term hormone replacement therapy can result in a variety of adverse effects. This study aimed to identify potential drug targets and clarify the mechanisms underlying hypopituitarism. To identify potential therapeutic targets for hypopituitarism, summary statistics from expression quantitative trait loci (eQTL) datasets, serum and cerebrospinal fluid (CSF) metabolites, and hypopituitarism genome-wide association study (GWAS) data were integrated for analysis. Two-sample Mendelian randomization (MR) analysis was performed to identify causal genes associated with hypopituitarism. Subsequently, the relationship between serum and CSF metabolites and hypopituitarism was investigated. Finally, a two-step MR analysis explored the mediation of these metabolites in the causal gene-hypopituitarism pathway, quantifying both direct and mediation effects. A total of 20 genes associated with hypopituitarism were identified, with RMI2, UBAC1, and GLIPR1 further validated by Bayesian colocalization, and the causal relationship between CHST13, GABPB1-AS1, GLIPR1L2, RNF14, and hypopituitarism was confirmed by summary data-based MR (SMR) and HEIDI analysis. Additionally, 34 serum metabolites and 8 CSF metabolites were causally associated with hypopituitarism. Furthermore, mediation MR analysis demonstrated that 1-Methyl-4-imidazoleacetate was the only mediator, explaining 4.35% (P = 0.049) of the total effect of UBAC1 on increased hypopituitarism susceptibility. This study identified RMI2, UBAC1, CHST13, GABPB1-AS1, GLIPR1L2, RNF14, and GLIPR1 as potentially causal genes in the pathogenesis of hypopituitarism. Furthermore, UBAC1-mediated regulation of serum metabolites may contribute to promoting hypopituitarism progression, indicating that UBAC1 is a candidate gene warranting further functional validation. Future directions could include assessing UBAC1 expression in pituitary/hypothalamus single-cell RNA-seq or in vivo models.

Cancer is the leading threat to human health and lifespan. Every day, the number of deaths caused by cancer continues to rise. Therefore, accurately predicting survivability from cancer has become an important area in cancer research. In predicting survivability, multi-omics data is advantageous as it provides information from different molecular levels of human biological processes, encompassing different omics such as genomics, epigenomics, transcriptomics, proteomics, and metabolomics. In this article we introduce a novel method called Attention-Enabled Hybrid Deep Sequential Network (AHDSN) which utilizes Long Short-Term Memory, Bidirectional Gated Recurrent Unit, and the attention mechanism to extract latent features from multi-omics data and Dense layers with softmax activation function for classification. Unlike conventional approaches that predict survival at a fixed time point (e.g., 5-year survival), the proposed AHDSN method predicts overall survival across the complete follow-up period using each patient's survival time and censoring status. We evaluated the proposed AHDSN method against several state-of-the-art approaches to assess their relative performance in survivability prediction from multi-omics data. To address class imbalance, both Random Oversampling (ROS) and Synthetic Minority Oversampling Technique (SMOTE) are applied during preprocessing to ensure a more balanced distribution of samples across classes. The experimental results show that the proposed AHDSN method surpassed other state-of-the-art methods in terms of accuracy, precision, recall, and [Formula: see text]-score across five multi-omics cancer datasets, Glioblastoma, Colon, Breast, Kidney, and Lung, achieving accuracies of 98.33%, 96.00%, 97.14%, 88.24%, and 80.00% when using ROS, and 97.12%, 96.00%, 96.22%, 85.18%, and 80.00% when using SMOTE respectively. Confidence Interval test also demonstrates the superiority of the proposed AHDSN method compared to other existing methods in producing the lowest error rate and the smallest error bound for all five multi-omics datasets. Additionally, SHapley Additive exPlanations analysis and heatmaps are employed to explain feature importance and illustrate how individual omics features contribute to model classification. Furthermore, the ablation study confirms the synergistic benefit of the proposed hybrid architecture and validates the importance of each component.

The MoG+ (Mouse Genome database with high added value), which has been operational since 2019, provides detailed visualization of genomic variations in mouse experimental strains, including wild-derived inbred strains, in particular those maintained at RIKEN BioResource Research Center. Here, we report on the enhancement of MoG+ by inclusion of the latest genome reports and by incorporation of structural variation (SV) information from recent analyses. The latter included long-read sequencing studies of the disease model strains FLS/Shi, NC/Nga, STR/OrtCrlj, JF1/Ms, and MSM/Ms. These studies described SNPs (4,482,628 to 19,644,769), short indels (726,646 to 2,391,782), and SVs such as insertions (32,949 to 131,311), deletions (28,259 to 102,226), and inversions (32 to 164). The new version of the database, which is named MoG+3.0, includes a feature that allows users to visually observe variants in the five strains. Through enhancement of the functionality of the database, SVs have been incorporated and visualized, allowing users to visually examine variants that were difficult to detect using only short-read-based resequencing data. The inclusion of the new variant data, along with enhanced features such as visualization, is expected to serve as a valuable resource for studies of disease and phenotype in experimental mice.

Mucopolysaccharidosis-plus syndrome (MPS plus or MPSPS) is an ultrarare inherited metabolic disease, caused by mutations in the VPS33A gene. Like in different types of mucopolysaccharidosis (MPS), glycosaminoglycan (GAG) storage in cells of patients is evident. However, unlike MPS, the genetic defects in MPSPS cause impairment in the VPS33A protein level rather than inactivation of lysosomal hydrolases responsible for GAG degradation. Recent works demonstrated that low abundance of mutated VPS33A causes defective endosomal trafficking, resulting in poor delivery of GAGs (and perhaps also other compounds) to lysosomes, preventing their effective turnover. Here, we tested the hypothesis that impairment of protein degradation machineries, proteasomes by genistein (5,7-dihydroxy-3-(4-hydroxyphenyl)-4H-1-benzopyran-4-one) and endoplasmic-reticulum-associated protein degradation (ERAD) by ambroxol (4-((2-amino-3,5-dibromophenyl)methylamino) cyclohexan-1-ol), might result in elevation of levels of the mutated, partially active VPS33A and improvement of cellular functions. Using a line of MPSPS patient-derived fibroblasts, we demonstrated that treatment with genistein and ambroxol resulted in elevation of the mutant VPS33A protein level, as well as in improvement or correction of various previously reported cellular defects, including GAG levels, endosomal markers, and cytoskeleton elements. In the light of these results, and since both genistein and ambroxol were previously demonstrated to be safe when used in relatively high amounts, we suggest that the use of these compounds, and especially their combination, might be considered as a potential therapeutic approach in MPSPS, which is currently an incurable disease.

Italy hosts a remarkable ovine biodiversity shaped by centuries of history, regional traditions, and environmental heterogeneity. This diversity sustains agricultural production as well as ecosystem services and cultural heritage. Yet, many local breeds are undergoing severe demographic decline. To explore these dynamics, we analyzed census data from all registered Italian sheep, which revealed highly variable situations across breeds but confirmed that most are currently at risk of extinction. To complement this picture, we genotyped 34 Italian sheep populations using the Ovine50K BeadChip and compared them with foreign breeds with recognized herd books in Italy. Genomic analyses of diversity (including inbreeding and effective population size), population structure, and genomic background provided insights into the state of genetic variation and relationships among breeds, including patterns of introgression. By comparing these results with data from populations sampled twenty years ago, we assessed temporal changes in diversity, genomic background, and selection signatures. Fst analyses highlighted genomic regions that have undergone the most marked shifts, allowing us to explore associated genes and QTLs. Correlations between Fst and environmental changes across 20 variables further emphasized the role of local adaptation in shaping genomic landscapes. In addition, local ancestry inference in two breeds (Gentile di Puglia and Nera di Arbus) with evidence of recent admixture identified genomic regions influenced by gene flow. Overall, our study illustrates the complex evolutionary dynamics of Italian sheep breeds and underscores the importance of integrating demographic analyses with genomic tools to guide their conservation and sustainable management.