Search Results (11,026)

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive stage of metabolic dysfunction-associated steatotic liver disease characterized by lipid dysregulation, oxidative stress, inflammation, and fibrosis. Because these processes occur simultaneously, compounds targeting multiple pathways may offer therapeutic benefit. Naringin, a citrus-derived flavonoid, has reported antioxidant and anti-inflammatory properties, but its integrated effects in MASH remain unclear. In this study, the effects of naringin were evaluated using combined in silico analysis and in vivo experiments. Network pharmacology and molecular docking predicted targets related to lipid metabolism, oxidative stress, inflammation, and fibrosis, which were validated in a methionine- and choline-deficient diet-induced mouse model. Naringin reduced hepatic lipid accumulation and improved serum AST and ALT levels. It modulated oxidative stress-related genes, attenuated inflammatory responses, and reduced fibrogenic markers. Naringin also decreased Ly6Chigh inflammatory monocytes and Kupffer cell activation, and reduced hypothalamic microglial activation. These findings suggest that naringin exerts multi-target effects across hepatic, systemic, and central pathways, supporting its potential as a therapeutic candidate for MASH. Full article

Fungal endophytes are symbiotic microorganisms that establish strong relationships inside plant tissues, providing potential advantages, especially in grasses, by enhancing tolerance to both abiotic and biotic stresses. This review investigates the molecular mechanisms through which fungal endophytes mediate stress tolerance, targeting host–pathogen interactions. By modulating pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), and effector proteins, fungal endophytes may contribute to priming the plant’s immune system, enhancing its resistance to pathogen invasion. Moreover, endophyte colonization regulates core processes such as osmotic regulation, reactive oxygen species (ROS) detoxification, and secondary metabolite biosynthesis that enable plants to tolerate environmental stresses like drought, heat, and salinity. The review highlights the impact of endophytes on immune priming, systemic acquired resistance (SAR), and the regulation of non-coding RNAs that regulate host gene networks associated with stress tolerance. Furthermore, the integration of advanced multi-omics techniques genomics, transcriptomics, proteomics, metabolomics, and fluxomics has revealed emerging insights into the genetic and metabolic pathways driving these symbiotic associations. However, grass-specific molecular datasets remain limited, and the consistency of endophyte-mediated tolerance across host species and environmental conditions is not yet fully resolved. Fungal endophytes increase grass stress resilience through coordinated pathogen recognition, RNA regulation, and metabolic reprogramming while AI-assisted multi-omics approaches are emerging as tools for identifying candidate regulatory networks, although empirical validation in grass–endophyte systems remains limited. Together, these advances highlight the potential for climate-smart and sustainable crop improvement. Future research integrating functional genomics, field validation, and biosafety assessment will be essential for translating endophyte-based strategies into reliable agricultural applications. Full article

Idiopathic inflammatory myopathies constitute a group of immune-mediated disorders primarily affecting skeletal muscle, but they may also lead to significant involvement of internal organs. These conditions are highly heterogeneous, encompassing diverse clinical manifestations and multiple underlying pathophysiological mechanisms. A unifying feature across this disease spectrum is an autoimmune response characterized by the production of highly specific autoantibodies, which are detected in the majority of patients. Genetic studies have identified the principal susceptibility background as the 8.1 ancestral haplotype within the HLA region on chromosome 6. However, genetic predisposition extends beyond HLA loci and includes numerous genes encoding key molecules involved in cytokine production, the regulation of immune signaling pathways, and metabolic processes. In this paper, we review the currently identified genetic loci associated with inflammatory myopathies, with particular emphasis on the HLA system, as well as non-HLA genes and newly identified candidates. Full article

Background/Objectives: Alzheimer’s disease (AD) remains a progressive neurodegenerative disorder with limited therapeutic options. This study aimed to develop an integrative multi-omics computational pipeline to identify diagnostic biomarkers and prioritize druggable therapeutic targets for AD. Methods: We integrated transcriptomic data from 1047 samples (547 AD, 500 controls) using weighted gene co-expression network analysis (WGCNA) and three machine learning algorithms (LASSO, Random Forest, SVM) with strict separation of training, feature selection, and evaluation. Single-cell RNA sequencing of 48,481 nuclei from entorhinal cortex, two-sample Mendelian randomization (MR) with Bayesian colocalization, and structure-based molecular docking with triplicate 500 ns molecular dynamics (MD) simulations were also employed. Results: Machine learning identified 10 consensus biomarker genes involved in synaptic vesicle cycling, ion transport, and calcium homeostasis (internal test AUC = 0.891, 95% CI: 0.836–0.946; external validation on GSE48350: AUC = 0.847, 95% CI: 0.798–0.896). Covariate-adjusted differential expression and MR with Bayesian colocalization converged on eight immune-related therapeutic targets including APOE, TREM2, and TYROBP ($p<0.05$; Bonferroni-corrected threshold $p<0.00625$). Single-cell analysis revealed oligodendrocyte expansion in AD (28.5% versus 24.8%), with target genes predominantly expressed in microglia and astrocytes. Virtual screening of 2634 FDA-approved drugs prioritized 10 exploratory repurposing candidates; indomethacin–TREM2 and celecoxib–CSF1R are primary exploratory candidates given structurally validated binding pockets. Triplicate MD simulations (15 $\mathsf{\mu }$s aggregate) showed force-field-consistent structural stability (RMSD ≤ 3.2 Å). A quantitative multi-omics convergence framework identified four Tier 1 targets (APOE, TREM2, TYROBP, CX3CR1) supported by ≥5 analytical layers ($P_{\mathrm{perm}}=0.0003$; note: three of five layers share the same transcriptomic input). Conclusions: These findings provide a multi-evidence computational framework linking diagnostic biomarkers and druggable neuroinflammatory targets for AD. All predictions require experimental validation in biochemical and cellular models before clinical conclusions can be drawn. Full article

Staphylococcus aureus remains a leading cause of morbidity and mortality worldwide, with persistent and relapsing infections posing a major global health threat. Here, we report that baloxavir, an FDA-approved influenza antiviral, exhibits antibacterial activity against S. aureus. Baloxavir demonstrated potent activity against both MSSA and MRSA clinical isolates with MICs of 2–4 μg/mL and exhibited concentration-dependent antibacterial activity in time-kill assays. Notably, baloxavir effectively eliminated intracellular S. aureus in both A549 alveolar epithelial cells and RAW264.7 macrophages at 10 μg/mL and achieved complete eradication in A549 cells at 50 μg/mL. In vivo, baloxavir (20–40 mg/kg) significantly improved survival in MRSA-infected mice from 12.5% to 75–87.5%. Transcriptomic analysis revealed significant downregulation of purine de novo biosynthesis genes, including purF and purK, which was validated by RT-qPCR (r = 0.862, p = 0.027). This study demonstrates for the first time that baloxavir possesses significant antibacterial activity against S. aureus including MRSA, positioning it as a promising repurposed candidate for treating persistent intracellular infections and post-viral superinfections. Full article

Dihydroflavonol 4-reductase (DFR) plays a pivotal role in regulating flavonoid and anthocyanin biosynthesis, governing the accumulation of plant secondary metabolites. This study aimed to characterize the DFR gene family in Ginkgo biloba and elucidate the function of the predominant gene GbDFR2 in the flavonoid metabolic network. Through transcriptome analysis, three differentially expressed GbDFR genes were identified. Bioinformatic analysis revealed that all three GbDFR proteins are hydrophilic and acidic and belong to the NADB_Rossmann superfamily. RT-qPCR analysis of different tissues of ginkgo revealed that all three GbDFR genes exhibited the highest expression levels in the leaves. An overexpression vector of GbDFR2 was constructed and stably transformed into Nicotiana benthamiana. Metabolomic and qPCR analyses showed that heterologous GbDFR2 expression significantly remodeled the flavonoid profile, upregulating sakuranetin and 3,7-Di-O-methylquercetin while downregulating narcissin and naringenin chalcone. Additionally, it upregulated endogenous NbCHI and NbDFR, and suppressed the transcription factors NbMYL2b and NbERF4a. These findings suggest that GbDFR2 can act as a regulator of flavonol biosynthesis and provide a candidate gene for the metabolic engineering of flavonoids in woody plants. Full article

Hyphantria cunea (Drury) causes extensive ecological damage primarily during its larval stages, characterized by voracious feeding and rapid dispersal. Given that conventional dsRNA-mediated RNA interference (RNAi) is generally recalcitrant in Lepidoptera, endogenous microRNAs (miRNAs) may represent an additional class of regulatory molecules worthy of systematic investigation. In this study, we utilized high-throughput sequencing to construct nine comprehensive miRNA libraries across three critical developmental milestones (three biological replicates per instar): the 1st, 4th, and 7th instars (L1, L4, and L7). A total of 1667 miRNA entries were catalogued, including 1080 known and 587 bioinformatically predicted, as yet unvalidated novel miRNA candidates. Comparative transcriptomic analysis revealed 52 differentially expressed miRNAs with significant stage-dependent profiles, with the most pronounced divergence observed between the L1 and L7 groups. Bioinformatic prediction identified 16,784 non-redundant target genes. GO and KEGG enrichment analyses indicated that the predicted target genes of these differentially expressed miRNAs were enriched in developmental and metabolic categories, including cellular development, protein digestion, and nutrient absorption, suggesting that these miRNAs may be associated with tissue remodeling and larval developmental transitions. Collectively, our findings expand the currently available miRNA resource for H. cunea and define stage-associated miRNA expression patterns during larval development. Rather than establishing direct functional roles, this work provides a framework and candidate molecules for future design of RNAi-based biopesticides. Full article

Modern cattle comprise two major evolutionary lineages: intensively selected commercial breeds and locally adapted native populations. To investigate their genomic divergence, we performed a comparative population genomic analysis by integrating whole-genome resequencing (WGS) data from multiple representative native breeds and major European commercial breeds. Population genetic analyses showed clear phylogenetic separation between the two groups, with distinct patterns of genetic diversity. Chinese native cattle exhibited generally higher nucleotide diversity (π), lower inbreeding levels, and geographically structured admixed ancestry. Comparative analyses of selection signatures identified 886 candidate selected genes in European commercial breeds, which were primarily enriched in pathways related to production traits, including protein turnover, reproductive regulation, lipid metabolism, and neuro-regulation. In contrast, 50 candidate selected genes in Chinese native cattle were significantly enriched in nervous system functions, particularly ligand-gated ion channel activity and chloride transport (e.g., GRID2, GLRA2/4, GABRD), suggesting neural/ionic regulation may contribute to local adaptation alongside other polygenic mechanisms. Additionally, the two groups also differed in patterns of deleterious mutation load. These findings indicate partially distinct evolutionary trajectories between “production-optimized” and “environment-adapted” cattle and highlight the value of conserving the genetic diversity and adaptive alleles of Chinese native cattle. Full article

Seed aging is a critical biological process that leads to progressive loss of seed vigor, thereby constraining germplasm conservation and agricultural productivity. To elucidate the molecular mechanisms underlying this process in grass species, we performed transcriptomic analyses to characterize regulatory networks underlying seed aging in Elymus sibiricus, a dominant forage species on the Qinghai–Tibet Plateau. Seeds were subjected to artificial accelerated aging (45 °C, 80% relative humidity, 1–6 days), followed by physiological evaluation and RNA sequencing. Seed vigor and germination percentage declined markedly with aging, accompanied by extensive transcriptional reprogramming. Integrative analyses identified pyruvate metabolism, MAPK signaling, and peroxisome function as key processes associated with vigor loss during late-stage aging. WGCNA further revealed that genes encoding heat shock proteins and glutathione metabolism-related enzymes were co-localized within the same module, suggesting a possible synergistic role in preserving seed viability during aging. In addition, WRKY24, ARF9, and ARF19 were identified as candidate hub transcription factors. WRKY24 may contribute to aging by modulating antioxidant defense-related genes (e.g., TRX1 and NRPC1), while ARF9 and ARF19 may regulate ROS homeostasis through predicted downstream targets, including FQR1, PER2, MAO1B, ANN5, and MT2B. Together, these findings support a hypothetical regulatory model in which WRKY and ARF transcription factors coordinate redox homeostasis and hormone signaling to regulate seed longevity in E. sibiricus. This study provides a systems-level framework for understanding seed aging in perennial grasses and identifies potential genetic targets for improving seed storability, with implications for germplasm conservation and alpine grassland sustainability. Full article

Both the productive efficiency and physical health of sika deer are strongly linked to their body conformation phenotypes. Breeding sika deer with excellent growth traits using molecular breeding technologies has become essential. Phenotypic data of 12 body conformation traits were measured for 613 sika deer across three age groups, including body traits and cephalic traits. Genetic typing was performed using the Sika Deer 100K SNP Liquid Chip, and genetic parameters were estimated through animal models to obtain the heritability and genetic correlation of traits within each age group. Single-trait and multi-trait GWASs were conducted, using GEMMA software to identify gene variants significantly associated with sika deer body conformation traits. Most of the 12 body conformation traits exhibited moderate to high heritability. The single-trait GWAS identified 49 SNPs (38 candidate genes), while multi-trait GWAS detected 134 SNPs (80 candidate genes), including 114 novel loci. A total of 163 SNPs and 196 candidate genes were identified, with 17 genes detected by both methods. These genes may be involved in pain perception, cell cycle regulation, immune response, and protein ubiquitination. Two significant KEGG pathways were enriched: steroid hormone biosynthesis and drug metabolism–cytochrome P450. Collectively, these detected loci and genes may serve as potential genetic resources for marker-assisted breeding, contributing to subsequent genetic improvement of body conformation in sika deer. Full article

Acute lymphoblastic leukemia (ALL) is a clinically diverse cancer in which microRNA (miRNA)-mediated post-transcriptional regulation contributes to leukemogenesis and subtype heterogeneity. In this study, miRNA expression profiling by microarray was performed on ALL cases (B-ALL and T-ALL) and healthy controls. Data were normalized and analyzed for differential expression using false discovery rate (FDR)-adjusted p-values. Differentially expressed miRNAs were further examined using unsupervised visualization to assess overall disease-related expression patterns. To explore their biological significance, experimentally validated miRNA–target interactions were obtained using multiMiR, limited to validated databases (miRTarBase, TarBase, and miRecords) and summarized via target-burden ranking, miRNA–target network analysis, and Circos–style interaction mapping. A unique miRNA expression signature was identified in ALL. Upregulated miRNAs included miR-106a-5p, miR-106b-5p, miR-17-5p, miR-20a-5p, miR-20b-5p, miR-181b-5p, and miR-128-3p, while miR-127-3p, miR-139-5p, miR-433-3p, and miR-584-5p were downregulated. Validated targets concentrated on key leukemia-related genes like PTEN, BCL2L11, CDKN1A, CCND1, RB1, E2F1, and TGFBR2. KEGG pathway analysis highlighted pathways associated with leukemic cell survival and growth, including MAPK, cell cycle, autophagy, Hippo, ubiquitin-mediated proteolysis, and mTOR signaling pathways. These findings reveal a concise ALL-associated miRNA panel predominantly comprising the miR-17/20/106 family and provide a prioritized set of candidate regulatory networks for subtype-specific validation and functional follow-up studies. Full article

Ovarian cancer (OC) remains the deadliest gynecological malignancy, with aged tumor microenvironments linked to poorer outcomes. Our prior work identified reduced levels of free fatty acids (FFAs) within tumor-surrounding adipose tissue of aged OC xenograft rats compared to younger counterparts. In this study, we investigated the therapeutic potential of one such FFA, punicic acid (PunA). We evaluated PunA’s effects on OC and normal cell viability and compared its activity with that of its structural isomer, α-eleostearic acid (α-ESA). Both compounds decreased OC cell viability; however, α-ESA was cytotoxic to normal cells, whereas PunA selectively impaired OC cell viability while sparing normal cells. Additionally, PunA enhanced cisplatin efficacy, demonstrating its potential for use in combination therapy to reduce cisplatin dosage and toxicity without compromising antitumor activity. Mechanistically, PunA induced ferroptosis in OC cells while sparing normal cells by differently modulating lipid peroxidation, fatty acid oxidation, and mitochondrial function. Transcriptomic profiling further revealed coordinated gene expression changes associated with oxidative stress and ferroptosis in PunA-treated OC and normal cells. In a preliminary C57BL/6J-ID8 OC mouse model, PunA suppressed tumor growth. Collectively, these findings identify PunA as a promising therapeutic candidate for OC, acting through ferroptosis and mitochondrial dysfunction, and enhancing cisplatin efficacy while sparing normal cells. Full article

Tibetan pigs are an important indigenous genetic resource on the Qinghai-Tibetan Plateau, but their population history remains unclear. Here, we analyzed whole-genome resequencing data from 29 Tibetan pigs and 69 wild boars from different regions to investigate their genetic structure and origin. Population structure analyses showed that Tibetan pigs formed a distinct genetic cluster, but clear substructure was present among the four Tibetan pig groups. Demographic analyses indicated that all Tibetan pigs shared a similar deep ancestral background, whereas the Tibetan population from Tibet (TT) showed a distinct recent demographic trajectory relative to the other Tibetan pig groups. Model inference based on multidimensional site frequency spectra further supported a mixed origin of TT from northern and southern Asian wild boar-related ancestral components. In contrast, the other three Tibetan pig groups were best explained as lineages derived from TT after its formation. We also detected a persistent western Eurasian-related excess-sharing signal in TT, consistent with potential introgression. Selection scans identified candidate genes and pathways potentially related to hypoxia adaptation, cardiovascular function, and lung development. Full article

Ankylosing spondylitis (AS) is a chronic immune-mediated inflammatory disease affecting the axial skeleton, characterized by progressive structural damage and functional impairment. Although biologic therapies targeting tumor necrosis factor and interleukin-17 have improved clinical outcomes, a substantial proportion of patients fail to achieve sustained disease control. Emerging evidence suggests that metabolic alterations may contribute to AS pathogenesis; however, systematic characterization of metabolism-related biomarkers and their regulatory networks remains limited, and the interplay between metabolic dysfunction and immune dysregulation in AS is poorly understood. Two whole-blood GEO datasets (GSE25101, GSE73754; n = 104) were integrated as the primary analytical cohort. A third dataset (GSE11886, n = 18; monocyte-derived macrophages) was included for exploratory cross-tissue analysis. Differential expression analysis identified 847 DEGs, which were refined to 16 metabolism-related genes through weighted gene co-expression network analysis (WGCNA) and GeneCards database filtering. Eleven machine learning algorithms with 5-fold cross-validation were applied to construct diagnostic models and identify hub genes. Validation analyses included immune cell infiltration estimation using CIBERSORT, metabolic pathway activity assessment via ssGSEA, single-cell transcriptomics from GSE268839, functional enrichment through GSEA/GSVA, and chromosomal localization analysis. A competing endogenous RNA (ceRNA) regulatory network was constructed to map post-transcriptional regulation. Natural compounds from 66 AS-treating traditional Chinese medicines were screened against hub genes using deep learning-based binding prediction. Multiple machine learning algorithms achieved comparable cross-validated performance (CV AUC range 0.741–0.836; top five models: 0.805–0.836) using the six hub genes (MFN2, SLC27A3, RHOB, SMG7, AKR1B1, LCOR) identified through SHAP-based feature importance analysis of the PLS model. Leave-one-dataset-out validation between the two whole-blood cohorts showed that all algorithms exceeded an AUC of 0.77 in Round 1 (validate: GSE73754, n = 72; best AUC 0.861), while Round 2 (validate: GSE25101, n = 32) yielded more modest performance (best AUC, 0.715) reflecting the smaller validation sample. Exploratory application to GSE11886 (macrophage-derived samples) showed near-chance performance, consistent with the tissue-source discrepancy. AS patients exhibited significant downregulation of oxidative phosphorylation, TCA cycle, and glycolysis pathways (p < 0.01), accompanied by elevated glutathione metabolism (p < 0.001). Immune cell deconvolution revealed reduced CD8+ T cell proportions correlating with MFN2 downregulation, and increased neutrophil frequencies correlating with SLC27A3 upregulation. Exploratory single-cell analysis indicated that RHOB expression was relatively enriched in border-associated macrophages and fibroblasts, while AKR1B1 was more prominently expressed in vascular endothelial cells and plasmacytoid dendritic cells. The ceRNA network identified 21 miRNAs and 65 lncRNAs forming 86 regulatory interactions, with four key regulatory axes (SATB1-AS1/miR-539-5p/LCOR, FAM95B1/miR-223-3p/RHOB, LINC01106/miR-106a-5p/MFN2, AATBC/miR-185-5p/SMG7) predicted to regulate hub gene expression. Compound screening identified betaine, pyruvic acid, citric acid, etc., as top-ranking candidates, with MFN2 showing the highest binding capacity among hub genes. This study provides an integrative framework linking metabolic reprogramming with immune dysfunction in AS. The six-gene diagnostic signature showed preliminary discriminatory ability in the available datasets, while the ceRNA regulatory network and natural compound screening results prioritize candidate regulatory pathways and compounds for future validation. These findings advance our understanding of AS pathogenesis and may guide future biomarker development and targeted intervention strategies. Full article

Honey and propolis from the stingless bees Tetragonula drescheri and Tetragonula pagdeni remain underexplored for their health-promoting application. This study investigated the bioactive compounds, and antiviral and anticancer activities of honey and propolis extracts against herpes simplex virus (HSV), and human papillomavirus (HPV-16/18)-positive cervical cancer cells. Water and ethanol extracts were prepared and evaluated for anti-HSV activity using plaque assay, and for anticancer effects on CaSki and HeLa cells using apoptosis, colony formation, cell migration, and candidate gene expression analysis. Propolis water extract most potentially inhibited HSV wild-type and drug-resistant strains. Propolis ethanol extract from T. drescheri markedly suppressed CaSki and HeLa cell growth, induced apoptosis, downregulated HPV-16/18 E6, and upregulated BAX expression. Chemical profiles were identified by electrospray ionization quadrupole time-of-flight mass spectrometry. Most candidate compounds displayed preferable drug-likeness properties. Prototype herbal soup formulations containing selected extracts significantly inhibited HSV-1 drug-resistant strain and HPV-16 E6 expression. These findings demonstrated the high antiviral and anticancer potential of the extracted compounds from T. drescheri and T. pagdeni propolis, supporting their application in health-promoting products against HSV and HPV infection. Full article