Search Results (840)

Ataxia-telangiectasia (A-T) is a multisystemic genetic disorder caused by pathogenic mutations in the ATM gene, with effects extending beyond the canonical DNA damage response. We investigated whether two compact ATM transcript variants, ATM 4-53 (exons 4 and 53 joined) and ATM SINT (an in silico-designed ATM variant), could rescue disease associated with cellular alterations and inform construct selection for future delivery strategies. A-T fibroblasts transduced with either ATM variants or an empty vector were compared with wild-type fibroblasts using complementary label-free and tandem mass tag-based quantitative proteomics. Bioinformatic pathway and network analyses were integrated with biochemical and functional validation assays. A-T fibroblasts displayed coordinated alterations in proteostasis, proteasome function, RNA processing pathways, interferon-associated signaling, extracellular matrix organization, cell migration, and nanomechanical properties. Expression of both ATM variants partially or extensively reversed these abnormalities, restoring protein folding and proteasomal components, reducing protein aggregation, attenuating inflammatory signaling, and normalizing extracellular matrix-related phenotypes. ATM SINT generally produced the broader and more consistent rescue, particularly for proteostasis and RNA processing-associated networks. These findings show that compact ATM variants can recover multiple non canonical ATM dependent cellular functions in A-T fibroblasts and identify ATM SINT as the more effective construct in this model. Proteomic profiling combined with orthogonal functional validation may therefore support rational selection of ATM variants for subsequent preclinical delivery studies. Full article

Background: Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) primarily participates in protein synthesis by binding aminoacyl-tRNA complexes to facilitate peptide chain elongation on ribosomes. Its expression and functional roles exhibit significant heterogeneity across various malignancies, exerting dual regulatory effects as both an oncogene and a tumor suppressor. This study aims to investigate the potential prognostic value and tumor-suppressive role of EEF1A1 in kidney renal clear cell carcinoma (KIRC). Methods: We analyzed the differential expression of EEF1A1 in KIRC and its correlation with patient prognosis based on the TCGA, GEO, and HPA databases. The STRING and GEPIA databases were utilized to perform functional enrichment analysis of its interacting proteins and co-expressed genes. The xCell algorithm was employed to assess the correlation between EEF1A1 and immune cell infiltration, immune checkpoints, and immunomodulatory molecules. Furthermore, drug sensitivity analysis was conducted to evaluate its clinical application potential. Finally, the expression of EEF1A1 in 786-0 and A498 cell lines was validated via qRT-PCR and Western blotting. Furthermore, CCK-8, wound healing, and Transwell migration/invasion assays were performed to evaluate cell proliferation, migration, and invasion, respectively. Results: EEF1A1 may function as a negative regulator of malignant behaviors in KIRC tissues and cell lines, and its expression level was closely associated with clinicopathological features and prognosis of patients. GO, KEGG, and GSEA enrichment analyses revealed that low EEF1A1 expression is closely linked to immunosuppressive pathways. Further immunological analysis confirmed significant correlations between EEF1A1 and various immune cell infiltrates, immune checkpoints, tumor-infiltrating lymphocytes, and immunomodulatory molecules. Moreover, cells with high EEF1A1 expression exhibited increased sensitivity to anti-tumor drugs, with expression levels negatively correlated with inhibitory activity (IC50). Finally, overexpression of EEF1A1 significantly inhibited the proliferation, migration, and invasion of clear cell renal cell carcinoma cells. Conclusions: EEF1A1 serves as a potential prognostic biomarker in KIRC and is associated with clinical progression, immune-related characteristics, metabolic pathways, and drug sensitivity. Functional validation further supports its role in regulating malignant phenotypes of KIRC cells. Full article

Cervical cancer remains a major cause of cancer-related mortality worldwide, highlighting the need for strategies that may improve responses to conventional chemotherapeutics. Epigallocatechin gallate (EGCG), a green-tea polyphenol with diverse biological activities, has been investigated as a potential chemosensitizing agent. This study evaluated the interaction between EGCG and doxorubicin (DOX) in HeLa cervical cancer cells, with HaCaT keratinocytes included as a non-malignant comparator. Cell viability and drug interactions were assessed using the CCK-8 assay and Chou–Talalay combination index (CI) analysis. Complementary assays evaluated membrane integrity, wound closure, apoptosis, cell-cycle distribution, intracellular DCF-associated fluorescence with or without N-acetylcysteine (NAC) pretreatment, caspase-3 immunoreactivity, and EGFR, FOXP3, CASP3, and CASP7 mRNA expression. Network-based analyses were additionally used to identify candidate molecular associations and pathways. CI analysis demonstrated synergistic EGCG–DOX interactions in HeLa cells under the tested conditions, whereas additive or antagonistic interactions predominated in HaCaT cells. Combined treatment produced the greatest reduction in viable cells, increased apoptosis, altered cell-cycle distribution, and reduced wound closure. It also produced the highest viability-normalized DCF-associated fluorescence, which was attenuated by NAC pretreatment, indicating an antioxidant-sensitive change in intracellular oxidative status without establishing a causal role in cytotoxicity. Combined treatment was further associated with increased total caspase-3 immunoreactivity and altered EGFR, FOXP3, CASP3, and CASP7 transcript levels. Overall, EGCG and DOX exhibited synergistic interactions and multiple treatment-associated cellular and transcriptional responses in HeLa cells under the present in vitro conditions. These findings do not establish cancer-specific selectivity or a definitive molecular mechanism but provide a basis for validation in additional cervical cancer models and at clinically relevant exposures. Full article

Objective: This study established a rat model of lipopolysaccharide (LPS)-induced acute lung injury (ALI) to evaluate pathological damage, collagen deposition, inflammatory cytokine levels, and key gene/protein expression following Hedyotis diffusa water extract (HDWE) intervention. Combined with ultra-high-performance liquid chromatography-quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS), transcriptomic analysis, and molecular simulation, this study identified the bioactive components of HDWE, evaluated their potential interactions with ALI-related targets, and explored the multi-omics-based protective mechanisms of HDWE. Methods: Thirty-six Sprague–Dawley (SD) rats were randomly divided into six groups: Control group, ALI group, DXMS group, HDWE-L group (100 mg/kg), HDWE-M group (200 mg/kg), and HDWE-H group (300 mg/kg). Hematoxylin and eosin (H&E) and Masson’s trichrome staining were used to evaluate lung pathological changes and collagen deposition. Enzyme-linked immunosorbent assay (ELISA) was used to measure serum tumor necrosis factor-α $\mathrm{T}\mathrm{N}\mathrm{F}-\mathsf{\alpha }$ interleukin-1β $\mathrm{I}\mathrm{L}-1\mathsf{\beta }$, erleukin-6 (IL-6), and interleukin-10 (IL-10) levels. Transcriptomic analysis identified differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), receiver operating characteristic (ROC), and immune infiltration analyses. Quantitative real-time polymerase chain reaction (qRT-PCR) detected the mRNA expression levels of SPHK1, RELA, and NFKBIA. Immunohistochemistry evaluated the expression of eight hub targets, including endothelin-1 (EDN1), sphingosine kinase 1 (SPHK1), intercellular adhesion molecule 1 (ICAM1), interleukin-17 (IL-17), prostaglandin-endoperoxide synthase 2 (PTGS2/COX-2), NF-κB p65 (encoded by RELA), WT1-associated protein (WTAP), and myeloperoxidase (MPO). UHPLC-Q-Orbitrap HRMS characterized HDWE constituents. Molecular docking analysis was performed between 22 compounds and eight hub targets, followed by 100 ns molecular dynamics simulations and molecular mechanics-Poisson–Boltzmann surface area (MM/PBSA) binding free energy calculations for five core targets. Compared with the control group, the ALI group showed increased levels of TNF-α (86%), IL-1β (107%), and IL-6 (66%), accompanied by a 43% reduction in IL-10 and a 300% increase in lung collagen deposition. All HDWE doses alleviated inflammatory responses, with medium-dose HDWE showing the most pronounced effects. Specifically, medium-dose HDWE increased IL-10 levels by 52% and reduced IL-6, TNF-α, and IL-1β levels by 18%, 22%, and 11%, respectively. Transcriptomic analysis identified 2512 DEGs between the control group and ALI groups, 832 exclusive DEGs between the ALI group and HDWE-M groups, and 876 overlapping DEGs enriched in TNF, IL-17, and NF-κB signaling pathways. The eight-hub-gene diagnostic model achieved an area under the curve (AUC) of 0.969. RELA, SPHK1, and four other hub genes showed positive correlations with Th1, Th17, and neutrophil infiltration. In the ALI group, SPHK1, RELA, and NFKBIA mRNA expression levels were 1.30-, 0.96-, and 0.71-fold of those in the control group, respectively. Compared with the ALI group, high-dose HDWE treatment and low-dose HDWE treatment reduced SPHK1 expression to 0.62- and 0.57-fold, respectively, and increased NFKBIA expression to 1.68- and 1.58-fold, respectively. High-dose HDWE treatment reduced RELA expression to 0.43-fold. The expression levels of inflammation-related proteins were increased in the ALI group and were reduced after HDWE treatment. Twenty-two HDWE components were identified, 16 of which met the docking criteria. Asperulosidic acid exhibited favorable predicted binding affinities with all eight targets, with calculated binding free energies of −14.74, −14.92, −17.58, −23.04, and −16.10 kcal/mol for MPO, IL-17, NF-κB p65, PTGS2/COX-2, and SPHK1, respectively. Conclusions: This study provides systematic in vivo pharmacodynamic and in silico component-target evidence regarding the protective effects of HDWE against LPS-induced ALI. HDWE treatment increased NFKBIA expression and reduced SPHK1, RELA, and multiple inflammatory protein levels, suggesting that HDWE may regulate the IL-17/NF-κB-associated inflammatory network, although direct causal relationships require further validation. Asperulosidic acid may represent a key bioactive component with broad target-binding potential. This study was limited by the use of an LPS-induced rat ALI model without gene knockout or target inhibitor validation; therefore, further functional experiments are required to confirm the proposed regulatory mechanisms. Full article

Excessive body fat deposition during pregnancy is believed to have an adverse effect on the reproductive performance of sows. Feed intake regulation (REG) is an effective method to modulate energy intake and fat deposition. This study aimed to explore the impact of feed intake and body fat deposition on reproductive performance. A total of 24 Shaziling sows (parity 3–6) were divided into two groups based on their BF on day 30 of gestation, and subsequently randomly assigned to control (CON) and REG groups: (1) BF between 12 and 16 mm (LB-CON, n = 6), (2) BF between 12 and 16 mm (LB-IF, n = 6), (3) BF between 18 and 22 mm (HB-CON, n = 6), and (4) BF between 18 and 22 mm (HB-RF, n = 6). Sows in the LB-CON and HB-CON groups were fed a basic diet at a dosage of 1.88 kg/d. The LB-IF and HB-RF groups received REG and were fed a basic diet at dosages of 2.07 kg/d and 1.69 kg/d, respectively. Higher total litter weight and live litter weight were observed in HB-RF sows (p < 0.05). In addition, HB-CON sows displayed higher serum levels of IL-6, TG, and GLU when compared with LB-CON sows (p < 0.05), whereas HB-RF sows exhibited lower levels of these markers than HB-CON sows (p < 0.05). The lipid droplet area fraction was higher in HB-CON sows than in LB-CON sows (p < 0.05), and this fraction was reduced in HB-RF sows compared with HB-CON sows (p < 0.05). The placental level of TC increased in HB-CON sows when compared with LB-CON sows (p < 0.05). The placental levels of T-AOC and GPX increased in HB-RF sows when compared with HB-CON sows (p < 0.05). Moreover, the mRNA expression of FABP3 was higher in HB-CON sows when compared with LB-CON sows (p < 0.05). The mRNA expression of GLUT3 and PlGF increased in HB-RF sows when compared with HB-CON sows (p < 0.05). In addition, HB-RF sows exhibited increased Shannon, Simpson, and ACE indices when compared with HB-CON sows (p < 0.05). The characterization of the fecal microbiota revealed that HB-RF sows displayed a lower ratio of Firmicutes/Bacteroidota and an increased relative abundance of Limosilactobacillus when compared with HB-CON sows (p < 0.05). Collectively, these observations suggested that reduced feed intake in Shaziling sows with high backfat thickness improved reproductive indices, alleviated placental oxidative stress and inflammatory status, elevated placental nutrient transport and angiogenesis-related gene expression, and reshaped fecal microbiota. These results provide valuable reference for pig production. Full article

Morels (Morchella spp.) are highly valued edible fungi, but their cultivation remains largely dependent on seasonal field conditions. In this study, we established a stable off-season industrial cultivation system for Morchella eximia G10 through precise environmental regulation, including substrate and ambient temperature, humidity, and irrigation management. Based on this controllable cultivation platform, integrated transcriptomic and metabolomic analyses were conducted to explore developmental reprogramming from vegetative growth to fruiting body maturation. Metabolomic profiling was performed only at the reproductive stages, whereas transcriptomic analysis covered both vegetative and reproductive stages. Low-temperature stimulation was associated with marked increases in the expression of genes involved in cell wall remodeling, carbohydrate metabolism and stress responses, together with downregulation of genes annotated with oxidoreductase- and hydrolase-related functions. The transition to the primordium stage represented the most dynamic developmental transition and was associated with transcriptional regulation, cytoskeletal organization, and signal transduction pathways. Subsequently, distinct developmental trajectories were observed between pileus and stipe tissues, suggesting tissue-specific regulatory programs during fruiting body maturation. In the pileus, early amino acid- and nitrogen-related metabolism was coordinated with transcriptional changes, followed by a shift toward carbon and lipid metabolism. In the stipe, early development featured elevated aminoacyl-tRNA biosynthesis and translational capacity, followed by later adjustments in carbon, sulfur and lipid metabolism. These results provide a tissue-resolved multi-omics view of developmental reprogramming during the cold-treatment-associated transition from vegetative growth to fruiting in Morchella under controlled off-season cultivation. By linking environmental cues with stage- and tissue-specific transcriptional and metabolic programs, this work provides additional insights into reproductive development and extends previous descriptive omics studies, while offering a molecular basis for optimizing environmental regulation and improving the stability of industrial morel production. Full article

Background/Objectives: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited targeted therapeutic options. Although the anticancer and pro-apoptotic properties of boswellic acids have previously been reported, the interaction profile of chemically defined β-boswellic acid (BA) with doxorubicin (DOX) remains insufficiently characterised in the murine 4T1 TNBC-like model. This study quantitatively evaluated BA–DOX drug interactions using different reference models and characterised the cytotoxic and apoptosis-associated cellular phenotype accompanying combined exposure. Methods: Cytotoxicity was assessed using the MTT assay and BA–DOX interactions were evaluated using the Chou–Talalay combination index (CI), highest single-agent (HSA) and Bliss independence models. Apoptosis and cell-cycle distribution were analysed by flow cytometry and mitochondrial membrane potential was assessed by JC-1 staining. Caspase-3/7 activity, RT-qPCR, live/dead Calcein-AM/PI staining, 4′,6-Diamidino-2-phenylindole (DAPI) nuclear staining, and cytokine measurements were also performed. Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), and STRING-based protein–protein interaction (PPI) analyses were used to explore putative molecular pathways associated with experimental findings. Results: The 48 h selectivity index of BA was 1.28, indicating only modest differential cytotoxicity between 4T1 cells and HaCaT keratinocytes under the experimental conditions rather than definitive cancer-cell selectivity. Drug-interaction analyses revealed concentration- and model-dependent effects, with the Chou–Talalay analysis indicating synergism in selected intermediate and higher concentration pairs. Under the selected phenotypic-characterisation condition, BA + DOX produced a greater apoptotic response than either single treatment, accompanied by increased G2/M and Sub-G1 fractions, mitochondrial membrane depolarisation, and increased caspase-3/7 activity. This treatment condition was not included in the drug-interaction analysis and was therefore not interpreted as a pharmacologically validated synergistic combination. RT-qPCR demonstrated increased mRNA expression of Bax, Casp3, and Casp9, decreased mRNA expression of Bcl2, and a marked increase in the Bax/Bcl2 mRNA ratio. Calcein-AM/PI and DAPI analyses further demonstrated increased cell death and apoptotic nuclear alterations. The measured concentrations of TNF-α and IL-6 in culture supernatants were lower after BA + DOX treatment, whereas IL-10 remained unchanged; however, these cytokine measurements were not normalised to viable cell number and therefore require cautious interpretation. Exploratory bioinformatic analyses identified predicted associations with apoptosis-, mitochondrial-, and cell-cycle-related processes and pathways; however, these database-derived findings were considered hypothesis-generating and not evidence of BA-dependent target engagement or pathway activation. Conclusions: Combined BA and DOX exposure produced greater cytotoxic and apoptosis-associated responses than either single treatment in 4T1 cells, whereas formal drug-interaction classifications varied according to concentration and analytical model. The accompanying changes in mitochondrial membrane potential, caspase-3/7 activity, and apoptosis-related gene expression describe a treatment-associated cellular phenotype but do not identify a direct molecular target of BA or establish a causal molecular mechanism. The findings also do not demonstrate TNBC-specific selectivity. Further studies using additional breast cancer and tissue-matched non-malignant models, together with direct target-engagement and functional pathway-validation approaches, are required. Full article

Neoadjuvant chemotherapy (NAC) is the standard of care for locally advanced breast cancer, yet the molecular predictors of pathological response remain incompletely defined, particularly regarding microRNA (miRNA) dynamics. We investigated paired pre- and post-NAC miRNA expression profiles in relation to molecular subtype, residual cancer burden (RCB), and clinical timing parameters. Seven patients with invasive breast cancer (Luminal A n = 3, Luminal B n = 1, TNBC n = 2, HER2+ n = 1) who received NAC (AC-T or TCHP) were included in this pilot study. Small-RNA sequencing (NovaSeq X Plus, CeGaT GmbH, project S17293) was performed on 14 FFPE specimens (7 pre-NAC core needle biopsies, 7 post-NAC surgical specimens). Differential expression analysis used the paired Wilcoxon signed-rank test with Benjamini–Hochberg correction. Spearman correlations assessed associations between miRNA expression, RCB score, and clinical timing intervals. Candidate miRNAs were subsequently annotated using experimentally validated miRNA–target interactions. After filtering (≥ three counts in ≥ three samples), 759 miRNAs were analysed. No miRNA reached strict significance (padj < 0.05, |log₂FC| > 1.0) after multiple testing correction, consistent with the limited statistical power (n = 7). Under exploratory criteria (p < 0.10, |log₂FC| > 0.5), 156 candidate miRNAs were identified: 70 upregulated and 86 downregulated post-NAC. Leading candidates included hsa-miR-139-3p (+2.60), hsa-miR-139-5p (+2.36), and hsa-miR-1323 (+1.55) as upregulated, and hsa-miR-429 (−2.53), hsa-miR-141-3p (−1.79), and hsa-miR-1277-5p (−1.25) as downregulated post-NAC. The single patient achieving the lowest residual disease burden (P3, Luminal B, RCB-I, score 1.32) displayed a distinct pre-treatment miRNA profile, separating from all other pre-NAC specimens on principal component analysis and characterised by higher baseline hsa-miR-139-3p/-5p and lower baseline hsa-miR-429 and hsa-miR-141-3p expression, suggesting that baseline miRNA expression patterns may contribute to differential chemotherapy response. RCB score showed a non-significant positive trend with post-NAC Ki-67 (ρ = +0.71, p = 0.07). This pilot study identifies NAC-modulated candidate miRNAs in breast cancer and establishes a paired FFPE-based small-RNA-sequencing workflow applicable in routine clinical settings. The distinct pre-treatment profile of the single best responder generates the testable hypothesis that baseline expression of tumour suppressor miRNAs of the miR-139 family, together with low miR-200-family expression, may track chemosensitivity. As no candidate reached statistical significance after multiple testing correction and none has been validated in an independent cohort or by an orthogonal method, all findings are exploratory and hypothesis-generating. The results support larger prospective validation studies examining miRNA signatures as predictive biomarkers of NAC response across breast cancer molecular subtypes. Full article

Background/Objectives: Breast cancer exhibits substantial molecular heterogeneity, resulting in diverse therapeutic vulnerabilities and limiting the efficacy of single-agent therapies. Although multi-target strategies may offer improved therapeutic benefit, the systematic identification of synergistic higher-order target combinations remains challenging. This study aimed to identify and validate effective higher-order target combinations for heterogeneous breast cancer. Methods: DeepMDS, a previously developed deep learning-based multi-compound synergy prediction model, was used to prioritize candidate target combinations for breast cancer. Exhaustive two-target and three-target combinations were ranked in the gene-expression contexts of ER-positive luminal-like MCF-7 and triple-negative MDA-MB-231 breast cancer cells. The top-ranked target combinations were evaluated using single, pairwise, and triple small interfering RNA (siRNA) perturbations. Representative inhibitors were subsequently assessed in fixed-ratio combinations in MCF-7, MDA-MB-231, and 4T1 cells and in a 4T1 syngeneic mouse experiment. Results: BIRC5-NAMPT-TOP1 ranked first in both cell lines. Triple siRNA co-transfection targeting BIRC5, NAMPT, and TOP1 produced the strongest antiproliferative effects, with inhibition rates of 62.94% in MCF-7 cells and 55.62% in MDA-MB-231 cells. The corresponding inhibitors, LQZ-7I, FK866, and topotecan, exhibited synergistic antiproliferative activity at multiple molar ratios, with combination index values below 1. The optimized 2.5:10:1 molar ratio showed strong synergy in MCF-7, MDA-MB-231, and 4T1 cells, with combination index values of 0.26, 0.19, and 0.15, respectively. In tumor-bearing mice model, the triple-inhibitor regimen achieved a tumor inhibition rate of 62.05%. Topotecan-containing groups showed hematological alterations, whereas no statistically detectable elevations were observed in the measured terminal serum hepatic or renal biomarkers. Conclusions: The BIRC5-NAMPT-TOP1 combination showed reproducible phenotypic activity in the tested genetic and pharmacological models. These findings support the use of DeepMDS as a hypothesis-generation tool for higher-order target prioritization. Full article

Background: Prostate cancer (PCa) is a leading cause of cancer-related mortality worldwide, highlighting the need for improved prognostic tools. The integration of artificial intelligence (AI) and machine learning (ML) with multi-omics data offers new opportunities for biomarker discovery and risk stratification. Methods: We integrated bulk transcriptomic data from GSE116918 (training, n = 248) and three cross-cohort consistency evaluation cohorts (TCGA-PRAD, GSE70769, GSE46602), focusing on 1087 epithelial–mesenchymal transition (EMT)-associated genes. Using consensus clustering, weighted gene co-expression network analysis (WGCNA), and 91 machine learning algorithm combinations (including Random Forest, Lasso, and CoxBoost), we constructed a prognostic signature. SHAP analysis was used for model interpretability. Single-cell RNA sequencing (scRNA-seq, GSE268307, 10,672 cells) and spatial transcriptomics (10× Genomics Visium FFPE) provided hypothesis-generating evidence; spatial analysis was based on one tissue section. Results: A three-gene signature (INHBA, FAP, ITGBL1) effectively stratified patients into high- and low-risk groups, with the high-risk group showing significantly worse metastasis-free survival (HR = 1.61, 95% CI: 1.39–1.87; 4-year AUC = 0.93 in the training cohort; external AUCs ranged from 0.62 to 0.77). CytoTRACE inferred high differentiation potential of COMP+ fibroblasts, and Monocle3 inferred a transcriptional transition from COMP+ toward NELL2+ fibroblasts. BayesPrism deconvolution suggested that high inferred COMP+ fibroblast abundance was associated with poor prognosis and advanced T stage. NicheNet analysis prioritized BMP7 as a key upstream ligand, with downstream targets enriched in TGF-β signaling and stem cell pluripotency pathways. Conclusions: This study presents a machine learning-based multi-omics framework for prostate cancer risk stratification. The three-gene signature provides a new exploratory prognostic model while inferring a COMP+ to NELL2+ transcriptional transition. These findings may inform future hypothesis-driven studies of treatment sensitivity, pending experimental validation, and demonstrate the value of AI-driven multi-omics integration for precision oncology. Full article

Background/Objectives: L1 cell adhesion molecule (L1CAM) has been implicated in colorectal cancer progression, but its cellular source and immune microenvironmental context remain incompletely defined. This study aimed to characterize the expression pattern, cellular localization and immune-associated features of L1CAM in colorectal cancer using public bulk and single-cell datasets. Methods: TCGA, GTEx and CPTAC/UALCAN datasets were used to assess L1CAM expression, protein abundance and clinical associations across cancers, with a focus on colorectal cancer. Single-cell RNA sequencing data from GSE178341 were analyzed to identify L1CAM-expressing cell populations, characterize transcriptional programs and evaluate sample-level associations with immune-cell composition and T/NK cytotoxicity signatures. Candidate ligand-receptor interactions and conceptual mod el-based sensitivity analyses were used to explore stromal-immune communication axes. Supplementary external single-cell datasets were analyzed exploratorily. Results: In colorectal cancer, L1CAM showed tumor-normal expression differences and was associated with progression-free interval, but not overall survival. Single-cell analysis detected L1CAM mainly in rare fibroblast and epithelial subsets rather than T/NK cells. L1CAM-positive fibroblasts showed neural-like, wound-response and matrix-remodeling transcriptional features. In the main cohort, L1CAM-Fib+ samples showed lower T/NK cytotoxicity transcriptional signatures, whereas supplementary external datasets did not reproduce the same direction of association. Candidate communication analyses nominated Galectin, HLA-E, TGFB and extracellular matrix-related axes. Conclusions: These findings suggest that L1CAM-positive fibroblast-associated stromal states provide a dataset-specific exploratory context for interpreting L1CAM-associated immune features in colorectal cancer. The results should be considered hypothesis-generating and require spatial and functional validation. Full article

A secreted protein toxin encoded by a satellite dsRNA-enabled dissection of the genetic control of replication and expression of a single-segment dsRNA virus, the first Totivirus, L-A. Among the then-novel findings were i. “head-full replication”, ii. a supposedly forbidden “T = 2” capsid symmetry based on an asymmetric dimer, iii. a host N-acetyltransferase whose modification of the coat protein is necessary for packaging, iv. Kex1 and Kex2 pro-toxin peptidases leading to discovery of the pre-pro-insulin processing enzymes, and v. specific viral (+) strand sites/structures needed for RNA packaging and (-) strand synthesis. L-A viral (+) strands made in the particle are extruded to the cytoplasm. Those destined for translation are 5′ 7meGMP-capped by a coat protein activity that steals the cap from cellular mRNAs. (+) strands destined for encapsidation in new coats are not capped. Three host-encoded anti-viral systems were found, one based on blocking translation of the viral non-polyA mRNAs (Ski2,3,8 complex), another a 5′->3′ exoribonuclease specific for uncapped molecules (such as the viral (+) strands)(Ski1/Xrn1), and the third a mitochondrial nuclease released in cells undergoing meiosis/sporulation (Nuc1). All of these systems protect cells from virus-induced pathology and have clear animal homologs. The 3′ polyA of yeast mRNAs is dispensable for translation in ski2Δ slh1Δ cells, and such cells are healthy unless the L-A and M dsRNAs are present, suggesting that this polyA is primarily a device allowing cells to distinguish viral and cellular mRNAs. We suggest that the ribosome-associated Ski2,3,8 proteins block 60S subunit joining on polyA⁻ mRNAs. Recent evidence of roles for other cellular components controlling viral expression and replication suggests that yeast viruses will continue to be a fertile area for study of viral pathogenesis and host anti-viral systems. Full article

Malaria pathogenesis involves complex immunopathological mechanisms that hinder early diagnosis and effective treatment. This study integrates multi-omics data and experimental models to identify host-derived biomarkers and elucidate their functional roles. By combining human transcriptomic datasets, weighted gene co-expression network analysis (WGCNA), and machine learning (LASSO, SVM, RF), we identified C1QB as a key hub gene. In human data, C1QB was significantly upregulated in both training and validation cohorts (AUC 0.983 and 0.970). Single-gene GSEA and immune infiltration analyses linked C1QB to apoptosis, inflammation, and altered immune cell composition, including increased activated dendritic cells and neutrophils, and decreased naïve B cells and CD8⁺ T cells. In a murine malaria model (Plasmodium berghei ANKA), C1QB expression rose as early as day one post-infection, preceding detectable parasitemia. Immunohistochemistry revealed C1QB accumulation in the liver and spleen. Single-cell RNA sequencing in the murine model confirmed monocyte-predominant expression, and scTenifoldKnk analysis suggested its role in immune regulation. Crucially, inhibiting C1q in mice via antibody intervention alleviated malaria-induced inflammation, tissue damage, and apoptosis, indicating that C1QB/C1q actively contributes to immunopathology. AI-based drug prediction and molecular docking further supported its therapeutic potential. Collectively, our findings establish C1QB as a dual biomarker and pathogenic driver in malaria, with diagnostic and therapeutic implications. Further studies are required to validate direct target engagement and clarify upstream regulatory mechanisms. Full article

Background: Male sterility is a critical trait for large-scale hybrid rice seed production, yet the genetic and molecular regulatory networks governing tapetal degradation during anther development remain incompletely understood. This study aimed to clone the causal gene underlying a novel rice non-pollen male sterility mutant and elucidate its role in tapetal development and microsporogenesis. Methods: The nms1 (non-pollen male sterility 1) sterile mutant was screened from the ethyl methanesulfonate (EMS)-mutagenized progeny of the elite indica restorer line Shuhui 498 (R498). Map-based cloning and whole-genome resequencing-assisted bulked segregant analysis were used to identify the causal variant. Gene function was verified via cytological observation, genetic complementation testing, RNA sequencing, and quantitative real-time PCR (qRT-PCR) to profile sterility-associated transcriptional changes. Results: Gene mapping identified a T635A single-nucleotide substitution within OsR498G0305626400.01 on chromosome 3, which encodes a strictosidine synthase-like protein. This nucleotide alteration causes a Val212Glu amino acid change and is associated with delayed tapetal degradation and pollen abortion. Transgenic complementation experiments verified that functional NMS1 restores fertility in nms1 mutant plants. Spatiotemporal expression analysis showed predominant NMS1 expression in late-developing spikelets. Furthermore, combined RNA sequencing and qRT-PCR analyses demonstrated that loss of NMS1 function leads to significant transcriptional dysregulation of key regulators of programmed cell death (PCD) in the tapetum (PTC2, TIP2) and pollen wall biosynthesis genes (TIP3, OsMS2). Conclusions: This study demonstrates that NMS1 plays a crucial role in coordinating tapetal degradation and microspore development in rice. The discovered functional SNP of NMS1 provides a novel theoretical foundation and a valuable sterile genetic resource for hybrid rice breeding. Full article

Persistent racial and ethnic disparities in type 2 diabetes mellitus (T2DM) are incompletely explained by genetic susceptibility, obesity, lifestyle, and socioeconomic factors, suggesting that additional biological mechanisms may link environmental exposures to metabolic disease risk. Increasing evidence indicates that the exposome, encompassing environmental exposures across the life course, may influence long-term metabolic health through molecular mechanisms that integrate environmental signals with host biology. This Review synthesizes epidemiological, experimental, and mechanistic evidence on the gut microbiota–host epigenetic axis and its potential role in linking environmental exposures to population differences in T2DM susceptibility. Gut microbial dysbiosis alters the production and metabolism of short-chain fatty acids, bile acids, and tryptophan-derived metabolites. These microbial metabolites can modulate host signaling and epigenetic processes, including DNA methylation, histone modifications, and non-coding RNA activity, which may influence the expression of genes involved in glucose homeostasis, inflammation, and insulin sensitivity. Conversely, host epigenetic programs may influence intestinal barrier integrity and immune responses, thereby potentially affecting the gut microbial ecosystem, highlighting the reciprocal nature of host–microbiota interactions. We further examine how diet, psychosocial stress, environmental pollutants, and socioeconomic conditions may shape the microbiota–epigenetic axis across diverse populations, providing a framework for understanding differences in metabolic susceptibility without attributing disparities to intrinsic biological variation. However, direct human evidence linking the gut microbiota–host epigenetic axis to racial and ethnic disparities in T2DM risk remains limited, and much of the current framework is based on mechanistic studies, animal models, and associative human data rather than direct causal evidence. Further research in diverse human populations is needed to validate these pathways and establish their contribution to T2DM disparities. This framework may inform biomarker discovery, stratification, precision nutrition, and microbiome-targeted interventions and generate hypotheses for equitable prevention and personalized management of T2DM across diverse populations. Full article