Liquid-liquid phase separation (LLPS) may affect the therapeutic sensitivity of multiple myeloma (MM). This study aimed to identify LLPS-related genes with MM prognostic values and to confirm their effects on tumor progression.

Based on public transcriptomic data, this study screened LLPS- and immune-related genes for MM-derived plasma cells. Subtypes were identified using consensus clustering, followed by comparisons using t-test and survival analysis. Least absolute shrinkage and selection operator was implemented to screen prognostic signatures, and Kaplan-Meier and receiver operator characteristic curves were plotted to assess their prognostic values. After transfected with sh-DDX21, CCK8, flow cytometry, and Transwells were used to observe MM cell proliferation, apoptosis, migration, and invasion.

By overlapping LLPS- and immune-related genes, 103 genes were obtained to cluster MM samples into three subtypes, which had significant differences in survival and immune landscape. Cox regression analysis screened out EZH2 and DDX21 that significantly overexpressed in MM to construct a prognostic model, with superior performance in predicting MM prognostic risks. Notably, subtype2 with more adverse prognosis showed significantly elevated risk scores and was more distributed in groups with high prognostic risk. In vitro experiments confirmed that cell proliferation, invasion, and migration were significantly inhibited in MM.1S cells transfected with sh-DDX21.

LLPS-related EZH2 and DDX21 were novel markers to predict prognostic risk of MM. Among them, DDX21 was experimentally confirmed to promote MM cell proliferation, migration and invasion. These potential prognostic markers could be targeted in future personalized therapeutic strategies for MM, potentially improving patient outcomes.

To explore SLE staging markers, we analyzed eccDNA in plasma using circular sequencing, comparing healthy controls (HC), active SLE (ASLE), and inactive SLE (ISLE) patients. We found higher eccDNA levels and lower GC content in ASLE and ISLE compared to healthy controls, with a negative correlation between GC content and anti-daDNA, C3, and C4 levels in SLE and HC samples. Differential expression of exon-derived eccGenes in ASLE and ISLE suggests their role in SLE development, with KEGG analysis showing enrichment in SLE-related pathways for these differentially expressed genes. By protein-protein interactions network analysis we found 9 exon-derived eccGenes that were significantly differentially expressed and scored high in both ISLE-HC and ASLE-ISLE as diagnostic criteria for differentiating different disease stages of SLE. In conclusion, the present study reveals that eccDNA length GC content as well as chromosomal distribution in ASLE, ISLE and HC suggests that with eccDNA is associated with the creation of SLE, suggesting GC count of eccDNA as a diagnostic marker for systemic lupus erythematosus. Significant changes in the abundance of eccDNA-related genes from exons such as SOS1, GAD2, BCL11B, PPT1, and GCNT3 were observed in ISLE as compared to ASLE and HC groups and were significantly correlated with SLEDAI-2K. This suggests that these exon-derived eccGenes may play a role in the development and progression of the disease. Consequently, the abundance levels of these exon-derived eccGenes could potentially assist in distinguishing different stages of SLE, beyond a confirmed diagnosis, thus serving as possible biomarkers for the condition.

Ageing significantly contributes to osteoarthritis (OA) and metabolic syndrome (MetS) pathogenesis, yet the underlying mechanisms remain unknown. This study aimed to identify ageing-related biomarkers in OA patients with MetS. OA and MetS datasets and ageing-related genes (ARGs) were retrieved from public databases. The limma package was used to identify differentially expressed genes (DEGs), and weighted gene coexpression network analysis (WGCNA) screened gene modules, and machine learning algorithms, such as random forest (RF), support vector machine (SVM), generalised linear model (GLM), and extreme gradient boosting (XGB), were employed. The nomogram and receiver operating characteristic (ROC) curve assess the diagnostic value, and CIBERSORT analysed immune cell infiltration. We identified 20 intersecting genes among DEGs of OA, key module genes of MetS, and ARGs. By comparing the accuracy of the four machine learning models for disease prediction, the SVM model, which includes CEBPB, PTEN, ARPC1B, PIK3R1, and CDC42, was selected. These hub ARGs not only demonstrated strong diagnostic values based on nomogram data but also exhibited a significant correlation with immune cell infiltration. Building on these findings, we have identified five hub ARGs that are associated with immune cell infiltration and have constructed a nomogram aimed at early diagnosing OA patients with MetS.

Busulfan is the most commonly used drug for the treatment of chronic myelogenous leukemia and pretreatment for hematopoietic stem cell transplantation, which can damage the reproductive and immune system. However, little is known about the protein expression profiling in busulfan treated testis.

This research studies the proteomics for busulfan-induced spermatogenesis disorder. The model of busulfan-induced mouse spermatogenesis disorder was subjected to label-free quantification proteomics analysis. Clustering heatmap, gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein interaction analyses were performed and validated by molecular experiments.

The busulfan-treated mouse model showed abnormal testis morphology and reduced sperm number and testis weight. Testicular and sperm damage was most severe at 30 days after busulfan treatment. The busulfan-treated mouse testes were subjected to label-free quantification proteomics, which revealed 190 significantly downregulated proteins including lactate dehydrogenase A like 6B (LDHAL6B) and ubiquitin-specific protease 7 (USP7). In addition, the testis and spermatozoa in the epididymis progressively improved from 70 to 80 days after busulfan treatment, and that the testis weight and spermatozoa number gradually increased from 40 to 80 days after busulfan treatment. Western blotting revealed that LDHAL6B protein significantly increased at 10 days, decreased from 20 to 60 days, and then gradually elevated from 70 to 80 days after busulfan treatment.

We revealed 190 significantly downregulated proteins in busulfan-treated mouse testes at 30 days and indicated that 70 days is the cut-off point of spermatogenic recovery for busulfan-treated mouse testis, increasing our understanding of this reproductive disorder model. An increased understanding of busulfan's toxic effect will help to prevent and treat reproductive diseases.

The vedolizumab medication is the treatment that precisely targets the gut for Crohn's Disease (CD). It can inhibit the migration of lymphocytes to the intestinal site despite the fact that a significant portion of the population continues to be ineffectively treated. In this study, peripheral blood leukocytes sampled from the CD patients who are nonresponsive or responsive to vedolizumab treatment were used for transcriptome sequencing. Intersected differentially expressed mRNA obtained from transcriptome sequencing and GSE191328 were utilized to predict key therapeutic targets. Bioinformatics analyses were used to explore potential biological mechanisms and to screen pivotal genes. Inhibitor of S100A9 increased the body weight and colon length of mice with colitis, and decreased the DAI score. Our study also demonstrated that the combination of anti-α4β7 integrin antibody with inhibitor of S100A9 further alleviates colitis. Through flow cytometry, changes in the composition of immune cell populations in colon tissues were found after intragastric administration of paquinimod, an inhibitor of S100A9. It is important that blocking S100A9 inhibited the recruitment of neutrophils in the mice's colon. Our findings lay a foundation for the further exploration of the new targets for non-responders to vedolizumab in CD patients.

Mitral valve prolapse (MVP), the most prevalent primary valvular disease, serves as a direct risk factor for multiple cardiovascular disorders and exhibits a high prevalence in the general population. As no specific pharmacological therapies currently exist for MVP, the identification of precise therapeutic targets is imperative.

We conducted comprehensive causal genetic inference by integrating genetic data from expression quantitative trait loci (eQTL) and genome-wide association studies (GWAS). Analytical approaches included Mendelian Randomization (MR), colocalization analysis, Summary-data-based Mendelian Randomization (SMR), Linkage Disequilibrium Score Regression (LDSC), and High-Definition Likelihood (HDL) analysis. Protein quantitative trait loci (pQTL) were utilized to validate gene expression. Replication analyses were performed using additional exposure datasets. Methylation quantitative trait loci (mQTL) were employed to elucidate regulatory roles of methylation sites on genes and disease pathogenesis. Phenome-Wide Association Study (PheWAS) was conducted to predict potential adverse effects of gene-targeted therapies. Drug candidates targeting identified genes were predicted via the Drug Signature Database (DSigDB) and validated through molecular docking. Core targets were identified using the STRING database, followed by molecular dynamics simulations.

Two-sample MR analysis showed that genetically predicted 266 genes had positive or negative causal relationships with MVP. Colocalization analysis indicated that 9 genes had a posterior probability greater than 0.75. Subsequent SMR analysis excluded the gene GAPVD1. HDL analysis showed that except for the gene PTPN1, the remaining 7 genes were all significantly genetically associated with MVP, and LDSC analysis further showed that only NMB was associated with MVP. Validation using pQTL data confirmed that increased NMB protein expression reduced the risk of MVP. Replication analysis further verified this conclusion. In addition, SMR analysis of methylation sites for 8 genes indicated that multiple methylation sites played a key role in gene regulation of mitral valve prolapse. PheWAS results showed that targeted therapy for 8 genes did not detect other causal associations at the genome-wide significance level. Molecular docking showed that quercetin had good binding ability with 8 target genes. The STRING database identified 3 core target proteins, and molecular dynamics simulations further verified the binding ability of quercetin with core target proteins.

This study successfully predicted the potential of multiple druggable genes as effective therapeutic targets for MVP through genetic methods, validated the potential of quercetin as a drug, and provided new ideas for drug treatment strategies for MVP.

Anoikis, defined as programmed cell death triggered by the loss of cell-extracellular matrix (ECM) and cell-cell interactions, is crucial for maintaining tissue homeostasis and preventing aberrant cell migration. Cancer cells, however, display anoikis resistance (AR) which in turn enables cancer metastasis. AR results from alterations in apoptotic signaling, metabolic reprogramming, autophagy modulation, and epigenetic changes, allowing cancer cells to survive in detached conditions. In this review we describe the mechanisms underlying both anoikis and AR, focusing on intrinsic and extrinsic pathways, disrupted cell-ECM interactions, and autophagy in cancer. Recent findings (i.e., between 2014 and 2024) on epigenetic regulation of AR and its role in metastasis are discussed. Therapeutic strategies targeting AR, including chemical inhibitors, are highlighted alongside a network analysis of 122 proteins reported to be associated with AR which identifies 53 hub proteins as potential targets. We also evaluate in vitro and in vivo models for studying AR, emphasizing their role in advancing metastasis research. Our overall goal is to guide future studies and therapeutic developments to counter cancer metastasis.

JOURNAL/nrgr/04.03/01300535-202508000-00031/figure1/v/2024-09-30T120553Z/r/image-tiff The protein connector enhancer of kinase suppressor of Ras 2 (CNKSR2), present in both the postsynaptic density and cytoplasm of neurons, is a scaffolding protein with several protein-binding domains. Variants of the CNKSR2 gene have been implicated in neurodevelopmental disorders, particularly intellectual disability, although the precise mechanism involved has not yet been fully understood. Research has demonstrated that CNKSR2 plays a role in facilitating the localization of postsynaptic density protein complexes to the membrane, thereby influencing synaptic signaling and the morphogenesis of dendritic spines. However, the function of CNKSR2 in the cytoplasm remains to be elucidated. In this study, we used immunoprecipitation and high-resolution liquid chromatography-mass spectrometry to identify the interactors of CNKSR2. Through a combination of bioinformatic analysis and cytological experiments, we found that the CNKSR2 interactors were significantly enriched in the proteome of the centrosome. We also showed that CNKSR2 interacted with the microtubule protein DYNC1H1 and with the centrosome marker CEP290. Subsequent colocalization analysis confirmed the centrosomal localization of CNKSR2. When we downregulated CNKSR2 expression in mouse neuroblastoma cells (Neuro 2A), we observed significant changes in the expression of numerous centrosomal genes. This manipulation also affected centrosome-related functions, including cell size and shape, cell proliferation, and motility. Furthermore, we found that CNKSR2 interactors were highly enriched in de novo variants associated with intellectual disability and autism spectrum disorder. Our findings establish a connection between CNKSR2 and the centrosome, and offer new insights into the underlying mechanisms of neurodevelopmental disorders.

Thyroid cancer (TC) is the most prevalent endocrine malignancy, with a rising incidence necessitating safer treatment strategies to reduce overtreatment and its side effects. Xiaoyao Powder (XYP), a widely used herbal formula, shows promise in treating TC. This study aims to investigate the mechanisms by which XYP may affect TC.

The components of XYP were identified through database retrieval, and targets related to TC were collected to construct a target network for key screening. GEO dataset samples analyzed immune cells and identified significantly differentially expressed core genes (SDECGs). Based on SDECG expression and clustering, samples were classified for comparison. WGCNA was employed to identify gene modules linked to clinical characteristics. ML models screened characteristic genes and constructed a nomogram validated using another GEO dataset. MR methods explored causal relationships between genes and TC.

The top ten active components of XYP were identified, along with 27 SDECGs that exhibited significant differences in immune cell infiltration between TC patients and normal controls. The nomogram effectively predicted TC risk, validated through ROC curves. Key characteristic genes included SMIM1, PPP1R16A, KIAA1462, DNAJC22, and EFNA5.

XYP may treat TC by regulating SMIM1, PPP1R16A, KIAA1462, DNAJC22, EFNA5, and associated immune pathways; this provides theoretical support for its potential mechanisms.

Helicobacter pylori (H. pylori) is associated with various gastric diseases and is one of the pathogenic factors of gastric cancer (GC). We found that H. pylori induce the expression of TRAF1, but its mechanism of action is still unclear. Therefore, we wanted to determine whether TRAF1 is involved in the mechanism of H. pylori-related GC progression.

In this study, we analysed TRAF1 expression and its prognostic significance using clinical specimens, performed functional studies involving TRAF1 overexpression or knockdown in cellular models, identified downstream signalling pathways regulated via RNA-seq, validated these mechanisms through pathway blockade and rescue experiments, and further confirmed the findings in an H. pylori-infected gastritis mouse model.

TRAF1 expression was significantly elevated in GC tissues and served as a poor prognostic biomarker. TRAF1 promoted GC cell proliferation, migration and invasion. RNA-seq analysis revealed that TRAF1 activated the EGFR/STAT/OAS signalling axis, upregulated STAT3 expression and increased the transcription of the OAS gene family. Pharmacological inhibition with ruxolitinib and AG490 effectively blocked EGFR/STAT/OAS signalling. In H. pylori-treated cell models, H. pylori infection activated the EGFR/STAT/OAS signalling axis. In vivo, we established an H. pylori-induced gastritis mouse model to validate the activation of this signalling pathway during the gastritis-carcinoma transition.

TRAF1 may promote the proliferation, migration and invasion of H. pylori-associated GC by activating the EGFR/STAT/OAS signalling axis, suggesting that TRAF1 is a promising novel prognostic biomarker and therapeutic target for this malignancy.

Bacterial resistance has emerged as a major clinical challenge globally. Natural products, such as Aloe vera, offer promising antimicrobial potential due to their diverse active components. However, the explicit molecular mechanisms remain unknown. In this study, we employed a multidisciplinary approach integrating network pharmacology, molecular docking, and molecular dynamics simulation to explore the antibacterial mechanism of Aloe vera. We screened the eight major active components of Aloe vera and their targets using multi-source bioinformatics platforms, identifying 55 targets closely associated with the antibacterial effects of Aloe vera. Protein-protein interaction network analysis, revealed potential crucial targets, including cysteine-aspartic acid protease-3 (CASP3) and matrix metalloproteinase-9 (MMP-9). Gene ontology functional enrichment analysis revealed that these targets play critical roles in several essential biological processes, such as "response to xenobiotic stimulus", "positive regulation of gene expression", and "collagen catabolism". The Kyoto Encyclopedia of Genes and Genomes signal pathway analysis indicated that these targets are primarily involved in pathways associated with cancer, lipid metabolism, atherosclerosis, and the AGE/RAGE signaling pathway in diabetes. This finding suggests that Aloe vera may exert its antibacterial effects by regulating the host's immune response and metabolism. Molecular docking and molecular dynamics simulations demonstrated that active ingredients of Aloe vera, such as quercetin and aloe-emodin, can form stable complexes with CASP3 and MMP-9, exhibiting vigorous binding affinity to the active sites of the target. Further antibacterial activity assays and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis demonstrated that aloe-emodin exerts antibacterial effects against gram-positive bacteria and inhibits the expression of the MMP-9 gene. This study provided insight into the antibacterial mechanisms of Aloe vera, highlighting MMP-9 as a key target. These findings lay a foundation for further studies on natural antibacterial agents.

This study presents an in-silico approach to develop targeted therapies for Irritable Bowel Disease (IBD) by focusing on TNFSF15. Peptides derived from Macrotermes bellicosus and Curcuma longa were selected, conjugated with the 50S ribosomal protein L7/L12 adjuvant, and analyzed for immunogenic potential. Gene expression analysis showed differential TNFSF15 expression in gastrointestinal tissues. Functional enrichment revealed its role in immune regulation and cytokine signaling. Of the 20 peptides identified, 8 showed high antigenicity and 4 were allergenic. Structural modeling and docking predicted stable interactions with TNFSF15 (binding energy: -9.4 kJ/mol), supported by molecular dynamics. Immune simulations indicated robust IgM and IgG responses. These findings suggest that plant and insect derived peptides may offer promising therapeutic candidates for TNFSF15-associated IBD.

Lung adenocarcinoma (LUAD) is among the most prevalent malignancies worldwide. Cuproptosis, a copper-induced form of cell death, has been identified as a key process in LUAD progression; however, the molecular mechanisms underlying cuproptosis in LUAD and potential therapeutic targets remain unclear. The present study utilized The Cancer Genome Atlas database to retrieve mRNA expression profiles and clinical information of LUAD, identifying 10 candidate genes from differentially expressed genes associated with cuproptosis. Protein-protein interaction analysis indicated that CDK inhibitor 2A (CDKN2A), an upregulated gene in LUAD, may function as a hub gene. Furthermore, multiple online databases were used to analyze Spi-1 proto-oncogene (SPI1), a transcription factor upstream of CDKN2A, which was downregulated in LUAD cuproptosis. The LinkedOmics database identified the p53-mediated cuproptosis-related pathway regulated by CDKN2A. Gene expression patterns were examined through Gene Expression Profiling Interactive Analysis, the Human Protein Atlas and reverse transcription-quantitative polymerase chain reaction. Prognostic significance was assessed using the UALCAN and Kaplan-Meier plotter databases. In vitro experiments demonstrated that CDKN2A knockdown and SPI1 overexpression inhibited the proliferation and migration of the H1975 cell line. After copper-induced cuproptosis in H1975 cells, SPI1 expression was upregulated, whereas CDKN2A expression was downregulated. When H1975 cells were pretreated with tetrathiomolybdate, the upregulation of SPI1 was inhibited and the downregulation of CDKN2A was also suppressed. Cell Counting Kit-8 assays indicated that SPI1 overexpression and CDKN2A knockdown facilitated elesclomol-CuCl2-induced cuproptosis. Western blot analysis revealed an inverse association between SPI1 overexpression and CDKN2A/p53 levels. In conclusion, the present study demonstrated the role of the SPI1/CDKN2A/p53 axis in LUAD cuproptosis, providing insights into potential therapeutic targets and contributing to clinical research on treatment strategies.

The efficacy of clinical drugs for acute lung injury/acute respiratory distress syndrome (ALI/ARDS) remains suboptimal. Phillyrin (PHN), a compound derived from Forsythia, is believed to alleviate sepsis-related ALI/ARDS; however, its mechanisms are not fully elucidated. In this study, we screened 8331 target genes associated with ALI/ARDS from public databases and identified six hub genes relevant to PHN treatment: AKT1, GSK-3β, PPP2CA, PPP2CB, PPP2R1A, and AR. Receiver operating characteristic analysis and single-cell sequencing analysis revealed the expression of AKT1, GSK-3β, PPP2CA, PPP2CB, and PPP2R1A were markedly elevated. Molecular docking and dynamics simulations indicated that PHN forms a structurally stable complex with glycogen synthase kinase-3β (GSK-3β). Mendelian randomization analyses suggested that PHN, as a potent GSK-3β inhibitor, may promote M2 macrophage polarization and reduce neutrophil recruitment. We validated these findings through in vivo and in vitro experiments, demonstrating that PHN lowers iNOS levels and raises MMR levels by downregulating GSK-3β mRNA expression and protein activity during lipopolysaccharide (LPS)-induced macrophage inflammation. Additionally, PHN inhibited GSK-3β mRNA expression and protein activity, reducing NF-κB-p65 nuclear translocation in LPS-induced zebrafish inflammation and mice ALI. This inhibition decreased levels of TNF-α and IL-6, increased IL-10 levels, promoted M2 macrophage polarization, suppressed neutrophil recruitment, and ultimately ameliorated ALI/ARDS. In conclusion, our results indicate that PHN effectively alleviates LPS-induced ALI/ARDS by suppressing GSK-3β signaling.

Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between them are ambiguous, and the aim of this study was to explore the shared genetic features and associated pathways between these two disorders. MDD-related genes and mitochondrial function genes were downloaded from the GeneCards database. Weighted gene co-expression network analysis of Merge Cohort (GSE80432 and GSE34526) was performed to identify PCOS-related genes. Overlaps between PCOS-related genes, MDD-related genes, and mitochondrial function genes were defined as mitochondrial function-related shared genes. Functional enrichment analysis and protein-protein interaction (PPI) network analysis were performed on the shared genes. Functional genes were then identified using Last Absolute Shrinkage and Selection Operator Regression (LASSO), and a support vector machine (SVM-RFE) was constructed to measure the accuracy of the calculations. Finally, the results were tested using the whole blood datasets GSE54250 (for PCOS) and GSE98793 (for MDD) as external validation sets. A total of 498 PCOS-related genes, 5909 MDD-related genes, and 7232 mitochondrial function genes were acquired, and totally, 40 shared genes were obtained from the overlap of the above three. The shared mitochondrial function genes were enriched for biological processes mainly involving cholesterol biosynthetic process, lipid metabolic process, triglyceride biosynthetic process, response to drug phosphatidic acid biosynthetic process, and endoplasmic reticulum membrane. Based on LASSO regression and SVM-RFE model, NPAS2 and NTS were identified as characteristic genes shared by two disorders. According to two external validation sets for PCOS and MDD, NPAS2 was finally identified as a key shared gene. Our analysis identified a mitochondrial functional gene-NPAS2-as the most critical candidate for linking PCOS and MDD. The present findings may provide new insights into the diagnosis and treatment of PCOS and MDD comorbidities.

Celastrol (CEL) has demonstrated promising anti-cancer properties, yet its specific mechanisms against melanoma remain insufficient. This study investigated the CEL's anti-tumor effects and determined its potential mechanisms in the regulation of MHC-I expression in melanoma. In addition, we also tested its efficacy in sensitizing immune checkpoint inhibitors (ICIs) to melanoma.

CEL's anti-tumor activity was evaluated in B16F10 melanoma-bearing C57BL/6 mice across five groups (control, CEL 0.5 mg/kg, CEL 1 mg/kg, CEL 2 mg/kg, and ICIs), the tumor volume, histopathology, and body weight were assessed. Mechanistic insights were obtained through network pharmacology and RNA sequencing in B16F10 cells. Differential gene and pathway analysis were validated using qRT-PCR, Western blotting, and flow cytometry. CD8+T cell activation and cytotoxicity were analyzed in co-culture with CEL-pretreated B16F10 cells using flow cytometry and ELISA. CEL's interaction with potential targets was determined by molecular docking, surface plasmon resonance (SPR), and siRNA. The synergistic effect of CEL combined with ICIs was confirmed in B16F10-bearing C57BL/6 mice, and tumor-infiltrating T cells were assessed by flow cytometry across four groups (control, CEL, ICIs, CEL+ICIs).

CEL exhibited a significant anti-tumor effect in B16F10 melanoma-bearing mice. Mechanistically, CEL-pretreated B16F10 cells notably enhanced CD8+T cell activation and promoted IFNγ and TNFα secretion, leading to B16F10 cell death. CEL upregulated MHC-I expression through activation of the JAK/STAT1 pathway in B16F10 cells. The binding assay revealed that CEL interacted with SHP2, with an affinity of 37.93 μM. When SHP2 was silenced in B16F10 cells by siRNA, CEL failed to induce MHC-I upregulation. Moreover, CEL combined with ICIs produced superior antitumor efficacy compared to ICIs alone, which was accompanied by increased CD8+T cell infiltration in melanoma.

CEL enhanced CD8+T cell immunity by upregulating MHC-I expression in melanoma cells, these effects were at least partially through targeting SHP2 and activating JAK/STAT1 pathway. CEL might be a novel sensitizer for ICIs in melanoma.

This study aimed to explore the key efferocytosis-related genes in diabetic retinopathy (DR) and their regulatory mechanisms. Public DR-related gene expression datasets, GSE160306 (training) and GSE60436 (validation), were downloaded. Differentially expressed efferocytosis-related genes (DEERGs) were analyzed using differential expression analysis and weighted gene co-expression network analysis. Functional enrichment analysis was conducted. Moreover, efferocytosis-related signature genes were identified using machine learning analysis, and their expression levels and diagnostic value were analyzed. Furthermore, nomograms were constructed; immune cell infiltration was analyzed; and gene set enrichment analysis, transcriptional regulation analysis, and small-molecule drug (SMD) prediction of efferocytosis-related signature genes were performed. In total, 36 DEERGs were identified in DR, and were markedly enriched in multiple functions, such as visual system development. Through further machine learning analysis, two efferocytosis-related signature genes, Ferritin Light Chain (FTL) and Fc Gamma Binding Protein (FCGBP), were identified, and were found to be upregulated in DR samples and showed high diagnostic performance for DR. A nomogram constructed using FTL and FCGBP accurately predicted the risk of DR. Moreover, the level of infiltration of immature B cells was positively correlated with FTL and FCGBP expression levels. Multiple transcription factors (TFs), such as CCCTC-Binding Factor (CTCF) and KLF Transcription Factor 9 (KLF9), were found to interact with both FTL and FCGBP. In addition, FTL can be targeted by miRNAs, such as miR-22-3p, and FCGBP can be targeted by miR-7973. In addition, both FTL and FCGBP can be targeted by SMDs, such as bisphenol A. Key efferocytosis-related genes, such as FTL and FCGBP, may promote DR development. Detecting or targeting FTL and FCGBP may aid in the prevention, diagnosis, and treatment of DR.

Novel treatments for idiopathic pulmonary fibrosis (IPF) are needed urgently. A better understanding of the molecular pathways activated by TGFβ1 in human lung tissue may facilitate the development of more effective anti-fibrotic medications. This study utilized proteomic analysis to test the hypothesis that TGFβ1 induces pro-fibrotic effects on human lung parenchyma proteome, and to evaluate the viability of this model for testing novel therapeutic targets.

Non-fibrotic human lung parenchymal tissue from 11 patients was cultured for 7 days in serum-free (SF) media supplemented with TGFβ1 (10 ng/mL) or vehicle control, and the putative antifibrotic KCa3.1 ion channel blocker senicapoc or vehicle control. The tissue was homogenised, digested for bottom-up proteomics, and analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Principal component analysis, differential expression analysis, pathway analysis, and drug repurposing analysis were performed.

TGFβ1 stimulation for 7 days induced a strong fibrotic protein response relevant to IPF pathology. A total of 2391 proteins were quantified, 306 upregulated and 285 downregulated (FDR-adjusted p-value<0.05). Of these, 118 were upregulated and 28 downregulated at log2(FC) > 0.58. These changes were attenuated by senicapoc (100 nM). Drug repurposing analysis identified 265 drugs predicted to inhibit the effects of TGFβ1 in this model. These included clotrimazole, a KCa3.1 blocker, and nintedanib, a drug licenced for the treatment of IPF, providing validation of this approach.

A pro-fibrotic proteome is induced in human lung parenchyma exposed to TGFβ1, sensitive to pharmacological intervention. This approach has the potential to enhance therapeutic drug screening for IPF treatment.

Influenza A virus (IAV) poses a significant threat to human health. The outcome of IAV results from the viral-host interaction, with the underlying molecular mechanisms largely unknown. By integrating the plasma proteomics data of the IAV-infected patients into the viral-inflammation protein-protein interaction (VI-PPI) network created in this study, purine nucleoside phosphorylase (PNP), the critical enzyme in purine salvage, was identified as a potential hub gene that connected the different stages of IAV infection. Extended survival rates and reduced pulmonary inflammatory lesions were observed in alveolar epithelial cell (AEC)-specific PNP conditional knockout mice upon H1N1 infection. Mechanistically, PB1-F2 of IAV was revealed as a novel viral transcriptional factor to bind to the TATA box of PNP promoter, leading to enhanced purine salvage in H1N1-challenged AECs. The activation of PNP-mediated purine salvage was verified in IAV-infected patients and A549 cells. PNP knockdown elicited a purine metabolic shift from augmented salvage pathway to de novo synthesis, constraining both viral infection and pro-inflammatory signaling through APRT-AICAR-AMPK activation. Moreover, durdihydroartemisinin (DHA), predicted by VI-PPI as a novel PNP inhibitor, exerted beneficial effects on the survival and weight gain of H1N1-challenged mice via its direct binding to PNP. To reveal for the first time, we found that PNP, activated by IAV, plays a hub role within H1N1-host interaction, simultaneously modulating viral replication and hyperinflammation through purine salvage. Our study sheds new light on a "two-for-one" strategy by targeting purine salvage in combating IAV-related pathology, suggesting PNP as a potential novel anti-influenza host target.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer related death, and its molecular mechanisms have not been fully elucidated. This study aims to elucidate the molecular mechanisms linking pyroptosis and immune microenvironment changes in HCC, with a focus on macrophage polarization and inflammatory responses.

Selected gene expression profiles from the Gene Expression Omnibus database, established protein-protein interaction (PPI) networks, and performed functional enrichment analysis using databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of relevant hub genes was verified by immunohistochemistry, real-time quantitative PCR, and Western Blot based on clinical tissues. Single-cell identification of HCC cell types and malignant cells, trajectory analysis, and intercellular signal communication further analyzed the molecular mechanisms between immune cells and liver cells. Bioinformatics combined with single-cell analysis to elucidate the immune pyroptosis molecular mechanism that underlay the development of HCC.

Molecular biology has identified six pyroptosis hub genes in HCC. The key hub genes of immune pyroptosis were validated through immunohistochemistry and in vitro experiments. Enrichment analysis shows that intersecting genes are enriched in immune responses, chemokine mediated signaling pathways, and inflammatory responses. InferCNV and copyKAT accurately predict that malignant cells distribute in HCC tissues, and their main malignant cells may be hepatocytes, endothelium and epithelial cells. Cell trajectory analysis found that monocyte, macrophage polarization could play a first role in HCC. The cellular clustering of single cells revealed the infiltration of immune cells, especially the polarization of macrophages, which plays an important role. Immunohistochemistry suggests that hub genes such as HMGB1, CYCS, GSDMD, IL-1β, NLRP3, and IL18 are the link between macrophage polarization and pyroptosis during HCC development.

In summary, the main molecular mechanisms underlying the pathogenesis of HCC are related to immune cell infiltration, particularly macrophage infiltration polarization that promotes the secretion of inflammatory factors leading to hepatocyte pyroptosis. These findings provide novel insights into the macrophage-driven pyroptosis pathways in HCC, potentially paving the way for new immunotherapeutic strategies.

Integrator (INT) is a metazoan-specific complex that targets promoter-proximally paused RNA polymerase II (RNAPII) for termination, preventing immature RNAPII from entering gene bodies and functionally attenuating transcription of stress-responsive genes. Mutations in INT subunits are associated with many human diseases, including cancer, ciliopathies, and neurodevelopmental disorders, but how reduced INT activity contributes to disease is unknown. Here, we demonstrate that the loss of INT-mediated termination in human cells triggers the integrated stress response (ISR). INT depletion causes upregulation of short genes such as the ISR transcription factor activating transcription factor 3 (ATF3). Further, immature RNAPII that escapes into genes upon INT depletion is prone to premature termination, generating incomplete pre-mRNAs with retained introns. Retroelements within retained introns form double-stranded RNA (dsRNA) that is recognized by protein kinase R (PKR), which drives ATF4 activation and prolonged ISR. Critically, patient cells with INT mutations exhibit dsRNA accumulation and ISR activation, thereby implicating chronic ISR in diseases caused by INT deficiency.

To investigate the therapeutic effects of kinsenoside on cognitive dysfunction in APP/PS1 transgenic mice and to explore its potential targets.

Network pharmacology was employed to identify targets of kinsenoside in Alzheimer's disease (AD). The Morris water maze test was conducted to assess the therapeutic effects of kinsenoside on cognitive dysfunction in APP/PS1 transgenic mice, and immunofluorescence was used to evaluate the impact of kinsenoside on amyloid-beta (Aβ) pathology and brain lymphatic structure and function. The Raybiotech GSM-CAA-4000 protein chip was used to detect changes in inflammatory factors. Graph convolutional network (GCN) analysis was applied to analyze and identify core targets from the protein chip results, which were then intersected with the network pharmacology findings, followed by molecular docking and molecular dynamics simulations.

Network pharmacology analysis indicated that kinsenoside inhibits inflammation and oxidative stress signaling pathways involved in AD. The maximum neighborhood connectivity (MNC) algorithm identified HSP90AA1, HSP90AB1, PIK3CA, STAT3, IL6, and IFNγ as potential targets. In vivo mouse experiments demonstrated that kinsenoside has the ability to reduce Aβ plaque deposition and expand meningeal lymphatic vessels(mLVs), improving the glymphatic system drainage, which ultimately leads to improved cognitive function. This beneficial effect may be related to the inhibition of IFNγ by kinsenoside.

Based on preclinical data, kinsenoside shows promising potential in the treatment of AD.

To elucidate the early signaling components involved in thigmomorphogenesis in Arabidopsis thaliana, we combined microscopy and proximity-labeling (PL)-based quantitative biotinylproteomics to characterize the touch-responsive putative cytoskeleton-interacting protein WPRa4. Our findings revealed that WPRa4 localizes near plastids and interacts with cytosolic Plastid Movement-Impaired (PMI) proteins and a plastidic translocon component, suggesting a cytoskeleton-plastid network in mechanosensing. Bioinformatic analysis of PL and cross-linking mass spectrometry (XL-MS) data identified PMI4 as a key mediator, with pmi4 mutants lacking touch-induced bolting delay, rosette size reduction, and Ca2+ oscillations. Transcriptomics further showed that PMI4 regulates touch-responsive and jasmonic acid (JA)-associated genes, such as LOX2. We propose a molecular model where interconnected Cytoskeleton-Plastoskeleton Continuum (CPC) proteins act as early mechanosensors, integrating the touch responses of plant aerial organs with calcium signaling and transcriptional reprogramming in Arabidopsis.

This study identified and evaluated the expression of the AREB/ABF/ABI5 subfamily genes in chickpea and lentil, and revealed the major players involved in defense response to PEG-induced drought stress. Abscisic acid (ABA)-responsive element-binding protein/ABRE-binding factor/ABA-INSENSITIVE 5 (AREB/ABF/ABI5) subfamily proteins are major players in the ABA-mediated signaling pathway triggered by multiple stresses. AREB/ABF/ABI5 subfamily proteins belong to the basic-leucine zipper transcription factors that regulate the expression of several downstream defense genes to abiotic and biotic stresses. This protein set is highly targeted when trying to understand plant defense against abiotic stress or to improve plant tolerance to drought, cold, and salinity stresses. However, there is still very little information available about the genes of the AREB/ABF/ABI5 subfamily in chickpea and lentil. Herein, 8 chickpea and 9 lentil genes of the AREB/ABF/ABI5 subfamily were identified based on sequence analysis, and their expression levels were tested in a polyethylene glycol-induced drought experiment (20% PEG in Hoagland solution) using real-time RT-PCR and metadata analysis. Sequence analysis showed that members of this subfamily are highly conserved among themselves and with their orthologous genes in other closely related plant species. Overall, sequence data suggested that these genes may possess close or overlapping biological roles in regulating the transcription of abiotic stress-related defense genes. The meta-analysis from RNA-Seq datasets of unstressed plants showed that some members of this gene subfamily have a tissue-specific expression in both chickpea and lentil. Drought-contrasting chickpea and lentil cultivars showed that most AREB/ABF/ABI5 genes are modulated by PEG-induced drought. Furthermore, AREB/ABF/ABI5 genes had also a tendency for higher expression as cultivar tolerance increases. Therefore, this study identified the AREB/ABF/ABI5 subfamily genes in chickpea and lentil, and provides a comprehensive characterization of these members to support further focused research.

Chronic urticaria (CU), a prevalent and often debilitating allergic skin disorder, is primarily triggered by mast cell degranulation. Danggui Yinzi (DGYZ), a traditional Chinese medicine formula, has been employed to treat pruritic conditions. However, the molecular mechanisms underlying its effects in CU remain unclear. This study aimed to investigate the immunopharmacological mechanisms of DGYZ in CU, hypothesizing that it modulates immune responses through its bioactive components, which is critical for the development of novel therapeutic agents.

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS) was used to identify the active compounds in DGYZ. In vivo, BALB/c mouse models of DNP-IgE/DNFB-induced CU were established and grouped into Normal Control (NC), Model, various-dose DGYZ, and Loratadine groups. Post-treatment, immunopharmacological parameters were assessed, and skin tissue was collected for histopathological analysis, mast cell quantification, and immunohistochemistry to evaluate the impact on immune cells and molecules. Serum levels of inflammatory cytokines (TNF-α, IL-6) were quantified using ELISA kits. In vitro, the human mast cell line LAD2 was pretreated with key active components of DGYZ (Quercetin and Paeoniflorin) at different concentrations before mast cell degranulation was induced. Degranulation markers (β-HEX, HIS) and the expression of proteins in immune-related signaling pathways (PI3K-Akt, TLR4) were then measured.

A total of 38 active components were identified in DGYZ. In vivo, DGYZ inhibited mast cell degranulation, blue spot reactions, and skin damage in mice. It also decreased the levels of inflammatory cytokines (TNF-α, IL-6) and suppressed the activation of associated signaling pathways. In vitro, both Quercetin and Paeoniflorin reduced mast cell degranulation and the activation of TLR4 and PI3K-Akt pathways.

This study, employing UPLC-Q-TOF-MS and both in vivo and in vitro experiments, provides a comprehensive analysis of the mechanism of DGYZ in CU. The findings indicate that DGYZ exerts therapeutic effects in CU by modulating immune responses. This research lays the foundation for a deeper understanding of its immunopharmacological mechanisms, potentially aiding the development of novel drugs and therapeutic strategies for CU management.

Intracellular lipases can be broadly divided into two categories: neutral lipases and acid lipases. Adipose triglyceride lipase (ATGL), hormone-sensitive lipase (HSL), and monoacylglycerol lipase (MAGL) are three key neutral lipases responsible for the hydrolysis of triacylglycerol (TAG) in lipid droplets (LDs). Although these three TAG intracellular lipase genes have been identified and characterized in multiple model species, their evolutionary history remains largely unknown. For the TAG intracellular lipase genes in Decapoda, there is also a large knowledge gap. Thus, in this study, we performed a genome-wide identification and investigation of TAG intracellular lipase genes in Decapoda and outgroups, analyzing their phylogenetics, structural features, conserved motifs, and expression patterns. In total, 22 ATGL genes, 23 HSL genes and 21 MAGL genes were identified in 17 selected species. HSL is the oldest and most conserved gene to exist in any species. Furthermore, RNA-seq analysis was conducted on two representative Decapod species, Chinese mitten crab (Eriocheir sinensis) and swimming crab (Portunus trituberculatus), which represent freshwater and marine environments, respectively. The analysis revealed a positive correlation between the expression levels of TAG intracellular lipase genes and the energy demand during different molting stages. Overall, the results of this study provide valuable insights into the evolutionary history of TAG intracellular lipase genes, which could enhance our understanding for the role of these genes during key physiological processes of Decapods.

Shugan Yiyang capsule (SGYY), a commonly used traditional Chinese medicine formulation, is primarily indicated for the treatment of erectile dysfunction, yet existing studies on the therapeutic effects on male infertility (MI) are insufficient and the specific mechanisms remain poorly understood. Given the close relationship between MI, sperm quality, and erectile function, this study aims to investigate the role of SGYY in the restoration of MI and explore the underlying mechanisms.

The efficacy of SGYY is comprehensively evaluated through pharmacodynamic, metabolomic, and network pharmacology. Sperm parameters, reproductive hormones, sexual behavior, neural enzymes, oxidative stress markers, pro-inflammatory cytokines, and testicular histopathology are measured to reveal the restorative effects of MI. Furthermore, urine and serum metabolomics, along with network pharmacology and surface plasmon resonance, are employed to explore the molecular mechanisms and predict core targets.

SGYY significantly improved overall health parameters, including body weight, water intake, urine output, food consumption, and spontaneous activity. Specifically, SGYY prominently recovered sexual behavior, ameliorated sperm quality, increased mitochondrial membrane potential, normalized reproductive hormones, upregulated endothelial nitric oxide synthase, attenuated oxidative stress markers, and pro-inflammatory cytokines, and repaired testicular pathological damage. Metabolomic analysis identified 47 candidate biomarkers, among which SGYY significantly modulated 39 potential biomarkers, encompassing 8 main metabolic pathways such as histidine metabolism, cysteine and methionine metabolism, propanoate metabolism, and taurine and hypotaurine metabolism. Additionally, network pharmacology predicted 8 core targets, comprising HSP90AA1, ESR1, MAPK1, CASP3, IL6, TNF, BCL2, and MAPK8.

SGYY improves sperm quality and erectile function by regulating oxidative stress, energy metabolism, and neurological function, thereby exerting a restorative effect on MI, as evidenced by the modulation of 8 main metabolic pathways, 39 potential biomarkers, and 8 core targets. Pharmacodynamic provides foundational validation, metabolomic uncovers intrinsic metabolic changes, and network pharmacology predicts therapeutic targets, with findings from the 'Pharmaco-Metabo-Net' tripartite correlation analysis providing a solid theoretical strategy and scientific evidence to support the clinical application of SGYY in restoring MI.

Current risk assessment models for predicting ischemic stroke (IS) in patients with atrial fibrillation (AF) often fail to account for the effects of medications and the complex interactions between drugs, proteins, and diseases. We developed an interpretable deep learning model, the AF-Biological-IS-Path (ABioSPath), to predict one-year IS risk in AF patients by integrating drug-protein-disease pathways with real-world clinical data. Using a heterogeneous multilayer network, ABioSPath identifies mechanisms of drug actions and the propagation of comorbid diseases. By combining mechanistic pathways with patient-specific characteristics, the model provides individualized IS risk assessments and identifies potential molecular pathways involved. We utilized the electronic health record data from 7859 AF patients, collected between January 2008 and December 2009 across 43 hospitals in Hong Kong. ABioSPath outperformed baseline models in all evaluation metrics, achieving an AUROC of 0.7815 (95% CI: 0.7346-0.8283), a positive predictive value of 0.430, a negative predictive value of 0.870, a sensitivity of 0.500, a specificity of 0.885, an average precision of 0.409, and a Brier score of 0.195. Cohort-level analysis identified key proteins, such as CRP, REN, and PTGS2, within the most common pathways. Individual-level analysis further highlighted the importance of PIK3/Akt and cytokine and chemokine signaling pathways and identified IS risks associated with less-studied drugs like prochlorperazine maleate. ABioSPath offers a robust, data-driven approach for IS risk prediction, requiring only routinely collected clinical data without the need for costly biomarkers. Beyond IS, the model has potential applications in screening risks for other diseases, enhancing patient care, and providing insights for drug development.

With the increasing prevalence of environmental pollutants, there is growing concern about the potential effects of these substances in major diseases such as liver cancer. Previous studies have suggested that various chemicals, such as benzo[a]pyrene(BaP), produced by burning carbon containing fuels, may negatively affect liver health, but the exact mechanisms remain unclear. This study aimed to explore the potential molecular mechanisms of BaP in the progression of liver cancer. Through an exhaustive study of databases such as ChEMBL, SwissTargetPrediction, STITCH and TCGA, we identified 169 potential targets that are closely related to BaP and liver cancer. Next, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the clusterProfiler package to study the biological functions and important pathways of potential targets induced by BaP, which showed that these targets were associated with mitochondrial function, cellular energy metabolism and REDOX reactions. The protein interaction (PPI) network was constructed using the STRING database and Cytoscape software to identify the core targets UBA52, NDUFS8, CYP1A2, NDUFS1 and CYP3A4. The interaction between BaP and these core proteins was further analyzed via molecular docking using the CB-Dock2 database, demonstrating high binding stability, which suggests their critical role in BaP-induced hepatocellular carcinoma (HCC) toxicity. Subsequently, we found significant differences in the expression of five core genes (UBA52, NDUFS8, CYP1A2, NDUFS1, CYP3A4) in HCC, and significant correlation between UBA52, NDUFS8 and CYP3A4 and survival of HCC patients. Single-cell sequencing analysis showed that the expression of UBA52 gene was particularly pronounced in the three immune cells.

Motor neurons differ from sensory neurons in aspects including origins and surrounding environment. Understanding the similarities and differences in molecular response to peripheral nerve injury (PNI) and regeneration between sensory and motor neurons is crucial for developing effective drug targets for CNS regeneration. However, genome-wide comparisons of molecular changes between sensory and motor neurons following PNI remains limited.

This study aims to investigate genome-wide convergence and divergence of injury response between sensory and motor neurons to identify novel drug targets for neural repair.

We analyzed two large-scale RNA-seq datasets of in situ captured sensory neurons (SNs) and motoneurons (MNs) upon PNI, retinal ganglion cells and spinal cord upon CNS injury. Additionally, we integrated these with other related single-cell level datasets. Bootstrap DESeq2 and WGCNA were used to detect and explore co-expression modules of differentially expressed genes (DEGs).

We found that SNs and MNs exhibited similar injury states, but with a delayed response in MNs. We identified a conserved regeneration-associated module (cRAM) with 274 shared DEGs. Of which, 47% of DEGs could be changed in injured neurons supported by single-cell resolution datasets. We also identified some less-studied candidates in cRAM, including genes associated with transcription, ubiquitination (Rnf122), and neuron-immune cells cross-talk. Further in vitro experiments confirmed a novel role of Rnf122 in axon growth. Analysis of the top 10% of DEGs with a large divergence suggested that both extrinsic (e.g., immune microenvironment) and intrinsic factors (e.g., development) contributed to expression divergence between SNs and MNs following injury.

This comprehensive analysis revealed convergent and divergent injury response genes in SNs and MNs, providing new insights into transcriptional reprogramming of sensory and motor neurons responding to axonal injury and subsequent regeneration. It also identified some novel regeneration-associated candidates that may facilitate the development of strategies for axon regeneration.

The exploration of cell death and cellular senescence (CDS) in cancer has been an area of interest, yet a systematic evaluation of CDS features and their interactions in lung adenocarcinoma (LUAD) to understand tumor heterogeneity, tumor microenvironment (TME) characteristics, and patient clinical outcomes is previously uncharted. Our study characterized the activities and interconnections of 21 CDS features in 1788 LUAD cases across 15 cohorts, employing unsupervised clustering to categorize patients into three CDS subtypes with distinct TME profiles. The CDS index (CDSI), derived from principal component analysis, was developed to assess individual tumor CDS regulation patterns. Twelve CDSI core genes, enriched in proliferating T cells within the TME as per single-cell analysis, were identified and their functional roles and prognostic significance were validated. High CDSI correlated with improved overall survival in discovery cohort, four independent validation cohorts, and subgroup analysis. CDSI-low patients exhibited a favorable clinical response to immunotherapy and potential sensitivity to mitosis pathway drugs, while CDSI-high patients might benefit from drugs targeting ERK/MAPK and MDM2-p53 pathways. The clinical utility of CDSI was further validated using 9185 pan-cancer samples, demonstrating the broad relevance of our prediction model across various cancer types and its potential clinical implications for cancer management.

The rapid rise in drug-resistant tuberculosis poses a serious threat to public health and demands the discovery of new anti-mycobacterial agents. Medicinal plants are a proven potential source of bioactive compounds; however, identifying those responsible for the putative anti-mycobacterial action still remains a challenging task. In this study, we undertook a systematic network pharmacology approach to identify and evaluate anti-mycobacterial compounds from a traditional plant, Acacia nilotica, as a model system. The protein-protein interaction network revealed 17 key pathways in M. tuberculosis encompassing 40 unique druggable targets that are necessary for its growth and survival. The phytochemicals of A. nilotica were preferentially found to interfere with the cell division and cell wall biogenesis proteins, especially FtsZ and Mur. Notably, the compounds epigallocatechin, ellagic acid, chlorogenic acid, and D-pinitol were found to exhibit a potential polypharmacological effect against multiple proteins. Further, in vitro studies confirmed that the selected candidates, chlorogenic acid, and ellagic acid exhibited potent anti-mycobacterial activity (against M. smegmatis) with specific inhibition of purified M.tb FtsZ enzyme. Taken together, the present study demonstrates that network pharmacology combined with molecular docking can be utilized as an efficient approach to identify potential bioactive phytochemicals from natural products along with their mechanism of action. Hence, the compounds identified in this study can be potential lead candidates for developing novel anti-mycobacterial drugs, while the key proteins identified here can be potential drug targets.

Duchenne muscular dystrophy (DMD) is a progressive X-linked disorder causing muscle degeneration and multisystem involvement, requiring precise genetic diagnosis for timely intervention and treatment.

To investigate the genetic landscape of DMD using a two-tiered diagnostic approach combining MLPA and WES, and to correlate genetic findings with clinical outcomes for improved management.

A cross-sectional study of 80 male DMD patients was conducted using a sequential genetic approach, combining MLPA and WES, with bioinformatics and statistical analyses to explore genotype-phenotype correlations.

Pathogenic variants were identified in 65 cases (81.2 %), with deletions (67.5 %) being the most common, followed by duplications (6.3 %), splice-site (3.8 %), and nonsense variants (3.8 %). WES identified additional pathogenic variants in MLPA-negative cases, including novel mutations, expanding the known genetic spectrum of DMD. The combined MLPA-WES approach significantly improved diagnostic yield (χ² = 12.90, p < 0.001). Functional analysis revealed disruptions in glycogen metabolism (46 %), calcium transport (24 %), and mitochondrial function (12 %), with dystrophin-associated proteins (DAG1, SGCD) critically involved in muscle stability. Out-of-frame deletions were significantly associated with early disease onset (χ² = 49.03, p < 0.001) and severe phenotypes (χ² = 47.04, p < 0.001), supporting exon-skipping therapy. In-frame deletions correlated with milder progression, while nonsense variants posed a 2.5-fold increased risk of early cardiomyopathy (p = 0.002), emphasizing the need for early intervention.

Combining MLPA and WES enhances DMD diagnostic accuracy, enabling timely clinical interventions. Integrating functional analysis with genotype-phenotype correlations supports personalized therapeutic strategies, improving patient outcomes.

Bladder cancer (BLCA) is an aggressive malignancy characterized by limited therapeutic options and a poor prognosis. Research has indicated that abnormally expressed miRNAs play a significant role in the pathogenesis of BLCA, although the specific mechanisms remain unclear. MiR-125b plays a tumor suppressor role in a variety of cancers and affects the biological processes of cancer cells such as proliferation, invasion, migration and apoptosis by regulating different signaling pathways. Elucidation of the molecular mechanisms underlying miR-125b may provide clinical therapeutic strategies for bladder cancer. Here, miR-125b was downregulated whereas its targets IL-6R and STAT3 were upregulated in BLCA, as evidenced by bioinformatics analysis. Kaplan-Meier analysis confirmed that miR-125b serves as an independent prognostic factor linked to overall survival (OS) in patients with bladder cancer. Furthermore, overexpression of miR-125b significantly inhibited BLCA cell proliferation, migration, and invasion, while promoting apoptosis, as evidenced by an increased Bax/Bcl-2 ratio and activated cleaved caspase-3. Further investigations demonstrated that miR-125b directly targets and downregulates both IL-6R and STAT3. In a xenograft model, miR-125b overexpression effectively inhibited tumor growth in bladder cancer by blocking IL-6/IL-6R and STAT3 signaling pathways. Collectively, these findings broaden our understanding of the mechanism by which miR-125b acting as a BLCA suppressor in apoptotic regulation by targeting the IL-6/IL-6R/STAT3 signaling pathway, providing novel insights regarding the design of novel miRNA based therapeutic strategies against BLCA.

Interferon‑induced transmembrane proteins (IFITMs) are frequently overexpressed in cancer cells, including cervical carcinoma cells, and play a role in the progression of various cancer types. However, their mechanisms of action remain incompletely understood. In the present study, by employing a combination of surface membrane protein isolation and quantitative mass spectrometry, it was comprehensively described how the IFITM1 protein influences the composition of the cervical cancer cell surfaceome. Additionally, the effects of interferon‑γ on protein expression and cell surface exposure were evaluated in the presence and absence of IFITM1. The IFITM1‑regulated membrane and membrane‑associated proteins identified are involved mainly in processes such as endocytosis and lysosomal transport, cell‑cell and cell‑extracellular matrix adhesion, antigen presentation and the immune response. To complement the proteomic data, gene expression was analyzed using reverse transcription‑quantitative PCR to distinguish whether the observed changes in protein levels were attributable to transcriptional regulation or differential protein dynamics. Furthermore, the proteomic and gene expression data are supported by functional studies demonstrating the impact of the IFITM1 and IFITM3 proteins on the adhesive, migratory and invasive capabilities of cervical cancer cells, as well as their interactions with immune cells.

Lymph node metastasis in oral cancer (OC) complicates management due to its aggressive nature and high risk of recurrence, underscoring the need for biomarkers for early detection and targeted therapies. However, the drivers of this aggressive phenotype remain unclear due to the variability in gene expression patterns. To address this, an integrative meta-analysis of six publicly available transcriptomic profiles, categorized by lymph nodal status, is conducted. Key determinants of disease progression are identified through functional characterization and the TopConfects ranking approach of nodal associated differentially expressed genes (DEGs). To explore the critical nexus between lymph node metastasis and OC recurrence, significant metastatic genes were cross-analysed with literature-derived genes exhibiting aberrant methylation patterns in OC recurrence. Their clinical relevance and expression patterns were then validated in an external dataset from the TCGA head and neck cancer cohort. The analysis identified elevated expression of genes involved in extracellular matrix remodelling and immune response, while the expression of genes related to cellular differentiation and barrier functions was reduced, driving the transition to nodal positivity. The highest-ranked gene, MMP1, showed a log-fold change (LFC) of 4.946 (95 % CI: 3.71, 6.18) in nodal-negative samples, which increased to 5.899 (95 % CI: 4.80, 6.99) in nodal-positive samples, indicating consistent elevation across disease stages. In contrast, TMPRSS11B was significantly downregulated, with an LFC of -5.512 (95 % CI: -6.63, -4.38) in nodal-negative samples and -5.898 (95 % CI: -7.15, -4.64) in nodal-positive samples. Furthermore, MEIS1, down-regulated in nodal-positive status, was found to exhibit hypermethylation at CpG sites associated with OC recurrence. This study represents the first transcriptomic meta-analysis to explore the intersection of lymph node metastasis and OC recurrence, identifying MEIS1 as a potential key contributor. These comprehensive insights into disease trajectories offer potential biomarkers and therapeutic targets for future treatment strategies.

Alcohol use disorder (AUD) is a highly prevalent, complex, multifactorial and heterogeneous disorder, with 11 % and 30 % of adults meeting criteria for past-year and lifetime AUD, respectively. Identification of the molecular mechanisms underlying risk for AUD would facilitate effective deployment of personalized interventions. Studies using rhesus monkeys and rats, have demonstrated that individuals with low cognitive flexibility and a predisposition towards habitual behaviors show an increased risk for future heavy drinking. Further, low cognitive flexibility is associated with reduced dorsolateral prefrontal cortex (dlPFC) function in rhesus monkeys. To explore the underlying unique molecular signatures that increase risk for chronic heavy drinking, a genome-wide DNA methylation (DNAm) analysis of the alcohol-naïve dlPFC-A46 biopsy prior to chronic alcohol self-administration was conducted. The DNAm profile provides a molecular snapshot of the alcohol-naïve dlPFC, with mapped genes and associated signaling pathways that vary across individuals. The analysis identified 1,463 differentially methylated regions (DMRs) related to unique genes that were strongly associated with average ethanol intake consumed over 6 months of voluntary self-administration. These findings translate behavioral phenotypes into neural markers of risk for AUD, and hold promise for parallel discoveries in risk for other disorders involving impaired cognitive flexibility. SIGNIFICANCE: Alcohol use disorder (AUD) is a highly prevalent and heterogeneous disorder. Prevention strategies to accurately identify individuals with a high risk for AUD, would help reduce the prevalence, and severity of AUD. Our novel epigenomic analysis of the alcohol-naïve nonhuman primate cortex provides a molecular snapshot of the vulnerable brain, pointing to circuitry and molecular mechanisms associated with cortical development, synaptic functions, glutamatergic signaling and coordinated signaling pathways. With a complex disorder like AUD, having the ability to identify the molecular mechanisms underlying AUD risk is critical for better development of personalized effective treatments.