Senile osteoporosis is driven by bone marrow stromal cell (BMSC) senescence. Ferroptosis, an iron-dependent cell death pathway, is implicated in aging. The natural flavonoid galangin possesses anti-aging properties, yet its effects on ferroptosis and BMSC senescence are unknown. Natural aging and d-galactose-induced aging models were used, with galangin supplementation. Bone mass was assessed via micro-computed tomography and histomorphometry. Senescence markers (P21, SA-β-gal, NAD+) and ferroptosis regulators (GPX4, GSH/GSSG) were measured. BMSC senescence was induced by d-galactose or serial passaging. Effects of galangin on senescence, ferroptosis, osteogenic differentiation, and dipeptidyl peptidase-4 (DPP4) signaling were evaluated. Galangin significantly attenuated bone loss and reduced senescence markers in both aging mouse models. Ferroptosis was activated in senescent BMSC. Galangin suppressed ferroptosis, rescued senescence phenotypes, and restored osteogenic differentiation capacity. Mechanistically, galangin inhibited DPP4 nuclear translocation and disrupted its interaction with NADPH oxidase NOX1, thereby blocking reactive oxygen species-dependent ferroptosis signaling without altering total DPP4 expression. Galangin ameliorates Senile osteoporosis by specifically inhibiting DPP4 nuclear translocation and its interaction with NOX1, thereby suppressing ferroptosis, rescuing BMSC senescence, and restoring osteogenic function. This identifies galangin as a promising agent against skeletal aging.

Neuropathic pain (NP), a chronic condition resulting from nerve injury or dysfunction, represents considerable therapeutic difficulties owing to its intricate and multifactorial pathophysiology. Recent studies indicate that dysregulated fatty acid metabolism (FAM) plays a pivotal role in the onset and persistence of NP. Nonetheless, the molecular mechanisms underpinning this association remain incompletely elucidated. This research aims to characterize the expression profiles of FAM-related genes in NP and explore their relationship with immune cell infiltration (ICI). Publicly available gene expression data sets (GSE24982 and GSE2884) were analyzed using bioinformatics approaches to identify differentially expressed genes (DEGs) related to FAM in NP. Differential expression analysis was performed using the limma package in R. Functional enrichment analyses, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA), were carried out to elucidate relevant biological pathways. ICI was assessed using computational deconvolution methods. Overall, 116 FAM-related DEGs were identified in NP. Enrichment analyses highlighted key pathways such as FAM, arachidonic acid metabolism, and the PPAR signal transduction. Among these, Cyp3a2, Hadha, and Scp2 emerged as key genes potentially involved in NP pathogenesis, with Cyp3a2 exhibiting high mRNA levels in validated animal models. ICI analysis revealed significant correlations between the expression of these genes and various immune cell populations, including activated B cells and CD8+ T cells, indicating a strong inflammatory component in NP. Moreover, stratification by FAM scores demonstrated distinct gene expression and immune infiltration profiles between low- and high-risk groups. This study highlights the essential role of FAM in the molecular landscape of NP and identifies Cyp3a2, Hadha, and Scp2 as potential biomarkers or therapeutic targets. These findings advance our understanding of NP pathogenesis and offer insights into novel strategies for its management.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high metastatic potential and lacking effective treatment strategies. Vitexicarpin (VIT) has been reported to have excellent inhibitory effects on several types of cancer, including TNBC. However, its potential mechanisms on metastatic TNBC are not well understood. Herein, we found that VIT inhibited migration and invasion of TNBC through reducing MMP-9 expression in vitro and in vivo. Subsequently, RSK2 was identified as the potential target of VIT in TNBC by pull-down and MS analysis. Moreover, the further validations showed that VIT bound to Asp148 and Asp154 residues of NTKD, and Thr493 of CTKD, thereby inhibiting its phosphorylation and kinase activity. Mechanistically, we found that HIF-1α/MMP-9 was involved in VIT-mediated inhibition of migration and invasion of TNBC, and similar results were observed upon RSK2 knockdown or combined with VIT treatment, which demonstrated that VIT-mediated inhibition of HIF-1α/MMP-9 pathway was dependent on targeting RSK2. Finally, TNBC mouse xenograft models showed that VIT effectively inhibited TNBC metastasis and growth through regulating the RSK2/HIF-1α/MMP-9 axis in vivo. Taken together, our findings demonstrated that VIT downregulated the HIF-1α/MMP-9 pathway to suppress TNBC migration and invasion by directly targeting RSK2. These results suggested that VIT is a potential drug candidate for TNBC treatment.

Protein misfolding and aggregation of alpha-synuclein (α-syn) are central to Parkinson's disease (PD). Current therapies provide only symptomatic relief without addressing α-syn aggregation. Chemical chaperones such as 4-phenylbutyrate (4-PBA) and tauroursodeoxycholic acid (TUDCA) show promise but are limited by toxicity and high dosage requirements. This study aimed to develop a safer, more effective multi-target compound to counter α-syn aggregation and related cellular stress. To design, synthesize, and evaluate a novel multi-target chemical chaperone, IP-045, for inhibiting α-syn aggregation and ameliorating PD pathology. A structure-based virtual screen of >11,000 compounds against the α-syn fibril structure (PDB ID: 6UFR) identified four candidates with favorable pharmacokinetics. In vitro aggregation assays and SHSY5Y cell models assessed anti-aggregation activity, cytotoxicity, and modulation of rotenone-induced α-syn expression, oxidative stress, and ER stress. The lead compound, IP-045 (2-Fluorophenyl 3-(1H-indol-3-yl)propanoate), was synthesized and tested in a rotenone-induced PD rat model through behavioral, histological, and molecular analyses. IP-045 strongly inhibited α-syn aggregation in vitro with minimal cytotoxicity. In cell-based assays, it reduced reactive oxygen species, ER stress markers, and α-syn expression. In vivo, IP-045 improved motor coordination, memory, and cognitive performance. Immunohistochemistry showed reduced Ser129-phosphorylated α-syn and restored tyrosine hydroxylase. IP-045 also suppressed apoptotic and pro-inflammatory markers in the substantia nigra, confirming multi-target neuroprotective activity. IP-045 demonstrated favorable anti-aggregation and neuroprotective effects across in vitro and in vivo models, indicating its potential as a promising lead compound with chaperone-like activity for targeting pathological processes associated with PD. Further pharmacokinetic, toxicity, and mechanistic studies are warranted to support its future therapeutic development.

Drug repurposing involves identifying new therapeutic applications for existing clinically evaluated compounds. In contrast to conventional drug development, which typically spans over a decade and demands substantial financial investment, repurposed drugs can achieve regulatory approval in approximately half the time and cost by capitalizing on their established pharmacokinetic, safety, and clinical profiles. This review provides a comprehensive analysis of the traditional and computational strategies employed in drug repurposing. Experimental methodologies include binding affinity assays, clinical data mining and phenotype-based screening. Computational approaches are categorized into structure-based, signature-based, pathway-based, knowledge-based, and target-based strategies. The recent integration of artificial intelligence (AI) and machine learning (ML) within repurposing pipelines is also examined, emphasizing their ability to efficiently process large-scale datasets, improve the predictive accuracy of drug-target interactions, and support the advancement of repurposing efforts. Furthermore, this review systematically compares prominent computational platforms, virtual screening tools, and bioinformatics resources, highlighting their respective strengths and limitations. Emerging AI-driven models, such as deep learning architectures, graph neural networks, knowledge graphs, and network pharmacology frameworks, have transformative roles in broadening the scope of drug repurposing. This comprehensive review is intended to assist medicinal chemists, computational biologists, and drug discovery scientists in expediting research efforts by effectively utilizing existing resources for repurposing-driven innovations.

ABSTRACTHexahydroquinoline (HHQ) is a widely recognized scaffold that has garnered considerable attention owing to its diverse pharmacological properties. The structure of HHQ includes a 1,4‐dihydropyridine (DHP) ring, which serves as the pharmacophore for the predominant class of drugs known as calcium channel blockers. DHPs are frequently utilized in the management of cardiovascular diseases and also show potential for pain management. Since all DHPs on the market possess ester functionality, we aimed to employ bioisosteric replacement to observe if their amide‐containing counterparts would still block calcium channels. Therefore, we synthesized new HHQs with ester or amide functionality (EM1‐EM15) and investigated their effects on L‐(Cav1.2) and T‐(Cav3.2)‐type calcium channels using the whole‐cell patch clamp technique. Although the amide derivatives were somewhat less effective than their ester counterparts, they still blocked calcium channels to a significant degree. Retesting EM4 enantiomers on two types of calcium channels demonstrated that the (R)‐isomer was more responsible for the blocking activity in both cases. Molecular docking and molecular dynamics simulations demonstrated that (R)‐EM4 and (R)‐EM6 adopt binding modes in Cav1.2 similar to amlodipine, while showing favorable stability. Docking studies in Cav3.2 suggested that EM compounds bind within the Ⅲ‐Ⅳ fenestration, a reported non‐selective DHP binding site. Furthermore, amide derivatives were found to be more metabolically stable based on the in vitro experiments conducted on rat microsomes. Overall, our study reveals HHQ with an amide group as a promising new scaffold for developing future calcium channel blockers for treating cardiovascular and pain conditions.

Sepsis, a life-threatening condition triggered by dysregulated host response to infection, poses significant global health challenges. Identifying lipopolysaccharide (LPS)-related biomarkers and underlying mechanisms remains critical, yet underexplored. We integrated bulk microarray datasets and single-cell RNA-seq data from the Gene Expression Omnibus to identify LPS-related genes associated with sepsis. scRNA-seq was used for cell clustering, annotation, AUCell scoring, and cell-cell communication analysis. Differentially expressed LRGs were screened from both bulk and single-cell datasets and intersected. Three machine learning algorithms-least absolute shrinkage and selection operator regression, support vector machine-recursive feature elimination, and extreme gradient boosting-were applied to select robust diagnostic biomarkers. Gene expression was validated via qRT-PCR. Diagnostic and prognostic models were constructed and validated in independent cohorts. Seven key LRGs were identified. The diagnostic model achieved high AUCs (> 0.89) across validation cohorts, while the prognostic model effectively stratified patients into distinct survival groups. High-risk groups showed increased myeloid-derived suppressor cell and macrophage infiltration, activation of inflammatory pathways, and unique intercellular communication networks. scRNA-seq revealed cell-type-specific LRGs expression, particularly in myeloid populations. We established and validated a robust LPS-related biomarker model that integrates bulk microarray and single-cell transcriptomics, offering novel diagnostic, prognostic, and therapeutic insights for sepsis.

This study aimed to explore the therapeutic effect and underlying mechanism of α7 nicotinic acetylcholine receptor (α7nAChR) mediated by adeno-associated virus serotype 9 (AAV9) on dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) in mice. Male C57BL/6 mice were randomly divided into the blank control group, model group, AAV-α7nAChR low/medium/high-dose groups, and AAV-GFP group. A chronic UC model was established, with interventions administered via intraperitoneal injection. Meanwhile, an acute UC model was set up, together with control groups treated with the α7nAChR antagonist methyllycaconitine (MLA) and 5-aminosalicylic acid (5-ASA). A series of indicators were detected, including body weight, Disease Activity Index (DAI), colonic pathological changes, inflammatory factors, pathway-related proteins, and T-regulatory (T-reg)/T helper 17 (Th-17) cell balance. Results demonstrated that AAV9-α7nAChR ameliorated UC symptoms in mice in a dose-dependent manner: it relieved body weight loss and hematochezia, restored colon length and spleen weight, and alleviated colonic mucosal damage. Furthermore, it activated the cholinergic anti-inflammatory pathway (CAP), inhibited the NF-κB/NLRP3 inflammatory axis, repaired the intestinal barrier (by upregulating ZO-1 and occludin), and restored the T-reg/Th-17 immune balance. The therapeutic efficacy of the high-dose AAV9-α7nAChR group was superior to that of the 5-ASA group, while MLA could suppress its therapeutic effect. This study preliminarily clarified the multi-target mechanism of AAV9-α7nAChR in treating UC, providing an experimental foundation for the clinical gene therapy of UC.

The epidermal growth factor receptor (EGFR) is a key target in cancer therapy, mainly in non-small cell lung cancer (NSCLC). Though, the efficacy of EGFR-targeted therapies is limited by the development of resistance. This comprehensive review details the structural biology of EGFR and its role in oncogenic signaling, elucidating the major activating mutations, particularly exon 19 deletions and L858R point mutations, and acquired resistance. The progressive development of EGFR tyrosine kinase inhibitors (TKIs), from first-generation ATP-competitive inhibitors (e.g., gefitinib, erlotinib) to third-generation covalent agents (e.g., osimertinib) and emerging fourth-generation allosteric and degradation approaches, are critically examined for their mechanisms, efficacy, and clinical limitations. We have also discussed about the intrinsic and acquired resistance mechanisms, including alternative oncogenic drivers (KRAS, ALK), bypass pathway activations (MET, HER2), and phenotypic changes like epithelial-mesenchymal transition. Additionally, we emphasize the role of computational modeling, high-throughput SAR studies, and preclinical models, including patient-derived xenografts and organoids, in guiding rational drug design. Emerging approaches integrating artificial intelligence, machine learning, and precision oncology hold potential to accelerate EGFR-targeted drug discovery. The combination strategies with immunotherapy, and anti-angiogenic agents are considered in the context of improving patient outcomes. Together, ongoing advances in understanding EGFR signaling and resistance mechanisms are driving the development of next-generation inhibitors and personalized therapies, with the ultimate goal of overcoming drug resistance and improve patient outcomes in EGFR-mutant cancers.