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Multi-omics identification of therapeutic targets of compound sappan decoction in hepatocellular carcinoma.

BACKGROUND: Compound sappan decoction (CSD) is a multi-herbal traditional Chinese medicine formulation with clinical relevance in hepatocellular carcinoma (HCC). However, its therapeutic mechanisms remain unclear. METHODS: Bioactive compounds of CSD were identified and standardized using pharmacological and chemical databases. Potential targets were predicted via multiple target inference platforms. HCC-related genes were curated from comprehensive disease databases. Summary-data-based Mendelian randomization (SMR) was conducted to infer causal relationships between compound targets and HCC risk using large-scale quantitative trait loci (QTL) datasets and HCC genome-wide association study data. Colocalization analysis, protein-protein interaction (PPI) network construction, and GO/KEGG enrichment were performed on SMR-identified targets. Molecular docking evaluated binding affinities of representative compounds to prioritized targets. RESULTS: A total of 784 overlapping genes between predicted CSD targets and HCC-related genes were subjected to SMR analysis. Among these, 22 targets were significantly associated with HCC risk based on transcriptomic or proteomic QTLs and showed colocalization evidence. Notably, four targets (ADRB2, APOE, SYK, and PGF) were supported by both replication in an independent cohort and strong colocalization. These 22 targets were enriched in apoptosis, PI3K-Akt signaling, redox metabolism, and detoxification pathways. PPI analysis revealed central hubs including MMP9, BCL2, CASP1, and MCL1. Molecular docking demonstrated strong binding of APOE to quercetin, PGF to luteolin-7-olate, and SYK to kaempferol. CONCLUSIONS: CSD may exert therapeutic effects on HCC through modulation of genetically validated targets involved in tumor progression, inflammation, and metabolic reprogramming, supporting its potential clinical utility as an adjunctive treatment strategy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s12672-026-04740-8.

Caesalpinia

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Biological Products

A Computational Workflow for Prioritizing Microbial Metabolite-Associated Host Genes in Constipation-Predominant Irritable Bowel Syndrome.

No standardized computational pipeline exists for systematically prioritizing microbial metabolite-associated host genes and protein-ligand complexes from publicly available chemical, genomic, and structural databases. This article describes an eight-stage workflow that accepts a user-defined set of gut microbiota-derived metabolites and produces a ranked shortlist of candidate metabolite-associated host genes, enriched biological pathways, and structurally prioritized protein-ligand complexes for experimental follow-up. The pipeline integrates (i) chemoinformatic metabolite profiling; (ii) multi-database candidate target prediction using protein-chemical interaction and ligand-based target-prediction tool and a molecular docking program; (iii) differential gene expression analysis of publicly available transcriptomic data; (iv) target-differentially expressed gene overlap; (v) protein-protein interaction network construction and pathway enrichment; (vi) molecular docking with a molecular docking program; (vii) 200 ns molecular dynamics simulation using a molecular dynamics engine with a protein force field used for molecular dynamics simulations; and (viii) MM-PBSA binding free-energy estimation. As a worked example, nine gut microbiota-derived or microbiota-modified metabolites representing short-chain fatty acids, bile acids, tryptophan-derived metabolites, and urolithin A were processed using the public IBS-C rectal mucosal transcriptomic dataset GSE36701. The workflow ranked 17 unique predicted metabolite-associated genes that were differentially expressed in this dataset. Docking, molecular dynamics simulation, and MM-PBSA analyses structurally prioritized five metabolite-protein complexes: lithocholic acid-VDR, lithocholic acid-NR1H4/FXR, ursodeoxycholic acid-NR1H4/FXR, tryptamine-HTR2A (simulated in an explicit 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer), and urolithin A-CASP3. The protocol is designed to be adaptable to other metabolite sets, disease transcriptomic datasets, and target classes; all outputs are hypothesis-generating computational predictions that require independent transcriptomic replication, protein-level validation, and functional ligand-response assays before causal or therapeutic conclusions can be drawn.

Irritable Bowel Syndrome

Analysis of the molecular mechanism underlying di(2-ethylhexyl) phthalate-induced bladder carcinogenesis via network toxicology and molecular docking approaches: An observational study.

This study aims to investigate the toxicity of di(2-ethylhexyl) phthalate (DEHP) and the potential molecular mechanisms of DEHP-induced bladder cancer (BLCA) using network toxicology and molecular docking strategies. The toxicity of DEHP was assessed using Prox-II software, and potential targets for DEHP-induced BLCA were identified by integrating data from ChEMBL database, Search Tool for Interactions of Chemicals, SwissTargetPrediction, GeneCards, Therapeutic Target Database, Online Mendelian Inheritance in Man, and The Cancer Genome Atlas. STRING database and Cytoscape were employed to construct target networks and determine core targets. The expression levels of core targets were analyzed using R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on potential and core targets. Molecular docking was carried out using CB-Dock 2 to verify the interactions between DEHP and core targets. A total of 105 potential targets related to DEHP-induced BLCA were identified, from which 7 core targets were selected: cyclin-dependent kinase 1, interleukin 6, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, cyclin B2, and B-cell lymphoma 2. IL-6 and B-cell lymphoma 2 showed downregulated expression in tumor tissues, while cyclin-dependent kinase 1, cyclin-dependent kinase 2, cyclin B1, Erb-B2 receptor tyrosine kinase 2, and cyclin B2 were upregulated. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated that these targets were enriched in cell signaling and cancer-related pathways. Molecular docking confirmed that DEHP interacts with these core targets. DEHP may promote the development of BLCA by interacting with key proteins and signaling pathways. This study provides a theoretical basis for understanding the molecular mechanisms of DEHP-induced BLCA and offers references for future prevention and treatment strategies.

Diethylhexyl Phthalate

ToxiVerse: chemical bioprofiling, toxicity data sharing and customizable predictive modeling.

MOTIVATION: Chemical toxicity assessment is critical for drug development and environmental safety. Computational models have emerged as a promising alternative to animal testing and now play a significant role in efficiently evaluating new chemicals. To address the urgent need for user-friendly machine learning tools in computational toxicology, we developed ToxiVerse, a public web-based platform. RESULTS: ToxiVerse provides automatic chemical bioprofiling, curated toxicity datasets, and a predictive modeling interface designed for researchers who lack programming expertise. The platform comprises three integrated modules: (i) Bioprofiler, which provides chemical descriptors by combining chemical-bioactivity data from PubChem assays with a machine learning-based data gap-filling procedure; (ii) Database, which hosts ∼50 000 curated chemicals covering diverse toxicity endpoints; and (iii) Cheminformatics, which enables dataset upload, chemical curation, and automatic generation of quantitative structure-activity relationship models for toxicity prediction. AVAILABILITY: The tool is accessible at www.toxiverse.com, and source code is available at https://github.com/zhu-research-group/toxiverse.

Quantitative Structure-Activity Relationship

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy.

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Databases, Protein

A research synthesis of humans, animals, and environmental compartments exposed to PFAS: A systematic evidence map and bibliometric analysis of secondary literature.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are a class of widely used anthropogenic chemicals. Concerns regarding their persistence and potential adverse effects have led to multiple secondary research publications. Here, we aim to assess the resulting evidence base in the systematic secondary literature by examining research gaps, evaluating the quality of reviews, and exploring interdisciplinary connections. METHODS: This study employed a systematic evidence-mapping approach to assess the secondary literature on the biological, environmental, and medical aspects of exposure to 35 fluorinated compounds. The inclusion criteria encompassed systematic reviews published in peer-reviewed journals, pre-prints, and theses. Comprehensive searches across electronic databases and grey literature identified relevant reviews. Data extraction and synthesis involved mapping literature content and narrative descriptions. We employed a modified version of the AMSTAR2 checklist to evaluate the methodological rigour of the reviews. A bibliometric data analysis uncovered patterns and trends in the academic literature. A research protocol for this study was previously pre-registered (osf.io/2tpn8) and published (Vendl et al., Environment International 158 (2022) 106973). The database is freely accessible through the interactive and user-friendly web application of this systematic evidence map at https://hi-this-is-lorenzo.shinyapps.io/PFAS_SEM_Shiny_App/. RESULTS: Our map includes a total of 175 systematic reviews. Over the years, there has been a steady increase in the annual number of publications, with a notable surge in 2021. Most reviews focused on human exposure, whereas environmental and animal-related reviews were fewer and often lacked a rigorous systematic approach to literature search and screening. Review outcomes were predominantly associated with human health, particularly with reproductive and children's developmental health. Animal reviews primarily focused on studies conducted in controlled laboratory settings, and wildlife reviews were characterised by an over-representation of birds and fish species. Recent reviews increasingly incorporated quantitative synthesis methodologies. The methodological strengths of the reviews included detailed descriptions of study selection processes and disclosure of potential conflicts of interest. However, weaknesses were observed in the critical lack of detail in reporting methods. A bibliometric analysis revealed that the most productive authors collaborate within their own country, leading to limited and clustered international collaborations. CONCLUSIONS: In this overview of the available systematic secondary literature, we map literature content, assess reviews' methodological quality, highlight data gaps, and draw research network clusters. We aim to facilitate literature reviews, guide future research initiatives, and enhance opportunities for cross-country collaboration. Furthermore, we discuss how this systematic evidence map and its publicly available database benefit scientists, regulatory agencies, and other stakeholders by providing access to current systematic secondary literature on PFAS exposure.

Bibliometrics

In silico analysis based on network pharmacology and biomolecular informatics to explore the mechanism of action of Erjing Pills (from Shengji Zonglu) in the treatment of leukotrichia.

This study aimed to explore the core active ingredients and potential molecular mechanisms of Erjing Pills, a prescription in the classic work of Traditional Chinese Medicine, "Shengji Zonglu," in the treatment of leukotrichia by utilizing network pharmacology and biomolecular docking techniques. The chemical components and potential targets of Chinese herbal medicines were analyzed through databases such as the Traditional Chinese Medicine Systems Pharmacology Database. The targets related to leukotrichia were collected using GeneCards. The intersection targets were obtained using RStudio. The protein-protein interaction (PPI) network map and the "drug-component-target-disease" visualization network were generated using Cytoscape and STRING to screen the core components and key targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were carried out using the Database for Annotation, Visualization and Integrated Discovery and RStudio. Finally, molecular docking verification was performed by AutoDock and PyMOL (Schrödinger LLC). The key active ingredients of Erjing Pills in the treatment of leukotrichia are β-sitosterol, quercetin, baicalein, and stigmasterol. The top 5 PPI core target proteins, in order, are AKT serine/threonine kinase 1, interleukin 6, tumor protein p53, cysteine-aspartic acid protease 3, and interleukin 1 beta. The Gene Ontology enrichment analysis suggests that the biological processes mainly include responses to exogenous stimuli, membrane rafts, and DNA-binding transcription factor binding. The Kyoto Encyclopedia of Genes and Genomes pathways involve signal pathways such as lipid and atherosclerosis, hepatitis B, Kaposi sarcoma virus infection, chemical carcinogenesis, and human cytomegalovirus infection. The molecular docking results indicate that most of the main active ingredients in Erjing Pills have relatively stable binding activities with the key targets, such as AKT serine/threonine kinase 1, interleukin 6, tumor protein p53, cysteine-aspartic acid protease 3, and interleukin 1 beta, in the PPI network. The active ingredients of Erjing Pills may interfere with the pathological process of leukotrichia by regulating key targets and signal pathways. This study provides a theoretical basis for the clinical application of Erjing Pills and indicates the direction for subsequent experimental research.

Drugs, Chinese Herbal

Ageing effects on chemical, physical, mechanical, and morphological properties of clear aligners - a systematic review.

BACKGROUND: Clear aligner (CA) therapy has experienced rapid use over the past two decades to treat orthodontic malocclusions. However, evidence on CA material degradation in the oral environment remains limited and often focuses on single brands or isolated material properties. OBJECTIVES: To investigate CA ageing characteristics across different materials and brands and evaluate the chemical, physical, mechanical, and morphological changes following simulated or intraoral ageing. SEARCH METHODS: Five databases (PubMed, Web of Science, MEDLINE [Ovid], ProQuest, and Scopus) were searched to 18 March 2026, with no restrictions. ELIGIBILITY CRITERIA: Studies assessing CA properties after intraoral use or simulated ageing (thermocycling, cyclic loading, or liquid immersion) were included. DATA COLLECTION AND ANALYSIS: Study selection followed PRISMA 2020. RoB was assessed using QUIN for purely in vitro studies, JBI for cohort in vivo studies, and Cochrane RoB 2 for RCTs. Results were synthesised narratively and organised by property domain, as substantial methodological heterogeneity precluded formal meta-analysis. Where protocols were comparable, a simple pooled weighted mean was calculated and presented graphically. RESULTS: Ninety-five studies were included. RoB was low in eight studies, moderate in sixty-two, and high in twenty-five. Chemical composition remained largely stable during ageing, though some brands showed trace elemental release. Physical, mechanical, and morphological properties showed material-dependent deterioration. Pooled discolouration was greatest with coffee (weighted mean ΔE = 70.9), versus tea (ΔE = 18.4) and red wine (ΔE = 11.5), with Invisalign® consistently exceeding the clinically perceptible threshold. Force decay of 40-90% typically occurred within 48 h. Thermoplastic polyurethane (TPU)-based and directly printed aligners (DPAs) generally showed greater susceptibility than polyethylene terephthalate glycol-modified (PETG)-based aligners, though findings on hardness, roughness, and stiffness were inconsistent. CONCLUSIONS: CA materials undergo clinically relevant degradation during use, particularly in TPU-based and DPAs aligners. Clinicians may need to prioritise material-specific protocols, reinforce dietary and cleaning instructions, and consider force decay when determining aligner replacement intervals. PROSPERO number: CRD420251110248.

Humans

Association of MPO Expression with the Immune Microenvironment in Breast Cancer: Insights from Bioinformatics and Single-Cell Analyses.

Breast cancer remains a major cause of cancer-related mortality, and exploratory computational workflows can help prioritize immune-associated markers for further investigation. Here, we used the cancer genome atlas breast invasive carcinoma (TCGA-BRCA) bulk transcriptomic data and the public single-cell dataset GSE161529 to examine associations between myeloperoxidase (MPO) expression, clinical outcomes, immune infiltration, methylation, upstream-regulator annotations, single-cell expression patterns, virtual knockdown sensitivity outputs, drug-gene interaction retrieval, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) annotation. MPO expression was lower in breast cancer tissues than in adjacent non-tumor tissues. Higher MPO expression was associated with a longer progression-free interval, whereas its associations with overall survival and disease-specific survival were not statistically significant. Receiver operating characteristic (ROC) analysis suggested tumor-normal separation within the analyzed public dataset, but this should not be interpreted as clinical diagnostic validation. Immune deconvolution and enrichment analyses indicated that MPO expression mainly tracked with immune- and myeloid-related transcriptional features, rather than establishing tumor-intrinsic regulation of the immune microenvironment. At single-cell resolution, the MPO signal was sparse, with only 85 MPO-positive cells detected before k-nearest neighbor (KNN)-based neighborhood expansion. Detectable MPO signal and MPO-associated scores were interpreted cautiously because they may be influenced by sparse expression, cell-type annotation uncertainty, dropout, doublets, or ambient RNA. In silico virtual knockdown suggested candidate immune- and inflammatory-related transcriptional changes, but these results were considered exploratory and require validation. Drug-gene interaction database (DGIdb)-based drug-gene retrieval and ADMET annotation were used only as preliminary chemical annotations and were not interpreted as therapeutic evidence. Overall, this study provides a reproducible in silico workflow for generating hypotheses about MPO-associated immune/myeloid features in breast cancer, which require external cohort validation and experimental confirmation.

Humans

Exploring the Mechanism of Zhigancao Decoction in the Treatment of Chronic Heart Failure via Modulation of Oxidative Stress.

BACKGROUND: Zhigancao decoction has shown therapeutic potential in the management of chronic heart failure (CHF); however, the molecular mechanisms underlying its pharmacological effects remain incompletely understood. This study aimed to investigate its potential mechanisms, with a particular focus on oxidative stress-related pathways. METHODS: The chemical profile of Zhigancao decoction was characterized by LC-MS/MS, and putative targets were predicted using SwissTargetPrediction. A protein-protein interaction (PPI) network was established using the STRING database and Cytoscape software, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Differentially expressed genes from two GEO datasets (GSE9128 and GSE84796) were integrated with reactive oxygen species (ROS)-related genes to identify candidate targets. Network pharmacology and molecular docking were subsequently performed to investigate compound-target interactions. RESULTS: A total of 66 chemical constituents and 818 putative targets were characterized and collected, respectively. Among these targets, MMP9 emerged as a central candidate associated with the therapeutic effects of Zhigancao decoction. GO and KEGG enrichment analyses demonstrated that the core targets were significantly enriched in oxidative stress-related pathways, inflammatory signaling cascades, and cell fate regulatory pathways. Computational deconvolution of bulk transcriptomic data suggested marked alterations in the estimated immune cell composition of the CHF microenvironment. Network pharmacology analysis further indicated that multiple chemical constituents of Zhigancao decoction converge on MMP9 and its associated pathways. Molecular docking analysis demonstrated favorable binding affinities between 10 representative compounds and MMP9, with binding energies below -7.0 kcal/mol. CONCLUSIONS: In silico predictions suggest that Zhigancao decoction may exert potential therapeutic effects against CHF through computationally predicted targeting of MMP9 and associated oxidative stress- and immune-related pathways. These computational findings provide a theoretical foundation for future experimental investigations into the mechanisms of Zhigancao decoction in CHF, though clinical application would require confirmation through rigorous in vivo and clinical studies.

Oxidative Stress

Kefir and Its By-Products Supplementation Reduces Inflammation and Oxidative Stress, Improves Intestinal Barrier Integrity, and Modulates the Gut Microbiota in Animal Models of Inflammatory Bowel Disease: A Systematic Review.

UNLABELLED: Kefir is a beverage obtained by fermenting milk or sugary solutions with a symbiotic community of bacteria and yeasts, presenting promising antimicrobial, antioxidant, and immunomodulatory properties. This systematic review aimed to synthesize evidence from preclinical studies evaluating the effects of kefir or its by-products on biomarkers of inflammation, oxidative stress, and gut health in animal models of IBD. A systematic review was conducted in accordance with PRISMA guidelines, utilizing the PubMed/MEDLINE, Web of Science, Embase, and Scopus databases. The quality of the studies was assessed using SYRCLE’s Risk of Bias tool. Sixteen experimental studies were included, comprising 585 rodents with chemically induced colitis. The interventions included traditional milk kefir, rice and water kefir, as well as isolated microorganisms and kefir-derived supernatants. Most studies reported reductions in inflammatory cytokines (TNF-α, IL-1β, IL-6) and inflammatory enzymes (iNOS, COX-2, MPO), along with increases in anti-inflammatory cytokines (IL-10, IL-4). Reductions in MDA and H₂O₂ were reported, supporting the antioxidant effects of kefir and its derivatives. Changes in antioxidant enzyme activity, including SOD, were also observed. In addition, kefir modulated gut microbiota composition, upregulated the expression of tight junction proteins, and influenced immune and molecular signaling pathways. Improvements were also observed in clinical parameters of IBD models, including disease activity index, rectal bleeding, and histological damage. Kefir and its derivatives exhibit beneficial effects on inflammation, oxidative stress, gut permeability, and immune modulation in animal models of IBD, suggesting a potential alternative for treating these diseases in humans. Although the findings are promising, heterogeneity among study protocols and methodological limitations highlight the need for further studies. Registration PROSPERO number: CRD420251062931. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s12602-026-10948-5.

Animal model

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans

Polycystic ovary syndrome and idiopathic central precocious puberty: two sides of the same coin?

PURPOSE: Several studies have reported an association between central precocious puberty (CPP) and a higher prevalence of polycystic ovary syndrome (PCOS), raising the hypothesis that CPP may act as an early-life indicator of increased PCOS risk. This review investigates the shared genetic, epigenetic, and environmental factors potentially underlying CPP and PCOS, with the aim of clarifying their connection and supporting advances in early detection and management. METHODS: A comprehensive literature review was conducted using the PubMed/MEDLINE database, prioritizing research from the past two decades, supplemented by key studies from earlier years. This research included studies on genetic and epigenetic factors, endocrine-disrupting chemicals (EDCs), and metabolic influences related to CPP and PCOS. Both original research and review articles were selected, focusing on the identification of pathophysiological mechanisms and risk factors linking these disorders. RESULTS: Genome-wide association studies (GWAS) have linked genetic variants in the kisspeptin and neurokinin B signaling pathways to increased gonadotropin-releasing hormone (GnRH) secretion, triggering early puberty. Moreover, increased GnRH pulsatility contributes to elevated luteinizing hormone (LH) levels, altered LH/follicle-stimulating hormone (FSH) ratios, and ovarian hyperandrogenism—key pathophysiological features of PCOS. Additionally, epigenetic modifications, particularly changes in DNA methylation at CpG sites, have been observed in both CPP and PCOS. A hyperandrogenic intrauterine environment and inadequate fetal growth contribute to prenatal epigenetic alterations, while postnatal factors such as obesity, insulin resistance, and exposure to EDCs further influence epigenetic modifications. Although insulin resistance and hyperandrogenism are central features linking CPP to PCOS, the precise mechanisms underlying these associations remain complex and not yet fully elucidated. CONCLUSIONS: Identifying shared genetic and environmental factors influencing early puberty onset and PCOS highlights the importance of close clinical monitoring in early life, though preventive interventions remain unproven. Further research is needed to clarify these mechanisms, which will support the development of more precise prevention and treatment strategies in clinical practice.

Humans

Active components and potential mechanisms of Wuzhuyu decoction in the treatment of ethanol-induced acute gastric mucosal injury: a network pharmacology and experimental verification.

OBJECTIVE: To investigate the underlying mechanisms and active components of Wuzhuyu decoction (, WD) in alleviating ethanol-induced acute gastric mucosal injury (GMI) using an integrated approach of network pharmacology and experimental verification. METHODS: Sprague-Dawley rats were randomly divided into six groups: control (Con), model (Mod), bismuth potassium citrate (BPC), WD at low (WD-L), medium (WD-M), and high (WD-H) doses. Following seven days of continuous intragastric administration of the respective treatments, an ethanol-induced gastric mucosal injury model was established in all groups except the control group by oral gavage of anhydrous ethanol. The gastric mucosal injury index was evaluated, and pathological changes were assessed viahematoxylin and eosin (HE) staining. Levels of tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) were measured by enzyme-linked immunosorbent assay (ELISA). The chemical composition was identified by ultra-performance liquid chromatography-tandem mass spectrometry. Active compounds were screened using the Swiss-absorption, distribution, metabolism, and excretion database, and their potential targets were predicted using the Swiss Target Prediction database and bioinformatics annotation database for molecular mechanism. Simultaneously, disease targets related to GMI were retrieved from the online mendelian inheritance in man and GeneCards databases. A protein-protein interaction (PPI) network was constructed, and functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the Metascape database. Key predictions from the network pharmacology analysis were subsequently verified through animal experiments. Protein expression levels of B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), Cleaved Caspase-3, and Cleaved Caspase-9 were analyzed by Western blot. Finally, molecular docking was performed using AutoDock Vina to investigate the interactions between the active components and core targets. RESULTS: WD treatment significantly reduced the gastric mucosal injury index and the levels of TNF-α, IL-1β, MDA, while it increased the activities of SOD and GSH-Px. Histopathological examination revealed marked improvement in gastric tissue morphology. A total of 145 compounds were identified in WD. Network pharmacology analysis identified 440 overlapping targets between WD and GMI. GO and KEGG enrichment analyses highlighted the apoptosis signaling pathway as a key mechanism for WD's protective effect against ethanol-induced GMI. Experimental validation demonstrated that WD treatment reduced the apoptosis of gastric mucosal epithelial cells, promoted the expression of Bcl-2, and inhibited the expression of Bax, Cleaved Caspase-3 and Cleaved Caspase-9. Molecular docking results indicated that dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin are potential active components in WD that contribute to the inhibition of apoptosis. CONCLUSIONS: WD alleviates ethanol-induced acute GMI, at least in part, by inhibiting the apoptosis. The primary active components responsible for this effect are dehydroevodiamine, rutaecarpine, evodiamine, hexahydrocurcumin, and isorhamnetin.

Drugs, Chinese Herbal

Drug target ontology to classify and integrate drug discovery data.

BACKGROUND: One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. RESULTS: As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

Biological Ontologies

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4 > 0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans

Comprehensive identification of carboxylic acids by using bromine isotope-based chemical isotope labelling and structure-guided molecular network.

Carboxylic acids (CAs) are important contributors to the flavor quality of sauce-flavor Chinese Baijiu, yet their comprehensive analysis remains challenging due to poor ionization efficiency, weak chromatographic retention, and limited annotation capability. Herein, we developed a workflow for the high-coverage discovery and annotation of CAs in Baijiu by coupling chemical isotope labeling-liquid chromatography-mass spectrometry with a structure-guided molecular network strategy (SGMNS). A bromine-containing derivatization reagent, 1-(3-aminopropyl)-3-bromoquinolin-1-ium bromide (APBQ), was designed and synthesized to exploit the natural isotope distribution of bromine and characteristic MS/MS fragmentation behavior. Following APBQ derivatization, the target CAs showed superior chromatographic retention and favorable analytical performance. Based on isotopic peak pairing in MS1 and diagnostic fragment validation in MS2, 372 potential CA derivatives were discovered from pooled Baijiu samples and 355 of them were validated by diagnostic fragments in MS2 spectra. To address the scarcity of derivatized spectral libraries, SGMNS was employed for annotation using a background network constructed from APBQ-labeled candidates derived from the Expanded Chinese Baijiu Compound Database. The developed method was further applied to profile Baijiu samples, revealing pronounced differences in CA composition across the seven fermentation rounds. Notably, rounds 3 to 5 exhibited the largest numbers of differential CAs. This study provided an effective analytical strategy for large-scale CA profiling, offering new insight into the chemical basis of flavor formation during multi-round fermentation of sauce-flavor Baijiu.

Isotope Labeling