Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune disease that may lead to joint damage, deformity, and disability, if not treated effectively. Hedyotis diffusa Willd (HDW) and its main components have been widely used to treat a variety of tumors and inflammatory diseases. The present study utilized a network pharmacology approach, microarray data analysis and molecular docking to predict the key active ingredients and mechanisms of HDW against RA. Eleven active ingredients in HDW and 180 potential anti-RA targets were identified. The ingredients-targets-RA network showed that stigmasterol, beta-sitosterol, quercetin, kaempferol, and 2-methoxy-3-methyl-9,10-anthraquinone were key components for RA treatment. KEGG pathway results revealed that the 180 potential targets were inflammatory-related pathways with predominant enrichment of the AGE-RAGE, TNF, IL17, and PI3K-Akt signaling pathways. Screened through the PPI network and with Cytoscape software, RELA, TNF, IL6, TP53, MAPK1, AKT1, IL10, and ESR1 were identified as the hub targets in the HDW for RA treatment. Molecular docking was used to identify the binding of 5 key components and the 8 related-RA hub targets. Moreover, the results of network pharmacology were verified by vitro experiments. HDW inhibits cell proliferation in MH7A cells in a dose and time-dependent manner. RT-qPCR and WB results suggest that HDW may affect hub targets through PI3K/AKT signaling pathway, thereby exerting anti-RA effect. This study provides evidence for a clinical effect of HDW on RA and a research basis for further investigation into the active ingredients and mechanisms of HDW against RA.

Hedyotisdiffusa Willd (HDW) possesses heat-clearing, detoxification, anti-cancer, and anti-inflammatory properties. However, its effects on rheumatoid arthritis (RA) remain under-researched. In this study, we identified potential targets of HDW and collected differentially expressed genes of RA from the GEO dataset GSE77298, leading to the construction of a drug-component-target-disease regulatory network. The intersecting genes underwent GO and KEGG analysis. A PPI protein interaction network was established in the STRING database. Through LASSO, RF, and SVM-RFE algorithms, we identified the core gene MMP9. Subsequent analyses, including ROC, GSEA enrichment, and immune cell infiltration, correlated core genes with RA. mRNA–miRNA–lncRNA regulatory networks were predicted using databases like TargetScan, miRTarBase, miRWalk, starBase, lncBase, and the GEO dataset GSE122616. Experimental verification in RA-FLS cells confirmed HDW’s regulatory impact on core genes and their ceRNA expression. We obtained 11 main active ingredients of HDW and 180 corresponding targets, 2150 RA-related genes, and 36 drug-disease intersection targets. The PPI network diagram and three machine learning methods screened to obtain MMP9, and further analysis showed that MMP9 had high diagnostic significance and was significantly correlated with the main infiltrated immune cells, and the molecular docking verification also showed that MMP9 and the main active components of HDW were well combined. Next, we predicted 6 miRNAs and 314 lncRNAs acting on MMP9, and two ceRNA regulatory axes were obtained according to the screening. Cellular assays indicated HDW inhibits RA-FLS cell proliferation and MMP9 protein expression dose-dependently, suggesting HDW might influence RA’s progression by regulating the MMP9/miR-204-5p/MIAT axis. This innovative analytical thinking provides guidance and reference for the future research on the ceRNA mechanism of traditional Chinese medicine in the treatment of RA.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects millions worldwide, characterized by joint pain, swelling, and functional impairment. Current treatments like Non-steroidal anti-inflammatory drugs (NSAIDs), corticosteroids, and biologics, have limitations including side effects and resistance problems, which create a need for new therapeutic strategies. This study aims to explore the potential therapeutic role and mechanisms of Geniposide (GE), a natural compound extracted from Gardenia jasminoides, in RA treatment. Through network pharmacology methods and using target prediction databases including TCMSP, SwissTargetPrediction, Pharmmapper, and Batman, 330 potential targets of GE were identified. In RA, 1324 differentially expressed genes (DEGs) were identified from the GSE55235 dataset. By intersecting the datasets, 53 shared targets were identified, which were further analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, with pathways like IL-17 and JAK-STAT being significantly highlighted. Additionally, protein–protein interaction (PPI) network analysis identified 12 key targets (EGFR, MMP-9, CCL5, PPARG, STAT1, HCK, SYK, MAPK8, CTSB, RAC2, JAK2, TYMS) with high degree values. Furthermore, molecular docking studies confirmed strong binding affinities between GE and the identified targets. Experimental validation demonstrated that GE inhibited RA-FLS cell proliferation in a dose-dependent manner by using MTT assays and reduced the level of pro-inflammatory cytokines (IL-17, IL-8, TNF-α, MMP-3, MMP-9) as measured by ELISA. RT-qPCR and Western blot analyses further confirmed that GE modulated the mRNA expression of key targets and inhibited the phosphorylation of JAK1 and STAT1 proteins, respectively. Finally, we verified the anti-inflammatory effect of GE on CIA mice through in vivo experiments. These findings suggest that GE has anti-RA effects by targeting several key molecules and pathways. This provides a theoretical basis for developing GE as a novel therapeutic for RA.

Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune disease that may lead to joint damage, deformity, and disability, if not treated effectively. Hedyotis diffusa Willd (HDW) and its main components have been widely used to treat a variety of tumors and inflammatory diseases. The present study utilized a network pharmacology approach, microarray data analysis and molecular docking to predict the key active ingredients and mechanisms of HDW against RA. Eleven active ingredients in HDW and 180 potential anti-RA targets were identified. The ingredients-targets-RA network showed that stigmasterol, beta-sitosterol, quercetin, kaempferol, and 2-methoxy-3-methyl-9,10-anthraquinone were key components for RA treatment. KEGG pathway results revealed that the 180 potential targets were inflammatory-related pathways with predominant enrichment of the AGE-RAGE, TNF, IL17, and PI3K-Akt signaling pathways. Screened through the PPI network and with Cytoscape software, the expression levels of 8 hub targets, RELA, TNF, IL6, TP53, MAPK1, AKT1, IL10, and ESR1, were determined using 3 Gene Expression Omnibus (GEO) datasets and The Human Protein Atlas (HPA). Molecular docking was used to identify the binding of 5 key components and the 8 related-RA hub targets, providing evidence for a clinical effect of HDW on RA and a research basis for further investigation into the active ingredients and mechanisms of HDW against RA.

High mobility group box 1 (HMGB1) nuclear‑cytoplasmic translocation is a key event in sepsis‑associated inflammation, but the upstream mechanisms regulating this process remain incompletely understood. The present study aimed to investigate the associations among C‑X‑C motif chemokine ligand 8 (CXCL8)‑PI3K/Akt signaling in HMGB1 nuclear‑cytoplasmic translocation and to examine concurrent acetyltransferase (HAT)/histone deacetylase (HDAC)‑associated changes under inflammatory conditions. RAW264.7 macrophages were stimulated with lipopolysaccharide (LPS) to induce septic conditions and HMGB1 subcellular localization was assessed using western blotting. In addition, HAT and HDAC enzymatic activities were measured using colorimetric activity assay kits. Bioinformatics analysis of sepsis‑associated datasets (GSE46955 and GSE57065) identified CXCL8 as a hypothesis‑generating candidate core gene. In an LPS/IFN‑γ‑induced THP‑1‑derived inflammatory macrophage model, HMGB1 nuclear‑cytoplasmic translocation was also observed, together with increased CXCL8, CREB‑binding protein and p300 mRNA levels, decreased HDAC1, HDAC2 and HDAC4 mRNA levels and activated Akt phosphorylation at Ser473. Representative western blotting results following treatment with the C‑X‑C motif chemokine receptor (CXCR)1/2 inhibitor Reparixin or the PI3K inhibitor LY294002 provided preliminary support for the potential involvement of CXCR1/2‑PI3K/Akt signaling in HMGB1 nuclear‑cytoplasmic translocation. Collectively, these findings support a potential role for CXCL8/CXCR1/2‑PI3K/Akt signaling in HMGB1 nuclear‑cytoplasmic translocation and provide complementary, hypothesis‑generating evidence associating HAT/HDAC‑related changes to this process.