Ganoderma lucidum polysaccharides (G. PS) have been recognized for their immune-modulating properties. In this study, we investigated the impact of G. PS in a sepsis mouse model, exploring its effects on survival, inflammatory cytokines, Treg cell differentiation, bacterial load, organ dysfunction, and related pathways. We also probed the role of macrophages through chlorphosphon-liposome pretreatment. Using the cecal ligation and puncture (CLP) model, we categorized mice into normal, PBS, and G. PS injection groups. G. PS significantly enhanced septic mouse survival, regulated inflammatory cytokines (TNF-α, IL-17A, IL-6, IL-10), and promoted CD4+Foxp3+ Treg cell differentiation in spleens. Additionally, G. PS reduced bacterial load, mitigated organ damage, and suppressed the NF-κB pathway. In vitro, G. PS facilitated CD4⁺ T cell differentiation into Treg cells via the p-STAT5 pathway. Chlorphosphon-liposome pretreatment heightened septic mortality, bacterial load, biochemical markers, and organ damage, emphasizing macrophages' involvement. G. PS demonstrated significant protective effects in septic mice by modulating inflammatory responses, enhancing Treg cell differentiation, diminishing bacterial load, and inhibiting inflammatory pathways. These findings illuminate the therapeutic potential of G. PS in sepsis treatment.

Adhatoda vasica Nees (AVN) is commonly used to treat joint diseases such as rheumatoid arthritis (RA) in ethnic minority areas of China, especially in Tibetan and Dai areas, and its molecular mechanisms on RA still remain unclear. Network pharmacology, a novel strategy, utilizes bioinformatics to predict and evaluate drug targets and interactions in disease. Here, network pharmacology was used to investigate the mechanism by which AVN acts in RA. The chemical compositions and functional targets of AVN were retrieved using the systematic pharmacological analysis platform PharmMapper. The targets of RA were queried through the DrugBank database. The protein‐protein interaction network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of key targets were constructed in the STRING database, and the network visualization analysis was performed in Cytoscape. Maestro 11.1, a type of professional software, was used for verifying prediction and analysis based on network pharmacology. By comparing the predicted target information with the targets of RA‐related drugs, 25 potential targets may be related to the treatment of RA, among which MAPK1, TNF, DHODH, IL2, PTGS2, and JAK2 may be the main potential targets for the treatment of RA. Finally, the chemical components and potential target proteins were scored by molecular docking, and compared with the ligands of the protein, the prediction results of network pharmacology were preliminarily verified. The active ingredients and mechanism of AVN against RA were firstly investigated using network pharmacology. Additionally, this research provided a solid foundation for further experimental studies.

Smilax china L. (SCL) is extensively used in the treatment of pelvic inflammatory disease (PID). This study aimed to clarify the potential active ingredients of SCL and mechanisms on PID. SCL was widely distributed in Japan, South Korea, and China, which was traditionally considered heat-clearing, detoxicating, and dampness-eliminating medicine. Systems pharmacology revealed that 32 compounds in SCL may interact with 19 targets for immunoenhancement, antiapoptosis, anti-inflammation, and antioxidant activity of the PID model. Molecular docking revealed that isorhamnetin, moracin M, rutin, and oxyresveratrol may have higher binding potential with prostaglandin-endoperoxide synthase 2 (PTGS2), mitogen-activated protein kinase 1 (MAPK1), siderocalin (LCN2), tumor necrosis factor (TNF), and matrix metalloprotein-9 (MMP9), respectively. Molecular dynamics simulation showed that the binding modes of moracin M-MAPK1, rutin-TNF, and oxyresveratrol-MMP9 complexes were more stable, evidenced by relatively smaller fluctuations in root mean square deviation values. Conclusively, SCL may treat PID by inhibiting inflammatory factors, antitissue fibrosis, and microbial growth.