SummaryBackgroundImmune checkpoint inhibitor (ICI) combination therapy offers a new option for treatment of unresectable intrahepatic cholangiocarcinoma (uICC).AimTo compare the effect of different anti‐PD‐1 combination therapies as the first‐line treatments for uICC.MethodsThis study included 318 patients who received chemotherapy alone (Chemo), anti‐PD‐1 plus chemotherapy (ICI‐chemo), anti‐PD‐1 plus targeted therapy (ICI‐target) or anti‐PD‐1 plus targeted therapy and chemotherapy (ICI‐target‐chemo) as first line for uICC from 22 centres in China. The primary endpoint was progression‐free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR) and safety.ResultsPatients with ICI‐chemo (median PFS [mPFS], 6.3 months; HR: 0.61, 95% CI: 0.42–0.88; p = 0.008; median OS [mOS], 10.7 months; HR: 0.61, 95% CI: 0.39–0.94; p = 0.026), ICI‐target (7.2 months; HR: 0.54, 95% CI: 0.36–0.80; p = 0.002; 15.8 months; HR: 0.54, 95% CI: 0.35–0.84; p = 0.006) or ICI‐target‐chemo (6.9 months; HR: 0.65, 95% CI: 0.47–0.90; p = 0.009; 14.4 months; HR: 0.47, 95% CI: 0.31–0.70; p < 0.001) achieved better clinical outcomes than those with Chemo (3.8 months; 9.3 months). ICI‐target was not inferior to ICI‐chemo in survival outcomes (HR for PFS: 0.88, 95% CI: 0.55–1.42; p = 0.614; HR for OS: 0.89, 95% CI: 0.51–1.55; p = 0.680). ICI‐target‐chemo yielded similar prognoses as ICI‐chemo (HR for PFS: 1.07, 95% CI: 0.70–1.62; p = 0.764; HR for OS: 0.77, 95% CI: 0.45–1.31; p = 0.328) and ICI‐target (HR for PFS: 1.20, 95% CI: 0.77–1.88; p = 0.413; HR for OS: 0.86, 95% CI: 0.51–1.47; p = 0.583) but resulted in more adverse events (p < 0.001; p = 0.010). Multivariable and propensity score analyses supported these findings.ConclusionsAmong patients with uICC, ICI‐chemo or ICI‐target provided more survival benefits than Chemo while achieving comparable prognoses and fewer adverse events than ICI‐target‐chemo.

Objective. In this study, we investigated the potential material basis of Yupingfeng powder in the prevention and treatment of 2019 novel coronavirus pneumonia (NCP) by applying molecular docking and molecular dynamic simulation technology. Design. The active ingredients and predictive targets of Yupingfeng powder were sourced using the TCMSP, ETCM, and TCMIP traditional Chinese medicine databases. NCP-related targets were then acquired from the DisGeNET and GeneCards databases, and common disease-drug targets were imported into the STRING database, and Cytoscape software was used to generate a protein-protein interaction network following the use of a network topology algorithm to identify key target genes. Gene Ontology (GO) and KEGG pathway enrichment analysis was then performed using the target genes and GOEAST and DAVID online tools. The mechanism of Yupingfeng powder in the prevention and treatment of NCP was analyzed with reference to the relevant literature. AutoDock software was used for molecular docking, the preliminary analysis of binding status, and to identify the best conformation. Desmond software was used to perform molecular dynamic simulations for protein and compound complexes, perform free energy calculations and hydrogen bond analysis, and to further verify the binding mode. Results. Overall, 38 main active components and 218 predictive targets of Yupingfeng powder were identified and 298 disease targets related to NCP were retrieved from disease databases. Yupingfeng powder was found to act predominantly on the TNF, Toll-like receptor, HIF-1, NOD-like receptor, cytokine-receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. Molecular docking of the three selected key active components with the 3CL-like protease (3CL-Pro) of SARS-CoV-2 showed that they each had a strong binding force and good affinity. Conclusions. Yupingfeng powder primarily acts on multiple active ingredients and potential targets through multiple action channels and signal pathways. Molecular docking and molecular dynamic simulation technology were used to effectively predict and analyze the potential mechanism by which this Chinese medicine can combat NCP. These results provide a reference for developing new modern Chinese medicine preparations against NCP in the future.

Quercetin has demonstrated antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic activities, suggesting therapeutic potential against type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD). In this study, potential molecular targets of quercetin were first identified using the Swiss Target Prediction platform and pathogenic targets of T2DM and AD were identified using Online Mendelian Inheritance in Man (OMIM), DisGeNET, TTD, DrugBank, and GeneCards databases. The 95 targets shared among quercetin, T2DM, and AD were used to establish a protein–protein interaction (PPI) network, top 25 core genes, and protein functional modules using MCODE. Metascape was then used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein functional module with best score was obtained from the PPI network using CytoHubba, and 6 high-probability quercetin targets (AKT1, JUN, MAPK, TNF, VEGFA, and EGFR) were confirmed by docking simulations. KEGG pathway enrichment analysis suggested that the major shared mechanisms for T2DM and AD include “AGE-RAGE signaling pathway in diabetic complications,” “pathways in cancer,” and “MAPK signaling pathway” (the key pathway). We speculate that quercetin may have therapeutic applications in T2DM and AD by targeting MAPK signaling, providing a theoretical foundation for future clinical research.

BackgroundPrecancerous Lesions of Gastric Cancer (PLGC) is a common gastrointestinal tract and digestive systemdisease that lacks effective therapeutic drugs with good curative effects and few adverse reactions. Traditional Chinese medicine (TCM) has the advantages of multiple components, multiple channels, and fewer adverse reactions in the treatment of PLGC. Although Banxia xiexin Decoction (BXD) demonstrates a good therapeutic effect on PLGC, the pharmacological mechanism underlying its anticancer effect is still unclear. MethodsWe used a network pharmacology strategy, including the construction and analysis of a complex drug-disease network, to explore the complex mechanism of BXD treatment of PLGC. In addition, molecular docking technology was used to preliminarily study the binding ability of the potential active components and core therapeutic targets of BXD. ResultsThe networkpharmacology results showed 80 targets of BXD that are involved in PLGC. PPI network analysis demonstrated that the top10 core targets were JUN, TP53, MAPK3, MAPK1, TNF, VEGFA, MAPK14, ESR1, NR3C1, and MAPK8. The GO enrichment analysis results showed that the BXD anti-cancer and anti-inflammatory mechanism mainly involves cellular response to organic cyclic compound, response to toxic substance, response to oxidative stress, cellular response to nitrogen compound, response to inorganic substance, and others. The KEGG analysis results indicated that BXD may regulate 167 pathways such as MAPK signaling pathway and pathway in cancer in the treatment of PLGC. The molecular docking resultsshowed that the binding energies of beta sitosterol withMAPK1, MAPK3, MAPK14, JUN, and VEGFA were less than−7.0 kcal·mol−1, indicating a good docking effect. ConclusionsThis study reflects the characteristics of the mechanism of action by which BXD treats PLGC, which includes multiple components, multiple targets, and multiple pathways, and provides a biological basis for further verification and a novel perspective for drug discoveryin PLGC.