Hongjie Liu

Objective: To evaluate the efficacy and safety of Chinese herbal medicines (CHMs) combined with chemical drugs for the treatment of Alzheimer's disease (AD). Materials and Methods: Databases were searched to retrieve randomized controlled trials (RCTs) of CHMs combined with tacrine, galantamine, rivastigmine, donepezil, or memantine, following strict inclusion and exclusion criteria. Only research papers published in English, Chinese, and Japanese were considered. The primary outcome was the mini-mental state examination (MMSE) score and the secondary outcomes were AD assessment scale cognitive subscale (ADAS-Cog) score and safety evaluation. Meta-analysis was carried out using RevMan 5.3 and subgroup analysis was conducted to identify the sources of heterogeneity. Results: A total of 15 RCTs with 1386 participants were included in this study. Only donepezil was used in the retrieved literature. Meta-analyses showed that the combination of CHMs with donepezil led to significant improvement in the MMSE score (Z = 9.45; P < 0.00001; weighted mean difference [WMD] =2.68, 95% confidence interval [CI]: 2.12–3.24) and a significant decrease in the ADAS-Cog score (Z = 5.53; P < 0.00001; WMD = −3.79; 95% CI: −5.13–−2.44). Safety evaluation demonstrated that these combination treatments relieved adverse events such as insomnia (risk ratio [RR] =0.20, 95% CI: 0.06–0.68; P = 0.01) and hive (RR = 0.10; 95% CI: 0.01–0.73; P = 0.02). Conclusions: The combination of CHMs with a chemical drug like donepezil led to significant improvements in patient cognition as well as a better safety profile when compared to the application of a chemical drug alone.

Objective: To investigate the potential mechanism of Guishao Pingchan Recipe (GPR) against Parkinson's disease (PD) based on network pharmacology and molecular docking. Methods: The main components of GPR were collected based on TCMSP database, Batman-TCM database, Chinese Pharmacopoeia, and Literatures. The potential therapeutic targets of PD were predicted by Drug Bank Database and Gene Cards database. Cytoscape 3.8.2 software was used to construct herb–component–target network. Then, String database was used to construct a PPI network, and DAVID database was used for gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation of targets function. Core components of GPR and hub targets were imported into AutoDock Vina for molecular docking verification and results were visualized by Pymol. Results: 13 candidate components were selected and 288 corresponding targets of GPR for treating PD were obtained. The GO enrichment analysis mainly involved 135 cell components, 187 molecular functions, and 1753 biological processes. Moreover, KEGG pathway enrichment analysis mainly involved 200 signaling pathways. Molecular docking simulation indicated a good binding ability of components and targets. Conclusion: Based on network pharmacology and molecular docking, we found that sitosterol, 4-Cholesten-3-one and stigmasterol in GPR could combine with MAPK3, APP, VEGFA, and CXCR4 and involved in the cAMP, PI3K/Akt, Rap1 signaling pathways. It is suggested that GPR may have therapeutic effects on PD through multi-component, multi-target, and multi-pathway and predict the relevant mechanism of the anti-PD effect of GPR.

Background. Poststroke depression (PSD) is a serious complication of clinical cerebrovascular disease. Patients not only have depression-related emotional symptoms but also have physical symptoms, such as autonomic dysfunction. At the same time, patients with varying degrees of depression will delay the neurological function of stroke patients. The recovery time of cognitive function and limb function will increase the risk of accidental death and even aggravate the mortality of cerebrovascular disease. Through combining data analysis and related literature, seven types of Chinese patent medicines (CPMs) widely used in the clinical treatment of PSD have been screened out. These herbs exhibit some clinical comparability under the conditions that the syndrome type and dosage form are relatively uniform. Therefore, in this study, the network meta-analysis method was used to evaluate the safety and efficacy of the seven CPMs screened out, and the probability ranking was performed to screen the best clinical auxiliary treatment plan of CPM. Methods. We searched the Chinese databases, including CNKI, WANFANG, and VIP, as well as the English databases, including the Cochrane Library, EMBASE, and PubMed, from inception to May 31, 2020, to identify randomized controlled trials (RCTs) on seven kinds of CPMs that were the subjects of the clinical research. The bias risk and quality of the included studies were analyzed with the Cochrane Handbook (version 5.1), ADDIS, and R software, and the results were compared in a network meta-analysis (NMA). Results. In terms of clinical effectiveness, the seven kinds of CPMs all improved clinical curative effects, with Jieyu Anshen capsule adjuvant treatment having the most significant effect [odds ratio (OR)=5.00, 95 CI (1.729.48)]. Wuling capsule AT can effectively reduce the score index of scale factors for the HAMD score, NIHSS score, and TESS score [mean difference (MD)=3.95, 95 CI (4.883.00); OR=3.25, 95 CI (5.46)1.05); OR=0.22, 95 CI (0.050.79), resp.]. Conclusion. The mechanisms of seven CPMs in the adjuvant treatment of PSD have advantages. In terms of safety and efficacy, the CPMs had better clinical adjuvant treatment performance. Although this study concluded that the Jieyu Anshen capsule is the preferred drug for clinical treatment, a clear conclusion still needs to be verified in a high-quality randomized controlled study. In clinical practice, accurate selection and application can be carried out according to the specific characteristics of patients.

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.