Chinese herbal medicines for the treatment of depression: a systematic review and network meta-analysis.

Objectives: Amidst rising global burden of depression and the associated challenges with conventional antidepressant therapies, there is a growing interest in exploring the efficacy and safety of alternative treatments. This study uses a Bayesian network meta-analysis to rigorously evaluate the therapeutic potential of Chinese herbal medicines in the treatment of depression, focusing on their comparative efficacy and safety against standard pharmacological interventions. Methods: Five databases (PubMed, Wanfang Data, EMBASE, CNKI, and the Cochrane Library) and grey literature were searched from inception to end of July 2023 to identify studies that assessed the efficacy and safety of Chinese herbal medicines in treating depression. The response rate, Hamilton Depression Scale (HAMD) scores, and rates of adverse events were assessed through both direct and indirect comparisons. Data extraction and risk of bias assessment were meticulously performed. Statistical analysis used Markov chain Monte Carlo methods, with effect size estimates provided as odd ratios and their 95% confidence intervals. Results: A total of 198 RCTs involving 8,923 patients were analyzed, assessing 17 Chinese herbal medicines. Surface Under the Cumulative Ranking results indicated that the top three treatments with the best response rate were possibly Guipiwan, Ease Pill, and Chaihu Jia Longgu Muli Decoction; the top three treatments on the reduction of HAMD scores were Chai Hu Shu Gan San, Xingnao Jieyu Decoction, and Xiaoyao Powder; and the top three treatments with the lowest adverse effects rates were Xiaoyao Powder, Alprazolam, and Xingnao Jieyu Decoction. Interestingly, commonly used synthetic drugs such as Fluoxetine, Escitalopram, Amitriptyline, Sertraline, Flupentixol and Melitracen, and Venlafaxine, not only appeared to be less effective than specific Chinese herbal medicines (Gan Mai Da Zao Decoction, Chaihu Jia Longgu Muli Decoction, Chai Hu Shu Gan San, Danzhi-Xiaoyao-San, and Xingnao Jieyu Decoction), but they were also related to substantially higher risk of adverse events. Conclusion: Our findings elucidate the promising therapeutic potential of Chinese herbal medicines as viable alternatives in the treatment of depression, with certain herbs demonstrating enhanced efficacy and safety profiles. The outcomes of this study advocate for the integration of these alternative modalities into contemporary depression management paradigms. However, it underscores the necessity for larger, methodologically robust trials to further validate and refine these preliminary findings. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023452109.

Network pharmacological analysis and molecular docking of Huangqin-Baizhu herb pair in the treatment of threatened abortion.

BACKGROUND: The incidence of threatened abortion (TA) is increasing due to poor diet and living habits, which brings great pressure to pregnant women and their families. Huangqin-Baizhu herb pair recorded in ancient books of traditional Chinese medicine has been widely used in the treatment of TA with remarkable effect. In this study, we will use the network pharmacology method to predict the target and mechanism of Huangqin-Baizhu herb pair. METHODS: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to screen the active components of Huangqin-Baizhu herb pair. Pubchem and Swiss Target Prediction databases were used to predict the action targets. Genecards, OMIM, and Drugbank databases were used to predict the related targets of TA. The intersection of drug target and disease target was selected and the intersection genes were uploaded to STRING database to construct protein-protein interaction network and conduct module analysis. Metascape database was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, which was imported into Cytoscape software to construct component-pathway-gene network and finally verified by molecular docking. Ethical approval and informed consent of patients are not required because the data used in this study is publicly available and does not involve individual patient data or privacy. RESULTS: The main active components of the herb pair are baicalein, flavanone, and norwogonin, etc. The main targets are AKT1, VEGFA, STAT3, MAPK1, SRC, etc. Cluster module analysis shows that the targets are related to cell metabolism, immune regulation and hormone level regulation. There were 2073, 3169, and 161 KEGG pathways involved in the biological processes, cell components, and molecular functions of Gene Ontology analysis, respectively. The main KEGG pathways involved in the intervention were HIF1 signaling pathway, PI3K-Akt signaling pathway, and Rap1 signaling pathway. Molecular docking showed that the main active components of the herb pair were well combined with the key targets. CONCLUSIONS: In this study, 42 active components, 152 potential targets and 11 key targets of Huangqin-Baizhu herb pair for the treatment of TA were revealed, participating in multiple signaling pathways such as PI3K-Akt, providing a theoretical basis for further experimental research.

Exploring the relationship between osteoporosis and polycystic ovary syndrome based on bioinformatics.

BACKGROUND: In recent years, clinical studies have found that there is a close relationship between osteoporosis and polycystic ovary syndrome. However, there are few literature on the pathogenesis of osteoporosis and polycystic ovary syndrome. In order to clarify their common pathogenic mechanism and provide potential targets for drugs to regulate them at the same time, bioinformatics methods are used to explore, so as to provide a new direction for the study of the relationship between diseases in the future. METHODS: To screen the targets of osteoporosis and polycystic ovary syndrome by Genecards, Online Mendelian Inheritance in Man databases and Therapeutic Target Database to take the intersection of the two mappings and upload the intersection targets to the STRING database to construct protein-protein interaction network; to screen the core targets by degree value and import them to Metascape database for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis; and finally, to construct the visualization network of core targets and pathways by Cytoscape software. Ethical approval and informed consent of patients are not required because the data used in this study is publicly available and does not involve individual patient data or privacy. RESULTS: The core targets of polycystic ovary syndrome and osteoporosis were insulin gene, insulin-like growth factor 1, CTNNB1, serine/threonine kinase 1, signal transducer and activator of transcription 3, LEP, etc. The biological processes involved include the regulation of protein phosphorylation, cell proliferation and differentiation, hormone endocrine, reproductive system and skeletal system. The related pathways were concentrated in Foxo signaling pathway, HTLV-I infection, PI3K-AKT signaling pathway, MAPK signaling pathway and AGE-RAGE signaling pathway in diabetic complications. CONCLUSIONS: There is a close relationship between osteoporosis and polycystic ovary syndrome in terms of target and molecular mechanism. This study used bioinformatics to clarify their targets and mechanisms, providing potential targets for drugs to regulate both diseases simultaneously and providing new directions to explore the relationship between the diseases.