Preclinical evidence evaluation of Xiaoyao san in treating chronic unpredictable mild stress model of depression based on meta-analysis

In view of the current challenges in the treatment of depression, in order to improve the efficacy and avoid adverse reactions, people pay attention to the treatment of traditional Chinese medicine. Xiaoyao san is a classic prescription commonly used in the treatment of depression, with the role of harmonizing liver and spleen, and shows great potential in the treatment of depression.The purpose of this study is to comprehensively evaluate the efficacy and specific mechanism of Xiaoyao san in the treatment of chronic unpredictable mild stress (CUMS) model of depression through systematic evaluation and meta-analysis, so as to provide strong preclinical evidence for the clinical treatment of Xiaoyao san and provide a new strategy for the development of antidepressants.The preclinical literature published before March 2023 was searched in Cochrane Library, PubMed, Web of Science, EMbase, CNKI, VMIS, Wan-Fang, and CBM and other database systems. Stata15 was used for overall effect analysis and subgroup analysis, and summarized the potential mechanism of action.A total of 25 studies were included, involving 569 animals. The average score of methodological quality was 7.48/10. Meta-analysis shows that Xiaoyao san can effectively improve food intake and body weight, restore sucrose consumption, reduce the immobility time in forced swimming, and increase the total exercise distance, grid crossing and upright times in the open field experiment. Its therapeutic effect is closely related to improving the abnormal activation of Hypothalamic-pituitary-adrenal axis and inhibiting the expression of glutamate.To sum up, in CUMS animal model, Xiaoyao san can significantly improve the symptoms of depression, restore the lost pleasure behavior and curiosity about the new environment, relieve tension and anxiety, and improve the occurrence of depression in many ways, which may be a new treatment strategy for CUMS model of depression.