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A rapid, highly sensitive, and selective method was applied in a non-invasive way to investigate the antidepressant action of Xiaoyaosan (XYS) using ultra performance liquid chromatography-mass spectrometry (UPLC-MS) and chemometrics. Many significantly altered metabolites were used to explain the mechanism. Venlafaxine HCl and fluoxetine HCl were used as chemical positive control drugs with a relatively clear mechanism of action to evaluate the efficiency and to predict the mechanism of action of XYS. Urine obtained from rats subjected to chronic unpredictable mild stress (CUMS) was analyzed by UPLC-MS. Distinct changes in the pattern of metabolites in the rat urine after CUMS production and drug intervention were observed using partial least squares-discriminant analysis. The results of behavioral tests and multivariate analysis showed that CUMS was successfully reproduced, and a moderate-dose XYS produced significant therapeutic effects in the rodent model, equivalent to those of the positive control drugs, venlafaxine HCl and fluoxetine HCl. Metabolites with significant changes induced by CUMS were identified, and 17 biomarker candidates for stress and drug intervention were identified. The therapeutic effect of XYS on depression may involve regulation of the dysfunctions of energy metabolism, amino acid metabolism, and gut microflora changes. Metabonomic methods are valuable tools for measuring efficacy and mechanisms of action in the study of traditional Chinese medicines.

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Objectives: Cancer is well-known as a collection of diseases of uncontrolled proliferation of cells caused by mutated genes which are generated by external or internal factors. As the mechanisms of cancer have been constantly revealed, including cell cycle, proliferation, apoptosis and so on, a series of new emerging anti-cancer drugs acting on each stage have also been developed. It is worth noting that natural products are one of the important sources for the development of anti-cancer drugs. To the best of our knowledge, there is not any database summarizing the relationships between natural products, compounds, molecular mechanisms, and cancer types.Materials and methods: Based upon published literatures and other sources, we have constructed an anti-cancer natural product database (ACNPD) (http://www.acnpd-fu.com/). The database currently contains 521 compounds, which specifically refer to natural compounds derived from traditional Chinese medicine plants (derivatives are not considered herein). And, it includes 1,593 molecular mechanisms/signaling pathways, covering 10 common cancer types, such as breast cancer, lung cancer and cervical cancer.Results: Integrating existing data sources, we have obtained a large amount of information on natural anti-cancer products, including herbal sources, regulatory targets and signaling pathways. ACNPD is a valuable online resource that illustrates the complex pharmacological relationship between natural products and human cancers.Conclusion: In summary, ACNPD is crucial for better understanding of the relationships between traditional Chinese medicine (TCM) and cancer, which is not only conducive to expand the influence of TCM, but help to find more new anti-cancer drugs in the future.