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Background: Traditional Chinese medicine (TCM) has been used to treat various diseases for thousands of years. However, the uncertainty of dosage as well as the lack of systemic evaluation of pharmacology and toxicology is one major reason why TCM remains mysterious and is not accepted worldwide. Hence, we aimed to propose an integrated dose–response metabolomics strategy based on both therapeutic effects and adverse reactions to guide the TCM dosage in treatment. Methods: The proposed methodology of integrated dose–response metabolomics includes four steps: dose design, multiple comparison of metabolic features, response calculation and dose–response curve fitting. By comparing the changes of all metabolites under different doses and calculating these changes through superposition, it is possible to characterize the global disturbance and thus describe the overall effect and toxicity of TCM induced by different doses. Rhubarb, commonly used for constipation treatment, was selected as a representative TCM. Results: This developed strategy was successfully applied to rhubarb. The dose–response curves clearly showed the efficacy and adverse reactions of rhubarb at different doses. The rhubarb dose of 0.69 g/kg (corresponding to 7.66 g in clinic) was selected as the optimal dose because it was 90% of the effective dose and three adverse reactions were acceptable in this case. Conclusion: An integrated dose–response metabolomics strategy reflecting both therapeutic effects and adverse reactions was established for the first time, which we believe is helpful to uncover the mysterious veil of TCM dosage. In addition, this strategy benefits the modernization and internationalization of TCM, and broadens the application of metabolomics. [ABSTRACT FROM AUTHOR]

Background: Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding effect of individual components in rhubarb. Hence, we aimed to develop a novel strategy to fuzzily identify bioactive components for different efficacies of rhubarb by the back propagation (BP) neural network association analysis of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for every data (UPLC-Q-TOF/MSE) and integrated effects. Methods: Through applying the fuzzy chemical identification, most components of rhubarb were classified into different chemical groups. Meanwhile the integration effect values of different efficacies can be determined by animal experiment evaluation and multi-attribute comprehensive indexes. Then the BP neural network was employed for association analysis of components and different efficacies by correlating the component contents determined from UPLC-Q-TOF/MSE profiling and the integration effect values. Finally, the effect contribution of one type of components may be totaled to demonstrate the universal and individual characters for different efficacies of rhubarb. Results: It suggested that combined anthraquinones, flavanols and their polymers may be the universal character to the multi-functional properties of rhubarb. Other components contributed to the individuality of rhubarb efficacies, including stilbene glycosides, anthranones and their dimers, free anthraquinones, chromones, gallic acid and gallotannins, butyrylbenzenes and their glycosides. Conclusions: Our findings demonstrated that the bioactive components for different efficacies of rhubarb were not exactly the same and can be systematically differentiated by the network-oriented strategy. These efforts will advance our knowledge and understanding of the bioactive components in rhubarb and provide scientific evidence to support the expansion of its use in clinical applications and the further development of some products based on this medicinal herb. [ABSTRACT FROM AUTHOR]