Evaluation of myocardial ischemia rat model based on metabonomic method of small molecule metabolites of plasma and cardiac muscle / 药学学报

Isoproterenol (ISO)-induced myocardial ischemia animal model has been widely applied to the study of myocardial ischemia and evaluation of drug efficacy. Metabolic profiling of endogenous compounds can make a deep insight into biochemical process of the ISO-induced myocardial ischemia rats. Herein, rats were treated with ISO (2 mg x kg(-1)) for 10 days. After the model was established by measuring myocardial histopathology and plasma creatine kinase, GC/TOF-MS was used to determine endogenous metabolites in plasma and cardiac muscle of rats, and pattern recognition was used to process the data. Results showed that the plasma metabolic profiling of ISO-induced myocardial ischemia rats was significantly different from that of the control, and it had the tendency to the normal state after the discontinue of ISO injection. Besides, the cardiac muscle of rats treated with ISO for 10 days and the normal cardiac muscle could also be separated clearly. The potential biomarkers in plasma and cardiac muscle of model rats had homogeneity and their own specialty. Biochemical metabolic pathway analysis indicated that this myocardial ischemia model was involved in the alternation of energy metabolism, saccharometabolism, lipid metabolism, nucleoside metabolism and amino acid metabolism, and in relationship with oxidative stress. These findings revealed that metabonomics may be a promising tool to evaluate myocardial ischemia rat model induced by ISO and could further extend the study of pharmacodynamic action of drugs at the molecular level.

Study on LC-MS fingerprint for quality assessment of Aristolochia manshuriensis with chemical pattern recognition / 中国中药杂志

<p><b>OBJECTIVE</b>To analyze LC-MS fingerprints of Aristolochia manshuriensis for quality assessment with two different chemical pattern recognition models.</p><p><b>METHOD</b>LC-MS fingerprints of A. manshuriensis were established from 24 batches of samples from different habitats. SIMCA and Clustering analysis were used to compare the parameters of the 29 common peaks.</p><p><b>RESULT</b>Two methods had good consistency, while they reflected the inherent sample information from different perspectives, respectively.</p><p><b>CONCLUSION</b>Modern equipment analysis technology and multivariable chemical pattern recognition would be an efficient way for quality control and variety identification of A. manshuriensis.</p>