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    High-performance liquid chromatography–based fingerprint analysis with chemical pattern recognition for evaluation of Mahonia bealei (Fort.) Carr

    发布时间:2021-03-12 文章来源: 深圳市药品检验研究院
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      Yang Huang1,2,3 Tiejie Wang1,4 Guo Yin1,4 Jue Wang1,4 Kun Jiang1,4 Jiasheng Tu2


      1 Shenzhen Institute for Drug Control, Shenzhen, P. R. China


      2 State Key Laboratory of Natural Medicines, Department of Pharmaceutics, China Pharmaceutical University, Nanjing, P. R. China


      3 Key Laboratory of Molecular Target & Clinical Pharmacology and the State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences & the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, P. R. China


      4 Shenzhen Key Laboratory of Drug Quality Standard Research, Shenzhen, P. R. China




      ABSTRACT

      

      

      A simple and efficient high-performance liquid chromatography method combined with chemical pattern recognition was established for quality evaluation of Mahonia bealei (Fort.) Carr. A common pattern of 30 characteristic peaks was applied for similarity analysis, hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis in the 37 batches of M. bealei (Fort.) Carr. to discriminate wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes. The results showed that partial least squares discriminant analysis was the most effective method for discrimination. Eight characteristics peaks with higher variable importance in projection values were selected for pattern recognition model. A permutation test and 26 batches of testing set samples were performed to validate the model that was successfully established. All of the training and testing set samples were correctly classified into three clusters (wild M. bealei (Fort.) Carr., cultivated M. bealei (Fort.) Carr., and its substitutes) based on the selected chemical markers. Moreover, 26 batches of unknown samples were used to predict the accuracy of the established model with a discrimination accuracy of 100%. The obtained results indicated that the method showed great potential application for accurate evaluation and prediction of the quality of M. bealei (Fort.) Carr.




      KEYWORDS

      

      

      chemical pattern recognition, high-performance liquid chromatography fingerprint, quality evaluation, traditional Chinese medicine

      该论文发表于《JOURNAL OF SEPARATION SCIENCE》


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