Quantitative determination of nine furanocoumarins for quality evaluation of Angelica dahurica from different habitats / 中国中药杂志

A UPLC method has been developed for simultaneous determination of nine furanocoumarins of Angelica dahurics,and was used for quality evaluation of A. dahurica from different habitats. ACQUITY UPLC BEH C18 chromatographic column was employed,the separation was performed with the mobile phase consisting of acetonitrile and water,and the detection wavelength was set at254 nm. This method was used to simultaneously determine the content of xanthotoxol,oxypeucedaninhydrate,byak-angelicin,psoralen,xanthotoxin,bergapten,oxypeucedanin,imperatorin and isoimperatorin in A. dahurica from different habitats. Then,the further quality assessment of the drug was carried out by similarity evaluation,cluster analysis( CA),principal component analysis( PCA),and orthogonal partial least squares discriminant analysis( OPLS-DA). The content order of measured furanocoumarins from high to low was: oxypeucedanin>imperatorin>isoimperatorin>oxypeucedaninhydrate>bergapten>byak-angelicin>xanthotoxin>xanthotoxol>psoralen,with the mean content 2. 844,1. 277,0. 649 2,0. 216 2,0. 129 8,0. 062 68,0. 052 68,0. 019 30,0. 018 19 mg·g-1,respectively. There were difference between the batches of the drug,and the quality was influenced by smouldering sulphur based on the results of chemical pattern recognition and content determination. Finally,six active ingredients were recognized as the quality makers using OPLS-DA method. The validated UPLC fingerprint combined with chemical pattern recognition method can be used in the quality control and evaluation of A. dahurica.

Prediction of Cinnamomum cassia grade based on binary Logistic regression analysis / 中草药

Objective: In this study, a two-classification model based on the idea of “ingredient-efficacy” was established for the quality classification of Cinnamomum cassia with considerations to quality control components and biological activities. Methods: A method to determine quality control components was proposed by UPLC. The in vitro anti-oxidant activity of C. cassia was reflected by DPPH and hydroxyl radical scavenging experiment. The quality control index and anti-oxidant index were correlated by a Logistic algorithm. Finally, a binary logistic regression model for classification of C. cassia was established. Results: UPLC fingerprints of 20 samples of C. cassia were established, and their anti-oxidant activities were determined. Four quality control components (coumarin, cinnamyl alcohol, cinnamic acid, and cinnamaldehyde) were screened out by principal component analysis, and their methodological validation was carried out. According to the regression equation, 20 batches of C. cassia were divided into four grades: excellent, good, medium, and poor. Conclusion: The binary logistic regression model can describe the mapping relationship between the grade of C. cassia. It can better express the classification standard for the prepared C. cassia. This study provides a new idea for quality evaluation of C. cassia.