化学
偏最小二乘回归
线性判别分析
一致性(知识库)
主成分分析
人参皂甙
色谱法
人参皂苷Rg1
高效液相色谱法
人工智能
统计
数学
计算机科学
人参
病理
替代医学
医学
作者
Yanfang Zheng,Chun‐Lin Fan,Menghua Liu,Ye Chen,Zibin Lu,Nishan Xu,Haijing Huang,Huhu Zeng,Shanhong Liu,Hongxin Cao,Junshan Liu,Linzhong Yu
标识
DOI:10.1016/j.jpba.2020.113411
摘要
ShengMai Formula (SMF), a famous traditional Chinese medicine (TCM) formula, has been extensively used for treating the diseases caused by Qi-Yin deficiency for almost 1000 years. However, few studies are elucidated about its batch-to-batch quality control system and the quality control markers remain largely unrevealed, which have hindered the development and utilization of SMF. In this study, we aimed to screen the optimal quality control markers to evaluate the overall quality consistency of SMF. High-performance liquid chromatography (HPLC) fingerprint coupled with similarity analysis (SA), principal components analysis (PCA) and hierarchical cluster analysis (HCA) was firstly established to hunt for the discriminant components that resulting in the chemical inconsistence among different batches of SMF. Subsequently, different batches of samples were selected to explore their immunomodulatory activities by neutral red method, Cell Counting Kit-8 (CCK-8) assay and enzyme-linked immunosorbent assay (ELISA). Finally, the fingerprint-efficacy relationships were further illuminated to discover the major bioactive compositions using grey relational analysis (GRA), partial least squares regression (PLSR) analysis and artificial neural network (ANN) analysis. As a result, schisandrol A, schisandrol B, methylophiopogonanone A, schisandrin B, ginsenoside Rf, ginsenoside Rb1, ginsenoside Rg2 and ginsenoside Rb2 were selected as the quality control markers and thus their simultaneous quantification was performed to both evaluate the batch-to-batch chemical and bioactive consistency among different batches of SMF. Our investigation not only stresses the necessity of consistency in efficacy besides chemical consistency, but also provides a comprehensive and powerful quality assessment approach, which is promising to monitor the overall quality consistency of SMF.
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