Qian Zhang, Yiyang Chen, Lixia Ma, Yue Jiang, Jun Chen, Jie Dong, Yifan Ma, Jingjing Zhang, Guojun Yan
School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH, USA.
Dose Response. 2020 Sep 22;18(3):1559325820951730. doi: 10.1177/1559325820951730. eCollection 2020 Jul-Sep.
To establish a HPLC fingerprints evaluation method for Radix (ASR) based on traditional decoction process of Ancient Classical Prescriptions of Traditional Chinese Medicine (ACPTCM).
The fingerprints of 10 batches of ASR were further evaluated by chemometrics methods. The similarity analyzed with "Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine 2004A," and hierarchical clustering analysis (HCA) and principal component analysis (PCA) were performed by SPSS (version 22.0, SPSS Inc., Chicago, IL, USA).
There were 12 common peaks, and the similarity degrees of 10 batches of samples were more than 0.923 and showed that all the samples from different origins were of good consistency. The samples were divided into 4 clusters by HCA. The results of PCA showed that the 3 factors were chosen, the quality of samples could be evaluated basically. The comprehensive score results show that the ASR with Lot.Nos.DG-18007, DG-18008 in Weiyuan County, Gansu and DG-18009 produced in Minle County, Gansu Province rank among the top 3 in all samples.
These results demonstrated that the combination of HPLC chromatographic fingerprint and chemometrics offers an efficient and reliable approach for quality evaluation of ASR from different sources as Ancient Classical Prescriptions ingredients.
基于《中医古籍经典名方》传统汤剂制备工艺,建立当归的高效液相色谱指纹图谱评价方法。
采用化学计量学方法对10批当归的指纹图谱进行进一步评价。使用“中药色谱指纹图谱相似度评价系统2004A”进行相似度分析,采用SPSS(版本22.0,美国伊利诺伊州芝加哥SPSS公司)进行层次聚类分析(HCA)和主成分分析(PCA)。
共确定12个共有峰,10批样品的相似度均大于0.923,表明不同产地的样品一致性良好。通过HCA将样品分为4类。PCA结果显示,选取3个因子即可基本评价样品质量。综合评分结果表明,甘肃省渭源县的DG - 18007、DG - 18008批次以及甘肃省民乐县的DG - 18009批次当归在所有样品中排名前三。
这些结果表明,高效液相色谱指纹图谱与化学计量学相结合,为评价不同来源作为古籍经典名方药材的当归质量提供了一种有效且可靠的方法。