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基于色谱指纹图谱与化学计量学相结合的小儿豉翘清热颗粒质量控制优化方法

A Preferable Approach for the Quality Control of Xiaoer Chiqiao Qingre Granules Based on the Combination of Chromatographic Fingerprints and Chemometrics.

作者信息

Xu Tong, Li Xiaoqi, Huang Mengmeng, Wang Qi, Li Chao, Tian Gang, Chen Yan

机构信息

Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing 210028, China.

The State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.

出版信息

J Anal Methods Chem. 2020 Sep 29;2020:6836981. doi: 10.1155/2020/6836981. eCollection 2020.

DOI:10.1155/2020/6836981
PMID:33062374
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7542504/
Abstract

A preferable approach of a combination of a multiwavelength fusion HPLC fingerprint and chemometrics for the quality control of Xiaoer Chiqiao Qingre granules (XCQG) was established in this study. A single-wavelength HPLC fingerprint was performed to identify 18 peaks as common peaks in the beginning, and 12 of them were recognized by HPLC-Q/TOF-MS. To overcome the limitation of the single-wavelength HPLC fingerprint, a three-wavelength (230 nm, 250 nm, and 330 nm) fusion fingerprint was established for a more thorough quality assessment. Six main active ingredients (geniposide, paeoniflorin, forsythin, forsythoside A, baicalin, and wogonoside) were selected as chemical markers for simultaneous quantitative analysis, while the results indicated that the content of other five ingredients except forsythoside A presented comparatively stable. Chemometrics including hierarchical cluster analysis (HCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the homogeneity and heterogeneity of sixteen batches of XCQG. The results of the multiwavelength fingerprint were clearly classified into two clusters by HCA, whereas the single-wavelength fingerprint showed no distinct difference between them. OPLS-DA was further employed to prove that the above six main active ingredients made great contributions to clustering. In summary, this integrated analysis provided a better promoted and more comprehensive method to control the quality of XCQG.

摘要

本研究建立了一种多波长融合高效液相色谱指纹图谱与化学计量学相结合的小儿豉翘清热颗粒(XCQG)质量控制优选方法。首先采用单波长高效液相色谱指纹图谱鉴定出18个峰为共有峰,其中12个峰经高效液相色谱-四极杆/飞行时间质谱(HPLC-Q/TOF-MS)确认。为克服单波长高效液相色谱指纹图谱的局限性,建立了三波长(230 nm、250 nm和330 nm)融合指纹图谱以进行更全面的质量评价。选择6种主要活性成分(栀子苷、芍药苷、连翘苷、连翘酯苷A、黄芩苷和汉黄芩苷)作为化学对照品进行同步定量分析,结果表明除连翘酯苷A外的其他5种成分含量相对稳定。采用包括层次聚类分析(HCA)和正交偏最小二乘判别分析(OPLS-DA)在内的化学计量学方法评价16批次XCQG的均一性和异质性。多波长指纹图谱结果经HCA清晰地分为两类,而单波长指纹图谱显示它们之间无明显差异。进一步采用OPLS-DA证明上述六种主要活性成分对聚类有很大贡献。综上所述,这种综合分析为控制XCQG的质量提供了一种更好的、更全面的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/c1cdd09ca8cf/JAMC2020-6836981.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/a1e0bf92257c/JAMC2020-6836981.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/8ea5918db2e9/JAMC2020-6836981.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/c1cdd09ca8cf/JAMC2020-6836981.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/a1e0bf92257c/JAMC2020-6836981.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/8ea5918db2e9/JAMC2020-6836981.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dab6/7542504/c1cdd09ca8cf/JAMC2020-6836981.003.jpg

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