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基于酚类成分、生物活性以及结合化学计量学的高效液相色谱指纹图谱对Sieb. et Zucc.的质量评价

Quality Evaluation of Sieb. et Zucc. Based on Phenolic Profiles, Bioactivity, and HPLC Fingerprint Combined with Chemometrics.

作者信息

Liu Zehua, Wang Dongmei, Li Dengwu, Zhang Shuai

机构信息

Department of Forestry Engineering, College of Forestry, Northwest A&F UniversityYangling, China.

出版信息

Front Pharmacol. 2017 Apr 19;8:198. doi: 10.3389/fphar.2017.00198. eCollection 2017.

Abstract

() which is endemic to East Asia, has traditionally been used as an ethnomedicinal plant in China. This study was undertaken to evaluate the quality of samples derived from 11 primary regions in China. Ten phenolic compounds were simultaneously quantified using reversed-phase high-performance liquid chromatography (RP-HPLC), and chlorogenic acid, catechin, podophyllotoxin, and amentoflavone were found to be the main compounds in needles, with the highest contents detected for catechin and podophyllotoxin. from Jilin (S9, S10) and Liaoning (S11) exhibited the highest contents of phenolic profiles (total phenolics, total flavonoids and 10 phenolic compounds) and the strongest antioxidant and antibacterial activities, followed by Shaanxi (S2, S3). A similarity analysis (SA) demonstrated substantial similarities in fingerprint chromatograms, from which 14 common peaks were selected. The similarity values varied from 0.85 to 0.98. Chemometrics techniques, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA), were further applied to facilitate accurate classification and quantification of the samples derived from the 11 regions. The results supported HPLC data showing that all samples exhibit considerable variations in phenolic profiles, and the samples were further clustered into three major groups coincident with their geographical regions of origin. In addition, two discriminant functions with a 100% discrimination ratio were constructed to further distinguish and classify samples with unknown membership on the basis of eigenvalues to allow optimal discrimination among the groups. Our comprehensive findings on matching phenolic profiles and bioactivities along with data from fingerprint chromatograms with chemometrics provide an effective tool for screening and quality evaluation of and related medicinal preparations.

摘要

()原产于东亚,在中国传统上被用作民族药用植物。本研究旨在评估来自中国11个主要地区的样本质量。使用反相高效液相色谱法(RP-HPLC)同时对10种酚类化合物进行定量分析,发现绿原酸、儿茶素、鬼臼毒素和穗花杉双黄酮是该植物针叶中的主要化合物,其中儿茶素和鬼臼毒素含量最高。来自吉林(S9、S10)和辽宁(S11)的样本表现出最高的酚类成分含量(总酚、总黄酮和10种酚类化合物)以及最强的抗氧化和抗菌活性,其次是陕西(S2、S3)。相似性分析(SA)表明指纹图谱存在显著相似性,从中选取了14个共有峰。相似性值在0.85至0.98之间。进一步应用化学计量学技术,包括层次聚类分析(HCA)、主成分分析(PCA)和判别分析(DA),以促进对来自11个地区的该植物样本进行准确分类和定量。结果支持了HPLC数据,表明所有样本在酚类成分上表现出相当大的差异,并且样本进一步聚类为与它们的地理起源区域一致的三个主要组。此外,构建了两个判别率为100%的判别函数,以根据特征值进一步区分和分类未知归属的样本,从而实现组间最佳判别。我们关于匹配酚类成分和生物活性以及指纹图谱数据与化学计量学的综合研究结果为该植物及其相关药用制剂的筛选和质量评估提供了一种有效工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/866b/5395569/da062de9bb70/fphar-08-00198-g0001.jpg

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