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基于电感耦合等离子体质谱法的多元指纹图谱对三种麻黄属植物及其地理来源的鉴别。

Discrimination of three Ephedra species and their geographical origins based on multi-element fingerprinting by inductively coupled plasma mass spectrometry.

机构信息

Ningxia Medical University Pharmacy College, Yinchuan, 750004, Ningxia, China.

Ningxia Research Center of Modern Hui Medicine Engineering and Technology, Yinchuan, 750004, Ningxia, China.

出版信息

Sci Rep. 2018 Jul 6;8(1):10271. doi: 10.1038/s41598-018-28558-9.

DOI:10.1038/s41598-018-28558-9
PMID:29980710
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6035214/
Abstract

Discrimination of species and geographical origins of traditional Chinese medicine (TCM) is essential to prevent adulteration and inferior problems. We studied Ephedra sinica Stapf, Ephedra intermedia Schrenk et C.A.Mey. and Ephedra przewalskii Bge. to investigate the relationship between inorganic element content and these three species and their geographical origins. 38 elemental fingerprints from six major Ephedra-producing regions, namely, Inner Mongolia, Ningxia, Gansu, Shanxi, Shaanxi, and Sinkiang, were determined to evaluate the importance of inorganic elements to three species and their geographical origins. The contents of 15 elements, namely, N, P, K, S, Ca, Mg, Fe, Mn, Na, Cl, Sr, Cu, Zn, B, and Mo, of Ephedra samples were measured using inductively coupled plasma mass spectroscopy. Elemental contents were used as chemical indicators to classify species and origins of Ephedra samples using a radar plot and multivariate data analysis, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and discriminant analysis (DA). Ephedra samples from different species and geographical origins could be differentiated. This study showed that inorganic elemental fingerprint combined with multivariate statistical analysis is a promising tool for distinguishing three Ephedra species and their geographical origins, and this strategy might be an effective method for authenticity discrimination of TCM.

摘要

鉴别中药(TCM)的品种和产地对于防止掺假和劣质问题至关重要。本研究以麻黄属的麻黄、中麻黄和木贼麻黄为对象,调查了无机元素含量与这三个种及其产地的关系。从内蒙古、宁夏、甘肃、山西、陕西和新疆六个主要麻黄产地,共确定了 38 个元素指纹图谱,以评估无机元素对这三个种及其产地的重要性。采用电感耦合等离子体质谱法测定了麻黄样品中 15 种元素(N、P、K、S、Ca、Mg、Fe、Mn、Na、Cl、Sr、Cu、Zn、B 和 Mo)的含量。利用雷达图和多元数据分析,包括层次聚类分析(HCA)、主成分分析(PCA)和判别分析(DA),将元素含量用作化学指标来对麻黄样品的种和产地进行分类。不同种和不同产地的麻黄样品可以区分开来。本研究表明,无机元素指纹图谱结合多元统计分析是鉴别三种麻黄属植物及其产地的一种很有前途的工具,这种策略可能是鉴别中药真实性的有效方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/d7238d729738/41598_2018_28558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/578c0eb29c78/41598_2018_28558_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/da5962cca1f7/41598_2018_28558_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/588216d795f1/41598_2018_28558_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/45903044cf85/41598_2018_28558_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/d7238d729738/41598_2018_28558_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/578c0eb29c78/41598_2018_28558_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/da5962cca1f7/41598_2018_28558_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/588216d795f1/41598_2018_28558_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/45903044cf85/41598_2018_28558_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee98/6035214/d7238d729738/41598_2018_28558_Fig5_HTML.jpg

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