文献类型：期刊文献

中文题名：不同产地高乌头药材HPLC指纹图谱及2种生物碱成分含量测定

英文题名：HPLC Fingerprints Analysis of Aconitum sinomontanum from Different Areas and Content Determination of Two Alkaloids

作者：张立军[1];戴海蓉[1];樊秦[1];夏鹏飞[1];姚娟[1];李芸[1]

第一作者：张立军

机构：[1]甘肃中医药大学药学院甘肃省高校中(藏)药化学与质量研究省级重点实验室

第一机构：甘肃中医药大学药学院（西北中藏药协同创新中心办公室）|甘肃中医药大学科研实验中心（甘肃省中医药标准化技术委员会秘书处）

年份：2017

卷号：23

期号：17

起止页码：41

中文期刊名：中国实验方剂学杂志

外文期刊名：Chinese Journal of Experimental Traditional Medical Formulae

收录：CSTPCD;;北大核心:【北大核心2014】；CSCD:【CSCD_E2017_2018】；

基金：国家自然科学基金项目(81560650);甘肃省自然基金项目(1107RJZA242)

语种：中文

中文关键词：高乌头;指纹图谱;主成分分析;聚类分析;不同产区;高乌甲素;冉乌头碱

外文关键词：Aconitum sinomontanum; fingerprint; principal component analysis; cluster analysis;different areas; lappacontine; ranaconitine

摘要：目的:建立不同产地高乌头药材的HPLC指纹图谱,并测定其中2种主要生物碱成分含量,为高乌头药材质量控制提供参考依据。方法:采用HPLC-DAD技术,以Dikma spursil C18色谱柱(4.6 mm×250 mm,5μm),乙腈-0.05 mol·L^(-1)磷酸二氢钠水溶液为流动相梯度洗脱,建立高乌头药材的指纹图谱并进行含量测定;采用中药指纹图谱相似度评价系统(2012版)对10批样品进行共有峰确认及相似度评价;通过SPSS 21.0统计软件采用主成分分析(PCA)和聚类分析(CA)对HPLC指纹图谱进行模式识别分析。结果:建立了高乌头药材指纹图谱,10批高乌头药材的相似度均>0.90;标定共有峰11个,并对其中2主要成分(高乌甲素、冉乌头碱)进行含量测定;聚类分析法(CA)将所有批次高乌头药材共分为4类,反映了10个批次不同地区高乌头药材的质量特征;主成分分析法(PCA)筛选出累计贡献率达到89.748%的4个主成分,得到决定高乌头药材质量5个化学成分。结论:建立的HPLC指纹图谱结合含量测定,PCA,CA方法,可以客观、有效、全面地用于高乌头药材的质量评价。
Objective： To establish the high performance liquid chromatography （HPLC） fingerprints of Aconitum sinomontanum from different areas, determine the contents of two alkaloids, and provide basis for quality control of A. sinomontanum. Method： HPLC-DAD method was developed to establish fingerprints for A. sinomontanum, and the contents were determined by Dikma spursil C18 （4.6 mm × 250 mm, 5 μm）, with acetonitrile-0.05 mol·L^-1 sodium phosphate dibasic solution as the mobile phase for gradient elution. Similarity evaluation system for chromatographic fingerprint of traditional Chinese medicine （2012 edition） was used to confirm the common peaks in 10 batches of samples and evaluate the similarity. SPSS 21.0 statistical software was used to make principal component analysis （PCA） and cluster analysis （CA） for the HPLC fingerprint. Result：The common mode for A. sinomontanum fingerprint was established; the similarity was greater than 0.90 in 10 batches of A. sinomontanum medicinal herbs; 11 common fingerprint peaks were identified, and the content of lappacontine and ranaconitinewas determined. All batches of samples can be classified into four groups by using CA, reflecting the quality characteristics of 10 batches of A. sinomontanum in different areas. Four principal components with a cumulative contribution rate of 89. 748% were screened by using principle component analysis to obtain five chemical compositions that could determine the quality of A. sinomontanum.. Conclusion： The HPLC fingerprint, PCA and CA methods can objectively, effectively and comprehensively evaluate the quality of A. sinomontanum.