文献类型：期刊文献

中文题名：中药复杂样品高效液相色谱和超高效液相色谱分析条件转换方法

英文题名：HPLC and UPLC Switch for TCM Analysis

作者：金郁[1];薛兴亚[1];肖远胜[1];章飞芳[1];石慧[2];梁鑫淼[1]

机构：[1]中国科学院大连化学物理研究所,大连116023;[2]华东理工大学药学院,上海200237

年份：2008

卷号：10

期号：1

起止页码：80

中文期刊名：世界科学技术-中医药现代化

外文期刊名：Modernization of Traditional Chinese Medicine and Materia Medica-World Science and Technology

收录：CSTPCD

语种：中文

中文关键词：高效液相色谱法;超高效液相色谱法;保留参数;方法转换;中药

外文关键词：high performanced liquid chromatography （HPLC）;ultra performance liquid chromatography （UPLC）;retention parameters;method migration;tradition Chinese medicine

摘要：目的:建立中药复杂样品高效液相色谱(HPLC)和超高效液相色谱(UPLC)分析条件相互转化的方法。方法:采用丹参水提组分为模型样本,利用五次线性梯度分别求算该样品中12个色谱峰在HPLC和UPLC中的保留参数(a,c值),然后对a,c值进行分别关联,获取线性方程,利用该线性方程可以实现a,c值的相互转换,由计算的a,c值进行色谱条件的预测与优化。结果:HPLC和UPLC的a,c值存在良好的线性关系。a,c值线性关联的R2值分别为0.9914和0.9936。根据a,c值转换的线性方程,将川芎水提组分中各色谱峰在HPLC上的a,c值转换为UPLC上的a,c值,利用计算的a,c值进行UPLC的分离预测,以实验验证,模拟图与实验谱图一致。结论:本方法实现了两种分析条件的相互转化,实现了数据在这两个分析方法的通用性。方法简单、准确,有利于复杂样品的分析预测与优化。
Authors have developed a method to make a switch between HPLC and UPLC for analyzing a complex sample. In the study, water extracts of Radix Salvia miltiorrhizae was taken as a model sample. Retention parameters （a and c values） of 12 peaks were calculated on five linear gradients using both HPLC and UPLC. The relation ship for the a and c values on HPLC and UPLC was developed, respectively. with the linear equation, The a and c values on HPLC and UPLC Could be/ branferred each other, and predication and optimization was realized with calculated a and c values in the CSASS So ftware. We have obtained fine linear relationship for both a and c values under HPLC and UPLC. R^2 for a and c linear equation resulted in 0.9914 and 0.9936 respectively. The a and c values of water-extracts of Ligusticum chuanxiong was calculated using UPLC, while UPLC based analysis was predicted with calculated a and c values. The UPLC chromatogram was similar to the simulated one. We realized the switch between HPLC and UPLC using the method, allowing compatible data for both techniques. The method is simple and accurate. It facilitates the predication and optimization of a complex sample.