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响应面法在用于分析人血清中三环类抗抑郁药的堆积敏感毛细管电泳方法开发中的应用

Response surface methodology in the development of a stacking-sensitive capillary electrophoresis method for the analysis of tricyclic antidepressants in human serum.

作者信息

Galeano-Díaz Teresa, Acedo-Valenzuela María-Isabel, Mora-Díez Nielene, Silva-Rodríguez Antonio

机构信息

Departamento de Química Analítica, Facultad de Ciencias, Universidad de Extremadura, Badajoz, Spain.

出版信息

Electrophoresis. 2005 Sep;26(18):3518-27. doi: 10.1002/elps.200500120.

Abstract

Stacking methods are very important in overcoming the poor detection limits in capillary electrophoresis (CE). In this paper, the separation and determination of several tricyclic antidepressants by a stacking method is described. The inclusion of acetonitrile (ACN) in the sample causes stacking (transient pseudoisotachophoresis) especially in presence of sodium chloride. An experimental design (central composite design) together with the response surface methodology has been used to find the optimum composition of the separation buffer and the optimal stacking conditions in few experiments. The response functions used are the product of the total resolution by the number of peaks, for the optimization of the separation buffer, and the product of the total resolution by the mean of the peak heights, for the optimization of the stacking conditions. About 28% of the capillary volume is loaded with sample. The calibration curves are linear over the working range (50-300 ng/mL). With a bubble capillary, the limits of detection (LODs) are in the order of 5 ng/mL. For the analysis of serum samples, enrichment with sodium chloride and the protein precipitation with ACN are enough to avoid interferences and to get stacking. Recoveries between 91.6 and 104% and RSD between 0.6 and 12% are obtained in the analysis of samples of lyophilized human serum and non-lyophilized human serum, spiked with the drugs.

摘要

堆积方法在克服毛细管电泳(CE)中较差的检测限方面非常重要。本文描述了用一种堆积方法对几种三环类抗抑郁药的分离和测定。在样品中加入乙腈(ACN)会引起堆积(瞬态假等速电泳),尤其是在存在氯化钠的情况下。实验设计(中心复合设计)与响应面方法一起被用于在少量实验中找到分离缓冲液的最佳组成和最佳堆积条件。用于优化分离缓冲液的响应函数是总分辨率与峰数的乘积,用于优化堆积条件的响应函数是总分辨率与峰高平均值的乘积。约28%的毛细管体积加载样品。校准曲线在工作范围(50 - 300 ng/mL)内呈线性。使用气泡毛细管时,检测限(LOD)约为5 ng/mL。对于血清样品的分析,用氯化钠富集和用ACN进行蛋白质沉淀足以避免干扰并实现堆积。在对添加了药物的冻干人血清和非冻干人血清样品的分析中,回收率在91.6%至104%之间,相对标准偏差(RSD)在0.6%至12%之间。

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