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通过改进样品预处理和高效液相色谱测定法同时测定帕金森病患者血浆中的左旋多巴、其代谢产物和卡比多巴。

Simultaneous measurement of L-dopa, its metabolites and carbidopa in plasma of parkinsonian patients by improved sample pretreatment and high-performance liquid chromatographic determination.

作者信息

Lucarelli C, Betto P, Ricciarello G, Giambenedetti M, Corradini C, Stocchi F, Belliardo F

机构信息

Istituto Superiore di Sanità, Rome, Italy.

出版信息

J Chromatogr. 1990 Jul 6;511:167-76. doi: 10.1016/s0021-9673(01)93282-0.

Abstract

A procedure is described for the determination of L-3,4-dihydroxyphenylalanine (L-DOPA), its metabolites and carbidopa (CD) in plasma of Parkinsonian patients by high-performance liquid chromatography with dual working-electrode coulometric electrochemical detection. An efficient sample preparation scheme is presented for the isolation of L-DOPA, its metabolites and the catecholamines from the same plasma aliquot. After a simple deproteinization with methanol containing 2% of 0.5 M perchloric acid and evaporation of the solvent, L-DOPA, its metabolites and CD were separated with a 5-micron Nucleosil C18 column. Catecholamines were extracted from the supernatant of the deproteinized plasma by ion exchange on small columns and adsorption on alumina. Recoveries were close to 100% for L-DOPA, its metabolites and CD and 70% for catecholamines. The use of the same mobile phase for the concurrent assay of L-DOPA, its metabolites and catecholamines considerably increased the throughput of samples in the chromatographic system. The dual-electrode coulometric detector afforded peak identification by comparing current ratios. Monitoring of data from patients under L-DOPA therapy is reported.

摘要

本文描述了一种通过高效液相色谱结合双工作电极库仑电化学检测法,测定帕金森病患者血浆中L-3,4-二羟基苯丙氨酸(L-DOPA)、其代谢产物及卡比多巴(CD)的方法。文中介绍了一种有效的样品制备方案,可从同一血浆等分试样中分离出L-DOPA、其代谢产物及儿茶酚胺。用含2% 0.5 M高氯酸的甲醇进行简单的脱蛋白处理并蒸发溶剂后,使用5微米的Nucleosil C18柱分离L-DOPA、其代谢产物及CD。儿茶酚胺通过在小柱上进行离子交换并吸附在氧化铝上,从脱蛋白血浆的上清液中提取。L-DOPA、其代谢产物及CD的回收率接近100%,儿茶酚胺的回收率为70%。使用相同的流动相同时测定L-DOPA、其代谢产物及儿茶酚胺,显著提高了色谱系统中样品的通量。双电极库仑检测器通过比较电流比来进行峰识别。报告了对接受L-DOPA治疗患者的数据监测情况。

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