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首页> 外文期刊>Journal of chromatography, A: Including electrophoresis and other separation methods >Strategy for metabonomics research based on high-performance liquid chromatography and liquid chromatography coupled with tandem mass spectrometry
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Strategy for metabonomics research based on high-performance liquid chromatography and liquid chromatography coupled with tandem mass spectrometry

机译:基于高效液相色谱和液相色谱-串联质谱联用的代谢组学研究策略

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摘要

Metabonomics, the study of metabolites and their roles in various disease states, is a novel methodology arising from the post-genomics era. This methodology has been applied in many fields. Current metabonomic practice has relied on mass spectrometry (MS), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR) to analyze metabolites. In this study, a strategy was developed for applying high-performance liquid chromatography (HPLC) and LC-MS-MS to metabonomics research. One of the key problems to be solved in this strategy is to match the peaks between the chromatograms. A peak alignment algorithm has been developed to match the chromatograms before the pattern recognition. As an application example, the strategy described above was applied to metabonomics research on liver diseases, and the false-positive result of live cancer diagnosis from the hepatocirrhosis and hepatitis diseases was effectively reduced to 7.40%. Based on the pattern recognition, several potential biomarkers were found and further identified by the following LC-MS-MS experiments. The structures of eight potential biomarkers were given for distinguishing the liver cancer from the hepatocirrhosis and hepatitis diseases. (c) 2004 Elsevier B.V. All rights reserved.
机译:代谢组学是对代谢物及其在各种疾病状态中的作用的研究,是后基因组学时代兴起的一种新颖方法。该方法已经在许多领域中应用。当前的代谢组学实践依靠质谱(MS),气相色谱-质谱(GC-MS)和核磁共振(NMR)来分析代谢物。在这项研究中,开发了一种将高效液相色谱(HPLC)和LC-MS-MS应用于代谢组学研究的策略。此策略要解决的关键问题之一是使色谱图之间的峰匹配。已开发出峰比对算法,以在模式识别之前匹配色谱图。作为一个应用实例,上述策略被应用于肝病的代谢组学研究,从肝硬化和肝炎疾病诊断活癌的假阳性结果有效降低到7.40%。基于模式识别,发现了一些潜在的生物标记,并通过以下LC-MS-MS实验进一步鉴定。给出了八个潜在生物标志物的结构,以区分肝癌与肝硬化和肝炎疾病。 (c)2004 Elsevier B.V.保留所有权利。

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