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基于定量核磁共振代谢组学的模式识别与生物标志物验证

Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics.

作者信息

Serkova Natalie J, Niemann Claus U

机构信息

University of Colorado Health Sciences Center, Biomedical MRI/MRS Cancer Center Core, Department of Anesthesiology, Denver, CO 80262, USA.

出版信息

Expert Rev Mol Diagn. 2006 Sep;6(5):717-31. doi: 10.1586/14737159.6.5.717.

Abstract

The collection of global metabolic data and their interpretation (both spectral and biochemical) using modern spectroscopic techniques and appropriate statistical approaches, are known as 'metabolic profiling', 'metabonomics' or 'metabolomics'. This review addresses 1H-nuclear magnetic resonance (NMR)-based metabolomic principles and their application in biomedical science, with special emphasis on their potential in translational research in transplantation, oncology, and drug toxicity or discovery. Various steps in metabolomics analysis are described in order to illustrate the types of biological samples, their respective handling and preparation for 1H-NMR analysis; provide a rationale for using pattern-recognition techniques (spectral database concept) versus quantitative 1H-NMR-based metabolomics (metabolite database concept); and identify necessary technological and logistical future developments that will allow 1H-NMR-based metabolomics to become an established tool in biomedical research and patient care.

摘要

利用现代光谱技术和适当的统计方法收集全球代谢数据并对其进行解释(包括光谱和生化方面),这被称为“代谢谱分析”“代谢组学”或“代谢物组学”。本综述阐述了基于氢核磁共振(NMR)的代谢组学原理及其在生物医学科学中的应用,特别强调了它们在移植、肿瘤学以及药物毒性或发现等转化研究中的潜力。文中描述了代谢组学分析的各个步骤,以说明生物样本的类型、它们各自的处理方式以及用于氢核磁共振分析的制备方法;为使用模式识别技术(光谱数据库概念)与基于定量氢核磁共振的代谢组学(代谢物数据库概念)提供理论依据;并确定未来必要的技术和后勤发展,以使基于氢核磁共振的代谢组学成为生物医学研究和患者护理中的既定工具。

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