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首页> 外文期刊>Clinica chimica acta: International journal of clinical chemistry and applied molecular biology >Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications
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Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications

机译:临床分析和其他生物医学应用的机器人蛋白样品制备的最新进展

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摘要

Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, and further monitoring of disease. However, their analysis requires powerful, selective and high-throughput sample preparation and product (analyze) characterisation approaches. In general, manual sample processing is tedious, complex and time-consuming, especially when large numbers of samples have to be processed (e.g., in clinical studies). Automation via microtiter-plate platforms involving robotics has brought improvements in high-throughput performance while comparable or even better precisions and repeatability (intra-day, inter-day) were achieved. At the same time, waste production and exposure of laboratory personnel to hazards were reduced. In comprehensive protein analysis workflows (e.g., liquid chromatography-tandem mass spectrometry analysis), sample preparation is an unavoidable step. This review surveys the recent achievements in automation of bottom-up and top-down protein and/or proteomics approaches. Emphasis is put on high-end mull-well plate robotic platforms developed for clinical analysis and other biomedical applications. The literature from 2013 to date has been covered.
机译:新蛋白质生物标志物候选人的发现已成为临床化学,分析化学和生物医学领域的主要研究目标。当涉及诊断,预后和进一步监测疾病时,这些重要物种构成了分子靶标。然而,它们的分析需要强大,选择性和高通量的样品制备和产品(分析)表征方法。通常,手动样品加工乏味,复杂且耗时,特别是当必须加工大量样品(例如,在临床研究中)。涉及机器人的微量滴定板平台的自动化使高通量的性能提高,而可比或甚至更好的精确和重复性(日内,日内,日内)。与此同时,减少了废物生产和实验室人员对危害的暴露。在综合蛋白质分析工作流(例如,液相色谱 - 串联质谱分析)中,样品制备是不可避免的步骤。此述评调查最近的自动化蛋白质和/或蛋白质组学方法的自动化成果。强调为临床分析和其他生物医学应用开发的高端仔细井板机器人平台。从2013年到达迄今为止的文献已被涵盖。

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