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为生物分子的图案形成提供传输现象的基础。

Underpinning transport phenomena for the patterning of biomolecules.

机构信息

IBM Research - Zurich, Säumerstrasse 4, Rüschlikon, 8803, Switzerland.

Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, 8092, Switzerland.

出版信息

Chem Soc Rev. 2019 Mar 4;48(5):1236-1254. doi: 10.1039/c8cs00852c.

Abstract

Surface-based assays are increasingly being used in biology and medicine, which in turn demand increasing quantitation and reproducibility. This translates into more stringent requirements on the patterning of biological entities on surfaces (also referred to as biopatterning). This tutorial focuses on mass transport in the context of existing and emerging biopatterning technologies. We here develop a step-by-step analysis of how analyte transport affects surface kinetics, and of the advantages and limitations this entails in major categories of patterning methods, including evaporating sessile droplets, laminar flows in microfluidics or electrochemistry. Understanding these concepts is key to obtaining the desired pattern uniformity, coverage, analyte usage or processing time, and equally applicable to surface assays. A representative technological review accompanies each section, highlighting the technical progress enabled by transport control in e.g. microcontact printing, inkjet printing, dip-pen nanolithography and microfluidic probes. We believe this tutorial will serve researchers to better understand available patterning methods/principles, optimize conditions and to help design protocols/assays. By highlighting fundamental challenges and available approaches, we wish to trigger the development of new surface patterning methods and assays.

摘要

基于表面的分析方法在生物学和医学中的应用越来越广泛,这反过来又要求更高的定量和重现性。这就对生物实体在表面上的图案化(也称为生物图案化)提出了更严格的要求。本教程专注于现有和新兴生物图案化技术背景下的质量传输。我们在这里逐步分析了分析物传输如何影响表面动力学,以及在主要的图案化方法类别中,这带来了哪些优势和限制,包括蒸发的液滴、微流控或电化学中的层流。理解这些概念是获得所需图案均匀性、覆盖范围、分析物使用或处理时间的关键,同样适用于表面分析。每一节都附有代表性的技术综述,突出了通过运输控制在微接触印刷、喷墨印刷、蘸笔纳米光刻和微流控探针等方面实现的技术进步。我们相信,本教程将有助于研究人员更好地理解现有的图案化方法/原理,优化条件,并帮助设计方案/分析。通过突出基本挑战和可用方法,我们希望能够激发新的表面图案化方法和分析的发展。

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