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基于大体积处理提高纸基诊断敏感性的设计原理。

Design Principles for Enhancing Sensitivity in Paper-Based Diagnostics via Large-Volume Processing.

机构信息

Department of Chemical Engineering , Massachusetts Institute of Technology , Cambridge , Massachusetts 02142 , United States.

出版信息

Anal Chem. 2018 Aug 7;90(15):9472-9479. doi: 10.1021/acs.analchem.8b02113. Epub 2018 Jul 10.

DOI:10.1021/acs.analchem.8b02113
PMID:29924932
Abstract

In this work, we characterize the impact of large-volume processing upon the analytical sensitivity of flow-through paper-based immunoassays. Larger sample volumes feature greater molar quantities of available analyte, but the assay design principles which would enable the rapid collection of this dilute target are ill-defined. We developed a finite-element model to explore the operating conditions under which processing large sample volumes via pressure-driven convective flow would yield an improved binding signal. Our simulation results underscore the importance of establishing a high local concentration of the analyte-binding species within the porous substrate. This elevated abundance serves to enhance the binding kinetics, matching the time scale of target capture to the period during which the sample is in contact with the test zone (i.e., the effective residence time). These findings were experimentally validated using the rcSso7d-cellulose-binding domain (CBD) fusion construct, a bifunctional binding protein which adsorbs to cellulose in high abundance. As predicted by our modeling efforts, the local concentration achieved using the rcSso7d-CBD species is uniquely enabling for sensitivity enhancement through large-volume processing. The rapid analyte depletion which occurs at this high surface density also permits the processing of large sample volumes within practical time scales and flow regimes. Using these findings, we present guidance for the optimal means of processing large sample volumes for enhanced assay sensitivity.

摘要

在这项工作中,我们研究了大容量处理对流动纸基免疫分析的分析灵敏度的影响。较大的样品体积具有更多可用分析物的摩尔量,但能够快速收集这种稀释靶标所需的分析设计原则尚未明确。我们开发了一个有限元模型来探索通过压力驱动的对流来处理大体积样品的操作条件,这将产生改善的结合信号。我们的模拟结果强调了在多孔基质内建立分析物结合物质的局部高浓度的重要性。这种增加的丰度有助于增强结合动力学,使目标捕获的时间尺度与样品与测试区接触的时间(即有效停留时间)相匹配。使用 rcSso7d-纤维素结合域(CBD)融合构建体(一种大量吸附纤维素的双功能结合蛋白)实验验证了这些发现。正如我们的建模工作所预测的那样,使用 rcSso7d-CBD 物质实现的局部浓度对于通过大容量处理来提高灵敏度是唯一可行的。这种高表面密度下发生的快速分析物耗尽也允许在实际时间尺度和流动条件下处理大体积的样品。利用这些发现,我们提出了用于处理大体积样品以提高分析灵敏度的最佳方法的指导。

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