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数值模拟电渗流推挽灌流及其在定量测定哺乳动物组织细胞外空间中酶活性中的应用评估。

Numerical Modeling of Electroosmotic Push-Pull Perfusion and Assessment of Its Application to Quantitative Determination of Enzymatic Activity in the Extracellular Space of Mammalian Tissue.

机构信息

Department of Chemistry, University of Pittsburgh , Pittsburgh, Pennsylvania 15260, United States.

出版信息

Anal Chem. 2017 Jun 6;89(11):5864-5873. doi: 10.1021/acs.analchem.7b00187. Epub 2017 May 11.

DOI:10.1021/acs.analchem.7b00187
PMID:28447456
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5823015/
Abstract

Many sampling methods have been developed to measure the extracellular concentrations of solutes in the extracellular space of mammalian tissue, e.g., brain. However, few have been used to quantitatively study the various processes, such as enzymatic degradation, that determines the fate of these solutes. For a method to be useful in this pursuit, it must be able to (1) perfuse tissue and collect the perfusate for quantitative analysis of the solutes introduced and reaction products produced, (2) control the average residence time of the active solutes, and (3) have the appropriate spatial resolution for the process of interest. Our lab previously developed a perfusion technique based on electroosmosis (EO), called EO push-pull perfusion (EOPPP), that is in principle suitable to meet these needs. However, much like the case for other sampling methods that came before, there are parameters that are needed for quantitative interpretation of data but that cannot be measured easily (or at all). In this paper, we present a robust finite element model that provides a deep understanding of fluid dynamics and mass transport in the EOPPP method, assesses the general applicability of EOPPP to studying enzyme activity in the ECS, and grants a simple approach to data treatment and interpretation to obtain, for example, V and K for an enzymatic reaction in the extracellular space of the tissue. This model is a valuable tool in optimizing and planning experiments without the need for costly experiments.

摘要

许多采样方法已经被开发出来,用于测量哺乳动物组织细胞外空间中溶质的细胞外浓度,例如大脑。然而,很少有方法被用于定量研究各种过程,如酶降解,这些过程决定了这些溶质的命运。对于一种方法来说,要想在这方面有所帮助,它必须能够:(1)灌注组织并收集灌流液,以便对引入的溶质和产生的反应产物进行定量分析;(2)控制活性溶质的平均停留时间;(3)对感兴趣的过程具有适当的空间分辨率。我们实验室之前开发了一种基于电渗流(EO)的灌注技术,称为 EO 推挽式灌注(EOPPP),从原理上讲,它适合满足这些需求。然而,与之前的其他采样方法一样,存在一些需要进行定量解释的数据参数,但这些参数不容易(或根本无法)测量。在本文中,我们提出了一个稳健的有限元模型,该模型深入了解了 EOPPP 方法中的流体动力学和质量传递,评估了 EOPPP 方法一般适用于研究细胞外空间中酶活性的适用性,并提供了一种简单的数据处理和解释方法,例如,在组织细胞外空间中进行酶反应时,可以获得 V 和 K 值。该模型是一种优化和规划实验的有价值的工具,无需进行昂贵的实验。

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ACS Chem Neurosci. 2020 Jul 15;11(14):2085-2093. doi: 10.1021/acschemneuro.0c00037. Epub 2020 Jul 6.
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ACS Chem Neurosci. 2013 May 15;4(5):838-48. doi: 10.1021/cn400082d. Epub 2013 Apr 30.