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通过强度阈值分析量化微流控系统中生物标志物预浓缩和耗尽的时空动态。

Quantifying spatio-temporal dynamics of biomarker pre-concentration and depletion in microfluidic systems by intensity threshold analysis.

机构信息

Electrical and Computer Engineering, University of Virginia , Charlottesville, Virginia 22904, USA.

出版信息

Biomicrofluidics. 2014 Oct 6;8(5):052009. doi: 10.1063/1.4897283. eCollection 2014 Sep.

DOI:10.1063/1.4897283
PMID:25538800
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4222295/
Abstract

Microfluidic systems are commonly applied towards pre-concentration of biomarkers for enhancing detection sensitivity. Quantitative information on the spatial and temporal dynamics of pre-concentration, such as its position, extent, and time evolution are essential towards sensor design for coupling pre-concentration to detection. Current quantification methodologies are based on the time evolution of fluorescence signals from biomarkers within a statically defined region of interest, which does not offer information on the spatial dynamics of pre-concentration and leads to significant errors when the pre-concentration zone is delocalized or exhibits wide variations in size, shape, and position over time under the force field. We present a dynamic methodology for quantifying the region of interest by using a statistical description of particle distribution across the device geometry to determine the intensity thresholds for particle pre-concentration. This method is applied to study the delocalized pre-concentration dynamics under an electrokinetic force balance driven by negative dielectrophoresis, for aligning the pre-concentration and detection regions of neuropeptide Y, and for quantifying the polarizability dispersion of silica nano-colloids with frequency of the force field. We envision the application of this automated methodology on data from 2D images and 3D Z-stacks for quantifying pre-concentration dynamics over delocalized regions as a function of the force field.

摘要

微流控系统通常用于生物标志物的预浓缩,以提高检测灵敏度。关于预浓缩的空间和时间动态的定量信息,如其位置、程度和时间演变,对于将预浓缩与检测相结合的传感器设计至关重要。当前的定量方法基于静态定义的感兴趣区域内生物标志物的荧光信号随时间的演变,该方法无法提供预浓缩的空间动态信息,并且当预浓缩区在力场下空间定位时会导致显著的误差或表现出大小、形状和位置的广泛变化。我们提出了一种通过使用粒子在整个器件几何形状上的分布的统计描述来定量感兴趣区域的动态方法,以确定粒子预浓缩的强度阈值。该方法应用于研究由负介电泳驱动的电动力学力平衡下的分散预浓缩动力学,以对齐神经肽 Y 的预浓缩和检测区域,并量化频率为电场的二氧化硅纳米胶体的极化率色散。我们设想将这种自动化方法应用于来自 2D 图像和 3D Z 堆叠的数据,以量化作为力场函数的分散区域的预浓缩动力学。

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