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微流控芯片中物理细胞捕获的数值模拟

Numerical Modeling of Physical Cell Trapping in Microfluidic Chips.

作者信息

Cardona Sara, Mostafazadeh Nima, Luan Qiyue, Zhou Jian, Peng Zhangli, Papautsky Ian

机构信息

Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.

出版信息

Micromachines (Basel). 2023 Aug 26;14(9):1665. doi: 10.3390/mi14091665.

Abstract

Microfluidic methods have proven to be effective in separation and isolation of cells for a wide range of biomedical applications. Among these methods, physical trapping is a label-free isolation approach that relies on cell size as the selective phenotype to retain target cells on-chip for follow-up analysis and imaging. In silico models have been used to optimize the design of such hydrodynamic traps and to investigate cancer cell transmigration through narrow constrictions. While most studies focus on computational fluid dynamics (CFD) analysis of flow over cells and/or pillar traps, a quantitative analysis of mechanical interaction between cells and trapping units is missing. The existing literature centers on longitudinally extended geometries (e.g., micro-vessels) to understand the biological phenomenon rather than designing an effective cell trap. In this work, we aim to make an experimentally informed prediction of the critical pressure for a cell to pass through a trapping unit as a function of cell morphology and trapping unit geometry. Our findings show that a hyperelastic material model accurately captures the stress-related softening behavior observed in cancer cells passing through micro-constrictions. These findings are used to develop a model capable of predicting and extrapolating critical pressure values. The validity of the model is assessed with experimental data. Regression analysis is used to derive a mathematical framework for critical pressure. Coupled with CFD analysis, one can use this formulation to design efficient microfluidic devices for cell trapping and potentially perform downstream analysis of trapped cells.

摘要

微流控方法已被证明在广泛的生物医学应用中,对于细胞的分离和隔离是有效的。在这些方法中,物理捕获是一种无标记的隔离方法,它依赖细胞大小作为选择性表型,将目标细胞保留在芯片上以便后续分析和成像。计算机模拟模型已被用于优化此类流体动力学陷阱的设计,并研究癌细胞通过狭窄通道的迁移。虽然大多数研究集中在对细胞和/或柱形陷阱上的流动进行计算流体动力学(CFD)分析,但缺少对细胞与捕获单元之间机械相互作用的定量分析。现有文献集中在纵向延伸的几何形状(如微血管)上以理解生物学现象,而不是设计有效的细胞陷阱。在这项工作中,我们旨在根据细胞形态和捕获单元几何形状,通过实验得出细胞通过捕获单元的临界压力的预测值。我们的研究结果表明,超弹性材料模型准确地捕捉到了癌细胞通过微通道时观察到的与应力相关的软化行为。这些结果被用于开发一个能够预测和推断临界压力值的模型。该模型的有效性通过实验数据进行评估。回归分析用于推导临界压力的数学框架。结合CFD分析,人们可以使用这个公式来设计用于细胞捕获的高效微流控装置,并可能对捕获的细胞进行下游分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7729/10538085/25903230d153/micromachines-14-01665-g001.jpg

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