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Numerical Modeling of Physical Cell Trapping in Microfluidic Chips

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-u...

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Autores principales: Cardona, Sara, Mostafazadeh, Nima, Luan, Qiyue, Zhou, Jian, Peng, Zhangli, Papautsky, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538085/
https://www.ncbi.nlm.nih.gov/pubmed/37763828
http://dx.doi.org/10.3390/mi14091665
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author Cardona, Sara
Mostafazadeh, Nima
Luan, Qiyue
Zhou, Jian
Peng, Zhangli
Papautsky, Ian
author_facet Cardona, Sara
Mostafazadeh, Nima
Luan, Qiyue
Zhou, Jian
Peng, Zhangli
Papautsky, Ian
author_sort Cardona, Sara
collection PubMed
description 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.
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spelling pubmed-105380852023-09-29 Numerical Modeling of Physical Cell Trapping in Microfluidic Chips Cardona, Sara Mostafazadeh, Nima Luan, Qiyue Zhou, Jian Peng, Zhangli Papautsky, Ian Micromachines (Basel) Article 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. MDPI 2023-08-26 /pmc/articles/PMC10538085/ /pubmed/37763828 http://dx.doi.org/10.3390/mi14091665 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cardona, Sara
Mostafazadeh, Nima
Luan, Qiyue
Zhou, Jian
Peng, Zhangli
Papautsky, Ian
Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title_full Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title_fullStr Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title_full_unstemmed Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title_short Numerical Modeling of Physical Cell Trapping in Microfluidic Chips
title_sort numerical modeling of physical cell trapping in microfluidic chips
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10538085/
https://www.ncbi.nlm.nih.gov/pubmed/37763828
http://dx.doi.org/10.3390/mi14091665
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