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Numerical Modeling of Physical Cell Trapping in Microfluidic Chips.
Cardona, Sara; Mostafazadeh, Nima; Luan, Qiyue; Zhou, Jian; Peng, Zhangli; Papautsky, Ian.
Afiliación
  • Cardona S; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
  • Mostafazadeh N; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
  • Luan Q; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
  • Zhou J; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
  • Peng Z; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
  • Papautsky I; Department of Biomedical Engineering, University of Illinois, Chicago, IL 60607, USA.
Micromachines (Basel) ; 14(9)2023 Aug 26.
Article en En | MEDLINE | ID: mdl-37763828
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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Micromachines (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Micromachines (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza