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Modelling the compression and reorganization of cell aggregates
1Department of Mathematics, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino 10129, Italy. chiara.giverso@polito.it
This study models multicellular aggregates as porous materials, incorporating liquid components to explain their mechanical behavior. The enhanced elasto-visco-plastic model accurately predicts responses to compression, validating experimental observations.
Area of Science:
- Biophysics
- Materials Science
- Cellular Mechanics
Background:
- Multicellular aggregates exhibit complex mechanical behaviors influenced by cellular and interstitial components.
- Existing models often simplify the interplay between solid cellular structures and fluid phases within aggregates.
- Understanding these behaviors is crucial for fields like tissue engineering and developmental biology.
Purpose of the Study:
- To extend an existing elasto-visco-plastic model for multicellular aggregates.
- To incorporate the effects of a liquid constituent (water) within cellular spheroids.
- To accurately describe the mechanical responses of porous cellular materials under compression.
Main Methods:
- Developed an elasto-visco-plastic constitutive model for porous multicellular aggregates.
- Treated aggregates as composite materials with distinct elastic/plastic (cellular) and viscous (liquid) properties.
- Applied the model to simulate uniaxial homogeneous compression under constant load and fixed deformation conditions.
Main Results:
- The model successfully integrates elastic, plastic, and viscous behaviors of cell aggregates.
- Plasticity arises from cell-cell adhesion bond rearrangement, introducing a yield stress.
- The liquid phase contributes a viscous response, crucial for dynamic deformation.
Conclusions:
- The extended model provides a comprehensive framework for understanding the mechanical behavior of multicellular aggregates.
- Model predictions align well with experimental data on the dynamics of biological tissues under deformation.
- This approach enhances the predictive power for cellular material responses in various biological contexts.
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