Title: Immersed Boundary Models for Quantifying Flow-Induced Mechanical Stimuli on Stem Cells Seeded on 3D Scaffolds in Perfusion Bioreactors
Authors: Guyot, Yann *
Smeets, Bart * ×
Odenthal, Tim
Subramani, Ramesh
Luyten, Frank
Ramon, Herman #
Papantoniou, Ioannis #
Geris, Liesbet #
Issue Date: 22-Sep-2016
Publisher: Public Library of Science
Series Title: PLoS Computational Biology vol:12 issue:9
Article number: e1005108
Abstract: Perfusion bioreactors regulate flow conditions in order to provide cells with oxygen, nutrients and flow-associated mechanical stimuli. Locally, these flow conditions can vary depending on the scaffold geometry, cellular confluency and amount of extra cellular matrix deposition. In this study, a novel application of the immersed boundary method was introduced in order to represent a detailed deformable cell attached to a 3D scaffold inside a perfusion bioreactor and exposed to microscopic flow. The immersed boundary model permits the prediction of mechanical effects of the local flow conditions on the cell. Incorporating stiffness values measured with atomic force microscopy and micro-flow boundary conditions obtained from computational fluid dynamics simulations on the entire scaffold, we compared cell deformation, cortical tension, normal and shear pressure between different cell shapes and locations. We observed a large effect of the precise cell location on the local shear stress and we predicted flow-induced cortical tensions in the order of 5 pN/μm, at the lower end of the range reported in literature. The proposed method provides an interesting tool to study perfusion bioreactors processes down to the level of the individual cell’s micro-environment, which can further aid in the achievement of robust bioprocess control for regenerative medicine applications.
ISSN: 1553-734X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Biomechanics Section
Skeletal Biology and Engineering Research Center (+)
Division of Mechatronics, Biostatistics and Sensors (MeBioS)
* (joint) first author
× corresponding author
# (joint) last author

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