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Deformation simulation of cells seeded on a collagen-GAG scaffold in a flow perfusion bioreactor using a sequential 3D CFD-elastostatics model
Authors:C Jungreuthmayer  MJ Jaasma  AA Al-Munajjed  J Zanghellini  DJ Kelly  FJ O’Brien
Institution:1. Department of Chemistry, Sapienza University of Rome, 00185 Rome, Italy;2. Tissue Engineering Lab, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;3. Warsaw University of Technology, Faculty of Materials Science and Engineering, 02507 Warsaw, Poland
Abstract:Tissue-engineered bone shows promise in meeting the huge demand for bone grafts caused by up to 4 million bone replacement procedures per year, worldwide. State-of-the-art bone tissue engineering strategies use flow perfusion bioreactors to apply biophysical stimuli to cells seeded on scaffolds and to grow tissue suitable for implantation into the patient's body. The aim of this study was to quantify the deformation of cells seeded on a collagen-GAG scaffold which was perfused by culture medium inside a flow perfusion bioreactor. Using a μCT scan of an unseeded collagen-GAG scaffold, a sequential 3D CFD-deformation model was developed. The wall shear stress and the hydrostatic wall pressure acting on the cells were computed through the use of a CFD simulation and fed into a linear elastostatics model in order to calculate the deformation of the cells. The model used numerically seeded cells of two common morphologies where cells are either attached flatly on the scaffold wall or bridging two struts of the scaffold. Our study showed that the displacement of the cells is primarily determined by the cell morphology. Although cells of both attachment profiles were subjected to the same mechanical load, cells bridging two struts experienced a deformation up to 500 times higher than cells only attached to one strut. As the scaffold's pore size determines both the mechanical load and the type of attachment, the design of an optimal scaffold must take into account the interplay of these two features and requires a design process that optimizes both parameters at the same time.
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