Journal article 680 views
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading
Computers in Biology and Medicine, Volume: 89, Pages: 181 - 189
Swansea University Author:
Feihu Zhao
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DOI (Published version): 10.1016/j.compbiomed.2017.08.003
Abstract
Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation a...
Published in: | Computers in Biology and Medicine |
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ISSN: | 0010-4825 |
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2017
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URI: | https://cronfa.swan.ac.uk/Record/cronfa51685 |
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2019-10-11T11:28:54.2221352 v2 51685 2019-09-04 A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading 1c6e79b6edd08c88a8d17a241cd78630 0000-0003-0515-6808 Feihu Zhao Feihu Zhao true false 2019-09-04 MEDE Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation and overall tissue formation. However, due to the complex multi-physics environment of cells within TE scaffolds, cell transport under mechanical stimulation is not fully understood. Therefore, in this study, we have developed a coupled multiphysics model to predict cell density distribution in a TE scaffold. In this model, cell transport is modelled as a thermal conduction process, which is driven by the pore fluid pressure under applied loading. As a case study, the model is investigated to predict the cell density patterns of pre-osteoblasts MC3T3-e1 cells under a range of different loading regimes, to obtain an understanding of desirable mechanical stimulation that will enhance cell density distribution within TE scaffolds. The results of this study have demonstrated that fluid perfusion can result in a higher cell density in the scaffold region closed to the outlet, while cell density distribution under mechanical compression was similar with static condition. More importantly, the study provides a novel computational approach to predict cell distribution in TE scaffolds under mechanical loading. Journal Article Computers in Biology and Medicine 89 181 189 0010-4825 Coupled thermal-pore pressure, Biphasic poroelasticity, Cell transport, Mechanical stimulation 1 10 2017 2017-10-01 10.1016/j.compbiomed.2017.08.003 COLLEGE NANME Biomedical Engineering COLLEGE CODE MEDE Swansea University 2019-10-11T11:28:54.2221352 2019-09-04T15:40:55.7532561 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Feihu Zhao 0000-0003-0515-6808 1 Ted J. Vaughan 2 Myles J. Mc Garrigle 3 Laoise M. McNamara 4 |
title |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
spellingShingle |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading Feihu Zhao |
title_short |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
title_full |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
title_fullStr |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
title_full_unstemmed |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
title_sort |
A coupled diffusion-fluid pressure model to predict cell density distribution for cells encapsulated in a porous hydrogel scaffold under mechanical loading |
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1c6e79b6edd08c88a8d17a241cd78630 |
author_id_fullname_str_mv |
1c6e79b6edd08c88a8d17a241cd78630_***_Feihu Zhao |
author |
Feihu Zhao |
author2 |
Feihu Zhao Ted J. Vaughan Myles J. Mc Garrigle Laoise M. McNamara |
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Journal article |
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Computers in Biology and Medicine |
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89 |
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181 |
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2017 |
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Swansea University |
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0010-4825 |
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10.1016/j.compbiomed.2017.08.003 |
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Faculty of Science and Engineering |
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School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering |
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description |
Tissue formation within tissue engineering (TE) scaffolds is preceded by growth of the cells throughout the scaffold volume and attachment of cells to the scaffold substrate. It is known that mechanical stimulation, in the form of fluid perfusion or mechanical strain, enhances cell differentiation and overall tissue formation. However, due to the complex multi-physics environment of cells within TE scaffolds, cell transport under mechanical stimulation is not fully understood. Therefore, in this study, we have developed a coupled multiphysics model to predict cell density distribution in a TE scaffold. In this model, cell transport is modelled as a thermal conduction process, which is driven by the pore fluid pressure under applied loading. As a case study, the model is investigated to predict the cell density patterns of pre-osteoblasts MC3T3-e1 cells under a range of different loading regimes, to obtain an understanding of desirable mechanical stimulation that will enhance cell density distribution within TE scaffolds. The results of this study have demonstrated that fluid perfusion can result in a higher cell density in the scaffold region closed to the outlet, while cell density distribution under mechanical compression was similar with static condition. More importantly, the study provides a novel computational approach to predict cell distribution in TE scaffolds under mechanical loading. |
published_date |
2017-10-01T04:03:40Z |
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1763753298190401536 |
score |
11.021648 |