Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/117357
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Type: Journal article
Title: Computational investigation on the biomechanical responses of the osteocytes to the compressive stimulus: a poroelastic model
Author: Wang, L.
Dong, J.
Xian, C.J.
Citation: BioMed Research International, 2018; 2018:4071356-1-4071356-16
Publisher: Hindawi
Issue Date: 2018
ISSN: 2314-6133
2314-6141
Statement of
Responsibility: 
Liping Wang, Jianghui Dong and Cory J. Xian
Abstract: Osteocytes, the major type of bone cells embedded in the bone matrix and surrounded by the lacunar and canalicular system, can serve as biomechanosensors and biomechanotranducers of the bone. Theoretical analytical methods have been employed to investigate the biomechanical responses of osteocytes in vivo; the poroelastic properties have not been taken into consideration in the three-dimensional (3D) finite element model. In this study, a 3D poroelastic idealized finite element model was developed and was used to predict biomechanical behaviours (maximal principal strain, pore pressure, and fluid velocity) of the osteocyte-lacunar-canalicular system under 150-, 1000-, 3000-, and 5000-microstrain compressive loads, respectively, representing disuse, physiological, overuse, and pathological overload loading stimuli. The highest local strain, pore pressure, and fluid velocity were found to be highest at the proximal region of cell processes. These data suggest that the strain, pore pressure, and fluid velocity of the osteocyte-lacunar-canalicular system increase with the global loading and that the poroelastic material property affects the biomechanical responses to the compressive stimulus. This new model can be used to predict the mechanobiological behaviours of osteocytes under the four different compressive loadings and may provide an insight into the mechanisms of mechanosensation and mechanotransduction of the bone.
Keywords: Osteocytes; compressive strength; computer simulation
Rights: © 2018 Liping Wang et al.This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOI: 10.1155/2018/4071356
Grant ID: NHMRC
Published version: http://dx.doi.org/10.1155/2018/4071356
Appears in Collections:Aurora harvest 8
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