Abstract
A general multi-scale strategy is presented for modeling the mechanical environment of a group of neurons that were embedded within a collagenous matrix. The results of the multi-scale simulation are used to estimate the local strains that arise in neurons when the extracellular matrix is deformed. The distribution of local strains was found to depend strongly on the configuration of the embedded neurons relative to the loading direction, reflecting the anisotropic mechanical behavior of the neurons. More importantly, the applied strain on the surrounding extracellular matrix is amplified in the neurons for all loading configurations that are considered. In the most severe case, the applied strain is amplified by at least a factor of 2 in 10% of the neurons' volume. The approach presented in this paper provides an extension to the capability of past methods by enabling the realistic representation of complex cell geometry into a multi-scale framework. The simulation results for the embedded neurons provide local strain information that is not accessible by current experimental techniques.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 113-129 |
| Number of pages | 17 |
| Journal | Computer methods in biomechanics and biomedical engineering |
| Volume | 22 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jan 25 2019 |
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Keywords
- back pain
- multiscale modeling
- neuron deformation
- spine mechanics
Cite this
Image-based multi-scale mechanical analysis of strain amplification in neurons embedded in collagen gel. / Chan, Victor W.L.; Tobin, William R.; Zhang, Sijia; Winkelstein, Beth A.; Barocas, Victor H.; Shephard, Mark S.; Picu, Catalin R.
In: Computer methods in biomechanics and biomedical engineering, Vol. 22, No. 2, 25.01.2019, p. 113-129.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Image-based multi-scale mechanical analysis of strain amplification in neurons embedded in collagen gel
AU - Chan, Victor W.L.
AU - Tobin, William R.
AU - Zhang, Sijia
AU - Winkelstein, Beth A.
AU - Barocas, Victor H.
AU - Shephard, Mark S.
AU - Picu, Catalin R.
PY - 2019/1/25
Y1 - 2019/1/25
N2 - A general multi-scale strategy is presented for modeling the mechanical environment of a group of neurons that were embedded within a collagenous matrix. The results of the multi-scale simulation are used to estimate the local strains that arise in neurons when the extracellular matrix is deformed. The distribution of local strains was found to depend strongly on the configuration of the embedded neurons relative to the loading direction, reflecting the anisotropic mechanical behavior of the neurons. More importantly, the applied strain on the surrounding extracellular matrix is amplified in the neurons for all loading configurations that are considered. In the most severe case, the applied strain is amplified by at least a factor of 2 in 10% of the neurons' volume. The approach presented in this paper provides an extension to the capability of past methods by enabling the realistic representation of complex cell geometry into a multi-scale framework. The simulation results for the embedded neurons provide local strain information that is not accessible by current experimental techniques.
AB - A general multi-scale strategy is presented for modeling the mechanical environment of a group of neurons that were embedded within a collagenous matrix. The results of the multi-scale simulation are used to estimate the local strains that arise in neurons when the extracellular matrix is deformed. The distribution of local strains was found to depend strongly on the configuration of the embedded neurons relative to the loading direction, reflecting the anisotropic mechanical behavior of the neurons. More importantly, the applied strain on the surrounding extracellular matrix is amplified in the neurons for all loading configurations that are considered. In the most severe case, the applied strain is amplified by at least a factor of 2 in 10% of the neurons' volume. The approach presented in this paper provides an extension to the capability of past methods by enabling the realistic representation of complex cell geometry into a multi-scale framework. The simulation results for the embedded neurons provide local strain information that is not accessible by current experimental techniques.
KW - back pain
KW - multiscale modeling
KW - neuron deformation
KW - spine mechanics
UR - http://www.scopus.com/inward/record.url?scp=85057315785&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057315785&partnerID=8YFLogxK
U2 - 10.1080/10255842.2018.1538414
DO - 10.1080/10255842.2018.1538414
M3 - Article
C2 - 30450957
AN - SCOPUS:85057315785
VL - 22
SP - 113
EP - 129
JO - Computer Methods in Biomechanics and Biomedical Engineering
JF - Computer Methods in Biomechanics and Biomedical Engineering
SN - 1025-5842
IS - 2
ER -