Image-based multi-scale mechanical analysis of strain amplification in neurons embedded in collagen gel. Issue 2 (25th January 2019)

• Record Type: Journal Article
• Authors: Chan, Victor W. L.; Tobin, William R.; Zhang, Sijia; Winkelstein, Beth A.; Barocas, Victor H.; Shephard, Mark S.; Picu, Catalin R.
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 22:Issue 2(2019)
• Page Start: 113
• Page End: 129
• Publication Date: 2019-01-25
• Subjects: neuron deformation -- back pain -- multiscale modeling -- spine mechanics; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2018.1538414
• Languages: English
• ISSNs: 1025-5842

Abstract

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.