Image-based multi-scale mechanical analysis of strain amplification in neurons embedded in collagen gel

Victor W.L. Chan, William R. Tobin, Sijia Zhang, Beth A. Winkelstein, Victor H. Barocas, Mark S. Shephard, Catalin R. Picu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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 languageEnglish (US)
Pages (from-to)113-129
Number of pages17
JournalComputer methods in biomechanics and biomedical engineering
Volume22
Issue number2
DOIs
StatePublished - Feb 2019

Bibliographical note

Funding Information:
Computing resources were provided by the Center for Computational Innovations at Rensselaer Polytechnic Institute.This work by supported by the National Institute of Health through Grant No. U01-EB016638.

Keywords

  • back pain
  • multiscale modeling
  • neuron deformation
  • spine mechanics

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