The agent-based model (ABM) developed in this study provides a comprehensive representation of the muscle regeneration process, including the spatial dynamics of cytokines and the microvasculature. The model was calibrated to temporal biological datasets describing cross-sectional area (CSA) recovery, satellite stem cell (SSC), and fibroblast cell counts following muscle injury.
The calibrated model was validated by comparing additional outputs, such as macrophage, neutrophil, and capillary counts, to experimental observations. The model was then used to conduct in silico experiments by perturbing various cell or cytokine input conditions and comparing the results to published experimental studies.
A sensitivity analysis using Latin hypercube sampling and partial rank correlation coefficient identified specific cytokine diffusion coefficients and decay rates that could enhance CSA recovery. Combining alterations to HGF and VEGF-A decay, TGF-β and MMP-9 decay, and increased MCP-1 diffusion resulted in a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. This synergistic effect was driven by increased fibroblast and SSC proliferation compared to individual cytokine perturbations.
The model provides valuable insights into the complex, nonlinear interplay between cytokines and their impact on cellular behaviors and regeneration outcomes. These findings suggest that targeting specific combinations of cytokine dynamics could guide the development of more effective therapeutic strategies to enhance muscle recovery after injury.
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by Haase,M., Co... at www.biorxiv.org 08-16-2023
https://www.biorxiv.org/content/10.1101/2023.08.14.553247v2Deeper Inquiries