Multiscale Kinematic Growth Coupled With Mechanosensitive Systems Biology in Open-Source Software

Area of Science:

• Biomechanics
• Computational Biology
• Systems Biology

Background:

• Multiscale modeling integrates cell-scale biological processes with tissue-scale mechanical behavior.
• Disease growth modeling requires understanding the interplay between cell signaling and tissue mechanics.
• Existing models often lack comprehensive multiscale connections between different biological scales.

Purpose of the Study:

• To develop and validate multiscale growth and remodeling (G&R) models.
• To investigate the influence of cell-level signaling pathways on tissue-level G&R.
• To provide open-source tools for simulating and studying multiscale biomechanical phenomena.

Main Methods:

• Cell-scale modeling using systems of ordinary differential equations (ODEs) and partial differential equations (PDEs) for biochemical reactions.
• Tissue-scale modeling employing kinematic growth within continuum frameworks.
• Integration of cell- and tissue-scale models using one-way and two-way coupling strategies within the open-source software frameworks, FEBio and FEniCS.

Main Results:

• Emergent growth patterns are driven by biochemical reactions, the choice of ODE vs. PDE systems biology models, and the coupling strategy.
• Biochemical diffusivity significantly impacts G&R outcomes.
• FEBio and FEniCS frameworks produced nearly identical results, confirming cross-verification.

Conclusions:

• Multiscale modeling effectively captures the complex interactions between cell-level signaling and tissue-level mechanics in disease growth.
• The choice of modeling approach (ODE/PDE) and coupling strategy influences simulation outcomes.
• The developed open-source tools facilitate reproducibility and education in the biomechanics community.