Elucidating the interaction between stretch and stiffness using an agent-based spring network model of progressive...

Area of Science:

• Computational biology
• Mechanobiology
• Pulmonary medicine

Background:

• Pulmonary fibrosis involves mechanosensitive fibroblasts and myofibroblasts.
• Existing models focus on stiffness but neglect stretch-mediated behaviors, such as stretch-sensitive channels and latent TGF-β release.

Purpose of the Study:

• To develop a hybrid agent-based and spring network model that incorporates both stiffness and stretch.
• To evaluate the role of mechanical signaling in lung tissue homeostasis and fibrosis progression.

Main Methods:

• Developed a hybrid agent-based and spring network computational model.
• Simulated mechanical signaling (stiffness and stretch) in lung tissue networks.
• Identified a fibrotic threshold influencing network stability and disease outcome.

Main Results:

• The model recapitulates both stiffness- and stretch-mediated behaviors.
• A fibrotic threshold was identified, below which healing occurs and above which fibrosis develops.
• Altering stretch and stiffness signal weights produced pathological network structures resembling human IPF tissue.
• Network healing or fibrosis outcome depends on initial damage organization and mechanical signal balance.

Conclusions:

• Mechanical signaling, including stretch and stiffness, is crucial for lung tissue homeostasis and fibrosis.
• Network effects and initial damage organization significantly impact disease progression.
• The developed model offers insights into the complex interplay of mechanical forces in lung diseases.