Learning Epithelial Elasticity via Local Tension Remodeling.

Area of Science:

• Biophysics
• Cell Biology
• Materials Science

Background:

• Epithelial tissues dynamically remodel in response to mechanical forces.
• Understanding how tissues store mechanical memory is a key challenge.

Purpose of the Study:

• Investigate mechanical memory in epithelial sheets using an active Vertex Model.
• Identify consequences of history-dependent mechanosensitive remodeling.

Main Methods:

• Developed an active Vertex Model for epithelial sheets.
• Incorporated a local, mechanosensitive tension-remodeling rule.
• Analyzed tissue response to localized and cyclic deformations.

Main Results:

• Localized stress permanently reprograms global shear modulus, tunable by remodeling rate.
• Tissues exhibit long-range mechanical memory, with distant stimuli responses modulated by prior events.
• Cyclic deformation programs tissue properties, including auxetic Poisson ratio.

Conclusions:

• Epithelial mechanics operates under unsupervised physical learning.
• Mechanosensitive remodeling rates control programmable tissue-scale rheology.