2023/06/12 by Satyam Pandey, Soumitra Kolya, Pandey, Satyam +7 · 3 citations
Agricultural and Biological Sciences · Materials Science · Physics and Astronomy · #Biological Physics (physics.bio-ph) #FOS: Physical sciences #Material Dynamics and Properties #Plant and animal studies #Soft Condensed Matter (cond-mat.soft) #Spectroscopy and Quantum Chemical Studies
paper · pdf · doi:10.48550/arxiv.2306.07250
openalex publication_date 2023/06/12 · openalex created_date 2023/06/14 · openalex updated_date 2026/08/01
The glassy dynamics in confluent epithelial monolayers is crucial for several biological processes, such as wound healing, embryogenesis, cancer progression, etc. Several experiments have indicated that, unlike particulate systems, the glassy dynamics in these systems correlates with the static properties and shows a readily-found sub-Arrhenius relaxation. However, whether the statics-dynamics correlation is only qualitative or can provide quantitative predictions and what leads to the sub-Arrhenius relaxation remains unclear. We apply a particular analytical theory of glassy dynamics, the mode-coupling theory (MCT) that predicts dynamics using static properties alone as input, to the confluent systems. We demonstrate the remarkable applicability of MCT in simulations of the Vertex model and experiments on Madin-Darby Canine Kidney cells and show the quantitative nature of the structure-dynamics correlation in these systems. Our results elucidate that the structure-dynamics feedback mechanism of MCT, and not the barrier crossing mechanism, dominates the glassy dynamics in these systems where the relaxation time diverges as a power law with a universal exponent of 3/2. This slower-than-exponential divergence naturally explains the sub-Arrhenius relaxation dynamics in these systems. The quantitative nature of the structure-dynamics correlation also suggests the possibility of describing various complex biological processes, such as cell division and apoptosis, via the static properties of the systems, such as cell shape or shape variability.