[论文解读] Universal Persistent Brownian Motions in Confluent Tissues

Alessandro Rizzi, Sangwoo Kim|arXiv (Cornell University)|Feb 25, 2026

Micro and Nano Robotics被引用 0

一句话总结

该论文表明，在二维共形组织模型中，在两种不同的主动力模式——牵引力和连接处张力波动——作用下的长时间细胞运动，尽管在细胞形状、重排和时空相关性方面存在模式特异性差异，仍收敛到持续的布朗运动动力学。

ABSTRACT

Biological tissues are active materials whose non-equilibrium dynamics emerge from distinct cellular force-generating mechanisms. Using a two-dimensional active foam model, we compare the effects of traction forces and junctional tension fluctuations on confluent tissue dynamics. While these two modes of activity produce qualitatively different cell shapes, rearrangement statistics, and spatiotemporal correlations in fluid states, we find that the long-time cellular motion universally converges to persistent Brownian dynamics. This universal feature contrasts with the non-universal correlations between cell geometry, rearrangement rate, and fluidity, which depend sensitively on the underlying modes of active force. Our results demonstrate that persistent Brownian motion provides a minimal framework for describing tissue dynamics, while distinct active forces leave identifiable structural and dynamical signatures, thereby enabling inference of the dominant active force in fluid state tissues.

研究动机与目标

• Motivate understanding of how active cellular forces drive non-equilibrium tissue dynamics in confluent monolayers.
• Compare two dominant activity modes—traction forces and junctional tension fluctuations—within a 2D active foam/vertex framework.
• Identify universal features of long-time cell motion and mode-specific signatures in fluid states.

提出的方法

• Use a two-dimensional active foam/vertex model under confluent conditions to simulate tissue dynamics.
• Represent traction as self-propulsion with polarity undergoing rotational diffusion; model tension fluctuations via an Ornstein-Uhlenbeck process.
• Solve overdamped Langevin dynamics for vertex positions with forces from tensions, normals, and traction.
• Analyze mean-squared relative displacement (MSRD) to classify solid versus fluid states and to extract persistent dynamics.
• Compute cell geometry metrics (shape factor q and aspect ratio α) and track T1 transitions to study rearrangements and energy landscapes.

实验结果

研究问题

• RQ1 How do traction forces and tension fluctuations individually affect fluidization and cell rearrangements in confluent tissues?
• RQ2 What are the universal features of long-time cell movement across these activity modes?
• RQ3 How do cell geometry and T1 dynamics correlate with fluidity under each active-force mode?
• RQ4 Can persistent Brownian motion describe long-time MSD/MSRD despite non-universal short-time correlations?
• RQ5 What signatures in structure and dynamics can indicate the dominant active force in a tissue?

主要发现

• Long-time cell motion in both traction-dominated and tension-fluctuation-dominated fluids is universally described by persistent Brownian motion.
• MSRD(t*) scales with a persistent Brownian framework without free parameters for both modes, after adjusting for velocity correlations.
• Traction and tension fluctuations yield non-universal correlations between cell shape metrics and fluidity, reflecting mode-specific structural dynamics.
• Traction-driven rearrangements show uniaxial elongation and high T1 success rates with zero stalling time, while tension fluctuations produce lax, highly curved junctions and finite T1 stalling with many unsuccessful events.
• Velocity correlations reveal collective motion and velocity persistence under traction, but not under tension fluctuations, which remain largely non-collective.
• Correcting MSRD by velocity correlation length collapses data into two branches, indicating a universal long-time behavior despite distinct microscopic mechanisms.