AI 中文总结
研究上皮层集体迁移中细胞形态差异，开发随机粒子 - 沃罗诺伊框架捕捉六向列组织，揭示边界驱动运动产生速度梯度，结合相关规则致外周与主体细胞形态不同，展现非平衡机械相互作用引发自组织图案形成。
AI 中文摘要
上皮层的集体迁移是从伤口愈合到癌症侵袭等过程的基础。一个关键且具有挑战性的特征是在单个迁移的融合片中出现不同的细胞形态，在活跃边界有更大、更长的细胞，而在主体中有更小、呈六向有序排列的细胞。在此，我们开发了一个随机粒子 - 沃罗诺伊框架，无需规定目标几何形状和不同细胞类型就能捕捉这种六向列组织。我们表明边界驱动的集体运动会产生向外的速度梯度。该梯度与密度和速度相关的分裂规则相结合，产生更大、更长且更容易出现缺陷的外周细胞，而主体细胞则保持更小、各向同性且呈六边形排列。这些结果展示了在集体迁移过程中，最小的非平衡机械相互作用如何导致涌现的、自组织的组织尺度图案形成。
英文摘要
Collective migration of epithelial layers underlies processes ranging from wound healing to cancer invasion. A defining yet challenging feature is the emergence of distinct cell morphologies within a single migrating confluent sheet, with larger, elongated cells at the active boundary and smaller, hexatically ordered cells in the bulk. Here, we develop a stochastic particle-Voronoi framework that captures this hexanematic organization without prescribing target geometries and distinct cell types. We show that boundary-driven collective motion generates an outward velocity gradient. This gradient, coupled to a density and velocity-dependent division rule, produces peripheral cells that are larger, more elongated, and more defect-prone, while bulk cells remain smaller, isotropic, and hexagonally packed. These results show how minimal, non-equilibrium mechanical interactions give rise to emergent, self-organized tissue-scale patterning during collective migration.
