论文标题

拓扑包装统计数据区分了生活和非生命问题

Topological packing statistics distinguish living and non-living matter

论文作者

Skinner, Dominic J., Jeckel, Hannah, Martin, Adam C., Drescher, Knut, Dunkel, Jörn

论文摘要

需要多少结构信息来区分生活与非生存系统?在这里,我们表明,Delaunay Tessellations的统计特性足以区分原核生物和eukaroytic细胞包装与各种无生命的物理结构。通过引入一个数学框架,用于测量一般3D点云之间的拓扑距离,我们构建了一个通用拓扑图集,包括细菌生物膜,雪花酵母,植物芽,斑马鱼脑物质,类器官,胚胎和胚胎组织,以及泡沫,泡沫,胶合包装,玻璃材料,玻璃材料,玻璃材料和Stellar构型。发现生活系统本地化在一个界面状的区域内,这反映出生长记忆本质上将多细胞与物理包装区分开。通过检测细微的拓扑差异,基本的度量框架可以使3D无序培养基的统一分类,从微生物种群,器官和组织到无定形材料和天体物理系统。

How much structural information is needed to distinguish living from non-living systems? Here, we show that the statistical properties of Delaunay tessellations suffice to differentiate prokaryotic and eukaroytic cell packings from a wide variety of inanimate physical structures. By introducing a mathematical framework for measuring topological distances between general 3D point clouds, we construct a universal topological atlas encompassing bacterial biofilms, snowflake yeast, plant shoots, zebrafish brain matter, organoids, and embryonic tissues as well as foams, colloidal packings, glassy materials, and stellar configurations. Living systems are found to localize within a bounded island-like region, reflecting that growth memory essentially distinguishes multicellular from physical packings. By detecting subtle topological differences, the underlying metric framework enables a unifying classification of 3D disordered media, from microbial populations, organoids and tissues to amorphous materials and astrophysical systems.

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