A mathematical model to predict network growth in Physarum polycephalum as a function of extracellular matrix viscosity, measured by a novel viscometer

利用新型粘度计测量细胞外基质粘度,建立预测多头绒泡菌网络生长与细胞外基质粘度关系的数学模型

阅读:1

Abstract

Physarum polycephalum is a slime mould that forms complex networks, making it an ideal model organism for studying network formation and adaptation. We introduce a novel viscometer capable of accurately measuring extracellular slime matrix (ECM) viscosity in small biological samples, overcoming the limitations of conventional instruments. Using this device, we measured the relative kinematic viscosity and developed continuous models to predict network size over time as a function of ECM viscosity. Our results show that increased ECM viscosity, driven by higher salt (MgCl(2)·6H(2)O) concentrations, significantly slows network expansion but does not affect the final network complexity. Fractal dimension analysis revealed that network complexity converged to a similar value across all viscosity conditions during the equilibrium state. The models demonstrated strong predictive power, with a mean squared error below 0.4%, closely aligning with experimental data. These findings highlight the critical role of ECM viscosity in influencing network expansion while demonstrating that complexity remains stable across varying conditions. This study advances our understanding of the physical parameters shaping P. polycephalum networks and provides a foundation for exploring network dynamics in other adaptive systems. These insights offer new tools for research in biological systems where sample material is limited.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。