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无记忆化学趋向性与离散线索。

Memoryless chemotaxis with discrete cues.

机构信息

Department of Mathematics, Imperial College London, South Kensington, London SW7 2BZ, UK.

Department of Chemical Engineering and Biotechnology, University of Cambridge, Philippa Fawcett Drive, Cambridge CB3 0AS, UK.

出版信息

J R Soc Interface. 2024 Jul;21(216):20240100. doi: 10.1098/rsif.2024.0100. Epub 2024 Jul 31.

Abstract

Biological systems such as axonal growth cones perform chemotaxis at micrometre-level length scales, where chemotactic molecules are sparse. Such systems lie outside the range of validity of existing models, which assume smoothly varying chemical gradients. We investigate the effect of introducing chemoattractant molecules by constructing a minimal dynamical model consisting of a chemotactic cell without internal memory. Significant differences are found in the behaviour of the cell as the chemical gradient is changed from smoothly varying to discrete, including the emergence of a homing radius beyond which chemotaxis is not reliably performed.

摘要

生物系统,如轴突生长锥,在微米级长度尺度上进行趋化运动,而趋化分子则很稀疏。这些系统超出了现有模型的有效性范围,因为这些模型假设化学梯度是平滑变化的。我们通过构建一个没有内部记忆的趋化细胞的最小动力模型,来研究引入趋化分子的效果。当化学梯度从平滑变化变为离散变化时,细胞的行为会发生显著差异,包括出现一个归巢半径,超出该半径后,趋化运动就不再可靠。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/643e/11289677/2d42cbd5bb2b/rsif.2024.0100.f001.jpg

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