Lintilhac Philip M
Department of Plant Biology, The University of Vermont, Burlington, VT, United States.
Front Plant Sci. 2022 Oct 19;13:999304. doi: 10.3389/fpls.2022.999304. eCollection 2022.
Understanding plant development is in part a theoretical endeavor that can only succeed if it is based upon a correctly contrived axiomatic framework. Here I revisit some of the basic assumptions that frame our understanding of plant development and suggest that we consider an alternative informational ecosystem that more faithfully reflects the physical and architectural realities of plant tissue and organ growth. I discuss molecular signaling as a stochastic process and propose that the iterative and architectural nature of plant growth is more usefully represented by deterministic models based upon structural, surficial, and stress-mechanical information networks that come into play at the trans-cellular level.
理解植物发育在一定程度上是一项理论工作，只有基于正确构建的公理框架才能取得成功。在此，我重新审视一些构成我们对植物发育理解的基本假设，并建议我们考虑一种替代性的信息生态系统，它能更忠实地反映植物组织和器官生长的物理及结构现实。我将分子信号传导视为一个随机过程进行讨论，并提出基于在跨细胞水平发挥作用的结构、表面和应力 - 力学信息网络的确定性模型，能更有效地体现植物生长的迭代性和结构性本质。
