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Nonlinear Time Series Analysis of Nodulation Factor Induced Calcium Oscillations: Evidence for Deterministic Chaos?

机译:结瘤因子引起的钙振荡的非线性时间序列分析:确定性混沌的证据?

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摘要

Legume plants form beneficial symbiotic interactions with nitrogen fixing bacteria (called rhizobia), with the rhizobia being accommodated in unique structures on the roots of the host plant. The legume/rhizobial symbiosis is responsible for a significant proportion of the global biologically available nitrogen. The initiation of this symbiosis is governed by a characteristic calcium oscillation within the plant root hair cells and this signal is activated by the rhizobia. Recent analyses on calcium time series data have suggested that stochastic effects have a large role to play in defining the nature of the oscillations. The use of multiple nonlinear time series techniques, however, suggests an alternative interpretation, namely deterministic chaos. We provide an extensive, nonlinear time series analysis on the nature of this calcium oscillation response. We build up evidence through a series of techniques that test for determinism, quantify linear and nonlinear components, and measure the local divergence of the system. Chaos is common in nature and it seems plausible that properties of chaotic dynamics might be exploited by biological systems to control processes within the cell. Systems possessing chaotic control mechanisms are more robust in the sense that the enhanced flexibility allows more rapid response to environmental changes with less energetic costs. The desired behaviour could be most efficiently targeted in this manner, supporting some intriguing speculations about nonlinear mechanisms in biological signaling.
机译:豆科植物与固氮细菌(称为根瘤菌)形成有益的共生相互作用,根瘤菌被容纳在宿主植物根部的独特结构中。豆科植物/根瘤菌共生是全球生物可利用氮的很大一部分。这种共生的开始受植物根毛细胞内钙的特征性振荡的控制,该信号被根瘤菌激活。最近对钙时间序列数据的分析表明,随机效应在确定振荡的性质方面起着很大的作用。但是,使用多种非线性时间序列技术提出了另一种解释,即确定性混沌。我们对这种钙振荡反应的性质进行了广泛的非线性时间序列分析。我们通过一系列测试确定性,量化线性和非线性分量以及测量系统局部差异的技术来建立证据。混沌在自然界中很常见,似乎混沌的动力学特性可能会被生物系统利用来控制细胞内的过程。具有混沌控制机制的系统在增强的灵活性允许以更少的能量成本更快速地响应环境变化的意义上更强大。以这种方式可以最有效地针对所需行为,从而支持一些有关生物信号中非线性机制的有趣推测。

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