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引用次数: 0
摘要
单粒子追踪(SPT)实验中的分子运动表明,扩散在信号传递、细胞组织、运输机制等许多生物过程中都起着至关重要的作用。SPT 分析不仅能检测到经典的布朗运动,还能检测到具有其他特征的扩散。这些特征包括定向扩散和封闭运动。由于多种原因,这种行为仍然是一个具有挑战性的问题。由于许多物理过程的作用,细胞分子的随机轨迹被分割成不同的扩散模式。对它们的研究通常需要复杂的统计特性分析算法。在本文中,我们考虑对活细胞中的 G 蛋白和耦合受体的轨迹进行分段分析。它们的运动通常是瞬时的,并在自由扩散、封闭扩散、定向扩散和不动之间切换。此外,受限段可能具有高斯和非高斯统计量。本文分析了 G 蛋白和耦合受体轨迹上的扩散模式交替类型。
Transient motion classification and segment analysis of diffusive trajectories of G proteins and coupled-receptors in a living cell
The molecular movement in single particle tracking (SPT) experiments shows a crucial role of diffusion in many biological processes such as signaling, cellular organization, transport mechanisms, and more. The SPT analysis detects not only classical Brownian motion but diffusion with other features. These include directed diffusion and confined motion. The behavior remains a challenging problem for several reasons. Due to the action of many physical processes, random trajectories of cellular molecules are segmented in different diffusive modes. Often their study requires sophisticated algorithms for the analysis of statistical properties. In this paper we consider the segment analysis for trajectories of G proteins and coupled-receptors in living cells. Their movement is often transient and switches among free diffusion, confined diffusion, directed diffusion, and immobility. Moreover, the confined segments can have both Gaussian and non-Gaussian statistics. The types of alternation of diffusive modes along the trajectories of G proteins and coupled-receptors are analyzed.