标题： 考虑实验帧率和分段线性微粒轨迹的鲁棒分割分析 显示英文标题

标题： Considering experimental frame rates and robust segmentation analysis of piecewise-linear microparticle trajectories

摘要： 细胞内由分子马达运输的货物运动通常以定向运动和静止暂停之间的切换为标志。 评估运动的主要指标是有效扩散系数，它预测了粒子在长时间尺度上的均方位移。 在本工作中，我们考虑了一种替代分析方法，该方法关注较短的时间尺度，并依赖于路径的自动分割。 由于变化点分析中的固有不确定性，我们强调了对分割算法性能具有鲁棒性的统计摘要的重要性。 与平均多种行为的有效扩散系数不同，我们强调突出不同马达-货物状态的工具，旨在识别决定整体细胞运输特性的生物物理机制。 通过开发一个用于噪声、连续、分段线性微粒运动的马尔可夫链模型及相关的数学分析，我们提供了对实验者提出的一个常见问题的见解：观测帧率的选择如何影响对运输特性的推断？ 显示英文摘要

摘要： The movement of intracellular cargo transported by molecular motors is commonly marked by switches between directed motion and stationary pauses. The predominant measure for assessing movement is effective diffusivity, which predicts the mean-squared displacement of particles over long time scales. In this work, we consider an alternative analysis regime that focuses on shorter time scales and relies on automated segmentation of paths. Due to intrinsic uncertainty in changepoint analysis, we highlight the importance of statistical summaries that are robust with respect to the performance of segmentation algorithms. In contrast to effective diffusivity, which averages over multiple behaviors, we emphasize tools that highlight the different motor-cargo states, with an eye toward identifying biophysical mechanisms that determine emergent whole-cell transport properties. By developing a Markov chain model for noisy, continuous, piecewise-linear microparticle movement, and associated mathematical analysis, we provide insight into a common question posed by experimentalists: how does the choice of observational frame rate affect what is inferred about transport properties?