Department of Theoretical Physics, Saarland University, 66123 Saarbrücken, Germany.
Center for Biophysics, Saarland University, 66123 Saarbrücken, Germany.
Phys Rev Lett. 2020 Dec 31;125(26):268102. doi: 10.1103/PhysRevLett.125.268102.
Migration of immune cells within the human body allows them to fulfill their main function of detecting pathogens. We present experimental evidence showing the optimality of the search strategy of these cells, which is of crucial importance to achieve an efficient immune response. We find that the speed and directional persistence of migrating dendritic cells in our in vitro experiments are highly correlated, which enables them to reduce their search time. We introduce theoretically a new class of random search optimization problems by minimizing the mean first-passage time (MFPT) with respect to the strength of the coupling between influential parameters. We derive an analytical expression for the MFPT in a confined geometry and verify that the correlated motion enhances the search efficiency if the mean persistence length is sufficiently shorter than the confinement size. Our correlated search optimization approach provides an efficient searching recipe and predictive power in a broad range of correlated stochastic processes.
免疫细胞在人体内的迁移使它们能够发挥其检测病原体的主要功能。我们提出了实验证据，表明这些细胞的搜索策略具有最优性，这对于实现有效的免疫反应至关重要。我们发现，在我们的体外实验中，迁移树突状细胞的速度和方向持久性高度相关，这使它们能够减少搜索时间。我们通过最小化有影响力参数之间的耦合强度来引入一个新的随机搜索优化问题的理论类别。我们导出了在受限几何中的平均首次通过时间 (MFPT) 的解析表达式，并验证了如果平均持久性长度明显短于限制尺寸，则相关运动增强了搜索效率。我们的相关搜索优化方法为广泛的相关随机过程提供了有效的搜索方案和预测能力。
