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Automated Cell Transport in Optical Tweezers-Assisted Microfluidic Chambers

机译:镊子辅助微流腔中的自动细胞运输。

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In this paper, we present a physics-aware, planning approach for automated transport of cells in an optical tweezers-assisted microfluidic chamber. The approach can be used for making a uniform distribution of cells inside the chamber to allow the study of a variety of biological processes, including cell signaling. Fluid forces inside the chamber, modeled using computational fluid dynamics, are incorporated into the widely used Langevin equation to simulate the motion of cells. The developed simulator was used for building a map that contains probabilities of a cell successfully reaching one of the outlets of the chamber from different locations under the influence of the fluid flow. The developed planner not only generates collision-free paths that exploit the fluid flow inside the chamber but also utilizes the offline generated simulation data to decide suitable locations for releasing the cells. This ensures fast and robust cell transport, while minimizing the required laser power and operational time. The planner is based on the heuristic D* Lite algorithm that employs a specific cost function for searching over a novel state-action space representation. The effectiveness of the planning algorithm is demonstrated using both simulation and physical experiments in a microfluidics-optical tweezers hybrid manipulation setup.
机译:在本文中,我们提出了一种物理感知的计划方法,用于在镊子辅助的微流控室中自动运输细胞。该方法可用于使室内的细胞均匀分布,以便研究包括细胞信号在内的多种生物学过程。使用计算流体动力学建模的腔室内的流体力被合并到广泛使用的Langevin方程中,以模拟细胞的运动。所开发的模拟器用于构建地图,该地图包含在流体流的影响下从不同位置成功到达腔室出口之一的单元格的概率。开发的计划人员不仅生成利用腔室内流体流动的无碰撞路径,而且利用离线生成的模拟数据来确定释放细胞的合适位置。这确保了快速而稳定的细胞运输,同时将所需的激光功率和操作时间降至最低。该计划程序基于启发式D * Lite算法,该算法采用特定的成本函数来搜索新颖的状态动作空间表示形式。在微流体-光学镊子混合操纵设置中使用仿真和物理实验都证明了规划算法的有效性。

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