%0 Online Multimedia %A W. Henkel, Andreas %A Al-Abdullah, Lulwa A. A. D. %A Al-Qallaf, Mohammed S. %A Redzic, Zoran B. %D 2019 %T Video_3_Quantitative Determination of Cellular-and Neurite Motility Speed in Dense Cell Cultures.MP4 %U https://frontiersin.figshare.com/articles/media/Video_3_Quantitative_Determination_of_Cellular-and_Neurite_Motility_Speed_in_Dense_Cell_Cultures_MP4/7829648 %R 10.3389/fninf.2019.00015.s004 %2 https://frontiersin.figshare.com/ndownloader/files/14566469 %K cell motility %K velocity measurement %K image analysis %K membrane contraction %K pericytes %K hippocampal neurons %X

Mobility quantification of single cells and cellular processes in dense cultures is a challenge, because single cell tracking is impossible. We developed a software for cell structure segmentation and implemented 2 algorithms to measure motility speed. Complex algorithms were tested to separate cells and cellular components, an important prerequisite for the acquisition of meaningful motility data. Plasma membrane segmentation was performed to measure membrane contraction dynamics and organelle trafficking. The discriminative performance and sensitivity of the algorithms were tested on different cell types and calibrated on computer-simulated cells to obtain absolute values for cellular velocity. Both motility algorithms had advantages in different experimental setups, depending on the complexity of the cellular movement. The correlation algorithm (COPRAMove) performed best under most tested conditions and appeared less sensitive to variable cell densities, brightness and focus changes than the differentiation algorithm (DiffMove). In summary, our software can be used successfully to analyze and quantify cellular and subcellular movements in dense cell cultures.

%I Frontiers