Presentation Information
[11a-PA1-3]Quantitative Analysis of Fibroblast Collective Motion and Ordering in Microgrooves
〇Mizuki Yoshida1, Kazuhiro Aoki1, Keisuke Imamura1, Yuuta Moriyama1, Toshiyuki Mitsui1 (1.Aogaku Univ.)
Keywords:
fibroblasts,biophysics,machine learning
Fibroblasts, which play essential roles in tissue morphogenesis, are known to establish orientational order within groove-like microenvironments. In this study, we employed PDMS-based microgroove structures and performed time-lapse imaging to investigate the emergence of cellular alignment during cell invasion into the grooves. Cell behaviors were quantitatively analyzed using a convolutional neural network (CNN)-based machine learning approach. We found that the orientations of leading cells were highly dispersed, whereas cells located behind the leading front exhibited preferential alignment along the groove axis. In this presentation, we report the collective dynamics of fibroblast populations and discuss the role of cell density in the development of orientational order.