Understanding the mobility of T-cells "in vitro" experiments

T-cells play a critical role in preventing the proliferation of anomalous cells that may become carcinogenic. A better mathematical or biological understanding of T lymphocytes would bring us closer to curing or even preventing diseases such as cancer. This thesis focuses on analyzing real data related to T-cell movement. The living cells were placed into a micro-well and recorded using a spinning disk confocal laser microscope. The raw images were then processed with a program called DeepKymoTracker, which produces numerical data of interest. The results of the data analysis, including statistical examination and comparisons with simple model simulations, clarify key aspects of the cells' motility. However, due to insufficient and suboptimal data quality, a more comprehensive understanding of this movement is left for future work. The initial chapters provide a brief review of essential concepts in cellular biology, fluorescence microscopy, convolutional neural networks, and relevant mathematical theories from the literature. This is followed by a description of the experimental setup conducted at Swinburne University of Technology. One chapter is devoted to explaining how the DeepKymoTracker program operates. The subsequent chapters focus on the statistical analysis of the acquired data and the simulation of random walks. The final chapter outlines how the work presented in this thesis will continue in the future to deepen our understanding of cell motility.