DEVELOPMENT OF A NOVEL SIMULATION CODE TO PREDICT THREE-DIMENSIONAL NEUROGENESIS BY USING MULTILAYERED CELLULAR AUTOMATON

摘要

In this study, a novel simulation code to predict three-dimensional (3D) neurogenesis was developed by using a multilayered cellular automaton (CA) method. Recently, the induced pluripotent stem cell therapy treatments have rapidly grown up as an attractive repair and regeneration technologies for damaged central nervous system (CNS). However, understanding the repair mechanism and developing a numerical analysis code to predict CNS neurogenesis process have ultimate difficulties because more than hundreds of billions of neurons connect each other, and it is almost impossible to analyze the neurogenesis evolution process. Especially, the axonal extension to generate the neural network system is extremely difficult. In this study, based on the phase contrast microscopy (PCM) and the multiphoton microscope (MPM) observations of two-dimensional (2D) and 3D nerve cell network generation of the pheochromocytoma cells (PC12), a novel simulation code to predict the CNS morphogenesis was developed. At first, time-lapse PCM observations have been executed to understand the nerve cell axonal extension and branching. Secondly, 3D representative volume elements (RVEs) of cortex were derived by using Nissl-stained cerebral cortex images. Finally, a 3D CA simulation code for neurogenesis was developed based on multilayered CA algorithms, such as the dendrites outgrowth, an axon selection from dendrites, the extension enhancement induced by the nerve growth factor (NGF), and the branching caused by microtubule collapse under the effect of Netrin-1. Our newly developed CA simulation code was confirmed as a comprehensive code to predict neurogenesis processes through comparison with PCM and MPM observation results.