"The last few years have seen a growing interest for computational cell mechanics. This field encompasses different scales ranging from individual monomers, cytoskeleton constituents, up to the full cell. Its focus, fueled by the development of interdisciplinary collaborative efforts between engineering, computer science and biology, until recently relatively isolated, has allowed for important breakthroughs in biomedicine, bioengineering or even neurology. However, the natural “knowledge barrier” between fields often leads to the use of one numerical tool for one bioengineering application with a limited understanding of either the tool or the field of application itself. Few groups, to date, have the knowledge and expertise to properly avoid both pits. Within the computational mechanics realm, new methods aim at bridging scale and modeling techniques ranging from density functional theory up to continuum modeling on very large scale parallel supercomputers. To the best of the knowledge of the author, a thorough and comprehensive research campaign aiming at bridging scales from proteins to the cell level while including its interaction with its surrounding media/stimulus is yet to be done. Among all cells, neurons are at the heart of tremendous medical challenges (TBI, Alzheimer, etc.). In nearly all of these challenges, the intrinsic coupling between mechanical and chemical mechanisms in neuron is of drastic relevance. I thus propose here the development of a neuron model constituted of length-scale dedicated numerical techniques, adequately bridged together. As an illustration of its usability, the model will be used for two specific applications: neurite growth and electrical-chemical-mechanical coupling in neurons. This multiscale computational framework will ultimately be made available to the bio- medical community to enhance their knowledge on neuron deformation, growth, electrosignaling and thus, Alzheimer’s disease, cancer or TBI."
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