Abstract
Neurodegenerative diseases are frequently associated with aggregation and propagation of toxic proteins. In particular, it is well known that along with amyloid-beta, the tau protein is also driving Alzheimer’s disease. Multiscale reaction-diffusion models can assist in our better understanding of the evolution of the disease. Based on a coarse-graining procedure of the continuous model and taking advantage of the brain data connectome, a computationally challenging network mathematical model has been described where the edges of the network are the axonal bundles in white-matter tracts. Further, we have modified the heterodimer model in such a way that it can now capture some of the critical characteristics of this evolution such as the conversion time from healthy to toxic proteins. Finally, we have analyzed the modified model theoretically and validated the theoretical findings with numerical simulations.
Authors are grateful to the NSERC and the CRC Program for their support. RM is also acknowledging support of the BERC 2018–2021 program and Spanish Ministry of Science, Innovation and Universities through the Agencia Estatal de Investigacion (AEI) BCAM Severo Ochoa excellence accreditation SEV-2017-0718 and the Basque Government fund AI in BCAM EXP. 2019/00432.
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Pal, S., Melnik, R. (2021). Pathology Dynamics in Healthy-Toxic Protein Interaction and the Multiscale Analysis of Neurodegenerative Diseases. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12746. Springer, Cham. https://doi.org/10.1007/978-3-030-77977-1_42
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