HeMiTo-dynamics: a characterization of mammalian prion toxicity using non-dimensionalization, linear stability and perturbation analyses
Artikel i vetenskaplig tidskrift, 2024

Prion-like proteins play crucial parts in biological processes in organisms ranging from yeast to humans. For instance, many neurodegenerative diseases are believed to be caused by the production of prion-like proteins in neural tissue. As such, understanding the dynamics of prion-like protein production is a vital step toward treating neurodegenerative disease. Mathematical models of prion-like protein dynamics show great promise as a tool for predicting disease trajectories and devising better treatment strategies for prion-related diseases. Herein, we investigate a generic model for prion-like dynamics consisting of a class of non-linear ordinary differential equations (ODEs), establishing constraints through a linear stability analysis that enforce the expected properties of mammalian prion-like toxicity. Furthermore, we identify that prion toxicity evolves through three distinct phases for which we provide analytical descriptions using perturbation analyses. Specifically, prion-toxicity is initially characterized by the healthy phase, where the dynamics are dominated by the healthy form of prions, thereafter the system enters the mixed phase, where both healthy and toxic prions interact, and lastly, the system enters the toxic phase, where toxic prions dominate, and we refer to these phases as HeMiTo-dynamics. These findings hold the potential to aid researchers in developing precise mathematical models for prion-like dynamics, enabling them to better understand underlying mechanisms and devise effective treatments for prion-related diseases.

non-dimensionalization

linear stability analysis

prions

perturbation analysis

non-linear ordinary differential equations (ODEs)

Författare

Johannes Borgqvist

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Göteborgs universitet

Christoffer Gretarsson Alexandersen

University of Oxford

Mathematical Medicine and Biology

1477-8599 (ISSN) 14778602 (eISSN)

Vol. In Press

Ämneskategorier (SSIF 2011)

Neurovetenskaper

Matematisk analys

DOI

10.1093/imammb/dqae024

PubMed

39611452

Mer information

Senast uppdaterat

2025-01-10