A jump-diffusion stochastic formalism for muscle contraction models at multiple timescales - Archive ouverte HAL
Journal Articles Journal of Applied Physics Year : 2023

A jump-diffusion stochastic formalism for muscle contraction models at multiple timescales

Abstract

Muscle contraction at the macro level is a physiological process that is ultimately due to the interaction between myosin and actin proteins at the micro level. The actin-myosin interaction involves slow attachment and detachment responses and a rapid temporal change in protein conformation called power-stroke. Jump-diffusion models that combine jump processes between attachment and detachment with a mechanical description of the power-stroke have been proposed in the literature. However, the current formulations of these models are not fully compatible with the principles of thermodynamics. To solve the problem of coupling continuous mechanisms with discrete chemical transitions, we rely on the mathematical formalism of Poisson random measures. First, we design an efficient stochastic formulation for existing muscle contraction PDE models. Then, we write a new jumpdiffusion model for actin-myosin interaction. This new model describes both the behavior of muscle contraction on multiple time scales and its compatibility with thermodynamic principles. Finally, following a classical calibration procedure, we demonstrate the ability of the model to reproduce experimental data characterizing muscle behavior on fast and slow time scales.
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hal-04264293 , version 1 (30-10-2023)

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Louis-Pierre Chaintron, François Kimmig, Matthieu Caruel, Philippe Moireau. A jump-diffusion stochastic formalism for muscle contraction models at multiple timescales. Journal of Applied Physics, 2023, ⟨10.1063/5.0158191⟩. ⟨hal-04264293⟩
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