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

Author:

Chaintron L.-P.1234ORCID,Kimmig F.23ORCID,Caruel M.5ORCID,Moireau P.23ORCID

Affiliation:

1. DMA, École normale supérieure, Université PSL, CNRS 1 , 75005 Paris, France

2. Inria, Team MΞDISIM, Inria Saclay 2 , 91128 Palaiseau, France

3. LMS—École polytechnique, CNRS—Institut Polytechnique de Paris 3 , 91128 Palaiseau, France

4. CERMICS, École des ponts 4 , 77420 Champs-sur-Marne, France

5. Univ Paris Est Creteil, Univ Gustave Eiffel, CNRS, UMR 8208, MSME 5 , 94010 Créteil, France

Abstract

Muscle contraction at the macrolevel is a physiological process that is ultimately due to the interaction between myosin and actin proteins at the microlevel. 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 partial differential equation models. Then, we write a new jump-diffusion 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.

Publisher

AIP Publishing

Subject

General Physics and Astronomy

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multiscale modeling and analysis in biophysics;Journal of Applied Physics;2024-06-03

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