Developing an Enhanced Computational Framework for Simulating Myocyte Membrane Mechanics: Catch-Bond Dynamics and Algorithmic Optimization

Abstract

The loading and mechanical deformation of myocytes provide important information about muscular deficits, particularly Duchenne Muscular Dystrophy (DMD). Although current computational models generally treat the interaction of the cell membranes and cytoskeletons as a slip bond, they do not accurately simulate the dynamic properties of catch bonds in a physiological setting. This paper describes an upgraded computational method for simulating the mechanical response of myocytes by implementing an upgraded two-state catch bond model that is capable of representing multiple dynamic velocity profiles when simulating cell responses to loading conditions. Additionally, a variance-preserving prefix-sum algorithm has been created to represent the non-homogeneous Poisson process in a more efficient manner. The development of this algorithm decreased the level of computational complexity from  to , thus enabling larger-scale simulations. As part of the validation process, the developed method was implemented on cells undergoing deformation through four biological states: normal (healthy cells), stiffened (abnormal), aged (senescent), and diseased (DMD), yielding results consistent with established theories of biomechanics and mechanobiology.