A Simplified Model of Skeletal Muscle Contraction Dynamics

IF 4.033 Q4 Biochemistry, Genetics and Molecular Biology
I. D. Bekerov, A. V. Vlakhova, P. A. Kruchinin
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引用次数: 0

Abstract

The skeletal muscle contraction model as a complex of active motor units (sarcomeres) is discussed. The sarcomere model takes the fact into account that forces are generated by myosin bridges interacting with actin filaments in muscle myofibrils. The input of the model is the rate of calcium ion influx into muscle cells, which is assumed to be proportional to the motor neuron potential. The description of the muscle force as a whole uses averaging over an ensemble of motor units. The parameters of the model are adapted to describe contraction of a skeletal muscle sacromere. The transition from contraction of a single sarcomere to slow contraction of the whole muscle is constructed using motion separation methods. The model of “slow” contraction of a single muscle fiber excited by a single nerve impulse has no independent value because the characteristic time of change of the impulse potential is short. Nevertheless, for description of tetanic muscle contraction, when the change in the total action on the muscle is smooth enough, it seems acceptable to use such an approximate model. Approximate numerical estimates of the error of the constructed model for a simplified example are given.

Abstract Image

Abstract Image

一个简化的骨骼肌收缩动力学模型
骨骼肌收缩模型作为一个复杂的活动运动单元(肌节)进行了讨论。肌节模型考虑了肌球蛋白桥与肌原纤维中的肌动蛋白丝相互作用产生力的事实。模型的输入是钙离子流入肌肉细胞的速率,假设与运动神经元电位成正比。将肌肉力量作为一个整体来描述,使用对运动单元集合的平均。该模型的参数适用于描述骨骼肌骶肌的收缩。从单个肌节的收缩到整个肌肉的缓慢收缩的过渡是使用运动分离方法构建的。由于脉冲电位的特征变化时间较短,单一神经冲动刺激单个肌纤维的“慢”收缩模型没有独立的值。然而,对于强直肌收缩的描述,当对肌肉的总作用变化足够平滑时,使用这种近似模型似乎是可以接受的。对于一个简化的例子,给出了所建模型误差的近似数值估计。
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来源期刊
Biophysics
Biophysics Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
1.20
自引率
0.00%
发文量
67
期刊介绍: Biophysics is a multidisciplinary international peer reviewed journal that covers a wide scope of problems related to the main physical mechanisms of processes taking place at different organization levels in biosystems. It includes structure and dynamics of macromolecules, cells and tissues; the influence of environment; energy transformation and transfer; thermodynamics; biological motility; population dynamics and cell differentiation modeling; biomechanics and tissue rheology; nonlinear phenomena, mathematical and cybernetics modeling of complex systems; and computational biology. The journal publishes short communications devoted and review articles.
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