Load sharing between synergistic muscles characterized by a ligand-binding approach and elastography

Abstract

The skeletal muscle contraction is determined by cross-bridge formation between the myosin heads and the actin active sites. When the muscle contracts, it shortens, increasing its longitudinal shear elastic modulus ($${\mu }_{L}$$ μ L ). Structurally, skeletal muscle can be considered analogous to the molecular receptors that form receptor–ligand complexes and exhibit specific ligand-binding dynamics. In this context, this work aims to apply elastography and the ligand-binding framework to approach the possible intrinsic mechanisms behind muscle synergism. Based on the short-range stiffness principle and the acoustic–elasticity theory, we define the coefficient $$C$$ C , which is directly related to the fraction saturation of molecular receptors and links the relative longitudinal deformation of the muscle to its $${\mu }_{L}$$ μ L . We show that such a coefficient can be obtained directly from $${\mu }_{L}$$ μ L estimates, thus calculating it for the biceps brachii, brachioradialis, and brachialis muscles during isometric elbow flexion torque (τ) ramps. The resulting $$C\left(\tau \right)$$ C τ curves were analyzed by conventional characterization methods of receptor–ligand systems to study the dynamical behavior of each muscle. The results showed that, depending on muscle, $$C\left(\tau \right)$$ C τ exhibits typical ligand-binding dynamics during joint torque production. Therefore, the above indicates that these different behaviors describe the longitudinal shortening pattern of each muscle during load sharing. As a plausible interpretation, we suggested that this could be related to the binding kinetics of the cross-bridges during their synergistic action as torque increases. Likewise, it shows that elastography could be useful to assess contractile processes at different scales related to the change in the mechanical properties of skeletal muscle.

Model-Based Estimation of Active and Passive Muscle Forces Using MRE in Forearm Muscles During 2-DOF Wrist Tasks

“…With the proposed estimator, κ is estimated for all muscles resulting in a lower estimation error. Previous studies have shown accuracy in using rest contractions to estimate the passive muscle force components [12], [17]. The original estimator yields a higher R 2 value than the proposed estimator.…”