Voiland School of Chemical Engineering and Bioengineering, Washington State University, PO Box 646515, Pullman, WA 99164, USA.
Department of Biological Sciences, University of Idaho, 875 Perimeter Drive, MS 3051, Moscow, ID 83844, USA.
J Exp Biol. 2020 Sep 18;223(Pt 18):jeb219980. doi: 10.1242/jeb.219980.
The force-velocity (-) properties of isolated muscles or muscle fibers have been well studied in humans and other animals. However, determining properties of individual muscles remains a challenge because muscles usually function within a synergistic group. Modeling has been used to estimate the properties of an individual muscle from the experimental measurement of the muscle group properties. While this approach can be valuable, the models and the associated predictions are difficult to validate. In this study, we measured the - properties of the maximally activated kangaroo rat plantarflexor group and used two different assumptions and associated models to estimate the properties of the individual plantarflexors. The first model (Mdl1) assumed that the percent contributions of individual muscles to group force and power were based upon the muscles' cross-sectional area and were constant across the different isotonic loads applied to the muscle group. The second model (Mdl2) assumed that the - properties of the fibers within each muscle were identical, but because of differences in muscle architecture, the muscles' contributions to the group properties changed with isotonic load. We compared the two model predictions with independent estimates of the muscles' contributions based upon sonomicrometry measurements of muscle length. We found that predictions from Mdl2 were not significantly different from sonomicrometry-based estimates while those from Mdl1 were significantly different. The results of this study show that incorporating appropriate fiber properties and muscle architecture is necessary to parse the individual muscles' contributions to the group - properties.
在人类和其他动物中，已经对离体肌肉或肌纤维的力-速度（-）特性进行了深入研究。然而，确定单个肌肉的特性仍然是一个挑战，因为肌肉通常在协同作用的肌肉群中发挥作用。建模已被用于根据肌肉群特性的实验测量来估计单个肌肉的特性。虽然这种方法可能很有价值，但模型和相关预测很难验证。在这项研究中，我们测量了最大激活的袋鼠后肢跖屈肌群体的-特性，并使用了两种不同的假设和相关模型来估计单个跖屈肌的特性。第一个模型（Mdl1）假设，单个肌肉对群体力和功率的贡献百分比基于肌肉的横截面积，并且在施加于肌肉群的不同等张负荷下保持不变。第二个模型（Mdl2）假设，每个肌肉内的纤维的-特性是相同的，但由于肌肉结构的差异，肌肉对群体特性的贡献随着等张负荷而变化。我们将这两种模型预测与基于超声测量的肌肉长度的肌肉贡献的独立估计进行了比较。我们发现，来自 Mdl2 的预测与基于超声测量的估计没有显著差异，而来自 Mdl1 的预测则有显著差异。这项研究的结果表明，将适当的纤维特性和肌肉结构纳入模型是解析肌肉群体-特性中单个肌肉贡献所必需的。
