Structure and Motion Lab, Comparative Biomedical Sciences, Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, AL9 7TA, U.K.
Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, The William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX, U.K.
Biol Rev Camb Philos Soc. 2022 Aug;97(4):1640-1676. doi: 10.1111/brv.12856. Epub 2022 Apr 7.
The size and arrangement of fibres play a determinate role in the kinetic and energetic performance of muscles. Extrapolations between fibre architecture and performance underpin our understanding of how muscles function and how they are adapted to power specific motions within and across species. Here we provide a synopsis of how this 'fibre to function' paradigm has been applied to understand muscle design, performance and adaptation in animals. Our review highlights the widespread application of the fibre to function paradigm across a diverse breadth of biological disciplines but also reveals a potential and highly prevalent limitation running through past studies. Specifically, we find that quantification of muscle architectural properties is almost universally based on an extremely small number of fibre measurements. Despite the volume of research into muscle properties, across a diverse breadth of research disciplines, the fundamental assumption that a small proportion of fibre measurements can accurately represent the architectural properties of a muscle has never been quantitatively tested. Subsequently, we use a combination of medical imaging, statistical analysis, and physics-based computer simulation to address this issue for the first time. By combining diffusion tensor imaging (DTI) and deterministic fibre tractography we generated a large number of fibre measurements (>3000) rapidly for individual human lower limb muscles. Through statistical subsampling simulations of these measurements, we demonstrate that analysing a small number of fibres (n < 25) typically used in previous studies may lead to extremely large errors in the characterisation of overall muscle architectural properties such as mean fibre length and physiological cross-sectional area. Through dynamic musculoskeletal simulations of human walking and jumping, we demonstrate that recovered errors in fibre architecture characterisation have significant implications for quantitative predictions of in-vivo dynamics and muscle fibre function within a species. Furthermore, by applying data-subsampling simulations to comparisons of muscle function in humans and chimpanzees, we demonstrate that error magnitudes significantly impact both qualitative and quantitative assessment of muscle specialisation, potentially generating highly erroneous conclusions about the absolute and relative adaption of muscles across species and evolutionary transitions. Our findings have profound implications for how a broad diversity of research fields quantify muscle architecture and interpret muscle function.
纤维的大小和排列在肌肉的动力学和能量性能中起着决定性的作用。纤维结构与性能之间的推断是我们理解肌肉功能以及肌肉如何适应特定物种内和跨物种的运动的基础。在这里,我们概述了这一“从纤维到功能”的范例如何应用于理解动物肌肉的设计、性能和适应。我们的综述强调了这一范例在广泛的生物学学科中的广泛应用,但也揭示了过去研究中存在的一个潜在且普遍存在的局限性。具体来说,我们发现肌肉结构特性的量化几乎完全基于非常少量的纤维测量。尽管有大量的肌肉特性研究,涉及广泛的研究领域,但一个小比例的纤维测量可以准确代表肌肉结构特性的基本假设从未经过定量测试。随后,我们首次使用医学成像、统计分析和基于物理的计算机模拟来解决这个问题。通过结合弥散张量成像(DTI)和确定性纤维追踪,我们快速生成了大量个体人类下肢肌肉的纤维测量值(>3000 个)。通过对这些测量值进行统计抽样模拟,我们证明了分析少量纤维(n < 25)通常用于之前的研究可能会导致对整体肌肉结构特性的描述,如平均纤维长度和生理横截面积,产生极大的误差。通过对人类行走和跳跃的动态肌肉骨骼模拟,我们证明了在纤维结构特征的恢复误差对物种内活体动力学和肌肉纤维功能的定量预测有重大影响。此外,通过将数据抽样模拟应用于人类和黑猩猩肌肉功能的比较,我们证明了误差幅度对肌肉专业化的定性和定量评估都有重大影响,可能会对肌肉在物种之间和进化过渡中的绝对和相对适应产生高度错误的结论。我们的发现对广泛的研究领域如何量化肌肉结构以及解释肌肉功能具有深远的意义。