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An unusual pattern among the scaling laws in nature is that the fastest animals are neither the largest, nor the smallest, but rather intermediately sized. Because of the enormous diversity in animal shape, the mechanisms underlying this have long been difficult to determine. To address this, we challenge predictive human musculoskeletal simulations, scaled in mass from the size of a mouse (0.1 kg) to the size of an elephant (2000 kg), to move as fast as possible. Our models replicate patterns observed across extant animals including: (i) an intermediate optimal body mass for speed; (ii) a reduction in the cost of transport with increasing size; and (iii) crouched postures at smaller body masses and upright postures at larger body masses. Finally, we use our models to determine the mechanical limitations of speed with size, showing larger animals may be limited by their ability to produce muscular force while smaller animals are likely limited by their ability to produce larger ground reaction forces. Despite their bipedal gait, our models replicate patterns observed across quadrupedal animals, suggesting these biological phenomena likely represent general rules and are not the result of phylogenetic or other ecological factors that typically hinder comparative studies.
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http://dx.doi.org/10.1038/s41467-024-52924-z | DOI Listing |
JB JS Open Access
September 2025
Department of Orthopaedic Surgery, Mass General Brigham, Harvard Medical School, Boston, Massachusetts.
Background: It is unclear whether the current North Atlantic Treaty Organization (NATO) trauma system will be effective in the setting of Large-Scale Combat Operations (LSCO). We sought to model the efficacy of the NATO trauma system in the setting of LSCO. We also intended to model novel scenarios that could better adapt the current system to LSCO.
View Article and Find Full Text PDFMed Sci Sports Exerc
September 2025
Department of Engineering Mechanics, Tsinghua University, Beijing, CHINA.
Purpose: Develop a musculoskeletal-environment interaction model to reconstruct the dynamic-interaction process in skiing.
Methods: This study established a skier-ski-snow interaction (SSSI) model that integrated a 3D full-body musculoskeletal model, a flexible ski model, a ski boot model, a ski-snow contact model, and an air resistance model. An experimental method was developed to collect kinematic and kinetic data using IMUs, GPS, and plantar pressure measurement insoles, which were cost-effective and capable of capturing motion in large-scale field conditions.
Mater Today Bio
October 2025
Department of Orthopedic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Organ-on-a-chip (OoC) systems can simulate the key functions of human organs, combining microfluidics, cell culture, and biomaterials. 3D printing can be integrated into these technologies to facilitate the construction of OoC models. The high precision and layer-by-layer fabrication process of 3D printing not only enables the creation of complex structures for the microfluidic chip but also improves the cellular microenvironment within the chip by harnessing bioinks for 3D bioprinting.
View Article and Find Full Text PDFAnn Biomed Eng
September 2025
LaBS - Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, Italy.
Understanding spine biomechanics is essential for maintaining posture under static and dynamic conditions, relying on a balance of muscular and gravitational forces. Computational musculoskeletal (MSK) models are increasingly being used in biomechanical research as non-invasive alternatives to in vivo and in vitro methods. Two main MSK modeling strategies are multibody (MB) models, which simplify the spine using rigid vertebrae and intervertebral joints to study muscle recruitment, and finite element (FE) models, which provide detailed tissue representation but often rely on oversimplified loading conditions.
View Article and Find Full Text PDFDeveloping musculoskeletal hand models requires a variety of experimental biomechanics data. However, collecting robust biomechanics hand data is a time intensive process leading to a lack of widely available datasets. To address this issue the biomechanics hand modeling database (BHaM) was made as a collection of experimental data to aid the development, testing, and validation of musculoskeletal models and simulations.
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