News Release

Scientists show a promising way to reliably assess muscle damage after exercise

Scientists explore potential predictors for the symptoms of exercise-induced muscle damage in knee muscles

Peer-Reviewed Publication

Shibaura Institute of Technology

The recovery of the maximal voluntary isometric contraction (MVIC) torque reveals two distinct groups of people

image: Muscle damage, if left untreated, can lead to physical disabilities. A reliable predictor of muscle damage symtoms is, therefore, necessary. Researchers from SIT, Japan, have now identified changes in MVIC torque after exercise as a suitable indicator of just that. view more 

Credit: Ryota Akagi from Shibaura Institute of Technology (SIT)

Most of us have experienced some form of muscle damage caused by exercise. The three most common symptoms are a long-lasting reduction in physical performance, an increase in muscle stiffness, and muscular soreness that sets in within one to three days after the damage. In the best-case scenario, the symptoms subside on their own after a while and one continues to lead a normal life. In the worst-case scenario, however, the symptoms can lead to physical disabilities if left untreated.

Considering such potentially extreme consequences, a reliable way to predict the associated symptoms as soon as people finish exercising is necessary. While changes in muscle strength are a good indicator of muscle damage, they can also reflect other variables, such as neuromuscular fatigue. Thus, we need to find an alternative way to effectively assess muscle damage and its symptoms.

In a recent study published in Frontiers in Physiology, a team of researchers comprising Dr. Ryota Akagi, Mikio Shoji, M.Sc., and Akihiro Kanda, M.Sc., from Shibaura Institute of Technology (SIT), Japan, Dr. Ryoichi Ema from Shizuoka Sangyo University, Japan, Dr. Kazunori Nosaka from Edith Cowan University, Australia, and Dr. Kosuke Hirata from Waseda University, Japan, investigated a promising approach to predicting muscle damage symptoms in the knee extensor muscles following eccentric exercise. Using an isokinetic dynamometer, a device that can precisely control the speed of an exercise by resisting the forces applied by the user, they had 28 young men perform multiple sets of “maximal voluntary isometric contractions (MVICs)” of the right knee extensors. The participants tried to resist the movement of the dynamometer as hard as they could during each repetition, which caused muscle damage within a safe limit.

Before and multiple times after the exercise, the researchers measured certain variables to determine a good predictor of muscle damage. The study primarily focused on the changes in MVIC torque over the course of three days post-exercise, measured using the isokinetic dynamometer. Other variables examined included muscle shear modulus (a measure of muscle stiffness determined through ultrasound shear-wave elastography) and the “potentiated doublet torque” produced when externally stimulating the nerves that control the knee extensors. This torque measurement allowed them to quantify the voluntary activation of the knee muscles. In turn, these data were used to investigate whether neuromuscular effects or fatigue, rather than raw muscle damage, was the culprit of any changes in the experimental results.

Unlike a similar previous study conducted on the elbow flexors, the researchers found that the participants could be categorized into two distinct groups based on how their MVIC torque had recovered one day post-exercise compared to immediately after the exercise. They observed marked differences in some of the other variables measured between both groups, hinting at the possibility of using change in the MVIC torque as a measure of muscle damage.

We found that the recovery rate of the MVIC torque can be used for the prediction of exercise-induced changes in maximum voluntary strength and evoked strength,” explain Dr. Akagi and Dr. Ema (who was a postdoctoral researcher at Dr. Akagi’s laboratory at SIT from 2015 to 2018). “However, it could not be used to predict the extent of delayed-onset muscle soreness and changes in muscle stiffness,” they add.

Despite its limitations, MVIC torque changes could be leveraged as useful predictors for the symptoms (and thus the extent) of muscle damage after exercise. “The next step in our work will be to establish the best predictor for the magnitude of muscle damage, which should be very beneficial for anyone who enjoys sports or physical exercise,” comment Dr. Ema and Dr. Akagi.

They believe that these findings could ultimately help future scientists find countermeasures against muscle damage. Needless to say, this would lead to a happier and healthier world in which more people could enjoy their favorite physical activities. Let us hope this vision becomes a reality soon!

 

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Reference

DOI: http://doi.org/10.3389/fphys.2021.775157

 

About Shibaura Institute of Technology (SIT), Japan

Shibaura Institute of Technology (SIT) is a private university with campuses in Tokyo and Saitama. Since the establishment of its predecessor, Tokyo Higher School of Industry and Commerce, in 1927, it has maintained “learning through practice” as its philosophy in the education of engineers. SIT was the only private science and engineering university selected for the Top Global University Project sponsored by the Ministry of Education, Culture, Sports, Science and Technology and will receive support from the ministry for 10 years starting from the 2014 academic year. Its motto, “Nurturing engineers who learn from society and contribute to society,” reflects its mission of fostering scientists and engineers who can contribute to the sustainable growth of the world by exposing their over 8,000 students to culturally diverse environments, where they learn to cope, collaborate, and relate with fellow students from around the world.
Website: https://www.shibaura-it.ac.jp/en/

 

About Associate Professor Ryota Akagi from SIT, Japan

Ryota Akagi obtained a Bachelor of Engineering degree, a Master’s degree, and a PhD from Waseda University, Japan, in 2004, 2006, and 2009, respectively. He joined SIT in 2013 as an Assistant Professor in the Department of Life Sciences, where he currently serves as Associate Professor since 2017. His group studies the human skeletal muscles and the effects of physical exercise and aging on changes in the human skeletal muscle data using techniques such as ultrasound and dynamometry.


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