New mathematical models can predict optimal exercise regimes for building muscle

Researchers have developed a mathematical model that can predict the optimal motor regime for building muscle.

Researchers at the University of Cambridge built the model using theoretical biophysical methods. This tells you how much muscle grows with a particular amount of exercise and how long it takes. This model may form the basis of a software product that allows the user to optimize the exercise regime by entering some details of individual physiology.

This model is based on a previous study by the same team who discovered that a muscle component called titin is involved in the generation of chemical signals that affect muscle growth.

Result is, Biophysical Journal, Suggests that you have the optimal weight to do strength training for each person and each muscle growth target. Muscles can approach maximum load for a very short period of time, and it is the integrated load over time that activates cellular signaling pathways that lead to the synthesis of new muscle proteins. However, below a certain value, the load is not enough to generate many signals, and the exercise time needs to increase exponentially to compensate for it. The value of this critical load may depend on the particular physiology of the individual.

We all know that exercise builds muscle. Or are we? “Surprisingly, little is known about why or how exercise builds muscle. There is a lot of case knowledge and wisdom learned, but there are solid and proven data methods. Almost none. “

Professor Eugene Terenchev of the Cavendish Laboratory in Cambridge, one of the authors of the treatise.

When exercising, the higher the load, the more repetitions or the more often, the larger the muscle size. But looking at the whole muscle, we don’t know why and how much it happens. Answering both questions becomes even more difficult as the focus goes down to a single muscle or its individual fibers.

Muscles are made up of individual filaments, only 2 micrometers long and less than 1 micrometer wide, smaller than the size of muscle cells.

For this reason, part of the description of muscle growth must be on the molecular scale. The interactions between the major structural molecules of muscle were only spliced ​​together about 50 years ago. It is not yet completely clear how the smaller, accessory proteins fit in the image. “

Neil Ibata, co-author

This is because it is very difficult to get the data. Humans have very different physiology and behavior, and it is almost impossible to carry out controlled experiments on changes in actual human muscle size. “Muscle cells can be extracted and examined individually, but other issues such as oxygen and glucose levels during exercise are ignored,” Terentjev said. “It’s very difficult to see everything together.”

Terentjev and his colleagues began to look at the mechanism of mechanical perception a few years ago, the ability of cells to perceive mechanical cues in the environment. This study was noted by the English Institute of Sport, which was interested in whether it was related to their observations in muscle rehabilitation. Together, they found that muscular atrophy / atrophy was directly related to Cambridge work.

In 2018, Cambridge researchers launched a project on how muscle filament proteins are transformed by force. They found that the major muscle components, actin and myosin, lacked binding sites for signaling molecules. Therefore, it had to be titin, the third most abundant muscle component, involved in signaling changes in the applied force.

Whenever a part of a molecule is under tension for long enough, it switches to another state, exposing previously hidden areas. If this region can bind to a small molecule involved in cell signaling, it activates that molecule and produces a chemical signaling chain. Titin is a huge protein, most of which is stretched when the muscle is stretched, but a small portion of the molecule is also tensioned during muscle contraction. This part of titin contains the so-called titin kinase domain, which produces chemical signals that affect muscle growth.

Molecules are more likely to open when more force is applied, or when the same force is held longer. Both conditions increase the number of activated signaling molecules. These molecules then induce the synthesis of more messenger RNA, leading to the production of new muscle proteins and increasing the cross-sectional area of ​​muscle cells.

This awareness led to the current work initiated by the avid athlete Ibata. “I was excited to better understand both the reasons and methods of muscle growth,” he said. “Avoiding unproductive athletic regimes and considering the specific amount an athlete can achieve, maximizing the athlete’s potential with regular high-value sessions can save a lot of time and resources. . “

Terentjev and Ibata set out to shrink a mathematical model that can quantitatively predict muscle growth. They started with a simple model that tracks titin molecules that open under force and initiates a signaling cascade. They used microscopic data to determine the force-dependent probability that the titin kinase unit would open and close under force and activate signaling molecules.

We then made the model more complex by including additional information such as metabolic energy exchange, repeat length, and recovery. The model was validated using past long-term studies on muscle hypertrophy.

“Our model provides a physiological basis for the idea that strength training occurs primarily at 70% of maximum load. This is the idea behind strength training,” Terentjev said. .. “Below below, the release rate of titin kinase drops sharply, preventing mechanistic signaling. Above that, rapid depletion hinders the good results that our model quantitatively predicted. increase.”

Fion McPartlin, Senior Strength and Conditioning Coach, English Institute of Sport, said: “This task provides more insight into the potential mechanisms of how muscles sense and respond to loads, and more specifically design interventions to achieve these goals. Useful for. “

This model also addresses the problem of muscle atrophy that occurs in astronauts at long-term rest or under microgravity, how long they can be inactive before muscles begin to deteriorate, and the optimal recovery regime. Indicates.

Ultimately, researchers want to create user-friendly software-based applications that can give individual exercise regimes for specific goals. Because many motor studies are heavily biased towards male athletes, researchers also want to improve the model by extending the analysis with detailed data for both men and women.