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JNK activation in TA and EDL muscle is load-dependent in rats receiving identical excitation patterns.

ABSTRACT: As the excitation-contraction coupling is inseparable during voluntary exercise, the relative contribution of the mechanical and neural input on hypertrophy-related molecular signalling is still poorly understood. Herein, we use a rat in-vivo strength exercise model with an electrically-induced standardized excitation pattern, previously shown to induce a load-dependent increase in myonuclear number and hypertrophy, to study acute effects of load on molecular signalling. We assessed protein abundance and specific phosphorylation of the four protein kinases FAK, mTOR, p70S6K and JNK after 2, 10 and 28 min of a low- or high-load contraction, in order to assess the effects of load, exercise duration and muscle-type on their response to exercise. Specific phosphorylation of mTOR, p70S6K and JNK was increased after 28 min of exercise under the low- and high-load protocol. Elevated phosphorylation of mTOR and JNK was detectable already after 2 and 10 min of exercise, respectively, but greatest after 28 min of exercise, and JNK phosphorylation was highly load-dependent. The abundance of all four kinases was higher in TA compared to EDL muscle, p70S6K abundance was increased after exercise in a load-independent manner, and FAK and JNK abundance was reduced after 28 min of exercise in both the exercised and control muscles. In conclusion, the current study shows that JNK activation after a single resistance exercise is load-specific, resembling the previously reported degree of myonuclear accrual and muscle hypertrophy with repetition of the exercise stimulus.

SUBMITTER: Eftestol E

PROVIDER: S-EPMC8361015 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Fiber type composition, organization, and distribution are key elements in muscle functioning. These properties can be modified by intrinsic and/or extrinsic factors, such as undernutrition and injuries. Currently, there is no methodology to quantitatively analyze such modifications. On one hand, we propose a fractal approach to determine fiber type organization, using the fractal correlation method in software Fractalyse. On the other hand, we applied the kernel methodology from machine learning to build radial-basis functions for the spatial distribution of fibers (distribution functions), by dividing into square cells a two-dimensional binary image for the spatial distribution of fibers from a muscle fascicle and mounting on each cell a radial-basis function in such a way that the sum of all cell functions creates a smooth version of the fiber histogram on the cell grid. The distribution functions thus created belong in a reproducing kernel Hilbert space which permits us to regard them as vectors and measure distances and angles between them. In the present study, we analyze fiber type organization and distribution in fascicles (F2, F3, F4, and F5) of the extensor digitorum longus muscle (EDLm) from control and undernourished male rats. Fibers were classified according to the ATPase activity in slow, intermediate, and fast. Then, (x, y) coordinates of fibers were used to build binary images and distribution functions for each fiber type and both conditions. The fractal organization analysis showed that fast and intermediate fibers, from both groups, had a fractal organization within the four fascicles, i.e., the fiber assembly is distributed in clusters. We also show that chronic undernutrition altered the organization of fast fibers in the F3, although it still is considered a fractal organization. Distribution function analysis showed that each fiber type (slow, intermediate, and fast) has a unique distribution within the fascicles, in both conditions. However, chronic undernutrition modified the intra-fascicular fiber type distributions, except in the F2. Altogether, these results showed that the methodology herein proposed allows for analyzing fiber type organization and distribution modifications. On the other side, we show that chronic undernutrition alters not only the fiber type composition but also the organization and distribution, which could affect the muscle functioning, and ultimately, its behavior (e.g., locomotion).

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JNK activation in TA and EDL muscle is load-dependent in rats receiving identical excitation patterns.

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