Effects of Low-Intensity and Long-Term Aerobic Exercise on the Psoas Muscle of mdx Mice: An Experimental Model of Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a muscle disease characterized by the absence of the protein dystrophin, which causes a loss of sarcolemma integrity, determining recurrent muscle injuries, decrease in muscle function, and progressive degeneration. Currently, there is a need for therapeutic treatments to improve the quality of life of DMD patients. Here, we investigated the effects of a low-intensity aerobic training (37 sessions) on satellite cells, peroxisome proliferator-activated receptor-gamma coactivator (PGC)-1α protein (PGC-1α), and different types of fibers of the psoas muscle from mdx mice (DMD experimental model). Wildtype and mdx mice were randomly divided into sedentary and trained groups (n = 24). Trained animals were subjected to 37 sessions of low-intensity running on a motorized treadmill. Subsequently, the psoas muscle was excised and analyzed by immunofluorescence for dystrophin, satellite cells, myosin heavy chain (MHC), and PGC-1α content. The minimal Feret’s diameters of the fibers were measured, and light microscopy was applied to observe general morphological features of the muscles. The training (37 sessions) improved morphological features in muscles from mdx mice and caused an increase in the number of quiescent/activated satellite cells. It also increased the content of PGC-1α in the mdx group. We concluded that low-intensity aerobic exercise (37 sessions) was able to reverse deleterious changes determined by DMD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".