The Late Effects of Radiation Therapy on Skeletal Muscle Morphology and Progenitor Cell Content are Influenced by Diet-Induced Obesity and Exercise Training in Male Mice
Bibliographic record
Abstract
Radiation exposure during muscle development induces long-term decrements to skeletal muscle health, which contribute to reduced quality of life in childhood cancer survivors. Whether the effects of radiation on skeletal muscle are influenced by relevant physiological factors, such as obesity and exercise training remains unknown. Using skeletal muscle from our previously published work examining the effects of obesity and exercise training on radiation-exposed bone marrow, we evaluated the influence of these physiological host factors on irradiated skeletal muscle morphology and cellular dynamics. Mice were divided into control and high fat diet groups with or without exercise training. All mice were then exposed to radiation and continued in their intervention group for an additional 4 weeks. Diet-induced obesity resulted in increased muscle fibrosis, while obesity and exercise training both increased muscle adiposity. Exercise training enhanced myofibre cross-sectional area and the number of satellite cells committed to the myogenic lineage. High fat groups demonstrated an increase in p-NFĸB expression, a trend for a decline in IL-6, and increase in TGFB1. These findings suggest exercise training improves muscle morphology and satellite cell dynamics compared to diet-induced obesity in irradiated muscle, and have implications for exercise interventions in cancer survivors.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".