Altered muscle satellite cell activation following 16 wk of resistance training in young men
Bibliographic record
Abstract
Skeletal muscle satellite cells (SC) play an important role in muscle adaptation. In untrained individuals, SC content and activation status have been observed to increase in response to a single bout of exercise. Muscle fiber characteristics change considerably when resistance exercise is performed chronically, but whether training status affects the activity of SC in response to a single bout of exercise remains unknown. We examined the changes in SC content and activation status following a single bout of resistance exercise, before and following a 16-wk progressive resistance training (RT) program in 14 young (25 ± 3 yr) men. Before and after RT, percutaneous biopsies from the vastus lateralis muscle were taken before a single bout of resistance exercise and after 24 and 72 h of postexercise recovery. Muscle fiber size, capillarization, and SC response were determined by immunohistochemistry. Following RT, there was a greater activation of SC after 24 h in response to a single bout of resistance exercise (Pre, 1.4 ± 0.3; 24 h, 3.1 ± 0.3 Pax7+/MyoD+cells per 100 fibers) compared with before RT (Pre, 1.4 ± 0.3; 24 h, 2.2 ± 0.3 Pax7+/MyoD+cells per 100 fibers, P < 0.05); no difference was observed 72 h postexercise. Following 16 wk of RT, MyoD mRNA expression increased from basal to 24 h after the single bout of exercise ( P < 0.05); this change was not observed before training. Individual capillary-to-fiber ratio (C/F i) increased in both type I (1.8 ± 0.3 to 2.0 ± 0.3 C/F i, P < 0.05) and type II (1.7 ± 0.3 to 2.2 ± 0.3 C/F i, P < 0.05) fibers in response to RT. After RT, enhanced activation of SC in response to resistance exercise is accompanied by increases in muscle fiber capillarization.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".