Myofibre Hypertrophy in the Absence of Changes to Satellite Cell Content Following Concurrent Exercise Training in Young Healthy Men
Bibliographic record
Abstract
Concurrent exercise training has been suggested to create an ‘interference effect,’ attenuating resistance training-based skeletal muscle adaptations, including myofibre hypertrophy. Satellite cells support myofibre hypertrophy and are influenced by exercise mode. To determine whether satellite cells contribute to the ‘interference effect’ changes in satellite cell and myonuclear content were assessed following a period of training in 32 recreationally active males (age: 25 ± 5 year; body mass index: 24 ± 3 kg⋅m–2; mean ± SD) who undertook 12-week of either isolated (3 d⋅w–1) resistance (RES; n = 10), endurance (END; n = 10), or alternate day (6 d⋅w–1) concurrent (CET, n = 12) training. Skeletal muscle biopsies were obtained pre-intervention and after 2, 8, and 12 weeks of training to determine fibre type-specific cross-sectional area (CSA), satellite cell content (Pax7+DAPI+), and myonuclei (DAPI+) using immunofluorescence microscopy. After 12 weeks, myofibre CSA increased in all training conditions in type II (P = 0.0149) and mixed fibres (P = 0.0102), with no difference between conditions. Satellite cell content remained unchanged after training in both type I and type II fibres. Significant correlations were observed between increases in fibre type-specific myonuclear content and CSA of Type I (r = 0.63, P < 0.0001), Type II (r = 0.69, P < 0.0001), and mixed fibres (r = 0.72, P < 0.0001). Resistance, endurance, and concurrent training induce similar myofibre hypertrophy in the absence of satellite cell and myonuclear pool expansion. These findings suggest that myonuclear accretion via satellite cell fusion is positively correlated with hypertrophy after 12 weeks of concurrent training, and that individuals with more myonuclear content displayed greater myofibre hypertrophy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".