Evidence for the contribution of muscle stem cells to nonhypertrophic skeletal muscle remodeling in humans
Bibliographic record
Abstract
The purpose of this study was to explore the possible role of muscle stem cells, also referred to as satellite cells (SCs), in adaptation and remodeling following a nonhypertrophic stimulus in humans. Muscle biopsies were obtained from the vastus lateralis of previously untrained women (n=15; age: 27±8 yr, BMI: 29±6 kg/m(2)) before and after 6 wk of aerobic interval training. The fiber type-specific SC response to training was analyzed using immunofluorescent microscopy of muscle cross sections. Following training, the number of SCs associated with fibers expressing myosin heavy-chain type I and II isoforms (hybrid fibers) increased (pre: 0.062±0.035 SC/hybrid fiber; post: 0.38±0.063 SC/hybrid fiber; P<0.01). In addition, there was a greater number of MyoD(+)/Pax7(-) SCs, indicative of differentiating SCs, associated with hybrid fibers (0.18±0.096 MyoD(+)/Pax7(-) SC/hybrid fiber) compared to type I (0.015±0.00615 MyoD(+)/Pax7(-) SC/type I fiber) or II (0.012±0.00454 MyoD(+)/Pax7(-) SC/type II fiber) fibers (P<0.05). There was also a training-induced increase in the number of hybrid fibers containing centrally located nuclei (15.1%) compared to either type I (3.4%) or II fibers (3.6%) (P<0.01). These data are consistent with the hypothesis that SCs contribute to the remodeling of muscle fibers even in the absence of 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 | 0.000 |
| 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) | 0.002 | 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".