Myogenic mRNA markers in young and old human skeletal muscle prior to and following sequential exercise bouts
Bibliographic record
Abstract
This study examined how multiple bouts of conventional resistance training affected the mRNA expression of transcripts and a protein associated with satellite cell activity in human skeletal muscle. Ten younger men (means ± SE; age, 21.0 ± 0.5 years; body mass, 82.3 ± 4.2 kg; height, 178.4 ± 2.2 cm; percent body fat, 15.4% ± 2.9%) and 10 older men (age, 66.4 ± 1.6 years; body mass, 94.2 ± 3.7 kg; height, 180.9 ± 2.2 cm; percent body fat, 27.4% ± 1.8%) completed 3 lower-body workouts (Monday, Wednesday, Friday; 9 sets of 10 repetitions at 80% 1 repetition maximum). Vastus lateralis muscle biopsies were collected prior to intervention (T1), 48 h following workout 1 (T2), 48 h following workout 2 (T3), and 24 h following workout 3 (T4). Real-time reverse transcription-polymerase chain reaction was performed to assess genes of interest, and muscle proliferating cell nuclear antigen (PCNA) was assessed using Western blotting. The CYCLIN D1 gene was expressed more highly in the older vs. younger men (p < 0.05), whereas the expression of all other genes and muscle PCNA were similar between age groups. MYOD mRNA expression increased at T2 (p < 0.05) and MHCEMB gene expression modestly increased (p < 0.05) at T4 relative to baseline expression values in the younger men. Baseline elevations in CYCLIN D1 mRNA expression in older persons may indicate that a compensatory expression of this transcript is occurring in an attempt to retain the muscle's proliferative potential. Increases in MYOD and MHCEMB indicate that 1 week of conventional resistance exercise may i crease myogenic activity, including satellite cell proliferation and differentiation, respectively, in younger men.
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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) | 0.001 | 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".