Resistance training alters the response of fed state mixed muscle protein synthesis in young men
Bibliographic record
Abstract
Ten healthy young men (21.0 +/- 1.5 yr, 1.79 +/- 0.1 m, 82.7 +/- 14.7 kg, means +/- SD) participated in 8 wk of intense unilateral resistance training (knee extension exercise) such that one leg was trained (T) and the other acted as an untrained (UT) control. After the 8 wk of unilateral training, infusions of L-[ring-d(5)]phenylalanine, L-[ring-(13)C(6)]phenylalanine, and d(3)-alpha-ketoisocaproic acid were used to measure mixed muscle protein synthesis in the T and UT legs by the direct incorporation method [fractional synthetic rate (FSR)]. Protein synthesis was determined at rest as well as 4 h and 28 h after an acute bout of resistance exercise performed at the same intensity relative to the gain in single repetition maximum before and after training. Training increased mean muscle fiber cross-sectional area only in the T leg (type I: 16 +/- 10%; type II: 20 +/- 19%, P < 0.05). Acute resistance exercise increased muscle protein FSR in both legs at 4 h (T: 162 +/- 76%; UT: 108 +/- 62%, P < 0.01 vs. rest) with the increase in the T leg being significantly higher than in the UT leg at this time (P < 0.01). At 28 h postexercise, FSR in the T leg had returned to resting levels; however, the rate of protein synthesis in the UT leg remained elevated above resting (70 +/- 49%, P < 0.01). We conclude that resistance training attenuates the protein synthetic response to acute resistance exercise, despite higher initial increases in FSR, by shortening the duration for which protein synthesis is elevated.
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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".