Resistance and endurance training differentially affect myofibrillar and mitochondrial protein synthesis at rest and following exercise in human skeletal muscle
Bibliographic record
Abstract
We aimed to determine the acute and chronic changes in myofibrillar (MYOFIB) and mitochondrial protein synthesis rates (MITO) with aerobic exercise (AE) and resistance exercise (RE). We infused d 3 ‐α‐KIC at REST and for 4 hours after an acute bout of RE or AE prior to (UT) and following 10 weeks (TR) of training in healthy 20 yr old men. In the UT state, both MYOFIB (REST: 0.06±0.01, RE: 0.10±0.01 %/h, p=0.01) and MITO (REST: 0.08±0.02, RE: 0.14±0.04 %/h, p=0.02) increased following RE. Following TR only MYOFIB increased with RE (REST: 0.08±0.01, RE: 0.11±0.01 %/h, p=0.05), while MITO did not change from resting values (p=0.43). AE stimulated MITO (UT REST: 0.07±0.02, AE: 0.18±0.03, TR REST 0.07±0.01, AE: 0.15±0.03 %/h, p<0.05) but not MYOFIB regardless of training. In conclusion, RE acutely increases both MYOFIB and MITO, while AE increases MITO only. Acute responses to RE appear to be redundant in that synthesis of both MYOFIB and MITO were both stimulated. Following TR, the rate of MYOFIB was increased at rest with RE, and also following an acute bout of RE. By contrast AE activated only MITO in both the UT and TR states. These protein fraction responses are exercise specific and indicate the responses of mixed muscle protein synthesis are likely heavily influenced by exercise mode and training status. Supported by NSERC, CIHR, UK BBSRC, NIH‐NCRR.
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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".