The impact of a 48-h fast on SIRT1 and GCN5 in human skeletal muscle
Bibliographic record
Abstract
The present study examined the impact of a 48 h fast on the expression and activation status of SIRT1 and GCN5, the relationship between SIRT1/GCN5 and the gene expression of PGC-1α, and the PGC-1α target PDK4 in the skeletal muscle of 10 lean healthy men (age, 22.0 ± 1.5 years; peak oxygen uptake, 47.2 ± 6.7 mL/(min·kg)). Muscle biopsies and blood samples were collected 1 h postprandial (Fed) and following 48 h of fasting (Fasted). Plasma insulin (Fed, 80.8 ± 47.9 pmol/L; Fasted, not detected) and glucose (Fed, 4.36 ± 0.86; Fasted, 3.74 ± 0.25 mmol/L, p = 0.08) decreased, confirming participant adherence to fasting. Gene expression of PGC-1α decreased (p < 0.05, -24%), while SIRT1 and PDK4 increased (p < 0.05, +11% and +1023%, respectively), and GCN5 remained unchanged. No changes were observed for whole-muscle protein expression of SIRT1, GCN5, PGC-1α, or COX IV. Phosphorylation of SIRT1, AMPKα, ACC, p38 MAPK, and PKA substrates as well as nuclear acetylation status was also unaltered. Additionally, nuclear SIRT1 activity, GCN5, and PGC-1α content remained unchanged. Preliminary findings derived from regression analysis demonstrate that changes in nuclear GCN5 and SIRT1 activity/phosphorylation may contribute to the control of PGC-1α, but not PDK4, messenger RNA expression following fasting. Collectively, and in contrast with previous animal studies, our data are inconsistent with the altered activation status of SIRT1 and GCN5 in response to 48 h of fasting in human skeletal muscle.
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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".