SirT1 is not required for exercise‐induced mitochondrial biogenesis, but maintains basal organelle content and function
Bibliographic record
Abstract
The purpose of this research was to evaluate the role of SirT1 in exercise-induced mitochondrial biogenesis. To do this, we produced skeletal-muscle specific SirT1-deficient (KO) mice. These KO mice had similar body, heart and muscle weights as wild-type (WT) animals. Isolated muscle mitochondria from KO mice exhibited a 30% decline in COX activity, and 40% and 20% reductions in state 4 and state 3 respiration, respectively. There was a corresponding 2.5-fold elevation in ROS generation during both state 4 and state 3 respiration. To examine the dependence of exercise-induced mitochondrial biogenesis on SirT1, we trained the WT and KO mice on voluntary running wheels for 9 weeks. Both WT and KO mice ran the same average (14 km/day) and total distances. Voluntary exercise produced 1.4- and 1.7-fold increases in COX activity in both the WT and KO animals, bringing them to the same absolute value of COX activity. In addition, the deficits in state 3 and 4 respiration, along with the elevated ROS levels in KO mice were rescued to values that were of the WT mice. Interestingly, Nampt protein, a positive modulator of SirT1 activity, increased by ~2.5-fold in both WT and KO mice. These data indicate SirT1 is necessary for the maintenance of basal mitochondrial content and function. However, SirT1 does not does not seem to be necessary for exercise-induced mitochondrial biogenesis.
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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".