Reductions in RIP140 are not required for exercise and high fat diet mediated increases in mitochondrial enzymes
Bibliographic record
Abstract
The over-expression of RIP140 reduces the expression of mitochondrial enzymes whereas the deletion of RIP140 increases mitochondrial content. Despite the importance of RIP140 in the control of mitochondrial biogenesis the effects of physiological perturbations on regulating RIP140 in skeletal muscle has not been determined. To this end, rats were exercised by 2 hours of daily swim training for 14 consecutive days or fed a high fat diet (HFD) for 6 weeks. In an additional study 6 healthy college aged males completed 6 sessions of high intensity exercise training consisting of 8–12 X 1 min sprints on a stationary bicycle at 100% of peak power. Exercise training increased the protein contents of CORE1 (48% increase), COXI (91% increase) and COXIV (30% increase) and citrate synthase activity (45% increase) while having no effect on RIP140 mRNA levels and protein content in rat triceps. Similarly, high intensity exercise training in humans did not cause reductions in the nuclear protein content of RIP140. The consumption of a HFD increased the protein contents of CORE1 (72% increase) and COXIV (53% increase) and the enzyme activities of citrate synthase (26% increase) and beta HAD (71% increase). RIP140 mRNA and protein content was not reduced by the consumption of a HFD. Collectively our results demonstrate that reductions in RIP140 are not required for the induction of mitochondrial biogenesis in 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".