Oxidative status of muscle is determined by p107 regulation of PGC-1α
Bibliographic record
Abstract
Mice lacking p107 exhibit a white adipose deficiency yet do not manifest the metabolic changes typical for lipodystrophy, and instead exhibit low levels of serum triglycerides and a normal liver phenotype. When fed a high fat diet, p107-null mice still did not accumulate fat in the liver, and display markedly elevated energy expenditures together with an increased energy preference for lipids. Skeletal muscle was therefore examined, as this is normally the major tissue involved in whole body lipid metabolism. Notably, p107-deficient muscle express increased levels of peroxisome proliferator-activated receptor gamma co-activator-1alpha (PGC-1alpha) and contained increased numbers of the pro-oxidative type I and type IIa myofibers. Chromatin immunoprecipitation revealed binding of p107 and E2F4 to the PGC-1alpha proximal promoter, and this binding repressed promoter activity in transient transcription assays. Ectopic expression of p107 in muscle tissue in vivo results in a pronounced 20% decrease in the numbers of oxidative type IIa myofibers. Lastly, isolated p107-deficient muscle tissue display a threefold increase in lipid metabolism. Therefore, p107 determines the oxidative state of multiple tissues involved in whole body fat metabolism, including 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".