PGC-1α-mediated regulation of gene expression and metabolism: implications for nutrition and exercise prescriptions
Bibliographic record
Abstract
The discovery 10 years ago of PGC-1alpha represented a major milestone towards understanding of the molecular processes regulating energy metabolism in many tissues, including skeletal muscle. PGC-1alpha orchestrates a metabolic program regulating oxidative lipid metabolism and insulin sensitivity. This is essentially the same metabolic program that is activated by exercise and down-regulated by sedentary lifestyles and high-fat diets, as well as in cases of obesity and type 2 diabetes. The present review examines the evidence in support of the key role for PGC-1alpha regulation of substrate metabolism and mitochondrial biogenesis in skeletal muscle. Surprisingly, studies with PGC-1alpha null and transgenic mice have revealed unexpected pathologies when PGC-1alpha is completely repressed (KO animals) or is massively overexpressed. In contrast, PGC-1alpha overexpression within normal physiological limits results in marked improvements in fatty acid oxidation and insulin-stimulated glucose transport. Exercise, sedentary lifestyles, and nutritional factors can regulate PGC-1alpha expression. We speculate that optimal targeting of PGC-1alpha upregulation, whether by diet, exercise, or a combination of both, could represent effective prophylactic or therapeutic means to improve insulin sensitivity. Indeed, using modern molecular tools, it may indeed be possible to prescribe optimally individualized nutrition and exercise programs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".