Peroxisome proliferator-activated receptor-γ coactivator 1α (PGC-1α) regulates triglyceride metabolism by activation of the nuclear receptor FXR
Bibliographic record
Abstract
Peroxisome proliferator-activated receptor-gamma coactivator 1alpha (PGC-1alpha) has been shown to regulate adaptive thermogenesis and glucose metabolism. Here we show that PGC-1alpha regulates triglyceride metabolism through both farnesoid X receptor (FXR)-dependent and -independent pathways. PGC-1alpha increases FXR activity through two pathways: (1) it increases FXR mRNA levels by coactivation of PPARgamma and HNF4alpha to enhance FXR gene transcription; and (2) it interacts with the DNA-binding domain of FXR to enhance the transcription of FXR target genes. Ectopic expression of PGC-1alpha in murine primary hepatocytes reduces triglyceride secretion by a process that is dependent on the presence of FXR. Consistent with these in vitro studies, we demonstrate that fasting induces hepatic expression of PGC-1alpha and FXR and results in decreased plasma triglyceride levels in wild-type but not in FXR-null mice. Our data suggest that PGC-1alpha plays an important physiological role in maintaining energy homeostasis during fasting by decreasing triglyceride production/secretion while it increases fatty acid beta-oxidation to meet energy needs.
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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 | 0.001 |
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".