Glucose represses PPARαgene expression via AMP‐activated protein kinase but not via p38 mitogen‐activated protein kinase in the pancreatic β‐cell
Bibliographic record
Abstract
BACKGROUND: Peroxisome proliferator-activated receptor α (PPARα) regulates the expression of fatty acid metabolism genes and is thought to play a role in the regulation of insulin secretion and lipid detoxification. We have examined the mechanism whereby glucose decreases PPARα gene expression in the pancreatic β-cell. METHODS: INS832/13 β-cell and isolated rat islets were incubated at 3 and 20 mM glucose for 18 h in the absence or presence of adenosine monophosphate (AMP)-activated protein kinase (AMPK) activators and inhibitors, as well as p38 mitogen-activated protein kinase (p38 MAPK) inhibitors. In another set of experiments, INS832/13 were infected with an adenovirus expressing a dominant-negative form of AMPK. PPARα expression levels were measured by reverse transcription polymerase chain reaction and Western blot. RESULTS: Elevated glucose reduced the abundance of the PPARα transcript and protein, and its target genes acyl-coenzyme A (CoA) oxidase (ACO) and uncoupling protein 2 (UCP-2) in INS832/13 β-cell and isolated rat islets. Glucose reduced AMPK activity, while the AMPK activators 5-amino-4-imidazolecarboxamide riboside and metformin increased PPARα expression and suppressed the action of glucose. By contrast, the AMPK inhibitor compound C mimicked the glucose effect. A dominant negative form of AMPKα reduced the PPARα, ACO and UCP-2 transcripts to the same extent as elevated glucose. Pharmacological evidence indicated that glucose-regulated PPARα expression does not involve p38 MAPK, a target of AMPK in several cell types. CONCLUSIONS: The results indicate that glucose represses PPARα gene expression via AMPK, but not via p38 MAPK in the β-cell.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".