A novel pathway for regulation of glucose‐dependent insulinotropic polypeptide receptor expression in β‐cells
Bibliographic record
Abstract
Glucose-dependent insulinotropic polypeptide (GIP) is secreted postprandially and acts in concert with glucose to stimulate insulin secretion from the pancreas. Here, we describe a novel pathway for the regulation of GIP receptor (GIPR) expression within clonal beta-cell lines, pancreatic islets, and in vivo. High (25 mM) glucose was able to significantly reduce GIPR mRNA levels in INS(832/13) cells after only 6 h. In contrast, palmitic acid (2 mM) and WY 14643 (100 microM) stimulated approximate doublings of GIPR expression in INS(832/13) cells under low (5.5 mM), but not high (25 mM), glucose conditions, suggesting that fat can regulate GIPR expression via PPARalpha in a glucose-dependent manner. Both MK-886, an antagonist of PPARalpha, and a dominant negative form of PPARalpha transfected into INS(832/13) cells caused a significant reduction in GIPR expression in low, but not high, glucose conditions. Finally, in hyperglycemic clamped rats, there was a 70% reduction in GIPR expression in the islets and a 71% reduction in GIP-stimulated insulin secretion from the perfused pancreas. Thus, evidence is presented that the GIPR is controlled at normoglycemia by the fatty acid load on the islet; however, when exposed to hyperglycemic conditions, the GIPR is down-regulated, which may contribute to the decreased responsiveness to GIP that is observed in type 2 diabetes.
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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 | 0.001 | 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".