Peroxisome Proliferator–Activated Receptor-γ Regulates Expression of PDX-1 and NKX6.1 in INS-1 Cells
Bibliographic record
Abstract
In the 60% pancreatectomy (Px) rat model of beta-cell adaptation, normoglycemia is maintained by an initial week of beta-cell hyperplasia that ceases and is followed by enhanced beta-cell function. It is unknown how this complex series of events is regulated. We studied isolated islets and pancreas sections from 14-day post-Px versus sham-operated rats and observed a doubling of beta-cell nuclear peroxisome proliferator-activated receptor (PPAR)-gamma protein, along with a 2-fold increase in nuclear pancreatic duodenal homeobox (Pdx)-1 protein and a 1.4-fold increase in beta-cell nuclear Nkx6.1 immunostaining. As PPAR-gamma activation is known to both lower proliferation and have prodifferentiation effects in many tissues, we studied PPAR-gamma actions in INS-1 cells. A 3-day incubation with the PPAR-gamma agonist troglitazone reduced proliferation and increased Pdx-1 and Nkx6.1 immunostaining, along with glucokinase and GLUT2. Also, a 75% knockdown of PPAR-gamma using RNA interference lowered the mRNA levels of Pdx-1, glucokinase, GLUT2, and proinsulin II by more than half. Our results show a dual effect of PPAR-gamma in INS-1 cells: to curtail proliferation and promote maturation, the latter via enhanced expression of Pdx-1 and Nkx6.1. Additional studies are needed to determine whether there is a regulatory role for PPAR-gamma signaling in the beta-cell adaptation following a 60% Px in rats.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".