Role of prolyl hydroxylase domain proteins in the regulation of insulin secretion
Bibliographic record
Abstract
Type 2 diabetes is associated with impaired nutrient-regulated anaplerosis and insulin secretion in pancreatic β-cells. One key anaplerotic substrate that may be involved in regulating insulin release is α-ketoglutarate (αKG). Since prolyl hydroxylase domain proteins (PHDs) can metabolize cytosolic αKG, we sought to explore the role of this enzyme in the regulation of β-cell function. The oxygen-sensing PHDs regulate the stability of hypoxia-inducible factor 1α (HIF1α) as well as other proline-containing proteins by catalyzing the hydroxylation of proline residues. This reaction is dependent on sufficient levels of oxygen, iron, and αKG. In the present study, we utilized both pharmacological and genetic approaches to assess the impact of inhibiting PHD activity on β-cell function. We demonstrate that ethyl-3,4-dihydroxybenzoate (EDHB), a PHD inhibitor, significantly blunted glucose-stimulated insulin secretion (GSIS) from 832/13 clonal cells, rat, and human islets. EDHB reduced glucose utilization, ATP/ADP ratio, and key TCA cycle intermediates such as pyruvate, citrate, fumarate, and malate. siRNA-mediated knockdown of PHD1 and PHD3 inhibited GSIS, whereas siRNA-mediated knockdown of PHD2 had no effect on GSIS. Taken together, the current results demonstrate an important role for PHDs as mediators of islet insulin secretion.
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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) | 0.000 | 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 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".