Hedgehog Interacting Protein (Hhip) Regulates Insulin Secretion in Mice Fed High Fat Diets
Bibliographic record
Abstract
Hedgehog interacting protein (Hhip) is essential for islet formation and beta-cell proliferation during pancreatic development; abnormally elevated Hhip expression has been linked to human pancreatitis. Here, we investigate the role of Hhip in modulating insulin secretion in adult Hhip mice (Hhip +/- vs. Hhip+/+) fed high fat diets (HFD). Both sexes of HFD-Hhip +/+ mice developed impaired glucose intolerance, that was only ameliorated in male HFD-Hhip +/- mice that had high levels of circulating plasma insulin, but not in female HFD-Hhip +/- mice. HFD stimulated Hhip gene expression, mainly in beta cells. Male HFD-Hhip +/+ mice had more large islets in which insulin content was reduced; islet architecture was disordered; and markers of oxidative stress (8-OHdG and Nox 2) were increased. In contrast, male HFD-Hhip +/- mice had more small islets with increased beta cell proliferation, enhanced GSIS, less oxidative stress and preserved islet integrity. In vitro, recombinant Hhip increased Nox2 and NADPH activity and decreased insulin-positive beta cells. siRNA-Hhip increased GSIS and abolished the stimulation of sodium palmitate (PA)-BSA on Nox2 gene expression. We conclude that pancreatic Hhip gene inhibits insulin secretion by altering islet integrity and promoting Nox2 gene expression in beta cells in response to HDF-mediated beta cell dysfunction, a novel finding.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".