β-cell SENP1 facilitates responsiveness to incretins and limits oral glucose intolerance in high fat fed mice
Bibliographic record
Abstract
Abstract SUMOylation reduces oxidative stress and preserves islet mass; but this happens at the expense of robust insulin secretion. To investigate a role for the deSUMOylating enzyme sen trin-specific p rotease 1 (SENP1) in glycemia following metabolic stress, we put pancreas/gut-specific SENP1 knockout mice (pSENP1-KO) on an 8-10-week high fat diet (HFD). Male pSENP1-KO mice were more glucose intolerant following HFD than littermate controls, but this was only obvious in response to oral glucose, and a similar but milder phenotype was observed in females. Plasma incretin responses were identical, and glucose-dependent insulinotropic polypeptide (GIP) was equally upregulated after HFD, in pSENP1-KO and - WT littermates. Islet mass was not different, but insulin secretion and β-cell exocytotic responses to Exendin4 (Ex4) and GIP were impaired in islets lacking SENP1. Glucagon secretion from pSENP1-KO islets was also reduced, consistent with the expected SENP1 knockout in all islet cells, so we generated β-cell–specific SENP1 knockout mice (βSENP1-KO). These phenocopied the pSENP1-KO mice with selective impairment in oral glucose tolerance following HFD, preserved islet mass expansion, and impaired β-cell exocytosis and insulin secretion to Ex4 and GIP. Thus, β-cell SENP1 limits glucose intolerance following HFD by ensuring a robust facilitation of insulin secretion by incretins such as GIP.
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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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".