Interleukin-1 signaling contributes to acute islet compensation
Bibliographic record
Abstract
IL-1β is a well-established inducer of both insulin resistance and impaired pancreatic islet function. Despite this, findings examining IL-1 receptor deficiency or antagonism in in vivo animal models, as well as in clinical studies of type 2 diabetic (T2D) patients, have led to conflicting results, suggesting that the actions of IL-1β on glycemic control may be pleiotropic in nature. In the present work, we find that the ability of IL-1β to amplify glucose-stimulated insulin secretion from human islets correlates with donor BMI. Islets from obese donors are sensitized to the insulinotropic effects of this cytokine, whereas the stimulatory effects of IL-1β are lost in islets from obese T2D patients, suggesting a role for IL-1 signaling in islet compensation. Indeed, mice deficient in IL-1 receptor type I become glucose intolerant more rapidly than their WT littermates and have impaired secretory responses during the acute stages of inflammatory and metabolic stress induced by LPS and high-fat diet, respectively. IL-1β directly enhances β cell insulin secretion by increasing granule docking and soluble N-ethylmaleimide-sensitive factor attachment receptor (SNARE) complex formation at the plasma membrane. Together, our study highlights the importance of IL-1β signaling in islet compensation to metabolic and inflammatory stress.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".