Amyloid formation disrupts the balance between interleukin-1β and interleukin-1 receptor antagonist in human islets
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Bibliographic record
Abstract
OBJECTIVES: model of amyloid formation to: (1) investigate the effects of amyloid on islet levels of the natural IL-1 receptor antagonist (IL-1Ra); (2) examine if modulating the IL-1β/IL-1Ra balance can prevent amyloid-induced β-cell Fas upregulation and apoptosis. METHODS: Isolated human islets (n = 10 donors) were cultured in elevated glucose (to form amyloid) with or without a neutralizing human IL-1β antibody for up to 7 days. Parallel studies were performed with human islets in which amyloid formation was prevented by adeno-siRNA-mediated suppression of hIAPP expression (as control). β-cell levels of IL-1Ra, Fas, apoptosis as well as islet function, insulin- and amyloid-positive areas, and IL-1Ra release were assessed. RESULTS: Progressive amyloid formation in human islets during culture was associated with alterations in IL-1Ra. Islet IL-1Ra levels were higher at early stages but were markedly reduced at later stages of amyloid formation. Furthermore, IL-1Ra release from human islets was reduced during 7-day culture in a time-dependent manner. These changes in IL-1Ra production and release from human islets during amyloid formation adversely correlated with islet IL-1β levels, β-cell Fas expression and apoptosis. Treatment with IL-1β neutralizing antibody markedly reduced amyloid-induced β-cell Fas expression and apoptosis, thereby improving islet β-cell survival and function during culture. CONCLUSIONS: These data suggest that amyloid formation impairs the balance between IL-1β and IL-1Ra in islets by increasing IL-1β production and reducing IL-1Ra levels thereby promoting β-cell dysfunction and death. Restoring the IL-1β/IL-1Ra ratio may provide an effective strategy to protect islet β-cells from amyloid toxicity in T2D.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it