Cytokines Tumor Necrosis Factor-α and Interferon-γ Induce Pancreatic β-Cell Apoptosis through STAT1-mediated Bim Protein Activation
Bibliographic record
Abstract
Type 1 diabetes is characterized by local inflammation (insulitis) in the pancreatic islets causing β-cell loss. The mitochondrial pathway of apoptosis is regulated by the balance and interaction between Bcl-2 members. Here we clarify the molecular mechanism of β-cell death triggered by the pro-inflammatory cytokines tumor necrosis factor (TNF)-α and interferon (IFN)-γ. The combination of TNF-α + IFN-γ induced DP5, p53 up-regulated modulator of apoptosis (PUMA), and Bim expression in human islets and rodent β-cells. DP5 and PUMA inactivation by RNA interference partially protected against TNF-α + IFN-γ-induced β-cell apoptosis. DP5 knock-out mice had increased β-cell area, and isolated islets from these mice were resistant to cytokine exposure. Bim expression was transcriptionally regulated by STAT1, and its activation triggered cleavage of caspases. Silencing of Bim protected rodent and human β-cells to a large extent against TNF-α + IFN-γ, indicating a major role of this BH3-only activator protein in the mechanism of apoptosis. Our data support a highly regulated and context-dependent modulation of specific Bcl-2 members controlling the mitochondrial pathway of β-cell apoptosis during insulitis.
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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) | 0.002 | 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".