Proinflammatory Cytokines Activate the Intrinsic Apoptotic Pathway in β-Cells
Bibliographic record
Abstract
OBJECTIVE: Proinflammatory cytokines are cytotoxic to beta-cells and have been implicated in the pathogenesis of type 1 diabetes and islet graft failure. The importance of the intrinsic mitochondrial apoptotic pathway in cytokine-induced beta-cell death is unclear. Here, cytokine activation of the intrinsic apoptotic pathway and the role of the two proapoptotic Bcl-2 proteins, Bad and Bax, were examined in beta-cells. RESEARCH DESIGN AND METHODS: Human and rat islets and INS-1 cells were exposed to a combination of proinflammatory cytokines (interleukin-1beta, interferon-gamma, and/or tumor necrosis factor-alpha). Activation of Bad was determined by Ser136 dephosphorylation, mitochondrial stress by changes in mitochondrial metabolic activity and cytochrome c release, downstream apoptotic signaling by activation of caspase-9 and -3, and DNA fragmentation. The inhibitors FK506 and V5 were used to investigate the role of Bad and Bax activation, respectively. RESULTS: We found that proinflammatory cytokines induced calcineurin-dependent dephosphorylation of Bad Ser136, mitochondrial stress, cytochrome c release, activation of caspase-9 and -3, and DNA fragmentation. Inhibition of Bad Ser136 dephosphorylation or Bax was found to inhibit cytokine-induced intrinsic proapoptotic signaling. CONCLUSIONS: Our findings demonstrate that the intrinsic mitochondrial apoptotic pathway contributes significantly to cytokine-induced beta-cell death and suggest a functional role of calcineurin-mediated Bad Ser136 dephosphorylation and Bax activity in cytokine-induced apoptosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".