Both cIAP1 and cIAP2 regulate TNFα-mediated NF-κB activation
Bibliographic record
Abstract
The cellular inhibitor of apoptosis 1 and 2 (cIAP1 and cIAP2) proteins have been implicated in the activation of NF-kappaB by TNFalpha; however, genetic deletion of either cIAP1 or 2 did not support a physiologically relevant role, perhaps because of functional redundancy. To address this, we used combined genetic and siRNA knockdown approaches and report that cIAP1 and 2 are indeed critical, yet redundant, regulators of NF-kappaB activation upon TNFalpha treatment. Whereas NF-kappaB was properly activated by TNFalpha in cultured and primary cells deficient in either cIAP1 or 2, removal of both cIAPs severely blunted its activation. After treatment with TNFalpha, cIAP1 and 2 were rapidly recruited to the TNF receptor 1, along with the adapter protein TNF receptor associated factor 2. Importantly, either cIAP1 or 2 was required for proper TNF receptor 1 signalosome function. In their combined absence, polyubiquitination of receptor interacting protein 1, an upstream event necessary for NF-kappaB signaling, was attenuated. As a result, phosphorylation of the inhibitor of kappaB kinase beta was diminished, and signal transduction was severely blunted. Consequently, cells missing both cIAP1 and 2 were sensitized to TNFalpha-mediated apoptosis. Collectively, these data demonstrate that either cIAP1 or 2 is required for proper Rip1 polyubiquitination and NF-kappaB activation upon TNFalpha treatment.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".