TRAF2 exerts opposing effects on basal and TNFα-induced activation of the classic IKK complex in hematopoietic cells in mice
Bibliographic record
Abstract
The role of TRAF2 and TRAF5 in TNFα-induced NF-κB activation has become complicated owing to the accumulation of conflicting data. Here, we report that 7-day-old TRAF2-knockout (KO) and TRAF2 TRAF5 double KO (TRAF2/5-DKO) mice exhibit enhanced canonical IκB kinase (IKK) and caspase-8 activation in spleen and liver, and that subsequent knockout of TNFα suppresses the basal activity of caspase-8, but not of IKK. In primary TRAF2 KO and TRAF2/5-DKO cells, TNFα-induced immediate IKK activation is impaired, whereas delayed IKK activation occurs normally; as such, owing to elevated basal and TNFα-induced delayed IKK activation, TNFα stimulation leads to significantly increased induction of a subset of NF-κB-dependent genes in these cells. In line with this, both TRAF2 KO and TRAF2/5-DKO mice succumb to a sublethal dose of TNFα owing to increased expression of NF-κB target genes, diarrhea and bradypnea. Notably, depletion of IAP1 and IAP2 (also known as BIRC2 and BIRC3, respectively) also results in elevated basal IKK activation that is independent of autocrine TNFα production and that impairs TNFα-induced immediate IKK activation. These data reveal that TRAF2, IAP1 and IAP2, but not TRAF5, cooperatively regulate basal and TNFα-induced immediate IKK activation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".