Crucial role for TNF receptor-associated factor 2 (TRAF2) in regulating NFκB2 signaling that contributes to autoimmunity
Bibliographic record
Abstract
TNF receptor-associated factor 2 (TRAF2) is a key intracellular signaling mediator that acts downstream of not only TNFα but also various members of the TNFα superfamily. Here, we report that, despite their lack of TNFα signaling, TRAF2(-/-)TNFα(-/-) mice develop an inflammatory disorder characterized by autoantibody accumulation and organ infiltration by T cells with the phenotypes of activated, effector, and memory cells. RAG1(-/-) mice reconstituted with TRAF2(-/-)TNFα(-/-) bone marrow cells showed increased numbers of hyperactive T cells and rapidly developed progressive and eventually lethal inflammation. No inflammation was observed in RAG1(-/-) mice reconstituted with TRAF2(-/-)TNFα(-/-)T-cell receptor β(-/-) or TRAF2(-/-)TNFα(-/-)NFκB-induced kinase(+/-) bone marrow cells. The pathogenic TRAF2(-/-)TNFα(-/-) T cells showed constitutive NFκB2p52 activation and produced elevated levels of T-helper 1 and T-helper 17 cytokines. Our results suggest that a regulatory circuit consisting of TRAF2-NFκB-induced kinase-NFκB2p52 is essential for the proper control of effector T-cell polarization and that loss of T-cell TRAF2 function induces constitutive NFκB2p52 activity that drives fatal autoimmune inflammation independently of TNFα signaling. The involvement of this regulatory circuit in controlling autoimmune responses highlights the delicate balance required to avoid paradoxical adverse events when implementing new targeted anti-inflammatory therapies.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".