The role of TRAF1 in stabilizing TRAF2 from proteasome mediated degradation downstream of 4-1BB signaling (138.1)
Bibliographic record
Abstract
Abstract TNF receptor family members play important roles in the innate and adaptive immune response, inducing signals for cell survival or apoptosis. This signaling in most cases relies on TNF receptor associated factors (TRAFs) to relay the signal from the TNFR family member to activation of NF-κB or MAPK pathways. Results from our lab have shown that TRAF1 is critical in the downregulation of the proapoptotic molecule Bim and the survival of activated and memory CD8 T cells, acting downstream of the prosurvival TNF receptor family member 4-1BB. We show here that in the absence of TRAF1, signaling downstream of 4-1BB results in the rapid proteasome dependent degradation of TRAF2. To identify interacting binding partners of TRAF1 that may mediate its stabilizing role on TRAF2 we performed a yeast two hybrid screen using a cDNA library from activated mouse lymph nodes. Among the interacting proteins identified were PSMC3, a subunit of the 19S regulatory particle of the 26S proteasome. We have confirmed the interaction between TRAF1 and PSMC3 in T cells and are currently investigating its functional role in the signaling downstream of 4-1BB. The results suggest that TRAF1 may have an important role in controlling the duration of the signal.
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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 | 0.000 |
| 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".