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The role of TRAF1 in stabilizing TRAF2 from proteasome mediated degradation downstream of 4-1BB signaling (138.1)

2010· article· en· W2290033448 on OpenAlexaff
Ann J. McPherson, Tania H. Watts

Bibliographic record

VenueThe Journal of Immunology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTRAF2ProteasomeCell biologySignal transductionDownregulation and upregulationBiologyReceptorTumor necrosis factor alphaCancer researchImmunologyTumor necrosis factor receptorGeneticsGene

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.211
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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