TRAF6 Specifically Contributes to FcϵRI-mediated Cytokine Production but Not Mast Cell Degranulation
Bibliographic record
Abstract
TRAF6 (tumor necrosis factor-associated factor 6) is an essential adaptor downstream from the tumor necrosis factor (TNF) receptor and Toll-like receptor superfamily members. This molecule is critical for dendritic cell maturation and T cell homeostasis. Here we show that TRAF6 is important in high affinity IgE receptor, FcepsilonRI-mediated mast cell activation. In contrast to dendritic cells and T cells, TRAF6-deficient mast cells matured normally and showed normal IgE-dependent degranulation. Importantly, TRAF6-deficient mast cells showed impaired production of cytokine interleukin-6, CCL-9, interleukin-13, and TNF following FcepsilonRI aggregation. Chromatin immunoprecipitation assay showed decreased NF-kappaB p65 binding to CCL-9 and TNF promoters in TRAF6-deficient mast cells. Antigen and IgE-induced IkappaB phosphorylation and NF-kappaB p65 translocation to the nucleus were diminished in TRAF6-deficient mast cells. NF-kappaB luciferase activity in response to antigen and IgE stimulation was severely impaired in TRAF6-deficient mast cells. In addition, antigen and IgE-induced phosphorylation of mitogen-activated protein kinase p38 and JNK, but not ERK1/2, was significantly reduced in TRAF6-deficient mast cells. These results identified TRAF6 as an important signal transducer in FcepsilonRI-mediated signaling in mast cells. Our findings implicate TRAF6 as a new adaptor/regulator molecule for allergen-mediated inflammation in allergy.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".