TNFR1 functions as a survival receptor in TNFR2-/- CD8 T cells (50.19)
Bibliographic record
Abstract
Abstract TNF/TNFR superfamily members play central roles in host defense, inflammation, apoptosis, autoimmunity and organogenesis. Previous reports showed that TNFR2 regulates T cell activation by lowering the activation threshold and providing costimulatory signaling. Furthermore, activated TNFR2-/- CD8 cells are highly resistant to AICD. Here, we show that blocking of activated wild-type (wt) CD8 cells with anti-TNFR2 antibodies also renders these cells resistant to AICD. The resistance of activated TNFR2-/- CD8 cells to AICD correlates with the accumulation of TRAF2. Retroviral transfection studies showed that TRAF2 overexpression was partially effective in preventing AICD in activated wt CD8+ cells. Furthermore, neutralization of TNF-α inhibits the proliferation of anti-CD3-stimulated wt CD8 T cells and increases apoptotic death cells in activated TNFR2-/- cells. TNF-α blocking also reduced TRAF2 accumulation in activated TNFR2-/- CD8 cells, which correlates with their increase susceptibility to AICD. AICD-resistant TNFR2-/- CD8 cells expressed elevated levels of phosphorylated IκBα and neutralization of TNF-α blocked this increase. These results indicate that in activated TNFR2-/- CD8 cells, TNFR1 functions as a survival receptor by promoting TNF-α-mediated regulation of TRAF2 levels and the extent of phosphorylation of pro-survival signaling molecules such as IκBα. This work is supported by the Canadian Cancer Society.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".