c‐Rel phenocopies PKCθ but not Bcl‐10 in regulating CD8<sup>+</sup> T‐cell activation <i>versus</i> tolerance
Bibliographic record
Abstract
Elucidating the signaling events that promote T-cell tolerance versus activation provides important insights for manipulating immunity in vivo. Previous studies have suggested that the absence of PKCtheta results in the induction of anergy and that the balance between the induction of the transcription factors NFAT, AP1 and NF-kappaB plays a key role in determining whether T-cell anergy or activation is induced. Here, we examine whether Bcl-10 and specific family members of NF-kappaB act downstream of PKCtheta to alter CD8(+) T-cell activation and/or anergy. We showed that T cells from mice deficient in c-Rel but not NF-kappaB1 (p50) have increased susceptibility to the induction of anergy, similar to T cells from PKCtheta-deficient mice. Surprisingly T cells from Bcl-10-deficient mice showed a strikingly different phenotype to the PKCtheta-deficient T cells, with a severe block in TCR-mediated activation. Furthermore, we have also shown that survival signals downstream of NF-kappaB, are uncoupled from signals that mediate T-cell anergy. These results suggest that c-Rel plays a critical role downstream of PKCtheta in controlling CD8(+) T-cell anergy induction.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".