Bcl10/Malt1 Signaling Is Essential for TCR-Induced NF-κB Activation in Thymocytes but Dispensable for Positive or Negative Selection
Bibliographic record
Abstract
During T cell development in the thymus, high-affinity/avidity TCR engagement induces negative selection by apoptosis, while lower affinity/avidity TCR interactions lead to positive selection and survival of thymocytes. Yet, the mechanisms that discriminate between positive and negative selection are not fully understood. One major regulator of survival and apoptosis in lymphoid cells is the transcription factor NF-kappaB. Several reports have indicated key roles for NF-kappaB in positive and negative selection. In peripheral T cells, TCR ligation activates NF-kappaB through a selective pathway that involves protein kinase Ctheta, Bcl10, and Malt1. While protein kinase Ctheta is dispensable for thymic TCR signaling, the molecular roles of Bcl10 and Malt1 in thymocytes have not been investigated. In the present study, we show that both Bcl10 and Malt1 are essential for TCR signaling in thymocytes as a genetic disruption of either molecule blocks TCR-induced NF-kappaB activation in these cells. To investigate the function of this pathway in thymic selection, we introduced the Bcl10 or Malt1 mutations into three well-established TCR transgenic mouse models. Surprisingly, using several in vivo or in vitro assays, we were unable to demonstrate a role for TCR-induced NF-kappaB activation in either positive or negative selection. Thus, while TCR signaling to NF-kappaB controls the activation of mature T cells, we suggest that this pathway is not involved in the positive or negative selection of thymocytes.
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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 | 0.001 |
| 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".