Differential contributions for Bim and Nur77 in negative selection against ubiquitous and tissue-restricted self-antigens (BA2P.122)
Bibliographic record
Abstract
Abstract The thymic cortex and medulla are both sites of negative selection, where high affinity encounter with ubiquitous (UbA) and tissue-restricted (TRA) self-antigens, respectively, is thought to result in clonal deletion. Our group has shown that Bim is not required for UbA-mediated deletion but is required for TRA-mediated deletion. Nur77 is another protein implicated in thymocyte apoptosis, though its mechanism of action and regulation remain unclear. Using a physiological TCR transgenic model, HYcd4, we found that Nur77 was also dispensable for clonal deletion against UbA. Though Nur77 and its family member Nor-1 were induced during negative selection in HYcd4 Bim-/- mice, caspase-3 activation remained abrogated. Concurrent expression of a TCR transgene with a Nur77 transgene significantly inhibited Nur77-mediated thymocyte apoptosis, suggesting that TCR signalling can impair the pro-apoptotic function of Nur77. In contrast to a recent study using the OT-II Rip-mOva system, we found that Nur77 deficiency only modestly inhibited TRA-mediated clonal deletion in OT-I Rip-mOva chimeras. Furthermore, in polyclonal Bim-/- or Nur77-/- mice, we observed an increase in anergic phenotype CD4+ T cells, which may indicate an increase in self-specificities due to a block in clonal deletion. Collectively, these studies highlight potential differences in the molecular mechanisms of negative selection against UbA versus TRA, as well as of MHC class I versus MHC class II restricted thymocytes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".