Revisiting the specificity of the MHC class II transactivator CIITA <i>in vivo</i>
Bibliographic record
Abstract
CIITA is a master regulatory factor for the expression of MHC class II (MHC-II) and accessory genes involved in Ag presentation. It has recently been suggested that CIITA also regulates numerous other genes having diverse functions within and outside the immune system. To determine whether these genes are indeed relevant targets of CIITA in vivo, we studied their expression in CIITA-transgenic and CIITA-deficient mice. In contrast to the decisive control of MHC-II and related genes by CIITA, nine putative non-MHC target genes (Eif3s2, Kpna6, Tap1, Yars, Col1a2, Ctse, Ptprr, Tnfsf6 and Plxna1) were found to be CIITA independent in all cell types examined. Two other target genes, encoding IL-4 and IFN-gamma, were indeed found to be up- and down-regulated, respectively, in CIITA-transgenic CD4(+) T cells. However, there was no correlation between MHC-II expression and this Th2 bias at the level of individual transgenic T cells, indicating an indirect control by CIITA. These results show that MHC-II-restricted Ag presentation, and its indirect influences on T cells, remains the only pathway under direct control by CIITA in vivo. They also imply that precisely regulated MHC-II expression is essential for maintaining a proper Th1-Th2 balance.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".