B7-CTLA4 reverse signaling is responsible for regulatory T cell-induced suppression of dendritic cells (168.23)
Bibliographic record
Abstract
Abstract CD4+CD25+Foxp3+ regulatory T cells (Treg) are essential for maintaining immune tolerance and homeostasis. It has been shown that natural Treg can inhibit up-regulation of costimulatory molecules on dendritic cells (DC). However, the mechanism leading to this phenomenon has not been elucidated. Whether inducible Treg (iTreg) also possess this function has not been previously investigated. Here, we demonstrate that iTreg could inhibit LPS-induced DC maturation and mediate down-regulation of CD80 and CD86 on mature DC. This process is CTLA4-dependent as Treg isolated from CTLA4-/- mice did not down-modulate B7 molecules on DC. Furthermore, CTLA4Ig, but not CD28Ig, mimicked iTreg action. Down-regulation of CD80/CD86 was not due to endocytosis or protease-dependent shedding, but rather to a reverse signaling through B7. CTLA4Ig treatment decreased CD80 and CD86 transcription, as well as NFκB activity upon LPS stimulation. Interestingly, both CTLA4Ig and co-incubation with iTreg induced a profound STAT3 phosphorylation in DC, whereas no significant effect on the proximal NFκB pathway was observed. Inhibition of STAT3 activation partially abolished CTLA4Ig-induced CD80/CD86 down-modulation suggesting involvement of this molecule in the observed process. Our data reveal a novel signaling pathway by which Treg can suppress DC via reverse signaling, and may provide new opportunities for therapies targeting costimulatory pathways.
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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) | 0.003 | 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".