Nitric Oxide–Induced Regulatory T Cells Inhibit Th17 but Not Th1 Cell Differentiation and Function
Bibliographic record
Abstract
NO is a free radical with pleiotropic functions. We have shown earlier that NO induces a population of CD4(+)CD25(+)Foxp3(-) regulatory T cells (NO-Tregs) that suppress the functions of CD4(+)CD25(-) effector T cells in vitro and in vivo. We report in this study an unexpected finding that NO-Tregs suppressed Th17 but not Th1 cell differentiation and function. In contrast, natural Tregs (nTregs), which suppressed Th1 cells, failed to suppress Th17 cells. Consistent with this observation, NO-Tregs inhibited the expression of retinoic acid-related orphan receptor γt but not T-bet, whereas nTregs suppressed T-bet but not retinoic acid-related orphan receptor γt expression. The NO-Treg-mediated suppression of Th17 was partially cell contact-dependent and was associated with IL-10. In vivo, adoptively transferred NO-Tregs potently attenuated experimental autoimmune encephalomyelitis. The disease suppression was accompanied by a reduction of Th17, but not Th1 cells in the draining lymph nodes, and a decrease in the production of IL-17, but an increase in IL-10 synthesis. Our results therefore demonstrate the differential suppressive function between NO-Tregs and nTregs and indicate specialization of the regulatory mechanism of the immune system.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".