Direct Alloreactivity Is More Susceptible to Regulation by Natural Regulatory T Cells Than Indirect Alloreactivity
Bibliographic record
Abstract
The contribution of natural CD4(+)CD25(+) regulatory T cells (nTregs) in controlling graft rejection and the mechanism used remain controversial. Using the duality of the 2.102 TCR Ag recognition, we were able to study, for the first time to our knowledge, the involvement of nTregs in the two pathways of allorecognition in a murine adoptive transfer model in which TCR-transgenic nTregs were or were not depleted before transplantation. We show that nTregs used at a physiological ratio were able to delay graft rejection after direct alloreactivity by controlling proliferation and differentiation of alloreactive CD4(+) conventional T cells in draining lymph nodes. In contrast, similar results were found in the indirect alloreactivity pathway only when nTregs were used in high numbers. In the latter pathway, nTregs used at a physiological ratio failed to delay graft rejection and to control proliferation of conventional T cells. These results support recent therapeutic approaches aimed at producing and using in vitro Ag-specific Foxp3(+) nTregs to control graft rejection in transplantation. Finally, late inhibition of Th1 differentiation was shown in indirect alloreactivity, but this suppression could also be mediated by Foxp3(+)-induced Tregs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".