Donor double‐negative Treg promote allogeneic mixed chimerism and tolerance
Bibliographic record
Abstract
Bone marrow (BM) transplantation is an efficient approach to develop donor-specific tolerance and prevent chronic rejection. Allogeneic BM transplantation is limited by donor T cell-mediated graft-versus-host disease, requirement of cytoreduction and high numbers of BM cells. In addition of these drawbacks, recent studies demonstrate that not only T cells, but also NK cells can mediate BM rejection, and long-term mixed chimerism depends on NK cell tolerance. Thus, NK cell is another potential barrier against engraftment of BM and an important target in efforts to induce transplant tolerance. We have previously identified a novel type of Treg with the phenotype TCRalphabeta+CD3+CD4-CD8- (double-negative, DN). We and others have demonstrated that DN-Treg can effectively suppress anti-donor T cell responses. In this study, we found that donor-derived DN-Treg can suppress NK cell-mediated allogeneic BM graft rejection in both parent-to-F1 and fully MHC-mismatched BM transplantation models. Perforin and FasL in DN-Treg play important roles in the suppression of NK cells. Furthermore, adoptive transfer of DN-Treg can promote a stable mixed chimerism and donor-specific tolerance without inducing graft-versus-host disease. These results demonstrate a potential approach to control innate immune responses and promote allogeneic BM engraftment.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".