Double negative <scp>T</scp>reg cells promote nonmyeloablative bone marrow chimerism by inducing <scp>T</scp>‐cell clonal deletion and suppressing <scp>NK</scp> cell function
Bibliographic record
Abstract
The establishment of immune tolerance and prevention of chronic rejection remain major goals in clinical transplantation. In bone marrow (BM) transplantation, T cells and NK cells play important roles for graft rejection. In addition, graft-versus-host-disease (GVHD) remains a major obstacle for BM transplantation. In this study, we aimed to establish mixed chimerism in an irradiation-free condition. Our data indicate that adoptive transfer of donor-derived T-cell receptor (TCR) αβ(+) CD3(+) CD4(-) CD8(-) NK1.1(-) (double negative, DN) Treg cells prior to C57BL/6 to BALB/c BM transplantation, in combination with cyclophosphamide, induced a stable-mixed chimerism and acceptance of C57BL/6 skin allografts but rejection of third-party C3H (H-2k) skin grafts. Adoptive transfer of CD4(+) and CD8(+) T cells, but not DN Treg cells, induced GVHD in this regimen. The recipient T-cell alloreactive responsiveness was reduced in the DN Treg cell-treated group and clonal deletions of TCRVβ2, 7, 8.1/2, and 8.3 were observed in both CD4(+) and CD8(+) T cells. Furthermore, DN Treg-cell treatment suppressed NK cell-mediated BM rejection in a perforin-dependent manner. Taken together, our results suggest that adoptive transfer of DN Treg cells can control both adoptive and innate immunities and promote stable-mixed chimerism and donor-specific tolerance in the irradiation-free regimen.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".