Inhibition of Graft-Versus-Host Disease by Double-Negative Regulatory T Cells
Bibliographic record
Abstract
Pretransplant infusion of lymphocytes that express a single allogeneic MHC class I Ag has been shown to induce tolerance to skin and heart allografts that express the same alloantigens. In this study, we demonstrate that reconstitution of immunoincompetent mice with spleen cells from MHC class I L(d)-mismatched donors does not cause graft-vs-host disease (GVHD). Recipient mice become tolerant to skin allografts of lymphocyte donor origin while retaining immunity to third-party alloantigens. The mechanism involves donor-derived CD3(+)CD4(-)CD8(-) double-negative T regulatory (DN Treg) cells, which greatly increase and form the majority of T lymphocytes in the spleen of recipient mice. DN Treg cells isolated from tolerant recipient mice can suppress the proliferation of syngeneic antihost CD8(+) T cells in vitro. Furthermore, we demonstrate that DN Treg cells can be generated in vitro by stimulating them with MHC class I L(d)-mismatched lymphocytes. These in vitro generated L(d)-specific DN Treg cells are able to down-regulate the activity of antihost CD8(+) T cells in vitro by directly killing activated CD8(+) T cells. Moreover, infusing in vitro generated L(d)-mismatched DN Treg cells prevented the development of GVHD caused by allogeneic CD8(+) T cells. Together these data demonstrate that infusion of single MHC class I locus-mismatched lymphocytes may induce donor-specific transplantation tolerance through activation of DN Treg cells, which can suppress antihost CD8(+) T cells and prevent the development of GVHD. This finding indicates that using single class I locus-mismatched grafts may be a viable alternative to using fully matched grafts in bone marrow transplantation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".