Both Infiltrating Regulatory T Cells and Insufficient Antigen Presentation Are Involved in Long-Term Cardiac Xenograft Survival
Bibliographic record
Abstract
We have previously shown that pretransplant donor lymphocyte infusion (DLI) together with transient depletion of CD4(+) T cells could induce permanent rat-to-mouse heart graft survival, whereas depleting CD4(+) T cells alone failed to do so. In this study, we investigated the mechanism leading to long-term xenograft survival. We found that peripheral CD4(+) T cells from DLI/anti-CD4-treated mice could mount rat heart graft rejection after adoptive transfer into B6 CD4(-/-) mice. Infusing donor-Ag-loaded mature dendritic cells (DCs) could break long-term cardiac xenograft survival in DLI/anti-CD4-treated mice. Interestingly, when the number and phenotype of graft-infiltrating cells were compared between anti-CD4- and DLI/anti-CD4-treated groups, we observed a significant increase in both the number and suppressive activity of alphabeta-TCR(+)CD3(+)CD4(-)CD8(-) double negative regulatory T cells and decrease in the numbers of CD4(+) and CD8(+) T cells in the xenografts of DLI/anti-CD4-treated mice. Moreover, there was a significant reduction in MHC class II-high DCs within the xenografts of DLI/anti-CD4-treated recipients. DCs isolated from the xenografts of anti-CD4- but not DLI/anti-CD4-treated recipients could stimulate CD4(+) T cell proliferation. Our data indicate that functional anti-donor T cells are present in the secondary lymphoid organs of the mice that permanently accepted cardiac xenografts. Their failure to reject xenografts is associated with an increase in double negative regulatory T cells as well as a reduction in Ag stimulation by DCs found within grafts. These findings suggest that local regulatory mechanisms need to be taken into account to control anti-xenograft T cell responses.
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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) | 0.001 | 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".