Adoptive transfer of double negative T regulatory cells induces B‐cell death in vivo and alters rejection pattern of rat‐to‐mouse heart transplantation
Bibliographic record
Abstract
BACKGROUND: Antibody-mediated hyperacute and acute graft rejection are major obstacles in achieving long-term graft survival in xenotransplantation. It is well documented that regulatory T (Treg) cells play a very important role in regulating immune responses to self and non-self antigens. Our previous studies have shown that TCRalphabeta+CD3+CD4-CD8- (double negative, DN)-Treg cells can suppress anti-donor T-cell responses and prolong graft survival in allo- and xenotransplantation models. We have demonstrated that DN-Treg cells can induce B-cell apoptosis in vitro through a perforin-dependent pathway. METHODS: B6 mice received rat heart grafts, followed by 14 days of LF15-0195 treatment. Some mice received Lewis rat cell activated DN-Treg cells after LF treatment. DN-Treg cells, purified from perforin-/- mice and from B6 mice pre-immunized with third party rat cells, were used as controls. RESULTS: In this study, we investigated the possibility that adoptive transfer of xenoreactive DN-Treg cells could suppress B cells in vivo, thus prolonging xenograft survival. We found that apoptotic death of B cells significantly increased after adoptive transfer of DN-Treg cells. In addition, anti-donor IgG subtypes were significantly inhibited in the DN-Treg cell-treated group, in which the rejection pattern was altered towards cellular-mediated rejection rather than antibody-mediated acute vascular rejection. However, perforin-deficient DN-Treg cells failed to induce B-cell death and to prolong heart graft survival, indicating a perforin-dependent mechanism contributes to B-cell death in vivo. CONCLUSIONS: This study suggests that adoptive transfer of xenoreactive DN-Treg cells can inhibit B-cell responses in vivo. DN-Treg cells may be valuable in controlling B-cell responses in xenotransplantation.
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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".