CAR T <sub>reg</sub> cells mediate linked suppression and infectious tolerance in islet transplantation in mice
Bibliographic record
Abstract
Regulatory T cells (T reg cells) have potential as a cell-based therapy to prevent or treat transplant rejection and autoimmunity. Using a human leukocyte antigen (HLA)–A2-specific chimeric antigen receptor (A2-CAR), we previously showed that adoptive transfer of A2-CAR T reg cells can limit anti–HLA-A2 alloimmunity. However, it was unknown whether A2-CAR T reg cells could also limit immunity to autoantigens. Using a model of HLA-A2 + islet transplantation into immunodeficient nonobese diabetic mice, we investigated whether A2-CAR T reg cells could control hyperglycemia induced by diabetogenic BDC2.5 effector T cells. In mice transplanted with HLA-A2 + islets, A2-CAR T reg cells reduced BDC2.5 T cell engraftment, proliferation, and cytokine production and protected mice from diabetes. Islet tolerance was systemic, including protection of the HLA-A2 negative endogenous pancreas. Treated mice remained euglycemic even after removal of the HLA-A2 + islet graft and A2-CAR T reg cells. Thus, A2-CAR T reg cells can induce linked suppression and long-lasting tolerance to a distinct autoimmune antigen. Tolerance to the autoantigen does not require A2-CAR T reg persistence, indicating the presence of infectious tolerance. Overall, these data demonstrate that A2-CAR T reg cells have potential therapeutic use to simultaneously control both allo- and autoimmunity in islet transplantation.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".