Induction of Xenogeneic Neonatal Tolerance to Transgenic Human Leukocyte Antigen Class I Grafts
Bibliographic record
Abstract
BACKGROUND: The immune response against xenografts is vigorous and poorly controlled with conventional immunosuppressants. Therefore, success in xenotransplantation will depend on developing additional approaches such as induction of immunologic unresponsiveness or tolerance. Although classic protocols of neonatal tolerance induction in mice are very tolerogenic in many allogeneic models, they have generally failed in xenogeneic models. The purpose of these studies was to determine whether failure results from an intrinsic property of xenogenic major histocompatibility complex (MHC) molecules themselves or, instead, is caused by some limitation in species-specific molecular interactions distinct from the polymorphic domains of xenogenic MHC molecules. METHODS: Our approach was to test the ability of lymphoid cells from a transgenic (Tg) mouse donor expressing a xeno-MHC class I molecule encoding the polymorphic alpha1/alpha2 for human leukocyte antigen (HLA)-B7 to induce neonatal tolerance in non-Tg syngeneic C57BL/6 recipients. Because the donor and recipient strains are genetically identical (C57BL/6, H-2b) except for Tg human MHC HLA-B7, any species-specific molecular incompatibility in this mouse anti-human class I xeno-combination that could potentially interfere with induction of tolerance has been eliminated. RESULTS: Our results show that HLA-B7 Tg-, but not C57BL/6 syngeneic-, injected neonates were unresponsive as adults to HLA-B7-expressing target cells in vitro and specifically accepted HLA-B7-expressing Tg skin grafts. In addition, neonatal injection of donor cells resulted in peripheral chimerism. CONCLUSIONS: These experiments demonstrate that, as long as species-specific molecular interactions are maintained, recognition of the polymorphic domains of xenogeneic MHC does not represent a barrier to neonatal tolerance induction.
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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) | 0.000 | 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".