Targeting Antibody-Mediated Rejection in the Setting of ABOIncompatible Infant Heart Transplantation: Graft Accommodation vs. B Cell Tolerance
Bibliographic record
Abstract
In order for ABO-incompatible organ transplantation to be performed successfully, the antibody response must be targeted. Aggressive strategies are usually required both to remove pre-existing antibodies directed at donor A/B antigens and to suppress further production of antibodies. If this can be accomplished in the short-term, graft accommodation of ABO-incompatible transplants may develop upon eventual re-accumulation of antibodies as the graft acquires resistance to antibody-mediated damage. In contrast to mature individuals, very young infants lack isohemagglutinins due to a natural lag in development of immunity to T cell-independent polysaccharide antigens. This delay in maturation permits a window of safety during which infants can receive ABO-incompatible grafts without the requirement for aggressive immunosuppressive strategies. We have recently demonstrated that ABO-incompatible heart transplantation performed during this stage of immaturity is followed by the spontaneous development of donor-specific B cell tolerance rather than graft accommodation, and that tolerance in this setting occurs by a cellular mechanism of antigen-specific B cell elimination. This finding is strikingly similar to the original descriptions of neonatal T cell tolerance in mice. Our data provide compelling justification that every effort should be made to include juvenile recipients routinely as subjects in tolerance research. Through understanding the mechanisms underlying tolerance in this setting, as with murine models of neonatal tolerance originally described by Medawar and colleagues, it may be possible to expand the potential applications of tolerance strategies to older patient populations.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".