Late onset of development of natural anti-nonGal antibodies in infant humans and baboons: implications for xenotransplantation in infants
Bibliographic record
Abstract
If an ABO-incompatible heart is transplanted into an infant before natural antibodies have developed to the specific donor carbohydrate A/B antigen(s), then B-cell tolerance to the donor A/B antigen is achieved, and these antibodies never develop. Anti-carbohydrate antibodies play a role in the rejection of wild type (WT) and alpha1,3-galactosyltransferase gene-knockout (GT-KO) pig xenografts. We investigated development of these antibodies in infant baboons and humans. Serum samples from infant baboons (n = 42) and humans (n = 42) were tested by flow cytometry for immunoglobulin M and immunoglobulin G binding to peripheral blood mononuclear cells from WT and GT-KO pigs, and for complement-dependent cytotoxicity. The presence of anti-blood group antibodies was tested in baboon serum. In infant baboons and humans, cytotoxic anti-Galalpha1,3Gal antibodies develop during the first 3 months, and steadily increase with age, whereas cytotoxic anti-nonGal antibodies are either absent or minimal in the majority of cases throughout the first year of life. Anti-blood group antibodies were not detected before 16 weeks of age. Our data suggest GT-KO pig organ/cell transplants could be carried out in early infancy in the absence of preformed cytotoxic anti-nonGalalpha1,3Gal antibodies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".