Sex, T Cells, and the Microbiome in Natural ABO Antibody Production in Mice
Bibliographic record
Abstract
BACKGROUND: "Natural" ABO antibodies (Abs) are produced without known exposure to A/B carbohydrate antigens, posing significant risks for hyperacute rejection during ABO-incompatible transplantation. We investigated anti-A "natural" ABO antibodies versus intentionally induced Abs with regard to the need for T-cell help, the impact of sex, and stimulation by the microbiome. METHODS: Anti-A was measured by hemagglutination assay of sera from untreated C57BL/6 wild-type (WT) or T cell-deficient mice of both sexes. Human ABO-A reagent blood cell membranes were injected intraperitoneally to induce anti-A Abs. The gut microbiome was eliminated by maintenance of mice in germ-free housing. RESULTS: Compared with WT mice, CD4 + T-cell knockout (KO), major histocompability complex-II KO, and αβ/γδ T-cell receptor KO mice produced much higher levels of anti-A nAbs; females produced dramatically more anti-A nAbs than males, rising substantially with puberty. Sensitization with human ABO-A reagent blood cell membranes did not induce additional anti-A in KO mice, unlike WT. Sex-matched CD4 + T-cell transfer significantly suppressed anti-A nAbs in KO mice and rendered mice responsive to A-sensitization. Even under germ-free conditions, WT mice of several strains produced anti-A nAbs, with significantly higher anti-A nAbs levels in females than males. CONCLUSIONS: Anti-A nAbs were produced without T-cell help, without microbiome stimulation, in a sex- and age-dependent manner, suggestive of a role for sex hormones in regulating anti-A nAbs. Although CD4 + T cells were not required for anti-A nAbs, our findings indicate that T cells regulate anti-A nAb production. In contrast to anti-A nAbs, induced anti-A production was T-cell dependent without a sex bias.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".