THE STRUCTURE OF ANTI-GAL IMMUNOGLOBULIN GENES IN NA??VE AND STIMULATED GAL KNOCKOUT MICE
Bibliographic record
Abstract
BACKGROUND: Naturally occurring antibodies (Nabs) that bind to terminal galactose alpha1,3-galactose carbohydrate structures (Gal) are present in humans and Old World monkeys but are negatively regulated in other mammalian species because they express Gal epitopes on their cell surfaces. A Gal knockout mouse (Gal-/-) model, generated by homologous disruption of alpha1,3-galactosyltransferase gene, is capable of producing natural anti-Gal Abs. METHODS: To study the genetic control of the anti-Gal response, we have generated anti-Gal hybridomas from Gal-/- mice and analyzed VH genes of anti-Gal Abs from naïve animals and from mice stimulated by rat heterotopic heart transplantation. RESULTS: Six immunoglobulin (Ig)M anti-Gal hybridomas derived from naïve Gal-/- mice exhibited anti-Gal binding activity with some cross-reactivity to related carbohydrate structures. These naïve anti-Gal Abs used five different VH genes in a germline configuration. Anti-Gal IgM hybridomas isolated after a rat heterotopic heart xenograft (4 days) utilized germline VH gene segments from the VH7183 family and exhibited less cross-reactivity. In contrast to mice 4 days after xenograft, we have predominantly isolated IgG anti-Gal hybridomas from mice 21 days after rat heterotopic heart xenografts, indicating an isotype switch. Nine of the IgG anti-Gal hybridomas secreted IgG3 subclass and one produced IgG1. Sequence analysis of the VH gene usage from the induced anti-Gal IgG antibodies demonstrated a restricted gene utilization (VHJ606-V14A). CONCLUSION: Our results demonstrate that the anti-Gal response in naïve Gal-/- mice is encoded by multiple germline progenitors. In response to a xenograft, the induced anti-Gal Abs exhibited a restricted gene usage and somatic mutations, indicating a positive selection.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".