Epistatic Suppression of Fatal Autoimmunity in New Zealand Black Bicongenic Mice
Bibliographic record
Abstract
Numerous mapping studies have implicated genetic intervals from lupus-prone New Zealand Black (NZB) chromosomes 1 and 4 as contributing to lupus pathogenesis. By introgressing NZB chromosomal intervals onto a non-lupus-prone B6 background, we determined that: NZB chromosome 1 congenic mice (denoted B6.NZBc1) developed fatal autoimmune-mediated kidney disease, and NZB chromosome 4 congenic mice (denoted B6.NZBc4) exhibited a marked expansion of B1a and NKT cells in the surprising absence of autoimmunity. In this study, we sought to examine whether epistatic interactions between these two loci would affect lupus autoimmunity by generating bicongenic mice that carry both NZB chromosomal intervals. Compared with B6.NZBc1 mice, bicongenic mice demonstrated significantly decreased mortality, kidney disease, Th1-biased IgG autoantibody isotypes, and differentiation of IFN-γ-producing T cells. Furthermore, a subset of bicongenic mice exhibited a paucity of CD21(+)CD1d(+) B cells and an altered NKT cell activation profile that correlated with greater disease inhibition. Thus, NZBc4 contains suppressive epistatic modifiers that appear to inhibit the development of fatal NZBc1 autoimmunity by promoting a shift away from a proinflammatory cytokine profile, which in some mice may involve NKT cells.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".