Genetic dissection of B cell traits in New Zealand black mice. The expanded population of B cells expressing up-regulated costimulatory molecules shows linkage toNba2
Bibliographic record
Abstract
B cell abnormalities are a prominent feature of the immunologic derangement in NZB and NZB / W mice. We recently demonstrated that these mice have an increased proportion of splenic B cells expressing B7.1 and elevated levels of B7.2 and ICAM-1 that possess the characteristics of marginal zone B cells (CD23(low / -) CD5(-) CD44(hi) CD24(hi) IgD(- / low) IgM(hi)) and are found as early as 4 - 6 weeks of age. These findings suggest that activated B cells in NZB and NZB / W mice could serve a costimulatory function leading to activation of autoreactive T cells. However, it remains unclear whether there is any association between B abnormalities and nephritis in these mice. Here we have used genetic mapping techniques to address this issue. We show that increases in the proportion of B cells expressing costimulatory molecules, serum IgM levels, the number of IgM ELISpots, and IgG anti-single-stranded (ss) DNA antibody production, are significantly associated with a chromosomal region that overlaps with Nba2, a genetic locus previously linked to nephritis. Based on these findings we propose that immune mechanisms leading to polyclonal B cell activation and up-regulation of costimulatory molecules in these mice play a central role in the loss of tolerance that leads to production of pathogenic autoantibodies.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".