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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

2000· article· en· W1994703016 on OpenAlexafffund
Joan Wither, Andrew D. Paterson, Brian Vukusic

Bibliographic record

VenueEuropean Journal of Immunology · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsCentre for Addiction and Mental HealthToronto Western Hospital
FundersMedical Research CouncilArthritis Society
KeywordsBiologyImmunologyB cellMarginal zoneImmune systemAntibodyImmunoglobulin DPopulationAutoantibodyMolecular biology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.207
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations72
Published2000
Admission routes2
Has abstractyes

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