The Anti-mutated Citrullinated Vimentin Response Classifies Patients with Rheumatoid Arthritis into Broad and Narrow Responders
Bibliographic record
Abstract
OBJECTIVE: Autoantibodies against citrullinated peptide antigens (ACPA) are routinely determined to diagnose rheumatoid arthritis (RA) and are predictive of a more severe course of the disease. We here set out to address an involvement of ACPA in the pathogenesis of RA and investigated the recognition pattern of antibodies against 2 citrullinated antigens in more detail. METHODS: The sera of 77 patients fulfilling the American College of Rheumatology criteria for RA were analyzed for subclass titers of anti-mutated citrullinated vimentin (MCV) and anticyclic citrullinated peptide (CCP) antibodies by combining subclass specific detection antibodies with commercially available CCP and MCV ELISA plates. Cross-reactivities between anti-MCV and anti-CCP antibodies were detected using a sequential ELISA system. RESULTS: IgG1, IgG3, and IgG4 titers among anti-MCV and anti-CCP antibodies correlated significantly. Cross-reactivity of MCV-specific antibodies against CCP could be detected in 8 of 16 patients' sera; however, cross-binding of MCV-specific IgG4 was weaker compared to total IgG. CONCLUSION: The inherent capacity of IgG4 to exchange F(ab) arms provides insight into the anti-MCV antibody diversity and suggests a classification of ACPA positive patients into broad and narrow responders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".