Avidity maturation of anti–citrullinated protein antibodies in rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: Anti-citrullinated protein antibodies (ACPAs) are highly specific for rheumatoid arthritis (RA) and are present years before the onset of symptoms. The avidity of autoantibodies can have a strong impact on their effector potency. This study was undertaken to analyze the avidity of ACPAs in serum samples obtained from ACPA-positive healthy individuals (predisease), patients with early disease, and patients with established RA as well as the avidity maturation over time in samples from healthy subjects who later developed RA. METHODS: We measured ACPA avidity in serum samples from ACPA-positive healthy individuals, symptomatic individuals, and patients with established RA in 5 collections from The Netherlands, Canada, and Austria. We determined the dynamics of avidity maturation of ACPAs from the predisease stage to established disease in 1 case from the native North American population and in 10 cases from a Dutch blood donor cohort. RESULTS: The overall ACPA response was characterized by low-avidity antibodies. Higher-avidity ACPAs were observed in symptomatic patients only, while low-avidity ACPAs were observed in both healthy subjects and patients. In longitudinal samples obtained from subjects prior to disease onset, ACPA avidity increased over time until disease onset. No further avidity maturation was observed after disease onset. CONCLUSION: Our findings indicate that avidity maturation of the ACPA response takes place prior to disease onset.
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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 | 0.001 | 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) | 0.001 | 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".