Diagnostic Utility of Anticarbamylated Protein Antibodies as Measured Using Carbamylated Fetal Calf Serum
Bibliographic record
Abstract
To the Editor: Rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA) are important biomarkers in the diagnosis of rheumatoid arthritis (RA), but leave a gap of about 30–50% seronegative RA, which drives the demand for novel biomarkers. In 2011 a novel autoantibody system, anticarbamylated protein (anti-CarP) antibodies, was described in the sera of patients with RA1. In contrast to enzyme-mediated protein citrullination, carbamylation is a chemical reaction whereby cyanate converts lysine into homocitrulline1, a protein modification that is chemically similar to citrulline (1 CH2 longer side chain)2. Most studies on anti-CarP antibodies have used an ELISA based on carbamylated fetal calf serum (Ca-FCS) and accordingly a complex mixture of carbamylated proteins as the antigen(s)1,2. Although many clinical observations have been reported, precise information on the antigenic targets of anti-CarP antibodies is limited. Importantly, anti-CarP antibodies have been detected in both ACPA-positive and ACPA-negative RA patients, suggesting that they might represent an important test in the diagnosis of RA1,2. A recent metaanalysis estimated the sensitivity, specificity, and OR of … Address correspondence to Dr. M. Mahler, Inova Diagnostics, 9900 Old Grove Road, San Diego, California 32131-1638, USA. E-mail: mmahler{at}inovadx.com or m.mahler.job{at}web.de.
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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 | 0.010 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".