Reference standards for the detection of anti-mitochondrial and anti-rods/rings autoantibodies
Bibliographic record
Abstract
Abstract Background: Anti-mitochondrial antibodies (AMA) are found in >90% of primary biliary cholangitis patients. Anti-rods/rings antibodies (anti-RR) are most commonly associated with interferon-α and ribavirin treatment in hepatitis C patients. Clinical laboratories routinely screen for AMA and anti-RR using indirect immunofluorescence on HEp-2 cells (HEp-2-IFA). Therefore, we sought to establish reference materials for use in AMA and anti-RR testing. Methods: AMA-positive and anti-RR-positive human plasma samples (AMA-REF and RR-REF), identified as potential reference materials based on preliminary data, were further validated by multiple laboratories using HEp-2-IFA, immunoprecipitation (IP), western blotting, IP-western, line immunoassay (LIA), addressable laser bead immunoassay (ALBIA) and enzyme-linked immunosorbent assay (ELISA). Results: AMA-REF showed a strong positive cytoplasmic reticular/AMA staining pattern by HEp-2-IFA to ≥1:1280 dilution and positive signal on rodent kidney/stomach/liver tissue. AMA-REF reacted with E2/E3, E3BP, E1α and E1β subunits of the pyruvate dehydrogenase complex by IP and western blotting and was positive for AMA antigens by LIA, ALBIA and ELISA. RR-REF showed a strong positive rods and rings staining pattern by HEp-2-IFA to ≥1:1280 dilution. RR-REF reacted with inosine monophosphate dehydrogenase by IP, IP-western and ALBIA. RR-REF also produced a nuclear homogenous staining pattern by HEp-2-IFA, immunoprecipitated proteins associated with anti-U1RNP antibody and reacted weakly with histones, nucleosomes, Sm and nRNP/Sm by LIA. Conclusions: AMA-REF and RR-REF are useful reference materials for academic or commercial clinical laboratories to calibrate and establish internal reference standards for immunodiagnostic assays. AMA-REF and RR-REF are now available for free distribution to qualified laboratories through Plasma Services Group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".