Autoantibodies to GW bodies and other autoantigens in primary biliary cirrhosis
Bibliographic record
Abstract
Autoantibodies to intracellular targets in mitochondria and nuclei are serological hallmarks of primary biliary cirrhosis (PBC). One of the most recently identified cellular targets of PBC autoantibodies is a novel cytoplasmic structure referred to as GW bodies [GWB, G (glycine) W (tryptophan)-containing bodies (GWB)]. GWB are indentified as discrete cytoplasmic domains that are involved in mRNA processing via the RNA interference (RNAi) pathway. Key components of GWB include the proteins GW182, Ago2, RNA-associated protein 55 (RAP55) and Ge-1/Hedls. The primary objective was to study the frequency and clinical association of antibodies directed to GWB components, in 109 PBC patients. Autoantibodies to mitochondrial antigen-pyruvate dehydrogenase complex (M2), branched-chain 2-oxo-acid dehydrogenase complex and 2-oxo glutarate dehydrogenase complex (3E-BPO), gp210, sp100, promyelocytic leukaemia cell antigen (PML) and liver kidney microsomal-1 antigen (LKM-1) were detected by a line immunoassay and antibodies to GWB (GW182, RAP55, Ge-1, GW2, GW3) and glutamate receptor interacting protein (GRIP)-associated protein-1 (GRASP-1), by an addressable laser bead immunoassay (ALBIA). The most common GWB autoantigen targets were: RAP55-28%, GW182-12%, GW2-2% and antibodies to GRASP-1-17%. By comparison, the frequency of reactivity to established PBC autoantigens was: gp210, 27%; sp100, 27% and PML, 17%. None of the autoantibodies were associated with differences in Mayo risk score or liver decompensation. This study is the first study to show that antibodies to RAP55, GW182 and GRASP-1 are the most common GWB targets in PBC.
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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 | 0.002 | 0.001 |
| 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".