Identification and characterization of IgG4-associated autoimmune hepatitis
Bibliographic record
Abstract
BACKGROUND: Autoimmune hepatitis (AIH) and autoimmune pancreatitis (AIP) share clinical and pathological features such as high serum levels of immunoglobulin (Ig) G and autoantibodies, and lymphoplasmacytic infiltration, suggesting the presence of common immunological abnormalities. However, little is known about the possible involvement of IgG4, a hallmark of AIP, in AIH. AIMS: In this study, we examined whether the IgG4 response contributes to the histopathological and clinical findings in AIH. METHODS: Liver sections from 26 patients with AIH, 10 patients with primary biliary cirrhosis (PBC), three patients with primary sclerosing cholangitis (PSC) and 20 chronic hepatitis patients with hepatitis C virus (HCV) infection were immunostained for IgG4. We investigated the relationship among the histopathology, the responses to steroid therapy and the IgG4 staining. RESULTS: Nine of the 26 liver specimens from patients with AIH showed positive staining for IgG4 whereas none of the 10 samples from patients with PBC, the three samples from patients with PSC or the 20 samples from patients with HCV hepatitis were positive. Patients with IgG4-positive AIH also showed increased serum levels of IgG. The numbers of T cells, B cells and plasma cells were significantly increased in the livers of patients with IgG4-positive AIH as compared with those patients with IgG4-negative AIH. Patients with IgG4-positive AIH also showed a marked response to prednisolone therapy. CONCLUSIONS: AIH may be classified into either an IgG4-associated type or an IgG4 non-associated type with the former showing a marked response to prednisolone treatment.
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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 | 0.000 |
| 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".