Fas Polymorphisms Influence Susceptibility to Autoimmune Hepatitis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Genetic factors associated with autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), immune-mediated chronic inflammatory liver diseases of unknown etiology, remain to be elucidated. Polymorphisms of the gene encoding Fas have been linked to a variety of autoimmune diseases. We hypothesized that Fas gene polymorphisms might be genetic markers for AIH and PBC. METHODS: To determine the frequency and significance of Fas polymorphisms in patients with AIH and PBC, 74 Japanese AIH patients, 98 Japanese PBC patients, and 132 ethnically matched control subjects were investigated by the use of the Taqman assay. RESULTS: We found significant differences between AIH patients and controls in allele frequencies of Fas-670 (p=0.009), Fas IVS (intervening sequence) 2nt176 (p=0.018), Fas IVS3nt46 (p=0.031), and Fas IVS5nt82 (p=0.013) polymorphisms. Haplotype analysis revealed that one of the haplotypes, GATGC, was associated with increased AIH prevalence. On the other hand, we found no statistically significant differences between PBC patients and controls in allele frequencies of the Fas polymorphisms genotyped in this study. CONCLUSIONS: These results indicate a genetic link of Fas polymorphisms to the development of AIH. Further studies are needed to determine the genetic factors contributing to the development of AIH.
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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 | 0.000 | 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) | 0.004 | 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".