Apoptosis of biliary epithelial cells in primary biliary cirrhosis and primary sclerosing cholangitis
Bibliographic record
Abstract
BACKGROUND/AIMS: Primary biliary cirrhosis (PBC) is an autoimmune disease characterized by inflammatory destruction of small bile ducts. Primary sclerosing cholangitis (PSC) is a different, presumed autoimmune cholestatic liver disease where the bile ducts are also destroyed. In this study, apoptosis and portal triad inflammation in liver tissue from patients with PBC is examined and compared to that from patients with PSC and patients with normal liver. METHODS: Explanted liver tissue from patients with PBC and PSC and normal liver from patients with metastases to liver were examined. The liver samples were stained for apoptosis using the terminal deoxynucleotidyl triphosphate (TdT)-mediated deoxyuridine triphosphate nick end labelling (TUNEL) assay. The biliary epithelial cells (BEC) were then scored on the basis of their TUNEL stain and the degree of periductal inflammation. RESULTS: In PBC, apoptosis of BEC, as detected by the TUNEL assay, was significantly increased in the presence of inflammation. Regardless of the presence or absence of inflammation, the small bile ducts in PBC liver tissue exhibited greater evidence of apoptosis than did similar ducts from PSC or control livers. CONCLUSION: These findings suggest that in PBC, unlike PSC, the apoptosis of BEC in PBC is secondary to the invasion of inflammatory cells.
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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 | 0.001 | 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) | 0.002 | 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".