Hepadnaviral infection augments hepatocyte cytotoxicity mediated by both CD95 ligand and perforin pathways
Bibliographic record
Abstract
BACKGROUND/AIM: Recently, we documented that hepatocytes can eliminate contacted cells via the CD95 ligand (CD95L)-CD95 pathway and that they are also equipped in perforin and granzyme B and can eradicate other cells via the granule exocytosis mechanism. The aim of this study was to assess whether hepadnaviral infection modifies hepatocyte-mediated cell killing. METHODS: Primary hepatocytes from woodchucks with progressing or resolved hepadnaviral hepatitis and hepatocyte lines transfected with woodchuck hepatitis virus (WHV) genes were examined for cytotoxic effector activity against cell targets susceptible to CD95L and/or perforin-dependent killing. Hepatocytes from healthy animals served as controls. RESULTS: Actively progressing and resolved hepadnaviral hepatitis is associated with a significantly greater capacity of hepatocytes to kill contacted cells. Both hepatocyte CD95L- and perforin-dependent cytotoxicity were augmented. Hepatocytes transfected with WHV X gene, but not those with complete WHV genome or virus envelope or core gene, transcribed significantly more CD95L and perforin and killed cell targets more efficiently. Exposure to interferon-gamma profoundly enhanced hepatocyte cell killing. CONCLUSIONS: Hepatocyte cytotoxic potential is significantly augmented during and following resolution of active hepadnaviral hepatitis. Hepatocyte cytotoxic activity may contribute to both liver physiological functions and the pathogenesis and progression of liver disease, including viral hepatitis.
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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 | 0.000 | 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) | 0.001 | 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".