Hepatitis C Virus Infection of Cultured Human Hepatoma Cells Causes Apoptosis and Pyroptosis in Both Infected and Bystander Cells
Bibliographic record
Abstract
Abstract Individuals infected with hepatitis C virus (HCV) are at high risk of developing progressive liver disease, including cirrhosis and hepatocellular carcinoma (HCC). How HCV infection causes liver destruction has been of significant interest for many years, and apoptosis has been proposed as one operative mechanism. In this study, we employed a tissue culture-adapted strain of HCV (JFH1T) to test effects of HCV infection on induction of programmed cell death (PCD) in Huh-7.5 cells. We found that HCV infection reduced the proliferation rate and induced caspase-3-mediated apoptosis in the infected cell population. However, in addition to apoptosis, we also observed infected cells undergoing caspase-1-mediated pyroptosis, which was induced by NLRP3 inflammasome activation. By co-culturing HCV-infected Huh-7.5 cells with an HCV-non-permissive cell line, we also demonstrated induction of both apoptosis and pyroptosis in uninfected cells. Bystander apoptosis, but not bystander pyroptosis, required cell-cell contact between infected and bystander cells. In summary, these findings provide new information on mechanisms of cell death in response to HCV infection. The observation that both apoptosis and pyroptosis can be induced in bystander cells extends our understanding of HCV-induced pathogenesis in the liver.
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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) | 0.002 | 0.001 |
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".