A novel helper-dependent adenovirus-based cell culture model for Hepatitis C virus replication and production
Bibliographic record
Abstract
BACKGROUND: By using the hepatitis C virus (HCV) genotype 2a JFH-1 or its chimeric strains, a HCV infection system has been previously developed through several methods- such as in vitro-transcribed JFH1-RNA transfection or stable transfection of the JFH1 cDNA into human hepatoma Huh-7 cell line or its derivatives. However, other reliable methods for delivery of the HCV genome into cells are still worth trying. The helper-dependent adenovirus (HDAd) is devoid of all viral coding sequences and has a package capacity of 37 kb, which is suitably large for the delivery of the HCV genome. Here we report a new method for delivery of the HCV genome into Huh-7 and HepG2 cells by using the HDAd vector. RESULTS: Our results demonstrated that the infection of Huh-7 cells with the HDAdJFH1 virus led to efficient HCV replication and virion production. We found that the HCV viral RNA levels could reach 107 copies per milliliter (ml) in the culture medium. HDAdJFH1-infected Huh-7 cells could be cultured for 8 passages with the culture medium remaining infectious for naïve Huh-7 cells throughout this period. This infection system proved effective for evaluating the anti-HCV effects of IFN-α in Huh-7 cells. Co-infection of HepG2 cells with the HDAdJFH1 and HDAdmiR-122 virus also resulted in HCV expression and replication. CONCLUSION: This is the first report of an HDAd-based strategy for HCV replication and production in vitro.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".