Hepatitis C Virus Replicons Escape RNA Interference Induced by a Short Interfering RNA Directed against the NS5b Coding Region
Bibliographic record
Abstract
RNA interference represents an exciting new technology that could have therapeutic applications for the treatment of viral infections. Hepatitis C virus (HCV) is a major cause of chronic liver disease and affects over 270 million individuals worldwide. The HCV genome is a single-stranded RNA that functions as both an mRNA and a replication template, making it an attractive target for therapeutic approaches using short interfering RNA (siRNA). We have shown previously that double-stranded siRNA molecules designed to target the HCV genome block gene expression and RNA synthesis from hepatitis C replicons propagated in human liver cells. However, we now show that this block is not complete. After several treatments with a highly effective siRNA, we have shown growth of replicon RNAs that are resistant to subsequent treatment with the same siRNA. However, these replicon RNAs were not resistant to siRNA targeting another part of the genome. Sequence analysis of the siRNA-resistant replicons showed the generation of point mutations within the siRNA target sequence. In addition, the use of a combination of two siRNAs together severely limited escape mutant evolution. This suggests that RNA interference activity could be used as a treatment to reduce the devastating effects of HCV replication on the liver and the use of multiple siRNAs could prevent the emergence of resistant viruses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".