ISG15, a ubiquitin-like interferon-stimulated gene, promotes hepatitis C virus production in vitro: implications for chronic infection and response to treatment
Bibliographic record
Abstract
Upregulation of interferon (IFN)-stimulated genes (ISGs), including IFN-stimulated gene 15 (ISG15) and other members of the ISG15 pathway, in pre-treatment liver tissue of patients chronically infected with hepatitis C virus (HCV) is associated with subsequent treatment failure (pegylated IFN-alpha/ribavirin). This study assessed the effect of ISG15 on HCV production in vitro. The levels of ISG15 and of its conjugation to target proteins (ISGylation) were increased by plasmid transfection, but ISGylation was inhibited by small interfering RNA directed against the E1 activating enzyme, Ube1L, in Huh7.5 cells. Cells were infected with HCV FL-J6/JFH virus, and HCV RNA and viral titres were determined. Levels of both HCV RNA and virus increased when levels of ISG15 and ISGylation were increased, and decreased when ISGylation was inhibited. The effects of ISGylation on HCV were independent of upstream IFN signalling: IFN-alpha-induced ISG expression was not altered by Ube1L knockdown. Thus, although ISG15 has antiviral activity against most viruses, ISG15 promotes HCV production. HCV might exploit ISG15 as a host immune evasion mechanism, and this may in part explain how increased expression of ISGs, especially ISG15, correlates with subsequent IFN-based treatment failure.
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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 | 0.000 |
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".