Modulation of Hepatitis C Virus RNA Accumulation and Translation by DDX6 and miR-122 Are Mediated by Separate Mechanisms
Bibliographic record
Abstract
DDX6 and other P-body proteins are required for efficient replication of Hepatitis C Virus (HCV) by unknown mechanisms. DDX6 has been implicated in miRNA induced gene silencing, and since efficient HCV replication and translation relies on the cellular microRNA, miR-122, we hypothesized that DDX6 had a role in the mechanism of action of miR-122. However, by using multiple HCV translation and replication assays we have found this is not the case. DDX6 silencing decreased HCV replication and translation, but did not affect the ability of miR-122 to stimulate HCV translation or promote HCV RNA accumulation. In addition, the negative effect of DDX6 silencing on HCV replication and translation was not dependent on miR-122 association with the HCV genome. Thus, DDX6 does not have a role in the activity of miR-122, and it appears that DDX6 and miR-122 modulate HCV through distinct pathways. This effect was seen in both Huh7.5 cells and in Hep3B cells, indicating that the effects are not cell type specific. Since infections by other viruses in the Flaviviridae family, including Dengue and West Nile Virus, also disrupt P-bodies and are regulated by DDX6, we speculate that DDX6 may have a common function that support the replication of several Flaviviruses.
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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 | 0.001 | 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".