5′-Triphosphate-Short Interfering RNA: Potent Inhibition of Influenza A Virus Infection by Gene Silencing and RIG-I Activation
Bibliographic record
Abstract
Limited protection of current vaccines and antiviral drugs against influenza A virus infection underscores the urgent need for development of novel anti-influenza virus interventions. While short interfering RNA (siRNA) has been shown to be able to inhibit influenza virus infection in a gene-specific manner, activation of the retinoic acid-inducible gene I protein (RIG-I) pathway has an antiviral effect in a non-gene-specific mode. In this study, we designed and tested the anti-influenza virus effect of a short double-stranded RNA, designated 3p-mNP1496-siRNA, that possesses dual functions: an siRNA-targeting influenza NP gene and an agonist for RIG-I activation. This double-stranded siRNA possesses a triphosphate group at the 5' end of the sense strand and is blunt ended. Our study showed that 3p-mNP1496-siRNA could potently inhibit influenza A virus infection both in cell culture and in mice. The strong inhibition effect was attributed to its siRNA function as well as its ability to activate the RIG-I pathway. To the best of our knowledge, this is the first report that the combination of siRNA and RIG-I pathway activation can synergistically inhibit influenza A virus infection. The development of such dual functional RNA molecules will greatly contribute to the arsenal of tools to combat not only influenza viruses but also other important viral pathogens.
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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 | 0.000 |
| 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) | 0.000 | 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".