ArticleMediators of inflammation2015
Altered viral replication and cell responses by inserting microRNA recognition element into PB1 in pandemic influenza A virus (H1N1) 2009.
Article in Mediators of inflammation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
- Review
- Article
- MicroRNA let-7 and viral infections: focus on mechanisms of action.Cellular & molecular biology letters · 2022Review
- Review
- DisCoVering potential candidates of RNAi-based therapy for COVID-19 using computational methods.PeerJ · 2021Article
- MiRNA Targeted NP Genome of Live Attenuated Influenza Vaccines Provide Cross-Protection against a Lethal Influenza Virus Infection.Vaccines · 2020Article
- Down-Regulation of miR-378d Increased Rab10 Expression to Help Clearance ofFrontiers in cellular and infection microbiology · 2020Article
- Genetic, Molecular, and Pathogenic Characterization of the H9N2 Avian Influenza Viruses Currently Circulating in South China.Viruses · 2019Article
- Article
- Endogenous Cellular MicroRNAs Mediate Antiviral Defense against Influenza A Virus.Molecular therapy. Nucleic acids · 2018Article
- Potential Role of MicroRNAs in the Regulation of Antiviral Responses to Influenza Infection.Frontiers in immunology · 2018Review
- MicroRNA-134 regulates poliovirus replication by IRES targeting.Scientific reports · 2017Article
- The Clinical Application of MicroRNAs in Infectious Disease.Frontiers in immunology · 2017Review
- Involvement of Host Non-Coding RNAs in the Pathogenesis of the Influenza Virus.International journal of molecular sciences · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective. MicroRNAs (miRNAs) are endogenous noncoding RNAs that spatiotemporally modulate mRNAs in a posttranscriptional manner. Engineering mutant viruses by inserting cell-specific miRNA recognition element (MRE) into viral genome may alter viral infectivity and host responses in vital tissues and organs infected with pandemic influenza A virus (H1N1) 2009 (H1N1pdm). Methods. In this study, we employed reverse genetics approach to generate a recombinant H1N1pdm with a cell-specific miRNA target sequence inserted into its PB1 genomic segment to investigate whether miRNAs are able to suppress H1N1pdm replication. We inserted an MRE of microRNA-let-7b (miR-let-7b) into the open reading frame of PB1 to test the feasibility of creating a cell-restricted H1N1pdm virus since let-7b is abundant in human bronchial epithelial cells. Results. miR-let-7b is rich in human bronchial epithelial cells (HBE). Incorporation of the miR-let-7b-MRE confers upon the recombinant H1N1pdm virus susceptibility to miR-let-7b targeting, suggesting that the H1N1pdm and influenza A viruses can be engineered to exert the desired replication restrictive effect and decrease infectivity in vital tissues and organs. Conclusions. This approach provides an additional layer of biosafety and thus has great potential for the application in the rational development of safer and more effective influenza viral vaccines.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.