↓ Skip to main content

Inhibiting avian influenza virus shedding using a novel RNAi antiviral vector technology: proof of concept in an avian cell model

Overview of attention for article published in AMB Express, February 2016
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

2 X users
1 patent
2 Facebook pages


6 Dimensions

Readers on

34 Mendeley
Inhibiting avian influenza virus shedding using a novel RNAi antiviral vector technology: proof of concept in an avian cell model
Published in
AMB Express, February 2016
DOI 10.1186/s13568-016-0187-y
Pubmed ID

Lyndsey M. Linke, Jeffrey Wilusz, Kristy L. Pabilonia, Johannes Fruehauf, Roberta Magnuson, Francisco Olea-Popelka, Joni Triantis, Gabriele Landolt, Mo Salman


Influenza A viruses pose significant health and economic threats to humans and animals. Outbreaks of avian influenza virus (AIV) are a liability to the poultry industry and increase the risk for transmission to humans. There are limitations to using the AIV vaccine in poultry, creating barriers to controlling outbreaks and a need for alternative effective control measures. Application of RNA interference (RNAi) techniques hold potential; however, the delivery of RNAi-mediating agents is a well-known obstacle to harnessing its clinical application. We introduce a novel antiviral approach using bacterial vectors that target avian mucosal epithelial cells and deliver (small interfering RNA) siRNAs against two AIV genes, nucleoprotein (NP) and polymerase acidic protein (PA). Using a red fluorescent reporter, we first demonstrated vector delivery and intracellular expression in avian epithelial cells. Subsequently, we demonstrated significant reductions in AIV shedding when applying these anti-AIV vectors prophylactically. These antiviral vectors provided up to a 10,000-fold reduction in viral titers shed, demonstrating in vitro proof-of-concept for using these novel anti-AIV vectors to inhibit AIV shedding. Our results indicate this siRNA vector technology could represent a scalable and clinically applicable antiviral technology for avian and human influenza and a prototype for RNAi-based vectors against other viruses.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Other 7 21%
Student > Master 6 18%
Researcher 5 15%
Student > Bachelor 4 12%
Lecturer 2 6%
Other 3 9%
Unknown 7 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 26%
Veterinary Science and Veterinary Medicine 4 12%
Agricultural and Biological Sciences 4 12%
Medicine and Dentistry 3 9%
Business, Management and Accounting 1 3%
Other 5 15%
Unknown 8 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2022.
All research outputs
of 22,851,489 outputs
Outputs from AMB Express
of 1,235 outputs
Outputs of similar age
of 298,866 outputs
Outputs of similar age from AMB Express
of 26 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,235 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 298,866 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.