Evidence map›Paper›PMID 23691205›Full record

ArticlePloS one2013

Potent inhibition of Hendra virus infection via RNA interference and poly I:C immune activation.

Jana L McCaskill, Glenn A Marsh, Paul Monaghan, Lin-Fa Wang, Timothy Doran, Nigel A J McMillan

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Prophylactic intranasal administration of lipid nanoparticle formulated siRNAs reduce SARS-CoV-2 and RSV lung infection.Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi · 2023
    Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Jana L McCaskillThe University of Queensland Diamantina Institute, Brisbane, Queensland, Australia.
Glenn A Marsh
Paul Monaghan
Lin-Fa Wang
Timothy Doran
Nigel A J McMillan
Australian Centre for Disease Preparedness · AUCommonwealth Scientific and Industrial Research Organisation · AUGriffith University · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hendra virus (HeV) is a highly pathogenic zoonotic paramyxovirus that causes fatal disease in a wide range of species, including humans. HeV was first described in Australia in 1994, and has continued to re-emerge with increasing frequency. HeV is of significant concern to human health due to its high mortality rate, increasing emergence, absence of vaccines and limited post exposure therapies. Here we investigate the use of RNA interference (RNAi) based therapeutics targeting HeV in conjunction with the TLR3 agonist Poly I:C and show that they are potent inhibitors of HeV infection in vitro. We found that short interfering RNAs (siRNAs) targeting the abundantly expressed N, P and M genes of HeV caused over 95% reduction of HeV virus titre, protein and mRNA. Furthermore, we found that the combination of HeV targeting siRNA and Poly I:C had an additive effect in suppressing HeV infection. Our results demonstrate for the first time that RNAi and type I interferon stimulation are effective inhibitors of HeV replication in vitro and may provide an effective therapy for this highly lethal, zoonotic pathogen.

Indexed as

RNA InterferenceHeLa CellsHendra VirusHenipavirus InfectionsHumansPoly I-CToll-Like Receptor 3Viral LoadPoly I-CTLR3 protein, humanToll-Like Receptor 3

Identifiers

PMID23691205
PMCPMC3653894
OpenAlexW1966895169

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.