Evidence map›Paper›PMID 30505886›Full record

ArticleBio-protocol2018

Detection and Differentiation of Multiple Viral RNAs Using Branched DNA FISH Coupled to Confocal Microscopy and Flow Cytometry.

Nicholas van Buuren, Karla Kirkegaard

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bio-protocol, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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

2 authors at 1 institution in 1 country.

Nicholas van BuurenDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Karla KirkegaardDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Stanford University · US

Funding

Translational Incubator CoreU19AI109662 · NIAID · STANFORD UNIVERSITY · PI GLENN, JEFFREY S · 2014 to 2019
$28.6M
NIH Director's Pioneer AwardDP1OD000827 · OD · STANFORD UNIVERSITY · PI KIRKEGAARD, KARLA · 2006 to 2010
$3.9M
Viral use and mimicry of autophagy pathway and componentsR01AI134912 · NIAID · STANFORD UNIVERSITY · PI KIRKEGAARD, KARLA · 2018 to 2021
$1.6M
Nikon A1Rsi resonant spectral confocal microscopeS10OD010580 · OD · STANFORD UNIVERSITY · PI FULLER, MARGARET T · 2013 to 2013
$377k
NIAID NIH HHS R01 AI134912NIAID NIH HHS U19 AI109662NIH HHS DP1 OD000827NIH HHS S10 OD010580
6 · The paper itself

Abstract

Due to the exceptionally high mutation rates of RNA-dependent RNA polymerases, infectious RNA viruses generate extensive sequence diversity, leading to some of the lowest barriers to the development of antiviral drug resistance in the microbial world. We have previously discovered that higher barriers to the development of drug resistance can be achieved through dominant suppression of drug-resistant viruses by their drug-susceptible parents. We have explored the existence of dominant drug targets in poliovirus, dengue virus and hepatitis C virus (HCV). The low replication capacity of HCV required the development of novel strategies for identifying cells co-infected with drug-susceptible and drug-resistant strains. To monitor co-infected cell populations, we generated codon-altered versions of the JFH1 strain of HCV. Then, we could differentiate the codon-altered and wild-type strains using a novel type of RNA fluorescent

Indexed as

Branched DNAsDrug ResistanceGenetic selectionHCVRNA FISHRNA flow cytometryViral evolution

Identifiers

PMID30505886
PMCPMC6269108
OpenAlexW2896073378

What OpenQuestion holds

Textmetadata
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.