Evidence map›Paper›PMID 18299250›Full record

ArticleJournal of clinical virology : the official publication of the Pan American Society for Clinical Virology2008

Detection of adamantane-resistant influenza on a microarray.

Michael B Townsend, James A Smagala, Erica D Dawson, Varough Deyde, Larisa Gubareva, Alexander I Klimov, Robert D Kuchta, Kathy L Rowlen

Abstract readEvaluation Study
In one paragraph

Article in Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

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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

8 authors.

Michael B TownsendDepartment of Chemistry and Biochemistry, The University of Colorado at Boulder, UCB #215, Boulder, CO 80309, USA.
James A Smagala
Erica D Dawson
Varough Deyde
Larisa Gubareva
Alexander I Klimov
Robert D Kuchta
Kathy L Rowlen

Funding

Development of Diagnostic Microarray for Influenza AU01AI056528 · NIAID · UNIVERSITY OF COLORADO AT BOULDER · PI ROWLEN, KATHY L · 2003 to 2007
$2.0M
NIAID NIH HHS U01 AI056528
6 · The paper itself

Abstract

backgroundInfluenza A has the ability to rapidly mutate and become resistant to the commonly prescribed influenza therapeutics, thereby complicating treatment decisions.

objectiveTo design a cost-effective low-density microarray for use in detection of influenza resistance to the adamantanes. STUDY

designWe have taken advantage of functional genomics and microarray technology to design a DNA microarray that can detect the two most common mutations in the M2 protein associated with adamantane resistance, V27A and S31N.

resultsIn a blind study of 22 influenza isolates, the antiviral resistance-chip (AVR-Chip) had a success rate of 95% for detecting these mutations. Microarray data from a larger set of samples were further analyzed using an artificial neural network and resulted in a correct identification rate of 94% for influenza virus samples that had V27A and S31N mutations.

conclusionsThe AVR-Chip provided a method for rapidly screening influenza viruses for adamantane sensitivity, and the general approach could be easily extended to detect resistance to other chemotherapeutics.

Indexed as

AdamantaneAntiviral AgentsDrug Resistance, ViralHumansInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeMicrobial Sensitivity TestsMutationNeural Networks, ComputerOligonucleotide Array Sequence AnalysisViral Matrix ProteinsViroporin ProteinsAdamantaneAntiviral AgentsM2 protein, Influenza A virusViral Matrix ProteinsViroporin Proteins

Identifiers

PMID18299250
PMCPMC2493413

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Registered trials

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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.