Evidence map›Paper›PMID 19718237›Full record

ArticleThe open virology journal2009

A microarray based approach for the identification of common foodborne viruses.

Mobolanle Ayodeji, Michael Kulka, Scott A Jackson, Isha Patel, Mark Mammel, Thomas A Cebula, Biswendu B Goswami

Abstract read
In one paragraph

Article in The open virology journal, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. DNA microarray for detection of gastrointestinal viruses.Journal of clinical microbiology · 2015
    Article
  4. A DNA microarray for the versatile diagnosis of infectious diarrhea.APMIS : acta pathologica, microbiologica, et immunologica Scandinavica · 2013
    Article
  5. 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

7 authors.

Mobolanle AyodejiDivision of Molecular Biology, Office of Applied Research and Safety Assessment (OARSA), Food And Drug Administration, 8301 Muirkirk Road, Laurel, Maryland, 20708, USA.
Michael Kulka
Scott A Jackson
Isha Patel
Mark Mammel
Thomas A Cebula
Biswendu B Goswami

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An oligonucleotide array (microarray) incorporating 13,000 elements representing selected strains of hepatitis A virus (HAV), human coxsackieviruses A and B (CVA and CVB), genogroups I and II of Norovirus (NV), and human rotavirus (RV) gene segments 3,4,10, and 11 was designed based on the principle of tiling. Each oligonucleotide was 29 bases long, starting at every 5th base of every sequence, resulting in an overlap of 24 bases in two consecutive oligonucleotides. The applicability of the array for virus identification was examined using PCR amplified products from multiple HAV and CV strains. PCR products labeled with biotin were hybridized to the array, and the biotin was detected using a brief reaction with Cy3-labeled streptavidin, the array subjected to laser scanning, and the hybridization data plotted as fluorescence intensity against each oligonucleotide in the array. The combined signal intensities of all probes representing a particular strain of virus were calculated and plotted against all virus strains identified on a linear representation of the array. The profile of the total signal intensity identified the strain that is most likely represented in the amplified cDNA target. The results obtained with HAV and CV indicated that the hybridization profile thus generated can be used to identify closely related viral strains. This represents a significant improvement over current methods for virus identification using PCR amplification and amplicon sequencing.

Identifiers

PMID19718237
PMCPMC2707758

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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.