Evidence map›Paper›PMID 27492058›Full record

ArticleBiotechnology journal2016

Multiplex 16S rRNA-derived geno-biochip for detection of 16 bacterial pathogens from contaminated foods.

Hwa Hui Shin, Byeong Hee Hwang, Hyung Joon Cha

Open access · hybridAbstract read
In one paragraph

Article in Biotechnology journal, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 28% 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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Hwa Hui ShinDepartment of Chemical Engineering, Pohang University of Science and Technology, Pohang, Korea.
Byeong Hee HwangDepartment of Chemical Engineering, Pohang University of Science and Technology, Pohang, Korea.
Hyung Joon ChaDepartment of Chemical Engineering, Pohang University of Science and Technology, Pohang, Korea.
Pohang University of Science and Technology · KRIncheon National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Foodborne diseases caused by various pathogenic bacteria occur worldwide. To prevent foodborne diseases and minimize their impacts, it is important to inspect contaminated foods and specifically detect many types of pathogenic bacteria. Several DNA oligonucleotide biochips based on 16S rRNA have been investigated to detect bacteria; however, a mode of detection that can be used to detect diverse pathogenic strains and to examine the safety of food matrixes is still needed. In the present work, a 16S rRNA gene-derived geno-biochip detection system was developed after screening DNA oligonucleotide specific capture probes, and it was validated for multiple detection of 16 pathogenic strains that frequently occur with a signature pattern. rRNAs were also used as detection targets directly obtained from cell lysates without any purification and amplification steps in the bacterial cells separated from 8 food matrixes by simple pretreatments. Thus, the developed 16S rRNA-derived geno-biochip can be successfully used for the rapid and multiple detection of the 16 pathogenic bacteria frequently isolated from contaminated foods that are important for food safety.

Indexed as

Food MicrobiologyBacteriaHazard Analysis and Critical Control PointsHumansOligonucleotide Array Sequence AnalysisRNA, Ribosomal, 16SRNA, Ribosomal, 16SDirect RNA-detectionFoodborne pathogenFood matrixMultiple detectionOligonucleotide microarray

Identifiers

PMID27492058
PMCPMC5132059
OpenAlexW2489051706

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.