Evidence map›Paper›PMID 30873266›Full record

ArticleIranian journal of microbiology2018

A rapid method for separating and concentration of food-borne pathogens using elution from ready-to-eat vegetables.

Safieh Rajabzadeh, Masoumeh Bahreini, Mohammad Reza Sharifmoghadam

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In one paragraph

Article in Iranian journal of microbiology, 2018. 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
0.4field-weighted citation impact, top 34% 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, 7 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Safieh RajabzadehDepartment of Food Sciences and Technology, Resarch Institute of Food Sciences and Technology, Mashhad, Iran.
Masoumeh BahreiniDepartment of Biology, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Mohammad Reza SharifmoghadamDepartment of Biology, Faculty of Sciences, Ferdowsi University of Mashhad, Mashhad, Iran.
Ferdowsi University of Mashhad · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesTraditional culture methods for detection of food-borne pathogens, a major public health problem, are simple, easily adaptable and very practical, but they can be laborious and time consuming. In this study, we eliminated culturing steps by developing a new separation method and therefore, decreased the detection time of food-borne pathogens ( MATERIALS AND

methodsWe used alkaline water and different alkaline buffers to elute bacteria from the lettuce surface as a model for ready-to-eat vegetables. Buffers used were as follows: 1) 0.05 M glycine; 2) 0.05 M glycine -100 mM Tris base -1% (w/v) beef extract; 3) buffer peptone water; 4) buffer phosphate saline. Buffers were adjusted to pH of 9, 9.5 and 10. In order to elute the bacteria, the lettuce pieces were suspended into buffers and shacked for 30, 45 and 60 min. Moreover, a multiplex PCR method for the simultaneous detection of food-borne pathogens was performed.

resultsThe results showed that buffer peptone water at pH 9.5 for 45 min have high ability to elute bacteria from the lettuce surface and the bacteria can be detected using multiplex PCR.

conclusionWe developed a new rapid and efficient method for simultaneous separation of food-borne pathogens. This method eliminates culturing stages and permits the detection and identification of target pathogens in a few hours.

Indexed as

ElutionFood-borne pathogensMultiplex polymerase chain reactionRapid detectionReady-to-eat vegetables

Identifiers

PMID30873266
PMCPMC6414744
OpenAlexW2917400634

What OpenQuestion holds

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LicenceCC BY
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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.