Evidence map›Paper›PMID 24949460›Full record

ArticleBioMed research international2014

A fast, reliable, and sensitive method for detection and quantification of Listeria monocytogenes and Escherichia coli O157:H7 in ready-to-eat fresh-cut products by MPN-qPCR.

Pasquale Russo, Giuseppe Botticella, Vittorio Capozzi, Salvatore Massa, Giuseppe Spano, Luciano Beneduce

Abstract read
In one paragraph

Article in BioMed research international, 2014. 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
–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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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  3. Molecular detection ofJournal of environmental health science & engineering · 2021
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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

6 authors.

Pasquale RussoDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.
Giuseppe BotticellaDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.
Vittorio CapozziDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.
Salvatore MassaDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.
Giuseppe SpanoDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.
Luciano BeneduceDepartment of Agriculture, Food and Environmental Sciences, University of Foggia, Via Napoli 25, 71122 Foggia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the present work we developed a MPN quantitative real-time PCR (MPN-qPCR) method for a fast and reliable detection and quantification of Listeria monocytogenes and Escherichia coli O157:H7 in minimally processed vegetables. In order to validate the proposed technique, the results were compared with conventional MPN followed by phenotypic and biochemical assays methods. When L. monocytogenes and E. coli O157:H7 were artificially inoculated in fresh-cut vegetables, a concentration as low as 1 CFU g(-1) could be detected in 48 hours for both pathogens. qPCR alone allowed a limit of detection of 10(1) CFU g(-1) after 2 hours of enrichment for L. monocytogenes and E. coli O157:H7. Since minimally processed ready-to-eat vegetables are characterized by very short shelf life, our method can potentially address the consistent reduction of time for microbial analysis, allowing a better management of quality control. Moreover, the occurrences of both pathogenic bacteria in mixed salad samples and fresh-cut melons were monitored in two production plants from the receipt of the raw materials to the early stages of shelf life. No sample was found to be contaminated by L. monocytogenes. One sample of raw mixed salad was found positive to an H7 enterohemorrhagic serotype.

Indexed as

Food AnalysisEscherichia coli O157Fast FoodsHumansListeria monocytogenesReal-Time Polymerase Chain ReactionVegetables

Identifiers

PMID24949460
PMCPMC4052075

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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.