Evidence map›Paper›PMID 36985198›Full record

ArticleMicroorganisms2023

Development of an Extraction Method to Detect Hepatitis A Virus, Hepatitis E Virus, and Noroviruses in Fish Products.

Catherine Hennechart-Collette, Océane Dehan, Audrey Fraisse, Sandra Martin-Latil, Sylvie Perelle

Open access · goldAbstract read
In one paragraph

Article in Microorganisms, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
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

5 authors at 1 institution in 1 country.

Catherine Hennechart-ColletteLaboratory for Food Safety, Université Paris-Est, ANSES, 14 rue Pierre et Marie Curie, CEDEX, F-94701 Maisons-Alfort, France.
Océane DehanLaboratory for Food Safety, Université Paris-Est, ANSES, 14 rue Pierre et Marie Curie, CEDEX, F-94701 Maisons-Alfort, France.
Audrey FraisseLaboratory for Food Safety, Université Paris-Est, ANSES, 14 rue Pierre et Marie Curie, CEDEX, F-94701 Maisons-Alfort, France.ORCID 0000-0001-9567-6270
Sandra Martin-LatilLaboratory for Food Safety, Université Paris-Est, ANSES, 14 rue Pierre et Marie Curie, CEDEX, F-94701 Maisons-Alfort, France.
Sylvie PerelleLaboratory for Food Safety, Université Paris-Est, ANSES, 14 rue Pierre et Marie Curie, CEDEX, F-94701 Maisons-Alfort, France.
Sorbonne Université · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Viruses are a leading cause of foodborne disease worldwide. Hepatitis viruses (hepatitis A (HAV) and hepatitis E (HEV)) and human norovirus are recognized as the main viruses of public health concern in food hygiene. ISO 15216 approved procedures are not validated for detection of HAV and human norovirus in foodstuffs, such as fishes, leading to an inability to ensure the safety of these products. This study aimed to provide a rapid and sensitive method for detecting these targets in fish products. An existing method that includes proteinase K treatment was selected for further validation using artificially contaminated fish products, according to the recent international standard ISO 16140-4. Recovery efficiencies in pure RNA extracts of viruses ranged from 0.2% to 66.2% for HAV, 4.0% to 100.0% for HEV, 2.2% to 100.0% for norovirus GI, and 0.2% to 12.5% for norovirus GII. LOD

Indexed as

detectionfish products and fish mealshepatitis A virushepatitis E virushuman norovirusprocess controlRT-qPCR

Identifiers

PMID36985198
PMCPMC10051274
OpenAlexW4322742576

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.