Evidence map›Paper›PMID 34070525›Full record

ArticleFoods (Basel, Switzerland)2021

Building of an Internal Transcribed Spacer (ITS) Gene Dataset to Support the Italian Health Service in Mushroom Identification.

Alice Giusti, Enrica Ricci, Laura Gasperetti, Marta Galgani, Luca Polidori, Francesco Verdigi, Roberto Narducci, Andrea Armani

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2021. 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

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Biology · 2022
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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

8 authors.

Alice GiustiFishLab, Department of Veterinary Sciences, University of Pisa, Viale delle Piagge 2, 56124 Pisa, Italy.
Enrica RicciExperimental Zooprophylactic Institute of Lazio and Tuscany M. Aleandri, UOT Toscana Nord, SS Abetone e Brennero 4, 56124 Pisa, Italy.
Laura GasperettiExperimental Zooprophylactic Institute of Lazio and Tuscany M. Aleandri, UOT Toscana Nord, SS Abetone e Brennero 4, 56124 Pisa, Italy.
Marta GalganiFishLab, Department of Veterinary Sciences, University of Pisa, Viale delle Piagge 2, 56124 Pisa, Italy.ORCID 0000-0003-4019-1369
Luca PolidoriTuscany Mycological Groups Association, via Turi, 8 Santa Croce sull'Arno, 56124 Pisa, Italy.
Francesco VerdigiNorth West Tuscany LHA (Mycological Inspectorate), via A. Cocchi, 7/9, 56124 Pisa, Italy.
Roberto NarducciTuscany Mycological Groups Association, via Turi, 8 Santa Croce sull'Arno, 56124 Pisa, Italy.
Andrea ArmaniFishLab, Department of Veterinary Sciences, University of Pisa, Viale delle Piagge 2, 56124 Pisa, Italy.ORCID 0000-0002-9614-2032

Funding

Italian Ministry of Health IZS LT 04/18 RC
6 · The paper itself

Abstract

This study aims at building an ITS gene dataset to support the Italian Health Service in mushroom identification. The target species were selected among those mostly involved in regional (Tuscany) poisoning cases. For each target species, all the ITS sequences already deposited in GenBank and BOLD databases were retrieved and accurately assessed for quality and reliability by a systematic filtering process. Wild specimens of target species were also collected to produce reference ITS sequences. These were used partly to set up and partly to validate the dataset by BLAST analysis. Overall, 7270 sequences were found in the two databases. After filtering, 1293 sequences (17.8%) were discarded, with a final retrieval of 5977 sequences. Ninety-seven ITS reference sequences were obtained from 76 collected mushroom specimens: 15 of them, obtained from 10 species with no sequences available after the filtering, were used to build the dataset, with a final taxonomic coverage of 96.7%. The other 82 sequences (66 species) were used for the dataset validation. In most of the cases (n = 71; 86.6%) they matched with identity values ≥ 97-100% with the corresponding species. The dataset was able to identify the species involved in regional poisoning incidents. As some of these species are also involved in poisonings at the national level, the dataset may be used for supporting the National Health Service throughout the Italian territory. Moreover, it can support the official control activities aimed at detecting frauds in commercial mushroom-based products and safeguarding consumers.

Indexed as

internal transcribed spacer: genetic datasetmushroomsofficial controlpoisoningspecies identification

Identifiers

PMID34070525
PMCPMC8227961

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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.