Evidence map›Paper›PMID 29360783›Full record

ReviewToxins2018

Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective.

Luca Dellafiora, Chiara Dall'Asta, Gianni Galaverna

Abstract readReview
In one paragraph

Review in Toxins, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. A Novel Deoxynivalenol-Activated WheatJournal of fungi (Basel, Switzerland) · 2021
    Article
  11. Article
  12. Toxicological and Medical Aspects ofFrontiers in microbiology · 2019
    Review
  13. Article
  14. 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

3 authors.

Luca DellafioraDepartment of Food and Drug, University of Parma, 43124 Parma, Italy. luca.dellafiora@unipr.it.ORCID 0000-0002-1901-3317
Chiara Dall'AstaDepartment of Food and Drug, University of Parma, 43124 Parma, Italy. chiara.dallasta@unipr.it.
Gianni GalavernaDepartment of Food and Drug, University of Parma, 43124 Parma, Italy. gianni.galaverna@unipr.it.ORCID 0000-0001-9042-2378

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mycotoxins severely threaten the health of humans and animals. For this reason, many countries have enforced regulations and recommendations to reduce the dietary exposure. However, even though regulatory actions must be based on solid scientific knowledge, many aspects of their toxicological activity are still poorly understood. In particular, deepening knowledge on the primal molecular events triggering the toxic stimulus may be relevant to better understand the mechanisms of action of mycotoxins. The present work presents the use of in silico approaches in studying the mycotoxins toxicodynamics, and discusses how they may contribute in widening the background of knowledge. A particular emphasis has been posed on the methods accounting the molecular initiating events of toxic action. In more details, the key concepts and challenges of mycotoxins toxicology have been introduced. Then, topical case studies have been presented and some possible practical implementations of studying mycotoxins toxicodynamics have been discussed.

Indexed as

Food ContaminationAnimalsComputer SimulationDietary ExposureHumansMycotoxinsRisk AssessmentMycotoxinsin silico molecular modelingmechanism of actionmycotoxinsrisk assessment computational toxicologytoxicodynamictoxicology

Identifiers

PMID29360783
PMCPMC5848153

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.