ReviewToxins2015
A novel Peptide-binding motifs inference approach to understand deoxynivalenol molecular toxicity.
Review in Toxins, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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.
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.
Who cites it
13 citing papers in PubMed, 33 citations in OpenAlex.
- Article
- 3-keto-DON, but Not 3-International journal of molecular sciences · 2022Article
- Epimerization of Deoxynivalenol by theToxins · 2021Article
- A Novel Deoxynivalenol-Activated WheatJournal of fungi (Basel, Switzerland) · 2021Article
- The Ribosome-Binding Mode of Trichothecene Mycotoxins Rationalizes Their Structure-Activity Relationships.International journal of molecular sciences · 2021Article
- Detoxification of Deoxynivalenol by a Mixed Culture of Soil Bacteria With 3Frontiers in microbiology · 2019Article
- Understanding the Bacterial Response to Mycotoxins: The Transcriptomic Analysis of Deoxynivalenol-Induced Changes inFrontiers in pharmacology · 2019Article
- The enzymatic detoxification of the mycotoxin deoxynivalenol: identification of DepA from the DON epimerization pathway.Microbial biotechnology · 2018Article
- Toxicodynamics of Mycotoxins in the Framework of Food Risk Assessment-An In Silico Perspective.Toxins · 2018Review
- The enzymatic epimerization of deoxynivalenol by Devosia mutans proceeds through the formation of 3-keto-DON intermediate.Scientific reports · 2017Article
- Beyond Ribosomal Binding: The Increased Polarity and Aberrant Molecular Interactions of 3-epi-deoxynivalenol.Toxins · 2016Article
- Bacterial Epimerization as a Route for Deoxynivalenol Detoxification: the Influence of Growth and Environmental Conditions.Frontiers in microbiology · 2016Article
- Bacterial endophytes from wild maize suppress Fusarium graminearum in modern maize and inhibit mycotoxin accumulation.Frontiers in plant science · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deoxynivalenol (DON) is a type B trichothecene mycotoxin that is commonly detected in cereals and grains world-wide. The low-tolerated levels of this mycotoxin, especially in mono-gastric animals, reflect its bio-potency. The toxicity of DON is conventionally attributed to its ability to inhibit ribosomal protein biosynthesis, but recent advances in molecular tools have elucidated novel mechanisms that further explain DON's toxicological profile, complementing the diverse symptoms associated with its exposure. This article summarizes the recent findings related to novel mechanisms of DON toxicity as well as how structural modifications to DON alter its potency. In addition, it explores feasible ways of expanding our understating of DON-cellular targets and their roles in DON toxicity, clearance, and detoxification through the utilization of computational biology approaches.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.