Evidence map›Paper›PMID 35573279›Full record

ArticleFrontiers in toxicology2022

Leveraging a High-Throughput Screening Method to Identify Mechanisms of Individual Susceptibility Differences in a Genetically Diverse Zebrafish Model.

Dylan J Wallis, Jane La Du, Preethi Thunga, Daniel Elson, Lisa Truong, Siva K Kolluri, Robyn L Tanguay, David M Reif

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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 at 2 institutions in 1 country.

Dylan J WallisBioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States.
Jane La DuSinnhuber Aquatic Research Laboratory, Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
Preethi ThungaBioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States.
Daniel ElsonCancer Research Laboratory, Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
Lisa TruongSinnhuber Aquatic Research Laboratory, Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
Siva K KolluriCancer Research Laboratory, Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
Robyn L TanguaySinnhuber Aquatic Research Laboratory, Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, United States.
David M ReifBioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States.
Oregon State University · USNorth Carolina State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the mechanisms behind chemical susceptibility differences is key to protecting sensitive populations. However, elucidating gene-environment interactions (GxE) presents a daunting challenge. While mammalian models have proven useful, problems with scalability to an enormous chemical exposome and clinical translation faced by all models remain; therefore, alternatives are needed. Zebrafish (

Indexed as

abamectincomputational toxicologygenomichigh-throughput (HT) approachesmechanismpathwayszebrafish

Identifiers

PMID35573279
PMCPMC9098949
OpenAlexW4225117311

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.