Evidence map›Paper›PMID 30471335›Full record

ArticleRegulatory toxicology and pharmacology : RTP2019

Multi-dimensional in vitro bioactivity profiling for grouping of glycol ethers.

Fabian A Grimm, John S House, Melinda R Wilson, Oksana Sirenko, Yasuhiro Iwata, Fred A Wright, Nicholas Ball, Ivan Rusyn

Open access · greenAbstract read
In one paragraph

Article in Regulatory toxicology and pharmacology : RTP, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

  1. Application ofFrontiers in toxicology · 2026
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  4. Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025
    Review
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  13. High-Throughput Transcriptomics Platform for Screening Environmental Chemicals.Toxicological sciences : an official journal of the Society of Toxicology · 2021
    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 3 institutions in 1 country.

Fabian A GrimmDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA.
John S HouseBioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695, USA.
Melinda R WilsonDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA.
Oksana SirenkoMolecular Devices, LLC, San Jose, CA, 95134, USA.
Yasuhiro IwataDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA.
Fred A WrightBioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA.
Nicholas BallToxicology and Environmental Research and Consulting (TERC), Environment, Health and Safety (EH&S), The Dow Chemical Company, Horgen, Zurich, 8810, Switzerland.
Ivan RusynDepartment of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA. Electronic address: irusyn@tamu.edu.
Texas A&M University · USNorth Carolina State University · USAnalog Devices (United States) · US

Funding

Single cell, multi-parametric high throughput platform to classify endocrine disruptor potential of mixturesP42ES027704 · NIEHS · TEXAS A&M UNIVERSITY · PI Weihsueh A Chiu · 2017 to 2026
$21.2M
NIEHS NIH HHS P42 ES027704
6 · The paper itself

Abstract

High-content screening data derived from physiologically-relevant in vitro models promise to improve confidence in data-integrative groupings for read-across in human health safety assessments. The biological data-based read-across concept is especially applicable to bioactive chemicals with defined mechanisms of toxicity; however, the challenge of data-derived groupings for chemicals that are associated with little or no bioactivity has not been explored. In this study, we apply a suite of organotypic and population-based in vitro models for comprehensive bioactivity profiling of twenty E-Series and P-Series glycol ethers, solvents with a broad variation in toxicity ranging from relatively non-toxic to reproductive and hematopoetic system toxicants. Both E-Series and P-Series glycol ethers elicited cytotoxicity only at high concentrations (mM range) in induced pluripotent stem cell-derived hepatocytes and cardiomyocytes. Population-variability assessment comprised a study of cytotoxicity in 94 human lymphoblast cell lines from 9 populations and revealed differences in inter-individual variability across glycol ethers, but did not indicate population-specific effects. Data derived from various phenotypic and transcriptomic assays revealed consistent bioactivity trends between both cardiomyocytes and hepatocytes, indicating a more universal, rather than cell-type specific mode-of-action for the tested glycol ethers in vitro. In vitro bioactivity-based similarity assessment using Toxicological Priority Index (ToxPi) showed that glycol ethers group according to their alcohol chain length, longer chains were associated with increased bioactivity. While overall in vitro bioactivity profiles did not correlate with in vivo toxicity data on glycol ethers, in vitro bioactivity of E-series glycol ethers were indicative of and correlated with in vivo irritation scores.

Indexed as

AnimalsCell LineEthersGlycolsHumansRisk AssessmentSolventsToxicity TestsEthersGlycolsSolventsGlycol ethersIn vitroNew assessment methodologiesRead-acrossSafety assessmentToxPi

Identifiers

PMID30471335
PMCPMC6333527
OpenAlexW2901595342

What OpenQuestion holds

Textmetadata
LicenceTDM
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.