Evidence map›Paper›PMID 38139254›Full record

ArticleInternational journal of molecular sciences2023

High-Throughput Transcriptomics Differentiates Toxic versus Non-Toxic Chemical Exposures Using a Rat Liver Model.

Venkat R Pannala, Michele R Balik-Meisner, Deepak Mav, Dhiral P Phadke, Elizabeth H Scholl, Ruchir R Shah, Scott S Auerbach, Anders Wallqvist

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.Toxicological sciences : an official journal of the Society of Toxicology · 2025
    Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Venkat R PannalaDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, Frederick, MD 21702, USA.
Michele R Balik-MeisnerSciome LLC, Research Triangle Park, Durham, NC 27709, USA
Deepak MavSciome LLC, Research Triangle Park, Durham, NC 27709, USA
Dhiral P PhadkeSciome LLC, Research Triangle Park, Durham, NC 27709, USA
Elizabeth H SchollSciome LLC, Research Triangle Park, Durham, NC 27709, USA
Ruchir R ShahSciome LLC, Research Triangle Park, Durham, NC 27709, USA
Scott S AuerbachDivision of Translational Toxicology, National Institute of Environmental Health Sciences, Research Triangle Park, Durham, NC 27709, USA
Anders WallqvistDepartment of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, Frederick, MD 21702, USA.
Research Triangle Park Foundation · USHenry M. Jackson Foundation · USNational Institute of Environmental Health Sciences · USTelemedicine & Advanced Technology Research Center · US

Funding

Environmental Health Perspectives, NIEHS27302C0031 · NIEHS · 2008 to 2008
$1.2M
NIEHS NIH HHS 13862488NIEHS NIH HHS 27302C0031
6 · The paper itself

Abstract

To address the challenge of limited throughput with traditional toxicity testing, a newly developed high-throughput transcriptomics (HTT) platform, together with a 5-day in vivo rat model, offers an alternative approach to estimate chemical exposures and provide reasonable estimates of toxicological endpoints. This study contains an HTT analysis of 18 environmental chemicals with known liver toxicity. They were evaluated using male Sprague Dawley rats exposed to various concentrations daily for five consecutive days via oral gavage, with data collected on the sixth day. Here, we further explored the 5-day rat model to identify potential gene signatures that can differentiate between toxic and non-toxic liver responses and provide us with a potential histopathological endpoint of chemical exposure. We identified a distinct gene expression pattern that differentiated non-hepatotoxic compounds from hepatotoxic compounds in a dose-dependent manner, and an analysis of the significantly altered common genes indicated that toxic chemicals predominantly upregulated most of the genes and several pathways in amino acid and lipid metabolism. Finally, our liver injury module analysis revealed that several liver-toxic compounds showed similarities in the key injury phenotypes of cellular inflammation and proliferation, indicating potential molecular initiating processes that may lead to a specific end-stage liver disease.

Indexed as

End Stage Liver DiseaseLiverAnimalsGene Expression ProfilingMaleRatsRats, Sprague-DawleyToxicity Testsdose responsegene expressionhigh-throughput transcriptomicshistopathologyliver toxicity

Identifiers

PMID38139254
PMCPMC10743995
OpenAlexW4389680261

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.