Evidence map›Paper›PMID 22347226›Full record

ArticleFrontiers in genetics2012

The impact of classification of interest on predictive toxicogenomics.

Robnet T Kerns, Pierre R Bushel

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2012. 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
2.4field-weighted citation impact, top 10% 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, 10 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

2 authors at 2 institutions in 1 country.

Robnet T KernsMicroarray and Genome Informatics, National Institute of Environmental Health Sciences Research Triangle Park, NC, USA.
Pierre R Bushel
National Institute of Environmental Health Sciences · USSRA International (United States) · US

Funding

Microarray and Genome InformaticsZIAES102345 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI BUSHEL, ROBERT · 2009 to 2021
$10.8M
Microarray and Genome InformaticsZ01ES102345 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI BUSHEL, PIERRE · 2007 to 2008
$2.5M
Intramural NIH HHS Z01 ES102345
6 · The paper itself

Abstract

The era of toxicogenomics has introduced a new way of monitoring the effect of environmental stressors and toxicants on biological systems via quantification of changes in gene expression. Because the liver is one of the major organs for synthesis and secretion of substances which metabolize endogenous and exogenous materials, there has been a great deal of interest in elucidating predictive and mechanistic genomic markers of hepatotoxicity. This mini-review will bring context to a limited number of toxicogenomics studies which used genomics to evaluate the transcriptional changes in blood and liver in response to acetaminophen (APAP) or other liver toxicants, but differed according to the classification of interest (COI), i.e., the partitioning of the samples a priori according to a common toxicological characteristic. The toxicogenomics studies highlighted are characterized by a classification of either no/low vs. high APAP dose exposure, none vs. observed necrosis, and severity of necrosis. The overlap or lack thereof between the gene classifiers and the modulated biological processes that are elucidated will be discussed to enhance the understanding of the effect of the particular COI model and experimental design used for prediction.

Indexed as

biomarkerclassificationgene expressiongenomicspredictiontoxicogenomics

Identifiers

PMID22347226
PMCPMC3273729
OpenAlexW2162279238

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.