Evidence map›Paper›PMID 30326626›Full record

ArticleInternational journal of molecular sciences2018

Tissue-Specific Profiling of Oxidative Stress-Associated Transcriptome in a Healthy Mouse Model.

Jung Min Kim, Hyeong Geug Kim, Chang Gue Son

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

29 citing papers in PubMed, 46 citations in OpenAlex.

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  13. International journal of molecular sciences · 2022
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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

3 authors at 1 institution in 1 country.

Jung Min KimGenoplan Korea, Inc., Seoul 06221, Korea. brant@genoplan.com.ORCID 0000-0001-6319-0217
Hyeong Geug KimLiver and Immunology Research Center, Dunsan Hospital of Daejeon University, Daejeon 301-724, Korea. okskjw04@gmail.com.
Chang Gue SonLiver and Immunology Research Center, Dunsan Hospital of Daejeon University, Daejeon 301-724, Korea. ckson@dju.ac.kr.
Daejeon University · KR

Funding

Traditional Korean Medicine R&D Project and National Research Foundation HI15C-0112-000015, NRF-2018R1A6A1A03025221
6 · The paper itself

Abstract

Oxidative stress is a common phenomenon and is linked to a wide range of diseases and pathological processes including aging. Tissue-specific variation in redox signaling and cellular responses to oxidative stress may be associated with vulnerability especially to age-related and chronic diseases. In order to provide a basis for tissue-specific difference, we examined the tissue-specific transcriptional features of 101 oxidative stress-associated genes in 10 different tissues and organs of healthy mice under physiological conditions. Microarray analysis results, which were consistent with quantitative polymerase chain reaction (qPCR) results, showed that catalase, Gpx3, and Gpx4 were most highly regulated in the liver, kidney, and testes. We also found the tissue-specific gene expression of SOD1 (liver and kidney), SOD2 (heart and muscle), and SOD3 (lung and kidney). The current results will serve as a reference for animal models and help advance our understanding of tissue-specific variability in oxidative stress-associated pathogenesis.

Indexed as

Gene Expression RegulationTranscriptomeAnimalsComputational BiologyGene Expression ProfilingGene OntologyMaleMiceOrgan SpecificityOxidative StressReactive Oxygen SpeciesReactive Oxygen Speciesgene expressionoxidative stresstissue-specific variationtranscriptome

Identifiers

PMID30326626
PMCPMC6214011
OpenAlexW2896701868

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.