Evidence map›Paper›PMID 28045090›Full record

ArticleScientific reports2017

miRNA and mRNA expression analysis reveals potential sex-biased miRNA expression.

Li Guo, Qiang Zhang, Xiao Ma, Jun Wang, Tingming Liang

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed
–field-weighted citation impact
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

77 citing papers in PubMed.

  1. Trial
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  7. Anti-inflammatory effects of kawakawa (Food science & nutrition · 2024
    Article
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17 more citing papers are in PubMed but not listed here.

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

5 authors.

Li GuoDepartment of Bioinformatics, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China.
Qiang ZhangDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Xiao MaDepartment of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
Jun WangDepartment of Bioinformatics, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China.
Tingming LiangJiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Science, Nanjing Normal University, Nanjing, 210023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies suggest that mRNAs may be differentially expressed between males and females. This study aimed to perform expression analysis of mRNA and its main regulatory molecule, microRNA (miRNA), to discuss the potential sex-specific expression patterns using abnormal expression profiles from The Cancer Genome Atlas database. Generally, deregulated miRNAs and mRNAs had consistent expression between males and females, but some miRNAs may be oppositely expressed in specific diseases: up-regulated in one group and down-regulated in another. Studies of miRNA gene families and clusters further confirmed that these sequence or location related miRNAs might have opposing expression between sexes. The specific miRNA might have greater expression divergence across different groups, suggesting flexible expression across different individuals, especially in tumor samples. The typical analysis regardless of the sex will ignore or balance these sex-specific deregulated miRNAs. Compared with flexible miRNAs, their targets of mRNAs showed relative stable expression between males and females. These relevant results provide new insights into miRNA-mRNA interaction and sex difference.

Indexed as

BiasFemaleHumansMaleMicroRNAsRNA, MessengerSex FactorsTranscriptomeMicroRNAsRNA, Messenger

Identifiers

PMID28045090
PMCPMC5206641

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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.