Evidence map›Paper›PMID 28117343›Full record

ArticleScientific reports2017

Selection of reference genes is critical for miRNA expression analysis in human cardiac tissue. A focus on atrial fibrillation.

Michela Masè, Margherita Grasso, Laura Avogaro, Elvira D'Amato, Francesco Tessarolo, Angelo Graffigna, Michela Alessandra Denti, Flavia Ravelli

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 55 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 2 pooled it
–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

55 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  9. NinoaPathogens (Basel, Switzerland) · 2024
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  10. MicroRNAs, endometrial receptivity and molecular pathways.Reproductive biology and endocrinology : RB&E · 2024
    Review
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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

8 authors.

Michela MasèDepartment of Physics, University of Trento, Trento, Italy.
Margherita GrassoCentre for Integrative Biology, University of Trento, Trento, Italy.
Laura AvogaroDepartment of Physics, University of Trento, Trento, Italy.
Elvira D'AmatoDepartment of Physics, University of Trento, Trento, Italy.
Francesco TessaroloHealthcare Research and Innovation Program (IRCS-PAT), Bruno Kessler Foundation, Trento, Italy.
Angelo GraffignaDivision of Cardiac Surgery, Santa Chiara Hospital, Trento, Italy.
Michela Alessandra DentiCentre for Integrative Biology, University of Trento, Trento, Italy.
Flavia RavelliDepartment of Physics, University of Trento, Trento, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are emerging as key regulators of complex biological processes in several cardiovascular diseases, including atrial fibrillation (AF). Reverse transcription-quantitative polymerase chain reaction is a powerful technique to quantitatively assess miRNA expression profile, but reliable results depend on proper data normalization by suitable reference genes. Despite the increasing number of studies assessing miRNAs in cardiac disease, no consensus on the best reference genes has been reached. This work aims to assess reference genes stability in human cardiac tissue with a focus on AF investigation. We evaluated the stability of five reference genes (U6, SNORD48, SNORD44, miR-16, and 5S) in atrial tissue samples from eighteen cardiac-surgery patients in sinus rhythm and AF. Stability was quantified by combining BestKeeper, delta-C

Indexed as

AgedAtrial FibrillationGene Expression ProfilingGene Expression RegulationHumansMaleMicroRNAsMiddle AgedMyocardiumReference StandardsMicroRNAs

Identifiers

PMID28117343
PMCPMC5259703

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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.