Evidence map›Paper›PMID 31484960›Full record

ArticleScientific reports2019

Identification of stably expressed housekeeping miRNAs in endothelial cells and macrophages in an inflammatory setting.

Fabian Link, Knut Krohn, Julia Schumann

Erratum issuedAbstract read
In one paragraph

Article in Scientific reports, 2019. 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 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  5. Lipopolysaccharide (LPS) induces sclerostin secretion by extracellular vesicle via TLR4/miR-92a-3p/PTEN/NF-κB signalling pathway in murine macrophage.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Fabian LinkClinic for Anaesthesiology and Operative Intensive Care, University Hospital Halle (Saale), Halle, Saale, Germany.
Knut KrohnCore Unit DNA Technologies, Medical Faculty, Leipzig University, Leipzig, Germany.ORCID http://orcid.org/0000-0001-8110-1273
Julia SchumannClinic for Anaesthesiology and Operative Intensive Care, University Hospital Halle (Saale), Halle, Saale, Germany. julia.schumann@uk-halle.de.ORCID http://orcid.org/0000-0003-4403-3018

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable quantification of miRNA expression by qRT-PCR crucially depends on validated housekeepers for data normalization. Here we present thoroughly tested miRNAs eligible as references in immunological studies utilizing endothelial cells and macrophages, respectively. Endothelial cells (cell line: TIME) and macrophages (cell line: RAW264.7) were treated with various pro- and anti-inflammatory mediators (cytokines, LPS, unsaturated fatty acids) given as either single substances or in combination. Isolated RNA was screened for stably expressed miRNAs by next generation sequencing. Housekeeper candidates were thereafter validated by means of two independent quantification techniques: qRT-PCR for relative quantification and ddPCR for absolute quantification. Both methods consistently confirmed the suitability of let-7g-5p, let-7i-5p, miR-127-3p and miR-151a-5p in cytokine/fatty acid-treated TIME and miR-16-5p, miR-27b-3p, miR-103a-3p and miR-423-3p in LPS/fatty acid-treated RAW264.7, respectively as housekeeping miRNAs. With respect to abundancy and over all expression stability the miRNAs miR-151a-5p (cell line: TIME) as well as miR-27b-3p and miR-103a-3p (cell line: RAW264.7) can be particularly recommended for normalization of qRT-PCR data.

Indexed as

Gene Expression RegulationGenes, EssentialAnimalsEndothelial CellsInflammationMacrophagesMiceMicroRNAsRAW 264.7 CellsMicroRNAs

Identifiers

PMID31484960
PMCPMC6726651

What OpenQuestion holds

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Registered trials

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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.