Evidence map›Paper›PMID 26302899›Full record

ArticleScientific reports2015

Integrated Transcriptomics Establish Macrophage Polarization Signatures and have Potential Applications for Clinical Health and Disease.

Matheus Becker, Marco A De Bastiani, Mariana M Parisi, Fátima T C R Guma, Melissa M Markoski, Mauro A A Castro, Mark H Kaplan, Florencia M Barbé-Tuana, Fábio Klamt

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

39 citing papers in PubMed, 66 citations in OpenAlex.

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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

9 authors at 3 institutions in 2 countries.

Matheus BeckerLaboratory of Cellular Biochemistry, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Marco A De BastianiLaboratory of Cellular Biochemistry, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Mariana M ParisiLaboratory of Molecular Biology and Bioinformatics, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Fátima T C R GumaLaboratory of Biochemistry and Cellular Biology of Lipids, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Melissa M MarkoskiLaboratory of Cellular and Molecular Cardiology, IC/FUC, Porto Alegre, RS 90620-000, Brazil.
Mauro A A CastroLaboratory of Bioinformatics, Professional and Technological Education Sector, Polytechnic Center, UFPR, 81531-970 Curitiba (PR), Brazil.
Mark H KaplanDepartment of Pediatrics, Herman B Wells Center for Pediatric Research, Indianapolis (IN), 46202, USA; Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis (IN), 46202, USA.
Florencia M Barbé-TuanaLaboratory of Molecular Biology and Bioinformatics, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Fábio KlamtLaboratory of Cellular Biochemistry, Department of Biochemistry, ICBS/UFRGS, 90035-003 Porto Alegre (RS), Brazil.
Universidade Federal do Rio Grande do Sul · BRIndiana University – Purdue University Indianapolis · USUniversidade Federal do Paraná · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Growing evidence defines macrophages (Mφ) as plastic cells with wide-ranging states of activation and expression of different markers that are time and location dependent. Distinct from the simple M1/M2 dichotomy initially proposed, extensive diversity of macrophage phenotypes have been extensively demonstrated as characteristic features of monocyte-macrophage differentiation, highlighting the difficulty of defining complex profiles by a limited number of genes. Since the description of macrophage activation is currently contentious and confusing, the generation of a simple and reliable framework to categorize major Mφ phenotypes in the context of complex clinical conditions would be extremely relevant to unravel different roles played by these cells in pathophysiological scenarios. In the current study, we integrated transcriptome data using bioinformatics tools to generate two macrophage molecular signatures. We validated our signatures in in vitro experiments and in clinical samples. More importantly, we were able to attribute prognostic and predictive values to components of our signatures. Our study provides a framework to guide the interrogation of macrophage phenotypes in the context of health and disease. The approach described here could be used to propose new biomarkers for diagnosis in diverse clinical settings including dengue infections, asthma and sepsis resolution.

Indexed as

Cells, CulturedCytokinesFeasibility StudiesGene Expression ProfilingHumansMacrophage-Activating FactorsMacrophage ActivationMacrophagesSystems IntegrationTranscriptomeCytokinesMacrophage-Activating Factors

Identifiers

PMID26302899
PMCPMC4548187
OpenAlexW2273849298

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.