Evidence map›Paper›PMID 30356351›Full record

ArticleBioMed research international2018

Computing of Low Shear Stress-Driven Endothelial Gene Network Involved in Early Stages of Atherosclerotic Process.

Federico Vozzi, Jonica Campolo, Lorena Cozzi, Gianfranco Politano, Stefano Di Carlo, Michela Rial, Claudio Domenici, Oberdan Parodi

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 16 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

8 authors at 3 institutions in 1 country.

Federico VozziCNR Institute of Clinical Physiology, Pisa, Italy.ORCID 0000-0001-5457-2328
Jonica CampoloCNR Institute of Clinical Physiology, Milan, Italy.ORCID 0000-0002-1711-6216
Lorena CozziGenetic Laboratory, Niguarda Hospital, Milan, Italy.ORCID 0000-0002-7429-8706
Gianfranco PolitanoDepartment of Control and Computer Engineering, Politecnico di Torino, Italy.ORCID 0000-0001-5268-9899
Stefano Di CarloDepartment of Control and Computer Engineering, Politecnico di Torino, Italy.ORCID 0000-0002-7512-5356
Michela RialCNR Institute of Clinical Physiology, Pisa, Italy.
Claudio DomeniciCNR Institute of Clinical Physiology, Pisa, Italy.
Oberdan ParodiCNR Institute of Clinical Physiology, Pisa, Italy.ORCID 0000-0003-2459-1047
Istituto di Fisiologia Clinica · ITPolitecnico di Torino · ITAzienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the pathogenesis of atherosclerosis, a central role is represented by endothelial inflammation with influx of chemokine-mediated leukocytes in the vascular wall. Aim of this study was to analyze the effect of different shear stresses on endothelial gene expression and compute gene network involved in atherosclerotic disease, in particular to homeostasis, inflammatory cell migration, and apoptotic processes.

methodsHUVECs were subjected to shear stress of 1, 5, and 10 dyne/cm

resultsAt low shear stress (1 dyne/cm

conclusionsThe significant modulation of these genes at low shear stress and their close relationships through transcription factors and microRNAs suggest that all may promote an initial inflamed endothelial cell phenotype, favoring the atherosclerotic disease.

Indexed as

Gene Expression RegulationGene Regulatory NetworksModels, CardiovascularShear StrengthStress, PhysiologicalAtherosclerosisHumansHuman Umbilical Vein Endothelial Cells

Identifiers

PMID30356351
PMCPMC6176299
OpenAlexW2892754123

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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.