Evidence map›Paper›PMID 32712749›Full record

ArticleMolecular and cellular biochemistry2020

SRGN, a new identified shear-stress-responsive gene in endothelial cells.

Qinfeng Ma, Wei Gu, Tianhan Li, Kun Zhang, Yuliang Cui, Kai Qu, Nan Wang, Rose Humphry, Colm Durkan, Juhui Qiu and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular and cellular biochemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.9field-weighted citation impact, top 30% 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

11 citing papers in PubMed, 40 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

11 authors at 2 institutions in 3 countries.

Qinfeng MaKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China.
Wei GuSchool of Medicine, Faculty of Medicine, Chongqing University, Chongqing, China.
Tianhan LiKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China.
Kun ZhangKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China.
Yuliang CuiKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China.
Kai QuKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China.
Nan WangThe Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK.
Rose HumphryThe Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK.
Colm DurkanThe Nanoscience Centre, University of Cambridge, Cambridge, CB3 0FF, UK.
Juhui QiuKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China. jhqiu@cqu.edu.cn.
Guixue WangKey Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, Faculty of Medicine, Bioengineering College, Chongqing University, Chongqing, 400030, China. wanggx@cqu.edu.cn.ORCID http://orcid.org/0000-0002-0258-4113
Chongqing University · CNUniversity of Cambridge · GB

Funding

Chongqing Science and Technology Commission cstc2019jcyj-zdxm0033Fundamental Research Funds for the Central Universities 2019CDYGZD008National Natural Science Foundation of China 31971242
6 · The paper itself

Abstract

Endothelial cells (ECs) play an important role in the pathogenesis of cardiovascular disease, especially atherosclerosis (AS). The abnormal wall shear stress (WSS) which directly contacts with ECs is the key stimulating factor leading to AS. However, the underlying mechanism of ECs responding to WSS is still incompletely understood. This study aims to explore the novel mechano-sensitive genes and its potential mechanism in response to WSS in ECs by employing bioinformatics methods based on previously available high-throughput data from zebrafish embryos, both before and after blood flow formation. Six common differentially expressed genes (DEGs) (SRGN, SLC12A3, SLC25A4, PVALB1, ITGAE.2, zgc:198419) were selected out from two high-throughput datasets (GSE126617 and GSE20707) in the GEO database. Among them, SRGN was chosen for further verification through the in vitro shear stress loading experiments with human umbilical vein endothelial cells (HUVECs) and the in vivo partial ligation of carotid artery in mice. Our data indicated that low shear stress (LSS) could enhance the expression of SRGN via the PKA/CREB-dependent signaling pathway. The proportion of Ki67

Indexed as

Mechanotransduction, CellularShear StrengthStress, MechanicalAnimalsAtherosclerosisEndothelium, VascularHumansHuman Umbilical Vein Endothelial CellsMiceMice, Knockout, ApoENeovascularization, PathologicProteoglycansVesicular Transport ProteinsProteoglycansserglycinVesicular Transport ProteinsAtherosclerosisBioinformaticsEndothelial cellsShear stressSRGN

Identifiers

PMID32712749
OpenAlexW3044600523

What OpenQuestion holds

Textmetadata
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.