Evidence map›Paper›PMID 35345996›Full record

ArticleCombinatorial chemistry & high throughput screening2023

Mechanism Research of Platelet Core Marker Prediction and Molecular Recognition in Cardiovascular Events.

Hongdan Wang, Bingyu Zhang, Xianhua Zhong, Dui Qin, Zhangyong Li

Abstract read
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In one paragraph

Article in Combinatorial chemistry & high throughput screening, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 60% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
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

5 authors at 1 institution in 1 country.

Hongdan WangChongqing Engineering Research Center of Medical Electronics and Information Technology, College of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Bingyu ZhangChongqing Engineering Research Center of Medical Electronics and Information Technology, College of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Xianhua ZhongChongqing Engineering Research Center of Medical Electronics and Information Technology, College of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Dui QinChongqing Engineering Research Center of Medical Electronics and Information Technology, College of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Zhangyong LiChongqing Engineering Research Center of Medical Electronics and Information Technology, College of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Chongqing University of Posts and Telecommunications · CN

Funding

National Natural Science Foundation of China 11904042National Natural Science Foundation of China 81901839
6 · The paper itself

Abstract

backgroundThrombosis triggered by platelet activation plays a vital role in the pathogenesis of cardiovascular and cerebrovascular diseases.

objectiveThis study aims to find platelet combined biomarkers for cardiovascular diseases and investigate the possibility of Concanavalin A (ConA) acting on platelets as a new pharmacological target.

methodsHigh-throughput Technology and bioinformatics analysis were combined and groups of microarray chip gene expression profiles for acute myocardial infarction (AMI) and sickle cell disease (SCD) were obtained using GEO database screening. R language limma package was used to obtain differentially expressed genes (DEGs). GO, KEGG, and other databases were utilized to perform the enrichment analysis of DEGs' functions, pathways, etc. PPI network was constructed using STRING database and Cytoscape software, and MCC algorithm was used to obtain the 200 core genes of the two groups of DEGs. Core targets were confirmed by constructing an intersection area screening. A type of molecular probe, ConA, was molecularly docked with the above core targets on the Zdock, HEX, and 3D-DOCK servers.

resultsWe found six core markers, CD34, SOCS2, ABL1, MTOR, VEGFA, and SMURF1, which were simultaneously related to both diseases, and the docking effect showed that VEGFA is the best-performing.

conclusionVEGFA is most likely to reduce its expression by binding to ConA, which could affect the downstream regulation of the PI3K/Akt signaling pathway during platelet activation. Some other core targets also have the opportunity to interact with ConA to affect platelet-activated thrombosis and trigger changes in cardiovascular events.

Indexed as

Blood PlateletsGene Expression ProfilingOligonucleotide Array Sequence AnalysisPhosphatidylinositol 3-KinasesTranscriptomePhosphatidylinositol 3-KinasesCardiovascular diseasesenrichment analysisgene regulationmolecular dockingplatelet activationsickle cell disease

Identifiers

PMID35345996
OpenAlexW4220765699

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.