Evidence map›Paper›PMID 29620629›Full record

ArticleMedicine2018

Identification of biomarkers of venous thromboembolism by bioinformatics analyses.

Guiming Wang, Wenbo Zhao, Yudong Yang, Gaochao Yang, Zhigang Wei, Jiansheng Guo

Abstract read
In one paragraph

Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Genetic Variants of RPL5 and RPL9 Genes among Saudi Patients Diagnosed with Thrombosis.Medical archives (Sarajevo, Bosnia and Herzegovina) · 2021
    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

6 authors.

Guiming WangDepartment of Vascular Surgery Department of Surgery, The First Hospital of Shanxi Medical University, Taiyuan, PR, China.
Wenbo Zhao
Yudong Yang
Gaochao Yang
Zhigang Wei
Jiansheng Guo

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses.Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The differentially expressed genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were identified. Then, pathway enrichment analysis of DEGs were performed, followed by protein-protein interaction (PPI) network construction.Total 433 upregulated and 222 downregulated DEGs were obtained between sVTE and control samples. For rVTE versus control, 625 upregulated and 302 downregulated DEGs were identified. The overlap DEGs were mainly enriched in the pathways related to ribosome, cancer, and immune disease. The DEGs specific to rVTE were enriched in several pathways, such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of VTE genes, including ribosomal protein family genes and NADH family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53).The nod-like receptor signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis and treatment of VTE.

Indexed as

Genes, p53Computational BiologyDatabases, GeneticDown-RegulationGenetic MarkersHumansNADNLR ProteinsProtein Interaction MapsRibosomal ProteinsSignal TransductionUp-RegulationVenous ThromboembolismGenetic MarkersNADNLR ProteinsRibosomal Proteins

Identifiers

PMID29620629
PMCPMC5902267

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.