Evidence map›Paper›PMID 35287505›Full record

ArticleThe Journal of international medical research2022

Identification of

Sheng Yan, Lingbing Meng, Xiaoyong Guo, Zuoguan Chen, Yuanmeng Zhang, Yongjun Li

Open access · goldAbstract read
In one paragraph

Article in The Journal of international medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.8field-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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
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  7. Review
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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

6 authors at 4 institutions in 1 country.

Sheng YanDepartment of Vascular Surgery, 117555Beijing Hospital, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science and Peking Union Medical College, Graduate School of Peking Union Medical College, Beijing, P.R. China.
Lingbing MengNeurology Department, 117555Beijing Hospital, Beijing Hospital, National Center of Gerontology, No. 1 Dahua Road, Dong Dan, Beijing, P. R. China.
Xiaoyong GuoInternal Medicine Department, 12485Anhui Medical University, Anhui Medical University, Meishan Road, Hefei, Anhui, P. R. China.
Zuoguan ChenDepartment of Vascular Surgery, 117555Beijing Hospital, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science and Peking Union Medical College, Graduate School of Peking Union Medical College, Beijing, P.R. China.
Yuanmeng ZhangInternal Medicine Department, 154516Jinzhou Medical University, Jinzhou Medical University, No. 40, Section 3, Songpo Road, Linghe District, Jinzhou, Liaoning, P.R. China.ORCID https://orcid.org/0000-0003-0236-0635
Yongjun LiDepartment of Vascular Surgery, 117555Beijing Hospital, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Science and Peking Union Medical College, Graduate School of Peking Union Medical College, Beijing, P.R. China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNAnhui Medical University · CNBeijing Hospital · CNJinzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveAtherosclerosis (AS) is a life-threatening disease in aging populations worldwide. However, the molecular and gene regulation mechanisms of AS are still unclear. This study aimed to identify gene expression differences between atheroma plaques and normal tissues in humans.

methodsThe expression profiling dataset GSE43292 was obtained from the Gene Expression Omnibus (GEO) dataset. The differentially expressed genes (DEGs) were identified between the atheroma plaques and normal tissues via GEO2R, and functional annotation of the DEGs was performed by GSEA. STRING and MCODE plug-in of Cytoscape were used to construct a protein-protein interaction (PPI) network and analyze hub genes. Finally, quantitative polymerase chain reaction (qPCR) was performed to verify the hub genes.

resultsOverall, 134 DEGs were screened. Functional annotation demonstrated that these DEGs were mainly enriched in sphingolipid metabolism, apoptosis, lysosome, and more. Six hub genes were identified from the PPI network:

conclusionsWe used bioinformatics to identify six hub genes:

Indexed as

AtherosclerosisGene Expression ProfilingReceptors, CCR1BiomarkersCD11 AntigensGene Regulatory NetworksHumansProtein Interaction MapsBiomarkersCCR1 protein, humanCD11 AntigensReceptors, CCR1Atherosclerosisbioinformaticsdifferentially expressed geneGene Set Enrichment Analysishub geneprotein–protein interaction networktherapeutic target

Identifiers

PMID35287505
PMCPMC8928411
OpenAlexW4221137556

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.