Evidence map›Paper›PMID 36619898›Full record

ArticleGenetics research2022

Bioinformatics Analysis of miRNAs Targeting TRAF5 in DLBCL Involving in NF-

Chunyao Li, Lanshan Huang, Yongqin Wen, Muhua Yi, Min Gao

Open access · goldAbstract read
In one paragraph

Article in Genetics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Functions and mechanisms of miR-650 in human diseases.Frontiers in molecular biosciences · 2026
    Review
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 2 institutions in 2 countries.

Chunyao LiDepartment of Pathology, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, Guangdong 523000, China.ORCID 0000-0001-9016-847X
Lanshan HuangDepartments of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China.
Yongqin WenDepartment of Pathology, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, Guangdong 523000, China.
Muhua YiDepartment of Pathology, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, Guangdong 523000, China.
Min GaoDepartment of Pathology, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, Guangdong 523000, China.ORCID 0000-0003-2761-3694
Dongguan People’s Hospital · CNQueen's University Belfast · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diffuse large B-cell lymphoma (DLBCL) is an aggressive B-cell lymphoma with high heterogeneity. There is an unmet need to investigate valid indicators for the diagnosis and therapy of DLBCL. Methods: GEO database was utilized to screen for differentially expressed genes (DEGs) and differential miRNAs in DLBCL tissues. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to analyse DEGs. Then multiple databases were searched for related miRNAs within DLBCL, TNF receptor-associated factor 5 (TRAF5) and NF-kappa B (NF- Results: DEGs were significantly concentrated in the NF- Conclusions: Subsets of miRNAs may participate in the NF-

Indexed as

Lymphoma, Large B-Cell, DiffuseMicroRNAsApoptosisComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansNF-kappa BSignal TransductionTNF Receptor-Associated Factor 5MicroRNAsMIRN532 microRNA, humanMIRN650 microRNA, humanNF-kappa BTNF Receptor-Associated Factor 5TRAF5 protein, human

Identifiers

PMID36619898
PMCPMC9803564
OpenAlexW4312178302

What OpenQuestion holds

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LicenceCC BY
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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.