Evidence map›Paper›PMID 35115816›Full record

ArticleInternational journal of general medicine2022

Identification and Validation of Novel Diagnostic Biomarkers for Keloid Based on GEO Database.

Yeletai Nurzati, Zhu Zhu, Heng Xu, Yixin Zhang

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 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
0.6field-weighted citation impact, top 31% 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, 3 citations in OpenAlex.

  1. Article
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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

4 authors at 1 institution in 1 country.

Yeletai NurzatiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People's Republic of China.ORCID 0000-0003-3188-6505
Zhu ZhuDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People's Republic of China.
Heng XuDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People's Republic of China.
Yixin ZhangDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 201100, People's Republic of China.
Shanghai Ninth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionKeloid is a pathological scar type, which invades normal surrounding tissue without self-limiting to cause pain, itching, cosmetic disfigurement, etc. Knowledge of the molecular mechanisms underlying keloid remains unclear. This dilemma leads to no biomarker available for diagnosis. Thus, to seek accurate diagnosis, biomarkers are necessary for keloid diagnosis to help control its incidence.

methodsGene Expression Omnibus (GEO) database was used to select differentially expressed miRNAs (DE-miRNAs) in GSE113620. miRTarBase miRNA-target tools were used to predict the interactions between miRNAs and their target mRNAs. Target mRNAs that were differentially expressed in keloid were selected by analyzing differentially expressed genes (DEGs) in GSE44270 and GSE92566. PPI network analysis, gene enrichment analysis, cell-specific and tissue-specific expression analyses of DE-target mRNAs were conducted. RT-PCR analysis was conducted to validate our results.

resultsThree novel miRNAs (miR-30b-5p, miR-212-3p, miR-149-5p) and five target mRNAs ( DISCUSSION: These findings of keloid-related miRNAs, mRNAs, and miRNA-mRNAs regulatory networks may provide insights into the underlying pathogenesis of keloid and serve as potential biomarkers for keloid diagnosis.

Indexed as

diagnostic biomarkersdifferentially expressed geneskeloidsmiRNA–mRNA network

Identifiers

PMID35115816
PMCPMC8801514
OpenAlexW4206988362

What OpenQuestion holds

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LicenceCC BY-NC
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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.