Evidence map›Paper›PMID 35359345›Full record

ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2022

Eight Differential miRNAs in DN Identified by Microarray Analysis as Novel Biomarkers.

Chao Tu, Lan Wei, Liangzhi Wang, Ying Tang

Open access · goldAbstract read
In one paragraph

Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 47% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Comprehensive bioinformatics andFrontiers in endocrinology · 2025
    Article
  3. 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

4 authors at 1 institution in 1 country.

Chao TuDepartment of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, People's Republic of China.ORCID 0000-0003-2142-8666
Lan WeiDepartment of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, People's Republic of China.ORCID 0000-0003-0673-725X
Liangzhi WangDepartment of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, People's Republic of China.ORCID 0000-0002-0950-5211
Ying TangDepartment of Rehabilitation Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213000, People's Republic of China.
Soochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetic nephropathy (DN) is the common cause of renal diseases such as end-stage renal disease (ESRD) and chronic kidney disease (CKD). Various diagnostic applications and treatment methods are used for clinical but remain some prognosis issues. To avoid morbidity and mortality related to DN, early detection of disease complications as well as targeted therapeutic strategies is essential. Considerable evidence indicates that non-coding RNA plays a vital role in the biological processes of various diseases, used as biomarkers and therapeutic targets. And the most known ncRNAs are the microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs). Materials and Methods: Our study aimed to identify potential prognostic ncRNAs involved in DN by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. Our research focuses on differential expression miRNAs (DEmiRNAs) in DN and their interactions with critical genes. Results: We identified 8 up-regulated DEmiRNAs, including miR-103a-2-5p, miR-297, miR-548x-3p, miR-604, miR-644a, miR-1256, miR-3911 and miR-5047 finally. We further validated these miRNAs in a murine model. Conclusion: Identifying these up-regulated genes and elucidating these miRNAs regulatory network will contribute to a better understanding of the molecular mechanism of DN and how they can be used as new biomarkers and potential therapeutic targets for DN.

Indexed as

bioinformaticsbiomarkersdiabetic nephropathymicroRNAs

Identifiers

PMID35359345
PMCPMC8961165
OpenAlexW4225753830

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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.