Evidence map›Paper›PMID 31637139›Full record

ArticlePeerJ2019

ncRNA2MetS: a manually curated database for non-coding RNAs associated with metabolic syndrome.

Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, Chee Keong Kwoh, Yuezhongyi Sun

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 4 institutions in 2 countries.

Dengju YaoSchool of Software and Microelectronics, Harbin University of Science and Technology, Harbin, Heilongjiang, China.
Xiaojuan ZhanCollege of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China.
Xiaorong ZhanDepartment of Endocrinology and Metabolism, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Chee Keong KwohSchool of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore.
Yuezhongyi SunSchool of Software and Microelectronics, Harbin University of Science and Technology, Harbin, Heilongjiang, China.
Harbin University of Science and Technology · CNFirst Affiliated Hospital of Harbin Medical University · CNHarbin Medical University · CNNanyang Technological University · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic syndrome is a cluster of the most dangerous heart attack risk factors (diabetes and raised fasting plasma glucose, abdominal obesity, high cholesterol and high blood pressure), and has become a major global threat to human health. A number of studies have demonstrated that hundreds of non-coding RNAs, including miRNAs and lncRNAs, are involved in metabolic syndrome-related diseases such as obesity, type 2 diabetes mellitus, hypertension, etc. However, these research results are distributed in a large number of literature, which is not conducive to analysis and use. There is an urgent need to integrate these relationship data between metabolic syndrome and non-coding RNA into a specialized database. To address this need, we developed a metabolic syndrome-associated non-coding RNA database (ncRNA2MetS) to curate the associations between metabolic syndrome and non-coding RNA. Currently, ncRNA2MetS contains 1,068 associations between five metabolic syndrome traits and 627 non-coding RNAs (543 miRNAs and 84 lncRNAs) in four species. Each record in ncRNA2MetS database represents a pair of disease-miRNA (lncRNA) association consisting of non-coding RNA category, miRNA (lncRNA) name, name of metabolic syndrome trait, expressive patterns of non-coding RNA, method for validation, specie involved, a brief introduction to the association, the article referenced, etc. We also developed a user-friendly website so that users can easily access and download all data. In short, ncRNA2MetS is a complete and high-quality data resource for exploring the role of non-coding RNA in the pathogenesis of metabolic syndrome and seeking new treatment options. The website is freely available at http://www.biomed-bigdata.com:50020/index.html.

Indexed as

DatabaselncRNAMetabolic syndromemiRNANon-coding RNA

Identifiers

PMID31637139
PMCPMC6798904
OpenAlexW2980462819

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.