Evidence map›Paper›PMID 32095365›Full record

ArticlePeerJ2020

Comprehensive analysis of long non-coding RNAs and mRNAs in skeletal muscle of diabetic Goto-Kakizaki rats during the early stage of type 2 diabetes.

Wenlu Zhang, Yunmeng Bai, Zixi Chen, Xingsong Li, Shuying Fu, Lizhen Huang, Shudai Lin, Hongli Du

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2020. 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 54% 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
  2. 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

8 authors at 1 institution in 1 country.

Wenlu ZhangSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Yunmeng BaiSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Zixi ChenSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Xingsong LiSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Shuying FuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Lizhen HuangSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Shudai LinSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Hongli DuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
South China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skeletal muscle long non-coding RNAs (lncRNAs) were reported to be involved in the development of type 2 diabetes (T2D). However, little is known about the mechanism of skeletal muscle lncRNAs on hyperglycemia of diabetic Goto-Kakizaki (GK) rats at the age of 3 and 4 weeks. To elucidate this, we used RNA-sequencing to profile the skeletal muscle transcriptomes including lncRNAs and mRNAs, in diabetic GK and control Wistar rats at the age of 3 and 4 weeks. In total, there were 438 differentially expressed mRNAs (DEGs) and 401 differentially expressed lncRNAs (DELs) in skeletal muscle of 3-week-old GK rats compared with age-matched Wistar rats, and 1000 DEGs and 726 DELs between GK rats and Wistar rats at 4 weeks of age. The protein-protein interaction analysis of overlapping DEGs between 3 and 4 weeks, the correlation analysis of DELs and DEGs, as well as the prediction of target DEGs of DELs showed that these DEGs (

Indexed as

Long noncoding RNA (lncRNA)RNA-seqSkeletal muscleType 2 diabetes (T2D)

Identifiers

PMID32095365
PMCPMC7023842
OpenAlexW3005728317

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.