Evidence map›Paper›PMID 29443776›Full record

Observational studyMedicine2018

Differential expression of microRNAs in the normal skin of the Han and Uyghur populations in Xinjiang Province.

Xiujuan Wu, Zongfeng Zhao, Yuan Ding, Fang Xiang, Xiaojing Kang, Xiongming Pu

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Medicine, 2018. 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
0.2field-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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 1 institution in 1 country.

Xiujuan WuDepartment of Dermatology and Venereology Clinical Medical Research Center, People's Hospital of Xinjiang, Uygur Autonomous Region, Urumqi, Xinjiang, China.
Zongfeng Zhao
Yuan Ding
Fang Xiang
Xiaojing Kang
Xiongming Pu
People's Hospital of Xinjiang Uygur Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we investigated the expression of microRNAs (miRNAs) in the skin samples from the Han and Uyghur populations in Xinjiang, China. The miRNA levels of the normal skin samples from 10 individuals of Uyghur or Han were tested by microarray and the expression differentiations were compared. Among the 3100 probes for microarray, a total of 247 miRNAs were differentially expressed in the Han versus Uyghur population, including 76 upregulated miRNAs and 171 downregulated miRNAs. The most significantly upregulated miRNAs were miR-141-3p, miR-1915-5p, kshv-miR-K12-2-5p, and miR-222-3p. And the most significantly downregulated miRNAs included miR-1207-3p and miR-625-3p. We have confirmed the upregulation of miR-141-3p and miR-1915-5p by qRT-PCR. There were no statistical correlations in the expression of miR-141-3p or miR-1915-5p with the age or gender within each group. Interestingly, the differentially expressed miRNAs were enriched in some cancer-related pathways, such as p53, mitogen-activated protein kinase, and WNT signal pathways. Collectively, these dysregulated expressions of the miRNAs may provide a better understanding of the differences in the incidence and mortality of skin-related carcinoma between the Uyghur and Han populations in Xinjiang.

Indexed as

AdultAsian PeopleChinaDown-RegulationFemaleGene Expression ProfilingHumansMaleMicroRNAsReverse Transcriptase Polymerase Chain ReactionSequence Analysis, RNASkinSkin NeoplasmsUp-RegulationMicroRNAs

Identifiers

PMID29443776
PMCPMC5839858
OpenAlexW2793212198

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.