Evidence map›Paper›PMID 32104287›Full record

ArticleExperimental and therapeutic medicine2020

Identification of differentially expressed miRNAs associated with thermal injury in epidermal stem cells based on RNA-sequencing.

Hao-Tian Rong, De-Wu Liu

Open access · diamondAbstract read
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Article in Experimental and therapeutic medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.7field-weighted citation impact, top 37% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Hao-Tian RongBurns Institute, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China.
De-Wu LiuBurns Institute, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China.
First Affiliated Hospital of Nanchang University · CNNanchang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current research indicates that epidermal stem cells (EpSCs) play an important role in promoting wound healing, but the mechanism of action of these cells during wound repair following thermal damage remains unclear. In the present study, the trypsin digestion method was used to isolate human EpSCs and the cells were incubated in a 51.5°C water tank for 35 sec to construct a thermal injury model. The differentially expressed miRNAs were identified using high-throughput sequencing technology, and bioinformatic methods were used to predict their target genes and signaling pathways that may be involved in wound repair. A total of 33 miRNAs including, hsa-miR-1973, hsa-miR-4485-3p, hsa-miR-548-5p, hsa-miR-212-3p and hsa-miR-4461 were upregulated, whereas 21 miRNAs including, hsa-miR-4520-5p, hsa-miR-4661-5p, hsa-miR-191-3p, hsa-miR-129-5p, hsa-miR-147b and hsa-miR-6868-3p were downregulated following thermal injury of the human EpSCs. The bioinformatic analysis indicated that the differentially expressed miRNAs are involved in biological processes such as cell proliferation and differentiation, cell growth apoptosis, cell adhesion and migration. The results showed that there is a differential expression pattern of miRNAs after thermal injury of human EpSCs and these differences are involved in the regulation of the wound healing process. These findings provide new clues for further study of the wound healing mechanism and targeted therapy.

Indexed as

epidermal stem cellshigh-throughput sequencingmicroRNA profilingthermal damage

Identifiers

PMID32104287
PMCPMC7027234
OpenAlexW2999809488

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.