Evidence map›Paper›PMID 38136906›Full record

ArticleAnimals : an open access journal from MDPI2023

Identification of Potential miRNA-mRNA Regulatory Network Associated with Growth and Development of Hair Follicles in Forest Musk Deer.

Wen-Hua Qi, Ting Liu, Cheng-Li Zheng, Qi Zhao, Nong Zhou, Gui-Jun Zhao

Open access · goldAbstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

Wen-Hua QiCollege of Biological and Food Engineering, Chongqing Three Gorges University, Chongqing 404100, China.
Ting LiuCollege of Biological and Food Engineering, Chongqing Three Gorges University, Chongqing 404100, China.
Cheng-Li ZhengSichuan Institute of Musk Deer Breeding, Chengdu 611830, China.
Qi ZhaoCollege of Biological and Food Engineering, Chongqing Three Gorges University, Chongqing 404100, China.
Nong ZhouCollege of Biological and Food Engineering, Chongqing Three Gorges University, Chongqing 404100, China.
Gui-Jun ZhaoChongqing Institute of Medicinal Plant Cultivation, Chongqing 408435, China.
Chongqing Three Gorges University · CNInstitute of Medicinal Plant Development · CN

Funding

National Natural Science Foundation C31702032, 32370560, 82274046Natural Science Foundation of Chongqing 2023NSCQ-MSX0404
6 · The paper itself

Abstract

In this study, sRNA libraries and mRNA libraries of HFs of FMD were constructed and sequenced using an Illumina HiSeq 2500, and the expression profiles of miRNAs and genes in the HFs of FMD were obtained at the anagen and catagen stages. In total, 565 differentially expressed unigenes (DEGs) were identified, 90 of which were upregulated and 475 of which were downregulated. In the BP category of GO enrichment, the DEGs were enriched in the processes related to HF development and differentiation, including the hair cycle regulation and processes, HF development, skin epidermis development, regulation of HF development, skin development, the Wnt signaling pathway, and the BMP signaling pathway. Through KEGG analysis it was found that DEGs were significantly enriched in pathways associated with HF development and growth. A total of 186 differentially expressed miRNAs (DEmiRNAs) were screened (

Indexed as

forest musk deerhair folliclemiRNA–mRNA networkRT-qPCRsignal pathway analysistranscriptome

Identifiers

PMID38136906
PMCPMC10740511
OpenAlexW4389780811

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.