Evidence map›Paper›PMID 33993410›Full record

ReviewJournal of molecular neuroscience : MN2021

Study on the Relationship between the miRNA-centered ceRNA Regulatory Network and Fatigue.

Xingzhe Yang, Feng Li, Jie Ma, Yan Liu, Xuejiao Wang, Ruochong Wang, Yifei Zhang, Wei Zhang, Qingyun He, Dandan Song and 1 more

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of molecular neuroscience : MN, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
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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

11 authors at 1 institution in 1 country.

Xingzhe YangCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.ORCID http://orcid.org/0000-0003-4271-7256
Feng LiCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China. lifeng_bucm0610@126.com.
Jie MaCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Yan LiuCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Xuejiao WangCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Ruochong WangCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Yifei ZhangCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Wei ZhangCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Qingyun HeCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Dandan SongCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Jiaojiao YuCollege of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Beijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the incidence of fatigue has been increasing, and the effective prevention and treatment of fatigue has become an urgent problem. As a result, the genetic research of fatigue has become a hot spot. Transcriptome-level regulation is the key link in the gene regulatory network. The transcriptome includes messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). MRNAs are common research targets in gene expression profiling. Noncoding RNAs, including miRNAs, lncRNAs, circRNAs and so on, have been developed rapidly. Studies have shown that miRNAs are closely related to the occurrence and development of fatigue. MiRNAs can regulate the immune inflammatory reaction in the central nervous system (CNS), regulate the transmission of nerve impulses and gene expression, regulate brain development and brain function, and participate in the occurrence and development of fatigue by regulating mitochondrial function and energy metabolism. LncRNAs can regulate dopaminergic neurons to participate in the occurrence and development of fatigue. This has certain value in the diagnosis of chronic fatigue syndrome (CFS). CircRNAs can participate in the occurrence and development of fatigue by regulating the NF-κB pathway, TNF-α and IL-1β. The ceRNA hypothesis posits that in addition to the function of miRNAs in unidirectional regulation, mRNAs, lncRNAs and circRNAs can regulate gene expression by competitive binding with miRNAs, forming a ceRNA regulatory network with miRNAs. Therefore, we suggest that the miRNA-centered ceRNA regulatory network is closely related to fatigue. At present, there are few studies on fatigue-related ncRNA genes, and most of these limited studies are on miRNAs in ncRNAs. However, there are a few studies on the relationship between lncRNAs, cirRNAs and fatigue. Less research is available on the pathogenesis of fatigue based on the ceRNA regulatory network. Therefore, exploring the complex mechanism of fatigue based on the ceRNA regulatory network is of great significance. In this review, we summarize the relationship between miRNAs, lncRNAs and circRNAs in ncRNAs and fatigue, and focus on exploring the regulatory role of the miRNA-centered ceRNA regulatory network in the occurrence and development of fatigue, in order to gain a comprehensive, in-depth and new understanding of the essence of the fatigue gene regulatory network.

Indexed as

Gene Regulatory NetworksAnimalsFatigueHumansMicroRNAsRNA, MessengerTranscriptomeMicroRNAsRNA, MessengerceRNAcircRNAFatiguelncRNAMiRNANF-κB pathway

Identifiers

PMID33993410
PMCPMC8500871
OpenAlexW3162846060

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.