Evidence map›Paper›PMID 30634538›Full record

ReviewMolecules (Basel, Switzerland)2019

MicroRNAs as a Novel Tool in the Diagnosis of Liver Lipid Dysregulation and Fatty Liver Disease.

Jingwei Yu, Jun Peng, Zhilin Luan, Feng Zheng, Wen Su

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

  1. Article
  2. Review
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  11. Review
  12. Article
  13. Targeting miRNA by Natural Products: A Novel Therapeutic Approach for Nonalcoholic Fatty Liver.Evidence-based complementary and alternative medicine : eCAM · 2021
    Review
  14. Review
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  16. 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

5 authors.

Jingwei YuShenzhen University Medical Center, Shenzhen University Health Science Center, Shenzhen 518060, China. brent1008@gmail.com.
Jun PengShenzhen University Medical Center, Shenzhen University Health Science Center, Shenzhen 518060, China. fkuejun3092@163.com.
Zhilin LuanAdvanced Institute for Medical Sciences, Dalian Medical University, Dalian, Liaoning 116044, China. luanzl@dmu.edu.cn.
Feng ZhengAdvanced Institute for Medical Sciences, Dalian Medical University, Dalian, Liaoning 116044, China. fzheng63@163.com.
Wen SuShenzhen University Medical Center, Shenzhen University Health Science Center, Shenzhen 518060, China. suwen@szu.edu.cn.

Funding

China National Natural Science Foundation 81870405The Foundation of Shenzhen Basic Research Project (JCYJ20170818144501119)
6 · The paper itself

Abstract

In recent years, metabolic disorder, especially fatty liver disease, has been considered a major challenge to global health. The attention of researchers focused on expanding knowledge of the regulation mechanism behind these diseases and towards the new diagnostics tools and treatments. The pathophysiology of the fatty liver disease is undoubtedly complex. Abnormal hepatic lipid accumulation is a major symptom of most metabolic diseases. Therefore, the identification of novel regulation factors of lipid metabolism is important and meaningful. As a new diagnostic tool, the function of microRNAs during fatty liver disease has recently come into notice in biological research. Accumulating evidence supports the influence of miRNAs in lipid metabolism. In this review, we discuss the potential role of miRNAs in liver lipid metabolism and the pathogenesis of fatty liver disease.

Indexed as

Lipid MetabolismGene Expression RegulationGene Regulatory NetworksHumansLiverMicroRNAsNon-alcoholic Fatty Liver DiseaseMicroRNAsfatty liver diseaselipogenesismicroRNA

Identifiers

PMID30634538
PMCPMC6358728

What OpenQuestion holds

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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.