Evidence map›Paper›PMID 37032500›Full record

ReviewCurrent neuropharmacology2024

A Comprehensive Review on the Importance of MiRNA-206 in the Animal Model and Human Diseases.

Wang Qi, Wei Guan

Open access · greenAbstract readReview
In one paragraph

Review in Current neuropharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

7 citing papers in PubMed, 15 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.

Wang QiDepartment of Pharmacology, The First People's Hospital of Yancheng, Yancheng, 224000, Jiangsu, China.
Wei GuanDepartment of Pharmacology, Pharmacy College, Nantong University, Nantong, 226001, Jiangsu, China.
Nantong University · CNYancheng First People's Hospital · CN

Funding

National Natural Science Foundation of China 81900551
6 · The paper itself

Abstract

MicroRNA-206 (miR-206) is a microRNA that is involved in many human diseases, such as myasthenia gravis, osteoarthritis, depression, cancers, etc. Both inhibition effects and progression roles of miR-206 have been reported for the past few years. High expression of miR-206 was observed in patients with osteoarthritis, gastric cancer and epithelial ovarian cancer compared to normal people. The study also showed that miR-206 promotes cancer progression in breast cancer patients and avascular necrosis of the femoral head. Meanwhile, several studies have shown that expression levels of miR-206 were down-regulated in laryngeal carcinoma cell multiplication, as well as in hepatocellular carcinoma, non-small lung cancer and infantile hemangioma. Moreover, miR-206 was up-regulated in the mild stage of amyotrophic lateral sclerosis patients and then down-regulated in the moderate and severe stages, indicating that miR-206 has the double effects of starting and aggravating the disease. In neuropsychiatric disorders, such as depression, miR-206 also plays an important role in the progression of the disease; the level of miR-206 is most highly expressed in the brains of patients with depression. In the current review, we summarize the role of miR-206 in various diseases, and miR-206 may be developed as a new biomarker for diagnosing diseases in the near future.

Indexed as

MicroRNAsNeoplasmsOsteoarthritisAnimalsBiomarkersGene Expression Regulation, NeoplasticHumansModels, AnimalBiomarkersMicroRNAsMIRN206 microRNA, humanAlzheimer’s disease.biomarkersexpression levelshuman diseasesmiR-206MiRNA

Identifiers

PMID37032500
PMCPMC10964108
OpenAlexW4362735579

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.