Evidence map›Paper›PMID 27725851›Full record

ArticleAmerican journal of translational research2016

BMP2 promotes the differentiation of neural stem cells into dopaminergic neurons

Wang Yan, Zhao-Ying Chen, Jia-Qi Chen, Hui-Min Chen

Abstract read
In one paragraph

Article in American journal of translational research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

4 authors.

Wang YanNeurological Department of Internal Medicine, Ningbo No. 2 Hospital Ningbo 315000, China.
Zhao-Ying ChenNeurological Department of Internal Medicine, Ningbo No. 2 Hospital Ningbo 315000, China.
Jia-Qi ChenNeurological Department of Internal Medicine, Ningbo No. 2 Hospital Ningbo 315000, China.
Hui-Min ChenNeurological Department of Internal Medicine, Ningbo No. 2 Hospital Ningbo 315000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeural stem cells (NSCs) are pluripotent and self-renewing cells which could differentiate into diverse types of neural cells, such as dopaminergic (DA) neurons, the loss of which is the typical characteristic of Parkinson's disease (PD). This study aimed to examine the molecular mechanisms of BMP2-mediating NSCs differentiation into DA neurons.

methodsDifferent concentrations of BMP2 were used to induce the differentiation of NSCs into DA neurons, which were characterized by the number and the neurite lengths of tyrosine hydroxylase (TH)+ and dopamine transporter (DAT)+ neurons by immunocytochemistry. qRT-PCR and Western blot were performed to explore the expression of miR-145 and Nurr1. The methylation level of miR-145 promoter was examined by DNA methylation analyses. The regulation of miR-145 on Nurr1 was detected by Dual-Luciferase reporter assay.

resultsThe number of TH+ and DAT+ neurons were significantly increased in NSCs treated with 20 and 100 ng/ml of BMP2, as well as the neurite lengths of TH+ and DAT+ neurons. The reduced level of miR-145 and up-regulated Nurr1 were observed in NSCs induced by BMP2. The hypermethylation level of miR-145 promoter down-regulated the expression of miR-145 in NSCs pretreated with BMP2, which was regulated by DNMT3b. Luciferase reporter assay showed that Nurr1 was a direct target of miR-145. miR-145 overexpression restrained the differentiating effect of BMP2. Moreover, overexpression of Nurr1 abrogated this effect of miR-145 overexpression.

conclusionOur results showed that BMP2 promoted the differentiation of NSCs into DA neurons

Indexed as

BMP2differentiationdopaminergic neuronsmiR-145Neural stem cellsNurr1

Identifiers

PMID27725851
PMCPMC5040669

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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.