| Title |
Differentiation of mesenchymal stem cells into cardiomyocytes is regulated by miRNA-1-2 via WNT signaling pathway
|
|---|---|
| Published in |
Journal of Biomedical Science, May 2017
|
| DOI | 10.1186/s12929-017-0337-9 |
| Pubmed ID | |
| Authors |
Xing Shen, Bo Pan, Huiming Zhou, Lingjuan Liu, Tiewei Lv, Jing Zhu, Xupei Huang, Jie Tian |
| Abstract |
Bone marrow derived stem cells (BMSCs) have the potential to differentiate into cardiomyocytes, but the rate of differentiation is low and the mechanism of differentiation is unclear completely. Here, we aimed to investigate the role of miR1-2 in differentiation of mouse BMSCs into cardiomyocyte-like cells and reveal the involved signaling pathways in the procedure. Mouse BMSCs were treated with miR1-2 and 5-azacytine (5-aza). The expression of cardiac cell markers: NKx2.5, cTnI and GATA4 in BMSCs were examined by qPCR. The apoptosis rate was detected by flow cytometry and the activity of the Wnt/β-catenin signaling pathway was evaluated by measuring the upstream protein of this signaling pathway. After over-expression of miR1-2 in mouse BMSCs, the apoptosis rate was significantly lower than the 5-aza group, while the expressions of cardiac-specific genes: such as Nkx2.5, cTnI and GATA4 were significantly increased compared to the control group and the 5-aza group. Meanwhile, over-expression of miR1-2 in mouse BMSCs enhanced the expression of wnt11, JNK, β-catenin and TCF in the Wnt/β-catenin signaling pathway. Use of LGK-974, an inhibitor of Wnt/β-catenin signaling pathway, significantly reduced the expression of cardiac-specific genes and partially blocked the role of the miR1-2. Over-expression of miR1-2 in mouse BMSCs can induce them toward promoted cardiomyocyte differentiation via the activation of the Wnt/β-catenin signaling pathway. Compared to 5-aza, miR1-2 can induce differentiation of BMSCs into cardiomyocytes more effectively with a less cytotoxicity. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 73 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 26% |
| Student > Bachelor | 13 | 18% |
| Student > Master | 12 | 16% |
| Student > Doctoral Student | 4 | 5% |
| Researcher | 4 | 5% |
| Other | 4 | 5% |
| Unknown | 17 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 26 | 36% |
| Medicine and Dentistry | 7 | 10% |
| Agricultural and Biological Sciences | 7 | 10% |
| Engineering | 6 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 17 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 May 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from Journal of Biomedical Science
#969
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Outputs of similar age
#284,807
of 325,190 outputs
Outputs of similar age from Journal of Biomedical Science
#9
of 11 outputs
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