| Title |
MicroRNA-34b/c inhibits aldosterone-induced vascular smooth muscle cell calcification via a SATB2/Runx2 pathway
|
|---|---|
| Published in |
Cell and Tissue Research, August 2016
|
| DOI | 10.1007/s00441-016-2469-8 |
| Pubmed ID | |
| Authors |
Jianbing Hao, Lei Zhang, Guangting Cong, Liansheng Ren, Lirong Hao |
| Abstract |
Increasing evidence shows that aldosterone and specific microRNAs (miRs) contribute to vascular smooth muscle cell (VSMC) calcification. In this study, we aim to explore the mechanistic links between miR-34b/c and aldosterone in VSMC calcification. VSMC calcification models were established both in vitro and in vivo. First, the levels of aldosterone, miR-34b/c and special AT-rich sequence-binding protein 2 (SATB2) were measured. Then, miR-34b/c mimics or inhibitors were transfected into VSMCs to evaluate the function of miR-34b/c. Luciferase reporter assays were used to demonstrate whether SATB2 was a direct target of miR-34b/c. Aldosterone and SATB2 were found to be markedly upregulated during VSMC calcification, whereas miR-34b/c expression was downregulated. Treatment with the mineralocorticoid receptor (MR) antagonist eplerenone inhibited VSMC calcification. In aldosterone-induced VSMC calcification, miR-34b/c levels were downregulated and SATB2 protein was upregulated. Furthermore, miR-34b/c overexpression alleviated aldosterone-induced VSMC calcification as well as inhibited the expression of SATB2 protein, whereas miR-34b/c inhibition markedly enhanced VSMC calcification and upregulated SATB2 protein. In addition, luciferase reporter assays showed that SATB2 is a direct target of miR-34b/c in VSMCs. Overexpression of SATB2 induced Runx2 overproduction and VSMC calcification. Therefore, miR-34b/c participates in aldosterone-induced VSMC calcification via a SATB2/Runx2 pathway. As miR-34b/c appears to be a negative regulator, it has potential as a therapeutic target of VSMC calcification. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 27% |
| Other | 1 | 9% |
| Student > Bachelor | 1 | 9% |
| Lecturer | 1 | 9% |
| Student > Master | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 3 | 27% |
| Biochemistry, Genetics and Molecular Biology | 2 | 18% |
| Agricultural and Biological Sciences | 1 | 9% |
| Unknown | 5 | 45% |
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 20 August 2016.
All research outputs
#19,236,357
of 23,839,820 outputs
Outputs from Cell and Tissue Research
#1,706
of 2,279 outputs
Outputs of similar age
#286,502
of 368,374 outputs
Outputs of similar age from Cell and Tissue Research
#21
of 36 outputs
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