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1.
J Cell Biochem ; 120(2): 1643-1650, 2019 Feb.
Article in English | MEDLINE | ID: mdl-30324654

ABSTRACT

Atherosclerosis has been recognized as a chronic inflammatory disease, which can harden the vessel wall and narrow the arteries. MicroRNAs exhibit crucial roles in various diseases including atherosclerosis. However, so far, the role of miR-328 in atherosclerosis remains barely explored. Therefore, our study concentrated on the potential role of miR-328 in vascular endothelial cell injury during atherosclerosis. In our current study, we observed that oxidized low-density lipoprotein (ox-LDL)-induced human umbilical vein endothelial cells (HUVECs) apoptosis and inhibited cell viability dose-dependently and time-dependently. In addition, indicated dosage of ox-LDL obviously triggered HUVECs inflammation and oxidative stress process. Then, it was found that miR-328 in HUVECs was reduced by ox-LDL. HUVECs apoptosis was greatly repressed and cell survival was significantly upregulated by overexpression of miR-328. Furthermore, mimics of miR-328 rescued cell inflammation and oxidative stress process induced by ox-LDL. Oppositely, inhibitors of miR-328 strongly promoted ox-LDL-induced endothelial cells injury in HUVECs. By using bioinformatics analysis, high-mobility group box-1 (HMGB1) was predicted as a downstream target of miR-328. HMGB1 has been reported to be involved in atherosclerosis development. The correlation between miR-328 and HMGB1 was validated in our current study. Taken these together, it was implied that miR-328 ameliorated ox-LDL-induced endothelial cells injury through targeting HMGB1 in atherosclerosis.

2.
J Cell Biochem ; 119(1): 650-658, 2018 01.
Article in English | MEDLINE | ID: mdl-28636181

ABSTRACT

Acute myocardial infarction (AMI) is a common disease with serious consequences in mortality and cost. Here we aim to screen the differentially expressed genes (DEGs) as biomarkers for early diagnosis of AMI. The microarray data of AMI was downloaded from Gene Expression Omnibus (GEO), including two independent types of research GSE66360 and GSE62646. The DEGs between control and processed samples were screened out by using limma package. Meanwhile, we performed functional analysis of GO terms and/or KEGG pathways to observe the enriched pathways of the DEGs. Finally, regression analysis of raw data was performed by using packet affyPLM in R language. Dataset GSE62646 contained 53 DEGs (FC log2>1 and P value <0.05) between first-day samples from 28 STEMI patients and control samples from 14 patients without myocardial infarction history. There were 12 up-regulated and 41 down-regulated genes, 35 DEGs annotated. In GSE66360, a total of 3034 DEGs between 32 AMI patients and 38 healthy persons were obtained, including 1861 up-regulated and 1173 down-regulated DEGs. The comparison of the DEGs in two datasets revealed four common up-regulated genes (EGR1, STAB1, SOCS3, TMEM176A). In enrichment analysis, STAB1, SOCS3, EGR1 involved in metabolic regulation and signaling pathways related to coronary artery disease with a characteristic change (P < 0.05). The DEGs, especially the four up-regulated common genes, could serve as biomarkers for early diagnosis of AMI. Additionally, the relative biological pathways these DEGs enriched in might provide a good reference to explore the molecular expression mechanism of AMI. J. Cell. Biochem. 119: 650-658, 2018. © 2017 Wiley Periodicals, Inc.


Subject(s)
Biomarkers, Tumor/genetics , Early Detection of Cancer/methods , Gene Regulatory Networks , Myocardial Infarction/diagnosis , Computational Biology , Databases, Genetic , Gene Expression Profiling/methods , Gene Expression Regulation , Genetic Predisposition to Disease , Humans , Myocardial Infarction/genetics , Oligonucleotide Array Sequence Analysis/methods , Regression Analysis
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