Authors: A.O. Chiromatzo, T.Y.K. Oliveira, G. Pereira, A.Y. Costa, C.A.E. Montesco, D.E. Gras, F. Yosetake, J.B. Vilar, M. Cervato, P.R.R. Prado, R.G.C.C.L. Cardenas, R. Cerri, R.L. Borges, R.N. Lemos, S.M. Alvarenga, V.R.C. Perallis, D.G. Pinheiro, I.T. Silva, R.M. Brand�£o, M.A.V. Cunha, S. Giuliatti and W.A. Silva Jr
MicroRNAs (miRNAs) are small non-coding RNAs that regulate target gene expression and hence play important roles in metabolic pathways. Recent studies have evidenced the interrelation of miRNAs with cell proliferation, differentiation, development, and diseases. Since they are involved in gene regulation, they are intrinsicall.. Read More»
Authors: L. Ren1*, R. Zhu2* and X. Li1
Epilepsy is one of the most frequent neurological disorders. Recently, the regulation of microRNAs was found to be associated with epilepsy, but the molecular mechanism by which microRNA influences epilepsy process remains to be unveiled and the development of microRNA-based therapy requires more intensive research. In this study, five microRNAs with pote.. Read More»
Authors: P.F. Liu, W.H. Jiang, Y.T. Han, L.F. He, H.L. Zhang and H. Ren
The main aim of this study was to explore the underlying molecular mechanisms and potential target molecules of pancreatic adenocarcinoma. The miRNA (GSE32678) and mRNA (GSE32676) expression profiles of patients with pancreatic ductal adenocarcinoma and healthy controls were downloaded from the Gene Expression Omnibus database. Differentially expressed mi.. Read More»
Authors: J. Han, H. Xie, M.L. Kong, Q.P. Sun, R.Z. Li and J.B. Pan
MicroRNAs (miRNAs) are a class of non-coding small RNAs that negatively regulate gene expression at the post-transcriptional level. Although thousands of miRNAs have been identified in plants, limited information is available about miRNAs in Phaseolus vulgaris, despite it being an important food legume worldwide. The high cons.. Read More»
Authors: Y.H. Cao, H.H. Zhang,H.F. Xu, Y.J. Duan, Q. Li, B. Huang
We investigated the clinical significance and prognostic value of microRNA-100 (miR-100) in bladder cancer. Quantitative real-time polymerase chain reaction was used to analyze the expression of miR-100 in 92 pairs of human bladder cancer and adjacent normal tissue samples. Overall survival (OS) curves were plotted using the K.. Read More»
Authors: L. Dong1, K.H. Bi1, N. Huang1 and C.Y. Chen2
Chronic lymphocytic leukemia (CLL) is a disease that involves progressive accumulation of nonfunctioning lymphocytes and has a low cure rate. There is an urgent requirement to determine the molecular mechanism underlying this disease in order to improve the early diagnosis and treatment of CLL. In this study, genes differentially expressed between CLL sam.. Read More»
Authors: Q.W. Li,T. Zhou, F. Wang,M. Jiang, C.B. Liu, K.R. Zhang, Q. Zhou, Z. Tian, K.W. Hu
It has been shown that microRNA-215 (miR-215) is dysregulated in several human malignancies, and this correlates with tumor progression. However, its expression and function in pancreatic cancer is still unclear. The aim of this study was to explore the effects of miR-215 on pancreatic cancer formation and progression. Using q.. Read More»
Authors: F.Q. Li, B. Xu, Y.J. Wu Z.L. Yang and J.J. Qian
Gastric cancer is a disease with a heterogeneous pathology; its pathological mechanisms remain unclear because there is a poor understanding of its etiology. In this study, we identified differentially expressed microRNAs (miRNAs) among various gastric cancer subtypes. miRNA microarray analysis and bioinformatic analysis were used to compare miRNA expression.. Read More»
Authors: X.H. Wang, F.R. Wang, Y.F. Tang, H.Z. Zou and Y.Q. Zhao
We investigate the potential association of miR-149C>T and miR-499A>G polymorphisms and the risk of hepatocellular carcinoma (HCC). A matched case-control study of 152 cases and 304 controls were conducted. The miR-149C>T and miR-499A>G genotypes were analyzed using duplex polymerase chain reaction with restricted .. Read More»
Authors: J.C. Lu and Y.P. Zhang
In this study, we examined the molecular mechanism of thyroid carcinoma (THCA) using bioinformatics. RNA-sequencing data of THCA (N = 498) and normal thyroid tissue (N = 59) were downloaded from The Cancer Genome Atlas. Next, gene expression levels were calculated using the TCC package and differentially expressed genes (DEGs) were identified using the ed.. Read More»