RESUMEN
BACKGROUND: MicroRNAs are found to be aberrantly expressed in multiple cancers, including glioblastoma (GBM), and microRNA-221 (miR-221) has been verified as an oncogene in various human cancers. Nevertheless, the role of miR-221 in GBM is unclear. This study aimed to investigate the miR-221 expression level in GBM and to evaluate its function and underlying mechanisms. METHODS: Western blotting and qPCR were used to determine the expression of human hedgehog-interacting protein (HHIP) and miR-221 levels. MiR-221-inhibited cell models were constructed, and siRNA was used for HHIP silencing. Cell proliferation was analyzed by MTT and colony formation assays and a subcutaneous xenograft model. Cell migration and invasion was analyzed by wound healing and Transwell invasion assays. A dual luciferase reporter assay system was used to clarify the relationship between miR-221 and HHIP. RESULTS: The results of this study revealed that miR-221 expression was upregulated in GBM tissues and A172, U251, as well as T98G cells, as detected by real-time PCR analysis. MTT, Transwell, and colony formation assays revealed that miR-221 knockdown could suppress GBM cells from proliferating, migrating, and invading in vitro. Moreover, animal experiments showed that tumor growth in vivo was inhibited when miR-221 expression decreased. Furthermore, HHIP was predicted and verified to be a target of miR-221 by bioinformatics analysis, and luciferase and western blot assays. In addition, HHIP silencing rescued the suppressive effect of a miR-221 inhibitor on the proliferation, migration, and invasion of GBM cells. CONCLUSIONS: Our results indicated that miR-221 is upregulated in GBM and enhances tumor progression by targeting HHIP, which suggests this may be a potential therapeutic target for GBM.
RESUMEN
In this paper, a three-dimensional fractional-order (FO) discrete Hopfield neural network (FODHNN) in the left Caputo discrete delta's sense is proposed, the dynamic behavior and synchronization of FODHNN are studied, and the system is applied to image encryption. First, FODHNN is shown to exhibit rich nonlinear dynamics behaviors. Phase portraits, bifurcation diagrams and Lyapunov exponents are carried out to verify chaotic dynamics in this system. Moreover, by using stability theorem of FO discrete linear systems, a suitable control scheme is designed to achieve synchronization of the FODHNN. Finally, image encryption system based on the chaotic FODHNN is presented. Some security analysis and tests are given to show the effective of the encryption system.