https://www.selleckchem.com/ALK.html Next generation cellular systems need efficient content-distribution schemes. Content-sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. In this article, we utilize Content-Centric Networking and Network Virtualization to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multifactor clustering algorithm is proposed for grouping the D2D User Equipment (DUEs) sharing a common interest. The proposed algorithm is evaluated in terms of energy efficiency, area spectral efficiency, and throughput. The effect of the number of clusters on these performance parameters is also discussed. The proposed algorithm has been further modified to allow for a tradeoff between fairness and other performance parameters. A comprehensive simulation study demonstrates that the proposed clustering algorithm is more flexible and outperforms several classical and state-of-the-art algorithms.Epithelial ovarian cancer (EOC) is the deadliest gynecological cancer, and the major cause of death is mainly attributed to metastasis. MicroRNAs (miRNAs) are a group of small non-coding RNAs that exert important regulatory functions in many biological processes through their effects on regulating gene expression. In most cases, miRNAs interact with the 3' UTRs of target mRNAs to induce their degradation and suppress their translation. Aberrant expression of miRNAs has been detected in EOC tumors and/or the biological fluids of EOC patients. Such dysregulation occurs as the result of alterations in DNA copy numbers, epigenetic regulation, and miRNA biogenesis. Many studies have demonstrated that miRNAs can promote or suppress events related to EOC metastasis, such as cell migration, invasion, epithelial-to-mesenchymal transition, and interaction with the tumor microenvironm