Pancreatic cancer (PC) is the fourth most common cause of cancer-related deaths in the United States, suggesting that designing novel therapeutic strategy is required to improve the survival outcome of patients diagnosed with PC. Recently, microRNAs (miRNA) have been found to be involved in the regulation of multiple aspects of tumor development and progression including PC. In this study, we investigate whether miR-34a plays a critical role in the control of cell growth and apoptosis in PC cells. We found that Re-expression (forced expression) of miR-34a inhibits cell growth and induces apoptosis, with concomitant down-regulation of Notch-1 signaling pathway, one of the target of miR-34a. Moreover, treatment of PC cells with a natural compound genistein led to the up-regulation of miR-34a, resulting in the down-regulation of Notch-1, which was correlated with inhibition of cell growth, and induction of apoptosis. Our findings suggest that genistein could function as a non-toxic activator of a miRNA that can suppress the proliferation of PC cells.

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In order to solve the problem that it is necessary to scan the database many times and produce unnecessary frequent itemsets in the process of mining indirect association rules, a new algorithm FPI-mine based on FP-Tree is designed to mine the indirect association rules in transaction database. Firstly, FP-Tree is constructed, and then the indirect item pairs and intermediate support sets of all frequent items are found. Finally, all the indirect association rules are obtained by mining algorithm. It can directly mine indirect association rules without generating all frequent itemsets. Finally, the effectiveness of the algorithm is verified by experiments.

Usually, the algorithm of constructing cost-sensitive decision tree assume that all types of cost can be converted into a unified units of the same price, apparently how to construct an cost conversion function is an challenge. In this paper, a strategy of constructing heterogeneous cost-sensitive decision tree is designed and the different cost are take into account together in split attribute selection. What's more, an attribute selection model based on heterogeneous cost-sensitive is constructed and the pruning strategy based on cost-sencitive is designed. The experimental results show that the proposed method is correct and more efficient than the present other methods