MicroRNA-937 inhibits the malignant phenotypes of breast cancer by directly targeting and downregulating forkhead box Q1.

Purpose: Numerous microRNAs (miRNAs) are aberrantly expressed in breast cancer, and the dysregulation of miRNAs may affect the aggressiveness of this cancer. Aberrant expression of miRNA-937 (miR-937) in gastric and lung cancers has been reported, which plays tumor-suppressive or oncogenic roles in carcinogenesis including cancer progression. Our purpose was to investigate the involvement of miR-937 in breast cancer progression. Patients and methods: The expression profile of miR-937 in breast cancer was assessed by reverse-transcription quantitative PCR. Biological effects of miR-937 upregulation on the malignant characteristics of breast cancer cells were determined in a series of functional experiments. The direct target of miR-937 in breast cancer cells was also identified. Results: Herein, the expression levels of miR-937 were notably lower in breast cancer, and its underexpression was significantly correlated with lymph node metastasis and TNM stage. Patients with breast cancer underexpressing miR-937 showed shorter overall survival than did patients with breast cancer overexpressing miR-937. Proliferation, migration, and invasiveness of breast cancer cells were evidently suppressed by miR-937 upregulation. In addition, ectopic miR-937 expression hindered breast cancer tumor growth in vivo. Forkhead box Q1 (FOXQ1) mRNA was found to be a direct target of miR-937 in breast cancer. FOXQ1 turned out to be overexpressed in breast cancer tissues, and its overexpression negatively correlated with miR-937 expression. Moreover, silencing of FOXQ1 recapitulated the tumor-suppressive effects of miR-937 overexpression on breast cancer cells. Notably, FOXQ1 restoration abrogated the miR-937-mediated suppression of proliferation, migration, and invasiveness of breast cancer cells. Conclusion: These results collectively revealed that miR-937 acts as a tumor suppressor in breast cancer and restrains cancer progression by directly targeting FOXQ1 mRNA. These data suggest that targeting of the novel miR-937-FOXQ1 axis is an attractive therapeutic method against breast cancer.

A steady-state target calculation method based on "point" model for integrating processes.

Aiming to eliminate the influences of model uncertainty on the steady-state target calculation for integrating processes, this paper presented an optimization method based on "point" model and a method determining whether or not there is a feasible solution of steady-state target. The optimization method resolves the steady-state optimization problem of integrating processes under the framework of two-stage structure, which builds a simple "point" model for the steady-state prediction, and compensates the error between "point" model and real process in each sampling interval. Simulation results illustrate that the outputs of integrating variables can be restricted within the constraints, and the calculation errors between actual outputs and optimal set-points are small, which indicate that the steady-state prediction model can predict the future outputs of integrating variables accurately.

Cascade process modeling with mechanism-based hierarchical neural networks.

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.