BACKGROUND: Nuclear pore membrane protein 121 (POM121) is a novel biomarker involved in tumorigenesis and metastasis. However, little is known about the role of POM121 in non-small-cell lung cancer (NSCLC). OBJECTIVE: The aim of this study was to detect the expression of POM121 in NSCLC and its relationship with clinicopathologic feature and cell biological behavior, and explore the underlying mechanisms. METHODS: The expression of POM121 in NSCLC tissues and para-carcinoma tissues was compared by quantitative real-time PCR and immunohistochemistry analysis. The relationship between POM121 protein and clinicopathological characteristics in NSCLC was investigated. Roles of POM121 in NSCLC cells were investigated by CCK-8 assay, clone formation assay, transwell migration and invasion assay, and in vivo experiments. Variations of signaling pathways were determined by qRT-PCR and Western blot. RESULTS: The POM121 expression in NSCLC tissues was significantly higher than that in para-carcinoma tissues, both at the mRNA and protein level. The POM121 expression was related to sex, advanced differentiation, tumor diameter, lymph node metastases, distant metastases, American Joint Committee on Cancer (AJCC) stage, venous invasion, and perineural invasion in NSCLC. Kaplan-Meier analysis indicated that NSCLC patients with high POM121 expression had poor overall survival. Downregulation of POM121 inhibited cell proliferation, clone formation, migration and invasion. TGF-β/SMAD and PI3K/AKT pathways were involved in POM121-induced functional changes in NSCLC cells. CONCLUSION: POM121 plays an oncogenic role in NSCLC through TGF-β/SMAD and PI3K/AKT pathways. POM121 expression is a potential independent prognostic factor for NSCLC.

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Compared with field oriented control (FOC), direct thrust control (DTC) is known to provide fast and robust response for permanent magnet linear synchronous motor (PMLSM). However, classical DTC produces notable thrust ripples because parameters variation and load perturbation. A novel adaptive variable structure controller is presented. The mover flux and thrust are controlled directly by adaptive variable structure controller, and mover voltage vectors calculated by the adaptive variable structure controller are applied to the motor by means of space vector modulation. Simulation results are presented to illustrate performances of the proposed method. The system provides smooth, fast mover speed and thrust responses and is robust with respect to motor parameters variation and load perturbations.

An recurrent fuzzy neural network (RFNN) compensation strategy combined with the backstepping approach for permanent magnet linear synchronous motors (PMLSMs) drive is proposed. Considering the lumped uncertainties with parameter variations and external disturbance for an actual PMLSM drives, a backstepping control law is derived by backstepping design technique. However, the upper bound of the lumped uncertainty is difficult to obtain in advance in practical applications. A RFNN observer is proposed to adapt the value of lumped uncertainty, the online parameters training of the RFNN is derived by the gradient descent method. Simulated results show that the proposed method possesses better position tracking performances and robustness to lumped uncertainty for PMLSM drive. Keywords-permanent magnet linear synchronous motor (PMLSM); gradient descent method; backstepping control; recurrent fuzzy neural network(RFNN)