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Lifen Peng,1 Hailan Yan,2 Shuyi Qi,3 Lifei Deng4 1Department of Otolaryngology, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, People’s Republic of China; 2Department of Clinical Medicine, Xi’an Jiaotong University Health Science Center, Xi’an, People’s Republic of China; 3Department of Pathology, Jiangxi Provincial Cancer Hospital, Nanchang, People’s Republic of China; 4Head and Neck Cancer Surgery, Jiangxi Provincial Cancer Hospital, Nanchang, People’s Republic of ChinaCorrespondence: Lifei DengHead and Neck Cancer Surgery, Jiangxi Provincial Cancer Hospital, Nanchang 330006, People’s Republic of ChinaTel +86 13657099876Email denglifei@126.comAim: To investigate the role of CAB39 in nasopharyngeal carcinoma (NPC) development and examine its expression level in NPC tumor samples.Methods: Immunohistochemistry staining of NPC tissue microarray was conducted to detect the expression of CAB39 protein in NPC tissues, and the clinical significance of CAB39 was evaluated. Lentivirus-mediated over-expression of CAB39 was designed to increase CAB39 expression in CNE-1 cells. Cell colony formation, cell cycle and CCK-8 proliferation experiments were performed to compare the proliferation ability of CNE-1 cells with or without CAB39 over-expression. Western blotting was conducted to examine downstream targets of CAB39.Results: CAB39 expression was higher in tumor samples compared to normal tissue and the higher CAB39 expression was positively correlated to higher TNM stage and distant metastasis rate and non-keratinized state. Further, CAB39 over-expression dramatically increased the proliferation and colony formation of CNE-1 cells. Finally, higher p-JNK protein level was found in CAB39 over-expressing cells.Conclusion: CAB39 promotes the proliferation of CNE-1 cells via up-regulating p-JNK.Keywords: CAB39, proliferation, nasopharyngeal carcinoma, p-JNK

In the DOA estimation of monostatic L-shaped array MIMO radar, Multiple Signal Classification algorithm is efficient. But the peak searching process of Multiple Signal Classification algorithm needs large amount of spectrum calculation. Focusing on the spectrum peak searching process of Multiple Signal Classification, an iterative search approach to reduce the calculation amount is proposed. The first- and second-order derivatives of Multiple Signal Classification spectrum functions are achieved and the calculation amount is analyzed. Two-dimensional Newton iteration methods are applied with multisearching threads and derivation information. The searching approach can greatly reduce the computational complexity of Multiple Signal Classification spectrum peak searching. The total calculation amount of the first and second derivatives is about 15 times of the spectrum function. However, in the two-dimensional searching, especially in the high accuracy processes, the amount of searched points can be reduced by ten hundreds times, and the computation is much lower than the common spectrum peak searching method. The simulation results show that when the search thread number reaches 100, the searching process can effectively achieve the entire spectrum peak and get the correct DOA estimation.