Objective To explore the expression of Octamers binding transcription factor 4 (Oct4) and its relationship with clinicopathological parameters in the non-small cell lung cancer (NSCLC) tissues .Methods From September 2013 to December 2016 ,100 cases of NSCLC patients with lung cancer (group NSCLC ,n=100) and their corresponding normal paracancerous tissues (the control group ,n=100) were selected as the samples .The expression of Oct4 mRNA and protein in two groups of tissue samples were detected by fluores-cence quantitative PCR ,immunohistochemistry and western blot .The relationship between the level of Oct4 expression and the clinicopathological parameters of the patients was analyzed ,and the prognosis of the Oct4 positive and negative patients in the NSCLC group was compared .Results The expression of Oct4 mRNA in NSCLC group was (3 .21 ± 0 .18) ,protein expression was (0 .74 ± 0 .11) and the positive rate was 74 .00％ , which were significantly higher than those of control group [(1 .47 ± 0 .11) ,(0 .10 ± 0 .03) ,10 .00％ ,P<0 .05] .The positive rate of Oct4 expression in NSCLC patients was not related to sex ,age ,smoking index and tumor size (P>0 .05) ,but related to pathological type ,degree of differentiation ,and TNM staging ,in which the positive rates of Oct4 in patients with adenocarcinoma ,low differentiation and TNM stage Ⅲ stage were significantly higher than those of non adenocarcinoma ,middle-high differentiation degree ,Ⅰ - Ⅱ TNM stage patients (P< 0 .05) .In NSCLC patients ,compared with Oct4 negative patients ,the distant metastasis rate (64 .86％ ) ,pulse tube infiltration rate (47 .30％ ) in Oct4 positive patients were significantly higher ,and the 1 year survival rate (67 .57％ ) decreased (P<0 .05) .Conclusion The expression of Oct4 in NSCLC tissue is closely related to its clinicopathological parameters .Oct4 is highly expressed in adenocarcinoma ,and with thedecrease of differentiation and progression of tumor stages ,the expression increases and affects the prognosis . Oct4 can be used as a specific diagnostic marker of NSCLC .

Brain-computer interface (BCI) is a revolutionary human-computer interaction technology, which includes both BCI that can output instructions directly from the brain to external devices or machines without relying on the peripheral nerve and muscle system, and BCI that bypasses the peripheral nerve and muscle system and inputs electrical, magnetic, acoustic and optical stimuli or neural feedback directly to the brain from external devices or machines. With the development of BCI technology, it has potential application not only in medical field, but also in non-medical fields, such as education, military, finance, entertainment, smart home and so on. At present, there is little literature on the relevant application of BCI technology, the current situation of BCI industrialization at home and abroad and its commercial value. Therefore, this paper expounds and discusses the above contents, which are expected to provide valuable information for the public and organizations, BCI researchers, BCI industry translators and salespeople, and improve the cognitive level of BCI technology, further promote the application and industrial transformation of BCI technology and enhance the commercial value of BCI, so as to serve mankind better.
Brain/physiology* ; Brain-Computer Interfaces ; Electroencephalography ; Humans ; Technology ; User-Computer Interface

Motor imagery (MI) is an important paradigm of driving brain computer interface (BCI). However, MI is not easy to control or acquire, and the performance of MI-BCI depends heavily on the performance of the subjects' MI. Therefore, the correct execution of MI mental activities, ability evaluation and improvement methods play important and even critical roles in the improvement and application of MI-BCI system's performance. However, in the research and development of MI-BCI, the existing researches mainly focus on the decoding algorithm of MI, but do not pay enough attention to the above three aspects of MI mental activities. In this paper, these problems of MI-BCI are discussed in detail, and it is pointed out that the subjects tend to use visual motor imagery as kinesthetic motor imagery. In the future, we need to develop some objective, quantitatively visualized MI ability evaluation methods, and develop some effective and less time-consumption training methods to improve MI ability. It is also necessary to solve the differences and commonness of MI problems between and within individuals and MI-BCI illiteracy to a certain extent.
Algorithms ; Brain-Computer Interfaces ; Electroencephalography ; Humans ; Imagery, Psychotherapy ; Imagination