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In this paper, we suggest an efficient, accurate and user-friendly brain-computer interface (BCI) system for recognizing and distinguishing different emotion states. For this, we used a multimodal dataset entitled "MAHOB-HCI" which can be freely reached through an email request. This research is based on electroencephalogram (EEG) signals carrying emotions and excludes other physiological features, as it finds EEG signals more reliable to extract deep and true emotions compared to other physiological features. EEG signals comprise low inf

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Functionally, both SNHG3 silencing and miR-326 overexpression enhanced cell apoptosis, but depressed cell viability, migration and invasion in MDA-MB-231 and BT-549 cells, as well as inhibited Vav2 and Rac1 expression. Notably, miR-326 deletion could abolish the tumor-suppressive role of SNHG3 silencing; meanwhile, the similar anti-tumor effect of miR-326 overexpression was abrogated by ITGA5 restoration. Mechanically, SNHG3 silencing downregulated ITGA5 expression by functioning as a molecular "sponge" for miR-326. Conclusions Silenc