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Gliomas are the most common and aggressive type of primary adult brain tumors. Although GGNBP2 has previously been considered to be a tumor suppressor gene, little is known about the association between GGNBP2 and glioma. In this study, we clearly demonstrated that GGNBP2 was downexpressed in glioma tissues, and its downexpression is related to the pathological grade and overall survival of patients with gliomas. Overexpression of GGNBP2 suppressed the proliferation, migration, and invasion of glioma cells. Mechanistically, we demonstrated that the PI3K/Akt and Wnt/β-catenin signaling pathways were suppressed by GGNBP2 overexpression. In contrast, knockdown of GGNBP2 has precisely the opposite effect. Collectively, these data indicate that GGNBP2 shows tumor suppressive activity in human glioma cells and may stand out as a potential therapeutic target for glioma.

A frequency‐reconfigurable antenna is presented for multiband (GSM850/900/GLONASS1616/DCS1800/PCS 1900/UMTS/LTE2300/2500/WLAN) mobile handset applications. It mainly consists of radiating elements with two PIN diodes. By switching the ON/OFF states of the PIN diodes, the proposed structure can operate in three states: OFF–ON, ON–OFF, and ON–ON. When PIN diodes are in the OFF–ON states, the proposed antenna can cover the GSM850/900, PCS1900, and UMTS2100 bands by operating in Invented‐F antenna (IFA) mode. When PIN diodes are in the ON–OFF states, the antenna can cover the LTE2300/2500 and WLAN2400 bands in monopole mode. Moreover, when PIN diodes are switched to the ON–ON states, the designed antenna works in loop mode and its resonant frequencies include the GLONASS1616, DCS1800/1900, and LTE2500 bands. With the reconfigurable technique, the proposed antenna achieves a compact size of 15 × 28.5 mm2 with high efficiency from 34% to 84.86% in the total frequency range.

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Aiming at the requirements of vehicle safety collision avoidance system, a safety collision avoidance algorithm based on environmental characteristics and driver characteristics is proposed. By analyzing the relationship between collision avoidance time and the environment, a safety time model is established. In the established safety time model, parameters based on driver characteristics are added, which increases the flexibility of the algorithm. The algorithm can adapt to more different driving conditions and give appropriate warning thresholds. After simulation and comparison with other algorithms, the algorithm proposed in this paper can satisfied the requirements of reducing vehicle collision risk. The effectiveness and feasibility of the algorithm are verified, and the safety of vehicle driving can be improved.