Jin-Shi Zhang

Currently, renal cell carcinoma (RCC) is the most prevalent type of kidney cancer. Targeted therapy has replaced radiation therapy and chemotherapy as the main treatment option for RCC due to the lack of significant efficacy with these conventional therapeutic regimens. Sunitinib, a drug used to treat gastrointestinal tumors and renal cell carcinoma, inhibits the tyrosine kinase activity of a number of receptor tyrosine kinases, including vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), c-Kit, rearranged during transfection (RET) and fms-related receptor tyrosine kinase 3 (Flt3). Although sunitinib has been shown to be efficacious in the treatment of patients with advanced RCC, a significant number of patients have primary resistance to sunitinib or acquired drug resistance within the 6-15 months of therapy. Thus, in order to develop more efficacious and long-lasting treatment strategies for patients with advanced RCC, it will be crucial to ascertain how to overcome sunitinib resistance that is produced by various drug resistance mechanisms. In this review, we discuss: 1) molecular mechanisms of sunitinib resistance; 2) strategies to overcome sunitinib resistance and 3) potential predictive biomarkers of sunitinib resistance.

Due to progress in the research of glioma stem cells and the glioma niche, development of an animal model that facilitates the elucidation of the roles of the host tissue and cells is necessary. The aim of the present study was to develop a subcutaneous xenograft green fluorescent protein nude mouse model and use this model to analyze the roles of host cells in tumor necrosis repair. Tumors derived from the human glioma stem/progenitor cell line SU3 were subcutaneously implanted in green fluorescent protein nude mice. The implanted tumors were then passed from animal to animal for 10 generations. Finally, subcutaneous xenografts were assayed with traditional pathology, immunopathological techniques and fluorescence photography. For each generation, the tumorigenicity rate was 100%. Subcutaneous xenografts were rich in blood vessels, and necrotic and hemorrhagic foci, which highly expressed hypoxia-inducible factor-1α, tumor necrosis factor, Ki-67, CD68 and CD11b. In the interstitial tissue, particularly in old hemorrhagic foci, there were numerous cells expressing green fluorescent protein, CD68 and CD11b. Green fluorescent protein nude mouse subcutaneous xenografts not only consistently maintained the high invasiveness and tumorigenicity of glioma stem/progenitor cells, but also consisted of a high concentration of tumor blood vessels and necrotic and hemorrhagic foci. Subcutaneous xenografts also expressed high levels of tumor microenvironment-related proteins and host-derived tumor interstitial molecules. The model has significant potential for further research on tumor tissue remodeling and the tumor microenvironment.

Aiming at problems such as tracking failure caused by illumination changes often encountered during unmanned aerial vehicle (UAV) tracking, a target tracking algorithm with illumination adaptive and future-aware correlation filters is proposed based on the background-aware correlation filters (BACF) algorithm, which realizes reliable UAV tracking tasks at night. First, the dark scene is recognized, and an efficient image enhancement module is used to enhance the brightness of low illumination images. Then a future-aware module is constructed to train the tracking model using the contextual information of the target in the next frame for better robustness. Finally, the model updating stage involves adaptive filter updating and adaptive learning rate updating to enhance target tracking precision. The results of the comparison experiments with the state-of-the-art algorithms on the UAVDark135, UAVDT, and DTB70 datasets show that the algorithm in this paper outperforms the state-of-the-art tracking methods and has better tracking performance under light changes and fast motion (FM) scenarios. The tracking speed on a single Central processing unit (CPU) reaches 49 FPS, which satisfies the real-time requirement of UAV tracking.

In this study, we propose effective monitoring equipment intended for monitoring the underground tunnel of illegal excavation (such as theft, jailbreak, and smuggling). It mainly detects the microseismic information produced by underground excavation in a short distance to detect the status of underground excavation. Based on the arrival time difference principle, the positioning mathematical models of the 5‐1‐1 layout method, 4‐3 layout method, and 7‐0‐0 layout method are established, respectively. In the research process, the measurement and the placement error caused by the installation of a seismic detector are joined into the detectors. Simulation results show that the relative error and its average value are obtained when mining outside the monitoring area. The experiment results demonstrate that, first, the depth positioning error is positively affected by the number of seismic detectors. Then, the relative error of plane positioning can be reduced when the installation distance among detectors is increased. Finally, the main causes of location error include time measurement error, propagation velocity difference caused by terrain, and the performance of detector hardware. The array of a ground motion detector has a weak influence on it. These emerging trends will have profound impacts on application of an underground excavation system.