Erlotinib resistance causes a high degree of lethality in non-small-cell lung cancer (NSCLC) patients. The high expression and activation of several receptor tyrosine kinases, such as JAK/STAT3, c-Met, and EGFR, play important roles in drug resistance. The development of tyrosine kinase inhibitors is urgently required in the clinic. Our previous study found that Gambogenic acid (GNA), a small molecule derived from the traditional Chinese medicine herb gamboge, induced cell death in several NSCLC cell lines through JAK/STAT3 inhibition. In this study, we investigated the mechanism of action of GNA in erlotinib-resistant NSCLC and patient-derived cells. The inhibition of GNA on FGFR signaling pathway was examined using biochemical kinase assays. NSCLC cell lines (HCC827, HCC827-Erlotinib-resistant, and H1650) and primary cells from patients with NSCLC with clinical resistance to erlotinib were treated with GNA, erlotinib, or their combination. Both kinase assays and cell- based assays showed that GNA inhibits the phosphorylation of multiple kinases in FGFR signaling pathway in NSCLC. The combination of GNA and erlotinib significantly attenuates the tumor growth of HCC827 and erlotinib-resistant HCC827 xenografts with low toxicity. Importantly, GNA significantly suppresses tumor growth in a lung patient-derived xenograft (PDX) model with FGFR fusion and low EGFR expression. Our findings provide preclinical evidence for using GNA as an FGFR signaling pathway inhibitor to overcome erlotinib resistance in NSCLC treatment or to enhance erlotinib efficacy when used as a combined administration.

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Under the challenge of climate change, fuel-based vehicles have been receiving increasingly harsh criticism. To promote the use of battery electric vehicles (BEVs) as an alternative, many researchers have studied the deployment of BEVs. This paper proposes a new method to choose locations for new BEV charging stations considering drivers’ perceived time cost and the existing infrastructure. We construct probability equations to estimate drivers’ demanding time for charging (and waiting to charge), use the Voronoi diagram to separate the study area (i.e., Shanghai) into service areas, and apply an optimization algorithm to deploy the charging stations in the right locations. The results show that (1) the probability of charging at public charging stations is 39.6%, indicating BEV drivers prefer to charge at home; (2) Shanghai’s central area and two airports have the busiest charging stations, but drivers’ time costs are relatively low; and (3) our optimization algorithm successfully located two new charging stations surrounding the central area, matching with our expectations. This study provides a time-efficient way to decide where to build new charging stations to improve the existing infrastructure.

The two-stroke engine is a common power source for small and medium-sized unmanned aerial vehicles (UAV), which has wide civil and military applications. To improve the engine performance, we chose a prototype two-stroke small areoengine, and optimized the geometric parameters of the scavenging ports by performing one-dimensional (1D) and three-dimensional (3D) computational fluid dynamics (CFD) coupling simulations. The prototype engine is tested on a dynamometer to measure in-cylinder pressure curves, as a reference for subsequent simulations. A GT Power simulation model is established and validated against experimental data to provide initial conditions and boundary conditions for the subsequent AVL FIRE simulations. Four parameters are considered as optimal design factors in this research: Tilt angle of the central scavenging port, tilt angle of lateral scavenging ports, slip angle of lateral scavenging ports, and width ratio of the central scavenging port. An evaluation objective function based on the Benson/Bradham model is selected as the optimization goal. Two different operating conditions, including the take-off and cruise of the UAV are considered. The results include: (1) Orthogonal experiments are analyzed, and the significance of parameters are discussed; (2) the best factors combination is concluded, followed by simulation verification; (3) results before and after optimization are compared in details, including specific scavenging indexes (delivery ratio, trapping efficiency, scavenging efficiency, etc.), conventional performance indicators, and the sectional views of gas composition distribution inside the cylinder.

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