BackgroundThe role of dysfunction of MCPH1, a recently identified tumor suppressor gene, has not yet been established in lung cancer. In our previous study, it was reported that MCPH1 expression is downregulated in lung cancer tissues and that MCPH1 overexpression inhibits the proliferation of non-small-cell lung cancer cells. The results can be found in the APJC and Oncology Letters journals.MethodsKaplan-Meier survival analysis was conducted to explore the prognostic significance of MCPH1. Cell experiments were performed to investigate the effects of MCPH1 on the biologic behaviors of lung cancer cells.ResultsIn the current study, microarray analysis of MCPH1 revealed that lung cancer patients with high MCPH1 expression had longer relapse-free survival. Overexpression of MCPH1 in A549 lung carcinoma cells successfully inhibited cell migration and invasion. Moreover, overexpression of MCPH1 inhibited migration and invasion by regulating the activities of several proteins that control the epithelial–mesenchymal transition, such as Slug, Snail, E-cadherin, Mdm2, and p53.ConclusionOur results indicate that downregulation of MCPH1 correlates with tumor progression in lung cancer, and hence MCPH1 may be an important tumor suppressor gene and a novel candidate therapeutic target in lung cancer.

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The overall outcomes for patients with advanced liver cancer are far from satisfactory, and the development of more effective therapeutic strategies for liver cancer is required. Sulforhodamine blue and colony formation assays were performed to detect the proliferation of liver certain cancer cells, including HepG2 and Hep3B. Western blotting was also preformed to detect the expression of indicated proteins, including cleaved-caspase-3, cleaved-poly (ADP-ribose) polymerase, dual-specificity tyrosine phosphorylation kinase 1A (DYRK1A), PARP-1/2, GAPDH, myeloid cell leukemia-1, phosphorylated-AKT (Ser473), caspase-3, α-tubulin and AKT. PI staining was used to detect cell death. In the present study, DYRK1A knockdown significantly enhanced the anti-liver cancer effect of regorafenib in vitro. Furthermore, DYRK1A inhibitor harmine together with regorafenib provided synergistic anti-liver cancer activity by suppressing cell proliferation. In addition, harmine significantly enhanced regorafenib-induced cell death in liver cancer cells. It has been reported that AKT signaling is activated in regorafenib-resistant cancer cells and plays a crucial role in the regulation of cellular sensitivity to regorafenib. In the present study, AKT was activated in regorafenib-treated cells, and harmine could suppress the activation of AKT and reinforce the anti-cancer effects of regorafenib via regulating AKT in liver cancer cells. These data indicated that harmine enhanced the anti-cancer effects of regorafenib on suppressing cell proliferation and inducing apoptosis in liver cancer cells via regulating the activation of AKT, and harmine plus regorafenib may be a potential therapeutic regimen for treating patients with liver cancer.

This study proposes a novel digital video stabilisation scheme based on modelling of motion imaging (MI). The modelling of MI eliminates the speed motion as a result of a moving car, which is ignored in other models such as rotation + translation model, and estimates movement parameters of the background in video sequences captured from cameras mounted on moving cars. The authors first analyse the MI to understand the principle of the effects of car motion on MI, and select the matching method according to the proposed model. Then, they employ symmetric points to remove the speed motion. Finally, unwanted motion vector is stimulated by employing adaptive step-length filter, and the boundary compensating approach is employed to suppress the image jitter effectively. Their major contribution is the elimination of the effect of carrier's speed in motion estimation. Other contributions include new robust block matching approach and adaptive-step selection for motion filtering. They conduct experiments on real videos and artificial data. Experiments on real videos show that the proposed model can remove the effect of car motion, whereas the experiments on artificial data are conducted for theoretical analysis.

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