ABSTRACT
Objective This study aimed to investigate the relationship between CLPTM1L gene and lung cancer 95-D cells sensitivity to gemcitabine,and to explore its potential mechanism of action. Methods Overexpression of lentivirus against CLPTM1L gene was constructed and infected with lung cancer 95-D cells;Cells were divided into the CLPTM1L overexpression group and con-trol group;The proliferation of cells in the overexpressing and control groups after gemcitabine treatment was detected by CCK-8;The changes of CLPTM1L gene and protein were detected by real-time PCR,Western blot and immunochemiluminescence;The changes of caspase-3/7 and caspase-9 activities were detected by bioluminescence;Western blot was used to detect the changes of p-4E-BP1 protein. Results The expression of CLPTM1L gene( P =0. 036) and its protein ( P <0. 01) was significantly increased after CLPTM1L overexpressed lentivirus-infected 95 -D cells;Compared with the control group,the proliferation of CLPTM1L overex-pressing group after gemcitabine treatment was increased(P <0. 01);The activity of caspase activity showed that the activities of caspase-3/7 and caspase-9 in the CLPTM1L overexpression group were significantly lower than those in the control group(P<0. 01);The phosphorylated level of 4E-BP1 protein in the CLPTM1L overexpression group was significantly higher than that in the control group. Conclusion Overexpression of CLPTM1L can reduce the sensitivity of lung cancer cells to gemcitabine. Its mechanism may be to increase the phosphorylation level of 4E-BP1.
ABSTRACT
Principal component analysis (PCA) is widely used to extract features and reduce dimensionality in various computer vision and image/video processing tasks. Conventional approaches either lack robustness to outliers and corrupted data or are designed for one-dimensional signals. To address this problem, we propose a robust PCA model for two-dimensional images incorporating structured sparse priors, referred to as structured sparse 2D-PCA. This robust model considers the prior of structured and grouped pixel values in two dimensions. As the proposed formulation is jointly nonconvex and nonsmooth, which is difficult to tackle by joint optimization, we develop a two-stage alternating minimization approach to solve the problem. This approach iteratively learns the projection matrices by bidirectional decomposition and utilizes the proximal method to obtain the structured sparse outliers. By considering the structured sparsity prior, the proposed model becomes less sensitive to noisy data and outliers in two dimensions. Moreover, the computational cost indicates that the robust two-dimensional model is capable of processing quarter common intermediate format video in real time, as well as handling large-size images and videos, which is often intractable with other robust PCA approaches that involve image-to-vector conversion. Experimental results on robust face reconstruction, video background subtraction data set, and real-world videos show the effectiveness of the proposed model compared with conventional 2D-PCA and other robust PCA algorithms.
ABSTRACT
The recent human infection with avian influenza virus revealed that H9N2 influenza virus is the gene donor for H7N9 and H10N8 viruses infecting humans. The crucial role of H9N2 viruses at the animal-human interface might be due to the wide host range, adaptation in both poultry and mammalian, and extensive gene reassortment. As the most prevalent subtype of influenza viruses in chickens in China, H9N2 also causes a great economic loss for the poultry industry, even under the long-term vaccination programs. The history, epidemiology, biological characteristics, and molecular determinants of H9N2 influenza virus are reviewed in this paper. The contribution of H9N2 genes, especially RNP genes, to the infection of humans needs to be investigated in the future.
