Investigation of the potential role of checkpoint kinase2 in the regulation of gastric cancer stem cells

Purpose: To investigate the potential role of checkpoint kinase2 (CHEK2) in regulating gastric cancer stem cells.Methods: The abnormal features of cellular arrangements in early and advanced stages of gastric cancer were analysed using histology. Immunohistochemistry and Western blotting were used to evaluate the expressions of cancer stem cell markers CD44 and CHEK2 at different stages of gastric cancer.Results: When compared with the control tissue, the size of the cellular nucleus was enlarged as the gastric tumour developed to more advanced stages, and the expression of CD44 increased exponentially. The expression of CHEK2, a protein that regulates cell cycle and apoptosis was aberrantly up-regulated at the early stage of cancer, but as the tumour advanced, its expression became down-regulated.Conclusion: These results show that the higher expression of CHEK2 at the early stages of gastric cancer exerts control over gastric cancer stem cell proliferation. Thus, CHECK2 is a potential target for early treatment of gastric cancer.Keywords: Gastric cancer, CD44, CHEK2, Gastric cancer stem cell

Transcriptome profiling of the floating-leaved aquatic plant Nymphoides peltata in response to flooding stress

This table provides all differentially expressed genes meeting the threshold (FDR ≤ 0.01) and the GO terms that the differentially expressed genes were enriched. (XLS 207 kb

The Study of the Composite Material Go/CF/PTFE Tribological Property

In this paper, the composite material Go/CF/PTFE tribological property was studied. The test of its mechanical property, and the fabrication of the filled PTEE composite material sample which is based on the technology of cold press molding and sinter molding proved that adding Go and CF moderately to the composite material was an efficient way to improve its mechanical property. Meanwhile the process of friction and wear trial and SEM analysis results of the micro-structure of wear pattern proved that the addition of the Go and CF tremendously improved the anti-wear property and that after the addition the plowing effect which took place on the material surface would turn into a kind of mixed wear effect that includes plowing effect and fatigue wear. Working as pinning and bridging, the Go which distributing uniformly in the matrix was able to improve the resistance and substantially resisted the crack propagation, therefore to a certain degree enhanced the intensity of composite material and prolong its lifespan

Representing Global Reactive Potential Energy Surfaces Using Gaussian Processes

This article presents a detailed study on constructing potential energy surfaces using a machine learning method, namely, Gaussian process regression

Multiscale Point Correspondence Using Feature Distribution and Frequency Domain Alignment

In this paper, a hybrid scheme is proposed to find the reliable point-correspondences between two images, which combines the distribution of invariant spatial feature description and frequency domain alignment based on two-stage coarse to fine refinement strategy. Firstly, the source and the target images are both down-sampled by the image pyramid algorithm in a hierarchical multi-scale way. The Fourier-Mellin transform is applied to obtain the transformation parameters at the coarse level between the image pairs; then, the parameters can serve as the initial coarse guess, to guide the following feature matching step at the original scale, where the correspondences are restricted in a search window determined by the deformation between the reference image and the current image; Finally, a novel matching strategy is developed to reject the false matches by validating geometrical relationships between candidate matching points. By doing so, the alignment parameters are refined, which is more accurate and more flexible than a robust fitting technique. This in return can provide a more accurate result for feature correspondence. Experiments on real and synthetic image-pairs show that our approach provides satisfactory feature matching performance