Validation and identification of tumour endothelial markers and their uses in cancer vaccine

The abnormal tumour microenvironment, which is typically hypoxic, acidic and with poor blood flow, induces the endothelial expression of genes not found on normal microvessels. By selectively targeting these tumour endothelial markers (TEMs) it is possible to induce tumour regression, presenting a potential strategy for therapeutic intervention. Potential TEMs were predicted by bioinformatics data mining. Validation of these TEM candidates identified a novel TEM CLEC14A. Functional characterization suggests a regulatory role of CLEC14A in endothelial cell migration. Inhibition of endothelial migration by CLEC14A antisera or monoclonal antibody holds therapeutic promise for the treatment of cancer. Differential gene expression analysis of freshly isolated lung tumour endothelium by 2nd generation sequencing identified 13 putative TEMs. Subsequent validation work confirmed six of which to be expressed on lung tumour vasculature. Finally, a pre-validated marker, Robo4, was investigated as a cancer vaccine. A strong antibody response was induced by delivery of pure mouse Robo4 protein or a Robo4 conjugate. The in vivo sponge assay in Robo4 vaccinated mice showed a significant reduction in vessel invasion. Tumour implantation experiments in vaccinated mice showed a marked delay in tumour growth

Understanding the role of rock heterogeneity in controlling fault strength and stability

The rock heterogeneity exists widely in fault zones; however, the intrinsic mechanism of how it affects the mechanical behavior of faults is poorly understood. To develop a quantitative understanding of the effect of the rock heterogeneity on the strength and stability of faults, here we investigate a pore-pressure model based on rate- and-state friction in the manner of two-degree-of-freedom spring-sliders and analyze the reasons of fault weakening and the conditions of frictional instability by carrying out nonlinear simulations and a linear stability analysis. We find that the strength of heterogeneous faults depends largely on the compaction difference (or differential compaction) between the two gouges (e.g. quartz and clay), and the stability is affected by the proportion of the two gouges patches. Our model implies that the rock heterogeneity is likely to weaken faults and reduce the stability of faults

Three-dimensional simulation of detonation initiation and propagation in supersonic combustible mixtures

Detonation initiation and propagation in supersonic combustible mixtures using a hot jet have been investigated in three-dimensional numerical simulations with the detailed reaction model on Tianhe-2 system. Results indicate that the side walls can help realize the triple lines collisions and triple lines reflections, which play an important role in the detonation initiation. There should exists a critical width between the front and back sides of the three-dimensional channel for the successful initiation, which is totally different from that of two-dimensional cases. When the width exceeds the critical value, there will be not the effective reflections of the bow shock surface on the side walls, hence resulting in the failure of detonation initiation. For the detonation propagation, none of the standard detonation modes(rectangular mode, diagonal mode and spinning mode) is observed in the three-dimensional case. The initiated detonation is actually in an overdriven state because of the presence of the hot jet in the supersonic flow field, thus resulting in more complex detonation fronts than that in the CJ detonation. Because of both directions of three-dimensional detonation development than that of the two-dimensional case where the transverse waves propagation and the collisions of triple points can be realized only in one direction, the detonation fronts in three-dimensional simulation shows significantly larger irregularities and variations

Qualitative Action Recognition by Wireless Radio Signals in Human–Machine Systems

Human-machine systems required a deep understanding of human behaviors. Most existing research on action recognition has focused on discriminating between different actions, however, the quality of executing an action has received little attention thus far. In this paper, we study the quality assessment of driving behaviors and present WiQ, a system to assess the quality of actions based on radio signals. This system includes three key components, a deep neural network based learning engine to extract the quality information from the changes of signal strength, a gradient-based method to detect the signal boundary for an individual action, and an activity-based fusion policy to improve the recognition performance in a noisy environment. By using the quality information, WiQ can differentiate a triple body status with an accuracy of 97%, whereas for identification among 15 drivers, the average accuracy is 88%. Our results show that, via dedicated analysis of radio signals, a fine-grained action characterization can be achieved, which can facilitate a large variety of applications, such as smart driving assistants