Phase behaviour and rheology of solutions of associative polymer and surfactant

Ph.DDOCTOR OF PHILOSOPH

Online Moving Object Visualization with Geo-Referenced Data

As a result of the rapid evolution of smart mobile devices and the wide application of satellite-based positioning devices, the moving object database (MOD) has become a hot research topic in recent years. The moving objects generate a large amount of geo-referenced data in different types, such as videos, audios, images and sensor logs. In order to better analyze and utilize the data, it is useful and necessary to visualize the data on a map. With the rise of web mapping, visualizing the moving object and geo-referenced data has never been so easy. While displaying the trajectory of a moving object is a mature technology, there is little research on visualizing both the location and data of the moving objects in a synchronized manner. This dissertation proposes a general moving object visualization model to address the above problem. This model divides the spatial data visualization systems into four categories. Another contribution of this dissertation is to provide a framework, which deals with all these visualization tasks with synchronization control in mind. This platform relies on the TerraFly web mapping system. To evaluate the universality and effectiveness of the proposed framework, this dissertation presents four visualization systems to deal with a variety of situations and different data types

SERS-Based Sensitive Detection of Organophosphorus Nerve Agents

Organophosphorus nerve agents, such as sarin, tabun, cyclosarin and soman, belong to the most toxic substances. So, it is very important to quickly detect it in trace-level and on-site or portable way. But, both fast and trace detections have been expected because current techniques are of low sensitivity or of poor selectivity and are time-consuming. The surface-enhanced Raman scattering (SERS)-based detection could be a suitable and effective method. However, the organophosphorus nerve agents only very weakly interact with highly SERS-activated noble metal substrates and are hardly adsorbed on them. In this case, it is difficult to detect such molecules, with reproducible or quantitative measurements and trace level, by the normal SERS technique. Recently, there have been some works on the SERS-based detection of the organophosphorus molecules. In this chapter, we introduce the main progresses in this field, including (1) the thin water film confinement and evaporation concentrating strategy and (2) the surface modification and amidation reaction. These works provide new ways for highly efficient SERS-based detection of the organophosphorus nerve agents and some other target molecules that weakly interact with the coin metal substrates

A Surface Protein From Lactobacillus plantarum Increases the Adhesion of Lactobacillus Strains to Human Epithelial Cells

Adhesion to epithelial cells is considered important for Lactobacillus to exert probiotic effects. In this study, we found that trypsin treatment decreased the adhesion ability of Lactobacillus plantarum AR326 and AR269, which exhibit good adhesion ability, and surface proteins extracts increased the adhesion of the strains with poor adhesion ability. By SDS–polyacrylamide gel electrophoresis and mass spectrometry analysis, the main component of the surface proteins was detected and identified as a protein of approximately 37 kDa. It was 100% homologous with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) from L. plantarum WCFS1. The adhesion of AR326 and AR269 was decreased significantly by blocking with the anti-GAPDH antibody, and GAPDH restored the adhesion of AR326 and AR269 treated with trypsin. In addition, purified GAPDH significantly increased the adhesion of the strains with poor adhesion ability. These results indicated that GAPDH mediates the adhesion of these highly adhesive lactobacilli to epithelial cells and can be used to improve the adhesion ability of probiotics or other bacteria of interest

Coordinative control of G2/M phase of the cell cycle by non-coding RNAs in hepatocellular carcinoma

Objective To investigate the interaction of non-coding RNAs (ncRNAs) in hepatocellular carcinoma. Methods We compared the ncRNAs and mRNAs expression profiles of hepatocellular carcinoma and adjacent tissue by microarray and RT-PCR. The relationship between different ncRNAs and mRNA was analyzed using bioinformatics tools. A regulatory model of ncRNAs in hepatocellular carcinoma cells was developed. Results A total of 1,704 differentially expressed lncRNAs, 57 miRNAs, and 2,093 mRNAs were identified by microarray analyses. There is a co-expression relationship between two ncRNAs (miRNA-125b-2-3p and lncRNA P26302). Bioinformatics analysis demonstrated cyclin-dependent kinases 1 and CyclinA2 as potential targets of miR-125b-2-3p and Polo-like kinase 1 as potential target of lncRNAP26302. All three gene are important components in the G2/M phase of cell cycle. Subsequently real-time polymerase chain reaction (PCR) studies confirmed these microarray results. Conclusion MiR-125b-2-3p and lncRNAP26302 may affect the G2/M phase of the cell cycle through the regulation of their respective target genes. This study shows a role of ncRNAs in pathogenesis of hepatocellular carcinoma at molecular level, providing a basis for the future investigation aiming at early diagnosis and novel treatment of hepatocellular carcinoma

Link quality aware channel allocation for multichannel body sensor networks.

Body Sensor Network (BSN) is a typical Internet-of-Things (IoT) application for personalized health care. It consists of economically powered, wireless and implanted medical monitoring sensor nodes, which are designed to continually collect the medical information of the target patients. Multichannel is often used in BSNs to reduce the spectrum competition of the tremendous sensor nodes and the problem of channel assignment has attracted much research attention. The health sensing data in BSNs is often required to be delivered to a sink node (or server) before a certain deadline for real time monitoring or health emergency alarm. Therefore, deadline is of significant importance for multichannel allocation and scheduling. The existing works, though designed to meet the deadline, often overlook the impact of the unreliable wireless links. As a result, the health sensing data can still be overdue because of the scheduled lossy links. Besides, potential collisions in the schedules also incur considerable delay in delivering the sensing data. In this paper, we propose a novel deadline- driven Link quality Aware Channel Assignment scheme (LACA), where link quality, deadlines and collisions are jointly considered. LACA prioritizes links with urgent deadlines and heavy collisions. Besides, LACA allows the exploition of the spare slots for retransmissions on lossy links, which can further reduce the retransmission delay. Extensive simulation experiments show that compared to the existing approaches, LACA can better utilize the wireless spectrum and achieve higher packet delivery ratio before the deadline.N/

REGγ is associated with multiple oncogenic pathways in human cancers

<p>Abstract</p> <p>Background</p> <p>Recent studies suggest a role of the proteasome activator, REGγ, in cancer progression. Since there are limited numbers of known REGγ targets, it is not known which cancers and pathways are associated with REGγ.</p> <p>Methods</p> <p>REGγ protein expressions in four different cancers were investigated by immunohistochemistry (IHC) analysis. Following NCBI Gene Expression Omnibus (GEO) database search, microarray platform validation, differential expressions of REGγ in corresponding cancers were statistically analyzed. Genes highly correlated with REGγ were defined based on Pearson's correlation coefficient. Functional links were estimated by Ingenuity Core analysis. Finally, validation was performed by RT-PCR analysis in established cancer cell lines and IHC in human colon cancer tissues</p> <p>Results</p> <p>Here, we demonstrate overexpression of REGγ in four different cancer types by micro-tissue array analysis. Using meta-analysis of publicly available microarray databases and biological studies, we verified elevated REGγ gene expression in the four types of cancers and identified genes significantly correlated with REGγ expression, including genes in p53, Myc pathways, and multiple other cancer-related pathways. The predicted correlations were largely consistent with quantitative RT-PCR analysis.</p> <p>Conclusions</p> <p>This study provides us novel insights in REGγ gene expression profiles and its link to multiple cancer-related pathways in cancers. Our results indicate potentially important pathogenic roles of REGγ in multiple cancer types and implicate REGγ as a putative cancer marker.</p

Parameter influence law analysis and optimal design of a dual mass flywheel

Abstract The influence of the dynamic parameters of a dual mass flywheel (DMF) on its vibration reduction performance is analyzed, and several optimization algorithms are used to carry out multiobjective DMF optimization design. First, the vehicle powertrain system is modeled according to the parameter configuration of the test vehicle. The accuracy of the model is verified by comparing the simulation data with the test results. Then, the model is used to analyze the influence of the moment of inertia ratio, torsional stiffness, and damping in reducing DMF vibration. The speed fluctuation amplitude at the transmission input shaft and the natural frequency of the vehicle are taken as the optimization objectives. The passive selection method, multiobjective particle swarm optimization, and the nondominated sorting genetic algorithm based on an elite strategy are used to carry out DMF multiobjective optimization design. The advantages and disadvantages of these algorithms are evaluated, and the best optimization algorithm is selected

Heterogeneity and Differentiation Trajectories of Infiltrating CD8+ T Cells in Lung Adenocarcinoma

CD8+ T cells infiltrating the tumor microenvironment (TME) of lung adenocarcinoma (LUAD) are critical for establishing antitumor immunity. Nevertheless, the global landscape of their numbers, functional status, and differentiation trajectories remains unclear. In the single-cell RNA-sequencing (scRNA-seq) dataset GSE131907 of LUAD, the CD8+T cells were selected for TSNE clustering, and the results showed that they could be divided into ten subsets. The cell differentiation trajectory showed the presence of abundant transition-state CD8+ T cells during the differentiation of naive-like CD8+ T cells into cytotoxic CD8+ T cells and exhausted CD8+ T cells. The differentially expressed marker genes among subsets were used to construct the gene signature matrix, and the proportion of each subset was identified and calculated in The Cancer Genome Atlas (TCGA) samples. Survival analysis showed that the higher the proportion of the exhausted CD8+ T lymphocyte (ETL) subset, the shorter the overall survival (OS) time of LUAD patients (p = 0.0098). A total of 61 genes were obtained by intersecting the differentially expressed genes (DEGs) of the ETL subset, and the DEGs of the TCGA samples were divided into a high and a low group according to the proportion of the ETL subset. Through protein interaction network analysis and survival analysis, four hub genes that can significantly affect the prognosis of LUAD patients were finally screened, and RT-qPCR and Western blot verified the differential expression of the above four genes. Our study further deepens the understanding of the heterogeneity and functional exhaustion of infiltrating CD8+ T cells in LUAD. The screened prognostic marker genes provide potential targets for targeted therapy and immunotherapy in LUAD patients