MIF family proteins in lung diseases

Chronic obstructive pulmonary disease (COPD) and lung cancer constitute an enormous disease burden in developed countries. Every year, COPD causes more than three million deaths worldwide. Outcomes for lung cancer are the poorest of all tumor types, with a five-year survival of 10-20%. Exploring the contributions of various proteins involved in these diseases will help in better understanding the disease pathogeneses and developing novel treatment strategies. Macrophage migration inhibitory factor (MIF) is a multi-tasking protein that together with close family member called D-dopachrome tautomerase (D-DT, also referred to as MIF-2) are highly expressed in the lung but their functions remain poorly understood. The research presented in this thesis has focused on studying the roles of MIF family proteins in pulmonary diseases, mainly COPD and lung cancer. We investigated if and how D-DT contributes to epithelial repair in COPD, and then compared the effects of MIF and D-DT on the function of lung epithelial progenitor cells in healthy lung tissue and lung tissue from patients with COPD. We also developed a research tool inhibited intracellular MIF expression and used this to further investigate the biological functions of MIF in lung cancer. Overall, studies in this thesis demonstrated that MIF and its homolog D-DT are associated with COPD and lung cancer and these studies showed novel roles of MIF and D-DT in lung epithelial repair

Multi-view Subspace Clustering via An Adaptive Consensus Graph Filter

Multiview subspace clustering (MVSC) has attracted an increasing amount of attention in recent years. Most existing MVSC methods first collect complementary information from different views and consequently derive a consensus reconstruction coefficient matrix to indicate the subspace structure of a multi-view data set. In this paper, we initially assume the existence of a consensus reconstruction coefficient matrix and then use it to build a consensus graph filter. In each view, the filter is employed for smoothing the data and designing a regularizer for the reconstruction coefficient matrix. Finally, the obtained reconstruction coefficient matrices from different views are used to create constraints for the consensus reconstruction coefficient matrix. Therefore, in the proposed method, the consensus reconstruction coefficient matrix, the consensus graph filter, and the reconstruction coefficient matrices from different views are interdependent. We provide an optimization algorithm to obtain their optimal values. Extensive experiments on diverse multi-view data sets demonstrate that our approach outperforms some state-of-the-art methods

Engineering formate assimilation in Synechocystis sp. PCC 6803

To improve photosynthetic efficiency, a synthetic formate assimilation (FA) pathway is designed in this study to function as an additional carbon-fixing route, which possibly also reduce the photorespiratory loss of CO2 via the inhibition of glycine decarboxylation. To establish FA, genes encoding the proteins 10-formyl-THF ligase (FTL), 5,10-methylene-THF dehydrogenase (MtdA), and 5,10-methenyl-THF cyclohydrolase (FchA) from M. extorquens AM1 were transferred into the model cyanobacterium Synechocystis sp. PCC 6803

The reformation of traditional television programs under the new media environment: a case study of the Phoenix Group’s program Omni Media Online

The purpose of the study was to explore how the new media and cyber environment prompt changes of the television programs toward an omni-media pattern of use. By using the Phoenix Group’s news program, Omni Media Online as an example, the case study examines the audience’s changing interests in programs’ content as well as watching channels. Both audiences from television and new media platforms demonstrated a trend of merging audience composition and changing habit in China’s media industry. When two-way communication could be built with multi-channel interaction, it brings more public opinions to live news broadcast. A survey was conducted to learn the relationships between modern audience and the program, taking the Phoenix Group as an example. It is important to know what viewers want based on their watching experience so that proper reform can be carried out draw their attentions.M.S., Television Management -- Drexel University, 201

Construction and Measure of the Evaluation Index System of Regional Soft Power - Taking Shandong Province as an Example

Based on the concept and connotation of regional soft power, combined with the actual situation of the economic and social development in Shandong Province, this paper builds a strong operational regional soft power rating index system. Using the data of the Statistical Yearbook of the 17 cities in Shandong Province in 2008, z-score standardized methods and factor analysis and so on, finally the paper have a comprehensive evaluation and analysis about the status quo of regional soft power of the 17 cities in Shandong Province.Key words: Regional soft power; Evaluation index system; Factor analysi

Wasserstein Generative Regression

In this paper, we propose a new and unified approach for nonparametric regression and conditional distribution learning. Our approach simultaneously estimates a regression function and a conditional generator using a generative learning framework, where a conditional generator is a function that can generate samples from a conditional distribution. The main idea is to estimate a conditional generator that satisfies the constraint that it produces a good regression function estimator. We use deep neural networks to model the conditional generator. Our approach can handle problems with multivariate outcomes and covariates, and can be used to construct prediction intervals. We provide theoretical guarantees by deriving non-asymptotic error bounds and the distributional consistency of our approach under suitable assumptions. We also perform numerical experiments with simulated and real data to demonstrate the effectiveness and superiority of our approach over some existing approaches in various scenarios.Comment: 50 pages, including appendix. 5 figures and 6 tables in the main text. 1 figure and 7 tables in the appendi

Preparation and Free Radical Detection of Doped ZnO Nanomaterials

Nanomaterials play an important role in the field of optics and medicine, and rare earth cerium can act as a catalyst and a dopant to increase improve its optical properties. Used nanometer zinc oxide as a carrier, the Ag-ZnO and Ag-Ce-ZnO samples were prepared with the sol-gel method and characterized by X-ray diffractometer. The nanometer zinc oxide materials can generate the free hydroxyl radicals, so the methylene blue solution (MB) was used as the capture agent, and the free radicals produced by the doped nanometer zinc oxide were detected by UV-spectrophotometry. The results showed that the preparation particle size of the Ag-ZnO sample was about 75nm, particle size of the Ag-Ce-ZnO sample was about 70nm. The concentration of two samples treated with the dispersant PAAS generated hydroxyl radicals is much larger than the two samples treated with the dispersant SDBS. The doping of Ce ions not only improved the optical activity of the samples, but also increased the content of hydroxyl radicals. Rare-earth doped effe ctively improved the optical properties of the ZnO nanoparticles, and the effect of sample Ag-Ce-ZnO was better than Ag-ZnO samples. Discussion and study on the nature of both the nanometer zinc oxide and doped nanometer zinc oxide, as well as the method of preparation and the theory of produce hydroxyl radicals. In the experiment, doped nano-ZnO was used as carrier and methylene blue (MB) as capture reagent. This study provided a new method for the detection of free radicals drugs