APPROACHING EFFICIENT NANOMOTORS VIA BIOMIMICKING MECHANISMS

Ph.DDOCTOR OF PHILOSOPH

MORC2 Enhances Tumor Growth by Promoting Angiogenesis and Tumor-Associated Macrophage Recruitment via Wnt/β-Catenin in Lung Cancer

Background/Aims: In this study, we aimed to investigate how MORC family CW-type zinc finger 2 (MORC2) affects tumor progression of lung cancer. Methods: The MORC2 level was analyzed by real-time RT-PCR and immunohistochemistry (IHC) in normal control tissues and lung cancers. LL/2 cells overexpressing MORC2 were used to study how MORC2 expression influences lung cancer progression. The effects of MORC2 on cell viability, migration and invasion were assessed by MTT assay, Western blotting, and transwell assays, respectively. Afterwards, the effects of MORC2 on the activation of the Wnt/β-catenin pathway were explored by Western blotting. The effects of MORC2 on tumor-associated macrophages (TAM) were determined by immunofluorescence (IF) staining, real-time RT-PCR and Western blotting. Results: Our results showed that MORC2 was upregulated in lung cancers relative to adjacent tissues. The results also demonstrated that MORC2 promoted lung cancer tumor growth in vivo. Additionally, MORC2 overexpression stimulated the upregulation of vascular endothelial growth factor (VEGF), driving angiogenesis. MORC2 overexpression in LL/2 also increased the amount of aldehyde dehydrogenase-1 (ALDH1) protein, indicating that MORC2 increased cancer stem cell features. We further determined that MORC2 activated Wnt/β-catenin signaling in lung cancer cells. Upregulation of macrophage-recruiting genes including VEGF and Macrophage-specific colony stimulating factor (CSF-1) recruits TAMs to the tumor site, which has the net effect of promoting additional tumor growth and metastasis. Conclusion: Our data suggest that MORC2 overexpression can drive lung cancer growth by stimulating the recruitment of TAMs in addition to angiogenesis and that activation of Wnt/β-signaling may be a key pathway underlying this phenotype that is amenable to pharmacological intervention

Improved Density Peak Clustering Algorithm Based on Choosing Strategy Automatically for Cut-off Distance and Cluster Centre

Due to the defect of quick search density peak clustering algorithm required an artificial attempt to determine the cut-off distance and circle the clustering centres, density peak clustering algorithm based on choosing strategy automatically for cut-off distance and cluster center (CSA-DP) is proposed. The algorithm introduces the improved idea of determining cut-off distance and clustering centres, according to the approximate distance that maximum density sample point to minimum density sample point and the variation of similarity between the points which may be clustering centres. First, obtaining the sample point density according to the k-nearest neighbour samples and tapping the sample sorting of the distance to the maximum density point; then finding the turning position of density trends and determining the cut-off distance on the basis of the turning position; finally, in view of the density peak clustering algorithm, finding the data points which may be the centres of the cluster, comparing the similarity between them and determining the final clustering centres. The simulation results show that the improved algorithm proposed in this paper can automatically determine the cut-off distance, circle the centres, and make the clustering results become more accurate. In the end, this paper makes an empirical analysis on the stock of 147 bio pharmaceutical listed companies by using the improved algorithm, which provides a reliable basis for the classification and evaluation of listed companies. It has a wide range of applicability

The effects of gastrointestinal function on the incidence of ventilator-associated pneumonia in critically ill patients

To investigate the effect of gastrointestinal function on the incidence of ventilator-associated pneumonia (VAP) in critically ill patients

Evaluating the Spatial Accessibility and Distribution Balance of Multi-Level Medical Service Facilities

Public medical service facilities are among the most basic needs of the public and are directly related to residents’ health. The balanced development of medical service facilities is of great significance. Public medical service facilities can be divided into different levels according to their medical equipment, service catchment, and medical quality, which is very important but has been ignored for a long time in accessibility evaluations. In this research, based on the hospital and population datasets of Shenzhen, we propose a hierarchical two-step floating catchment area (H2SFCA) method to evaluate the spatial accessibility of public medical resources considering the factors at different levels of medical resources. In the proposed method, the spatial accessibility of each level of public medical service facilities are evaluated using different distance attenuation functions according to the medical service’s scope. In addition, a measurement is proposed to evaluate the equity of medical service facilities based on accessibility and population density distributions. To synthesize the general spatial accessibility and the distribution balance of public medical service facilities, we standardize the spatial accessibility of public medical service facilities at each level and then calculate the weighted sums of the accessibility of each level. The general spatial equity of public medical service facilities is also evaluated. The results show that the accessibility and distribution balance of medical resources performs dissimilarly at the three levels and can be discriminated within different regions of the city. The accessibility of citywide medical facilities in Shenzhen decreases from the city center to the suburban area in a radial pattern and the accessibility and distribution balance in the suburban areas needs improvement

Identifying Urban Residents’ Activity Space at Multiple Geographic Scales Using Mobile Phone Data

Residents’ activity space reflects multiple aspects of human life related to space, time, and type of activity. How to measure the activity space at multiple geographic scales remains a problem to be solved. Recently, the emergence of big data such as mobile phone data and point of interest data has brought access to massive geo-tagged datasets to identify human activity at multiple geographic scales and to explore the relationship with built environment. In this research, we propose a new method to measure three types of urban residents’ activity spaces—i.e., maintenance activity space, commuting activity space, and recreational activity space—using mobile phone data. The proposed method identifies the range of three types of residents’ activity space at multiple geographic scales and analyzing the relationship between the built environment and activity space. The research takes Zhuhai City as its case study and discovers the spatial patterns for three activity space types. The proposed method enables us to achieve a better understanding of the human activities of different kinds, as well as their relationships with the built environment

Examining the effect of land-use function complementarity on intra-urban spatial interactions using metro smart card records

Spatial interaction is an important phenomenon that reflects the human–land relationship and has long been a core topic in multiple fields, such as urban planning, transportation planning, commodity trade, and epidemic prevention. However, as an underlying cause of spatial interaction, function complementarity has been ignored by existing research for a long time. At the same time, the increase in Big Data of travel behavior provides an opportunity to model spatial interactions in detail. In this paper, we proposed three types of land-use function complementarity indices according to the spatiotemporal characteristics of human mobility. These complementarity indices are introduced to spatial interaction to improve the gravity model. We also examined the effects of land function complementarity on intra-urban spatial interaction using smart card records of metro system for different time periods and directions. The results showed that all models could be improved by introducing the land-use function complementarity indices, but the models with a single travel pattern and clear direction were explained more by the complementary indices. The indices we propose in this paper could be used for predicting spatial flow and trip distribution, and also could be considered as factors in researches about transportation and land-use planning

Anaerobic Digestion Technology for Methane Production Using Deer Manure Under Different Experimental Conditions

Anaerobic digestion (AD) is an important technology for the treatment of livestock and poultry manure. The optimal experimental conditions were studied, with deer manure as a fermentation material and mushroom residue as an inoculum. At the same time, methane production was increased by adding zeolite and changing the magnetic field conditions. The results showed that a 6% solid content was the best condition for producing methane. The optimal conditions for methane production were obtained by adding 35 g of mushroom residue to 80 g of deer manure at 35 °C. The addition of organic wastewater (OW) improved methane production. The result of improving the methane production factor showed that adding zeolite during the reaction process could increase the methane production rate. When the amount of zeolite was over 8% total solids (TSes), methane production could improve, but the rate decreased. Setting a different magnetic field strength in the AD environment showed that when the distance between the magnetic field and the reactor was 50 mm and the magnetic field strength was 10–50 mT, the methane production increment and the content of methane in the mixed gases increased