Examining the roles of genetic and environmental factors in Drosophila melanogaster hematopoiesis and innate immune system

Nearly 24 million people are affected by autoimmune diseases in the United States. Main causes of autoimmune diseases have been attributed to genetic predisposition and environmental exposure to chemicals such as hormones and pesticides. Due to the large population that are affected by autoimmune diseases, it is critical to understand the mechanisms behind them. In this study, we sought to explore both genetic and environmental factors that affect hematopoiesis, or the formation of specific blood cells, and immune system in Drosophila melanogaster. As Drosophila melanogaster have conserved pathways of hematopoiesis as humans, they were used as the model organism for the study. We examined the presence of lamellocytes, a type of Drosophila blood cell typically only present upon immune challenge by wasp parasitoids, across Drosophila Genetic Reference Panel (DGRP) lines. We then conducted a Genome Wide Association Study (GWAS) to identify single nucleotide polymorphisms (SNPs) that lead to lamellocyte induction without any immune challenges. Post-GWAS bioinformatic analyses were used to characterize the genes where the SNPs were found. Drosophila were then treated with Methoprene, a common insecticide, to observe its effect on lamellocyte production. Unexpectedly, 4 DGRP lines showed lamellocyte production without any immune challenges. GWAS showed 365 SNPs associated with the lamellocyte phenotype. Post-GWAS results provided 44 genes that were associated with hematopoiesis and the immune system. In addition, Methoprene treatments induced lamellocytes in all DGRP lines used in the study. Future studies with this study include measuring the expression levels of immune system related genes upon Methoprene treatment to understand possible Methoprene genetic targets and their mechanisms to induce lamellocytes

Fast-Rate Capable Electrode Material with Higher Energy Density than LiFePO4: 4.2V LiVPO4F Synthesized by Scalable Single-Step Solid-State Reaction

Use of compounds that contain fluorine (F) as electrode materials in lithium ion batteries has been considered, but synthesizing single-phase samples of these compounds is a difficult task. Here, it is demonstrated that a simple scalable single-step solid-state process with additional fluorine source can obtain highly pure LiVPO4F. The resulting material with submicron particles achieves very high rate capability approximate to 100 mAh g(-1) at 60 C-rate (1-min discharge) and even at 200 C-rate (18 s discharge). It retains superior capacity, approximate to 120 mAh g(-1) at 10 C charge/10 C discharge rate (6-min) for 500 cycles with >95% retention efficiency. Furthermore, LiVPO4F shows low polarization even at high rates leading to higher operating potential >3.45 V (approximate to 3.6 V at 60 C-rate), so it achieves high energy density. It is demonstrated for the first time that highly pure LiVPO4F can achieve high power capability comparable to LiFePO4 and much higher energy density (approximate to 521 Wh g(-1) at 20 C-rate) than LiFePO4 even without nanostructured particles. LiVPO4F can be a real substitute of LiFePO4.1114Ysciescopu

The Impact of environmental policy stringency on Korean exports of environmental goods

Thesis(Master) --KDI School:Master of Development Policy,2018This paper studies the effects of two aspects of stringent environmental policy on Korea’s exports of environmental goods: 1. The effects of a trade partner’s environmental policy stringency; and 2. The effects of Korea’s environmental policy stringency. This paper uses panel data from 2002 to 2012 for OECD and BRIICS countries. The gravity model is implemented, with EPS index (OECD) serving as an indicator for environmental policy stringency. Based on the effects being analyzed by this paper, the empirical results show: 1. The stringent environmental policy of a trade partner has a positive effect on Korea’s exports because the market is greater in countries with stricter environmental policy; 2. Korea’s environmental policy has a decisive influence on the increase in Korea’s exports of environmental goods, which is consistent with the Porter Hypothesis. Stringent environmental policies should therefore be utilized to strengthen the competitiveness of Korea's environmental goods and a certain level must be maintained to promote the export of environmental goods.Ⅰ. Introduction Ⅱ. Theories and Literature Review Ⅲ. Korea’s Environmental Policy Stringency and Environmental Goods Ⅳ. Methodology and Data Ⅴ. Results Ⅵ. ConclusionmasterpublishedMinkyung LEE

Relationship of topology, multiscale phase synchronization, and state transitions in human brain networks

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram(EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are ��progressive and earlier�� or ��abrupt but delayed�� account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations. ? 2017 Kim, Kim, Mashour and Lee.115sciescopu

Demonstration of nanoimprinted hyperlens array for high-throughput sub-diffraction imaging

11124Nsciescopu

Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement

Individual tooth segmentation and identification from cone-beam computed tomography images are preoperative prerequisites for orthodontic treatments. Instance segmentation methods using convolutional neural networks have demonstrated ground-breaking results on individual tooth segmentation tasks, and are used in various medical imaging applications. While point-based detection networks achieve superior results on dental images, it is still a challenging task to distinguish adjacent teeth because of their similar topologies and proximate nature. In this study, we propose a point-based tooth localization network that effectively disentangles each individual tooth based on a Gaussian disentanglement objective function. The proposed network first performs heatmap regression accompanied by box regression for all the anatomical teeth. A novel Gaussian disentanglement penalty is employed by minimizing the sum of the pixel-wise multiplication of the heatmaps for all adjacent teeth pairs. Subsequently, individual tooth segmentation is performed by converting a pixel-wise labeling task to a distance map regression task to minimize false positives in adjacent regions of the teeth. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art approaches by increasing the average precision of detection by 9.1%, which results in a high performance in terms of individual tooth segmentation. The primary significance of the proposed method is two-fold: 1) the introduction of a point-based tooth detection framework that does not require additional classification and 2) the design of a novel loss function that effectively separates Gaussian distributions based on heatmap responses in the point-based detection framework.Comment: 11 pages, 7 figure