• Journal of Life Science
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• v.24 no.6
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• pp.664-670
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• 2014

In the present study, we investigate the role of V. vulnificus in promoting the inflammation of mouse ileal ephitelium and its related signaling pathways. ICR mice were infected orally with V. vulnificus ($1{\times}10^9CFU$) for 16 h as a representative model of food-borne infection. To find the major portal of entry of V. vulnificus in mouse intestine, we have measured the levels of bacterial colonization in small intestine, colon, spleen, and liver. V. vulnificus appeared to colonize in intestine and colon in the order of ileum >> jejunum> colon, but lack in the duodenum, spleen, and liver. V. vulnificus in ileum caused severe necrotizing enteritis and showed shortened villi heights accompanied by an expanded width and inflammation, compared with the control mice. V. vulnificus induced ileal epithelium inflammation by activating phosphorylation of PKC and membrane translocation of $PKC{\alpha}$. V. vulnificus induced the phosphorylation of ERK and JNK, but did not affect p38 MAPK phosphorylation. Notably, V. vulnificus stimulated the I-${\kappa}B$-dependent phosphorylation of NF-${\kappa}B$ in mouse ileal epithelium. Finally, the ileal infection of V. vulnificus resulted in a significant increase in expression of proinflammatory cytokines and Toll-like receptors, respectively, compared to the control. Collectively, our results indicate that V. vulnificus induces ileal epithelium inflammation by increasing NF-${\kappa}B$ phosphorylation via activation of PKC, ERK, and JNK, which is critical for host defense mechanism in food-borne infection by V. vulnificus.

• Journal of radiological science and technology
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• v.29 no.1
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• pp.1-6
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• 2006

Purpose: Renal stones are common and typically arise within the collecting system. The renal sinus are contains the collection system, the renal vessels, lymphatcs, fat, and fibrous tissue. Because of the compression of all the large echoes in signal processing, the echo from the renal stone generally cannot be distinguished from large echoes emanating from normal structures of the renal sinus. Use of ultrasonography has been difficult for detecting small renal stone without posterior shadowing and chemical composition of stone. The aim of study was measuring for posterior acoustic shadowing to a stone for various scan parameter and it examines a help in renal stone diagnosis. Material & Methods: The stone was place on sponge examined in a water bath with a 3.5MHz or 7.5MHz transducer(LOGIQ 400, USA). First, tested a variety of gain. Second, tested a variety of dynamic range. Third, tested a variety of focal zone. Fourth, measuring of the echo level for low and high frequency for depth. Results: 1) Average echo level was 98 for low total gain(10 dB) and was 142 for high total gain(40 dB). Posterior acoustic shadowing of renal stone was clear for low gain. 2) Average echo level was 129 for low dynamic range(42 dB) and was 101 for high dynamic range(72 dB). Posterior acoustic shadowing of renal stone was clear for high dynamic range. 3) When stone is in focal zone of transducer, definite posterior acoustic shadow is identified. 4) Stone was clear appeared for high frequency(7.5 MHz) than low frequency(3.5 MHz) and it is not distorted. Conclusion: The demonstration of an posterior acoustic shadow of renal stone dependents on several technical factors such as gain, dynamic range, focus, and frequency. This various factors are a help in renal stone diagnosis.

• Journal of Life Science
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• v.7 no.4
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• pp.392-401
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• 1997

The poliovirus is a small, and non-enveloped virus. The RNA genome of poliovirus is continuous, linear, and has a single open reading frame. This polyprotein precursor is cleaved proteolytically to yield mature products. Most of the cleavages occur by viral protease. The mature proteins derived from the P1 polyprotein precursor are the structural components of the viral capsid. The initial cleavage by 2A protease is indirectly involved in the cleavage of a cellular protein p220, a subunit of the eukaryotic translation initiation factor 4F. This cleavage leads to the shut-off of cap-dependent host cell translation, and allows poliovirus to utilize the host cell machinery exclusively for translation its own RNA, which is initiated by internal ribosome entry via a cap-independent mechanism. The functional role of the 2B, 2C and 2BC proteins are not much known. 2B, 2C, 2BC and 3CD proteins are involved in the replication complex of virus induced vesicles. All newly synthesized viral RNAs are linked with VPg. VPg is a 22 amino acid polypeptide which is derived from 3AB. The 3C and 3CD are protease and process most of the cleavage sites of the polyprotein precursor. The 3C protein is also involved in inhibition of RNA polymerase II and III mediated transcription by converting host transcription factor to an inactive form. The 3D is the RNA dependent RNA polymerase. It is known that poliovirus replication follows the general pattern of positive strand RNA virus. Plus strand RNA is transcribed into complementary minus strand RNA that, in turn, is transcribed for the synthesis of plus strand RNA is transcribed into complementary minus strand RNA that, in turn, is transcribed for the synthesis of plus strand RNA strands. Poliovirus RNA synthesis occurs in a membranous environment but how the template RNA and proteins required for RNA replication assemble in the membrane is not much known. The RNA requirements for the encapsidation of the poliovirus genome (packaging signal) are totally unknown. The poliovirus infection cycle lasts approximately 6 hours.

• Journal of Life Science
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• v.29 no.4
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• pp.402-409
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• 2019

Korean red ginseng made from steaming and drying fresh ginseng has long been used as a traditional herbal medicine due to its effects on the immune, endocrine, and central nerve systems and its anti-inflammatory activity. In this study, we investigated the molecular mechanism responsible for the anti-inflammatory effects of a formulated Korean red ginseng extract (RGE) in response to lipoteichoic acid (LTA), a cell wall component of gram-positive bacteria. RGE inhibited LTA-induced nitric oxide (NO) secretion and inducible nitric oxide synthase (iNOS) expression in BV-2 microglial cells, without affecting cell viability. RGE also inhibited nuclear translocation of nuclear factor kappa B ($NF-{\kappa}B$) p65 and degradation of $I{\kappa}B-{\alpha}$. In addition, RGE increased the expression of heme oxygenase-1 (HO-1) in a dose-dependent manner, and the inhibitory effect of RGE on iNOS expression was abrogated by small interfering RNA-mediated knockdown of HO-1. Moreover, RGE induced nuclear translocation of nuclear factor E2-related factor 2 (Nrf2), a transcription factor that regulates HO-1 expression. Furthermore, the phosphoinositide-3-kinase (PI-3K) inhibitor and mitogen-activated protein kinase (MAPK) inhibitors suppressed RGE-mediated expression of HO-1, and RGE enhanced the phosphorylation of Akt, extracellular signal-regulated kinases (ERKs), p38, and c-JUN N-terminal kinases (JNKs). These results suggested that RGE suppressed the production of NO, a proinflammatory mediator, by inducing HO-1 expression via PI-3K/Akt- and MAPK-dependent signaling in LTA-stimulated microglia. The findings indicate that RGE could be used for the treatment of neuroinflammation induced by grampositive bacteria and that it may have therapeutic potential for various neuroinflammation-associated disorders.

• Journal of The Korean Astronomical Society
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• v.52 no.1
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• pp.11-21
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• 2019

Intensive Monitoring Survey of Nearby Galaxies (IMSNG) is a high cadence observation program monitoring nearby galaxies with high probabilities of hosting supernovae (SNe). IMSNG aims to constrain the SN explosion mechanism by inferring sizes of SN progenitor systems through the detection of the shock-heated emission that lasts less than a few days after the SN explosion. To catch the signal, IMSNG utilizes a network of 0.5-m to 1-m class telescopes around the world and monitors the images of 60 nearby galaxies at distances D < 50 Mpc to a cadence as short as a few hours. The target galaxies are bright in near-ultraviolet (NUV) with $M_{NUV}$ < -18.4 AB mag and have high probabilities of hosting SNe ($0.06SN\;yr^{-1}$ per galaxy). With this strategy, we expect to detect the early light curves of 3.4 SNe per year to a depth of R ~ 19.5 mag, enabling us to detect the shock-heated emission from a progenitor star with a radius as small as $0.1R_{\odot}$. The accumulated data will be also useful for studying faint features around the target galaxies and other science projects. So far, 18 SNe have occurred in our target fields (16 in IMSNG galaxies) over 5 years, confirming our SN rate estimate of $0.06SN\;yr^{-1}$ per galaxy.

• Tuberculosis and Respiratory Diseases
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• v.42 no.6
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• pp.862-870
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• 1995

Background: Oxygen free radicals have generally been considered as cytotoxic agents. On the other hand, recent results suggest that small nontoxic amounts of these radicals may act a role in intracellular signal transduction pathway and many efforts to reveal the role of these radicals as secondary messengers have been made. It is evident that the oxygen radicals are released by various cell types in response to extracellular stimuli including LPS, TNF, IL-1 and phorbol esters, all of which translocate the transcription factor $NF{\kappa}B$ from cytoplasm to nucleus by releasing an inhibitory protein subunit, $I{\kappa}B$. Activation of $NF{\kappa}B$ is mimicked by exposure to mild oxidant stress, and inhibited by agents that remove oxygen radicals. It means the cytoplasmic form of the inducible tanscription factor $NF{\kappa}B$ might provide a physiologically important target for oxygen radicals. At the same time, it is well known that LPS induces the release of oxygen radicals in neutrophil with the activation of $NF{\kappa}B$. From above facts, we can assume the expression of IL-8 and IL-$1{\beta}$ gene by LPS stimulation may occur through the activation of $NF{\kappa}B$, which is mediated through the release of $I{\kappa}B$ by increasing amounts of oxygen radicals. But definitive evidence is lacking about the role of oxygen free radicals in the expression of IL-8 and IL-$1{\beta}$ gene in mononuclear phagocytic cells. We conducted a study to determine whether oxygen radicals act a role in the expression of IL-8 and IL-$1{\beta}$ gene in mononuclear phagocytic cells. Method: Human peripheral blood monocytes were isolated from healthy volunteers. Time and dose relationship of $H_2O_2$-induced IL-8 and IL-$1{\beta}$ mRNA expression was observed by Northern blot analysis. To evaluate the role of oxygen radicals in the expression of IL-8 and IL-$1{\beta}$ mRNA by LPS stimulation, pretreatment of various antioxiants including PDTC, TMTU, NAC, ME, Desferrioxamine were done and Northern blot analysis for IL-8 and IL-$1{\beta}$ mRNA was performed. Results: In PBMC, dose and time dependent expression of IL-8 and IL-$1{\beta}$ mRNA by exogenous $H_2O_2$ was not observed. But various antioxidants suppressed the expression of LPS-induced IL-8 and IL-$1{\beta}$ mRNA expression of PBMC and the suppressive activity was most prominant when the pretreatment was done with TMTU. Conclusion: Oxygen free radical may have some role in the expression of IL-8 and IL-$1{\beta}$ mRNA of PBMC but that radical might not be $H_2O_2$.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.