• Journal of Microbiology and Biotechnology
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• v.26 no.9
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• pp.1657-1660
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• 2016

Prion diseases are incurable neurodegenerative disorders. Our previous study demonstrated that polylysine was effective in prolonging the incubation period in a rodent model and in alleviating the scrapie prion protein (PrP^Sc) burden in the brain at the terminal stage of the disease. Here, we report that intraperitoneal administration of polylysine suppresses the accumulation of prions in the spleen during the early stages of the disease. This study supports the congruence of PrP^Sc inhibition by polylysine in both the spleen and brain.

• Korean Journal of Poultry Science
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• v.43 no.4
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• pp.243-251
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• 2016

Chicken not only serves as a high-protein source to humans, but it is also used as a suitable biomodel for increasing livestock productivity and studying human diseases. Chickens have numerous advantages as model organisms mainly because of they are relatively convenient to manage due to their small body size and short generational interval. In addition, they have a small genome size and numerous genes have biologically similar functions to those of human and livestock animals. In this review, we investigated the chicken biomodel for human disease research and the use of this model for increasing livestock productivity. This summary could provide useful and basic information for further development of strategies for enhancing livestock production and human disease studies.

• BMB Reports
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• v.51 no.1
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• pp.3-4
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• 2018

Parkinson's disease (PD) is a debilitating disorder resulting from loss of dopamine neurons. In dopamine deficient state, the basal ganglia increases inhibitory synaptic outputs to the thalamus. This increased inhibition by the basal ganglia output is known to reduce firing rate of thalamic neurons that relay motor signals to the motor cortex. This 'rate model' suggests that the reduced excitability of thalamic neurons is the key for inducing motor abnormalities in PD patients. We reveal that in response to inhibition, thalamic neurons generate rebound firing at the end of inhibition. This rebound firing increases motor cortical activity and induces muscular responses that triggers Parkinsonian motor dysfunction. Genetic and optogenetic intervention of the rebound firing prevent motor dysfunction in a mouse model of PD. Our results suggest that inhibitory synaptic mechanism mediates motor dysfunction by generating rebound excitability in the thalamocortical pathway.

• Environmental Engineering Research
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• v.23 no.4
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• pp.430-441
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• 2018

The adverse health impact of air pollution is becoming more serious. The purpose of this study is twofold: One is to analyze the effect of air pollution and temperatures on human health by analyzing the number of deaths from cardiovascular disease in Seoul, Korea; the other is to determine what impact the location of a monitoring site has on the results of a health study. For this latter purpose, air pollution and temperature monitors are sited at three locations termed green, public, and residential. Then, a decision tree model is used to analyze factors linked with deaths occurring at each monitoring site. The results show that the environmental temperatures before death and the $PM_{2.5}$ concentrations on the day of death are highly linked with the number of deaths regardless of the monitoring location. However, results are most accurate with residential data. The results of this study can be used as base data for a similar analysis and ultimately, as a guide to minimize the health impact of air pollution.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.6
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• pp.1795-1804
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• 2004

This research investigated the effect of the Chaenomelis fructus(CMF) on Alzheimer's disease. The effects of the CMF extract on the behavior in the Morris water maze experiment; the expression of IL-1β, TNF-α, ROS on the microglial cell; IL-1β mRNA, TNF-α mRNA, CD68/GFAP and MDA on the brain tissue; the infarction area of the hippocampus, and brain tissue injury in the mice with Alzheimer's disease induced by βA were investigated. The CMF extract group showed a significant inhibitory effect on the memory deficit on the mice with Alzheimer's disease induced by βA in the Morris water maze experiment. The CMF extract group suppressed the over-expression of IL-1β, TNF-α, IL-1β and TNF-α mRNA, ROS, MDA, CD68/GFAP in the mice with Alzheimer's disease induced by βA. The CMF extract reduced the infarction area of hippocampus, and controlled the injury of brain tissue in the mice with Alzheimer's disease induced by [3A. This study suggest that CMF may be effective for the prevention and treatment of Alzheimer's disease.

• The Korean Journal of Health Service Management
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• v.7 no.3
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• pp.261-273
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• 2013

The purpose of this study is a chronic liver disease that affects the drinking behavior is to identify the factors. The subjects of the study was diagnosed with chronic liver disease outpatient visit were studied in 120 patients. The collected data were analyzed by using SPSS WIN 18.0. Drinking behavior of chronic liver disease to determine the factors influencing the results of the multiple regression analysis, the regression model was found to be significant(F=8.58, p<.001), drinking behavior of chronic liver disease a major contributor to the drinking habits(${\beta}$ = -.29, p = .004)was found in, followed by drinking motives(${\beta}$ = .20, p = .044), drinking refusal self-efficacy(${\beta}$ = -.17, p = .037), after which the diagnosis of the disease(${\beta}$ = .15, p = .041), respectively. These variables showed explanatory power of 44.1%. Drinking behavior is a serious health problem in patients with chronic liver disease. The factors that influence drinking behavior by considering the management of chronic liver disease drinking continued to provide information and education is needed abstinence.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.9 no.1
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• pp.27-28
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• 2009

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1075-1081
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• 2016

The big data analysis has received much attention from the researchers working in various fields because the big data has a great potential in detecting or predicting future events such as epidemic outbreaks and changes in stock prices. Reflecting the current popularity of big data analysis, many authors have proposed methods tracking influenza epidemics based on internet-based information. The recently proposed 'autoregressive model using Google (ARGO) model' (Yang et al., 2015) is one of those influenza tracking models that harness search queries from Google as well as the reports from the Centers for Disease Control (CDC), and appears to outperform the existing method such as 'Google Flu Trends (GFT)'. Although the ARGO predicts well the outbreaks of influenza, this study demonstrates that a classical seasonal autoregressive integrated moving average (SARIMA) model can outperform the ARGO. The SARIMA model incorporates more accurate seasonality of the past influenza activities and takes less input variables into account. Our findings show that the SARIMA model is a functional tool for monitoring influenza epidemics.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• The Journal of Internal Korean Medicine
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• v.35 no.2
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• pp.184-194
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• 2014

Objectives : This study was designed to investigate the effect on lipoapoptosis of Alisma orientale extract against free fatty acid-induced cellular injury. Methods : HepG2 cells were used in an vitro model. HepG2 cells were treated with free fatty acids to generate a cellular model of nonalcoholic fatty liver disease (NAFLD). Using this cellular model, the anti-apoptotic effect and reducing steatosis of Alisma orientale extract against free fatty acid-induced cellular injury was evaluated by measuring steatosis and apoptosis. Results : Alisma orientale extract significantly attenuated free fatty acid-induced intracellular steatosis. Alisma orientale extract inhibited free fatty acid-mediated activation of pJNK, PUMA, BAX, caspase-3, and -9, and apoptotic kinases that are correlated with NAFLD. Alisma orientale extract also promoted Bcl-2, a anti-apoptotic protein. Conclusions : From the above, the Alisma orientale extract decreased the hepatocyte steatosis and showed the hepatocelluar protective effect by the regulation of apoptosis-related protein. It proposes the possibility of Alisma orientale extract to the treatment of nonalcoholic fatty liver disease in clinics.