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권세욱,Sung-Bong Jeon,Mingje Xin,Jun-Ho Kim,Ji-Young Im,차지윤,Ho-Kyun Jee,Oh-Gu Lee,김대기,이영미 한국생약학회 2012 Natural Product Sciences Vol.18 No.4
Hyperglycemia or high glucose (HG), is the hallmark of diabetes, known to induce oxidative stress, release of chemokines, and cytokines, which confer endothelial cell damage. On the other hand, microbial transformation of organic materials often leads to certain changes in their product structures which could enhance their biological activities. The aim of this study was to investigate the beneficial effects of fermented Gastrodia elata (FGE) in HG induced human umbilical vein endothelial cells (HUVECs) dysfunction. GE, fermented by Saccharomyces cerevisiae, which has an extensive history of safe use, exhibited higher phenolic compounds content than those of Gastrodia elata (GE). The HG-induced production of nitric oxide (NO) and interleukin-8 (IL-8) were significantly attenuated by FGE pretreatment to the cells, in a concentration dependent manner. In addition, FGE showed marked activity in free radical scavenging. These results suggest that FGE possesses beneficial effects in protecting against the oxidative stress, and inflammatory conditions in endothelial cells, caused by HG.
Antihyperglycemic Effect of Fermented Gastrodia elata Blume in Streptozotocin-induced Diabetic Mice
권세욱,임지영,전성봉,지호균,박용수,이훈연,김대기,이영미 한국식품과학회 2013 Food Science and Biotechnology Vol.22 No.5
Gastrodia elata Blume (GE) has been used in traditional medicine as a sedative, an anti-convulsant and anti-epileptic drug. This study was performed to investigate antihyperglycemic effect of fermented-Gastrodia elata Blume (FGE) in streptozotocin (STZ)-induced type 1 diabetic mice. FGE was prepared by fermentation with Saccharomyces cerevisia. GE and FGE were orally administered at 20 or 100 mg/kg/day for 3 weeks to STZ (70 mg/kg)-induced diabetic mice. Administartion of FGE significantly reduced blood glucose levels in an oral glucose tolerance test (OGTT), fasting blood glucose (FBG), and glycosylated hemoglobin (HbA1c) compared to GE. In addition, FGE significantly decreased serum total cholesterol (TC),triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and at the same time markedly increased serum high density lipoprotein cholesterol (HDL-C) and plasma insulin levels. The results of this experimental study indicate that FGE possesses antihyperglycemic effect in STZ-induced diabetic mice.
권세욱,현영주,태현철 한국산업경영시스템학회 2023 한국산업경영시스템학회지 Vol.46 No.1
Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.