• Journal of Periodontal and Implant Science
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• 제26권3호
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• pp.689-699
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• 1996

The purpose of this research is to determine elements affecting the out-of-pocket cost of woman. The sample consisted of 1907 women living Iksan city. The survey was conducted by means of questionnaires. The model used in the analysis of out-of-pocket cost was the Andersen-Newman model, while the analysis techniques used were stepwise multiple regression and path analysis. The number of independent variables used in the analysis was 28 in total, ie 19 predisposing components, 6 enabling components, and 3 need components. In this study, the amount of variance by the model was 17 percent. Number of restricted activity days caused by oral disease, perceived susceptibility of dental disease, having a regular dental care, dental treatment costs, education level and income were found to have significant major effects on out-of-pocket cost. Number of restricted activity days caused by oral disease was the most important variable affecting out-of-pocket cost of woman. Also out-of-pocket cost shows larger effect due to enabling components than frequency of dental utilization.

• Natural Product Sciences
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• 제22권4호
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• pp.246-251
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• 2016

This study investigated the effects of (-)-sesamin on memory deficits in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-lesioned mouse model of Parkinson's disease (PD). MPTP lesion (30 mg/kg/day, 5 days) in mice showed memory deficits including habit learning memory and spatial memory. However, treatment with (-)-sesamin (25 and 50 mg/kg) for 21 days ameliorated memory deficits in MPTP-lesioned mouse model of PD: (-)-sesamin at both doses improved decreases in the retention latency time of the passive avoidance test and the levels of dopamine, norepinephrine, 3,4-dihydroxyphenylacetic acid, and homovanillic acid, improved the decreased transfer latency time of the elevated plus-maze test, reduced the increased expression of N-methyl-D-aspartate (NMDA) receptor, and increased the reduced phosphorylation of extracellular signal-regulated kinase (ERK1/2) and cyclic AMP-response element binding protein (CREB). These results suggest that (-)-sesamin has protective effects on both habit learning memory and spatial memory deficits via the dopaminergic neurons and NMDA receptor-ERK1/2-CREB system in MPTP-lesioned mouse model of PD, respectively. Therefore, (-)-sesamin may serve as an adjuvant phytonutrient for memory deficits in PD patients.

• Reproductive and Developmental Biology
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• 제37권1호
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• pp.41-49
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• 2013

Ovarian cancer is the most lethal world-wide gynecological disease among women due to the lack of molecular biomarkers to diagnose the disease at an early stage. In addition, there are few well established relevant animal models for research on human ovarian cancer. For instance, rodent models have been established through highly specialized genetic manipulations, but they are not an excellent model for human ovarian cancer because histological features are not comparable to those of women, mice have a low incidence of tumorigenesis, and they experience a protracted period of tumor development. However, the laying hen is a unique and highly relevant animal model for research on human ovarian cancer because they spontaneously develop epithelial cell-derived ovarian cancer (EOC) as occurs in women. Our research group has identified common histological and physiological aspects of ovarian tumors from women and laying hens, and we have provided evidence for several potential biomarkers to detect, monitor and target for treatment of human ovarian cancers based on the use of both genetic and epigenetic factors. Therefore, this review focuses on ovarian cancer of laying hens and relevant regulatory mechanisms, based on genetic and epigenetic aspects of the disease in order to provide new information and to highlight the advantages of the laying hen model for research in ovarian carcinogenesis.

• 품질경영학회지
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• 제48권3호
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• pp.493-510
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• 2020

Purpose: As of July 31, there were 14,336 confirmed cases of COVID-19 in South Korea, including 301 deaths. Since the daily confirmed number of cases hit 909 on February 29, the spread of the disease had gradually decreased due to the active implementation of preventive control interventions, and the daily confirmed number had finally recorded a single digit on April 19. Since May, however, the disease has re-emerged and retaining after June. In order to eradicate the disease, it is necessary to suggest suitable forward preventive strategies by predicting future infectivity of the disease based on the cases so far. Therefore, in this study, we aim to evaluate the transmission potential of the disease in early phases by estimating basic reproduction number and assess the preventive control measures through effective reproduction number. Methods: We used publicly available cases and deaths data regarding COVID-19 in South Korea as of July 31. Using ensemble model integrated stochastic linear birth model and deterministic linear growth model, the basic reproduction number and the effective reproduction number were estimated. Results: Estimated basic reproduction number is 3.1 (95% CI: 3.0-3.2). Effective reproduction number was the highest with 7 on February 15, decreased as of April 20. Since then, the value is gradually increased to more than unity. Conclusion: Preventive policy such as wearing a mask and physical distancing campaigns in the early phase of the outbreak was fairly implemented. However, the infection potential increased due to weakening government policy on May 6. Our results suggest that it seems necessary to implement a stronger policy than the current level.

• Toxicological Research
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• 제12권2호
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• pp.213-221
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• 1996

In order to develop a suitable secondary renal disease model and diagnostic markers of renal disease in the rat, the change of PIIIP (aminoterminal procollagen III peptide) in serum and hydroxyproline levels in the renal tissue that reflect the synthesis of extracellular matrix (ECM) during development of experimental renal diseases were observed. Two types of experimental primary diseases, diabetes mellitus administrated by streptozotocin (STZ, 75 mg/kg, i.p.) and liver cirrhosis produced by bile duct ligation/scission (BDL/s) operation, were induced. The hydroxyproline level increased according to the high PIIIP and NCl(carboxyterminal procollagen IV peptide) in Western blot analysis as early as 1 week in the STZ treated-rat kidney. Increased renal ECM was observed at 15 weeks in STZ and BDL/s model under the microscopic examination. High PAS positive reaction was found in capillary basement membrane in STZ treated-rats and mesangium in BDL/s operated rats at this time, showing the histological characteristics of diabetic nephropathy and cirrhotic glomerulonephritis in human, respectively. Such secondary renal failure were supported by additional tests including urinalysis and renal function test. The serum PIIIP detected by ELISA was a useful parameter to estimate synthesis rate of renal ECM during development of renal disease without extrarenal fibrosis i.e. liver cirrhosis in rats. This study is proposed that STZ treatment or BDL/s operation may be a suitable experimental animal model for the induction and development of chronic secondary renal diseases. Morover, it was found that hydroxyproline level in renal tissues was a good parameter of the change of renal ECM at the early stage of the diseases without apparent histological changes. Especially, serum PIIIP could be a choice as a diagnostic or prognostic marker during the development of renal diseases in rats.

• 동의생리병리학회지
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• 제25권6호
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• pp.1113-1118
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• 2011

In this paper, when a physician make a diagnosis of the pattern identification (PI) in Korean stroke patients, the development methods of the PI classification function is considered by diagnostic questionnaire of the PI for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PI subtypes diagnosed by two physicians with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PI using Korean Stroke Syndrome Differentiation Standard was consist of the 44 items (Fire heat(19), Qi deficiency(11), Yin deficiency(7), Dampness-phlegm(7)). Using the 44 items, we took diagnostic and prediction accuracy rate through of discriminant model. The overall diagnostic and prediction accuracy rate of the PI subtypes for discriminant model was 74.37%, 70.88% respectively.

• Natural Product Sciences
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• 제19권2호
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• pp.173-178
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• 2013

The protective effect of SAPP, an extract from a novel herbal complex, on acute liver injury was investigated using mouse animal model in this study. The content of total phenol in SAPP was increased at dose dependent manner. Consistent with the content of total phenol, SAPP showed the significant anti-oxidative effects on 1, 1-diphenyl-2-picrylhydrazyl (DPPH) method. Acute liver injury was induced by D-galactosamine (D-GalN) in mouse. Treatment with SAPP significantly reduced the level of alanine transaminase (ALT) and aspartate transaminase (AST) in serum. Histological observation revealed that whereas D-GalN treated mouse showed vacuolization of hepatocytes, sinusoidal dilation and congestion, loss of cell boundaries and ballooning degeneration, loss of architecture and cell necrosis, treatment with SAPP improved D-GalN-induced liver injury. These results suggest that SAPP shows protective effects against D-GalN-induced hepatotoxicity in vivo acute mouse model.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.209-216
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• 2019

Over the past decade, researchers were able to solve complex medical problems as well as acquire deeper understanding of entire issue due to the availability of machine learning techniques, particularly predictive algorithms and automatic recognition of patterns in medical imaging. In this study, a technique called transfer learning has been utilized to classify Magnetic Resonance (MR) images by a pre-trained Convolutional Neural Network (CNN). Rather than training an entire model from scratch, transfer learning approach uses the CNN model by fine-tuning them, to classify MR images into Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal control (NC). The performance of this method has been evaluated over Alzheimer's Disease Neuroimaging (ADNI) dataset by changing the learning rate of the model. Moreover, in this study, in order to demonstrate the transfer learning approach we utilize different pre-trained deep learning models such as GoogLeNet, VGG-16, AlexNet and ResNet-18, and compare their efficiency to classify AD. The overall classification accuracy resulted by GoogLeNet for training and testing was 99.84% and 98.25% respectively, which was exceptionally more than other models training and testing accuracies.

• 기본간호학회지
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• 제19권4호
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• pp.463-473
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• 2012

Purpose: The main purpose of this study was to identify factors affecting medication adherence and to develop an explanatory model for medication adherence in elders with chronic disease. Method: Empirical data were collected from 312 older adults with chronic disease and the data collect period was from August 8 to 31, 2011, and were analyzed using SPSS for Windows 19.0 program and confirmatory factor analysis with the structural equation model (SEM) procedure performed with AMOS 19.0 program. Results: Results of this study showed that perceived self-efficacy was the strongest factor influencing medication adherence, and it affected also outcome expectations positively but impediments were negatively influenced by self-efficacy. Outcome expectations and impediments subsequently acted on medication adherence with the same relationship as self-efficacy. In additional results, self-efficacy and medication adherence were further significantly affected by the factors; social support, medication knowledge, and depression. Conclusion: These results show that nursing interventions to promote medication adherence in this population should focus on self-efficacy promotion including social support, education for delivery of medication knowledge, and reduction in depression.

• 응용통계연구
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• 제17권3호
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• pp.431-443
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• 2004

본 연구에서는 질병지도작성(disease mapping)을 위해 인접지역의 정보를 효과적으로 활용할 수 있는 EB(empirical Bayes) 추정 법과 HGLM(hierarchial generalized linear model)을 기초로 한 추정법을 다룬다. 사례연구로 이 추정방법들을 이용하여 2000년 사망원인통계자료를 이용해 경상도 및 전라도의 112개 시$.$군$.$구 단위 행정자치구역별 45세 이상 폐암 사망률을 산출하고, 경상도 및 전라도 지역 폐암 사망률 지도를 작성한다. 아울러 제시된 방법들에 위해 얻어진 추정치들의 변동과 3년간 평균 사망률을 기준으로 구한 MSD(mean square deviation)를 이용하여 추정방법들의 특성을 비교 분석한다.