• Journal of Korean Academy of Nursing
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• v.50 no.2
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• pp.191-199
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• 2020

Purpose: The purpose of this study was to compare sociodemographic characteristics of a normal cognitive group and mild cognitive impairment group, and establish prediction models of Mild Cognitive Impairment (MCI). Methods: This study was a secondary data analysis research using data from "the 4th Korea Longitudinal Study of Ageing" of the Korea Employment Information Service. A total of 6,405 individuals, including 1,329 individuals with MCI and 5,076 individuals with normal cognitive abilities, were part of the study. Based on the panel survey items, the research used 28 variables. The methods of analysis included a χ²-test, logistic regression analysis, decision tree analysis, predicted error rate, and an ROC curve calculated using SPSS 23.0 and SAS 13.2. Results: In the MCI group, the mean age was 71.4 and 65.8% of the participants was women. There were statistically significant differences in gender, age, and education in both groups. Predictors of MCI determined by using a logistic regression analysis were gender, age, education, instrumental activity of daily living (IADL), perceived health status, participation group, cultural activities, and life satisfaction. Decision tree analysis of predictors of MCI identified education, age, life satisfaction, and IADL as predictors. Conclusion: The accuracy of logistic regression model for MCI is slightly higher than that of decision tree model. The implementation of the prediction model for MCI established in this study may be utilized to identify middle-aged and elderly people with risks of MCI. Therefore, this study may contribute to the prevention and reduction of dementia.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.327-336
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• 2021

It is important to prevent progression of mild cognitive impairment (MCI) to Alzheimer's disease or other dementia. This study was conducted to investigate cognitive-based intervention and its effectiveness for the older patients with MCI through systematic review. Data search was conducted in September 2020, using the Korea Research Information Service (Riss) and KoreaMed. After selection of literatures according to the predefined inclusion criteria, a total of 12 articles were included. It is revealed that the cognitive-based intervention for the older adults with MCI was found to have a positive effect on the various factors including cognitive function, depression, physical health status, quality of life, and communication. However, it is difficult to draw a definite conclusion due to the various intervention strategies and instruments used. Thus, based on the results of this study, we suggest more studies to verify the effectiveness of such programs.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.940-952
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• 2020

The Alzheimer's disease (AD) is a neurodegenerative disease commonly found in the elderly individuals. It is one of the most common forms of dementia; patients with AD suffer from a degradation of cognitive abilities over time. To correctly diagnose AD, compuated-aided system equipped with automatic classification algorithm is of great importance. In this paper, we propose a novel deep learning based classification algorithm that takes advantage of MRI biomarker images including brain areas of hippocampus and cerebrospinal fluid for the purpose of improving the AD classification performance. In particular, we develop a new approach that effectively applies MRI biomarker patch images as input to 3D Deep Convolution Neural Network. To integrate multiple classification results from multiple biomarker patch images, we proposed the effective confidence score fusion that combine classification scores generated from soft-max layer. Experimental results show that AD classification performance can be considerably enhanced by using our proposed approach. Compared to the conventional AD classification approach relying on entire MRI input, our proposed method can improve AD classification performance of up to 10.57% thanks to using biomarker patch images. Moreover, the proposed method can attain better or comparable AD classification performances, compared to state-of-the-art methods.

• Journal of Agricultural Extension & Community Development
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• v.30 no.1
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• pp.1-13
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• 2023

This study aims to examine the effect of healing program using insect. For the insect resources, the program uses 3 species of emotional insects. The subjects were a total of 29, the elderly with mild dementia and adults with developmental disabilities in the facility. The activities are 9 programs in total and each program takes 2 hours once a week. For data collection, we measured a blood pressure, stress level using autonomic nervous system activity, and scale of happiness, depression and insomnia by a survey. The datas were collected every week before and after the program. As a result of paired-sample t-test analysis, the participants of the agro-healing program using insects had positive effects as follows: reducing a depression, relieving a symptom of insomnia and stabilizing a blood pressure. Through the results of this study, it was possible to confirm the positive effects of the agro-healing program using insects. If farms lead agro-healing program using insects on their own, it could be expected to contribute to improve the quality of life through agriculture as well as to improve the farms' income.

• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.167-172
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• 2019

The purpose of this study was to investigate the effect of computer based cognitive rehabilitation program on the generative naming. Twenty - one patients were assigned to the CoTras program and eight were treated with traditional face - to - face language rehabilitation such as paper and table activities. The experimental group and the control group performed sequential language recall memory training, association memory recall training, language categorization memory training, and language integrated memory training for 12 weeks. The Welch's robust ANCOVA showed significant differences in mean fluency and MMSE-K changes (p<0.05). On the other hand, phonemic fluency increased significantly after 12 weeks of treatment compared to baseline in both experimental and control groups, but there was no statistically significant difference between treatment groups. The results of this study suggest that the computer based cognitive rehabilitation program may be more effective in improving the semantic fluency than the conventional cognitive-linguistic rehabilitation.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.2
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• pp.141-151
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• 2007

Parkinson's disease is one of the most frequent neurodegenerative diseases, which mainly affects the elderly. Parkinson's disease is often difficult to differentiate from atypical parkinson diorder such as progressive supranuclear palsy, multiple system atrophy, dementia with Lewy body, and corticobasal ganglionic degeneration, based on the clinical findings because of the similarity of phenotypes and lack of diagnostic markers. The accurate diagnosis of Parkinson's disease and atypical Parkinson disorders is not only important for deciding on treatment regimens and providing prognosis, but also it is critical for studies designed to investigate etiology and pathogenesis of parkinsonism and to develop new therapeutic strategies. Although degeneration of the nigrostriatal dopamine system results in marked loss of striatal dopamine content in most of the diseases causing parkinsonism, pathologic studies revealed different topographies of the neuronal cell loss in Parkisonism. Since the regional cerebral glucose metabolism is a marker of integrated local synaptic activity and as such is sensitive to both direct neuronal/synaptic damage and secondary functional disruption at synapses distant from the primary site of pathology, an assessment of the regional cerebral glucose metabolism with F-18 FDG PET is useful in the differential diagnosis of parkinsonism and evaluating the pathophysiology of parkisonism.

• Journal of Veterinary Science
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• v.25 no.5
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• pp.60.1-60.6
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• 2024

Importance: Alzheimer's disease (AD) is the most common cause of dementia in the elderly with the incidence rising exponentially after the age of 65 years. Unfortunately, effective treatments are extremely limited and definite diagnosis can only be made at autopsy. This is in part due to our limited understanding of the complex pathophysiology, including the various genetic, environmental, and metabolic contributing factors. In an effort to better understand this complex disease, researchers have employed nonhuman primates as translational models. Case Presentation: This report aims to describe the AD-like neuropathology in the brain of a 37-year-old female baboon (Papio hamadryas), which at the time of her death made her the oldest hamadryas baboon at any member institution of the Association of Zoos and Aquariums. A diagnostic necropsy was performed, and the brain was evaluated for neurodegenerative disease. Frequent amyloid-β deposits were identified, consistent with what has been described in other geriatric nonhuman primates. Phospho-tau pathology, including neurofibrillary tangles, a feature not well-described in other primate models, was also abundant. Conclusions and Relevance: Our results suggest that more detailed, prospective, longitudinal studies are warranted utilizing this particular species to see if they represent a viable model for human brain aging.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.402-409
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• 2019

Patients with dementia or elderly patients who can not move at all by themselves are at a high risk of falls and bedsore due to lack of caregivers. In this paper, to solve this problem, we propose an algorithm to determine the patient's lying postures by discriminating the main body parts such as head, shoulders, and hips based on the pressure intensity sensed at regular intervals. A smart mat with a lattice structure in which a pressure sensor is arranged so that the body part can be discriminated irrespective of the physical characteristics has been implemented. It consists of two modules of $7{\times}7$ array size. Each module consists of 49 FSR-406 sensors and independently senses pressure. For each module, the body part corresponding to the upper body or the lower body is sequentially discriminated by using a pressure distribution such as a cumulative pressure sum using a filter. The proposed algorithm can identify five lying positions by examining the inclusion relationship between body parts belonging to layer-1 such as head, shoulder, and hip area.

• Biomolecules & Therapeutics
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• v.28 no.2
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• pp.145-151
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• 2020

Alzheimer's disease (AD) is a devastating neurodegenerative disease and a major cause of dementia in elderly individuals worldwide. Increased deposition of insoluble amyloid β (Aβ) fibrils in the brain is thought be a key neuropathological hallmark of AD. Many recent studies show that natural products such as polyphenolic flavonoids inhibit the formation of insoluble Aβ fibrils and/or destabilize β-sheet-rich Aβ fibrils to form non-cytotoxic aggregates. In the present study, we explored the structure-activity relationship of naturally-occurring biflavonoids on Aβ amyloidogenesis utilizing an in vitro thioflavin T assay with Aβ1-42 peptide which is prone to aggregate more rapidly to fibrils than Aβ1-40 peptide. Among the biflavonoids we tested, we found amentoflavone revealed the most potent effects on inhibiting Aβ1-42 fibrillization (IC₅₀: 0.26 µM), as well as on disassembling preformed Aβ1-42 fibrils (EC₅₀: 0.59 µM). Our structure-activity relationship study suggests that the hydroxyl groups of biflavonoid compounds play an essential role in their molecular interaction with the dynamic process of Aβ1-42 fibrillization. Our atomic force microscopic imaging analysis demonstrates that amentoflavone directly disrupts the fibrillar structure of preformed Aβ1-42 fibrils, resulting in conversion of those fibrils to amorphous Aβ1-42 aggregates. These results indicate that amentoflavone affords the most potent anti-amyloidogenic effects on both inhibition of Aβ1-42 fibrillization and disaggregation of preformed mature Aβ1-42 fibrils.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.1
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• pp.85-91
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• 2017

Alzheimer's disease (AD) is a progressive neurodegenerative disorder of insidious onset that causes gradual loss of memory and cognitive function, and it is the most common form of dementia in the elderly. AD is characterized by neuritic plaques and neurofibrillary tangles in the brain, together with loss of neuronal cells. The major neuropathological hallmark of AD is the accumulation of extracellular neurotoxic ${\beta}-amyloid$ ($A{\beta}$) peptides, such as $A{\beta}1-42$, in the brain. In the present study, we investigated the effect of sargachromenol (SCM), sargaquinoic acid (SQA) and sargahydroquinoic acid (SHQA) isolated from Sargassum serratifoilum ethanol extract (SSE) on $A{\beta}$ production in vitro using APP751-transfected Chinese hamster ovary cells (CHO-751). CHO-751 cells were treated with various concentrations of SSE, SCM, SQA and SHQA, and the level of extracellular $A{\beta}1-42$ was evaluated by enzyme-linked immunosorbent assay. SSE and SHQA reduced the production of $A{\beta}1-42$ in CHO-751 cells. Therefore, SHQA isolated from S. serratifolium has potential as an inhibitor of neurotoxic $A{\beta}$ peptide production.