• BMB Reports
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• v.47 no.7
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• pp.369-375
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• 2014

Pituitary adenylate cyclase-activating polypeptide (PACAP) is a pleiotropic bioactive peptide that was first isolated from an ovine hypothalamus in 1989. PACAP belongs to the secretin/glucagon/vasoactive intestinal polypeptide (VIP) superfamily. PACAP is widely distributed in the central and peripheral nervous systems and acts as a neurotransmitter, neuromodulator, and neurotrophic factor via three major receptors (PAC1, VPAC1, and VPAC2). Recent studies have shown a neuroprotective role of PACAP using in vitro and in vivo models. In this review, we briefly summarize the current findings on the neurotrophic and neuroprotective effects of PACAP in different brain injury models, such as cerebral ischemia, Parkinson's disease (PD), and Alzheimer's disease (AD). This review will provide information for the future development of therapeutic strategies in treatment of these neurodegenerative diseases.

• BMB Reports
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• v.56 no.1
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• pp.43-48
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• 2023

Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.04a
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• pp.47-62
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• 2007

• The Journal of Internal Korean Medicine
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• v.41 no.6
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• pp.993-1014
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• 2020

Objective: Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. Antioxidant stress and inflammatory reactions are important causes of neurodegenerative diseases and are major causes of PD. Many animal experiments have been aimed at treating PD using the antioxidant effects of various traditional medicines and dietary supplements. This review reports the research investigating the antioxidant effects of herbs in in vivo PD models. Methods: The study consisted of a database search for articles related to PD and herbal treatments using the OASIS, NDSL, KTKP, Korean KISS, PubMed, Science Direct, CNKI, Wanfang, and J-STAGE databases. The search period was limited from the start of the search engine application to November 14, 2019. Studies were selected to confirm the antioxidant effects of herbal medicines in an in vivo PD model. Results: Eighty-two studies were summarized for plant species, extracts (or compounds), animal models, neurotoxins, and functional results. The most frequently used herbal materials were Bacopa monnieri, Camellia sinensis, Centella asiatica, and Withania somnifera. MPTP and 6-OHDA were the most commonly used neurotoxins for inducing PD. Most studies confirmed an increased expression and activation of antioxidant enzymes and a decrease in oxidative stress. Herbal materials showed their antioxidant effects regardless of the order of treatment and confirmed their possible use as treatments for the prevention and treatment of neurodegeneration. Conclusion: Many herbal medicines have antioxidant effects and are likely to be effective in delaying neurodegenerative damage by inhibiting or reducing oxidative stress by expression of antioxidant enzymes.

• Therapeutic Science for Rehabilitation
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• v.1 no.1
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• pp.39-56
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• 2012

Introduction : Animal studies cannot be applied directly to Occupational Therapy(OT) intervention protocol. However, animal models still provide essential evidences and knowledge to improve OT practice and to develop OT theories as well as human studies do. The purpose of this scholarly paper is to explore the potential of animal models to inform OT theory and practice particularly as it relates to neuroscience. Body : The animal models provide related knowledge for a better understanding of the mechanism of diseases and related neural networks. Based on this knowledge, researchers can test their hypothesis of neural disease. In addition, accumulated animal studies contribute to introduce the new approaches to human diseases and to improve the effectiveness of treatment. Conclusions : Animal models of neurological disease are critical and have the potential to improve OT practice and theory in many ways. Therefore, OT researchers need to pay more attention to animal models in addition human studies.

• Korean Journal of Biological Psychiatry
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• v.4 no.2
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• pp.194-197
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• 1997

Neural network models, also known as connectionist models or PDP models, simulate some functions of the brain and may promise to give insight in understanding the cognitive brain functions. The models composed of neuron-like elements that are linked into circuits can learn and adapt to its environment in a trial and error fashion. In this article, the history and principles of the neural network modeling are briefly reviewed, and its applications to psychiatry are discussed.

• Journal of the Ergonomics Society of Korea
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• v.33 no.4
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• pp.289-297
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• 2014

Objective: The purpose of this study is to identify the incidence risk of cardiovascular disease (CVD) in the workplace, and to suggest the prediction models for level of CVD incidence risk. Background: CVD can be caused by various factors related to personal habits such as diet and exercise, or genetics. However it can also be caused and aggravated by work, making the elimination of such risk factors at work crucial disease (KOSHA, 2013). Method: The distribution of CVD risk assessment levels of 162 workers was compared with the acquired medical examination data to discuss the necessity of assigning additional risk factors. Two alternative risk assessment models were given to enhance the accuracy of the evaluation; adjusting risk scores given in the KOSHA GUIDE H-1-2013 (alternative 1) and building a matrix of KOSHA GUIDE H-1-2013 and risk assessment results based on work condition levels (alternative 2). To verify the suggested models, medical examination results of 12 workers approved of convalescence were referred to. Results: The second alternative showed more relevance between the results and workers approved of convalescence in predicting the risk group when applied to actual heath examination data from the approved workers. The power of description of the new method for determining the risk of CVD incidence, 83.3%, is higher than that of KOSHA GUIDE H-1-2013, 25%. Conclusion: Results of this study imply that more approved workers had been from unmanaged normal groups than managed risk groups, raising the importance of CVD management. Application: The new prediction model considering working time and shift work developed in this study is expected to be a fundamental data for risk analysis and management of CVD in the workplace.

• The Plant Pathology Journal
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• v.19 no.3
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• pp.129-132
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• 2003

Fusarium wilt of cucumber caused by Fusarium oxy-sporum f. sp. cucumerinum is a serious vascular disease worldwide. Biological control of Fusarium wilt in several crops has been accomplished by introducing non-pathogenic Fusarium sup. and other biocontrol agents in soil or in infection courts. In this study, quantitative models were used to determine the biocontrol efficacy of inundatively applied antagonist formulations and the length of their effectiveness in controlling Fusarium wilt of cucumber. Quantitative model of the form [Y=L (1${-exp}^{-kx}$)] best described the relationship between disease incidence (Y, %) and inoculum density (X) of isolates F51 and F55. Isolate F51 was selected as a more virulent isolate based on the extent of its effectiveness in causing the wilt disease. The degree of disease control (Xi/X) obtained with the density of the biocontrol agent (Z), was described by the model [Xi/X=A (1${-exp}^{-cz}$)]. The zeolite-based antagonist formulation amended with chitosan (ZAC) was better at lower rates of application and peaked at around 5 g/ kg of the potting medium, whereas the peat-based antagonist formulation (PA) peaked at around 10 g/kg of the potting medium. ZAC formulation provided significantly better suppression of Fusarium wilt as described by the curvilinear relationship of the type Y= a+bX+c$X^2$, where Y represents percent disease incidence and X represents sustaining effect of the biocontrol agent.

• Journal of Integrative Natural Science
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• v.7 no.4
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• pp.234-240
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• 2014

C-C chemokine receptor type 4 (CCR4) is a chemokine receptor with seven transmembrane helices and it belongs to the GPCR family. It plays an important role in asthma, lung disease, atopic dermatitis, allergic bronchopulmonary aspergillosis, cancer, inflammatory bowel disease, the mosquito-borne tropical diseases, such as dengue fever and allergic rhinitis. Because of its role in wide spectrum of disease processes, CCR4 is considered to be an important drug target. Three dimensional structure of the protein is essential to determine the functions. In the present study homology modeling of human CCR4 was performed based on crystal structure of CCR5 chemokine receptor. The generated models were validated using various parameters. Among the generated homology models the best one is selected based on validation result. The model can be used for performing further docking studies to identifying the critical interacting residues.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.171-180
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• 2020

With the recent increase in asthma, asthma has become recognized as one of the diseases. The perception that bronchial asthma is a chronic disease and requires treatment has been strengthened. In addition, asthma is recognized as a dangerous disease due to environmental changes and efforts are made to minimize these risks. However, the environmental impact on asthma is hardly a factor that individuals in asthmatic patients can cope with. Therefore, this study was conducted to see if the asthma disease could be replaced by the individual efforts of asthma patients. In particular, since the management of asthma is important during adolescence, we conducted research on asthma in teenagers. Utilizing support vector machines, artificial neural networks and deep learning techniques that have recently drawn attention, we propose models to predict the asthma of teenagers. The study also provides guidelines to avoid factors that can cause asthma in teenagers.