• Journal of the Mineralogical Society of Korea
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• v.26 no.4
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• pp.245-262
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• 2013

We analyzed 29 surface sediment samples in five submarine volcanoes (TA12, TA19, TA22, TA25, and TA26) located in the southern part of the Tonga arc for trace elements and rare earth elements to investigate characteristics of the hydrothermal alteration of surface sediments. Based on analytical results of trace element and rare earth element (REE), surface sediments of TA12, TA19, and TA22 submarine volcanoes, which are located in the northern part of the study area, were very little or not influenced by hydrothermal fluids. In contrast, some stations of TA25 and TA26 submarine volcanoes were strongly affected by hydrothermal fluids. However, these two submarine volcanoes showed different features in element concentration in the sediments. Some stations of TA25 submarine volcano showed enrichment of Ni, Cu, Sn, Zn, Pb, Cr, Cd, Sb, W, Ba, Ta, Rb, Sr, and As, however, those of TA26 submarine volcano showed enrichment of Sn, Zn, Pb, Cd, Sb, Ba, Rb, and Sr. Stations which enriched trace elements were observed, enriched REEs were also observed. Average upper continental crust (UCC)-normalized REE patterns of the surface sediments generally showed low light REE (LREE) abundances and increased heavy REE (HREE) abundances. Eu enrichment was identified at several stations of TA25 and TA26 submarine volcanoes. In addition, enrichment of Ce was found at some stations of TA26 submarine volcano and these enrichment patterns were similar with hydrothermal fluid of near stations. Furthermore, TA25 and TA26 submarine volcanoes showed different enrichment characteristics of trace elements and REE. Trace elements were concentrated at TA25 submarine volcano. TA26 submarine volcano, on the other hand, observed highly enrichment of REE especially, Eu and Ce. As a result of the investigation, the characteristics and concentrations of REEs and trace elements in the surface sediments of each submarine volcano can be applied to identify hydrothermal alteration of sediments during exploration for hydrothermal deposits.

• Applied Microscopy
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• v.40 no.2
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• pp.89-99
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• 2010

Fibroblasts are the most common cells in connective tissue and are responsible for the synthesis of extracellular matrix components. The fibrosis associated with chronic inflammation and injury may contribute to cholangiocarcinoma pathogenesis, particularly through an increase in extracellular matrix components, which participate in the regulation of bile duct differentiation during development. Mitochondria produce ATP through oxidative metabolism to provide energy to the cell under physiological conditions. Also, mitochondrial dysfunction and oxidative stress have been implicated in cellular senescence and aging. Alternations in mitochondrial structure and function are early events of programmed cell death or apoptosis and mitochondria appear to be a central regulator of apoptosis in most somatic cell. Clonorchis sinensis, one of the most important parasite of the human bile duct in East Asia, arouses epithelial hyperplasia and ductal fibrosis. Isolated fibroblast from the bile ducts of rats infected by C. sinensis showed increase of cytoplasmic process. In addition, decrease of cellular proliferation was observed in fibroblasts which was isolated from normal rat bile duct and then cultured in media containing C. sinensis excretory-secretory product. However, the effects of C. sinensis infection on the mitochondrial enzyme distribution is not clearly reported yet. Therefore, we investigated the structural change of C. sinensis infected bile duct and mitochondrial enzyme distribution of the cultured fibroblast isolated from the C. sinensis infected rat bile duct. As a result, C. sinensis infected SD rat bile ducts showed the features of chronic clonorchiasis, such as ductal connective and epithelial tissue dilatation, or ductal fibrosis. In addition, fibroblast in ductal connective tissue was damaged by physical effect of fibrotic tissue and chemical stimulation. Immunohistochemically detected mitochondrial electron transferase (ATPase, COXII, Porin) was decreased in C. sinensis infected rat bile duct and cultured fibroblast from infected rat bile duct. It can be hypothesized that the reason why number of electron transferase decrease in fibroblast isolated from the rat bile duct infected with C. sinensis is because dysfunction of electron transport system is occurred mitochondrial dysfunction, increase of ROS (reactive oxygen species) and apoptosis after chemical damage on the cell caused by C. sinensis infection. Overall, C. sinensis infection induces fibrotic change of ductal connective tissue, mutation of cellular metabolism in fibroblast and mitochondrial dysfunction. Consequently, ductal fibrosis inhibits fibroblast proliferation and decreases mitochondrial electron transferase on fibroblast cytoplasm. It was assumed that the structure of bile duct could not normalized and ductal fibrosis was maintained for a long period of time according to fibroblast metamorphosis and death induced by mitochondrial dysfunction.

• Journal of Korean Medical Science
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• v.33 no.49
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• pp.323.1-323.12
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• 2018

Background: Vitamin K antagonist (VKA) to prevent thromboembolism in non-valvular atrial fibrillation (NVAF) patients has limitations such as drug interaction. This study investigated the clinical characteristics of Korean patients treated with VKA for stroke prevention and assessed quality of VKA therapy and treatment satisfaction. Methods: We conducted a multicenter, prospective, non-interventional study. Patients with $CHADS_2{\geq}1$ and treated with VKA (started within the last 3 months) were enrolled from April 2013 to March 2014. Demographic and clinical features including risk factors of stroke and VKA treatment information was collected at baseline. Treatment patterns and international normalized ratio (INR) level were evaluated during follow-up. Time in therapeutic range (TTR) > 60% indicated well-controlled INR. Treatment satisfaction on the VKA use was measured by Treatment Satisfaction Questionnaire for Medication (TSQM) after 3 months of follow-up. Results: A total of 877 patients (age, 67; male, 60%) were enrolled and followed up for one year. More than half of patients (56%) had $CHADS_2{\geq}2$ and 83.6% had $CHA_2DS_2-VASc{\geq}2$. A total of 852 patients had one or more INR measurement during their follow-up period. Among those patients, 25.5% discontinued VKA treatment during follow-up. Of all patients, 626 patients (73%) had poor-controlled INR (TTR < 60%) measure. Patients' treatment satisfaction measured with TSQM was 55.6 in global satisfaction domain. Conclusion: INR was poorly controlled in Korean NVAF patients treated with VKA. VKA users also showed low treatment satisfaction.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.