• 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 Life Science
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• v.17 no.2 s.82
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• pp.167-173
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• 2007

To study the transcriptional mechanisms by which expression of the murine glial cell-derived neurotrophic factor inducible transcription factor (mGIF) gene is regulated, a murine genomic clone was iso-lated using a mGIF cDNA as probe. A 13-kb genomic fragment, which comprises 4-kb upstream of the transcription initiation site was sequenced. The promoter region lacks a TATA box and CAAT box, is rich in G+C content, and has multiple putative binding sites for the transcription factor Spl. The mGIF gene also has consensus sequences for AP2 binding sites. The transcriptional activity of five deletion mutants of a 2.1-kb fragment was analyzed by modulating transcription of the heterologous luciferase gene in the promoterless plasmid pGL2-Basic. All mutants showed significant transcriptional activity in the murine neuroblastoma cell line NB41A3. Transient expression assays suggested the presence of a positive regulator between -213 and -129 while a negative regulator was found in the region between -806 and -214. Relatively strong transcriptional activity was observed in neuronal NB41A3, glial C6 cells and hepatic HepG2, but very weak activity in skeletal muscle C2C12 cells. These findings confirm the tissue-specific activity of the mGIF promoter and suggest that this gene shares structural and functional similarities with the dopamine receptor genes that it regulates.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Knowledge Management Research
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• v.22 no.2
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• pp.119-144
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• 2021

Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.