• Korean Journal of Heritage: History & Science
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• v.39
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• pp.351-378
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• 2006

With the development of media, the methods for the documentation of intangible cultural heritage have been also developed and diversified. As well as the previous analogue ways of documentation, the have been recently applying new multi-media technologies focusing on digital pictures, sound sources, movies, etc. Among the new technologies, the documentation of intangible cultural heritage using the method of 'Motion Capture' has proved itself prominent especially in the fields that require three-dimensional documentation such as dances and performances. Motion Capture refers to the documentation technology which records the signals of the time varing positions derived from the sensors equipped on the surface of an object. It converts the signals from the sensors into digital data which can be plotted as points on the virtual coordinates of the computer and records the movement of the points during a certain period of time, as the object moves. It produces scientific data for the preservation of intangible cultural heritage, by displaying digital data which represents the virtual motion of a holder of an intangible cultural heritage. National Research Institute of Cultural Properties (NRICP) has been working on for the development of new documentation method for the Important Intangible Cultural Heritage designated by Korean government. This is to be done using 'motion capture' equipments which are also widely used for the computer graphics in movie or game industries. This project is designed to apply the motion capture technology for 3 years- from 2005 to 2007 - for 11 performances from 7 traditional dances of which body gestures have considerable values among the Important Intangible Cultural Heritage performances. This is to be supported by lottery funds. In 2005, the first year of the project, accumulated were data of single dances, such as Seungmu (monk's dance), Salpuri(a solo dance for spiritual cleansing dance), Taepyeongmu (dance of peace), which are relatively easy in terms of performing skills. In 2006, group dances, such as Jinju Geommu (Jinju sword dance), Seungjeonmu (dance for victory), Cheoyongmu (dance of Lord Cheoyong), etc., will be documented. In the last year of the project, 2007, education programme for comparative studies, analysis and transmission of intangible cultural heritage and three-dimensional contents for public service will be devised, based on the accumulated data, as well as the documentation of Hakyeonhwadae Habseolmu (crane dance combined with the lotus blossom dance). By describing the processes and results of motion capture documentation of Salpuri dance (Lee Mae-bang), Taepyeongmu (Kang seon-young) and Seungmu (Lee Mae-bang, Lee Ae-ju and Jung Jae-man) conducted in 2005, this report introduces a new approach for the documentation of intangible cultural heritage. During the first year of the project, two questions have been raised. First, how can we capture motions of a holder (dancer) without cutoffs during quite a long performance? After many times of tests, the motion capture system proved itself stable with continuous results. Second, how can we reproduce the accurate motion without the re-targeting process? The project re-created the most accurate motion of the dancer's gestures, applying the new technology to drew out the shape of the dancers's body digital data before the motion capture process for the first time in Korea. The accurate three-dimensional body models for four holders obtained by the body scanning enhanced the accuracy of the motion capture of the dance.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.101-118
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• 2023

During the COVID-19 pandemic, the utilization rate of neighborhood parks and green spaces increased significantly, and the outbreak served as an opportunity to highlight the values and functions of neighborhood parks and green spaces for urban residents. This study aims to empirically analyze how citizens' movement and the use of neighborhood parks and green spaces changed before and after COVID-19 and examine the social and spatial characteristics that affected these changes. As a research method, first, people's mobility around neighborhood parks and green spaces before and after the COVID-19 pandemic were compared using signal data from telecommunication carriers. Through the analysis of changes in residence time and movement volume, the movement characteristics of citizens after COVID-19 and changes in walking-based park visits were examined. Second, the factors affecting the mobility change in neighborhood parks and green spaces were analyzed. The social and spatial characteristics that affect citizens' visits to neighborhood parks and green spaces before and after COVID-19 were examined through correlation and multiple regression analysis. Subsequently, through cluster analysis, the types of living areas for the post-COVID era were classified from the perspective of the supply and management of neighborhood parks and green spaces services, and directions for improving neighborhood parks and green spaces by type were presented. Major research findings are as follows: First, since the outbreak of COVID-19, activities within 500m of the residence have increased. The amount of stay and walking movement increased in both 2020 and 2021, which means that the need to review the quantitative standards and attractions of neighborhood parks and green spaces has increased considering the changed scope of the walking and living area. Second, the overall number of visits to neighborhood parks and green spaces by walking has increased since the outbreak of COVID-19. The number of visits to neighborhood parks and green spaces centered on the house and the workplace increased significantly. The park green policy in the post-COVID era should be promoted by discovering underprivileged areas, focusing on areas where residential, commercial, and business facilities are concentrated, and improving neighborhood parks and green services in quantitative and qualitative terms. Third, it was found that the higher the level of park green service, the higher the amount of walking movement. It is necessary to use indicators that contribute to improving citizens' actual park green services, such as walking accessibility, rather than looking at the criteria for securing green areas. Fourth, as a result of cluster analysis, five types of neighborhood parks and green spaces were derived in response to the post-COVID era. This suggests that it is necessary to consider the socioeconomic status and characteristics of living areas and the level of park green services required in future park green policies. This study has academic and policy significance in that it has laid the basis for establishing neighborhood parks and green spaces policy in response to the post-COVID era by using various analysis methodologies such as carrier signal data analysis, GIS analysis, and statistical analysis.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• Asia Marketing Journal
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• v.14 no.2
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• pp.209-237
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• 2012

1. Research Purpose Consumers rely on various clues to evaluate their decision to patronize a retail store, and store brand is one of them (Dodds 1991; Grewal et al. 1998). As consumers find ever increasing variety of contact points connecting them to specific store, the value of experiential shopping as a means of increasing store's brand equity warrants greater attention from scholars of retail management. Retail shopping values are credited for creating not only cognitive experiences like brand knowledge but also emotional experiences such as shopping pleasure and pride (Schmitt 1999). This may be because today's consumers place emphasis on emotional values associated with shopping pleasure, lifestyle brought to life, brand relationship, and store atmosphere more than utilitarian values such as product quality and price. Many previous literature found this to be true (Ahn and Lee 2011; Mathwick et al. 2001). This brings forth important research issues and questions regarding the roles of shopping experiential values and brand equity with regard to consumer's retail patronage choice. However, despite this importance, research on this area remains quite inadequate (Hwang 2010). For this reason, this study aims to verify the relationships among experiential shopping values, retail store brand equity and tries to link that with customer loyalty by surveying large-scale discount store shoppers in Korea and China. 2. Research Contents In order to carry out the research objective, this study conducted comprehensive literature survey on previous literature by discussing major findings and implications with regard to shopping values and retail brand equity and store loyalty. For data collection, researcher employed survey-based research method where data were collected in two major cities of Korea (Seoul) and China (Bejing) and sampling frame was based on patrons of large discount stores in both countries. Specific research questions raised in this study are as follows; RQ1: How do Korean and Chinese consumers differently perceive of shopping values regarding shopping at large-sclae discount stores? RQ2: Are there differences in consumers' emotional consumption propensities? RQ3: Do Korean and Chinese consumers display different perceptions of brand equity towards large-scale discount stores? RQ4: Are there differences in relationships between shopping values and brand equity for Korean and Chinese consumers? For statistical analysis, SPSS17.0, AMOS17.0 and SmartPLS were employed. 3. Research Results The data collected through face-to-face survey conducted in Seoul and Bejing revealed appropriate data validity and reliability as a result of exploratory/confirmatory factor analysis and reliability tests, andh SEM model yielding satisfactory model fitness. The result of the study may be summarized by three main points. First, as a result of testing differences in consumption dispositions, Chinese consumers showed higher scores in aesthetic and symbolic dispositions, whereas Korean consumers scored higher in hedonic disposition. Second, testing on perceptions toward brand equity of large discount stores showed that Korean consumers exhibited more positive perceptions of brand awareness and brand image than Chinese counterparts. Third, the result of exploratory factor analysis on the experiential shopping values revealed different factors for each country. On Korean side, consumer interest value, aesthetic value, and hedonic value were prominent, whereas on Chinese side, hedonic value, aesthetic value, consumer interest value, and service excellence value were found salient. 4. Research Implications While many previous studies on inter-country differences in retailing area mainly focused on cultural dispositions or orientations to explain the differences, this study sets itself apart by specifically targeting individual consumer's shopping values from an experiential viewpoint. The study result provides important theoretical as well as practical implications for large-scale discount store, especially the impotance of fully exploring the linkage between shopping values and brand equity, which has significant influence on loyalty. Therefore, the specific implications deriving from the result shed some important insights upon the consumption values based on shopping experiences and brand equity. The differences found in store shoppers between the two countries may also provide useful insights for Korean and Chinese retailers who plan to expand their operations globally. Related strategic implications derived from this study is the importance of localizing retail strategy which is based on the differences found in experiential shopping values between the two country groups. Especially the finding that Chinese consumers value consumer interest and service excellence, whereas Koreans place importance on hedonic or aesthetic values indicates the need to differentiate the consumer's psychographical profiles when it comes to expanding retail operations globally. Particularly important will be to pursue price-orienated strategy in China in consideration of the high emphasis on consumer interests and service excellence, but to emphasize the symbolic aspects of brand equity in Korea by maximizing the brand equity associated with aesthetic values and hedonic orientations. 5. Recommendations This study focused on generic retail branded discount stores in both countries, thus making it difficult to tease out store-specific strategies based on specific retail brands. Future studies may benefit fro employing actual brand names in survey questionnaire to verify relationship between shopping values and brand-based store strategy. As with other studies of this nature, this study needs to strengthen the result's generalizability by selecting respondents from a wider spectrum of respondents.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.871-888
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• 1997

Background : It is now thought that the earliest manifestation of idiopathic pulmonary fibrosis is alveolitis, that is, an accumulation of inflammatory and immune effector cells within alveolar walls and spaces. Inflammatory cells including alveolar macrophages and resident normal pulmonary tissue cells participate through the release of many variable mediators such as inflammatory growth factors and cytokines, which contribute to tissue damage and finally cause chronic pulmonary inflammation and fibrosis. This study was performed to investigate the source and distribution pattern of transforming growth factor-${\beta}_1$(TGF-${\beta}_1$), platelet derived growth factor(PDGF), basic fibroblast growth factor(bFGF), interleukin 1(IL-1), interleukin 6(IL-6), tumor necrosis factor-$\alpha$ (TNF-$\alpha$) and the role of these mediators on bleomycin(BLM)-induced pulmonary injury and fibrosis in rats. Method : Wistar rats were divided into three groups(control group, BLM treated group, BLM and vitamine E treated group). Animals were sacrificed periodically at 1, 2, 3, 4, 5, 7, 14, 21, 28 days after saline or BLM administration. The effects were compared to the results of bronchoalveolar lavage fluid analysis, light microscopic findings, immunohistochemical stains for six different mediators(TGF-${\beta}_1$, PDGF, bFGF, IL-1, IL-6 and TNF-$\alpha$) and mRNA in situ hybridization for TGF-${\beta}_1$. Results : IL-1 and IL-6 are maximally expressed at postbleomycin 1~7th day which are mainly produced by neutrophils and bronchiolar epithelium. It is thought that they induce recruitment of inflammatory cells at the injury site. The expression of IL-1 and IL-6 at the bronchiolar epithelium within 7th day is an indirect evidence of contribution of bronchiolar epithelial cells to promote and maintain the inflammatory and immune responses adjacent to the airways. TNF-$\alpha$ is mainly produced by neutrophils and bronchiolar epithelial cells during 1~5th day, alveolar macrophages during 7~28th day. At the earlier period, TNF-$\alpha$ causes recruitment of inflammatory cells at the injury site and later stimulates pulmonary fibrosis. The main secreting cells of TGF-${\beta}_1$ are alveolar macrophages and bronchiolar epithelium and the target is pulmonary fibroblasts and extracellular matrix. TGF-${\beta}_1$ and PDGF stimulate proliferation of pulmonary fibroblasts and TGF-${\beta}_1$ and bFGF incite the fibroblasts to produce extracellular matrix. The vitamine E and BLM treated group shows few positive cells(p<0.05). Conclusion : After endothelial and epithelial injury, the neutrophils and bronchiolar epithelium secrete IL-1, IL-6, TNF-$\alpha$ which induce infiltration of many neutrophils. It is thought that variable enzymes and $O_2$ radicals released by these neutrophils cause destruction of normal lung architecture and progression of pulmonary fibrosis. At the 7~28th day, TGF-${\beta}_1$, PDGF, bFGF, TNF-$\alpha$ secreted by alveolar macrophages sting pulmonary fibroblasts into proliferating with increased production of extracellular matrix and finally, they make progression of pulmonary fibrosis. TNF-$\alpha$ compares quite important with TGF-${\beta}_1$ to cause pulmonary fibrosis. Vitamine E seems to decrease the extent of BLM induced pulmonary fibrosis.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.41-52
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• 2002

Purpose : 3D conformal radiotherapy, the optimum dose delivered to the tumor and provided the risk of normal tissue unless marginal miss, was restricted by organ motion. For tumors in the thorax and abdomen, the planning target volume (PTV) is decided including the margin for movement of tumor volumes during treatment due to patients breathing. We designed the respiratory gating radiotherapy device (RGRD) for using during CT simulation, dose planning and beam delivery at identical breathing period conditions. Using RGRD, reducing the treatment margin for organ (thorax or abdomen) motion due to breathing and improve dose distribution for 3D conformal radiotherapy. Materials and Methods : The internal organ motion data for lung cancer patients were obtained by examining the diaphragm in the supine position to find the position dependency. We made a respiratory gating radiotherapy device (RGRD) that is composed of a strip band, drug sensor, micro switch, and a connected on-off switch in a LINAC control box. During same breathing period by RGRD, spiral CT scan, virtual simulation, and 3D dose planing for lung cancer patients were peformed, without an extended PTV margin for free breathing, and then the dose was delivered at the same positions. We calculated effective volumes and normal tissue complication probabilities (NTCP) using dose volume histograms for normal lung, and analyzed changes in doses associated with selected NTCP levels and tumor control probabilities (TCP) at these new dose levels. The effects of 3D conformal radiotherapy by RGRD were evaluated with DVH (Dose Volume Histogram), TCP, NTCP and dose statistics. Results : The average movement of a diaphragm was 1.5 cm in the supine position when patients breathed freely. Depending on the location of the tumor, the magnitude of the PTV margin needs to be extended from 1 cm to 3 cm, which can greatly increase normal tissue irradiation, and hence, results in increase of the normal tissue complications probabiliy. Simple and precise RGRD is very easy to setup on patients and is sensitive to length variation (+2 mm), it also delivers on-off information to patients and the LINAC machine. We evaluated the treatment plans of patients who had received conformal partial organ lung irradiation for the treatment of thorax malignancies. Using RGRD, the PTV margin by free breathing can be reduced about 2 cm for moving organs by breathing. TCP values are almost the same values $(4\~5\%\;increased)$ for lung cancer regardless of increasing the PTV margin to 2.0 cm but NTCP values are rapidly increased $(50\~70\%\;increased)$ for upon extending PTV margins by 2.0 cm. Conclusion : Internal organ motion due to breathing can be reduced effectively using our simple RGRD. This method can be used in clinical treatments to reduce organ motion induced margin, thereby reducing normal tissue irradiation. Using treatment planning software, the dose to normal tissues was analyzed by comparing dose statistics with and without RGRD. Potential benefits of radiotherapy derived from reduction or elimination of planning target volume (PTV) margins associated with patient breathing through the evaluation of the lung cancer patients treated with 3D conformal radiotherapy.

• Solar Energy
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• v.13 no.2_3
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• pp.65-78
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• 1993

An overdose of fossil fuel for greenhouse heating causes not only the high cost and low quality of agricultural products, but also the environmental pollution of farm village. To solve these problems it is desirable to maximize the solar energy utilization for the heating of greenhouse in winter season. In this study phase change materials were selected to store solar energy concentratively for heating the greenhouse and their characteristics of thermal energy storage were analyzed. The results were summarized as follows. The organic $C_{28}H_{58}$, and the inorganic $CH_3COONa{\cdot}3H_2O\;and\;Na_2SO_4{\cdot}10H_2O$ were selected as low temperature latent heat storage materials. The equation of critical radius was derived to define the generating mechanism of the maximum latent heat of phase change materials. The melting point of $C_{28}H_{58}$ was $62^{\circ}C$, and the latent heat was $50.0{\sim}52.0kcal/kg$. The specific heat of liquid and solid phase was $0.54{\sim}0.69kcal/kg^{\circ}C$ and $0.57{\sim}0.75kcal/kg^{\circ}C$ respectively. The melting point of $CH_3COONa{\cdot}3H_2O$ was $61{\sim}62^{\circ}C$, the latent heat was $64.9{\sim}65.8$ kcal/kg and the specific heat of liquid and solid phase was respectively $0.83kcal/kg^{\circ}C$ and $0.51{\sim}0.52kcal/kg^{\circ}C$. The melting point of $Na_2SO_4{\cdot}10H_2O$ was $30{\sim}30.9^{\circ}C$, the latent heat was 53.0 kcal/kg and the specific heat of liquid and solid phase was respectively $0.78{\sim}0.89kcal/kg^{\circ}C$ and $0.50{\sim}0.7kcal/kg^{\circ}C$ When the urea of 21.85% was added to control the melting point of $Na_2SO_4{\cdot}10H_2O$ and the phase change cycles were repeated from 0 to 600, the melting point was $16.7{\sim}16.0^{\circ}C$ and the latent heat was $36.0{\sim}28.0kcal/kg^{\circ}C$.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Dairy Science and Biotechnology
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• v.34 no.2
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• pp.99-116
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• 2016

We herein performed animal safety assessment in accordance with Good Laboratory Practice (GLP) regulations with the aim of developing sialic acid from glycomacropeptide (hereafter referred to as "GMP") as an index ingredient and functional component in functional foods. GMP is a type of whey protein derived from milk and a safe food, with multiple functions, such as antiviral activity. A test substance was produced containing 7% (w/w) sialic acid and mostly-hydrolyzed whey protein (hereafter referred to as "7%-GNANA") by enzymatic treatment of substrate GMP. The maximum intake test dose level was selected based on 5,000 mg/kg/day dose set for male NOEL (no-observed-effect-level) and female NOAEL (no-observed-adverse-effect-level) determined by a dose-range finding (DRF) test (GLP Center of Catholic University of Daegu, Report No. 15-NREO-001) that was previously conducted with the same test substance. To evaluate the toxicity of a repeated oral dose of the test substance in connection with the previous DRF study, 1,250, 2,500, and 5,000 mg/kg of the substance were administered by a probe into the stomachs of 6-week-old SPF Sprague-Dawley male and female rats for 90 d. Each test group consisted of 10 male and 10 female rats. To determine the toxicity index, all parameters, such as observation of common signs; measurements of body weight and food consumption; ophthalmic examination; urinalysis, electrolyte, hematological, and serum biochemical examination; measurement of organ weights during autopsy; and visual and histopathological examinations were conducted according to GLP standards. After evaluating the results based on the test toxicity assessment criteria, it was determined that NOAEL of the test substance, 7%-GNANA, was 5,000 mg/kg/day, for both male and female rats. No animal death was noted in any of the test groups, including the control group, during the study period, and there was no significant difference associated with test substance, as compared with the control group, with respect to general symptoms, body weight changes, food consumption, ophthalmic examination, urinalysis, hematological and serum biochemical examination, and electrolyte and blood coagulation tests during the administration period (P<0.05). As assessed by the effects of the test substance on organ weights, food consumption, autopsy, and histopathological safety, change in kidney weight as an indicator of male NOAEL revealed up to 20% kidney weight increase in the high-dose group (5,000 mg/kg/day) compared with the change in the control group. However, it was concluded that this effect of the test substance was minor. In the case of female rats, reduction of food consumption, increase of kidney weight, and decrease of thymus weight were observed in the high-dose group. The kidney weight increased by 10.2% (left) and 8.9% (right) in the high-dose group, with a slight dose-dependency compared with that of the control group. It was observed that the thymus weight decreased by 25.3% in the high-dose group, but it was a minor test substance-associated effect. During the autopsy, botryoid tumor was detected on the ribs of one subject in the high-dose group, but we concluded that the tumor has been caused by a naturally occurring (non-test) substance. Histopathological examination revealed lesions on the kidney, liver, spleen, and other organs in the low-dose test group. Since these lesions were considered a separate phenomenon, or naturally occurring and associated with aging, it was checked whether any target organ showed clear symptoms caused by the test substance. In conclusion, different concentrations of the test substance were fed to rats and, consequently, it was verified that only a minor effect was associated with the test substance in the high-dose (5,000 mg/kg/day) group of both male and female rats, without any other significant effects associated with the test substance. Therefore, it was concluded that NOAEL of 7%-GNANA (product name: Helicobactrol) with male and female rats as test animals was 5,000 mg/kg/day, and it thus was determined that the substance is safe for the ultimate use as an ingredient of health functional foods.