• Journal of Ginseng Research
• /
• v.48 no.5
• /
• pp.454-463
• /
• 2024

Background: Panax quinquefolius L, widely recognized for its valuable contributions to medicine, has aroused considerable attention globally. Different from the extensive research has been dedicated to the root of P. quinquefolius, its berry has received relatively scant focus. Given its promising medicinal properties, this study was focused on the structural characterizations and anti-inflammatory potential of acidic polysaccharides from the P. quinquefolius berry. Materials and methods: P. quinquefolius berry was extracted with hot water, precipitated by alcohol, separated by DEAE-52-cellulose column to give a series of fractions. One of these fractions was further purified via Sephadex G-200 column to give three fractions. Then, the main fraction named as AGBP-A3 was characterized by methylation analysis, NMR spectroscopy, etc. Its anti-inflammatory activity was assessed by RAW 264.7 cell model, zebrafish model and molecular docking. Results: The main chain comprised of α-L-Rhap, α-D-GalAp and β-D-Galp, while the branch consisted mainly of α-L-Araf, β-D-Glcp, α-D-GalAp, β-D-Galp. The RAW264.7 cell assay results showed that the inhibition rates against IL-6 and IL-1β secretion at the concentration of 625 ng/mL were 24.83 %, 11.84 %, while the inhibition rate against IL-10 secretion was 70.17 % at the concentration of 312 ng/mL. In the zebrafish assay, the migrating neutrophils were significantly reduced in number, and their migration to inflammatory tissues was inhibited. Molecular docking predictions correlated well with the results of the anti-inflammatory assay. Conclusion: The present study demonstrated the structure of acidic polysaccharides of P. quinquefolius berry and their effect on inflammation, providing a reference for screening anti-inflammatory drugs.

• Trans-
• /
• v.12
• /
• pp.51-79
• /
• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• IMMUNE NETWORK
• /
• v.1 no.3
• /
• pp.236-243
• /
• 2001

Background: An immunological approach for aging mechanism appears to be important. Lymphocyte subsets analysis in peripheral blood is widely performed to assess the immune status and to diagnose and monitor various diseases. Some lymphocyte subsets are known to change with age, but only few data about age-related reference ragnes for these subsets in healthy individuals have been reported. So we attempted to report reference ranges for these subsets in each age group and review changes of the results with age for the secondary studies about immune cell function as lymphocyte blast transformation and immunoglobulin gene rearrangement (VDJ) including recombination activating genes (RAG-1 and RAG-2). Methods: Lymphocyte subset analysis was performed on 302 subjects, 189 males and 113 females with age group of all decades of life. Two color direct immunofluorescene flow cytometry (FCM) was done using $Simultest^{TM}$ IMK-Lymphocyte kit (Becton Dickinson, USA), $FACScan^{TM}$ (Becton Dickinson, USA) and $FACSCalibur^{TM}$ (Becton Dickinson, USA). Lymphocyte subsets analysed were T ($CD3^+$) and B cells ($CD19^+$), helper/inducer T ($CD4^+$) and suppressor/cytotoxic T cells ($CD8^+$), helper/suppressor ($CD4^+/CD8^+$) ratio and natural killer (NK) cells ($CD3^-CD16^+/CD56^+$). The absolute numbers of each subset were calculated from total lymphocyte counts. Data collected was analysed using SAS 6.12. A P-value of < 0.05 was considered significant. Results: We reported the counts and percentages of lymphocyte and these subsets in each age group. There were no statistically significant differences between male and female subjects. The percentage of $CD4^+$ T cells, and the count of NK cells did not show the significant difference among the various age groups. The age-related changes observed in our study were as following: 1) a decrease in the percentages of T cells, B cells and $CD8^+$ T cells ; 2) a decrease in the counts of B cells and $CD8^+$ T cells ; 3) an increase in the percentage and count of NK cells ; and 4) an increase in the $CD4^+/CD8^+$ ratio. Conclusion: The characteristics of aging process appeared to be showing a marked decrease of lympocyte subsets T and B cells as well as T8 ($CD8^+$). The age-related increase of the percentage of cells bearing NK marker can be interpreted as a compensatory consequence to cope with the decrease of T cells related to the thymic involution. These changes with age appeared to be for the secondary study about immune cell function as lymphocyte blast transformation and immunoglobulin gene rearrangement.

• Tuberculosis and Respiratory Diseases
• /
• v.45 no.3
• /
• pp.536-545
• /
• 1998

Background: The studies on prediction equations of pulmonary function parameters for adults in Korea have been performed in a reference population mainly consisted of young and middle ages. So they included a relatively few elderly who conducted pulmonary function test frequently in clinic. We established prediction equations of pulmonary function parameters for healthy adults over 50 years old in rural area and compared this results with those of other studies. Therefore we attempted to consider normative values of pulmonary function tests for elderly in Korea. Method: Five hundred thirty-three women and men over 50 years old in rural area were participated. A "healthy" subgroup of 110 women and 32 men were identified by excluding those who had conditions that negatively influenced pulmonary function. We derived prediction equations for FVC, $FEV_1$ and $FEV_1%$ by multiple linear regression method from their age, heights and weights in each sex. Results: Prediction equations for FVC and $FEV_1$ in each sex were derived as follows Male; FVC (L)=0.02488Height(cm)-0.0269Age(years)+0.493 $FEV_1(L)$=0.01874Weight(kg)-0.0282Age(years)+2.906 Female; FVC(L)=0.02160Height(cm)-0.0192Age(years)-0.0125 $FEV_1(L)$=0.01720Height(cm)-0.0194Age(years)+0.3890 Prediction equations for $FEV_1%$ were not derived because $FEV_1%$ didn't have statistically significant terms. Comparing Predicted values that were calculated by substitution into the equations of various studies of mean values of age, heights and weights from this study, FVC and $FEV_1$ values in men of this study were lower than those of other studies. In women, FVC and $FEV_1$ values of this study were as similar as or lower than those of the study conducted for healthy elderly blacks in U.S.A respectively. Conclusion: We have got prediction equations of pulmonary function parameters which were driven from forced expiratory spirogram in adults over 50 years old in rural area. Predicted values of this study were lower than those of other studies which were conducted in Korea. So we consider that the study for spirometry reference values for elderly Korean using the method compatible with ATS recommendation need to be conducted more frequently forward.

• Tuberculosis and Respiratory Diseases
• /
• v.54 no.2
• /
• pp.210-218
• /
• 2003

Background : Sex specific cross sectional reference values for the lung function indices usually employ a linear model with a term for age and height. The purpose of this study was to determine the effects of the body mass index (BMI), the fat percentage of the body mass and the fat-free mass index (FFMI) on the forced expiratory volume curve. Methods : Between January 2000 and December 2001, a total of 300 subjects, 150 men and 150 women (mean age : $45{\pm}13$ years), with a normal lung function were enrolled in the study sample. This study measured the $FEV_1$, FVC and $FEF_{25-75%}$ from the forced expiratory volume curve by a spirometer and the body composition by a bioelectrical impedance method in all subjects. Multiple regression analysis was used in order to examine the effects of the body composition on the parameters derived from the forced expiratory volume curve. Results : After adjusting for age, the BMI and Fat percentage improved the descriptions of the FVC (p<0.05, $r^2=0.491$) and $FEV_1$ (p<0.05, $r^2=0.654$) in women. In contrast, the FFMI contributed significantly to the FVC (p<0.05, $r^2=0.432$) and $FEV_1$ (p<0.05, $r^2=0.567$) in men. The $FEF_{25-75%}$ correlated with the fat percentage in women (p<0.05, $r^2=0.337$). Conclusion : These results suggest that the BMI, the fat percentage and the FFMI are significant determinants of the forced expiratory volume curve. The plmonary function test, when considering the BMI, the fat percentage and the FFMI, might be useful in clinical applications.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.32 no.4
• /
• pp.132-142
• /
• 2014

This study is the first stage to identify distinctive characteristics of American Romantic Garden compared to English Romantic Garden. The purpose of the study is to identify characteristics of transitional garden in the early period of America by analyzing of Paca garden, Mount Vernon and Monticello when English Naturalistic Garden was firstly imported. The analysis studied historical background, people who designed garden, formal garden and characteristics of natural garden through reference. Also based on data through reference and field research, spatial configuration and garden factors of each site were analyzed. In spatial configuration, straight line and curve line, formal terrace and natural slope, visible axis and invisible axis, symetric and asymmetric, and perspective and oblique perspectives were used as analyzing factors. As a result of analysis, each garden showed different type from that of formal gardens from colony period, which is natural garden of asymmetric garden(English natural garden) coexisted. Paca garden which planned formal garden and natural garden in each space showed characteristics of each space, but in formal garden residential axis and garden axis does not coincide which shows it is out of formal garden type. Such phenomena and the fact that naturalistic garden coexist in the same garden shows that the formal garden type from early days in US is starting to change in different types. Mount Vernon garden, similar to Paca garden, was designed to have two different types of gardens in harmony rather than divide the space into different space and design it. It adapted serpent walkway but shows symmetric by central axis and considered formalistic plan through same materials. However through terrace in hills and spatial plan of oblique perspective, one could observe that naturalistic type was beginning to settle in US gardens. Through Monticello analysis, space was designed with major characteristics of naturalistic garden which is serpent walkway, ornamental farm, winding flower bed grove and bush and oblique perspective, and it completely duplicates characteristics of naturalistic garden which could not be found in gardens imported from UK.

• Tuberculosis and Respiratory Diseases
• /
• v.45 no.6
• /
• pp.1178-1187
• /
• 1998

Background : Recently the incidence of tuberculosis is increasing in many countries and control of the disease is further threatened by the emergence of multi-drug resistant tuberculosis. So rapid detection of drug resistance is very important. Pyrazinamide (PZA) is a first-line chemotherapeutic agent for tuberculosis. Now in Korea, we perform PZase activity test instead of actual pyrazinamide susceptibility test for the detection of PZA resistant M. tuberculosis. Recently the pncA gene, encoding the PZase of M. tuberculosis, was completely sequenced. And it was reported that the mutation of pncA gene would be associated with PZA resistance of M. tuberculosis. Therefore we performed this study to evaluate the possibility for the rapid detection of PZA resistant M. tuberculosis using PCR-SSCP of pncA gene. Method : 44 cultured clinical isolates of M. tuberculosis, BCG Tokyo strain. BCG French strain, and one M. bovis isolate were studied. We used H37Rv as the reference strain, The PZase activity test was done at the reference laboratory of Korean Tuberculosis Institute. DNA was extracted by bead-beater method and 561 bp fragment including pncA gene was amplified by PCR. The PCR product were digested by BstB I enzyme. SSCP was done using MDE gel. Of the 44 strains of M. tuberculosis, 22 strains were PZase-positive and other 22 strains were PZase negative. Results : Of the 22 PZase positive strains, 18 strains(82%) showed the same mobility compared with that of H37Rv and 4(18%) showed different mobility. Of the 22 PZase-negative strains, 19(86%) strains showed the same mobility pattern compared with that of H37Rv and 3(14%) showed different mobility. Naturally PZA-resistant BeG-French strain, BCG-Tokyo strain, and one M. bovis isolate showed the same band pattern each other, but their mobility were different from that of H37Rv. The results of PZase activity test and PCR-SSCP of pncA of M. tuberculosis were statistically significantly correlated each other (p<0.01). Conclusion : The PCR-SSCP after BstB I restriction of pncA gene of M. tuberculosis may be a useful method for the rapid detection of PZA-resistant M. tuberculosis.

• Annals of Clinical Microbiology
• /
• v.18 no.2
• /
• pp.37-43
• /
• 2015

Background: Tuberculosis is globally the most important cause of death from single pathogen. Rapid and accurate identification of mycobacteria is essential for the control of tuberculosis. We evaluated a fluorescence in situ hybridization (FISH) method using peptide nucleic acid (PNA) probes for the differentiation of Mycobacterium tuberculosis complex (MTB) and nontuberculous mycobacteria (NTM) in direct smears of sputum specimens. Methods: The cross-reactivity of MTB- and NTM-specific PNA probes was examined with reference strains of M. tuberculosis ATCC 13950, Mycobacterium kansasii ATCC 12479, Mycobacterium fortuitum ATCC 6841, several clinical isolates of mycobacteria (Mycobacterium abscessus, Mycobacterium avium, Mycobacterium intracellulare, Mycobacterium gordonae and Mycobacterium chelonae), and 11 frequently isolated respiratory bacterial species other than mycobacteria. A series of 128 sputa (89 MTB culture positive, 29 NTM culture positive, and 10 under treatment culture negative) with grades of trace to 4+ were used to evaluate the performance of the method. Results: The MTB- and NTM-specific PNA probes showed specific reactions with the reference strains of MTB and M. kansasii and clinical isolates of mycobacteria except M. fortuitum ATCC 6841, and no cross-reactivity with other tested bacteria. The PNA probe-based FISH assay for detection of MTB had a sensitivity and specificity of 100%, respectively. The sensitivity and specificity of the NTM-specific PNA probe was 100%. The smear grades of the PNA FISH test were same as with those of the fluorescence AFB stain in 2+ or higher grade. Conclusion: Detection and differentiation based on PNA FISH is sensitive and accurate for detecting mycobacteria and for differentiating MTB from NTM in clinical sputum smears.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.16 no.2
• /
• pp.51-78
• /
• 2021

Followed by 'start-up', the theme of 'scale-up' has been considered as an important agenda in both corporate and policy spheres. In particular, although it is a term commonly used in industry and policy fields, even a conceptual definition has not been achieved from the academic perspective. "Corporate Growth" in the academic aspect and "Business Growth" in the practical management field have different understandings (Achtenhagen et al., 2010). Previous research on corporate growth has not departed from Penrose(1959)'s "Firm as a bundle of resources" and "the role of managers". Based on the theory and background of economics, existing research has mainly examined factors that contribute to firms' growth and their growth patterns. Comparatively, we lack knowledge on the firms' growth with a focus on 'annual revenue growth rate'. In the early stage of the firms, they tend to exhibit a high growth rate as it started with a lower level of annual revenue. However, when the firms reach annual revenue of more than 100 billion KRW, a threshold to be classified as a 'middle-standing enterprise' by Korean standards, they are unlikely to reach a high level of revenue growth rate. In our study, we used our sample of 333 companies (6.7% out of 5,000 'fastest-growing' companies) which reached 15% of the compound annual growth rate in the last three years with more than USD 100 million. It shows that sustaining 'high-growth' above a certain firm size is difficult. The study focuses on firms with annual revenue of more than $100 billion (approximately 120 billion KRW) from the 'Inc. 2020 fast-growing companies 5,000' list. The companies have been categorized into 1) Fast-growing companies (revenue CAGR 15%~40% between 2016 and 2019), 2) Hyper-growing companies (40%~99.9%), and 3) Super-growing (100% or more) with in-depth analysis of each group's characteristics. Also, the relationship between the revenue growth rate, individual company's strategy choice (market orientation, generic strategy, growth strategy, pioneer strategy), industry/market environment, and firm age is investigated with a quantitative approach. Through conducting the study, it aims to provide a reference to the 'Hyper-Growing Model' that combines the paths and factors of growth strategies. For policymakers, our study intends to provide a reference to which factors or environmental variables should be considered for 'optimal effective combinations' to promote firms' growth.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1181-1189
• /
• 2022

Clouds are composed of tiny water droplets, ice crystals, or mixtures suspended in the atmosphere and cover about two-thirds of the Earth's surface. Cloud detection in satellite images is a very difficult task to separate clouds and non-cloud areas because of similar reflectance characteristics to some other ground objects or the ground surface. In contrast to thick clouds, which have distinct characteristics, thin transparent clouds have weak contrast between clouds and background in satellite images and appear mixed with the ground surface. In order to overcome the limitations of transparent clouds in cloud detection, this study conducted cloud detection focusing on transparent clouds using machine learning techniques (Random Forest [RF], Convolutional Neural Networks [CNN]). As reference data, Cloud Mask and Cirrus Mask were used in MOD35 data provided by MOderate Resolution Imaging Spectroradiometer (MODIS), and the pixel ratio of training data was configured to be about 1:1:1 for clouds, transparent clouds, and clear sky for model training considering transparent cloud pixels. As a result of the qualitative comparison of the study, bothRF and CNN successfully detected various types of clouds, including transparent clouds, and in the case of RF+CNN, which mixed the results of the RF model and the CNN model, the cloud detection was well performed, and was confirmed that the limitations of the model were improved. As a quantitative result of the study, the overall accuracy (OA) value of RF was 92%, CNN showed 94.11%, and RF+CNN showed 94.29% accuracy.