• Tuberculosis and Respiratory Diseases
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• v.51 no.5
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• pp.409-415
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• 2001

Background : Multidrug-resistant tuberculosis(MDR-TB) in patients is mainly caused by acquired drug resistance. However, a small proportion of MDR-TB is caused by initial drug resistance(IDR), which may be somewhat different from acquired drug resistance. This study analyzed the clinical characteristics of IDR in MDR -TB patients to use the results as basic data in managing the disease. Methods : A retrospective study of 30 IDR cases in MDR-TB patients from Jan. 1995 to Dec. 1998 was performed. In order to analyze the clinical characteristics, the age, sex, family history, duration of negative conversion, number of resistant drugs, treatment regimens, duration of treatment, extent of disease and cavitary lesion on the chest X-ray was examined. In order to analyze the level of improvement, the extent of the disease and cavitary lesion on the chest X-ray, tested by Wilcoxon signed rank sum test, and the disease free interval rate of 1-year and 4-year was examined using the Kaplan-Meier method. Results : The mean age of the patients was 46.6 years and the sex ratio 1:1. Six(20%) patients had a family history. The mean negative conversion of the sputum AFB stain was 2.6 months. The number of resistant drugs was 7.6 and the number of used drugs 3.6. Twenty-three(67%) patients were treated for less than 12months and 28(93%) patients were treated with first-line drugs. The extent of the disease and the cavitary lesion on the chest X-ray improved after treatment(p<.05). Among 13 patients who were followed up for 22.6 months, 2(15%) patients relapsed and the disease free interval rate of I-year and 4-year was 85%. Conclusion: It is recommended that the duration of treatment of IDR in MDR-TB with first-line drugs be 9-12 months even if the extent of disease and cavitary lesion on the chest X-ray improves.

• The Journal of Korean Academy of Prosthodontics
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• v.47 no.2
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• pp.182-190
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• 2009

Statement of problem: Microleakage at the occlusal and gingival margin of Class V cavities restored with composite resin has traditionally been considered an obstacle to successful restoration. Purpose: The aim of this study was to assess the effectiveness of three different surface sealants(Fortify, Permaseal and Biscover LV) on the marginal sealing of Class V light-activated composite resin restorations(Z250). Material and methods: Forty noncarious human premolars and molars extracted within a three-month period were selected. Class V cavities with the occlusal margin in enamel and gingival margin in cementum were prepared in both buccal and lingual surfaces. The teeth, randomly assigned in four groups with twenty cavities in each group, were restored with composite resin after applying an adhesive system(Clearfil SE bond). After the finishing and polishing procedures, the restorations were covered with a specific surface sealants, except for the control samples, which were not sealed. After placing restorations, the specimens were thermocycled, and immersed in a 2% methylene blue solution for twenty four hours and sectioned longitudinally. The marginal microleakage was evaluated at the occlusal and gingival interfaces using a microscope and compared among the four groups using ANOVA test and Wilcoxon Rank-Sum test($\alpha$=0.05). Results: Statistical analysis showed that there was significantly less leakage when the surface sealants were used than there was in control group(P<.05). There were no significant differences of microleakage at occlusal and gingival margins among groups. There were no significant differences between microleakage of occlusal and gingival margins in each group. Fortify was not statistically different from control group at the gingival margin(P>.05). Conclusion: Application of surface sealants was an effective method of surface coating in reducing microleakage at occlusal and gingival margins of Class V composite resin restorations. However, it is certain that some microleakage still occurred despite the application of surface sealants, especially gingival margins.

• Restorative Dentistry and Endodontics
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• v.30 no.1
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• pp.1-6
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• 2005

In order to examine the immunoresponse of host cells to Enterococcus faecalis, this in vitro study monitored the production of Interleukin-2 (IL-2), Interleukin-4 (IL-4) and Transforming growth factor-$\beta1\;(TGF-\beta1)$ in human lymphocytes. Lymphocytes were activated with PHA in the presence or abscence of sonicated extracts of E. Faecalis (SEF) and further incubated for 72 hours. The level of each cytokine was measured by ELISA. Data were analyzed with Kruskal-Wallis test and Mann-Whitney U test (P < 0.05). PHA-activated group did exhibit higher level of IL-2 and IL-4 than untreated control group. The levels of expression of both cytokines were significantly decreased following the treatment of high (25 ${\mu}g/ml$) and medium concentration (12.5 ${\mu}g/ml$)) of SEF (P > 0.05) than those of PHA activated group. But low concentration (5 ${\mu}g/ml$)) of SEF showed th similar level of IL-2 and IL-4 production as those of PHA activated group. $TGF-\beta1$ was unaffected by SEF treatment. These results suggested that E. faecalis may suppress IL-2 and IL-4 production by lymphocytes and this could be one of possible factors why E. faecalis are found frequently in the teeth with failed endodontic treatment.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Hospice and Palliative Care
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• v.6 no.1
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• pp.51-57
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• 2003

Purpose : Anorexia-cachexia syndrome is one of the most common symptoms and main cause of death in terminal cancer patients. This symptom is due to the enlarged cancer mass as well as tumor released cytokines. Some doctors have suggested that vitamin C was preferentially toxic to tumor cells in vitro and in vivo, and improved clinical symptoms in terminal cancer patients. Therefore, we measured cytokines in serum of terminal cancer patients to determine whether vitamin C treatment improved the anorexia-cachexia syndrome. Methods : We investigated that 49 terminal cancer patients admitted to the department of family medicine, National Health Insurance Corporation Ilsan hospital from March 1, 2002 to August 31, 2002. The study was done on 22 patients who were given 10 g/day of vitamin C infusions during 1 week and 27 patients who were not infused. We measured the cytokines levels ($IL-1{\beta}$, IL-6, and $TNF-{\alpha}$) before and after 1 week between terminal cancer patients treated vitamin C and without vitamin C. Results : Out of 49 patients, patents treated with vitamin C infusions were 22 (12 male, 10 female), and these without vitamin C were 27 (18 male, 9 female). In patients treated with vitamin C, $IL-1{\beta}\;were\;6.19{\pm}5.17$ before day and $8.76{\pm}5.72$ after 1 week, IL-6 were $3.07{\pm}8.09$ before day and $1.31{\pm}2.36$ after 1 week, and $TNF-{\alpha}\;were\;2.74{\pm}14.24$ before day and $0.50{\pm}2.00$ after 1 week. In patients treated without vitamin C, $IL-1{\beta}\;were\;2.50{\pm}3.58$ before day and $6.49{\pm}12.01$ after 1 week, IL-6 were $1.00{\pm}2.19$ before day and $17.16{\pm}81.55$ after 1 week, and $TNF-{\alpha}\;were\;1.19{\pm}2.98$ before day and $1.27{\pm}1.52$ after 1 week. The level of cytokines in patients treated with vitamin C decreased more than those without vitamin C. However, this represented no statistical value (P=0.0598 in $IL-1{\beta}$, P=0.1664 in IL-6, and P=0.5395 in $TNF-{\alpha}$). Conclusion : In terminal cancer, even if there was no statistical difference in the cytokines levels between patients treated with vitamin C and those not treated, those who were treated had a decrease all cytokines levels. Vitamin C is very safe with almost no side effects. Therefore, vitamin C treatment in terminal cancer patients can be seen as beneficial and helpful for clinical symptoms.