22 research outputs found
a randomized controlled trial
íìë
Œë¬ž(ë°ì¬) -- ììžëíêµëíì : ì곌ëí ì곌í곌, 2021.8. ìµíì§.Background - Since lifestyle modification is the cornerstone of the obesity treatment, digital therapeutics (DTx) became one of the compelling and easily accessible treatment modalities.
Objective - This research proposes to validate the treatment efficacy, understand behavioral changes by eating behavioral analysis, identify the predictive digital phenotypes for engagement and clinical outcomes, and examine genetic precision medicine of a novel digital therapeutic for obesity (dCBT-O).
Method â This was an open-label, active-comparator, randomized controlled trial. Seventy female participants with body mass index (BMI) scores above 24kg/m² and no clinical problems besides obesity were randomized into experimental and control groups. The experimental group (dCBT-O group; 45 participants) was connected with a therapist intervention using a digital healthcare service that provided daily feedback and assignments for 8 weeks. The control group (25 participants) also used the digital healthcare service but practiced self-care without therapist intervention. Regarding the validating treatment efficacy, the primary outcomes of this study were objectively measured: weight in kg as well as other body compositions at 0, 8, and 24 weeks. Also, several eating behavioral phenotypes were assessed by buffet test-meal and food diary in app to examine the healthy behavioral change. Regarding the predictors for treatment efficacy, multidimensional digital phenotypes within time-series data were analyzed by elastic net regression method and obesity-related SNPs were genotyped from dCBT-O group.
Result â Both weight (â3.1%, SD 4.5, vs â0.7%, SD 3.4; p = 0.036) and fat mass (â6.3%, SD 8.8, vs â0.8%, SD 8.1; p = 0.021) reduction at 8 weeks in the dCBT-O group were significantly higher than in the control group. Applying the machine learning approach, sixteen types of digital phenotypes (i.e., lower intake of high calorie food and evening snack, higher interaction frequency with mentors) predicted engagement rates, thirteen different digital phenotypes (i.e., lower intake of high calorie food and carb, higher intake of low calorie food) predicted the short-term weight change, and eight measures of digital phenotypes (i.e., lower intake of carb and evening snack, higher motivation) predicted the long-term weight change. The dCBT-O was also successful in promoting healthy eating behaviors that led to physiological and psychological adjustment for the metabolic mechanisms and consequences of healthy eating behavior. Lastly, CETP and APOA2 SNPs were significantly associated with the change in BMI (p = 0.028 and p = 0.005, respectively) at 24 weeks and eating behavioral phenotypes (p = 0.007 for healthy diet diversity and p = 0.036 for healthy diet proportion, respectively), the clinical efficacy markers of this study.
Conclusion â These findings confirm that the multidisciplinary approach via digital modalities enhances the clinical efficacy of digital-based interventions for obesity. Moreover, it contributes to better understand the mechanisms of human eating behavior related to weight control. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics.ë¹ë§ì ëíì ìž ìíìµêŽ ì§ë³ìŒë¡ ìë €ì ž ìë€. ë°ëŒì, íšê³Œì ìž ë¹ë§ ì¹ë£ë¥Œ ìíŽìë ë€ì°šìì ìž ì¹ë£ì ì ê·ŒìŽ ì€ììëëë°, ëì§íž ì¹ë£ì (Digital Therapeutics; DTx)ë ìŽë¬í ì ê·Œì ìµì í ëìŽìë€. 볞 ì°êµ¬ì 목ì ì ìë¡ ê°ë°í ë¹ë§ ëì§íž ì¹ë£ì ì íšê³Œë¥Œ ììì ì§íë€ê³Œ ìì íë íííë€ì ë³í륌 êž°ë°ìŒë¡ ê²ìŠíë©°, ì¹ë£ì ììëì íšê³Œì±ì ììž¡í ì ìë ëì§íž íííë€ê³Œ ì ì íë€ì íìíë ê²ìŽë€.
볞 ì°êµ¬ììë BMI 24 ìŽì, êž°í ììì ìž ìŠìì 볎ìŽì§ ìë 70ëª
ì 2-30ë ì¬ì±ë€ì ëììŒë¡ ëì¡°êµ° ëë¹ ë¹ë§ ëì§íž ì¹ë£ì êµ°(Digital Therapeutic for Obesity; dCBT-Oêµ°)ì 1:2 ë¹ìšì 묎ììë°°ì ìììíì ìííìë€. dCBT-Oêµ°ì ë¹ë§ ì¹ë£ë ììì¬ëŠ¬í ì ê³µ ë° ëì§íž í¬ì€ìŒìŽ ì 묞ê°ê° 8죌 ëì ì§ííììŒë©°, 24죌찚ìë ì¹ë£ í 겜곌ì ëí íê°ë¥Œ ì€ìíìë€. ë¹ë§ ëì§íž ì¹ë£ì íšê³Œ ê²ìŠì 죌ì ì§íë 첎ì€ì ë¹ë¡¯í ë€ìí ì 첎 ê³ìž¡ ì§íë€ì ë³íìŽë€. ìŽì°š ì§íë ë·íì€í곌 몚ë°ìŒ ìŽí늬ìŒìŽì
ëŽ ìëšêž°ë¡ìì ìì§ë ììíë íííë€ì êž°ë°ìŒë¡ 걎ê°í ììíë ë³íìŽë€. ì¹ë£ ììë ë° íšê³Œ ììž¡ ìžìë€ì ë°êµŽíêž° ìíŽìë ë€ì°šìì ìž ìê³ìŽ ëì§íž íííë€ì ëšžì ë¬ë êž°ë²ìŒë¡ ë¶ìíìë€. ê·žëŠ¬ê³ , ì¹ë£ ë°ì ìì€ì ììž¡íë ì ì íë€ì ì°Ÿêž° ìíŽ ëšìŒìŒêž°ë€í(Single Nucleotide Polymorphisms; SNP) ë¶ìì ìííìë€.
볞 ì°êµ¬ì 죌ì ê²°ê³Œë¡ ì²«ì§ž, 8ì£Œê° ì¹ë£ ì§í dCBT-Oêµ°ì ì²Žì€ ë³íê° ëì¡°êµ°ì ì²Žì€ ë³íì ë¹íŽ ì ì믞íê² ê°ëíììŒë©°, ì¹ë£ ì¢
ë£ í 24죌찚ë 첎ì€ìŽ ê°ë ë° ì ì§ëìë€. ë짞, dCBT-Oêµ°ì ììíëìŽ ëì¡°êµ°ì ììíëì ë¹íŽ ì ì믞íê² ê±Žê°í ììíëìŒë¡ ìŠì§ëìë€. ì
짞, ëšžì ë¬ë ë¶ìì 결곌 16ê°ì§ ëì§íž íííë€ìŽ ì¹ë£ì ììë륌 ììž¡íê³ , 13ê°ì§ ëì§íž íííë€ìŽ ëšêž°ì ìž ì¹ë£íšê³Œë¥Œ ììž¡íë©°, 8ê°ì§ ëì§íž íííë€ìŽ ì¥êž°ì ìž ì¹ë£íšê³Œë¥Œ ììž¡íìë€. ë§ì§ë§ìŒë¡, CETPì APOA2 SNP ì ì íë€ìŽ ì 첎ê³ìž¡ ë³íì ììíëë³íì ì ì믞í ìêŽì 볎ìë€.
볞 ì°êµ¬ë ëì§íž êž°ì ì íì©í ë€íì ì ìž ì ê·ŒìŽ ë¹ë§ ëì§íž ì¹ë£ì ì ìì íšê³Œë¥Œ í¥ììíšë€ë ê²ì 볎ì¬ì€ë€. ëí ë€ì°šìì ìž ë¶ìì íµíŽ ì²Žì€ ì¡°ì 곌 êŽë šë ìžê°ì ìì íëì ë©ì»€ëìŠì ë ì ìŽíŽíë ë° êž°ì¬íë€. 볞 ì°êµ¬ë ì²šëš ìë°©ìí곌 ì ë°ìíì ìí ëì§íž ì¹ë£ì ê°ë°ì ì€ìí íšë¬ë€ìì ì ìí ê²ìŽë€.Chapter 1. Introduction 1
Part I. Validating the treatment efficacy and finding its predictive markers: development of a dCBT-O 6
Part II. Eating behavioral analysis using buffet test-meal and food diary in app: understanding human eating behavior change by dCBT-O 8
Part III. Digital phenotyping using machine-learning analysis: identifying a predictive model for engagement in application and clinical outcomes of dCBT-O 11
Part IV. Genetic analysis for predicting the clinical responses: genetic precision medicine of dCBT-O 14
Chapter 2. Method 19
Chapter 3. Results 40
Chapter 4. Discussion 75
Perspectives A. Main issues related to DTx for obesity and eating behavior problems 91
Perspectives B. Limitations of DTx being applied in the clinics 96
Perspectives C. Future perspectives and recommendations 96
Chapter 5. Conclusion 99
Bibliography 100
Abstract in Korean 118
Acknowledgement 120ë°
Survey for Government Policies Regarding Strategies for the Commercialization and Globalization of Digital Therapeutics
Purpose: This study was conducted to build a direction for government policies regarding strategies for the commercialization of digital therapeutics in Korea, as well as its globalization.
Materials and methods: The study included 37 participants from the Korea Digital Health Industry Association (KODHIA). The data was based on a survey conducted in 2020 targeting employees of companies engaged in the digital health industry in Korea. Participants were asked about their involvement in product development of digital therapeutics and their opinion about the growing motivator for digital therapeutics in Korea and the global market.
Results: According to our data, among subjects not involved in making digital therapeutics products, the main reason for not being involved was the lack of experts (73.9%) and difficulty in licensing (73.9%). Responses concerning the priority area in need of national support were R&D funding (43.2%), and the next was licensing guidance and simplifying regulations (24.3%). Possible difficulties of overseas market expansion were the unfamiliarity in digital therapeutics technology verification and licensing structures of foreign countries (73%), and concerns regarding the level of recognition of clinical trials and technology in Korea from overseas (70.3%). Overall, respondents were hesitant in starting a related business due to the lack of government support and the complexity of the regulation process. Moreover, concerns about global market entry were similar. Being unfamiliar with the novel process and worrying about the achievement despite existing challenges were the biggest drawback.
Conclusion: For the digital therapeutics industry to evolve domestically and internationally, government support and guidance are essential.ope
(A) follow-up study of pulmonary function after pneumonectomy or lobectomy
ìí곌/ìì¬[íêž]
íì ì ì ì ìííë íììì ìì íì ìì¬ íêž°ë¥ì íê°ë ìì ê°ë¥ì±ìŽë ìì ì íì ì ì ë²ì륌 ê²°ì íëë° ì€ìíë€. ëìŽê° ë§ê±°ë í¡ìžë ¥, ë§ì± íìì± íì§íìŽ ìë 겜ì°, íêž°ë¥ìŽ ê°ìë ìíìì íì€ì§ì ê°ìë íêž°ë¥ì ì íë ìì í íží¡ ë¶ì ì ìŽëí ì ìêž° ë묞ìŽë€. ìì ì íêž°ë¥ì ììž¡ ë°©ë²ìŒë¡ë ì¬ë¬ ê°ì§ ë°©ë²ìŽ ìëëìŽ ììŒë ííë ìž¡ì ë²ìŽ 볎ížì ìŒë¡ ì°ìŽê³ ìê³ , ìµê·Œìë íêŽë¥ 죌ì¬ë¥Œ ì¬ì©íì¬ ë¹êµì ì íí ìì íêž°ë¥ì ììž¡í ì ììŽ ììì ìŒë¡ ìŽì©ëê³ ìë€. íì ì ì í íêž°ë¥ìŽ ê°ìíë ì ëë íì ì ë²ì, ì ì ë¶ìì íêž°ë¥ êž°ì¬ë, ì ì íì€ì§ì ìì€ ì ë, ìì ë¡ ìží ìí¥ ë± ì¬ë¬ ììžìŽ ìì©íë©°, ìì í ëšììë íì¡°ì§ì ì¡°ì§íì ë³í, ì¬íêž°ë¥ì ë³íë íêž°ë¥ì ê²°ì íë ìììŽë€. 볞 ì°êµ¬ììë íì ì ì ì 곌 ìì í 1죌ìì 24ê°ìê¹ì§ íêž°ë¥ ê²ì¬ë¥Œ ì€ìíì¬ ìŽë¬í ìŒë šì ë³í 곌ì ì ë¶ìíê³ ì íììŒë©° ë€ì곌 ê°ì 결곌륌 ì»ìë€.
1. ëì íì 41ëª
ì€ ëšìë 25ëª
, ì¬ìë 16ëª
ìŽììŒë©° ì°ë ¹ì 25ìžìì 75ìžë¡ íê· ì°ë ¹ì 50.4±19.8ìžìë€. ëìêµ°ì ììž ì§íì íììŽ 30ìë¡ ê°ì¥ ë§ìê³ , ê·žìž íê²°íµìŽ 4ì, aspergilloma 4ì, êž°êŽì§ íì¥ìŠìŽ 1ì, êž°êŽì§ ê²°ììŽ 1ììë€. ìì ì íë³
ë¡ë ì íì ì ì ìŽ 20ì, íìœì ì ì ìŽ 21ììë€.
2. ìì ì íêž°ë¥ì íìœì ì 군곌 ì íì ì êµ°ìì ê°ê° EVC 2.99 L; 2.79L, FEV1 2.29 L; 2.13 L, FEF25-75 2.13 L/sec; 1.76 L/sec, MVV 91.9 L/min; 81.35 L/minìŒë¡ ì íì ì êµ°ìŽ ë®ìê³ , íêž°ë¥ ììž¡ì¹ë ê°ê° ìì ì ê°ì 79.9%, 68.7%ìë€.
3. ìì ì§í íêž°ë¥ì ì ëìêµ° 몚ëìì íì íê² ê°ìíììŒë©°, ìì í 3ê°ì짞ì ìì ì ìž¡ì ì¹ì ë¹ì·íê² íë³µëìê³ , ê·ž ìŽíë ì ì°š ê°ìíë 겜í¥ì 볎ìë€.
4. ìì í 6ê°ììì ì íì ì êµ°ìŽ íìœì ì êµ°ì ë¹íŽ 몚ë íêž°ë¥ ì§íìì ìììê² ê°ìëìŽ ììê³ (p<0.05), íµê³íì ììë ìììŒë 3ê°ì ìŽí ë¶í°ë ì íì ì êµ°ìŽ íìœì ì êµ° ë³Žë€ ê°ìíë 겜í¥ì 볎ìë€.
5. ìì í íêž°ë¥ì 3ê°ììë ììž¡ì¹ ë³Žë€ ìŠê°íììŒë©°, 6ê°ììì 12ê°ì ì¬ìŽìë ììž¡ì¹ì ì ì¬íìê³ , ê·ž ìŽíìë ììž¡ì¹ ë³Žë€ ê°ìíìë€.
6. íêž°ë¥ ê²ì¬ ì§íì€ììë FVC, FEV1ìŽ ìì ìì²Žë¡ ìží ìí¥ì ê°ì¥ ë§ìŽ ë°ë ê²ìŒë¡ ëíë¬ë€.
ìŽìì 결곌ë¡ì ì íì ì 군곌 íìœì ì êµ° ì¬ìŽì ìì í íêž°ë¥ì ì ìí ì°šìŽë ìììŒë, ì ëìêµ°ìì 몚ë ìì í 1죌ì íì í íêž°ë¥ ê°ì륌 볎ìë€. 3ê°ììë ìì ì ìž¡ì ì¹ì ê°ê¹ê² íë³µìŽ ëìŽ ììž¡ì¹ë³Žë€ ë€ì ìŠê°íììŒë©°, 6ê°ììì 12ê°ìê¹
ì§ë ììž¡ì¹ì ì ì¬í ê°ìŒë¡ ë³íê° ìë€ê° ê·ž ìŽíìë ê°ìíë ê²ìŒë¡ ëíë¬ë€. ë°ëŒì ìì íì êž°ê°ì ë°ëŒ íêž°ë¥ì íë³µìšìŽ ë€ë¥Žë¯ë¡ ìŽì êŽí ììì ìì©ì êŽíì¬ ììž¡ì¹ì ì°ì ë²ì í¬íší ì¶êµ¬ì ì°êµ¬ê° íìí ê²ìŒë¡ ìê°ëë€.
[ì묞]
It is important to evaluate the pulmonary reserve after lung resection in the preopertive determination of the operability and extent of resection. Loss of the functioning lung or the operation itself may precipitate respiratory distress postoperatively, especially in the elderly, smokers, or those who have had other pulmonary diseases. Among a number of methods to predict the postoperative pulmonary function, spirometry is the most familiar and convenient methods for patients and physicians. Recently, prediction of the postoperative pulmonary function became possible due to the combination of spirometry and radioisotope lung perfusion scan. The degree of loss of pulmonary function is related to the extent of resection, the function of the resected and the remaining lung, the operation itself and postoperative pathophysiologic changes of the cardiopulmonary system. In this study, the pulmonary function test was performed in pneumonectomy and lobectomy patients preoperatively, in the immediate postoperative period and thereafter to 24 months, and the results were as follows;
1. The preoperative values of the pulmonary function test were lower in the pneumonectomy group than in the lobectomy group.
2. The immediate postoperative pulmonary function was markedly decreased in both groups and the function improved closely to its preoperative value 3 months after the operation and then showed a tendency to decrease.
3. Differences in pulmonary function between the two groups were seen only 6 months after operation(p<0.05), but the values of the pneumonectomy group seemed to be lower after 3 months without statistical significance.
4. Pulmonary function increased above the predicted value at the 3rd month, was similar to it from the 6th ti 12th month, and decreased below it after 12 months.
5. The most vulnerable indices of the pulmonary function test after operation were FVC and FEV1.
From the above results, it is concluded that there were no significant differences in postoperative pulmonary function between the lobectomy and pneumonectomy groups, and the value of the pulmonary function test improved to the preoperative level at the 3rd month(above the predicted value), was similar to the
predicted value form the 6th to 12th month when it reached a plateau, and decreased thereafter.restrictio
ì°ëŠŒììíšìêž°ë¥íê°ë¥Œ íµí ììíšì볎ížêµ¬ì ì€ì ë°©ì ì°êµ¬
íìë
Œë¬ž (ìì¬)-- ììžëíêµ ëíì : ìí조겜·ì§ììì€í
ê³µíë¶(ìí조겜í), 2014. 2. ìŽëê·Œ.ì°ëŠ¬ëëŒë êµí ì 65%ê° ì°ëŠŒìŒë¡ ìŽë£šìŽì ž ìììì ìì ì ìŒë¡ ìŽì©íëë° ììŽ ì°ëŠŒì ë§€ì° ì€ìí ìí ì íë€. ì°ëŠŒì ìŠì°ìì©ì ìíŽ ì§íë©Žì ìŽ í겜ì ìíìí€ê³ , ì°ëŠŒì ë³íë ì§íì ìŽ í겜ì ë³íìí¬ ë¿ë§ ìëëŒ ìŠì°ëì ê°ìììŒ ë¬Œ ìíì ë³íìí¬ ì ìì ë¿ë§ ìëëŒ. ê°ë², ìì¢
ê°±ì ë±ì íµíŽ ê°ì© ìììì ìŠì§ ìí¬ ì ìë€. ìµê·Œ ì°ëŠŒì²ê³Œ ììì ê³µì¬ììë ììíšìêž°ë¥ìŽ ë¹ìœí ì°ëŠŒì 구조륌 ê°ëíì¬ ì°ëŠŒì ììíšìêž°ë¥ì ìŠì§ìí€ë ì¬ì
ì ìííê³ ìë€.
ì°ëŠŒì ììíšì êž°ë¥ì ìŠì§ ìí€êž° ìíŽìë ì²ê°êŸžêž° ì¬ì
ì íµí ì§ìì ìž ì°ëŠŒêŽëŠ¬ì ëë¶ìŽ ìê³ ìžì ì§ìì ê°ë° ë°©ì§ë¥Œ ìí ììíšì 볎ížêµ¬ìì í충íì¬ ììíšìêž°ë¥ì ê³ ëë¡ ë°íìí€êž° ìí ë
žë ¥ìŽ íìíë€.
ììíšìêž°ë¥ìŠì§ì ìíŽìë íŽë¹ëë ì°ëŠŒ ì ìì ì ì ì 첎륌 íëì 볎ížêµ¬ììŒë¡ íµí©íë êŽëŠ¬íë ê²ìŽ íšê³Œì ìŽì§ë§, 볎ížêµ¬ì ì§ì ì ê°ìžì ì¬ì°ê¶ ì¹šíŽ ì§ì 믌ì ë± ê°ë±ì ì ë° í ì ììŽì ìžì¬í ê²í ê° ì구ëë€.
볞 ì°êµ¬ììë êµëŽÂ·ìžìì ììíšìêž°ë¥ ì§í ì ì ë° íê°ì êŽë šë ë€ìì 묞íì ê³ ì°° í í ììíšìë¥ë ¥ì ìž¡ì í ì ìë ì§í륌 ì ì íêž° ìíŽ ê³ ë €í ì ìë í볎 ì§í목ë¡ì ëì¶ í í ì ì¬íê³ ìêŽì±ìŽ ëì í목ë€ì ì¢
í©íì¬ ëšìíí ì§í륌 ëì¶íìë€.
ì°ëŠŒììíšìêž°ë¥ì 볎ížíêž° ìí ì°ëŠŒ ì€ ì°ì ììê° ëì ì§ìì ì¶ì¶íêž° ìíŽ ê³ëí ë íê° êž°ì€ì ì ì©íìë€. ì°ëŠŒì 묌늬ì , ìíì , ì¬í·겜ì ì ì¬ê±Žì ë°ë¥ž ì°ì ìì륌 ë¶ì¬íì¬ ì¢
í©ì ìŒë¡ íê°íšìŒë¡ìš ì°ì ìì륌 ë¶ì¬íì¬ ì ëì ìŒë¡ íê°íì¬ ì¥í¥ë ì ìì 볞 ì°êµ¬ 결곌륌 ì ì©íì¬ ììíšì볎ížêµ¬ìì ì ì íìë€.
볞 ì°êµ¬ 결곌 ì€ì ë ììíšì볎ížêµ¬ìì ìŽ 132haìŽë©°, íì¬ì ììíšìêž°ë¥ìŽ ëì ì§ììŒë¡ íê° ë ì§ìì ì 첎 ì§ì ë©Žì ì 78%ìž 103haë¡ ëíë¬ë€. ììíšìêž°ë¥ì ìŠì§ ê°ë¥ì±ìŽ ëì ì§ìì 29haë¡ ëíë¬ë€. ììíšììŠì§ ê°ë¥ì±ìŽ ëì ì§ìì ì°ëŠŒ êŽëŠ¬ì ì°ê° ìœ 23tonì ìììì ìŠì§ ìí¬ ì ìì ê²ìŒë¡ ëíë¬ë€.
볞 ì°êµ¬ë¥Œ íµíŽ êŽëŠ¬ ë° ë¯Œìì 묞ì 륌 ê³ ë €íì¬ êµì 늌ì ííŽ ì ì íìì§ë§, ì¶í ì°êµ¬ë¥Œ íµíŽ 공·ì¬ì 늌 ì€ ììíšììŠì§ì ìíŽ êŽëŠ¬ê° ìêží ì§ììŽë íŒì ê°ë¥ì±ìŽ ëì ì§ìì íì
íì¬ ë¶ì² ê° íì륌 íµí ìì°šì ìŒë¡ 볎ížêµ¬ì ì€ì ê²í ê° íìíë€.â ì°š ë¡ â
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(The) effects of item wording on scale characteristics : focused on positive and negative attitude scale
íìë
Œë¬ž(ìì¬) --ììžëíêµ ëíì :êµì¡í곌(êµì¡íì ê³µ),2010.2.Maste
HLA DQA1, DQB1 alleles associated with genetic susceptibility to insulin-dependent diabetes mellitus in Korean
ìí곌/ë°ì¬[íêž]
ìžì늰 ìì¡Ží ë¹ëšë³ì ì ì ì ììžìŽ ìë ì¬ëìì ë°ìŽë¬ì€ ê°ìŒ ë±ì í겜ì ììžìŽ ìì©íì¬ ì·ì¥ì ë² íìží¬ê° ìê°ë©Žìë°ìì ìíì¬ íꎎëìŽ ìžì늰 ê²°íìŽ ìŽëëë ì§íìŒë¡ ìë €ì ž ìë€. ì ì ì ììžìŒë¡ìš HLA class â
íì곌ì ìêŽêŽê³ê° ìŒì°êž° 볎
ê³ ëìê³ , ìŽí HLA class â
볎ë€ë HLA class â
¡ íì곌 ë°ì í êŽê³ê° ìë ê²ìŒë¡ ë°íì¡ë€. ìµê·Œ ë¶ìì ì íì ë°ì ì ë°ëŒ HLA class â
¡ íì ì€ììë HLA DQì ì ìì ì€ìì±ìŽ ìë €ì§ë©Žì, DQA1ì 52ë²ì§ž ì믞ë
žì° ìì¹ì ì륎Ʞë, DQB1ì 57ë²ì§ž ì믞ë
žì° ìì¹ì ìì€í륎ížì° ë±ì ì¡Žì¬ ì 묎ì ë°ë¥ž ê°ìì±ì ì°šìŽ ë±ìŽ ì¬ë¬ ìžì¢
ìì ë³Žê³ ëìë€. HLA ì ì ìì ë¹ëë ìžì¢
ë° ì§ìì ë°ëŒ ì°šìŽê° ììŽ ìŽë€ ìžì¢
ê°ì ì°šìŽë¥Œ ë¹êµíšìŒë¡ìš ìžì늰 ìì¡Ží ë¹ëšë³ì ê°ìì±ì ê²°ì íë ì ì ì륌 ê·ëª
íë ê²ìŽ ê°ë¥í ê²ìŒ
ë¡ ìê°ëê³ ìë€. ìŽì 볞 ì°êµ¬ììë ì€í©íšìì°ìë°ìì ìŽì©í ì ííšì ë¶ì êžžìŽ ë€íì± ë°©ë², ë늜ì ì ì í¹ìŽ ì¬ëŠ¬ê³ ëŽíŽë ì€í°ëí칚(allele specific oligonucleotide probe)ì ìŽì©í ì ëžë¡¯(dot-blot) ë¶ì ë°©ë² ë° ì ì ì íŽë¡ëì ìí DNA ììŽ ê²°ì ë°©ë²ì ì¬ì©íì¬ íêµìž ìžì늰 ìì¡Ží ë¹ëšë³ íìì ì ììžì ëììŒë¡ HLA DR ííí, DQA1 ë° DQB1 ì ì ìì íë³ ë¶ìì ìííì¬ ë€ì곌 ê°ì 결곌륌 ì»ìë€.
1. íêµìž ìžì늰 ìì¡Ží ë¹ëšë³ íììì HLA DR3, DR4, DR3/4ë ì ììžë³Žë€ ì ìíê² ìŠê°ëìŽ ììê³ , DR2, DR8ì ê°ìëìŽ ììë€.
2. HLA DQA1 ì ì ì ì€ììë DQA1 (*)**0301 ìŽ íìêµ°ìì ì ìíê² ìŠê°ëìŽ ìììŒë©°, DQA1 (*)**0101 ,(*)**0102 ë íìêµ°ìì ê°ìëìŽ ììë€.
3. DQA1 ì ì ìì€ Arg52 ìì±/Arg52 ìì± ëíì í©ì²Ž(homozygote)ì ë¹ëë íìêµ°ìì ì ìíê² ëììŒë©°, íìêµ°ì 97%ìì ì ìŽë 1ê° ìŽìì Arg52 ìì±ìž ì ì ì륌 ê°ì§ê³ ìë ê²ìŒë¡ ëíë¬ë€.
4. HLA DQB1 ì ì ì ì€ììë DQB1 (*)**0201 ë° (*)**0303 ìŽ íìêµ°ìì ì ìíê² ìŠê°ëìŽ ììê³ (*)**0301 ì ê°ìëìŽ ììë€.
5. DQB1 ì ì ìì€ Asp57 ìì±ìž ì ì ìì ë¹ëë íì군곌 ì ììž ì¬ìŽì ì ìí ì°šìŽê° ììë€.
6. DQA1-DQB1ì ìí ë² í ìŽíìŽí©ì²Ž(heterodimer)ì ë¹ëë íìêµ°ìì DQA1 (*)**04 -DQB1 (*)**0201 , DQA1 (*)**301 -DQB1 (*)**0303 , DQA1 (*)**0301 -DQB1 (*)**0201 ìŽ ì ìíê² ìŠê°ëìŽ ììê³ , DQA1 (*)**0101 , 0102-DQB1 (*)**0604, DQA1 (*)**0101 ,
0102-DQB1 (*)**0302 ë ì ìíê² ê°ìëìŽ ììë€.
7 ì¶ì ê°ë¥í HLA DR-DQA1-DQB1 ìŒë°°ì²Ží(haplotype)ì ë¹ëë íìêµ°ìì DR3-DQAl (*)**0301 -DQB1 (*)**0201 ë° DR3-DQA1 (*)**04 -DQB1 (*)**0201 ìŽ ìŠê°ëìŽ ììë€. ìŽìì 결곌ìì íêµìž ìžì늰 ìì¡Ží ë¹ëšë³ íììì HLA DR íííì ë¹ëë ìœì¹Žìì곌 ë¹ì·íììŒë, DR3/4ê° ìëì ìŒë¡ ë®ìê³ , í¹í ëììžìž ì€êµìž, ìŒë³žìžê³Œë ì°šìŽê° ììŽ ìžì¢
ê°ì ì°šìŽê° ììë€. HLA DQ ì ì ìíì DQA1 (*)**0301 곌 DQB1 (*)**0303 , DQB1 (*)**0201 ìŽ ì ìíê² ìŠê°ëìŽ ììê³ , DQA1 (*)**0101 , (*)**0102 ì DQB1 (*)*
*0301 ì ì ìí ê°ì륌 ë³Žì¬ ì§ë³ì ê°ìì±ì êž°ì¬í ê²ìŒë¡ ìê°ëììŒë©°, ìŽë€ DQA1 ë° DQB1 ì ì ì ëšë
ìŒë¡ 볎ë€ë ìí ë² í ìŽíìŽí©ì²Žê° ê°ìì±ì ê²°ì íëë° ì€ìí ìí ì í ê²ìŒë¡ ì¬ë£ëìë€. ëí ë³ìžì ëë ë°©ìŽì ìž ì ì ìê°ì ìížìì© ë° ì©ëíšê³Œê° êŽì°°ëìŽ ìŽë¬í ìì©ì ìŽíë¡ìš ì§ë³ì ëí ê°ìì±ìŽ ê²°ì ë ê²ìŒë¡ ìê°ëìë€.
HLA DQA1, DQB1 alleles associated with genetic susceptibility to insulin-dependent
diabetes mellitus in Korean
Mi Rim Kim
Department of Medical Science The Graduate School, Yonsei University
(Directed by Associate Professor Hyun Chul Lee)
Family and population studies have shown that at least one susceptibility locus
for insulin-de-pendent diabetes mellitus(IDDM) is located in the HLA (human
leucocyte antigen) class â
¡ region. Transracial analysis provides a method of
distinguishing primary associations between IDDM and HLA calss â
¡ alleles from
those secondary to linkage disequilibrium. This study was aimed to investigate the
HLA association with IDDM in Korean population.
DNA, amplified by polymerase chain reaction(PCR), was subjected to allele
specific oligonucleotide dot-blot analysis, restriction fragment length
polymorphism(RFLP) analysis and DNA sequencing.
The frequency of HLA DR3, DR4 and DR3/4 was significantly increased in the
diabetic patients(15/55[27.3%] vs control subjects, 8/76[10.5%], p<0.05, RR =3.1,
39/55[70.9%] vs. 23/76[30.3%], RR=5.3, p<0.01, 8/55[14.5%] vs.3/76[4.1%], RR=4.0,
p<0.05).The frequency of DR2 and DR8 was significantly decreased in the diabetic
patients(3/55[5.4%] vs. 14/76[18.4%], RR=0.3, p<0.05 and 5/55[9.1%] vs.
21/76[27.6%], RR=0.3, p<0.05).
The frequency of DOQA1 (*)**0301, which was positively associated with IDDM in
Caucasian and Japanese but not in Chinese, was significantly higher in the
patients(27/32[84.5%] vs. control subjects,24/39[61.5%], RR=3.4, p<0.05).
The frequency of DQA1 (*)**0101 ,(*)**0102 was significantly lower in the diabetic
Patients(9/32[28.1% vs. control subjects, 21/39[53.8], RR=0.3, p<0.05).
The frequency of DQB1 (*)**0201 , which was not associated with IDDM in Chinese,
was significantly higher in the diabetic patients(16/37[43.3% vs. control subjects,
5/36[13.9%], RR=6.2, p<0.005). The frequency of DQB1 (*)^^0303 was significantly
higher in the diabetic patients(16//37[43.2%0 vs.control subjects, 3/36[8.3%],
RR=8.4, p<0.001).
The frequency of the heterodimer DQA1 (*)**0301 -DQB1 (*)**0201 , DQA1 (*)**0301
-DQB1 (*)**0303 , DQA1 (*)**04 -DQB1 (*)**0201 was significantly increased and DQA1
(*)**0101 , 0102-DQB1 (*)**0302 was significantly decreased in diabetic patients.
The frequency of the deduced haptotype DR3-DQA1 (*)**0301 -DQB1 (*)**0201 and
DQA1 (*)**04 -DQB1 (*)**0201 was significantly increased in diabetic
patients(9/28[32.1%] vs. DR3-positive control subjects, O/l8[0.0%], p<0.01 and 7/28
vs. 0/18[0.0%], p<0.05).
The frequency of Arg52 positive allele homozygotes was significantly increased in
diabetic patients but the frequency of Asp57 positive allele was not different from
control subjects. The distribution of HLA DR phenotype of Korean IDDM patients was
similar to Caucasian IDDM patients except for relatively low frequency of HLA DR3/4
and was slightly different from other Oriental populations. HLA DQAl (*)**0301 ,
DQB1 (*)**0303 , DQB1 (*)**0201 were increased and DQA1 (*)**0101 , DQA1 (*)**0102
, DQB1 (*)**0301 were decreased in Korean IDDM patients. It seems likely that there
exists dose effect among these susceptible and Protective alleles. And also the
role of heterodimer which is consisted of these alleles may be important to
determine susceptibility to IDDM.
[ì묞]
Family and population studies have shown that at least one susceptibility locus for insulin-de-pendent diabetes mellitus(IDDM) is located in the HLA (human leucocyte antigen) class â
¡ region. Transracial analysis provides a method of
distinguishing primary associations between IDDM and HLA calss â
¡ alleles from those secondary to linkage disequilibrium. This study was aimed to investigate the HLA association with IDDM in Korean population.
DNA, amplified by polymerase chain reaction(PCR), was subjected to allele specific oligonucleotide dot-blot analysis, restriction fragment length polymorphism(RFLP) analysis and DNA sequencing.
The frequency of HLA DR3, DR4 and DR3/4 was significantly increased in the diabetic patients(15/55[27.3%] vs control subjects, 8/76[10.5%], p<0.05, RR =3.1, 39/55[70.9%] vs. 23/76[30.3%], RR=5.3, p<0.01, 8/55[14.5%] vs.3/76[4.1%], RR=4.0,
p<0.05).The frequency of DR2 and DR8 was significantly decreased in the diabetic patients(3/55[5.4%] vs. 14/76[18.4%], RR=0.3, p<0.05 and 5/55[9.1%] vs. 21/76[27.6%], RR=0.3, p<0.05).
The frequency of DOQA1 (*)**0301, which was positively associated with IDDM in Caucasian and Japanese but not in Chinese, was significantly higher in the patients(27/32[84.5%] vs. control subjects,24/39[61.5%], RR=3.4, p<0.05).
The frequency of DQA1 (*)**0101 ,(*)**0102 was significantly lower in the diabetic Patients(9/32[28.1% vs. control subjects, 21/39[53.8], RR=0.3, p<0.05).
The frequency of DQB1 (*)**0201 , which was not associated with IDDM in Chinese, was significantly higher in the diabetic patients(16/37[43.3% vs. control subjects, 5/36[13.9%], RR=6.2, p<0.005). The frequency of DQB1 (*)^^0303 was significantly
higher in the diabetic patients(16//37[43.2%0 vs.control subjects, 3/36[8.3%], RR=8.4, p<0.001).
The frequency of the heterodimer DQA1 (*)**0301 -DQB1 (*)**0201 , DQA1 (*)**0301 -DQB1 (*)**0303 , DQA1 (*)**04 -DQB1 (*)**0201 was significantly increased and DQA1 (*)**0101 , 0102-DQB1 (*)**0302 was significantly decreased in diabetic patients.
The frequency of the deduced haptotype DR3-DQA1 (*)**0301 -DQB1 (*)**0201 and DQA1 (*)**04 -DQB1 (*)**0201 was significantly increased in diabetic patients(9/28[32.1%] vs. DR3-positive control subjects, O/l8[0.0%], p<0.01 and 7/28 vs. 0/18[0.0%], p<0.05).
The frequency of Arg52 positive allele homozygotes was significantly increased in diabetic patients but the frequency of Asp57 positive allele was not different from control subjects. The distribution of HLA DR phenotype of Korean IDDM patients was
similar to Caucasian IDDM patients except for relatively low frequency of HLA DR3/4 and was slightly different from other Oriental populations. HLA DQAl (*)**0301 , DQB1 (*)**0303 , DQB1 (*)**0201 were increased and DQA1 (*)**0101 , DQA1 (*)**0102
, DQB1 (*)**0301 were decreased in Korean IDDM patients. It seems likely that there exists dose effect among these susceptible and Protective alleles. And also the role of heterodimer which is consisted of these alleles may be important to determine susceptibility to IDDM.restrictio
Studies on Staphylococcus aureus derived extracellular vesicle as one of causes in immune-based inflammatory disorder in the lung
MasterAsthma is characterized by the over-whelming activation of the adaptive immune system against allergens and is caused by common allergens including house dust mite and pollen to invade in to the airway. The Th2 hypothesis of asthma is that exaggerated Th2 immune response in allergen sensitized person induces eosinophilic airway inflammation in combination with a decreased Th1 response. Although many reports support the Th2 hypothesis, recent researches reported that IFN-γ (a Th1 cytokine) is elevated in the blood and airway, and IL-17 (a Th17 cytokine) is also increased in asthma patients, especially severe asthma patients (neutrophilic asthma). Previously, our group first found that house dust, an important causative agent, induces lung inflammation derived by T helper cell (Th) 17 immune response and house dust-derived extracellular vesicles (dust EV) also induce lung inflammation mediated by Th17 immune response. We also found that house dust contaminates S. aureus which is gram-positive bacterium presenting in air or indoor dust as well as colonizing the human skin and nasopharynx. S. aureus is a one of the most important human pathogens, and it causes various superficial, systemic, and nosocomial infections. There are no researches that reported relationship between S. aureus-derived inflammatory lung diseases and Th17 immune response. Recent studies reported that S. aureus can produce S. aureus-derived vesicles that may be able to act as causative agent for inflammation such as atopic dermatitis.The vesicles were prepared by sequential ultrafiltration and ultracentrifugation. In vitro and in vivo innate immune dysfunction was evaluated after application to alveolar macrophages in vitro and after once application to the mouse airways, respectively. Adaptive immune dysfunction was evaluated after 3 weeks airway exposure of the vesicles with or without ovalbumin (OVA), respectively. Inflammation and immune response were evaluated at 6 h or 48 h after the final application. Inflammatory cytokines and serum antibody were measured by ELISA and flow cytometry. Else, evaluation of inflammation was measured by histology stained with H&E. The present study shows that S. aureus-derived vesicles enhanced the production of proinflammatory mediators, such as TNF-alpha, IL-6 and IP-10, from alveolar macrophages. In addition, once application of the vesicles into the mouse airways increased lung inflammation and the production of IL-12 and IL-6 (Th1 and Th17 polarizing cytokines, respectively) as well as proinflammatory mediators including TNF-alpha and IL-1. Repeated airway exposure of the vesicles for 3 weeks induced neutrophilic inflammation in the lung, which is associated with both Th1 and Th17 cell responses. In terms of adjuvant effect of the vesicles, sensitization with the vesicles and OVA and then challenge with OVA alone induced neutrophilic inflammation which is partially eliminated by the absence of IFN-gamma or IL-17. Our results indicate that S. aureus-derived vesicles can induce neutrophilic inflammation in the lung via both Th1- and Th17-dependent mechanisms. S. aureus-derived vesicles are a novel target for the development of technologies for neutrophilic asthma control
Analysis of Students Open-Ended Course Evaluation Using Topic Modeling
ìŽ ì°êµ¬ë í íœ ëªšëžë§(topic modeling)ì ìŒì¢
ìž ì ì¬ ë늬íŽë í ë¹(latent Dirichlet allocation, ìŽí LDA)ì íì©íì¬ Sëíêµì íìë€ìŽ ìì±í ê°ìíê° ìëµì ë¶ìíšìŒë¡ìš íìë€ìŽ ê°ê³ ìë ê°ìì ëí ìê°ì ë³Žë€ ì§ì ì ìŒë¡ ììë³Žê³ ì íìë€. ìŽë¥Œ ìíŽ 2015ë
1íêž°ì ê°ì€ë ìœ 1,500ê° ê°ìì ëíŽ íìë€ìŽ ê°ììì ê°ì ëìŽìŒ í ì 곌 ê°ììì ì¢ìë ì ì ëíŽ ìì í ìœ 47,000ê°ì ìëµ ëŽì©ì LDA륌 íì©íŽ ë¶ìíìë€. ììžë¬, 6ê°ì ëšê³Œëí(공곌ëí, ëì
ìëª
곌íëí, ì¬ë²ëí, ìžë¬žëí, ì¬í곌íëí, ìì°ê³Œíëí) ê°ìì ê°ì ëìŽìŒí ì , ì¢ìë ì ì ëíŽ ë¶ìíìë€. ë¶ì 결곌, 첫짞, ê°ììì ê°ì ëìŽìŒ í ì 곌 ê°ììì ì¢ìë ì 몚ë 3ê° ì£Œì 몚íìŽ ê°ì¥ ì í©í ê²ìŒë¡ ëíë¬ë€. 뚌ì , ê°ììì ê°ì ëìŽìŒ í ì ì 1) 곌ì ·ì€í·ì€ìµì ëí ê°ì ì¬í, 2) ë°í·í ë¡ ì ëí ê°ì ì¬í, 3) ìí·ì§ë·ìì
ëŽì©ì ëí ê°ì ì¬íì ìž ê°ì§ 죌ì ë¡ ëíë¬ë€. ë€ììŒë¡, ê°ììì ì¢ìë ì ì 1) êµìì·êµì ë°©ë²ì ëí êžì ì íŒëë°±, 2) ì§ì ì 겜í·ì€ìµì ëí êžì ì íŒëë°±, 3) ê°ìëŽì©ì ëí êžì ì íŒëë°±ì ìž ê°ì§ 죌ì ë¡ ëíë¬ë€. ë짞, ëšê³Œëíë³ ë¶ì 결곌, ëšê³Œëíë³ë¡ ëíë 죌ì ì ì믞ë ë첎ì ìŒë¡ ì 첎 ëí ìë£ë¥Œ ë¶ìíì ëì ë¹ì·íìŒë, íëì 죌ì ì ëê° ëšê³Œëíì í¹ì±ì ë°ìíê³ ìë ê²ìŒë¡ ëíë¬ë€. ìŽ ì°êµ¬ë ê°ìíê°ì ì íí 묞í ë¶ìì ì¹ì€íìë êž°ì¡Ž ì°êµ¬ì ë¬ëŠ¬, í íœ ëªšëžë§ì íì©íšìŒë¡ìš ëëì ìì í ê°ìíê° ìë£ë¥Œ íšìšì ìŒë¡ ììœíììŒë©°, ìŽë¥Œ íµíŽ ê°ì ì ë°ì ëí íìë€ì ìžìì ë³Žë€ ì§ì ì ìŽê³ ì¢
í©ì ìŒë¡ ìŽíŽë³Œ ì ììë€ë ìì륌 ê°ëë€
The profile analysis for private tutoring expenses of undergraduate and graduate students using the youth panel data collected by KEIS
ìŽ ì°êµ¬ë íêµê³ ì©ì 볎ìì ì²ë
íšë 2007ë
(1ì°šë
ë)ë¶í° 2010ë
(4ì°šë
ë)ê¹ì§ì ìë£ë¥Œ ìŽì©íì¬ ëí (ì)ìì ì¬êµì¡ ì€í륌 ë¶ìí ê²ìŽë€. ì°êµ¬ 결곌, ëí(ì)ì ì€ íì ê³ ì ë± ìíì€ë¹ë¥Œ íê±°ë ììŽê³µë¶ ë± ì·šì
ì ìí ì¬êµì¡ì ë°ì볞 겜íìŽ ìë€ê³ ìëµí ë¹ìšì ìµí 14.5%(2010ë
)ìì ìµê³ 22.6%(2007ë
) ì ì€ìŽë©°, ì¬êµì¡ì ë°ëë€ê³ ìëµí ëí(ì)ìì 1ìžë¹ ì íê· ìŽì¬êµì¡ë¹ë ìµí 25.2ë§ ì(2008ë
)ìì ìµê³ 28.2ë§ ì(2007ë
) ìì€ìž ê²ìŒë¡ ëíë¬ë€. ììžë¬, ìíì€ë¹ ì¬êµì¡ì ë°ëë€ê³ ìëµí ëí(ì)ìì 50% ì ëê° êµê°êž°ì ì격, ìžë¬Žì¬, íê³ì¬ ë±ì ì 묞ì격ìíì ì€ë¹íêž° ìí ì¬êµì¡ì ë°ê³ ìê³ , ì·šì
ì¬êµì¡ì ë° ëë€ê³ ìëµí ëí(ì)ìì 50% ì ëê° TOEIC, TOEFL, TEPS ë±ì ììŽìíì ìí ì¬êµì¡ì ë°ê³ ìë ê²ìŒë¡ ëíë¬ë€. ìŽë¬í 결곌ë ëí(ì)ììì êµì¡ ëŽì©ìŽ ìíì€ë¹ì ì·šì
ì€ë¹ë¥Œ ìí êµì¡ ëŽì©ê³Œì ì°ê³ë¥Œ ëì± ê°íí íìê° ììì ìì¬íë€. ííž, ëí(ì)ìì ì°ëë³ ì¬êµì¡ë¹ ì§ì¶ íšíŽì íìžíêž° ìíŽ 2007ë
ë ë¶í° 2010ë
ëê¹ì§ ê° ì°ëë³ë¡ ëí(ì)ìì ì¬êµì¡ ì íë³ í¡ëš íë¡íìŒì ë¶ìâ€ì ìíììŒë©°, ëíìì 1í ë
ë¶í° 4íë
ê¹ì§ì ì¬êµì¡ ì§ì¶ ë¹ì©ì ë³í íšíŽì íìžíêž° ìíŽ ì¢
ëš íë¡íìŒì ë¶ìâ€ì ìíìë€.
This study analyzed the status of a private tutoring for college students using the Youth Panel data from 2007 (the first year survey) to 2010 (the fourth year survey) collected by Korea Employment Information Service (KEIS). On the basis of 3,045 undergraduate and graduate students who was responded to the first year survey, 2,514 of the second year, 2,384 students of the third year, and 2,407 of the forth year response data were analyzed. As a result, from 14.5% in 2010 to 22.6% in 2007 of respondents were experienced private tutoring to prepare for the examination or to get a job. Moreover, total average monthly tutoring expenses were from 252,000 won to 282,000 won per student who was experienced private tutoring. In addition, about 50% of undergraduate and graduate students who spent private tutoring expenses to prepare for the examination were preparing examination for national and professional qualifications. About 50% of undergraduate and graduate students who spent private tutoring expenses to get a job were taking private tutoring for English tests. On the other hand, profiles for each year were analyzed in order to identify annual spending patterns for private tutoring types. Longitudinal-profile analyses were also conducted to check the patterns of changes from the first year to the forth year