3,4-다이메틸-5-바이닐싸이아졸리움 고분자 촉매를 이용한 반응들

학위논문 (석사)-- 서울대학교 대학원 : 화학부 무기화학전공, 2015. 8. 정영근.Poly(3,4-dimethyl-5-vinylthiazolium)s were synthesized from 3,4-dimethyl-5-vinylthiazole via free radical polymerization. It examined as polymer precatalysts in the presence of DBU for the thioesterification of aldehydes with thiols and for the thiol-ene click reaction of styrene with thiols. The poly(5-vinylthiazolium)s had excellent catalytic activity and could be reused more then three times without loss of activity.Contents Abstract ……………………………………………………………………………………………..…3 Introduction …....…………………………………………………………………………………..4 Results and Discussion...……………………………………………………………….……6 Conclusion ………………………………………………………………………………………….14 Experimental Section ………………………………………………………………….…..15 References …………………………………………………………………………………………42 국문초록 ……………………………………………………………………………………………..45Maste

Prevalence and risk factors of perforation after endoscopic submucosal dissection for esophageal neoplasm

AIM: To investigate prevalence and risk factors of esophageal perforation and which anesthesia is appropriate associated with esophageal endoscopic submucosal dissection (ESD) for esophageal neoplasm. Methods: We retrospectively analyzed 507 esophageal ESD lesions from October 2007 to February 2019 in Asan Medical Center. Binary regression logistic analysis and multivariate analysis were used to investigate the risk factors of perforation after esophageal ESD. Additionally, we compared general anesthesia (GA) and under conscious sedation (UCS) to find out perforation occurrence by anesthesia method since November 2010 when GA mainly conducted. 1:6 matching was performed based on observed covariate (tumor long axis, invasion depth, circumference) thought to be affect perforation. Outcome analysis was performed using GEE (Generalized estimating equation) or Linear mixed model that accounts for the clustering of matched pairs. Results: Esophageal perforation occurred in 24 of 507 cases (4.7 %) after esophageal ESD. UCS (OR= 3.861, 95% CI, 1.429- 10.42, P=0.008) and larger circumference (OR=3.465, 95% CI, 2.046- 5.955, P<0.001) were associated with esophageal perforation after ESD in total period investigation. Age (OR=1.007, 95% CI, 0.690- 1.056, P=0.773), sex (OR=1.687, 95% CI, 0.221- 12.88, P=0.614), underlying disease (OR=0.599, 95% CI, 0.264- 1.362, P=0.222), invasion depth (OR=1.333, 95% CI, 0.441- 4.023, P=0.61), histology (OR=6.624, 95% CI, 0.884- 49.61, P=0.066), predominance (OR=1.541, 95% CI, 0.661- 3.588, P=0.316), longitudinal location (OR=1.033, 95% CI, 0.946- 1.129, P=0.469), and direction (OR=0.434, 95% CI, 0.168- 1.120, P=0.085) were not significant. However, there was no significant statistical difference in perforation (OR=5.952, 95% CI, 0.365- 100.0, P=0.2106) and other complications (OR=0.856, 95% CI, 0.097- 7.566, P=0.889) when compared with GA and UCS after GA was mainly used. Conclusions: Larger circumference and UCS were considered as risk factors of perforation after esophageal ESD, but there was no significant difference of perforation by anesthesia method (OR=5.952, 95% CI, 0.365- 100.0, P=0.2106) when circumference was less than 25 %. Therefore, it is reasonable to choose methods of anesthesia by circumference of esophageal neoplasm. Keywords: Esophageal neoplasm; Endoscopic submucosal dissection; Risk factors; Perforation; AnesthesiaMaste

멀티 태스크 학습을 위한 해석 가능한 예측 모형 개발

DoctorMTL (Multi-task Learning)은 각 예측 모델을 독립적으로 학습하지 않고 동시에 학습하는 것을 말합니다. 예측 모델의 해석가능성은 실질적 중요성 때문에 주목을 받고 있습니다. 이 연구의 목표는 MTL을 위한 해석 가능한 예측 모델을 제안하는 것입니다. 구체적으로, 1) 동시 학습을 기반으로 과제 관련성을 활용하여 예측 모델의 일반화 성능을 향상하고, 2) 투명 모델을 추정하여 예측 모델의 해석성을 달성하고 3) 모수에 희소성을 부과하여 유의미한 변수를 선택하고 예측 모델의 해석성을 향상시킵니다. 우리는 선형 방법, 변수 상호 작용 모델 및 모델 트리를 포함하여 세 가지 투명한 예측 모델을 제안합니다. 선형 모델은 변수 선택과 작업간에 겹치는 그룹 구조를 학습을 동시에 수행합니다. 선형 모델은 낮은 행렬 분해를 사용하고 여기에 따라 발생하는 상관관계를 활용하면서 두 행렬에 희소성을 부과합니다. 우리는 결과적인 다중 볼록 목적 함수를 최소화하기 위해 좌표 최소화 및 근위 선형을 기반으로 두가지 최적화 절차를 제안합니다. 변수 상호 작용 모델은 희소 텐서 분해를 기반으로 중요한 상호 작용 및 선형 항을 선택합니다. 우리는 텐서 분해와 대칭 트릭을 사용하여 예측 모델간에 모수를 공유하고 목표 함수를 최소화하는 새로운 초기화 절차를 제안합니다. 모델 트리는 리프 노드에서 선형 모델을 추정 할 때 예측모형간 관련성을 활용합니다. 우리는 다중 출력 선형 모델을 적용하여 리프 노드에서 선형 모델을 추정하고 후보 분할 무시를 선택하여 새로운 2 단계 분할 절차를 제안합니다. 또한 제안 된 방법을 산업 프로젝트에 적용하고 그 효과를 입증했습니다.Multi-task Learning (MTL) refers to simultaneously learning of prediction models of related tasks rather than learning each prediction model independently. Interpretability of prediction models has gained attention because of its practical importance. The goal of this research is to propose interpretable prediction models for MTL. In details, 1) we improve the generalization performance of prediction models by leveraging task relatedness based on simultaneous learning, 2) we achieve interpretability of prediction models by estimating transparent models, and 3) significant variables are selected to enhance the interpretability of prediction models based on imposing sparsity to parameters. We propose three transparent prediction models including a linear method, a variable interaction model, and a model tree. The linear model aims to simultaneously perform variable selection and learns an overlapping group structure among tasks. The linear model uses a low-rank matrix factorization and imposes sparsitities to the sum-matrices while exploiting possible correlation. We propose two alternating optimization procedures based on coordinate minimization and proximal linear to minimize the resulting multi-convex objective function. The variable interaction model selects significant interaction and linear terms based on a sparse tensor decomposition. We use a low-rank tensor decomposition and a symmetrization trick to share parameter among interaction models and provide a novel initialization procedure to minimize the resulting objective function. The model tree exploits task relatedness in estimating linear models at leaf nodes. We apply a multi-output linear model to estimate linear models at leaf nodes and propose a novel two-stage splitting procedure by selecting promising candidate splits. Furthermore, we applied the proposed methods to industrial projects and demonstrated their effectiveness

Semi-Markov process를 이용한 노인장기요양보험의 적정유효기간 산정모형

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Allogeneic Umbilical Cord Blood-Derived Mesenchymal Stem Cell Implantation Versus Microfracture for Large, Full-Thickness Cartilage Defects in Older Patients: A Multicenter Randomized Clinical Trial and Extended 5-Year Clinical Follow-up

Background: There is currently no optimal method for cartilage restoration in large, full-thickness cartilage defects in older patients. Purpose: To determine whether implantation of a composite of allogeneic umbilical cord blood-derived mesenchymal stem cells and 4% hyaluronate (UCB-MSC-HA) will result in reliable cartilage restoration in patients with large, full-thickness cartilage defects and whether any clinical improvements can be maintained up to 5 years postoperatively. Study Design: Randomized controlled trial; Level of evidence, 1. Methods: A randomized controlled phase 3 clinical trial was conducted for 48 weeks, and the participants then underwent extended 5-year observational follow-up. Enrolled were patients with large, full-thickness cartilage defects (International Cartilage Repair Society [ICRS] grade 4) in a single compartment of the knee joint, as confirmed by arthroscopy. The defect was treated either with UCB-MSC-HA implantation through mini-arthrotomy or with microfracture. The primary outcome was proportion of participants who improved by >= 1 grade on the ICRS Macroscopic Cartilage Repair Assessment (blinded evaluation) at 48-week arthroscopy. Secondary outcomes included histologic assessment; changes in pain visual analog scale (VAS) score, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and International Knee Documentation Committee (IKDC) score from baseline; and adverse events. Results: Among 114 randomized participants (mean age, 55.9 years; 67% female; body mass index, 26.2 kg/m(2)), 89 completed the phase 3 clinical trial and 73 were enrolled in the 5-year follow-up study. The mean defect size was 4.9 cm(2) in the UCB-MSC-HA group and 4.0 cm(2) in the microfracture group (P = .051). At 48 weeks, improvement by >= 1 ICRS grade was seen in 97.7% of the UCB-MSC-HA group versus 71.7% of the microfracture group (P = .001); the overall histologic assessment score was also superior in the UCB-MSC-HA group (P = .036). Improvement in VAS pain, WOMAC, and IKDC scores were not significantly different between the groups at 48 weeks, however the clinical results were significantly better in the UCB-MSC-HA group at 3- to 5-year follow-up (P < .05). There were no differences between the groups in adverse events. Conclusion: In older patients with symptomatic, large, full-thickness cartilage defects with or without osteoarthritis, UCB-MSC-HA implantation resulted in improved cartilage grade at second-look arthroscopy and provided more improvement in pain and function up to 5 years compared with microfracture. Registration: NCT01041001, NCT01626677 (ClinicalTrials.gov identifier)