Fabry disease is an X-linked lysosomal storage disorder caused by GLA mutations, leading to a deficiency in α-Galactosidase A activity and subsequent accumulation of globotriaosylceramide (Gb3). This accumulation contributes to progressive multiorgan dysfunction, with cardiovascular complications, particularly endothelial dysfunction and left ventricular hypertrophy being major drivers of disease morbidity and mortality. Although enzyme replacement therapy is currently the standard treatment, its effectiveness is limited in addressing advanced cardiovascular pathology. To better understand Fabry-associated vascular and cardiac phenotypes, an isogenic human induced pluripotent stem cell (hiPSC) model in which GLA was knocked out was developed using CRISPR/ Cas9. GLA-knockout (GLA-KO) hiPSCs were differentiated into endothelial cells (ECs) and cardiomyocytes (CMs) to evaluate disease-relevant phenotypes in vitro . GLA-KO ECs exhibited normal morphology and differentiation capacity but showed markedly impaired tube formation, high expression of inflammatory genes ICAM1, VCAM1, and SELE, and increased mitochondrial and cytoplasmic reactive oxygen species levels. GLA-KO CMs demonstrated enlarged cell size and nuclear translocation of NFATC4, consistent with hypertrophic remodeling. Together, these findings recapitulate key features of Fabry vasculopathy and cardiomyopathy in a genetically defined, human-derived system. This platform enables direct investigation of Gb3-induced oxidative and inflammatory mechanisms and provides a valuable model for the preclinical evaluation of therapeutic strategies targeting the cardiovascular manifestations of Fabry disease.
In the present study, the effects of non-thermal plasma, corona discharge plasma jet (CDPJ) against foodborne disease bacteria (Escherichia coli O157:H7 ATCC 43894, Salmonella typhimurium ATCC 13311, Staphylococcus aureus ATCC 25923) were determined, and the inactivation patterns were modeled using GinaFiT software in Microsoft Excel. Among inactivation models studied, Weibull-tail model was chosen as the best fit model based on SSE, RMSE, and r 2 values. The initial decimal reduction times (δ) of E. coli O157:H7, S. aureus, and Sal. typhimurium were 6.36, 8.31, and 12.11 s respectively. The inactivation effect increased with the current strength and was highest at span length of 25 mm. After 120 s treatment of the CDPJ at 1.50 A with span length of 25 mm, E. coli O157:H7 was reduced by 5.26 log, S. aureus by 4.21 log, Sal. typhimurium by 2.89 log.
본 연구는 지속적으로 증가하고 있는 국내 쯔쯔가무시증 발병 분석에 적합한 회귀모형을 선정하고, 이에 영향을 미치는 공간 생태학적 요인을 분석하는 것을 목적으로 한다. 이를 통하여 향후 쯔쯔가무시증 방역사업 및 대상지 선정에 이론적 배경을 제시하고자 한다. 이 연구는 일반선형회귀모형, 공간오차모형, 아이겐벡터 공간필터링 모형 세 모형을 비교하였고, 이 중 아이겐벡터 공간필터링 모형이 가장 뛰어난 것으로 나타났다. 쯔쯔가무시증 발병 요인 분석 결과 가을 기온, 가을 강수량, 가을 습도,가을 NDVI, 논경작인구비율이 유의미한 변수로 나타났다. 한편 일반선형회귀모형의 상대적 중요도 분석 결과 논 경작 인구비율이결정계수 중 가장 큰 비중을 차지하여, 자연환경변수보다 인문환경이 쯔쯔가무시증 발병률에 더 큰 영향을 미치는 것으로 평가되었다.
본 연구에서는 질병 데이터를 활용한 사망률의 지도화에서 지역별 사망률의 변동성을 안정화할 수 있도록 하는 베이지언 기법을 적용하고, 기본적으로 활용되고 있는 SMR (Standardized mortality ratio)과 그 결과를 비교하였다. 우리나라 전국의 시군구 단위의 전립선암 사망자 수 데이터에 표준화와 베이지언 기법을 적용하고, 산출된 사망률을 지도화하여 기존에 없던 우리나라의 전립선암 사망률 지도를 질병 지도의 예시 자료로 작성하였다. 분석 결과, Bayesian 모델링 기법을 통해 계산된 위험비는 기존 SMR에 비해 좀 더 수렴된 형태의 안정적인 통계량을 가지는 것을 알 수 있었다. 국지적 Bayesian 기법은 이웃 지역들의 정보만을 반영하여 위험비를 평활화하기 때문에 본 연구에서 사용된 전역적 기법들과 비교할 때 평활화의 강도가 크지 않았다.
By means of the model competition, this research analyzed the factor of patient management, the factor of policy support, and the factor of medical treatment system. Concretely, the factor of policy support forms a positive effects on the factor of medical treatment system. Practically, well-established healthcare policy provide and facilitate the effective medical treatment system. of the hospital. And, in the effective medical treatment system, hospitals try to develop the patient management of the chronic disease. From the empirical research, this paper concluded that the factor of medical treatment system. mediated by the factor of policy support. Also, the factor of medical treatment system promotes the development of patient management in the chronic disease.