Intravenous sustained-release nifedipine ameliorates nonalcoholic fatty liver disease by restoring autophagic clearance

Lee, Solji,Han, Daewon,Kang, Hyun-Goo,Jeong, Su Jin,Jo, Jae-Eun,Shin, Jongdae,Kim, Do Kyung,Park, Hwan-Woo Elsevier 2019 Biomaterials Vol.197 No.-

<P><B>Abstract</B></P> <P>Obesity and overweight, the most serious health problems, are associated with chronic metabolic complications such as type 2 diabetes, insulin resistance, and nonalcoholic fatty liver disease (NAFLD). However, current pharmacological therapies for obesity are challenged by potential side effects, low effectiveness, and low aqueous solubility, which limit their clinical application. Here, we develop nifedipine-loaded nanoparticles (NFD-NPs) that alleviate obesity-related metabolic dysfunction to be used as instruments for translational medicine. Nanoparticles (NPs) composed of poly (lactic-co-glycolic acid) (PLGA) not only enhance water solubility of hydrophobic nifedipine (NFD), a calcium channel blocker, without modifying the chemical structure of NFD for intravenous administration, but also allow prolonged release of NFD <I>in vivo</I>. NFD-NPs do not show cytotoxicity and reduce palmitate-induced protein inclusions and endoplasmic reticulum stress in human hepatoma HepG2 cells. Importantly, tail-vein injection of NFD-NPs into diet-induced obese mice results in sustained retention of NFD-NPs in the liver and suppression of metabolic derangements associated with NAFLD by enhancing autophagic clearance through Ca2+/calmodulin-dependent kinase II (CaMKII) phosphorylation, consequently decreasing diet-induced insulin resistance and improving glucose tolerance. Our findings offer new clinical tools for NP-mediated pharmaceutical strategies to treat NAFLD and its related metabolic dysfunction.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

실내유출모델과 액상누출 풀 형성 모델 유무에 따른 확산범위 비교

최솔지(Solji Choi),신서린(Seolin Shin),허창환(Changhwan Huh),한종훈(Chonghun Han) 한국가스학회 2016 한국가스학회 학술대회논문집 Vol.2016 No.11

Surface Enhanced Raman Scattering on Non‐SERS Active Substrates and In Situ Electrochemical Study based on a Single Gold Microshell

Kim, Solji,Piao, Lilin,Han, Donghoon,Kim, Beom Jin,Chung, Taek Dong WILEY‐VCH Verlag 2013 ADVANCED MATERIALS Vol.25 No.14

<P><B>A single gold microshell, which was elaborately fabricated to carry numerous hot spots on its own surface</B>, enabled the acquisition of the SERS spectra from the molecules on non‐SERS active substrates such as Si/SiO<SUB>2</SUB>, ITO, and glass. A self‐assembled monolayer of 11‐mercaptoundecanols on the gold microshell offered an easy and reliable way to electrically insulate from the underlying flat Pt electrode and accomplish in situ monitoring the electrochemical reaction with minimal interference.</P>

Prediction of Postoperative Lung Function in Lung Cancer Patients Using Machine Learning Models

( Oh Beom Kwon ),( Solji Han ),( Hwa Young Lee ),( Hye Seon Kang ),( Sung Kyoung Kim ),( Ju Sang Kim ),( Chan Kwon Park ),( Sang Haak Lee ),( Seung Joon Kim ),( Jin Woo Kim ),( Chang Dong Yeo ) 대한결핵 및 호흡기학회 2023 Tuberculosis and Respiratory Diseases Vol.86 No.3

Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R² and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R² value was 0.27 and in set II, LightGBM was the best model with the highest R² value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R² value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.

Comparison of clinical characteristics between never-smokers and ever-smokers in female lung cancer patents: Evaluation of Korean Central Cancer Registry Data

( Jeong Uk Lim ),( Chan Kwon Park ),( Solji Han ),( Chang Min Choi ),( Chi Young Jung ),( Deog Gon Cho ),( Jae Hyun Jeon ),( Jeong Eun Lee ),( Jin Seok Ahn ),( Yeongdae Kim ),( Yoo-duk Choi ),( Yang-g 대한결핵 및 호흡기학회 2019 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.127 No.-

Purpose: The aim of this study was to compare clinical characteristics and prognosis between never and ever-smokers in female patients with lung cancer using nationwide registry in Korea. Materials and Methods: The Korean Association for Lung Cancer developed a registry in cooperation with the Korean Central Cancer Registry, and surveyed about 10% of lung cancer cases. For this first survey of cases diagnosed in 2014, cases were selected through a systematic sampling method. Results: Total of 2,621 lung cancer patients were surveyed and 744 female lung cancer patients were selected. After excluding 8 patients without data on smoking history, 736 patients were evaluated in this study. Among them, 644 (87.5%) were never-smokers, and 92 (12.5%) were ever-smokers. Median survival was compared between the two groups: median survival was not reached for the never smoker group, while it was 14.9 months for the ever-smoker group (P<0.001). During the study period, there were 635 non-small cell lung cancer (NSCLC), and 52 small cell lung cancer (SCLC). Among 635 NSCLC patients, 569 patients were never-smokers and 66 patients were ever-smokers. The ever smoker NSCLC group had significantly lower proportion of stage I patients and EGFR mutation when compared to the never-smokers (27.3% vs 41.7%, P=0.004, and 34.2% vs 50.3%, P=0.001, respectively). Among 469 patients with NSCLC, epidermal growth factor receptor (EGFR) mutation group (n=230) had higher proportion of clinical stage I (40.4% vs 29.1%, P=0.03), and patients who received targeted therapy as 1st line treatment (30.7% vs 1.8%, P<0.001) than wild-type group (n=239). From multivariable analysis for survival in 269 stage IV NSCLC patients, receiving only supportive care, and EGFR wild-type were significant predictors for shorter survival. Conclusion: From this nationwide cancer registry data, majority of female lung cancer patients were never-smokers, and showed different clinical characteristics and prognosis compared to ever-smoker patients.

탱크의 액상 누출량 정확도가 확산에 미치는 영향에 관한 연구

신서린(Seolin Shin),허창환(Changhwan Huh),최솔지(Solji Choi),이용석(Yongseok Lee),조재현(Jae Hyun Cho),한종훈(Chonghun Han) 한국가스학회 2016 한국가스학회 학술대회논문집 Vol.2016 No.6

CO₂ 농도 및 기온 상승에 대한 현사시나무의 광합성 반응

이솔지,오창영,한심희,김기우,김판기,Lee, Solji,Oh, Chang-Young,Han, Sim-Hee,Kim, Ki Woo,Kim, Pan-Gi 한국농림기상학회 2014 한국농림기상학회지 Vol.16 No.1

지구온난화와 같은 기후변화에 적응력이 높은 조림수종을 탐색하는 연구의 일환으로 $CO_2$농도 및 기온상승이 현사시나무의 광합성생리에 미치는 영향을 조사하였다. 그 결과 현사시나무는 $CO_2$농도 및 기온 상승에 의해서 줄기의 신장생장이 억제되고 광합성 능력이 저하되었다. 그리고 광합성능력과 관련된 색소(엽록소a, b, 카로티노이드)의 함량이 감소하였다. 특히 탄소고정계의 활성과 관련된 엽록소a의 감소가 현저하게 나타났다. 그리고 광-광합성곡선과 A-Ci곡선에서 광화학계의 활성을 나타내는 순양자수율이 7%, 전자전달속도가 14% 감소하고, 탄소고정계의 활성을 나타내는 탄소고정효율이 52%, 재인산화속도가 24% 감소하였다. 이러한 결과로 $CO_2$농도 및 기온 상승에 의한 현사시나무의 광합성능력 저하는 광화학계 및 탄소고정계의 활성저하에 기인하나, 탄소고정계의 활성저하가 더 크게 작용하였음을 알 수 있다. This study was conducted to investigate the photosynthetic characters of Populus alba${\times}$glandulosa cuttings in response to elevated $CO_2$ concentration and air temperature for selecting tree species adaptive to climate change. The cuttings were grown in environment controlled growth chambers with two combinations of $CO_2$ concentration and air temperature conditions: (i) $22^{\circ}C$ + $CO_2$ 380 ${\mu}mol$ $mol^{-1}$ (control) and (ii) $27^{\circ}C$ + $CO_2$ 770 ${\mu}mol$ $mol^{-1}$ (elevated) for almost three months. The cuttings under the elevated treatment showed reduced tree height and photosynthetic pigment contents such as chlorophyll and carotenoid. In particular, the elevated treatment resulted in a marked reduction in the chlorophyll a closely associated with $CO_2$ fixative reaction system. Different levels of reduction in photosynthetic characters were found under the elevated treatment. A decrease was noted in photochemical reaction system parameters: net apparent quantum yield (7%) and photosynthetic electron transport rate (14%). Moreover, a significant reduction was obvious in $CO_2$ fixative reaction system parameters: carboxylation efficiency (52%) and ribulose-1,5-bisphosphate(RuBP) regeneration rate (24%). These results suggest that the low level of photosynthetic capacity may be attributed to the decreased $CO_2$ fixative reaction system rather than photochemical reaction system.

기후변화 대응 산림의 장기 기후변화 연구시설

서동진 ( Dong-jin Seo ),김현철 ( Hyun-chul Kim ),이현석 ( Hyun Seok Lee ),이솔지 ( Solji Lee ),이위영 ( Wi-yeong Lee ),한심희 ( Sim-hee Han ),강준원 ( Jun Won Kang ) 한국농림기상학회 2016 한국농림기상학회지 Vol.18 No.4

전체 온실가스 배출량의 약 72%를 차지하는 이산화탄소(CO₂)는 지구온난화를 야기하는 대표적인 온실가스로 분류되어 있다. IPCC의 제5차 기후변화 종합평가 보고서(2014)에 의하면, 지난 100년간 지구 대기의 CO₂는 약 35% 증가했으며 지구의 온난화는 최근 30년간 심화되는 것으로 나타났다. 이에 따라 지구 온난화에 따른 기후변화, 기상이변으로 산림식생대의 이동과 식물계절 변화가 유발되고 있다. 산림은 교토의정서에서 인정한 유일한 온실가스 흡수원으로서 보전 및 증진 필요성이 있으며 기후변화에 대한 수목 반응의 연구는 미래의 산림생태계 변화를 예측하는데 필수불가결한 요소이다. 따라서 장기 기후변화 연구시설을 이용한 수목의 생리·생태적 반응 연구와 실제 산지에서 이루어지는 장기 모니터링 연구를 결부하여 이용한다면 기후변화로 인한 미래 산림생태계의 변화를 예측하고 대응하는데 크게 기여할 것이다. Carbon dioxide (CO₂) accounts for about 72% of the total greenhouse gas emissions. It is also widely known as a major cause of global warming. According to the IPCC`s fifth evaluation report, the growth rate of atmospheric CO₂ has increased by 35% for the last 100 years and global warming is occurring much more rapidly than expected since 1990s. As a result of climate change, global warming is increasing the frequency and severity of extreme weather events around the world, which has changed forest vegetation zone and vegetation phenology. The Kyoto Protocol recognizes the importance of forests and refers to the conservation and enhancement of forests as sinks and reservoirs of greenhouse gases. In this regard, studies of tree responses to climate change are indispensable for predicting changes in the forest ecosystems in the future. Therefore, studies using long-term climate change research facilities, associated with long-term ecological research (LTER) in the fields, will make a considerable contribution to predict and approach the changes in the future.