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Cancer risk based on alcohol consumption levels: a comprehensive systematic review and meta-analysis
Seunghee Jun(Seunghee Jun),Hyunjin Park(Hyunjin Park),Ui-Jeong Kim(Ui-Jeong Kim),Eun Jeong Choi(Eun Jeong Choi),Hye Ah Lee(Hye Ah Lee),Bomi Park(Bomi Park),Soon Young Lee(Soon Young Lee),Sun Ha Jee(Su 한국역학회 2023 Epidemiology and Health Vol.45 No.-
OBJECTIVES: Alcohol consumption is a well-established risk factor for cancer. Despite extensive research into the relationship between alcohol consumption and cancer risk, the effect of light alcohol consumption on cancer risk remains a topic of debate. To contribute to this discourse, we conducted a comprehensive systematic review and meta-analysis. METHODS: Our systematic review aimed to investigate the associations between different levels of alcohol consumption and the risk of several cancer types. We focused on analyzing prospective associations using data from 139 cohort studies. Among them, 106 studies were included in the meta-analysis after a quantitative synthesis. RESULTS: Our analysis did not find a significant association between light alcohol consumption and all-cause cancer risk (relative risk, 1.02; 95% confidence interval, 0.99 to 1.04), but we observed a dose-response relationship. Light alcohol consumption was significantly associated with higher risks of esophageal, colorectal, and breast cancers. Light to moderate drinking was associated with elevated risks of esophageal, colorectal, laryngeal, and breast cancers. Heavy drinking was also found to contribute to the risk of stomach, liver, pancreas, and prostate cancers, thereby increasing the risk of almost all types of cancer. Additionally, females generally had lower cancer risks compared to males. CONCLUSIONS: Our findings highlight that cancer risks extend beyond heavy alcohol consumption to include light alcohol consumption as well. These findings suggest that there is no safe level of alcohol consumption associated with cancer risk. Our results underscore the importance of public health interventions addressing alcohol consumption to mitigate cancer risks.
Seunghee Han,Jaeho Lee,Si Hyeock Lee 한국응용곤충학회 2016 한국응용곤충학회 학술대회논문집 Vol.2016 No.10
Colony collapse disorder (CCD), a phenomenon of honeybees disappearance, has been reported since 2006. Chronic exposure to neonicotinoid insecticides, particularly imidacloprid, has been suggested to impair forager’s ability for foraging and be a main cause of CCD. Recently, it has been reported that imidacloprid induces insulin resistance in animal cell line by blocking glucose uptake. Similarly to human insulin, insulin-like peptide (ILP) of insects is involved in maintaining blood glucose contents in hemolymph by regulating the concentration of trehalose and glycogen. Therefore, we have hypothesized that sublethal concentration of neonicotinoid may affect the metabolic pathway of honey bees as well. We investigated the transcription levels of the genes involved in the insulin/insulin-like signaling (IIS) pathway, such as AmILP and AmInR, following an acute or a chronic dietary exposure of sublethal concentrations of imidacloprid to foragers. In both experiments, honeybees showed increased expression levels of ILP and InR in a dose-dependent manner. Our results suggest that sublethal dose of imidacloprid likely upregulates IIS pathway, thereby rendering honey bees to become resistant to insulin.
Lee, Sangsik,Oh, Seunghee,Yang, Aerin,Kim, Jihyo,Sö,ll, Dieter,Lee, Daeyoup,Park, Hee‐,Sung WILEY‐VCH Verlag 2013 Angewandte Chemie Vol.125 No.22
<P><I><B>Einen selektiven Phosphoserin‐Einbau</B></I> beschreiben H.‐S. Park et al. in ihrer Zuschrift S. 5883 ff. Eine allgemeine Strategie für den Aufbau rekombinanter Histone mit ortsspezifischer Serinphosphorylierung wurde entwickelt, die auf der Modifizierung einer Phosphoseryl‐tRNA‐Synthetase (SepRS) und des Elongationsfaktors Tu (EF‐Tu) beruht. Die Methode dürfte die Erforschung der Histonphosphorylierung und kreuzregulatorischer Mechanismen vereinfachen.</P>
Lee Seunghee,Kim Hyun Woo,임진오,Kim Seok Ki,Kim Yong Tae,Chang Hyunju,Ko Tae-Wook,Lee Jonggul,Hyon YunKyong 한국물리학회 2020 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.77 No.8
Molecular dynamics (MD) simulations are useful in understanding the interaction between solid materials and molecules. However, performing MD simulations is possible only when interatomic potentials are available and constructing such interatomic potentials usually requires additional computational work. Recently, generating interatomic potentials was shown to be much easier when machine learning (ML) algorithms were used. In addition, ML algorithms require new descriptors for improved performance. Here, we present an ML approach with several categories of atomic descriptors to predict the parameters necessary for MD simulations, such as the potential energies and the atomic forces. We propose several atomic descriptors based on structural information and find that better descriptors can be generated from eXtreme gradient boosting (XGBoost). Moreover, we observe fewer descriptors that perform better in predicting the potential energies and the forces during methane activation processes on a catalytic Pt(111) surface. These results were consistently observed in two different ML algorithms: fully-connected neural network (FNN) and XGBoost. Taking into account the advantages of FNN and XGBoost, we propose an efficient ML model for estimating potential energies. Our findings will be helpful in developing new ML potentials for long-time MD simulations.