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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.
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>
A Comparative Review of Radiation-induced Cancer Risk Models
Lee, Seunghee,Kim, Juyoul,Han, Seokjung The Korean Association for Radiation Protection 2017 방사선방어학회지 Vol.42 No.2
Background: With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. Materials and Methods: A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. Results and Discussion: The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies.
( Seunghee Lee ),( Eiji Onchi ),( Hotei Ban ),( Kaihuan Wei ),( Han Zhang ),( Max Hanssen ),( Muneo Kitajima ) 한국감성과학회 2020 추계학술대회 Vol.2020 No.-
This study visualizes the results of a behavioral analysis experiment with college students as a group of subjects by combining psychological character trait testing and behavioral selection analysis. As the early stage of a research project for problem-solving behavior tracking and analysis, this study has explored the research direction for the research team through experimental results. The study uses cluster analysis to visually display the descriptive survey results of the participants. It also uses the Maudsley Personality Inventory to classify participants in two-dimensional factors to help the research team further grasp the Kansei performance of the participants.
Spike-inspired Deep Neural Network Design Using Binary Weight
Seunghee Lee,Kyukwang Kim,Jinki Kim,Yeeun Kim,Hyun Myung 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Recently, deep learning has achieved great results in many fields such as image classification. However, most general artificial neural networks with deep learning require graphics processing unit (GPUs) because of hard workload and it requires a large amount of power consumption. When we think about humans, we can do a lot of things without consuming a lot of power compared to computers or electric appliances. Human beings or organisms transmit and recognize information through signal transmission between neurons. This study aims to develop a novel deep neural network architecture which simulates the signaling system between biological neurons, unlike conventional neural networks. We propose a novel spike-inspired deep neural network structure with the spike-inspired block using binary weight motivated by spike’s on and off mechanism. We have also designed a modified DenseNet architecture consisting of spike-inspired blocks. Our proposed method was tested and validated with MNIST datasets. The obtained results show the potential of a spike-inspired deep neural network.