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Background: Atrial fibrillation (AF) is a well-known risk factor for stroke. Predicting the risk is important to prevent the first and secondary attacks of cerebrovascular diseases by determining early treatment. This study aimed to predict the ischemic stroke in AF patients based on the massive and complex Korean National Health Insurance (KNHIS) data through a machine learning approach. Methods: We extracted 65-dimensional features, including demographics, health examination, and medical history information, of 754,949 patients with AF from KNHIS. Logistic regression was used to determine whether the extracted features had a statistically significant association with ischemic stroke occurrence. Then, we constructed the ischemic stroke prediction model using an attention-based deep neural network. The extracted features were used as input, and the occurrence of ischemic stroke after the diagnosis of AF was the output used to train the model. Results: We found 48 features significantly associated with ischemic stroke occurrence through regression analysis (p-value < 0.001). When the proposed deep learning model was applied to 150,989 AF patients, it was confirmed that the occurrence ischemic stroke was predicted to be higher AUROC (AUROC = 0.727 ± 0.003) compared to CHA2DS2-VASc score (AUROC = 0.651 ± 0.007) and other machine learning methods. Conclusions: As part of preventive medicine, this study could help AF patients prepare for ischemic stroke prevention based on predicted stoke associated features and risk scores.

Purpose The National Health Insurance Service (NHIS)-Senior was set up to provide high-quality longitudinal data that can be used to explore various aspects of changes in the socio-economical and health status of older adults, to predict risk factors and to investigate their health outcomes.Participants The NHIS-Senior cohort, a Korean nationwide retrospective administrative data cohort, is composed of older adults aged 60 years and over in 2002. It consists of 558 147 people selected by 10% simple random sampling method from a total of 5.5 million subjects aged 60+ in the National Health Information Database. The cohort was followed up through 2015 for all subjects, except for those who were deceased.Findings to date The healthcare utilisation and admission rates were the highest for acute upper respiratory infections and influenza (75.2%). The age-standardised (defined with reference to the world standard population) mortality rate for 10 years (through 2012) was 4333 per 100 000 person-years. Malignant neoplasms were the most common cause of death in both sexes (1032.1 per 100 000 person-years for men, 376.7 per 100 000 person-years for women). A total of 34 483 individuals applied for long-term care service in 2008, of whom 17.9% were assessed as grade 1, meaning that they were completely dependent on the help of another person to live daily life.Future plans The data are provided for the purposes of policy and academic research under the Act on Promotion of the Provision and Use of Public Data in Korea. The NHIS-Senior cohort data are only available for Korean researchers at the moment, but it is possible for researchers outside the country to gain access to the data by conducting a joint study with a Korean researcher. The cohort will be maintained and continuously updated by the NHIS.

Introduction: Many studies in stem cell biology have demonstrated that dental pulp stem cells (DPSC) may be highly proliferative and capable of pluripotent differentiation into many different tissue types. Recent advances in stem cell research have outlined methods for directing in vitro or in vivo growth, viability, and proliferation, as well as differentiation of DPSC—although much remains to be discovered. Based upon this information, the primary objective of this study was to understand the functional biomaterials needed to more effectively direct DPSC viability, growth, and proliferation. Methods: Using an approved protocol, previously collected and isolated samples of DPSC from an existing repository were used. Previously established stem cell biomarkers (Sox-2, Oct-4, NANOG) from each isolate were correlated with their proliferation rates or doubling times to categorize them into rapid, intermediate, or slow-dividing multipotent DPSC. Growth factors and other functional dental biomaterials were subsequently tested to evaluate DPSC responses in proliferation, viability, and morphology. Results: Differential responses were observed among DPSC isolates to growth factors, including vascular endothelial growth factor (VEGF) and bone morphogenic protein (BMP-2), and functional biomaterials such as mineralized trioxide aggregates (MTA). The responsiveness of DPSC isolates did not correlate with any single factor but rather with a combination of proliferation rate and biomarker expression. Conclusions: These data strongly suggest that some, but not all, DPSC isolates are capable of a robust and significant in vitro response to differentiation stimuli, although this response is not universal. Although some biomarkers and phenotypes that distinguish and characterize these DPSC isolates may facilitate the ability to predict growth, viability, and differentiation potential, more research is needed to determine the other intrinsic and extrinsic factors that may contribute to and modulate these DPSC responses to these functional biomaterials for biotechnology and bioengineering applications.

Purpose The National Health Insurance Service (NHIS)- Senior was set up to provide high-quality longitudinal data that can be used to explore various aspects of changes in the socio-economical and health status of older adults, to predict risk factors and to investigate their health outcomes. Participants The NHIS-Senior cohort, a Korean nationwide retrospective administrative data cohort, is composed of older adults aged 60 years and over in 2002. It consists of 558 147 people selected by 10% simple random sampling method from a total of 5.5 million subjects aged 60+ in the National Health Information Database. The cohort was followed up through 2015 for all subjects, except for those who were deceased. Findings to date The healthcare utilisation and admission rates were the highest for acute upper respiratory infections and influenza (75.2%). The age-standardised (defined with reference to the world standard population) mortality rate for 10 years (through 2012) was 4333 per 100 000 person-years. Malignant neoplasms were the most common cause of death in both sexes (1032.1 per 100 000 person-years for men, 376.7 per 100 000 personyears for women). A total of 34 483 individuals applied for long-term care service in 2008, of whom 17.9% were assessed as grade 1, meaning that they were completely dependent on the help of another person to live daily life. Future plans The data are provided for the purposes of policy and academic research under the Act on Promotion of the Provision and Use of Public Data in Korea. The NHIS-Senior cohort data are only available for Korean researchers at the moment, but it is possible for researchers outside the country to gain access to the data by conducting a joint study with a Korean researcher. The cohort will be maintained and continuously updated by the NHIS. [ABSTRACT FROM AUTHOR]

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning–Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

Since the Fukushima Daiichi nuclear disaster, concern and worry about multiunit accidents have been increasing. Korea has a higher urgency to evaluate its site risk because its number of nuclear power plants (NPPs) and population density are higher than those in other countries. Since the 1980s, technical documents have been published on multiunit probabilistic safety assessment (PSA), but the Fukushima accident accelerated research on multiunit PSA. It is therefore necessary to summarize the present situation and draw implications for further research. This article reviews journal and conference papers on multiunit or site risk evaluation published between 2011 and 2016. The contents of the reviewed literature are classified as research status, initiators, and methodologies representing dependencies, and the insights and conclusions are consolidated. As of 2017, the regulatory authority and nuclear power utility have launched a full-scale project to assess multiunit risk in Korea. This article provides comprehensive reference materials on the necessary enabling technology for subsequent studies of multiunit or site risk assessment. Keywords: Multiunit, Nuclear Power Plant, Probabilistic Safety Assessment, Site Risk Assessment

Because the scope of risk assessments at nuclear power plants (NPPs) is being extended both spatially and temporally, conventional, or static fault trees might not be able to express failure mechanisms, or they could be unnecessarily conservative in their expression. Therefore, realistic assessment techniques are needed to adequately capture accident scenarios. In multi-unit probabilistic safety assessment (PSA), fault trees naturally become more complex as the number of units increases. In particular, when considering a shared facility between units of the electric power system (EPS), static fault trees (SFTs) that prioritize a specific unit are limited in implementing interactions between units. However, dynamic fault trees (DFTs) can be available without this limitation by using dynamic gates. Therefore, this study implements SFTs and DFTs for an EPS of two virtual NPPs and compares their results. In addition, to demonstrate the dynamic characteristics of the shared facilities, a station blackout (SBO), which causes the power system to lose its function, is assumed—especially with an inter-unit shared facility, AAC DG (Alternate AC Diesel Generator). To properly model the dynamic characteristics of the shared EPS in DFTs, a modified dynamic gate and algorithm are introduced, and a Monte Carlo simulation is adopted to quantify the DFT models. Through the analysis of the DFT, it is possible to confirm the actual connection priority of AAC DG according to the situation of units in a site. In addition, it is confirmed that some conservative results presented by the SFT can be evaluated from a more realistic perspective by reflecting this.