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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.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.We found 48 features significantly associated with ischemic stroke occurrence through regression analysis (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.

Atrial fibrillation (AF) is a well-known risk factor for stroke. Predicting the risk is important to prevent the first attack and re-attack of cerebrovascular diseases by determining the medication. Although several statistical methods have been developed to assess the stroke risk in AF patients, considerable improvement is needed in predictive performance. We propose a machine learning-based approach based on the massive and complex Korean National Health Insurance (KNHIS) data. We extracted 72-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 stroke occurrence. Then, we constructed the stroke risk prediction model based on a deep neural network. The extracted features were used as input, and the occurrence of stroke after the diagnosis of AF was the output used to train the model. When the proposed deep learning model was applied to 150,989 AF patients, it was confirmed that stroke risk was predicted with high accuracy, sensitivity, and specificity. As part of preventive medicine, this study could help AF patients prepare for stroke prevention based on predicted stoke associated feature and risk scores.

BACKGROUND 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 differentiation of DPSC - although much remains to be discovered. OBJECTIVE Based upon this information, the primary objective of this study was to understand the biology and biotechnology needed to more effectively direct DPSC differentiation. METHODS Previously collected and isolated samples of DPSC from an existing repository were used. Due to the use of previously collected, non-identifiable samples this protocol was granted exemption from Human Subjects review. 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 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 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 differentiation potential, more research is needed to determine the other intrinsic and extrinsic factors that may contribute to and modulate these DPSC responses for biotechnology and bioengineering applications. CLINICALTRIAL N/A (not applicable)

Importance Alopecia areata is associated with diverse systemic and psychiatric diseases. However, whether all-cause and cause-specific mortality in patients with alopecia areata differs from that of the general population remains unclear. Objective To investigate all-cause and cause-specific mortality risk in patients with alopecia areata. Design, Setting, and Participants Using the National Health Insurance Service database and National Death Registry of Korea, a retrospective cohort study of participants identified in 2006, with investigation of mortality until 2016, was carried out. Patients with alopecia areata with at least 3 documented visits to a dermatologist with an International Statistical Classification of Diseases (tenth revision) code of L63 during 2002 to 2006 were included. For comparison, 1:10 age- and sex-matched controls without documented visits with a code of L63 until 2016 were included. Exposures Patients with alopecia areata and controls without alopecia areata. Main Outcomes and Measures The study population was followed from January 1, 2007, for a period of 10 years to estimate all- and cause-specific mortality. Results The study comprised 73 107 patients with alopecia areata and 731 070 age- and sex-matched controls. Of these, 6023 were patients with alopecia totalis/universalis. No differences in all-cause mortality risk between the cohorts were found (HR, 0.97; 95% CI, 0.87-1.09). However, mortality associated with intentional self-harm/psychiatric diseases was greater in patients than in participants in the control group (HR, 1.21; 95% CI, 1.04-1.41). Adult patients aged 35 years or younger (HR, 1.68; 95% CI, 1.32-2.12) and those with alopecia totalis/universalis (HR, 1.85; 95% CI, 1.25-2.75) were particularly affected. Mortality associated with lung cancer was greater in patients with alopecia totalis/universalis (HR, 2.16; 95% CI, 1.41-3.33). However, mortality associated with diabetes mellitus was significantly lower in patients with alopecia areata (HR, 0.53; 95% CI, 0.36-0.79). Conclusions and Relevance Patients with alopecia areata have a higher risk of mortality associated with self-harm, psychiatric diseases, and smoking-associated malignant diseases including lung cancer. For better outcomes, clinicians should appropriately treat patients to ensure emotional and psychological well-being.

PurposeThe 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.ParticipantsThe 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 dateThe 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 plansThe 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.

The hypothalamic-pituitary-adrenal (HPA) axis undergoes critical developments during adolescence. Therefore, stressors experienced during this period potentially have long-term effects on adult HPA axis function. We hypothesized that adolescent intermittent ethanol (AIE) exposure would affect adult HPA axis function, resulting in altered responses to an alcohol challenge in young adults or adults. To test these hypotheses, male rats were exposed to alcohol vapor for 6 h per day from post-natal day (PND) 28–42, then acutely challenged with alcohol intragastrically (3.2–4.5 g/kg) in young adults (PND 70) or adults (PND 90). Overall, we observed blunted HPA axis responses to an alcohol challenge due to AIE exposure. Specifically, AIE tended to inhibit the alcohol-challenge-induced increase in plasma corticosterone (CORT) concentrations in young adult and adult rats. As well, AIE significantly blunted the alcohol challenge-induced arginine vasopressin (Avp) mRNA expression in the paraventricular nucleus (PVN) of the hypothalamus of adult rats. Results of the present study are similar to what we have previously shown, that these changes in PVN responsiveness may result from AIE-induced alterations in adrenergic neurons in brain stem regions C1–C3 known to project to the PVN. AIE elevated the number of colocalized c-fos/phenylethanolamine N-methyltransferase (PNMT)-positive cell bodies in the C1 region of adult rats. Together, this data suggests that AIE exposure produces alterations in male HPA axis responsiveness to administration of an acute alcohol challenge that may be long-lasting.