Laminaria japonica has frequently been used as a food supplement and drug in traditional oriental medicine. Among the major active constituents responsible for the bioactivities of L. japonica, fucoxanthin (FX) has been considered as a potential antioxidant. This study was conducted to examine the effects of L. japonica extract (LJE) or FX against oxidative stress on hepatocytes and to elucidate the overall their cellular mechanisms of the effects. We constructed an in vitro model with the treatment of arachidonic acid (AA) + iron in HepG2 cells to stimulate the oxidative damage. The cells were pre-treated with LJE or FX for 1 h, and incubated with AA + iron. The effect on oxidative damage and cellular mechanisms of LJE or FX were assessed by cytological examination and several biochemical assays under conditions with or without kinase inhibitiors. LJE or FX pretreatment effectively blocked the pathological changes caused by AA + iron treatment, such as cell death, altered expression of apoptosis-related proteins such as procaspase-3 and poly (ADP-ribose) polymerase, and mitochondria dysfunction. Moreover, FX induced AMPK activation and AMPK inhibitor, compound C, partially reduced the protective effect of FX on mitochondria dysfunction. Consistent with AMPK activation, FX increased the protein levels of autophagic markers (LC3II and beclin-1) and the number of acridine orange stained cells, and decreased the phosphorylation of mTOR and simultaneously increased the phosphorylation of ULK1. And the inhibition of autophagy by 3-methylanine or bafilomycin A1 partially inhibited the protective effect of FX on mitochondria dysfunction. These findings suggest that FX have the function of being a hepatic protectant against oxidative damages through the AMPK pathway for the control of autophagy.

With the advent of digital healthcare without borders, enormous amounts of health information are captured and computerized. As healthcare quality largely depends on the reliability of given health information, personal health records should be accessible according to patients’ mobility, even as they travel or migrate to other countries. However, since all the health information is scattered in multiple places, it is an onerous task to carry it whenever people move to other countries. To effectively and efficiently utilize health information, interoperability, which is the ability of various healthcare information technologies to exchange, to interpret, and to use data, is needed. Hence, building a robust transnational health information infrastructure with clear interoperability guidelines considering heterogeneous aspects is necessary. For this purpose, this study proposes a Transnational Health Record framework, which enables access to personal health records anywhere. We review related literature and define level-specific interoperability guidelines, business processes, and requirements for the Transnational Health Record system framework.

Objectives: This paper aimed to use machine learning to identify a new group of factors predicting frailty in the elderly population by utilizing the existing frailty criteria as a basis, as well as to validate the obtained results. Methods: This study was conducted using data from the Korean Frailty and Aging Cohort Study (KFACS). The KFACS participants were classified as robust or frail based on Fried’s frailty phenotype and excluded if they did not properly answer the questions, resulting in 1,066 robust and 165 frail participants. We then selected influential features through feature selection and trained the model using support vector machine, random forest, and gradient boosting algorithms with the prepared dataset. Due to the imbalanced distribution in the dataset with a low sample size, holdout was applied with stratified 10-fold and cross-validation for estimating the model performance. The reliability of the constructed model was validated using an unseen test set. The model was then trained with hyperparameter optimization. Results: During the feature selection process, 27 features were identified as meaningful factors for frailty. The model was trained based on the selected features, and the weighted average F1-score reached 95.30% with the random forest algorithm. Conclusions: The results of the study demonstrated the possibility of adopting machine learning to strengthen existing frailty criteria. As the method analyzes questionnaire responses in a short time, it can support higher volumes of data on participants’ health conditions and alert them regarding potential risks in advance.

Internet of Things (IoT) devices can be effectively used in cases where continuous observation of patients is required, such as Parkinson's disease. This is due to the characteristics of the IoT (Internet of Things), which allows data to be measured and transmitted at any time, anywhere. In this study, we developed a health data collection platform that stores and transmits the foot pressure data of Parkinson patients using FHIR (Fast Healthcare Interoperability Resources). The platform can be used to collect the foot pressure of a large number of Parkinson's patients. Based on the accumulated data, it is possible to identify abnormal behaviors such as walking pattern, tilt and instability of stride length in patients with Parkinson's disease. Based on the results of this study, accurate diagnosis and treatment of Parkinson's disease can be made.

Since 2019, the Korean government’s investments in making data more accessible to the public have grown by 337%. However, open government data, which should be accessible to everyone, are not entirely accessible to people with low vision, who represent an information-vulnerable class. Emergencies, such as the COVID-19 pandemic, decrease face-to-face encounters and inevitably increase untact encounters. Thus, the information gap experienced by low-vision people, who are underprivileged in terms of information, will be further widened, and they may consequently face various disadvantages. This study proposed visual communication design accessibility (VCDA) guidelines for people with low vision. Introduced screens enhanced by accessibility guidelines were presented to 16 people with low vision and 16 people with normal vision and the speed of visual information recognition was analyzed. No statistically significant difference (p > 0.05) was found due to the small sample size; however, this study’s results approached significance with improved visual recognition speed for people with low vision after adopting VCDA. As a result of the intervention, the visual information recognition speed of both normal and low-vision people improved. Thus, our results can help improve information recognition speed among people with normal and low vision.

Many Clinical Document Architecture (CDA) referrals and reply documents have been accumulated for patients since the deployment of the Health Information Exchange System (HIES) in Korea. Clinical data were scattered in many CDA documents and this took too much time for physicians to read. Physicians in Korea spend only limited time per patient as insurances in Korea follow a fee-for-service model. Therefore, physicians were not allowed sufficient time for making medical decisions, and follow-up care service was hindered. To address this, we developed CDA Integration Template (CIT) and CDA Integration System (CIS) for the HIES. The clinical items included in CIT were defined reflecting the Korean Standard for CDA Referral and Reply Letters and requests by physicians. CIS integrates CDA documents of a specified patient into a single CDA document following the format of CIT. Finally, physicians were surveyed after CIT/CIS adoption, and they indicated overall satisfaction.