Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression:Prediction Model Development Study

BACKGROUND: Mood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early prediction is challenging due to overlapping symptoms. Recently, there have been attempts to develop a prediction model by using federated learning. Federated learning in medical fields is a method for training multi-institutional machine learning models without patient-level data sharing. OBJECTIVE: This study aims to develop and validate a federated, differentially private multi-institutional bipolar transition prediction model. METHODS: This retrospective study enrolled patients diagnosed with the first depressive episode at 5 tertiary hospitals in South Korea. We developed models for predicting bipolar transition by using data from 17,631 patients in 4 institutions. Further, we used data from 4541 patients for external validation from 1 institution. We created standardized pipelines to extract large-scale clinical features from the 4 institutions without any code modification. Moreover, we performed feature selection in a federated environment for computational efficiency and applied differential privacy to gradient updates. Finally, we compared the federated and the 4 local models developed with each hospital's data on internal and external validation data sets. RESULTS: In the internal data set, 279 out of 17,631 patients showed bipolar disorder transition. In the external data set, 39 out of 4541 patients showed bipolar disorder transition. The average performance of the federated model in the internal test (area under the curve [AUC] 0.726) and external validation (AUC 0.719) data sets was higher than that of the other locally developed models (AUC 0.642-0.707 and AUC 0.642-0.699, respectively). In the federated model, classifications were driven by several predictors such as the Charlson index (low scores were associated with bipolar transition, which may be due to younger age), severe depression, anxiolytics, young age, and visiting months (the bipolar transition was associated with seasonality, especially during the spring and summer months). CONCLUSIONS: We developed and validated a differentially private federated model by using distributed multi-institutional psychiatric data with standardized pipelines in a real-world environment. The federated model performed better than models using local data only.</p

Changes and Challenges in Museum Management after the COVID-19 Pandemic

To investigate how museums will change after the coronavirus disease 2019 (COVID-19) pandemic, and to seek opinions on how well they can secure sustainable competitiveness, this study conducted 15 in-depth interviews using snowball sampling. The interviewees consisted of: an artists’ group, a museum-related group, and a users’ group. Our findings revealed that museums are working hard to gain competitiveness in the face of COVID-19, for which they changed their existing business models to a great extent. One of the most significant changes they introduced, was considering their users as internal, rather than external, stakeholders. For promoting museum products, encouraging users to participate makes them strong supporters who are more active across online platforms and engage and motivate new users, thereby configuring the network effects. The study concludes that this innovative trend will contribute to museums’ sustainable competitiveness during the pandemic as well as in the post-pandemic era

Low Power Switching Characteristics of CNT Field Effect Transistor Device with Al-Doped ZrHfO2 Gate Dielectric

In this report, we demonstrated a reliable switching effect of carbon nanotube (CNT) field-effect transistor (FET) devices integrated with 99% semiconducting CNT as a channel and high-k oxide as the dielectric. CNT FET devices with high-k oxides of Al-ZrHfO2 and Al2O3 were electrically characterized and compared. There was no considerable hysteresis in the Al2O3-based CNT FET device. The Al-ZrHfO2 with a tetragonal phase-based high dielectric constant (~47), designed by an atomic layer deposition process, showed a reliable switching effect as well as low operation voltage (<±3 V). Charge trapping/detrapping process via oxygen vacancy-related defects of Al-ZrHfO2 was proposed as a primary mechanism to explain a current change of a counterclockwise direction and threshold voltage (Vth) shift for transfer properties. The suggested charge trapping model within bulk oxide was experimentally proven since the hysteresis from the adsorption/desorption of gas molecules to CNT surface was negligible. Endurance characteristics of the CNT switching devices remained stable without any serious current fluctuation during a repetitive cycling test. The memory device with reliable switching properties as well as low operation power would pave a road toward next-generation memory components of portable electronic gadgets

Association between Preoperative Glucose Dysregulation and Delirium after Non-Cardiac Surgery

This study aimed to investigate the association between glucose dysregulation and delirium after non-cardiac surgery. Among a total of 203,787 patients who underwent non-cardiac surgery between January 2011 and June 2019 at our institution, we selected 61,805 with available preoperative blood glucose levels within 24 h before surgery. Patients experiencing glucose dysregulation were divided into three groups: hyperglycemia, hypoglycemia, and both. We compared the incidence of postoperative delirium within 30 days after surgery between exposed and unexposed patients according to the type of glucose dysregulation. The overall incidence of hyperglycemia, hypoglycemia, and both was 5851 (9.5%), 1452 (2.3%), and 145 (0.2%), respectively. The rate of delirium per 100 person-months of the exposed group was higher than that of the unexposed group in all types of glucose dysregulation. After adjustment, the hazard ratios of glucose dysregulation in the development of delirium were 1.35 (95% CI, 1.18–1.56) in hyperglycemia, 1.36 (95% CI, 1.06–1.75) in hypoglycemia, and 3.14 (95% CI, 1.27–7.77) in both. The subgroup analysis showed that exposure to hypoglycemia or both to hypo- and hyperglycemia was not associated with delirium in diabetic patients, but hyperglycemia was consistently associated with postoperative delirium regardless of the presence of diabetes. Preoperative glucose dysregulation was associated with increased risk of delirium after non-cardiac surgery. Our findings may be helpful for preventing postoperative delirium, and further investigations are required to verify the association and mechanisms for the effect we observed

Recent research trends in textile-based temperature sensors: a mini review

In this review, the current state of research on textile-based temperature sensors is explored by focusing on their potential use in various applications. The textile-based sensors show various advantages including flexibility, conformability and seamlessness for the wearer. Integration of the textile-based sensors into clothes or fabric-based products enables continuous and sensitive monitoring of change in temperature, which can be used for various medical and fitness applications. However, there are lacks of comprehensive review on the textile-based temperature sensors. This review introduces various types of textile-based temperature sensors, including resistive, thermoelectric and fibre-optical sensors. In addition, the challenges that need to be addressed to fully realise their potential, which include improving sensitivity and accuracy, integrating wireless communication capabilities, and developing low-cost fabrication techniques. The technological advances in textile-based temperature sensors to overcome the limitations will revolutionize wearable devices requiring function of temperature monitoring

Prediction model for myocardial injury after non-cardiac surgery using machine learning

Abstract Myocardial injury after non-cardiac surgery (MINS) is strongly associated with postoperative outcomes. We developed a prediction model for MINS and have provided it online. Between January 2010 and June 2019, a total of 6811 patients underwent non-cardiac surgery with normal preoperative level of cardiac troponin (cTn). We used machine learning techniques with an extreme gradient boosting algorithm to evaluate the effects of variables on MINS development. We generated two prediction models based on the top 12 and 6 variables. MINS was observed in 1499 (22.0%) patients. The top 12 variables in descending order according to the effects on MINS are preoperative cTn level, intraoperative inotropic drug infusion, operation duration, emergency operation, operation type, age, high-risk surgery, body mass index, chronic kidney disease, coronary artery disease, intraoperative red blood cell transfusion, and current alcoholic use. The prediction models are available at https://sjshin.shinyapps.io/mins_occur_prediction/ . The estimated thresholds were 0.47 in 12-variable models and 0.53 in 6-variable models. The areas under the receiver operating characteristic curves are 0.78 (95% confidence interval [CI] 0.77–0.78) and 0.77 (95% CI 0.77–0.78), respectively, with an accuracy of 0.97 for both models. Using machine learning techniques, we demonstrated prediction models for MINS. These models require further verification in other populations

Nanoadhesive layer to prevent protein absorption in a poly(dimethylsiloxane) microfluidic device

Poly(dimethylsiloxane) (PDMS) is widely used as a microfluidics platform material; however, it absorbs various molecules, perturbing specific chemical concentrations in microfluidic channels. We present a simple solution to prevent adsorption into a PDMS microfluidic device. We used a vapor-phase-deposited nanoadhesive layer to seal PDMS microfluidic channels. Absorption of fluorescent molecules into PDMS was efficiently prevented in the nanolayer-treated PDMS device. Importantly, when cultured in a nanolayer-treated PDMS device, yeast cells exhibited the expected concentration-dependent response to a mating pheromone, including mating-specific morphological and gene expression changes, while yeast cultured in an untreated PDMS device did not properly respond to the pheromone. Our method greatly expands microfluidic applications that require precise control of molecule concentrations.ISSN:0736-620

Computational Screening for Design of Optimal Coating Materials to Suppress Gas Evolution in Li-Ion Battery Cathodes

Ni-rich layered oxides are attractive materials owing to their potentially high capacity for cathode applications. However, when used as cathodes in Li-ion batteries, they contain a large amount of Li residues, which degrade the electrochemical properties because they are the source of gas generation inside the battery. Here, we propose a computational approach to designing optimal coating materials that prevent gas evolution by removing residual Li from the surface of the battery cathode. To discover promising coating materials, the reactions of 16 metal phosphates (MPs) and 45 metal oxides (MOs) with the Li residues, LiOH, and Li₂CO₃ are examined within a thermodynamic framework. A materials database is constructed according to density functional theory using a hybrid functional, and the reaction products are obtained according to the phases in thermodynamic equilibrium in the phase diagram. In addition, the gravimetric efficiency is calculated to identify coating materials that can eliminate Li residues with a minimal weight of the coating material. Overall, more MP and MO materials react with LiOH than with Li₂CO₃. Specifically, MPs exhibit better reactivity to both Li residues, whereas MOs react more with LiOH. The reaction products, such as Li-containing phosphates or oxides, are also obtained to identify the phases on the surface of a cathode after coating. On the basis of the Pareto-front analysis, P₂O₅ could be an optimal material for the reaction with both Li residuals. Finally, the reactivity of the coating materials containing 3d/4d transition metal elements is better than that of materials containing other types of elements