Effect of Dynamic Binaural Beats on Sleep Quality: A Proof-of-Concept Study with Questionnaire and Biosignals.

Binaural beat (BB) has been investigated as a potential modality to enhance sleep quality. In this study, we introduce a new form of BB, referred to as dynamic BB (DBB), which incorporates dynamically changing carrier frequency differences between the left and right ears. Specifically, the carrier frequency of the right ear varied between 100 and 103 Hz over a period, while the left ear remained fixed at 100 Hz, yielding a frequency difference range of 0 to 3 Hz. The objective of this study was to examine the effect of DBB on sleep quality. Ten healthy participants were included in a cross-over design, where they experienced both DBB and a SHAM (absence of sound) condition across two consecutive nights, with polysomnography evaluation. DBB was administrated during pre-sleep initiation, sleep onset, and transition from rapid-eye-movement (REM) to non-REM stage. DBB significantly reduced sleep latency compared to the SHAM condition. Electrocardiogram analysis revealed that exposure to DBB led to diminished heart rate variability during the pre-sleep initiation and sleep onset periods, accompanied by a decrease in low frequency power of heart rate during the sleep onset period. DBB might be effective in improving the sleep quality, suggesting its possible application in insomnia treatments.

Fuzzy Clustering-Based Deep Learning for Short-Term Load Forecasting in Power Grid Systems Using Time-Varying and Time-Invariant Features.

Accurate short-term load forecasting (STLF) is essential for power grid systems to ensure reliability, security and cost efficiency. Thanks to advanced smart sensor technologies, time-series data related to power load can be captured for STLF. Recent research shows that deep neural networks (DNNs) are capable of achieving accurate STLP since they are effective in predicting nonlinear and complicated time-series data. To perform STLP, existing DNNs use time-varying dynamics of either past load consumption or past power correlated features such as weather, meteorology or date. However, the existing DNN approaches do not use the time-invariant features of users, such as building spaces, ages, isolation material, number of building floors or building purposes, to enhance STLF. In fact, those time-invariant features are correlated to user load consumption. Integrating time-invariant features enhances STLF. In this paper, a fuzzy clustering-based DNN is proposed by using both time-varying and time-invariant features to perform STLF. The fuzzy clustering first groups users with similar time-invariant behaviours. DNN models are then developed using past time-varying features. Since the time-invariant features have already been learned by the fuzzy clustering, the DNN model does not need to learn the time-invariant features; therefore, a simpler DNN model can be generated. In addition, the DNN model only learns the time-varying features of users in the same cluster; a more effective learning can be performed by the DNN and more accurate predictions can be achieved. The performance of the proposed fuzzy clustering-based DNN is evaluated by performing STLF, where both time-varying features and time-invariant features are included. Experimental results show that the proposed fuzzy clustering-based DNN outperforms the commonly used long short-term memory networks and convolution neural networks.

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study.

BACKGROUND: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. METHODS: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP). RESULTS: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. CONCLUSION: Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Electrostatically Powered Multimode Liquid Crystalline Elastomer Actuators.

Soft actuators based on liquid crystalline elastomers (LCEs) are captivating significant interest because of their unique properties combining the programmable liquid crystalline molecular order and elasticity of polymeric materials. For practical applications, the ability to perform multimodal shape changes in a single LCE actuator at a subsecond level is a bottleneck. Here, we fabricate a monodomain LCE powered by electrostatic force, which enables fast multidirectional bending, oscillation, rotation, and complex actuation with a high degree of freedom. By tuning the dielectric constant and resistivity in LCE gels, a complete cycle of oscillation and rotation only takes 0.1 s. In addition, monodomain actuators exhibit anisotropic actuation behaviors that promise a more complex deployment in a potential electromechanical system. The presented study will pave the way for electrostatically controllable isothermal manipulation for a fast and multimode soft actuator.

Reconstruction of the lower back wound with delayed infection after spinal surgery: A case report.

BACKGROUND: Orthopedic surgeries after device implantation are susceptible to infections and may require device removal in the worst cases. For this reason, many efforts are being made to control infections after spinal surgery; however, the number of infection cases is increasing owing to the increasing number of elderly citizens. CASE SUMMARY: A 75-year-old male with a chronic spinal defect due to previous spine surgery underwent reconstruction using a perforator-based island flap. After bursectomy and confirmation that there was no connection with the deep tissue, reconstruction was performed. However, wound disruption occurred with abscess formation on postoperative day 29, which led to an imaging workup revealing delayed deep tissue infection. CONCLUSION: Infection is one of the most common causes of surgical wound dehiscence and is associated with devastating results if not controlled promptly and definitively. Surgeons should always suspect delayed infections when reconstructing chronic soft tissue defects.

Altered prefrontal beta oscillatory activity during removal of information from working memory in obsessive-compulsive disorder.

BACKGROUND: Obsessive-compulsive disorder (OCD) is related to working memory impairment. Since patients with OCD have difficulty controlling their obsessive thoughts, removal of irrelevant information might be important in the pathophysiology of OCD. However, little is known about brain activity during the removal of information from working memory in patients with OCD. Our goal was to explore potential deficits in inhibitory function related to working memory processes in patients with OCD. METHODS: Sixteen OCD patients and 20 healthy controls (HCs) were recruited. We compared in prefrontal alpha and beta band activity derived from magnetoencephalography (MEG) between patients with OCD and HCs during multiple phases of information processing associated with working memory, especially in post-trial period of the visuospatial working memory task (the delayed matching-to-sample task), which is presumed to be related to the information removal process of working memory. RESULTS: Prefrontal post-trial beta power change (presumed to occur at high levels during the post-trial period) exhibited significant reductions in patients with OCD compared to HCs. In addition, the post-trial beta power change was negatively correlated with Obsessive-Compulsive Inventory-Revised total scores in patients with OCD. CONCLUSIONS: These findings suggest that impairment in the removal of information from working memory might be a key mechanism underlying the inability of OCD patients to rid themselves of their obsessions.

Cellular Diversity in Human Subgenual Anterior Cingulate and Dorsolateral Prefrontal Cortex by Single-Nucleus RNA-Sequencing.

Regional cellular heterogeneity is a fundamental feature of the human neocortex; however, details of this heterogeneity are still undefined. We used single-nucleus RNA-sequencing to examine cell-specific transcriptional features in the dorsolateral PFC (DLPFC) and the subgenual anterior cingulate cortex (sgACC), regions implicated in major psychiatric disorders. Droplet-based nuclei-capture and library preparation were performed on replicate samples from 8 male donors without history of psychiatric or neurologic disorder. Unsupervised clustering identified major neural cell classes. Subsequent iterative clustering of neurons further revealed 20 excitatory and 22 inhibitory subclasses. Inhibitory cells were consistently more abundant in the sgACC and excitatory neuron subclusters exhibited considerable variability across brain regions. Excitatory cell subclasses also exhibited greater within-class transcriptional differences between the two regions. We used these molecular definitions to determine which cell classes might be enriched in loci carrying a genetic signal in genome-wide association studies or for differentially expressed genes in mental illness. We found that the heritable signals of psychiatric disorders were enriched in neurons and that, while the gene expression changes detected in bulk-RNA-sequencing studies were dominated by glial cells, some alterations could be identified in specific classes of excitatory and inhibitory neurons. Intriguingly, only two excitatory cell classes exhibited concomitant region-specific enrichment for both genome-wide association study loci and transcriptional dysregulation. In sum, by detailing the molecular and cellular diversity of the DLPFC and sgACC, we were able to generate hypotheses on regional and cell-specific dysfunctions that may contribute to the development of mental illness.SIGNIFICANCE STATEMENT Dysfunction of the subgenual anterior cingulate cortex has been implicated in mood disorders, particularly major depressive disorder, and the dorsolateral PFC, a subsection of the PFC involved in executive functioning, has been implicated in schizophrenia. Understanding the cellular composition of these regions is critical to elucidating the neurobiology underlying psychiatric and neurologic disorders. We studied cell type diversity of the subgenual anterior cingulate cortex and dorsolateral PFC of humans with no neuropsychiatric illness using a clustering analysis of single-nuclei RNA-sequencing data. Defining the transcriptomic profile of cellular subpopulations in these cortical regions is a first step to demystifying the cellular and molecular pathways involved in psychiatric disorders.

Evaluation of changes in neural oscillation after bilateral capsulotomy in treatment refractory obsessive-compulsive disorder using magnetoencephalogram.

Bilateral thermal capsulotomy with magnetic resonance-guided focused ultrasound (MRgFUS-capsulotomy) is a promising treatment option for treatment-refractory obsessive-compulsive disorder (OCD). Herein, we investigated the effects of bilateral thermal capsulotomy with MRgFUS on neural oscillations in treatment-refractory OCD patients. Eight patients underwent resting-state MEG with repeated recordings before and 1 and 6 months after MRgFUS-capsulotomy, and the oscillatory power and phase coherence over the entire cortical sensor area were measured. After MRgFUS-capsulotomy, the high beta band power in the fronto-central and temporal areas decreased at 1 month and remained stable for 6 months. Cortical connectivity of the high beta band gradually decreased over the entire cortical area during the following 6 months. At 1 month, improvement in anxiety and depression symptoms was significantly correlated with changes in high beta band power in both the frontotemporal and temporal areas. The treatment effect of MRgFUS-capsulotomy may be attributed to the cortical high beta band. Our results provide an advanced understanding of the neural mechanisms underlying MRgFUS-capsulotomy and other neuromodulatory interventions for treatment-refractory OCD.

In-Advance Prediction of Pressure Ulcers via Deep-Learning-Based Robust Missing Value Imputation on Real-Time Intensive Care Variables.

Pressure ulcers (PUs) are a prevalent skin disease affecting patients with impaired mobility and in high-risk groups. These ulcers increase patients' suffering, medical expenses, and burden on medical staff. This study introduces a clinical decision support system and verifies it for predicting real-time PU occurrences within the intensive care unit (ICU) by using MIMIC-IV and in-house ICU data. We develop various machine learning (ML) and deep learning (DL) models for predicting PU occurrences in real time using the MIMIC-IV and validate using the MIMIC-IV and Kangwon National University Hospital (KNUH) dataset. To address the challenge of missing values in time series, we propose a novel recurrent neural network model, GRU-D++. This model outperformed other experimental models by achieving the area under the receiver operating characteristic curve (AUROC) of 0.945 for the on-time prediction and AUROC of 0.912 for 48h in-advance prediction. Furthermore, in the external validation with the KNUH dataset, the fine-tuned GRU-D++ model demonstrated superior performances, achieving an AUROC of 0.898 for on-time prediction and an AUROC of 0.897 for 48h in-advance prediction. The proposed GRU-D++, designed to consider temporal information and missing values, stands out for its predictive accuracy. Our findings suggest that this model can significantly alleviate the workload of medical staff and prevent the worsening of patient conditions by enabling timely interventions for PUs in the ICU.

Optimal flickering light stimulation for entraining gamma rhythms in older adults.

With aging, optimal parameters of flickering light stimulation (FLS) for gamma entrainment may change in the eyes and brain. We investigated the optimal FLS parameters for gamma entrainment in 35 cognitively normal old adults by comparing event-related synchronization (ERS) and spectral Granger causality (sGC) of entrained gamma rhythms between different luminance intensities, colors, and flickering frequencies of FLSs. ERS entrained by 700 cd/m2 FLS and 32 Hz or 34 Hz FLSs was stronger than that entrained by 400 cd/m2 at Pz (p < 0.01) and 38 Hz or 40 Hz FLSs, respectively, at both Pz (p < 0.05) and Fz (p < 0.01). Parieto-occipital-to-frontotemporal connectivities of gamma rhythm entrained by 700 cd/m2 FLS and 32 Hz or 34 Hz FLSs were also stronger than those entrained by 400 cd/m2 at Pz (p < 0.01) and 38 Hz or 40 Hz FLSs, respectively (p < 0.001). ERS and parieto-occipital-to-frontotemporal connectivities of entrained gamma rhythms did not show significant difference between white and red lights. Adverse effects were comparable between different parameters. In older adults, 700 cd/m2 FLS at 32 Hz or 34 Hz can entrain a strong gamma rhythm in the whole brain with tolerable adverse effects.

Association between Heavy Metal Exposure and Dyslipidemia among Korean Adults: From the Korean National Environmental Health Survey, 2015-2017.

Cardiovascular disease (CVD) is a leading cause of death in Korea. Dyslipidemia, characterized by the presence of abnormal lipid levels, has been suggested as an early diagnostic and preventable factor for CVD. Recent studies have shown that exposure to lead (Pb), cadmium (Cd), and mercury (Hg) affects lipid metabolism. This study aimed to verify the association between heavy metal concentrations and serum lipid profiles in the general population. A representative sample of 2591 Korean adults from the Korean National Environmental Health Survey (2015−2017) was analyzed. The associations between heavy metals [Blood Pb (BPb), blood Hg (BHg), urinary Hg (UHg), urinary Cd (UCd)] and serum lipid profiles [total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), non-low level of high-density lipoprotein cholesterol (Non-HDL-C)] were assessed using regression analysis. After adjusting for demographic and socioeconomic factors, the proportional changes in serum lipid levels were significantly associated with increases in BPb, BHg, and UHg levels (p for trend < 0.05). Overall, BPb, BHg, and Uhg levels positively correlated with dyslipidemia, whereas UCd levels did not show a significant association. Our results suggest that heavy metal exposure, at low levels, may contribute to an increased prevalence of dyslipidemia in Korean adults.

Flexible Sol-Gel-Processed Y2O3 RRAM Devices Obtained via UV/Ozone-Assisted Photochemical Annealing Process.

Flexible indium tin oxide (ITO)/Y2O3/Ag resistive random access memory (RRAM) devices were successfully fabricated using a thermal-energy-free ultraviolet (UV)/ozone-assisted photochemical annealing process. Using the UV/ozone-assisted photochemical process, the organic residue can be eliminated, and thinner and smother Y2O3 films than those formed using other methods can be fabricated. The flexible UV/ozone-assisted photochemical annealing process-based ITO/Y2O3/Ag RRAM devices exhibited the properties of conventional bipolar RRAM without any forming process. Furthermore, the pure and amorphous-phase Y2O3 films formed via this process showed a decreased leakage current and an increased high-resistance status (HRS) compared with the films formed using other methods. Therefore, RRAM devices can be realized on plastic substrates using a thermal-energy-free UV/ozone-assisted photochemical annealing process. The fabricated devices exhibited a resistive window (ratio of HRS/low-resistance status (LRS)) of >104, with the HRS and LRS values remaining almost the same (i.e., limited deterioration occurred) for 104 s and up to 102 programming/erasing operation cycles.

Enhanced Switching Reliability of Sol-Gel-Processed Y2O3 RRAM Devices Based on Y2O3 Surface Roughness-Induced Local Electric Field.

Sol-gel-processed Y2O3 films were used as active channel layers for resistive random access memory (RRAM) devices. The fabricated ITO/Y2O3/Ag RRAM devices exhibited the properties of conventional bipolar memory devices. A triethylamine stabilizer with a high vapor pressure and low surface tension was added to realize the local electric field area. During drying and high-temperature post-annealing processes, the large convective flow enhanced the surface elevation, and the increased -OH groups accelerated the hydrolysis reaction and aggregation. These phenomena afforded Y2O3 films with an uneven surface morphology and an increased surface roughness. The increased roughness of the Y2O3 films attributable to the triethylamine stabilizer enhanced the local electrical field, improved device reliability, and achieved successful repetition of the switching properties over an extended period.

Estimation of Emotional Arousal Changes of a Group of Individuals During Movie Screening Using Steady-State Visual-Evoked Potential.

Neurocinematics is an emerging discipline in neuroscience, which aims to provide new filmmaking techniques by analyzing the brain activities of a group of audiences. Several neurocinematics studies attempted to track temporal changes in mental states during movie screening; however, it is still needed to develop efficient and robust electroencephalography (EEG) features for tracking brain states precisely over a long period. This study proposes a novel method for estimating emotional arousal changes in a group of individuals during movie screening by employing steady-state visual evoked potential (SSVEP), which is a widely used EEG response elicited by the presentation of periodic visual stimuli. Previous studies have reported that the emotional arousal of each individual modulates the strength of SSVEP responses. Based on this phenomenon, movie clips were superimposed on a background, eliciting an SSVEP response with a specific frequency. Two emotionally arousing movie clips were presented to six healthy male participants, while EEG signals were recorded from the occipital channels. We then investigated whether the movie scenes that elicited higher SSVEP responses coincided well with those rated as the most impressive scenes by 37 viewers in a separate experimental session. Our results showed that the SSVEP response averaged across six participants could accurately predict the overall impressiveness of each movie, evaluated with a much larger group of individuals.

Optimal flickering light stimulation for entraining gamma waves in the human brain.

Although light flickering at 40 Hz reduced Alzheimer's disease (AD) pathologies in mice by entraining gamma waves, it failed to reduce cerebral amyloid burden in a study on six patients with AD or mild cognitive impairment. We investigated the optimal color, intensity, and frequency of the flickering light stimulus for entraining gamma waves in young adults. We compared the event-related synchronization (ERS) values of entrained gamma waves between four different light colors (white, red, green, and blue) in the first experiment and four different luminance intensities in the second experiment. In both experiments, we compared the ERS values of entrained gamma waves between 10 different flickering frequencies from 32 to 50 Hz. We also examined the severity of six adverse effects in both experiments. We compared the propagation of gamma waves in the visual cortex to other brain regions between different luminance intensities and flickering frequencies. We found that red light entrained gamma waves most effectively, followed by white light. Lights of higher luminance intensities (700 and 400 cd/m2) entrained stronger gamma waves than those of lower luminance intensities (100 and 10 cd/m2). Lights flickering at 34-38 Hz entrained stronger and more widely spread beyond the visual cortex than those flickering at 40-50 Hz. Light of 700 cd/m2 resulted in more moderate-to-severe adverse effects than those of other luminance intensities. In humans, 400 cd/m2 white light flickering at 34-38 Hz was most optimal for gamma entrainment.

5G Security Threat Assessment in Real Networks.

Advances in mobile communication networks from 2G to 5G have brought unprecedented traffic growth, and 5G mobile communication networks are expected to be used in a variety of industries based on innovative technologies, fast not only in terms of extremely low latency but massive access devices. Various types of services, such as enhanced mobile broadband (eMBB), massive machine type communication (mMTC), and ultra-reliable and low latency communication (uRLLC), represent an increase in the number of attacks on users' personal information, confidential information, and privacy information. Therefore, security assessments are essential to verify and cope with these various attacks. In this research, we (1) looked at 5G mobile communication network backgrounds and problems to investigate existing vulnerabilities and (2) assessed the current situation through evaluation of 5G security threats in real-world mobile networks in service.

Association between Pb, Cd, and Hg Exposure and Liver Injury among Korean Adults.

BACKGROUND: Exposure to lead (Pb), cadmium (Cd), and mercury (Hg) has been reported to be associated with liver-related diseases. However, studies examining the association between heavy metal exposure and liver injury in a large population are scant and characterized by inconsistent results. This study aimed to evaluate the association between levels of heavy metal exposure and liver injury in the general population. METHODS: Data for 2953 participants aged 19 years or more obtained from the Korean National Environmental Health Survey (KoNEHS) Cycle 3 (2015-2017) were used. The associations between levels of blood or urine heavy metals (Pb, Cd, and Hg) and liver function biomarkers [aspartate aminotransferase (AST), alanine aminotransferase (ALT), and gamma-glutamyl transferase (GGT)] were evaluated using multiple linear regression analysis. RESULTS: Regarding the blood Pb (BPb), AST was higher in those of the 4th quartile, ALT was higher in those of the 2nd and 4th quartiles, and GGT was higher in those of the 3rd and 4th quartiles than in the 1st quartile. For urinary Cd (UCd), AST was higher in those of the 4th quartile; ALT was higher in those of the 2nd, 3rd, and 4th quartiles; and GGT was higher in the 4th quartile than in the 1st quartile. For the blood Hg (BHg), AST was higher in those of the 2nd and 4th quartile, ALT was higher in those of the 2nd, 3rd, and 4th quartiles; and GGT was higher in those of the 3rd and 4th quartiles than in the 1st quartile. There was no significant difference between urinary Hg (UHg) and liver function markers. CONCLUSION: Heavy metal exposure showed an association with liver injury among the general adult population in Korea. Further studies are required to clarify the relationship between heavy metals and liver injury.

Neural Oscillation Associated with Contagious Itch in Patients with Atopic Dermatitis.

OBJECTIVE: Itch is an unpleasant sensation associated with an urge to scratch and is a major health care issue associated with atopic dermatitis (AD). Contagious itch, i.e., subjective feelings of itchiness induced by watching others' scratching behavior, is common in patients with AD. Using electroencephalography, we examined alpha (8-13 Hz) oscillations in sensorimotor areas associated with the desire to scratch in patients with AD. METHODS: Thirty-six patients with AD and 34 healthy controls (HCs) participated in this study. They evaluated their itch levels after watching short videos of a model scratching or tapping parts of his body. Neural oscillations were recorded from nine electrodes, including those placed over sensorimotor areas. Time-frequency analysis was used to compare mu rhythm suppression over the sensorimotor areas in response to these videos between patients with AD and HCs. RESULTS: The behavioral test showed that the visual stimuli induced increased feelings of itchiness in patients with AD relative to HCs under the tapping and scratching conditions. The time-frequency analysis revealed that mu rhythm suppression in response to scratching images was significantly prominent in patients with AD, but not in HCs. CONCLUSION: Patients with AD exhibited increased susceptibility to contagious itch. This phenomenon might be related to enhanced mu rhythm suppression in sensorimotor areas of the brain in these patients. Our findings provide new insight into the neurophysiological basis of itch sensations in patients with AD.

Photoredox-Catalyzed α-Aminoalkylcarboxylation of Allenes with CO2.

The photoredox-catalyzed α-aminoalkylcarboxylation of aryl allenes with CO2 and N,N-dimethylanilines is reported for the first time (26 examples, up to 96% yield). In the case of electron-deficient allenes, good regioselectivity was observed (up to 94:6), exclusively generating kinetic products over thermodynamic products. This protocol is a novel synthetic method for highly functionalized ß,γ-unsaturated γ-aminobutyric esters.