EEG Dataset for the Recognition of Different Emotions Induced in Voice-User Interaction.

Electroencephalography (EEG)-based open-access datasets are available for emotion recognition studies, where external auditory/visual stimuli are used to artificially evoke pre-defined emotions. In this study, we provide a novel EEG dataset containing the emotional information induced during a realistic human-computer interaction (HCI) using a voice user interface system that mimics natural human-to-human communication. To validate our dataset via neurophysiological investigation and binary emotion classification, we applied a series of signal processing and machine learning methods to the EEG data.

Effect of modification methods on the physical properties and immunomodulatory activity of particulate β-glucan.

β-Glucan is an immunoenhancing agent whose biological activities are linked to molecular structure. On that basis, the polysaccharide can be physiochemically modified to produce valuable functional materials. This study investigated the physical properties and immunostimulatory activity of modified β-glucan.

Current technologies for heavy metal removal from food and environmental resources.

Exposure to heavy metals in water and food poses a significant threat to human well-being, necessitating the efficient removal of these contaminants. The process of urban development exacerbates heavy metal pollution, thereby increasing risks to both human health and ecosystems. Heavy metals have the capacity to enter the food chain, undergo bioaccumulation and magnify, ultimately resulting in adverse effects on human health.

Effects of Icariin and Its Metabolites on GPCR Regulation and MK-801-Induced Schizophrenia-Like Behaviors in Mice.

Icariin, a major bioactive compound found in the genus, has been reported to exert protective effects against neurodegenerative disorders. In the current study, we aimed to investigate the regulatory effect of icariin and its active metabolites (icariside II and icaritin) against prime G-protein-coupled receptor targets, considering their association with neuronal disorders. Icariside II exhibited selective agonist activity towards the dopamine D3 receptor (DR), with half-maximal effective concentrations of 13.

Effects of Interfacial Electron Transport on Field Electron Emission from Carbon Nanotube Paste Emitters.

Field electron emission from carbon nanotubes (CNT) is preceded by the transport of electrons from the cathode metal to emission sites. Specifically, a supporting layer indispensable for adhesion of CNT paste emitters onto the cathode metal would impose a potential barrier, depending on its work function and interfacial electron transport behaviors. In this paper, we investigated the supporting layer of silicon carbide and nickel nanoparticles reacted onto a Kovar alloy (Fe-Ni-Co) cathode substrate, which has been adopted for reliable CNT paste emitters.

Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages.

Overcrowding of emergency department (ED) has put a strain on national healthcare systems and adversely affected the clinical outcomes of critically ill patients. Early identification of critically ill patients prior to ED visits can help induce optimal patient flow and allocate medical resources effectively. This study aims to develop ML-based models for predicting critical illness in the community, paramedic, and hospital stages using Korean National Emergency Department Information System (NEDIS) data.

Association of ultra-early diffusion-weighted magnetic resonance imaging with neurological outcomes after out-of-hospital cardiac arrest.

Background: This study aimed to investigate the association between ultra-early (within 6 h after return of spontaneous circulation [ROSC]) brain diffusion-weighted magnetic resonance imaging (DW-MRI) and neurological outcomes in comatose survivors after out-of-hospital cardiac arrest.

Methods: We conducted a registry-based observational study from May 2018 to February 2022 at a Chungnam national university hospital in Daejeon, Korea. Presence of high-signal intensity (HSI) (P) was defined as a HSI on DW-MRI with corresponding hypoattenuation on the apparent diffusion coefficient map irrespective of volume after hypoxic ischemic brain injury; absence of HSI was defined as A.

Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.

Early diagnosis of lung cancer to increase the survival rate, which is currently at a low range of mid-30%, remains a critical need. Despite this, multi-omics data have rarely been applied to non-small-cell lung cancer (NSCLC) diagnosis. We developed a multi-omics data-affinitive artificial intelligence algorithm based on the graph convolutional network that integrates mRNA expression, DNA methylation, and DNA sequencing data.

Light-FER: A Lightweight Facial Emotion Recognition System on Edge Devices.

Facial emotion recognition (FER) systems are imperative in recent advanced artificial intelligence (AI) applications to realize better human-computer interactions. Most deep learning-based FER systems have issues with low accuracy and high resource requirements, especially when deployed on edge devices with limited computing resources and memory. To tackle these problems, a lightweight FER system, called Light-FER, is proposed in this paper, which is obtained from the Xception model through model compression.

A Propensity Score-Matched Comparison of In-Hospital Mortality between Dedicated Regional Trauma Centers and Emergency Medical Centers in the Republic of Korea.

Background: In the Republic of Korea, a trauma care system was not created until 2012, at which point regional trauma centers (RTCs) were established nationwide. In accordance with the national emergency care system and legislation, regional and local emergency medical centers (EMCs) also treat patients presenting with trauma. The aim of the present study was to assess whether treatment in RTCs is truly associated with better patient outcomes than that in EMCs by means of propensity score-matched comparisons and to identify populations that would benefit from treatment in RTCs.

Phytoestrogen Coumestrol Selectively Inhibits Monoamine Oxidase-A and Amyloid β Self-Aggregation.

leaves contain a variety of phytoestrogens, including flavonoids, isoflavonoids, and coumestan derivatives. In this study, we aimed to identify the active ingredients of leaves and to elucidate their function in monoamine oxidase (MAO) activation and Aβ self-aggregation using in vitro and in silico approaches. To the best of our knowledge, this is the first study to elucidate coumestrol as a selective and competitive MAO-A inhibitor.

Influence of the Level of Emergency Medical Facility on the Short-Term Treatment Results of Cardiac Arrest: Out-of-Hospital Cardiac Arrest and Interhospital Transfer.

Objective: This study aimed to elucidate whether direct transport of out-of-hospital cardiac arrest (OHCA) patients to higher-level emergency medical centres (EMCs) would result in better survival compared to resuscitation in smaller local emergency departments (EDs) and subsequent transfer.

Methods: This study was a retrospective population-based analysis of cases registered in the national database of 2019. This study investigated the immediate results of cardiopulmonary resuscitation for OHCA compared between EMCs and EDs and the results of therapeutic temperature management (TTM) compared between the patients directly transported from the field and those transferred from other hospitals.

Induction of apoptosis through inactivation of ROS-dependent PI3K/Akt signaling pathway by platycodin D in human bladder urothelial carcinoma cells.

Platycodin D (PD) is a triterpenoid saponin, a major bioactive constituent of the roots of Platycodon grandiflorum, which is well known for possessing various pharmacological properties. However, the anti-cancer mechanism of PD in bladder cancer cells remains poorly understood. In the current study, we investigated the effect of PD on the growth of human bladder urothelial carcinoma cells.

The preventive effect of loganin on oxidative stress-induced cellular damage in human keratinocyte HaCaT cells.

Loganin is a type of iridoid glycosides isolated from Corni fructus and is known to have various pharmacological properties, but studies on its antioxidant activity are still lacking. Therefore, in this study, the preventive effect of loganin on oxidative stress-mediated cellular damage in human keratinocyte HaCaT cells was investigated. Our results show that loganin pretreatment in a non-toxic concentration range significantly improved cell survival in hydrogen peroxide (HO)-treated HaCaT cells, which was associated with inhibition of cell cycle arrest at the G2/M phase and induction of apoptosis.

Induction of apoptotic cell death in human bladder cancer cells by ethanol extract of leaf, through ROS-dependent inactivation of the PI3K/Akt signaling pathway.

Background/objectives: is traditionally used as a spice for cooking in East Asian countries. This study was undertaken to evaluate the anti-proliferative potential of ethanol extracts of leaves (EEZS) against human bladder cancer T24 cells.

Materials/methods: Subsequent to measuring the cytotoxicity of EEZS, the anti-cancer activity was measured by assessing apoptosis induction, reactive oxygen species (ROS) generation, and mitochondrial membrane potential (MMP).

Automatic Cancer Cell Taxonomy Using an Ensemble of Deep Neural Networks.

Microscopic image-based analysis has been intensively performed for pathological studies and diagnosis of diseases. However, mis-authentication of cell lines due to misjudgments by pathologists has been recognized as a serious problem. To address this problem, we propose a deep-learning-based approach for the automatic taxonomy of cancer cell types.

Verification of De-Identification Techniques for Personal Information Using Tree-Based Methods with Shapley Values.

With the development of big data and cloud computing technologies, the importance of pseudonym information has grown. However, the tools for verifying whether the de-identification methodology is correctly applied to ensure data confidentiality and usability are insufficient. This paper proposes a verification of de-identification techniques for personal healthcare information by considering data confidentiality and usability.

A Novel Multistage Transfer Learning for Ultrasound Breast Cancer Image Classification.

Breast cancer diagnosis is one of the many areas that has taken advantage of artificial intelligence to achieve better performance, despite the fact that the availability of a large medical image dataset remains a challenge. Transfer learning (TL) is a phenomenon that enables deep learning algorithms to overcome the issue of shortage of training data in constructing an efficient model by transferring knowledge from a given source task to a target task. However, in most cases, ImageNet (natural images) pre-trained models that do not include medical images, are utilized for transfer learning to medical images.

Classification of the Sidewalk Condition Using Self-Supervised Transfer Learning for Wheelchair Safety Driving.

The demand for wheelchairs has increased recently as the population of the elderly and patients with disorders increases. However, society still pays less attention to infrastructure that can threaten the wheelchair user, such as sidewalks with cracks/potholes. Although various studies have been proposed to recognize such challenges, they mainly depend on RGB images or IMU sensors, which are sensitive to outdoor conditions such as low illumination, bad weather, and unavoidable vibrations, resulting in unsatisfactory and unstable performance.

A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications.

The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring.

Schisandrae Fructus ethanol extract attenuates particulate matter 2.5-induced inflammatory and oxidative responses by blocking the activation of the ROS-dependent NF-κB signaling pathway.

Background/objectives: Schisandrae Fructus, the fruit of Baill., has traditionally been used as a medicinal herb for the treatment of various diseases, and has proven its various pharmacological effects, including anti-inflammatory and antioxidant activities. In this study, we investigated the inhibitory effect of Schisandrae Fructus ethanol extract (SF) on inflammatory and oxidative stress in particulate matter 2.