Higher Physical Activity is Associated with Reduced Lower Urinary Tract Symptoms in Korean Men.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS.

Blood urea nitrogen to albumin ratio is associated with cerebral small vessel diseases.

Blood urea nitrogen (BUN) to albumin ratio (BAR) is a comprehensive parameter that reflects renal, inflammatory, nutritional, and endothelial functions. BAR has been shown to be associated with various cancers, pneumonia, sepsis, and pulmonary and cardiovascular diseases; however, few studies have been conducted on its association with cerebrovascular diseases. In this study, we evaluated the association between BAR and cerebral small vessel disease (cSVD) in health check-up participants.

Monocyte to high-density lipoprotein cholesterol ratio is associated with cerebral small vessel diseases.

Background: Inflammation is a major pathological mechanism underlying cerebrovascular disease. Recently, a new inflammatory marker based on the ratio between monocyte count and high-density lipoprotein (HDL) cholesterol has been proposed. In this study, we evaluated the relationship between monocyte-to-HDL cholesterol ratio (MHR) and cerebral small vessel disease (cSVD) lesions in health check-up participants.

Effect of anti-obesity agent HSG4112 on overweight and obese patients following 12 weeks of oral treatment: a study protocol for a randomised, double-blind, placebo-controlled, parallel-group, phase 2a clinical trial.

Background: Glaceum Inc. has proposed HSG4112, a structural analogue of glabridin, as a novel anti-obesity compound. Animal studies and phase I human trials have shown that HSG4112 improves energy consumption, normalises weight, and is safe and drug-resistant.

Association between long-term air pollution exposure and insulin resistance independent of abdominal adiposity in Korean adults.

Significant associations between air pollution (AP) and insulin resistance (IR) have been reported in limited populations or certain patient groups, but few studies have addressed this association in the general population, especially in Asians. Although abdominal fat is a major contributor to IR, previous studies have not fully controlled for its effect in the association between AP and IR. We investigated the association between exposure to AP and IR in Korean adults in the general population and whether this association is maintained even after controlling for the effects of abdominal fat, particularly visceral fat.

The relationship between smoking cigarettes and metabolic syndrome: A cross-sectional study with non-single residents of Seoul under 40 years old.

Introduction: Young adults receive health screenings at lower rates than other age groups, and it may be difficult to detect diseases in the early stages for this group. We examined differences in health status relative to smoking in a young age group using the results of health screenings conducted in engaged and newly married couples in a cross-sectional database.

Methods: The participants in this study were 808 young adults who visited a municipal hospital health screening center from July 2017 to March 2019.

Prediction Models for the Clinical Severity of Patients With COVID-19 in Korea: Retrospective Multicenter Cohort Study.

Background: Limited information is available about the present characteristics and dynamic clinical changes that occur in patients with COVID-19 during the early phase of the illness.

Objective: This study aimed to develop and validate machine learning models based on clinical features to assess the risk of severe disease and triage for COVID-19 patients upon hospital admission.

Methods: This retrospective multicenter cohort study included patients with COVID-19 who were released from quarantine until April 30, 2020, in Korea.

EEG-Based Estimation on the Reduction of Negative Emotions for Illustrated Surgical Images.

Electroencephalogram (EEG) biosignals are widely used to measure human emotional reactions. The recent progress of deep learning-based classification models has improved the accuracy of emotion recognition in EEG signals. We apply a deep learning-based emotion recognition model from EEG biosignals to prove that illustrated surgical images reduce the negative emotional reactions that the photographic surgical images generate.

Emotion Variation from Controlling Contrast of Visual Contents through EEG-Based Deep Emotion Recognition.

Visual contents such as movies and animation evoke various human emotions. We examine an argument that the emotion from the visual contents may vary according to the contrast control of the scenes contained in the contents. We sample three emotions including positive, neutral and negative to prove our argument.

Distinguishing Emotional Responses to Photographs and Artwork Using a Deep Learning-Based Approach.

Visual stimuli from photographs and artworks raise corresponding emotional responses. It is a long process to prove whether the emotions that arise from photographs and artworks are different or not. We answer this question by employing electroencephalogram (EEG)-based biosignals and a deep convolutional neural network (CNN)-based emotion recognition model.

Adaptive reconstruction of pipe-shaped human organs from 3D ultrasonic volume.

In this paper, we introduce an adaptive scheme for reconstructing pipe-shaped human organs from the volume data acquired by 3D ultrasonic devices. No other methods but the contour-based scheme was used in the process of reconstructing the volume data into a 3D polygonal surface. In the first step, the algorithm extracts contours from the sampled slices of the volume data using the modified radial gradient method, in which the points are sampled on the boundary of the region of interest by radiating rays and connected through making use of the chain code algorithm.