Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Background: The aim of this study is to evaluate the prevalence and associated psychosocial factors of behavioral addictions among school adolescents living in the Gwangju and Jeonnam regions in Korea. Methods: A self-reported survey was conducted from December 4, 2023, to January 31, 2024, including 855 middle and high school students residing in the Gwangju-Jeonnam regions. Aside from the information on demographic characteristics, data on depression, anxiety, Internet gaming addiction, gambling problems, and resilience was obtained. Results: The prevalence of Internet gaming addiction among adolescents was 5.4%, while the prevalence of gambling problems was 3.3%. The male adolescents had a significantly higher risk of behavioral addiction compared with the female adolescents. The logistic regression analysis revealed that male and depression were significant risk factors for Internet gaming addiction. For gambling problems, male was identified as a significant risk factor. Conclusion The findings of this study suggested that the prevalence of behavioral addiction among school adolescents has been relatively higher than that of previous studies, emphasizing the need for community-based prevention and intervention strategies tailored to the sex difference and psychological factors associated with adolescent behavioral addictions.

Objective: As the demand for community mental health services continues to grow, the need for well-equipped and organized services has become apparent. This study aimed to optimize the roles and infrastructure of mental health services, by establishing, among other initiatives, standardized operating models. Methods: The study was conducted in multiple phases from May 12, 2021, to December 29, 2021. Stakeholders within South Korea and metropolitan mental health welfare centers were targeted, but addiction management support centers, including officials, patients, and their families, were integrated as well. A literature review and survey, focus group interviews, a Delphi survey, and expert consultation contributed to comprehensive revisions and improvements of the mental health service model. Results: The proposed model for community mental health welfare centers emphasizes the expansion of personnel and infrastructure, with a focus on severe mental illnesses and suicide prevention. The model for metropolitan mental health welfare centers delineates essential tasks in areas such as project planning and establishment, community research, and education about severe mental illnesses. The establishment of a 24-hour emergency intervention center was a crucial feature. In the integrated addiction support center model, the need to promote addiction management is defined as an essential task and the establishment of national governance for addiction policies is recommended. Conclusion This study proposed standard operating models for three types of mental health service centers. To meet the increasing need for community care, robust mental health service delivery systems are of primary importance.

Oral lichen planus (OLP) is a chronic inflammatory disease, affecting approximately 0.5% to 2% of the global population. OLP can lead to long-term oral pain, reduced quality of life, with the potential for malignant transformation. Current treatment strategies focus on symptom management and reducing the risk of malignancy. Treatment of OLP is challenging and varies from patient to patient, especially in those who do not respond to corticosteroids. The effectiveness and safety of second-line and third-line treatment options in such cases are continually compared and evaluated, and recently, the application of Janus kinase inhibitors, micro ribonucleic acids, and mesenchymal stem cell-based therapies is being assessed. As a result, the ability of clinicians to select the most appropriate treatment modalities for each patient remains crucial. This review aims to evaluate the efficacy of recent treatment modalities and key considerations to assist clinicians in selecting effective and safe treatment strategies for OLP.

Purpose: This study evaluated the educational impact of an artificial intelligence (AI)–based decision support system for breast ultrasonography (US) on medical professionals not specialized in breast imaging. Methods: In this multi-case, multi-reader study, educational materials, including American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors, were provided alongside corresponding AI results during training. The AI system presented results in the form of AIheatmaps, AI scores, and AI-provided BI-RADS assessment categories. Forty-two readers evaluated the test set in three sessions: the first session (S1) occurred before the educational intervention, the second session (S2) followed education without AI assistance, and the third session (S3) took place after education with AI assistance. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and overall performance, were compared between the sessions. Results: The mean sensitivity increased from 66.5% (95% confidence interval [CI], 59.2% to 73.7%) to 88.7% (95% CI, 84.1% to 93.3%), with a statistically significant difference (P<0.001), and the AUC non-significantly increased from 0.664 (95% CI, 0.606 to 0.723) to 0.684 (95% CI, 0.620 to 0.748) (P=0.300). Both measures were higher in S2 than in S1. The AI-achieved AUC was comparable to that of the expert reader (0.747 [95% CI, 0.640 to 0.855] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.217). Additionally, with AI assistance, the mean AUC for inexperienced readers was not significantly different from that of the expert reader (0.745 [95% CI, 0.660 to 0.830] vs. 0.803 [95% CI, 0.706 to 0.900], P=0.120). Conclusion The mean AUC and sensitivity improved after incorporating AI into breast US education and interpretation. AI systems with high-level performance for breast US can potentially be used as educational tools in the interpretation of breast US images.

Hangovers from alcohol consumption cause symptoms like headaches, nausea, and fatigue, disrupting daily activities and overall well-being. Over time, they can also lead to inflammation and oxidative stress. Effective hangover relief alleviates symptoms, prevents dehydration, and replenishes energy needed for daily tasks. Natural foods considered high in antioxidants and antiinflammatory properties may aid in the hepatic breakdown of alcohol. The study aims to investigate the impact of glutathione or its enriched yeast extract, which is recognized for its antioxidant characteristics, on alcohol metabolism and alleviating hangovers in a rat model exposed to binge drinking. In this study, glutathione and its enriched yeast extract controlled hangover behaviour patterns, including locomotor activity. Additionally, it enhanced the activities of alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) following ethanol ingestion (3 g/kg). Further, the incorporation of glutathione led to an increase in the expression of antioxidant enzymes, such as SOD and catalase, by activating the nuclear erythroid 2-related factor 2 (Nrf2) signaling pathway.This activation reduced the excessive production of reactive oxygen species (ROS) and malondialdehyde. Next, glutathione modulated the activity of cytochrome P450 2E1 (CYP2E1) and the protein expressions of Bax and Bcl2. Besides, in vitro and in vivo investigations with glutathione demonstrated a regulating effect on the pan-s-glutathionylation and its associated protein expression, glutaredoxin 1 (Grx1), glutathione-S-transferase Pi (GST-π), and glutathione reductase (GR). Together, these findings suggest that glutathione or its enriched yeast extract as a beneficial dietary supplement for alleviating hangover symptoms by enhancing alcohol metabolism and its associated Nrf2/Keap1 signalings.

Human rhinovirus (HRV) causes the common cold and exacerbates chronic respiratory diseases, such as asthma and chronic obstructive pulmonary disease. Despite its significant impact on public health, there are currently no approved vaccines or antiviral treatments for HRV infection. Apoptosis is the process through which cells eliminate themselves through the systematic activation of intrinsic death pathways in response to various stimuli. It plays an important role in viral infections and serves as a key immune defense mechanism in the interactions between viruses and the host. In the present study, we investigated the antiviral effects of quercetin-3-methyl ether, a flavonoid isolated from Serratula coronata, on human rhinovirus 1B (HRV1B). Quercetin-3-methyl ether significantly inhibited HRV1B replication in HeLa cells in a concentration-dependent manner, thereby reducing cytopathic effects and viral RNA levels. Time-course and time-of-addition analyses confirmed that quercetin-3-methyl ether exhibited antiviral activity during the early stages of viral infection, potentially targeting the replication and translation phases. Gene expression analysis using microarrays revealed that pro-apoptotic genes were upregulated in quercetin-3-methyl ether-treated cells, suggesting that quercetin-3-methyl ether enhances early apoptosis to counteract HRV1B-induced immune evasion. In vivo administration of quercetin-3-methyl ether to HRV1B-infected mice significantly reduced viral RNA levels and inflammatory cytokine production in the lung tissues. Our findings demonstrated the potential of quercetin-3-methyl ether as a novel antiviral agent against HRV1B, thereby providing a promising therapeutic strategy for the management of HRV1B infections and related complications.

Purpose: This study aimed to project cancer incidence and mortality for 2025 to estimate Korea’s current cancer burden. Materials and Methods: Cancer incidence data from 1999 to 2022 were obtained from the Korea National Cancer Incidence Database, while cancer mortality data from 1993 to 2023 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observed age-specific cancer rates against their respective years and then by multiplying the projected age-specific rates by the anticipated age-specific population for 2025. A joinpoint regression model was applied to identify significant changes in trends, using only the most recent trend data for predictions. Results: A total of 304,754 new cancer cases and 84,019 cancer deaths are expected in Korea in 2025. The most commonly diagnosed cancer is projected to be thyroid cancer, followed by the colorectal, lung, breast, prostate and stomach cancers. These six cancers are expected to account for 63.8% of the total cancer burden. Lung cancer is expected to be the leading cause of cancer-related deaths, followed by liver, colorectal, pancreatic, stomach, and gallbladder cancers, together comprising 66.6% of total cancer deaths. Conclusion The increasing incidence of female breast cancer and the rise in prostate and pancreatic cancers are expected to continue. As aging accelerates, cancer commonly found in older adults are projected to rise significantly.