BACKGROUND/OBJECTIVES: Lutein, a dietary carotenoid, plays a crucial role in protecting eye health as an anti-inflammatory agent and antioxidant. Green leafy vegetables constitute a major source of lutein; however, comparative studies on different consumption methods are limited. Therefore, this study aimed to evaluate the bioavailability of lutein from lutein-rich foods, namely, raw vegetables and raw vegetable juice. SUBJECTS/METHODS: In this study, 18 adults were recruited. They were randomly divided into three groups: commercial lutein supplement (LUT, 20 mg), raw vegetable (RV), and raw vegetable juice (RVJ) groups. Blood was collected at 0-, 4-, 6-, 8-, 12-, 24-, and 30-h intervals after the consumption of each test meal. Participants’ serum lutein levels were analyzed using high-performance liquid chromatography (HPLC). Considering lutein’s wellestablished anti-inflammatory properties, changes in inflammatory status were assessed by measuring serum high-sensitivity C-reactive protein (hs-CRP) levels. Furthermore, urinary metabolomic profiling was conducted using 1 H nuclear magnetic resonance spectroscopy to evaluate metabolic alterations. RESULTS: After consuming each lutein-rich food, participants’ blood lutein levels were analyzed, and the serum concentration peaked at 12 h (0.37 ± 0.13 μg/mL), 24 h (0.61 ± 0.18 μg/mL), and 30 h (0.42 ± 0.16 μg/mL) after RV, LUT, and RVJ consumption, respectively.Additionally, hs-CRP levels decreased following lutein-rich food consumption. Twelve hours after consumption, hs-CRP levels decreased to 0.81 and 0.83 mg/L in the RV and RVJ groups, respectively. Twenty-four hours after consumption, they further decreased to 0.68 and 0.74 mg/L in the LUT and RVJ groups, respectively. Thirty hours after consumption, a reduction to 0.61 mg/L was observed in the RVJ group. Furthermore, after consuming each luteinrich food, N-acetyl glycoprotein levels decreased at 24 h, reflecting metabolic alterations potentially associated with lutein metabolism. CONCLUSION These findings suggest that the short-term consumption of lutein-rich foods, regardless of their type or source, potentially yields health benefits.

Objectives: . In this study, we investigated the neurophysiological impact of active noise cancellation (ANC) technology on auditory–cognitive processing and listening effort, addressing a critical gap in the literature on ANC efficacy. Although ANC is increasingly adopted in contemporary devices, its influence on underlying neurophysiological mechanisms remains underexplored. Given that current assessment approaches rely predominantly on subjective measures, we employed a multi-condition experimental design integrating subjective self-reports with electroencephalographic assessments, thereby providing a more comprehensive evaluation of ANC’s capacity to mitigate cognitive load. Methods: . Thirty participants underwent comprehensive audiological testing and cognitive event-related potential recordings during an auditory oddball paradigm to elucidate the efficacy of ANC functionality and its impact on cognitive processing, as indexed by the P3 component. Functional connectivity was quantified using the source-localized weighted phase-lag index, and graph-theory-based network analysis was applied to assess changes in neural efficiency under noisy conditions with and without ANC activation. Results: . The analyses revealed significant alterations in low-β–band functional architecture across the central executive, dorsal attention, salience, and default mode networks during effortless listening with ANC enabled, compared with the effortful listening condition. Subjective listening effort correlated with network efficiency in the left posterior middle frontal gyrus, dorsal anterior cingulate cortex, and inferior parietal lobule during ANC-aided effortless listening tasks. Conclusion . Our findings suggest that ANC activation significantly reduces neural processing demands across key cognitive networks during effortless listening. These results reinforce the role of ANC in alleviating cognitive load and enhancing neural efficiency in auditory–cognitive processing. Furthermore, the findings provide empirical support to inform evidence-based noise mitigation strategies in both clinical and ecological contexts.

Metaverse-based mental health interventions have recently emerged as an extension of telepsychiatry, digital therapeutics (DTx), and virtual reality (VR)–based treatments for children and adolescents. The coronavirus disease 2019 pandemic accelerated the adoption of remote psychological assessment and intervention, raising critical questions regarding their clinical validity, developmental appropriateness, and long-term applicability in youth populations. Accumulating evidence has demonstrated that remote assessments and internet-based interventions can achieve clinical outcomes comparable to face-to-face approaches in selected domains, particularly anxiety, depression, and social communication difficulties. In parallel, immersive technologies such as VR and metaverse-based platforms have been applied to exposure-based interventions, social skills training, and emotion regulation in controlled and repeatable environments. This narrative review examined 48 empirical and review studies on telepsychiatry, internet-based cognitive behavioral therapy, DTx, VR, and metaverse-based interventions for children and adolescents. Neurobiological mechanisms relevant to fear extinction, executive function, emotion regulation, and social cognition were critically reviewed. In addition, real-world implementation experiences from a hospital-based Wee Center in Korea were integrated to evaluate feasibility within school-linked mental health services. The findings suggested that metaverse-based counseling should not be conceptualized as a stand-alone replacement for face-to-face treatment, but rather as a complementary, hybrid platform linking remote screening, structured digital intervention, and in-person clinical care. While current evidence supported feasibility and conditional clinical utility, further longitudinal, controlled, and cost-effectiveness studies were required to establish its role in pediatric mental health.

Objective: To identify clinical factors associated with in-hospital mortality among patients presenting to the emergency department (ED) with nontraumatic myocardial injury. Methods: This retrospective observational study included adult patients who visited a single ED from January to December 2022 and had elevated high-sensitive troponin I levels above the 99th percentile. Patients with trauma, cardiac arrest, transfers, or do-not-resuscitate status were excluded. Data on the demographics, vital signs, mental status, comorbidities, and final ED diagnoses were analyzed using multivariable logistic regression analysis. Results: Among 989 patients, 117 (11.8%) died during hospitalization. The respiratory rate ≥25/min (adjusted odds ratio [aOR], 5.39; 95% confidence interval [CI], 1.65-6.59), respiratory rate 21-24/min (aOR, 3.30; 95% CI, 2.64-11.02), and SpO2 <91% (aOR, 5.47; 95% CI, 2.73-10.95) were significantly associated with mortality. Comorbidities, including coronary artery disease (aOR, 2.78; 95% CI, 1.47-5.26), respiratory disease (aOR, 2.89; 95% CI, 1.18-7.15), and malignancy (aOR, 2.91; 95% CI, 1.18-7.15), were also independent predictors. Compared to a type 1 myocardial infarction, the final ED diagnoses of infectious diseases (aOR, 31.88; 95% CI, 11.59-87.72), neoplasms (aOR, 6.71; 95% CI, 2.51-17.94), and cerebrovascular diseases (aOR, 4.76; 95% CI, 1.75-11.46) were associated with higher mortality. Conclusion In patients with nontraumatic myocardial injury presenting to the ED, respiratory abnormalities, coronary artery diseases, respiratory diseases and malignancy were independently associated with in-hospital mortality, while final ED diagnoses of infection, neoplasm, and cerebrovascular disease were associated with a higher risk of mortality compared to type 1 myocardial infarction.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Reliable preclinical models for assessing drug-induced cardiotoxicity are essential to reduce the high rate of drug withdrawals during development. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as a promising platform for such assessments due to their expression of cardiacspecific ion channels and electrophysiological properties. In this study, we investigated the effects of eight arrhythmogenic drugs—E4031, nifedipine, mexiletine, JNJ303, flecainide, moxifloxacin, quinidine, and ranolazine—on hiPSC-CMs derived from both healthy individuals and a long QT syndrome (LQTS) patient using multielectrode array systems. The results demonstrated dose-dependent changes in field potential duration and arrhythmogenic risk, with LQTS-derived hiPSC-CMs showing increased sensitivity to hERG channel blockers such as E4031. Furthermore, the study highlights the potential of hiPSC-CMs to model disease-specific cardiac responses, providing insights into genetic predispositions and personalized drug responses.Despite challenges related to the immaturity of hiPSC-CMs, their ability to recapitulate human cardiac electrophysiology makes them a valuable tool for preclinical cardiotoxicity assessments. This study underscores the utility of integrating patientderived hiPSC-CMs with advanced analytical platforms, such as multi-electrode array systems, to evaluate drug-induced electrophysiological changes. These findings reinforce the role of hiPSC-CMs in drug development, facilitating safer and more efficient screening methods while supporting precision medicine applications.

Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. Conclusion Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background and Objectives: This study aimed to investigate the effects of hearing aids (HAs) on reducing symptoms of dizziness in patients with hearing loss (HL) and dizziness. Subjects and Methods: A pre- and post-intervention study was conducted between February 2022 and July 2022 at the outpatient clinic of a tertiary hospital in Seoul, South Korea. Ten participants (four males and six females) with HL and dizziness were recruited. Participants were screened using pure-tone audiometry and visual analog scale scores at baseline. Selected participants underwent the Modified Clinical Test of Sensory Interaction on Balance (mCTSIB) and Korean Dizziness Handicap Inventory (K-DHI) in the unaided state. Thereafter, participants were provided HAs and instructed to use them for at least 6 hours every day. At the 1-month follow-up, all participants were assessed in the aided state using the same tests as at baseline. All tests were performed bilaterally. Results: In the mCTSIB, a significant difference was observed in the foam surface-eyes closed score before (median=2.35) and after (median=2.2) HA use (p=0.049). No significant differences were observed in the K-DHI scores before and after HA use. Conclusions HA use may improve the static and subjective perception of balance in patients with HL and dizziness. Future research should explore the benefits of HAs under various balance conditions such as dynamic balance and gait.