Purpose: Older cancer patients face unique challenges due to age-related physiological changes, increasing their vulnerability to treatment-related toxicities. Geriatric assessment (GA) is a validated tool for optimizing care, yet there is no consensus on integrating geriatric interventions into oncology. This study evaluates the feasibility of a tailored onco-geriatric intervention model incorporating the KG-7 screening tool. Materials and Methods: This prospective study included 30 patients aged ≥ 70 years with solid tumors undergoing adjuvant or palliative chemotherapy. Patients scoring ≤ 5 of KG-7 were eligible. Tailored interventions incorporating KG-7 included polypharmacy, functional status, mobility, nutrition, cognition, emotional well-being, insomnia, social support, and medical problem. KG-7, GA, and quality of life (QoL) were followed at 12 weeks. Results: Participants (median age, 79.5 years) had colon (43.3%), pancreatic (23.3%), or gastric cancer (23.3%). At baseline, most patients showed independent activities of daily living (100%)/instrumental activities of daily living (90%). However, 93.3% had abnormal GA. Particularly, 86.7% were either malnourished or at risk of malnutrition. The most frequently identified intervention needs included polypharmacy (70.0%), nutritional support (60.0%), and emotional well-being (50.0%) with high adherence (100.0%, 88.9%, and 46.7%, respectively). At 12 weeks, KG-7 scores improved in 43.8% of patients, and 69.2% of GA domains were improved. QoL analysis revealed modest improvement in Global Health Status (mean difference, 6.3; p=0.176). One-year survival rates were 92.3% and 79.4% for adjuvant and palliative groups, respectively. Conclusion The onco-geriatric intervention model incorporating KG-7 demonstrated high feasibility and potential to enhance clinical outcomes. Future studies should validate this approach in randomized trials to optimize care for older cancer patients.

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.

Background: There are limited long-term clinical outcome data comparing first-generation (1G) versus second-generation (2G) drug-eluting stents (DES) in patients with single-vessel disease (SVD). We sought to compare the efficacy and safety of 1G- and 2G-DES in SVD patients who underwent successful percutaneous coronary intervention (PCI) over 10 years of clinical follow-up. Methods: A total of 2,312 consecutive patients with SVD who underwent PCI with 1G-DES (paclitaxel- or sirolimus-eluting stents, n = 811) or 2G-DES (zotarolimus [Endeavor, Endeavor Resolute]- or everolimus-eluting stents [Promus Element, Xience], n = 1,082) were enrolled.After propensity score matching, 2 matched groups (538 pairs) were generated. Study endpoints included individual and composite clinical outcomes through 10 years. Results: During the 10-year follow-up, the 2G-DES group had lower incidences of myocardial infarction (MI; hazard ratio [HR], 0.44; 95% confidence interval [CI], 0.22–0.92; P = 0.028) and target lesion revascularization (TLR; HR, 0.54; 95% CI, 0.32–0.91; P = 0.021) than the 1G-DES group. Rates of total death, cardiac death, non-target vessel revascularization, stroke, major adverse cardiac events, and major adverse cardiac and cerebrovascular events were similar between groups. Conclusions In our single-center, all-comer registry, 2G-DES were associated with lower incidence rates of MI and TLR compared to 1G-DES in SVD patients over 10 years of followup, indicating a safer and more durable effect than 1G-DES.

Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

Background: and Purpose To determine the clinical phenotypes, relapse timing, treatment responses, and outcomes of children with relapsing myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Methods: We collected the demographic, clinical, laboratory, and radiological data of patients aged <18 years who had been diagnosed with MOGAD at Seoul National University Children’s Hospital between January 2010 and January 2022; 100 were identified as positive for MOG antibodies, 43 of whom experienced relapse. Results: The median age at onset was 7 years (range 2–16 years). The median number of relapses was 2 (range 1–8), and patients were followed up for a median of 65 months (range 5–214 months). The first relapse was experienced before 3 months from onset by 15 patients (34.9%). The most-common initial phenotypes were acute disseminated encephalomyelitis (n=17, 39.5%) and optic neuritis (ON; n=11, 25.6%). The most-common relapse phenotypes were neuromyelitis optica spectrum disorder (n=9, 20.9%), relapsing ON (n=6, 14.0%), and multiphasic disseminated encephalomyelitis (n=6, 14.0%). Many of the patients (n=18, 41.9%) were not specifically categorized. A high proportion of these patients had non-acute disseminated encephalomyelitis encephalitis. Atypical phenotypes such as prolonged fever or hemiplegic migraine-like episodes were also noted. Mycophenolate mofetil and cyclic immunoglobulin treatment significantly reduced the annual relapse rates. Conclusions Our 43 pediatric patients with relapsing MOGAD showed a tendency toward early relapse and various relapse phenotypes. The overall prognoses of these patients were good regardless of phenotype or response to second-line immunosuppressant treatment.

Objectives: Previous studies have shown that combined interventions involving cognitive training and physical activity are effective in enhancing brain function. This study examined the effects of a dual-task intervention—simultaneously combining cognitive and physical tasks—on the cognitive and physical function of community-dwelling older adults aged 65 years and older. Methods: From July to December 2023, cognitively normal adults aged 65 years or older were recruited through the Jeollabuk-do Regional Dementia Center. Participants completed an eightsession group-based program (60 minutes per session) that combined cognitive training and physical activity. The cognitive functions were evaluated using a neuropsychological test battery, and the physical functions were assessed using the Short Physical Performance Battery (SPPB), before and after the intervention. Results: Of 79 participants, 73 completed the intervention. After the program, significant improvements in orientation, memory, visuoconstruction, naming, total cognitive scores, and performance were observed on the Trail Making Test-Part A and Trail Making Test-Part B (p<0.05 to p<0.001).Physical performance also significantly improved the balance, gait speed, chair-stand ability, and total SPPB scores (p<0.001). Multiple regression analysis showed that lower educational attainment and cohabitation with children were associated with greater cognitive improvements, while antihypertensive medication use was negatively associated, and diabetes medication use was positively associated with cognitive outcomes. Conclusion Simultaneous dual-task–based combined intervention may be an effective strategy for enhancing the cognitive and physical functions in cognitively preserved older adults. Nevertheless, further studies will be needed to explore its long-term effects and underlying neurobiological mechanisms.

Background: Diabetic nephropathy (DN) is a progressive complication among patients with diabetes and the most common cause of end-stage kidney disease. Neutrophil extracellular traps (NETs) are known to play a role in kidney disease, thus this study aimed to determine their role in the development of diabetic kidney disease using diabetic murine models. Results: Protein and histological analyses revealed that db/db mice and streptozotocin DN models expressed no significant NET-related proteins, myeloperoxidase, citrullinated histone H3 (citH3), neutrophil elastase, and lymphocyte antigen 6 complex locus G6D (Ly6G). However, the inflamed individuals in the DN model showed that citH3 and Ly6G were highly deposited in the renal system based on immunohistochemistry images. In vitro, NET treatment did not induce apoptosis in glomerular endothelial and renal tubular epithelial cells. NET inhibition by DNase administration demonstrated no significant changes in cell apoptosis. Conclusions NET-related proteins were only expressed in the DN model with tubulointerstitial inflammation. Our study revealed that NETs are only induced in mice with hyperglycemia-induced inflammation.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.

Purpose: This study explored the feasibility of utilizing a deep learning artificial intelligence (AI) model to detect ileocolic intussusception on grayscale ultrasound images. Methods: This retrospective observational study incorporated ultrasound images of children who underwent emergency ultrasonography for suspected ileocolic intussusception. After excluding video clips, Doppler images, and annotated images, 40,765 images from two tertiary hospitals were included (positive-to-negative ratio: hospital A, 2,775:35,373; hospital B, 140:2,477). Images from hospital A were split into a training set, a tuning set, and an internal test set (ITS) at a ratio of 7:1.5:1.5. Images from hospital B comprised an external test set (ETS). For each image indicating intussusception, two radiologists provided a bounding box as the ground-truth label. If intussusception was suspected in the input image, the model generated a bounding box with a confidence score (0-1) at the estimated lesion location. Average precision (AP) was used to evaluate overall model performance. The performance of practical thresholds for the modelgenerated confidence score, as determined from the ITS, was verified using the ETS. Results: The AP values for the ITS and ETS were 0.952 and 0.936, respectively. Two confidence thresholds, CTopt and CTprecision, were set at 0.557 and 0.790, respectively. For the ETS, the perimage precision and recall were 95.7% and 80.0% with CTopt, and 98.4% and 44.3% with CTprecision. For per-patient diagnosis, the sensitivity and specificity were 100.0% and 97.1% with CTopt, and 100.0% and 99.0% with CTprecision. The average number of false positives per patient was 0.04 with CTopt and 0.01 for CTprecision. Conclusion The feasibility of using an AI model to diagnose ileocolic intussusception on ultrasonography was demonstrated. However, further study involving bias-free data is warranted for robust clinical validation.