Purpose: This study aimed to develop and evaluate the effectiveness of the Trauma-nursing Education and Skill Support (TESS) program based on the ADDIE model (Analysis, Design, Development, Implementation, Evaluation model). The program was designed to enhance trauma nurses’ clinical competencies, including trauma-related knowledge, self-efficacy, and problem-solving ability, through the integration of theoretical education and simulation-based practice. Methods: A quasi-experimental study using a non-equivalent control group pretest–posttest design was conducted. Participants included 108 trauma nurses from regional trauma centers, military trauma centers, and emergency care facilities, who were assigned to an experimental group (n=52) or a control group (n=56). The TESS program consisted of a 2-day, 14-hour blended-learning course that included eight lecture sessions and four simulation-based practice stations. Data were collected at baseline, immediately after the intervention, and at 6 months using validated instruments measuring trauma-related knowledge, self-efficacy, and problem-solving ability. Two-way repeated-measures analysis of variance was used for data analysis. Results: The experimental group demonstrated significant improvements in trauma-related knowledge, self-efficacy, and problem-solving ability compared with baseline (all p<.001). These improvements were sustained at 6 months, although trauma-related knowledge scores showed a slight decline compared with immediate posttest levels. Between-group analyses confirmed significant group-by-time interaction effects for all outcomes: trauma-related knowledge (η2=0.12, p<.001), self-efficacy (η2=0.09, p=.002), and problem-solving ability (η2=0.08, p=.003). Conclusion The TESS program effectively enhanced trauma nurses’ trauma-related knowledge, self-efficacy, and problem-solving ability, with effects sustained for up to 6 months. Incorporating blended learning and simulation-based training into standardized trauma nursing education may strengthen clinical competencies and ultimately contribute to improved patient outcomes.

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: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Background: and Purpose The National Brain Biobank of Korea (NBBK) is a brain bank consortium supported by the Korea Disease Control and Prevention Agency and the Korea National Institute of Health, and was launched in 2015 to support research into neurodegenerative disease dementia (NDD). This study aimed to introduce the NBBK and describes clinicopathological correlations based on analyses of data collected from the NBBK. Methods: Four hospital-based brain banks have been established in South Korea: Samsung Medical Center Brain Bank (SMCBB), Seoul National University Hospital Brain Bank (SNUHBB), Pusan National University Hospital Brain Bank (PNUHBB), and Myongji Hospital Brain Bank (MJHBB). Clinical and pathological data were collected from these brain banks using standardized protocols. The prevalence rates of clinical and pathological diagnoses were analyzed in order to characterize the clinicopathological correlations. Results: Between August 2016 and December 2023, 185 brain specimens were collected and pathologically evaluated (SNUHBB: 117; PNUHBB: 27; SMCBB: 34; MJHBB: 7). The age at consent was 70.8±12.6 years, and the age at autopsy was 71.7±12.4 years. The four-most-common clinical diagnoses were Alzheimer’s disease (AD) dementia (20.0%), idiopathic Parkinson’s disease (15.1%), unspecified dementia (11.9%), and cognitively unimpaired (CU) (11.4%).Most cases of unspecified dementia had a pathological diagnosis of central nervous system (CNS) vasculopathy (31.8%) or AD (31.8%). Remarkably, only 14.2% of CU cases had normal pathological findings. The three-most-common pathological diagnoses were AD (26.5%), CNS vasculopathy (14.1%), and Lewy body disease (13.5%). Conclusions These clinical and neuropathological findings provide a deeper understanding of the mechanisms underlying NDD in South Korea.

Purpose: Cone beam computed tomography (CBCT) is widely used to evaluate the temporomandibular joint (TMJ). For the three-dimensional (3D) assessment of the TMJ, segmentation of the mandibular condyle and articular fossa is essential. This study aimed to perform deep learning-based 3D segmentation of the mandibular condyle on CBCT images and evaluate the performance of the segmentation. Methods: CBCT scan data from 99 patients (mean age: 53.3±19.2 years) diagnosed with TMJ disorders were analyzed. From the CBCT images, sagittal, coronal, and axial planes showing the mandibular condyle were selected and combined to form two-dimensional (2D) images. The U-Net deep learning model was used to exclusively segment the mandibular condyle area from the 2D images. From these results, 3D images of the mandibular condyle were reconstructed. Accuracy, precision, recall, and the Dice coefficient were calculated to appraise segmentation performance in each plane. Results: The average Dice coefficient was 0.92 for the coronal and axial planes and 0.82 for the sagittal plane. The CBCT image-based segmentation performance of the mandibular condyle in the coronal and axial planes exceeded that in the sagittal plane. The sharpness and uniformity of the 2D images affected segmentation performance, with segmentation errors more likely occurring in non-uniform images. Certain segmentation errors were corrected through software processing. Finally, the segmented mandibular condyle images were applied to the CBCT data to reconstruct a 3D TMJ model. Conclusions Mandibular condyle 3D segmentation on CBCT images using U-Net may help evaluate and diagnose TMJ disorders. The proposed segmentation method may assist clinicians in efficiently analyzing CBCT images, particularly in cases involving anatomical abnormalities.

The gut microbiome plays an essential role in host immune responses, including allergic reactions. However, commensal gut microbiota is extremely sensitive to antibiotics and excessive usage can cause microbial dysbiosis. Herein, we investigated how changes in the gut microbiome induced by ampicillin affected the production of IgG1 and IgG2a antibodies in mice subsequently exposed to Anisakis pegreffii antigens. Ampicillin treatment caused a notable change in the gut microbiome as shown by changes in both alpha and beta diversity indexes. In a 1-dimensional immunoblot using Anisakis-specific anti-mouse IgG1, a 56-kDa band corresponding to an unnamed Anisakis protein was detected using mass spectrometry analysis only in ampicillin-treated mice. In the Anisakis-specific anti-mouse IgG2a-probed immunoblot, a 70-kDa band corresponding to heat shock protein 70 (HSP70) was only detected in ampicillin-treated and Anisakis-immunized mice. A 2-dimensional immunoblot against Anisakis extract with immunized mouse sera demonstrated altered spot patterns in both groups. Our results showed that ampicillin treatment altered the gut microbiome composition in mice, changing the immunization response to antigens from A. pegreffii. This research could serve as a basis for developing vaccines or allergy immunotherapies against parasitic infections.