Background: Bullous pemphigoid (BP) is an autoimmune blistering disease driven by autoantibodies against BP180 and BP230. While type 2 inflammation plays a key role, the precise immune cell alterations and transcriptomic changes remain unclear. Objective: To characterize immune cell composition and transcriptomic changes in BP patients using fluorescence-activated cell sorting (FACS)-based immunophenotyping and RNA sequencing. Methods: A case-control study was conducted on 10 newly diagnosed, treatment-naive BP patients and six healthy controls. Disease activity was assessed using the Bullous Pemphigoid Disease Area Index (BPDAI). Peripheral blood mononuclear cells were isolated for FACS analysis to determine immune cell subsets. RNA sequencing was performed to identify differentially expressed genes (DEGs) and enriched pathways. Statistical analyses included t-tests, Mann-Whitney U tests, and correlation analysis. Results: FACS analysis revealed a reduction in CD4 + T cells, T helper 2 (Th2), and B cells in BP patients (p<0.05), alongside an increase in M2a-like monocytes (p<0.001). RNA sequencing identified 262 DEGs, with secretory leukocyte peptidase inhibitor (SLPI) and transmembrane protein 237 being the most significantly upregulated. Proline-serine-threonine phosphatase interacting protein 2 (PSTPIP2) and SAM domain, SH3 domain, and nuclear localization signals 1 (SAMSN1) positively correlated with BPDAI (p<0.001). Gene ontology analysis highlighted enrichment in inflammatory responses and neutrophil degranulation pathways. Conclusion BP patients show distinct immune dysregulation, including decreased CD4 + T cells, Th2, and B cells, increased M2a-like monocytes, altered gene expression profiles, and correlations between PSTPIP2, SAMSN1 and disease activity. These findings provide insights into pathogenesis and potential therapeutic targets of BP.

Background: Skin rejuvenation has become an increasingly popular noninvasive approach to address age-related changes such as sagging, wrinkles, and skin laxity. Energy-based devices (EBDs) and injectables are widely used, but their application requires careful customization based on individual patient characteristics to optimize outcomes and minimize potential adverse effects. Objective: This study aimed to explore clinical practice patterns among board-certified dermatologists in South Korea, focusing on their strategies for tailoring skin rejuvenation treatments to individual patients, including the integration of EBDs, injectables, and senotherapeutics. Methods: A structured survey comprising 10 questions was administered to 13 experienced dermatologists specializing in skin rejuvenation. The survey covered treatment strategies for patients with varying facial fat volumes, pain management approaches, and the use of EBDs, injectables and senotherapeutics. Results: High-intensity focused ultrasound (HIFU) and radiofrequency (RF) were the most employed EBDs, often combined with injectables for enhanced outcomes. For patients with higher facial fat, HIFU and deoxycholic acid injections were preferred for contouring and tightening. For those with lower facial fat, biostimulatory agents such as poly-D, L-lactic acid and microneedle RF were favored to restore volume and elasticity. Pain management strategies included topical anesthetics and stepwise protocols. Although less commonly used, senotherapeutics were occasionally prescribed for specific conditions, such as melasma and extensive photoaging. Conclusion Dermatologists in South Korea employ a variety of patient-specific strategies for skin rejuvenation, combining various EBDs, injectables, and senotherapeutics. These findings highlight the importance of personalized treatment protocols and the need for further research to optimize treatment efficacy and safety.

Background: This study aimed to develop standard job categories for constructing a job-exposure matrix (JEM) for police officers in South Korea and to evaluate their applicability. Methods: We examined standard job codes related to police personnel management and compared them with job classifications from police publications. Using R Shiny, we developed a web-based search tool for standard codes. A pilot survey of 130 police officers assessed the codes' applicability and relevance to health-related hazardous factors. Results: Eighty-seven standard functional codes used in the police personnel management system POOL were organized into minor categories as the basic units of standard jobs. These were grouped into 20 sub-major categories and further consolidated into 10 major categories to develop the standard job codes. The responses to the standard job codes in the pilot survey were 75% accurate compared with the final expert evaluation results and 99.2% accurate compared with the algorithm-based automatic allocation results. The results of the job-hazardous factor network analysis revealed that the most frequently reported hazardous factor was emotional labor, followed by night shifts and electromagnetic waves. Emotional labor was identified as the top hazardous factor in six out of the nine standard job categories. Conclusions The standard job codes developed in this study were designed in connection with the personnel management system for police officers, making them well-suited for constructing a comprehensive JEM for the entire police force.

A comprehensive list of occupational diseases among farmers is crucial for both compensation and prevention efforts. In Korea, most farmers are self-employed, and some occupational diseases are compensated through farmer safety insurance. However, it is not harmonized with industrial accident compensation insurance and does not adequately reflect the true burden of occupational diseases among farmers. To address this gap, the authors compiled a list of occupational diseases tailored to Korean farmers by reviewing the International Labor Organization’s list of occupational diseases, the Korean Industrial Accident Compensation Insurance List, the occupational disease lists of other countries, and relevant literature on farmers’ work-related diseases.

Background: Shortage of organ donors in the Republic of Korea has become a major problem. To address this, it has been questioned whether heart transplant (HTx) allocation should be modified to reduce priority of older patients. We aimed to evaluate post-HTx outcomes according to recipient age and specific pre-HTx conditions using a nationwide prospective cohort. Methods: We analyzed clinical characteristics of 628 patients from the Korean Organ Transplant Registry who received HTx from January 2015 to December 2020. Enrolled recipients were divided into three groups according to age. We also included comorbidities including ambulatory status. Non-ambulatory status was defined as pre-HTx support with either extracorporeal membrane oxygenation, continuous renal replacement therapy, or mechanical ventilation. Results: Of the 628 patients, 195 were < 50 years, 322 were 50–64 years and 111 were ≥ 65years at transplant. Four hundred nine (65.1%) were ambulatory and 219 (34.9%) were nonambulatory. Older recipients tended to have more comorbidities, ischemic cardiomyopathy, and received older donors. Post-HTx survival was significantly lower in older recipients (P = 0.025) and recipients with non-ambulatory status (P < 0.001). However, in contrast to non-ambulatory recipients who showed significant survival differences according to the recipient’s age (P = 0.004), ambulatory recipients showed comparable outcomes (P = 0.465). Conclusion Our results do not support use of age alone as an allocation criterion. Transplant candidate age in combination with some comorbidities such as non-ambulatory status may identify patients at a sufficiently elevated risk at which suitability of HTx should be reconsidered.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Background: Shortage of organ donors in the Republic of Korea has become a major problem. To address this, it has been questioned whether heart transplant (HTx) allocation should be modified to reduce priority of older patients. We aimed to evaluate post-HTx outcomes according to recipient age and specific pre-HTx conditions using a nationwide prospective cohort. Methods: We analyzed clinical characteristics of 628 patients from the Korean Organ Transplant Registry who received HTx from January 2015 to December 2020. Enrolled recipients were divided into three groups according to age. We also included comorbidities including ambulatory status. Non-ambulatory status was defined as pre-HTx support with either extracorporeal membrane oxygenation, continuous renal replacement therapy, or mechanical ventilation. Results: Of the 628 patients, 195 were < 50 years, 322 were 50–64 years and 111 were ≥ 65years at transplant. Four hundred nine (65.1%) were ambulatory and 219 (34.9%) were nonambulatory. Older recipients tended to have more comorbidities, ischemic cardiomyopathy, and received older donors. Post-HTx survival was significantly lower in older recipients (P = 0.025) and recipients with non-ambulatory status (P < 0.001). However, in contrast to non-ambulatory recipients who showed significant survival differences according to the recipient’s age (P = 0.004), ambulatory recipients showed comparable outcomes (P = 0.465). Conclusion Our results do not support use of age alone as an allocation criterion. Transplant candidate age in combination with some comorbidities such as non-ambulatory status may identify patients at a sufficiently elevated risk at which suitability of HTx should be reconsidered.

Background: Psychological test reports are essential in assessing intellectual functioning, aiding in diagnosing and treating intellectual disability (ID) and attention-deficit/ hyperactivity disorder (ADHD). However, these reports can have several problems because they are diverse, unstructured, subjective, and involve human errors. Additionally, physicians often do not read the entire report, and the number of reports is lower than that of diagnoses. Methods: We developed explainable predictive models for classifying IDs and ADHDs based on written reports to address these issues. The reports of 1,475 patients with IDs and ADHDs who underwent intelligence tests were used for the models. These models were developed by analyzing reports using natural language processing (NLP) and incorporating the physician’s diagnosis for each report. We selected n-gram features from the models’ results by extracting important features using SHapley Additive exPlanations and permutation importance to make the models explainable. Developing the n-gram feature-based original text search system compensated for the lack of human readability caused by NLP and enabled the reconstruction of human-readable texts from the selected n-gram features. Results: The maximum model accuracy was 0.92, and the 80 human-readable texts were restored from four models. Conclusion The results showed that the models could accurately classify IDs and ADHDs, even with a few reports. The models were also able to explain their predictions. The explainability-enhanced model can help physicians understand the classification process of IDs and ADHDs and provide evidence-based insights.

Background: and Purpose We aimed to determine the proportion of Korean patients with early Alzheimer’s disease (AD) who are eligible to receive lecanemab based on the United States Appropriate Use Recommendations (US AUR), and also identify the barriers to this treatment. Methods: We retrospectively enrolled 6,132 patients with amnestic mild cognitive impairment or mild amnestic dementia at 13 hospitals from June 2023 to May 2024. Among them, 2,058 patients underwent amyloid positron emission tomography (PET) and 1,199 (58.3%) of these patients were amyloid-positive on PET. We excluded 732 patients who did not undergo brain magnetic resonance imaging between June 2023 and May 2024. Finally, 467 patients were included in the present study. Results: When applying the criteria of the US AUR, approximately 50% of patients with early AD were eligible to receive lecanemab treatment. Among the 467 included patients, 36.8% did not meet the inclusion criterion of a Mini-Mental State Examination (MMSE) score of ≥22. Conclusions Eligibility for lecanemab treatment was not restricted to Korean patients with early AD except for those with an MMSE score of ≥22. The MMSE criteria should therefore be reconsidered in areas with a higher proportion of older people, who tend to have lower levels of education.