Objective: To develop QingNangTCM, a specialized large language model (LLM) tailored for expert-level traditional Chinese medicine (TCM) question-answering and clinical reasoning, addressing the scarcity of domain-specific corpora and specialized alignment. Methods: We constructed QnTCM_Dataset, a corpus of 100 000 entries, by integrating data from ShenNong_TCM_Dataset and SymMap v2.0, and synthesizing additional samples via retrieval-augmented generation (RAG) and persona-driven generation. The dataset comprehensively covers diagnostic inquiries, prescriptions, and herbal knowledge. Utilizing P-Tuning v2, we fine-tuned the GLM-4-9B-Chat backbone to develop QingNangTCM. A multi-dimensional evaluation framework, assessing accuracy, coverage, consistency, safety, professionalism, and fluency, was established using metrics such as bilingual evaluation understudy (BLEU), recall-oriented understudy for gisting evaluation (ROUGE), metric for evaluation of translation with explicit ordering (METEOR), and LLM-as-a-Judge with expert review. Qualitative analysis was conducted across four simulated clinical scenarios: symptom analysis, disease treatment, herb inquiry, and failure cases. Baseline models included GLM-4-9B-Chat, DeepSeek-V2, HuatuoGPT-II (7B), and GLM-4-9B-Chat (freeze-tuning). Results: QingNangTCM achieved the highest scores in BLEU-1/2/3/4 (0.425/0.298/0.137/0.064), ROUGE-1/2 (0.368/0.157), and METEOR (0.218), demonstrating a balanced and superior normalized performance profile of 0.900 across the dimensions of accuracy, coverage, and consistency. Although its ROUGE-L score (0.299) was lower than that of HuatuoGPT-II (7B) (0.351), it significantly outperformed domain-specific models in expert-validated win rates for professionalism (86%) and safety (73%). Qualitative analysis confirmed that the model strictly adheres to the “symptom-syndrome-pathogenesis-treatment” reasoning chain, though occasional misclassifications and hallucinations persisted when dealing with rare medicinal materials and uncommon syndromes. Conclusion Combining domain-specific corpus construction with parameter-efficient prompt tuning enhances the reasoning behavior and domain adaptation of LLMs for TCM-related tasks. This work provides a technical framework for the digital organization and intelligent utilization of TCM knowledge, with potential value for supporting diagnostic reasoning and medical education.

Purpose: To report a case of primary orbital apocrine adenocarcinoma in a patient diagnosed with gastric adenocarcinoma.Case summary: A 43-year-old male patient diagnosed with gastric adenocarcinoma 3 months prior presented with a gradually enlarging mass in the lower medial aspect of the left eye for 1 year. At initial examination, his best-corrected visual acuity was 1.0 in both eyes and slit-lamp examination revealed no abnormalities. The left eye exhibited proptosis with restricted adduction, abduction, and depression. Orbital magnetic resonance imaging revealed an irregularly shaped mass measuring 56 × 46 × 38 mm in the left inferomedial orbit, invading the medial and inferior rectus muscles. Histopathological analysis of the orbital tumor revealed abundant eosinophilic cytoplasm. Immunohistochemical staining was positive for androgen receptor, and gross cystic disease fluid protein-15, both of which were negative in the gastric adenocarcinoma tissue. Additionally, the mucin phenotypes observed differed from those in the gastric cancer tissue. Based on these findings, the patient was diagnosed with primary orbital apocrine adenocarcinoma. Conclusions Primary orbital apocrine adenocarcinoma is an extremely rare malignant tumor. In patients with gastric cancer, malignant tumors in the orbit can arise as either primary neoplasms or metastatic lesions. Therefore, accurate diagnosis through immunohistochemical staining is essential to determine the appropriate treatment approach.

Objectives: In alignment with the World Health Organization’s goal of eliminating hepatitis C, this study assessed the current treatment status and reasons for non-treatment among patients with hepatitis C in Jeonbuk State, Republic of Korea, to inform strategies for improving care engagement. Methods: Among 311 individuals diagnosed with hepatitis C and reported through the NationalNotifiable Infectious Disease Surveillance system between January 2023 and June 2024, 208 patients were surveyed after excluding those who had died or could not be contacted.Statistical analyses included the chi-square test, the Cochran-Armitage test for trend, and logistic regression. Results: Overall, 116 participants (55.8%) reported having received antiviral therapy. Among the 92 untreated individuals, the most common reason for non-treatment was the absence of symptoms (n = 23; 25.0%), followed by the burden of drug costs (n = 21; 22.8%). Conclusion These findings highlight suboptimal treatment uptake and key barriers that may hinder progress toward hepatitis C elimination. Expanding screening and strengthening linkage-to-care strategies, while addressing financial barriers, will be essential to achievingnational elimination targets.

Background: Laser procedures are integral to dermatologic practice, yet safety measures- particularly regarding ocular protection and plume control- are poorly studied in real-world settings. Objective: To evaluate current practices in eye protection, infection control, and occupational risk awareness among Korean dermatologists performing laser treatments. Methods: A cross-sectional survey was conducted among board-certified dermatologists at the 2024 Korean Society for Dermatologic Laser Surgery meeting. The questionnaire covered demographics, laser frequency, use of goggles and masks, infection control strategies, ophthalmologic monitoring, and history of warts or cancer. Results: Seventy-nine respondents completed the survey. All reported using protective goggles, but only 26.6% and 22.8% did so for CO 2 and erbium-doped yttrium aluminium garnet lasers, respectively. Only 24.1% underwent regular eye exams, and 13.9% reported eye conditions after starting laser practice. While 89.9% used masks, 40.8% used dental masks, which are inadequate for plume protection. Suction devices were used by 94.9%, though performance specifications were unclear. Warts were reported by 46.8% of respondents; two reported cancer diagnoses after initiating laser work. Conclusion Despite high overall adherence to basic safety practices, critical gaps remain. Our findings highlight the need for standardized guidelines and long-term occupational health monitoring to ensure safe laser practice.

Background: Rosacea is a chronic inflammatory skin disorder characterized by erythema, papules, ocular symptoms, and heightened sensitivity. Patients with neurogenic symptoms such as burning or stinging remain particularly difficult to manage. Current guidelines often underrepresent energy-based devices (EBDs), pigmentary sequelae, psychosocial burden, and ocular comorbidities. Objective: To examine Korean dermatologists’ expert perspectives on rosacea management, focusing on skin sensitivity, neurogenic symptoms, pigmentary changes, psychosocial impact, ocular involvement, and EBD use. Methods: A web-based, 29-item survey was administered to 25 board-certified Korean dermatologists (May–June 2025). Quantitative and qualitative responses were analyzed. Results: Erythematotelangiectatic and papulopustular phenotypes with sensitivity skin predominated. EBDs (pulsed dye laser, intense pulsed light) were frequently used but limited by cost and sensitivity issues. Neurogenic symptoms were recognized but rarely treated with neuromodulators. Post-inflammatory hyperpigmentation was infrequent, yet monitoring was inconsistent.Psychosocial and ocular aspects were acknowledged but seldomly systematically addressed.Respondents expressed interest in emerging adjunctive treatments such as cold plasma, skin boosters, and holistic care approaches. Conclusion Korean dermatologists adopt individualized strategies for rosacea, yet practice gaps remain regarding neurogenic symptoms, pigmentary complications, and psychosocial and ocular comorbidities. Findings support the need for updated multidisciplinary, phenotype-driven guidelines aligned with real-world practice.

Background: Copy number variations (CNVs) play an important role in human genetic disorders. Detection of exon-level CNVs is crucial for accurate clinical diagnosis. The CytoScan XON Array, a high-resolution microarray, was recently developed to detect exonic CNVs of various genes. Methods: We evaluated the clinical performance of the CytoScan XON Array using 59 patient samples with previously identified CNVs, confirmed via methods including multiple ligation-dependent probe amplification (MLPA), gene-dose PCR, and mRNA assay. Concordance between CytoScan XON and orthogonal methods was evaluated in target regions, and diagnostic utility was compared with that of genome sequencing (GS)-based CNV calling tools through analysis of false-positive CNVs in non-target genomic regions. Results: For target regions, the CytoScan XON Array achieved concordance rates of 89.8% and 92.5% at the exon and gene levels, respectively, for all CNV calls. Concordance was higher for multi-exon CNVs (100%) than that for single-exon CNVs (82.6%, P = 0.03). For non-target regions, false-positive CNV calls were reduced to fewer than 0.01 per gene per person through filtering strategies. The array exhibited false-positive detection rates within dosage-sensitive genes comparable with those of GS-based tools. Conclusions The CytoScan XON Array, a reliable tool for detecting exon-level CNVs in target regions, can serve as a complementary approach to GS-based CNV calling tools for genome-wide CNV screening with high resolution. However, its performance for single-exon CNVs requires further optimization. Cross-validation with GS-based CNV calling tools is recommended to improve diagnostic accuracy.

Purpose: This study aimed to address the shift toward competency-based education and the planned 2028 “Integrated Nursing” National Licensing Examination (NLE), this study aimed to establish structural alignment among NLE domains, the seven integrated nursing competencies (INCs), and curriculum goals, with a particular focus on implementing symptom-based clinical reasoning (SBCR). Methods: This Delphi-based methodological study included seven content experts for content validity index (CVI) assessment and 24 nursing education experts who participated in a consensus workshop. The item-level CVI and the scale-level CVI/average were calculated to confirm the linkage between INCs and NLE domains. In addition, qualitative analysis of workshop materials and meeting records was conducted to derive 10 integrated learning topics and to develop an SBCR educational model for the key symptom of headache, grounded in Miller’s Clinical Competence Pyramid (levels 2–4). Results: The analysis confirmed the validity of integrating the INCs within the overall curriculum structure. The resulting framework delineates staged learning objectives and core clinical questions designed to systematically enhance clinical reasoning, promote safe nursing practice, and support professional reflection within a unified curriculum. Conclusion This study provides a practical foundation for nursing curriculum redesign by facilitating a transition from fragmented, subject-based instruction to a holistic, patient-centered SBCR model. This approach aligns with the requirements of the integrated NLE and is expected to contribute to meaningful improvements in actual clinical competency.

Purpose: This study analyzed public discourse on nurse retention through YouTube comments posted between 2018 and 2024 to examine how retention issues are collectively framed in online public spheres, thereby extending individual-level retention research to societal-level discourse analysis. Methods: Comments were collected from 226 YouTube videos uploaded between January 2015 and December 2024, identified using search terms that combined “nurse” with retention-related keywords. After duplicates and comments posted outside the study period were removed, 32,399 comments were analyzed using structural topic modeling with year and number of likes as covariates. Topic correlation network analysis with community detection was used to identify discourse coalitions. Results: Fourteen substantive topics and one noninterpretive topic emerged, spanning individual coping strategies, organizational workplace issues, and systemic policy structures. “International nursing migration and career pathways” (12.8%) and “Disputes regarding the scope of practice among professionals” (11.4%) were the most prevalent topics. Temporal analysis revealed discourse shifts consistent with focusing events theory: COVID-19 (coronavirus disease 2019) activated structural critique frames while suppressing career mobility discourse; the 2022 Nursing Law followed an issue-attention cycle pattern; and the 2024 medical school quota expansion embedded retention discourse within broader healthcare policy debates. Network analysis identified two discourse communities, professional identity and structural exploitation, with international migration serving as a bridging frame across both. Conclusion Public discourse framed nurse retention as a systemic and structural issue rather than as an expression of individual professional rejection. These collective framing patterns complement traditional survey-based research and may inform policy design by identifying which frames achieve public resonance and where discourse fragmentation may challenge policy implementation.