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.

Immunosenescence, an age-associated decline in immune function, is increasingly recognized as a central determinant of health and disease in older adults. Characterized by thymic involution, loss of naïve T cells, contraction of T cell receptor diversity, accumulation of senescent and exhausted lymphocytes, and a chronic inflammatory state known as inflammaging, immunosenescence compromises both innate and adaptive immune responses. Immunosenescence contributes to the pathogenesis of diverse age-related diseases. In autoimmune and metabolic diseases, premature accumulation of senescent T cells and impaired regulatory T cell function drive chronic inflammation and tissue damage, while in neurodegenerative diseases, microglial aging and sustained neuroinflammation exacerbate neuronal loss. These findings highlight immunosenescence as a unifying mechanism linking aging to systemic and organ-specific pathologies. Advances in biomarker discovery, including phenotypic markers, telomere attrition, and epigenetic signatures, have enabled the quantitative assessment of immune aging, while emerging therapeutic strategies, such as cytokine modulation, mTOR inhibition, senolytics, and epigenetic reprogramming, show promise in restoring immune competence. Here, we summarize recent research on immunosenescence in various diseases, particularly chronic inflammatory, metabolic, and neurodegenerative diseases, and suggest novel strategies for the development of senolytic drugs.

Pediatric kidney disease has a relatively lower prevalence than do other pediatric conditions and has a notably different etiology from kidney diseases observed in adults. Furthermore, the pediatric population is unique in that they experience ongoing growth and development, distinguishing them from adult patients. Consequently, pediatric patients with kidney disease require more specialized and meticulous nutritional management than do adults. To address this need and promote optimal dietary practices for pediatric patients with kidney disease, pediatric nephrologists from the Korean Society of Pediatric Nephrology and nutritionists from the Korean Society of Clinical Nutrition have collaborated to establish nutritional guidelines specifically tailored to Korean dietary patterns. These guidelines offer detailed, nutrient-specific recommendations covering energy, protein, calcium, phosphorus, and potassium consumption while providing practical, culturally relevant guidance intended to support both pediatric patients and their caregivers.

Purpose: Hereditary spastic paraplegia (HSP) refers to a group of genetic neurodegenerative diseases marked by gradually worsening spasticity and hyperreflexia in the lower extremities. This study aimed to describe the clinical and genetic characteristics of Korean patients with spastic paraplegia. Materials and Methods: We retrospectively reviewed medical records of 69 patients with spastic paraplegia from 54 unrelated families between 2002 and 2024. Genetic, clinical, electrophysiological, and radiological features were comprehensively analyzed. Results: Causative genes were identified in 34 (63%) of 54 unrelated families; SPAST, detected in 26 families, was the most prevalent. Seven novel pathogenic variants were identified. Clinically, the median age of symptom onset was 25 years [14.0–37.0]. Out of 69 patients with spastic paraplegia, 51 (74%) presented with the pure form of spastic paraplegia, which included all patients with SPG4. Spastic gait was a universal feature in all patients. Urinary dysfunction was present in 42 (61%) patients. Additional neurologic manifestations included peripheral neuropathy 9 (13%), cognitive impairment 5 (7%), upper limb weakness 4 (6%), dysarthria 4 (6%), dysphagia 3 (4%), ataxia 3 (4%), and scoliosis 1 (3%). Brain MRI findings demonstrated a thin corpus callosum in two patients with SPG11; all patients with SPG4 had normal findings. Spine MRI revealed spinal cord atrophy in 16 (27%) patients, including 6 (21%) patients with SPG4. Conclusion The study comprehensively reviewed genetic and clinical spectra of spastic paraplegia in Korean patients, emphasizing the predominance of SPAST as the causative gene and underscoring the genetic and phenotypic heterogeneity of spastic paraplegia.

OBJECTIVES: This mixed-methods observational study aimed to examine the temporal relationship between trends in cigarette smoking prevalence and lung cancer mortality and incidence rates, and to estimate the latency period between smoking initiation and lung cancer diagnosis among smokers at the individual level. METHODS: Smoking prevalence data for 1960–2022 were reconstructed using data from the Korea National Health and Nutrition Examination Survey (1998–2022). Lung cancer mortality data (1983–2022) and incidence data (1999–2022) were obtained from Statistics Korea and the Korea Central Cancer Registry. The population latency period was estimated using peak comparison and distributed lag non-linear models. The individual latency period was estimated as the average time interval between age at smoking initiation and age at lung cancer diagnosis using individual-level data from the National Health Insurance Service cohort. RESULTS: In men, smoking prevalence peaked around 1985, whereas lung cancer mortality peaked around 2000 during 1960–2022, indicating a lag time of approximately 15 years. In women, lung cancer mortality peaked in 2002, while smoking prevalence peaked around the same time. The population-level latency period between smoking and lung cancer incidence was estimated to be 15 years after adjustment for age, gender, and year of outcome. The individual latency period was estimated to be 42.6 years (standard deviation [SD], 12.5) in men and 34.4 years (SD, 14.2) in women. Smoking intensity and age at initiation did not appear to shorten the individual latency period. CONCLUSIONS Estimates of the smoking-attributable lung cancer burden should account for historical smoking prevalence from approximately 15 years earlier.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: Carbapenem-resistant Acinetobacter baumannii (CRAB) represents a devastating and growing global threat, calling for new antibiotic treatments. In Korea, the challenge of treating CRAB is compounded by high nosocomial acquisition rates and limited availability of novel antibiotics. Minocycline, a semisynthetic tetracycline derivative, has been proposed as a therapeutic option for CRAB infections. Nonsusceptibility to minocycline may occur through the efflux pump, TetB. The prevalence of tetB in A. baumannii has increased, along with higher minocycline minimum inhibitory concentrations (MICs). We aimed to evaluate minocycline susceptibility rates in clinical strains of CRAB, and the association between tetB carriage and minocycline susceptibility across different genotypes. Materials and Methods: Representative CRAB blood isolates were collected from Asan Medical Center, Seoul.Minocycline susceptibility was assessed using the Clinical and Laboratory Standards Institute (CLSI) breakpoint (≤4 mg/L) and the proposed pharmacokinetics (PK)/pharmacodynamics (PD) breakpoint (≤1 mg/L). Tigecycline was used as a comparator, and its susceptibility breakpoint for Enterobacterales defined by EUCAST was applied (≤0.5 mg/L).The presence of tetB was detected by PCR, and multilocus sequence typing (MLST) was performed using seven housekeeping genes. Results: Of the 160 CRAB blood isolates, 83.8% were susceptible to minocycline by the CLSI criteria, and 50.6% were PK-PD susceptible by the PK-PD criteria. The minocycline minimum inhibitory concentration (MIC)50 /MIC90 was 1/8 mg/L. tetB was present in 49% of isolates and was associated with a higher minocycline MIC (MIC50/90 2/8 mg/L vs. 1/2 mg/L). No clear correlation was observed between tetB positivity and tigecycline MIC. Nine MLSTs were identified, with significant differences in tetB carriage rates between the major sequence types. Notably, ST191, associated with non-tetB carriage and greater susceptibility to minocycline, declined over the study period (P=0.004), while ST451, associated with tetB carriage, increased. Conclusion tetB was present in 49% of CRAB isolates and was associated with higher MICs and non-susceptibility by both CLSI and PK-PD criteria. However, absence of tetB was not a reliable predictor of minocycline PK-PD susceptibility. Additionally, shifts over time towards genotypes with reduced minocycline susceptibility were observed. Further research is needed to correlate these findings with clinical outcomes and identify additional resistance mechanisms.

Background: and Purpose This study evaluated the diagnostic utility of an anti-signal-recognition particle 54 (anti-SRP54) antibody-based enzyme-linked immunosorbent assay (ELISA) as well as the clinical, serological, and pathological characteristics of patients with SRP immune-mediated necrotizing myopathy (IMNM). Methods: We evaluated 87 patients with idiopathic inflammatory myopathy and 107 healthy participants between January 2002 and December 2023. The sensitivity and specificity of the ELISA for anti-SRP54 antibodies were assessed, and the clinical profiles of patients with antiSRP54 antibodies were determined. Results: The ELISA for anti-SRP54 antibodies had a sensitivity and specificity of 88% and 99%, respectively, along with a test–retest reliability of 0.92 (p<0.001). The 32 patients diagnosed with anti-SRP IMNM using a line-blot immunoassay included 28 (88%) who tested positive for anti-SRP54 antibodies using the ELISA, comprising 12 (43%) males and 16 (57%) females whose median ages at symptom onset and diagnosis were 43.0 years and 43.5 years, respectively. Symptoms included proximal muscle weakness in all 28 (100%) patients, neck weakness in 9 (32%), myalgia in 15 (54%), dysphagia in 5 (18%), dyspnea in 4 (14%), dysarthria in 2 (7%), interstitial lung disease in 2 (7%), and myocarditis in 2 (7%). The median serum creatine kinase (CK) level was 7,261 U/L (interquartile range: 5,086–10,007 U/L), and the median anti-SRP54 antibody level was 2.0 U/mL (interquartile range: 1.0–5.6 U/mL). The serum CK level was significantly higher in patients with coexisting anti-Ro-52 antibodies. Conclusions This study has confirmed the reliability of the ELISA for anti-SRP54 antibodies and provided insights into the clinical, serological, and pathological characteristics of South Korean patients with anti-SRP IMNM.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.