Background: Non-thermal atmospheric pressure plasma (NTAP) generates reactive oxygen species, reactive nitrogen species, and ultraviolet radiation, which can inactivate microorganisms.Onychomycosis treatment is challenging, and its prognosis is poor owing to mixed infections and dermatophytosis. Although NTAP has shown in vitro antifungal effects against dermatophytes and yeast, its efficacy against non-dermatophyte molds (NDMs) and in clinical or nail model studies remains poorly understood. Objective: We evaluated the effects of NTAP on fungi, including NDMs, and infected nail plates. Methods: For the in vitro experiments, Trichophyton rubrum, Candida albicans, Aspergillus fumigatus, and Fusarium oxysporum strains were exposed to NTAP. After NTAP exposure (2,4 and 6 minutes), growth curve, cell viability, and biofilm biomass were assessed by absorbance wavelength of 600 nm, XTT assay, and crystal violet staining, respectively. For the ex vivo experiments, infected nail plates were analyzed using a scanning electron microscope. Results: T. rubrum and C. albicans showed greater growth inhibition with increasing NTAP exposure time, whereas A. fumigatus showed enhanced growth after 6 minutes exposure. Many fungal elements within the subungual hyperkeratosis of the ex vivo specimen were all damaged following NTAP exposure. Conclusion NTAP has antifungal effects on dermatophytes, yeast, and NDMs. We suggest that the intensity and time of NTAP application should be adjusted according to each strain and can be more effective when NTAP directly reaches the hyphae on the nail bed or subungual hyperkeratosis.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Background: With the aging population and advancements in medical care worldwide, the number of older patients with end-stage kidney disease continues to rise. This study aimed to identify factors associated with osteoporosis and osteopenia in older patients undergoing incident hemodialysis and assess their impact on mortality. Methods: We analyzed a large multicenter retrospective cohort of patients aged ≥70 years undergoing incident hemodialysis to identify factors associated with osteoporosis using logistic regression analysis and to assess the association of death with osteoporosis and osteopenia using Cox multivariable analysis. Results: Among 710 patients, 39.0% and 19.6% had osteoporosis and osteopenia, respectively. Osteoporosis was significantly associated with female sex, a history of fractures, and the absence of phosphate binder use. During a median follow-up of 36.8 months, 348 participants (58.8%) died. Mortality rates were the highest in the osteoporosis group (79.8%), followed by the osteopenia (77.2%) and normal bone mineral density (BMD) groups (35.2%). Cox regression analysis revealed that even after adjusting for covariates, the osteoporosis group was significantly associated with a higher mortality risk than the normal BMD group. Osteoporosis at the start of hemodialysis was significantly associated with higher mortality. Conclusion We should consider the importance of bone health in patients undergoing incident hemodialysis and pay attention to the use of phosphate binders and fracture prevention.

Background: Obesity is a well-known risk factor for chronic kidney disease and its progression. However, the impact of obesity on the renal function of the elderly population is uncertain. We investigated the association between obesity and renal outcomes in the elderly. Methods: We analyzed 130,504 participants from the Korean National Health Insurance Service-Senior cohort. Obesity was classified according to body mass index (BMI), sex-specific waist circumference (WC), and the presence of metabolic syndrome. The primary outcome was renal function decline, defined as a decline in the estimated glomerular filtration rate (eGFR) of at least 50% from baseline or new-onset end-stage renal disease. Results: During a follow-up period of 559,531.1 person-years (median, 4.3 years), 2,486 participants (19.0%; incidence rate of 4.44 per 1,000 person-years) showed renal function decline. A multivariate Cox proportional hazards model revealed that BMI/WC was not associated with renal function decline. However, the group with metabolic syndrome had a significantly increased risk of renal function decline compared to the group without metabolic syndrome (adjusted hazard ratio [HR], 1.24; 95% confidence interval [CI], 1.13–1.36). Compared with the non-metabolic syndrome group, the adjusted HRs (95% CI) for participants with one through five components were 0.96 (0.84–1.11), 1.10 (0.96–1.27), 1.24 (1.06–1.45), 1.37 (1.12–1.66), and 1.99 (1.42–2.79), respectively (p for trend < 0.001). Conclusion In elderly Korean adults, metabolic syndrome and the number of its components were associated with a higher risk of renal function decline, but BMI or WC was not significant.

Background and Objectives: Clinical characteristics and outcomes in acute heart failure (AHF) vary by phenotype. We assessed phenotype-specific features, treatment patterns, and outcomes in a nationwide Korean cohort. Methods: The Korean Heart Failure III registry prospectively enrolled 7,351 AHF admissions at 47 hospitals. Among 6,777 patients with available left ventricular ejection fraction (EF), phenotypes were defined as heart failure with reduced EF (HFrEF, ≤40%), mildly reduced EF (HFmrEF,41–49%), or preserved EF (HFpEF, ≥50%). The primary endpoint was a 12-month composite of all-cause death or heart transplantation, evaluated from index admission and, among hospital survivors, from discharge. We used inverse probability weighting (multinomial generalized boosted models with stabilized, trimmed weights) and weighted Cox proportional-hazards models to estimate hazard ratios (HRs). Results: Phenotype distribution was 58.9% HFrEF, 13.6% HFmrEF, and 27.5% HFpEF. Crude 12-month composite rates from index admission were 13.4% (HFrEF), 12.7% (HFmrEF), and 16.8% (HFpEF). After weighting, from index admission, HFmrEF (HR, 0.892; 95% confidence interval [CI], 0.731–1.088) and HFpEF (HR, 1.101; 95% CI, 0.939–1.291) did not differ from HFrEF; from discharge, HFpEF had modestly higher risk (HR, 1.207; 95% CI, 1.008–1.445) whereas HFmrEF did not (HR, 1.039; 95% CI, 0.844–1.279). Hyponatremia and chronic kidney disease were consistent adverse markers, while angiotensin-converting enzyme inhibitor/ angiotensin II receptor blocker use at discharge was protective. Conclusions Across the EF spectrum, phenotypes showed distinct profiles and risk. Postdischarge risk was modestly higher in HFpEF, supporting phenotype-tailored care and systematic discharge optimization in Korean patients with AHF.

Background and Objectives: In chronic heart failure (HF), natriuretic peptide (NP) levels are higher in atrial fibrillation (AF) compared to sinus rhythm (SR). However, due to the loss of atrial contraction, AF patients are prone to hemodynamic decompensation at earlier stages.Since NP levels reflect disease severity, acutely decompensated AF patients may exhibit lower NP levels compared to SR patients, who retain greater hemodynamic reserve. Methods: We analyzed 5,048 patients with acute HF from the Korea Acute Heart Failure registry with available NP data. NP levels and echocardiographic parameters were compared between AF and SR patients. The association of NP levels with in-hospital and one-year mortality was also assessed according to cardiac rhythm. Results: Brain natriuretic peptide (BNP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) were measured in 2,027 and 3,021 patients, respectively. NP levels were lower in AF than in SR (median BNP, 740 vs. 1,044 pg/mL; median NT-proBNP, 4,420 vs. 5,198 pg/mL), particularly in HF with reduced or mildly reduced ejection fraction. A similar trend was observed regardless of HF onset or etiology. AF patients had smaller left ventricular (LV) end-diastolic diameter and larger left atrial size compared to SR patients. Higher NP tertiles were associated with increased in-hospital and one-year mortality in both groups. Conclusions In acute HF, NP levels are lower in AF than in SR. AF patients also exhibited smaller LV chamber sizes. Nevertheless, NP levels remain strong predictors of outcomes in both AF and SR patients.

Early mortality following hemodialysis initiation hinders survival improvement in older patients. This study aimed to develop a clinical risk model for predicting 6-month mortality after dialysis initiation in older Korean hemodialysis patients. Methods: We analyzed data from incident hemodialysis patients aged >70 years from the Korean Society of Geriatric Nephrology (KSGN) database. A prediction model was developed using multivariate logistic regression analysis and externally validated with independent datasets. Results: Among 1,751 incident hemodialysis patients, the 6-month mortality rate was 15.5%. Using multivariate logistic analysis, we constructed the KSGN score as an independent risk factor for 6-month mortality, and its components and score are as follows: old age at dialysis initiation (≥85 years, score 2); hypertension and renovascular disease as a primary etiology of end-stage kidney disease (ESKD) (score 1); malignancy history (yes, score 1); low serum albumin (<3.5 g/dL, score 1); hypertension treatment (yes, score –1); prepared vascular access on maintenance dialysis (arteriovenous fistula/arteriovenous graft, score –3). In the development cohort, the area under the curve (AUC) for the KSGN score was significantly higher than the Alberta Wick’s score (0.707 vs. 0.683, p = 0.001). In the validation cohort, the KSGN score’s performance was comparable to existing models. Conclusion: The KSGN score may be a valuable tool for predicting early mortality after dialysis initiation in older patients with ESKD, aiding in decision-making and management regarding dialysis initiation.

Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.

Background: This study aimed to investigate the effects of applying the hot spring water exercise for 8 weeks to middle-aged females with knee osteoarthritis. Methods: To investigate this, body composition, isokinetic muscle function, and the knee flexion angle K-WOMAC were evaluated before and after the 8-week hot spring water exercise program and analyzed using a mixed-design two-way ANOVA. After analysis, if a significant difference was observed, the Bonferroni method was used as a post hoc method, and the following results were obtained. Results: First, among the body composition parameters, the body fat percentage showed a statistically significant reduction after the 8-week hot spring water exercise program in the exercise group (EG) (p = .031).However, there was no significant difference in body weight, muscle mass, body fat mass, and body mass index. Among the isokinetic muscle functions, the peak torque (p = .003, p = .001) and total work (p = .003, p = .003) of the flexion and extension movements, and the average power (p = .007) of the flexion movement significantly increased in the EG, while the average power of the extension movement did not change. The range of joint motion significantly increased after the exercise. The K-WOMAC index significantly decreased after the exercise. Conclusion Thus, the 8-week aquatic exercise program utilizing hot springs improved knee extension and flexion muscle strength. Hence, it is believed that it can be used as an interventional therapy for low back pain in the elderly and for obese people who have difficulty with land-based exercises.

Background: and Purpose We delineated the association between otolithic dysfunction and blood pressure (BP) variability. Methods: We prospectively recruited 145 consecutive patients (age=71 [59–79] years, median [interquartile range]; 76 females) with orthostatic intolerance between December 2021 and December 2023 at a tertiary hospital in South Korea. Each patient underwent evaluations of cervical and ocular vestibular-evoked myogenic potentials (oVEMPs), 24-h noninvasive ambulatory BP monitoring (ABPM), and a head-up tilt-table test using the Finometer device. As measures of BP variability, the standard deviations (SDs) of the systolic BP (SBP SD) and the diastolic BP were calculated based on serial ABPM recordings. Patients were divided into those with orthostatic hypotension (OH, n=68) and those with a normal head-up tilt-table test despite orthostatic intolerance (NOI, n=77) groups. Results: A multivariable logistic regression analysis showed that OH was associated with bilateral oVEMP abnormalities (p=0.021), SBP SD (p=0.012), and female sex (p=0.004). SBP SD was higher in patients with OH than in those with NOI (p<0.001), and was not correlated with n1–p1 amplitude (p=0.491) or normalized p13–n23 amplitude (p=0.193) in patients with OH.The sensitivity and specificity for differentiating OH from NOI were 72.1% and 67.5%, respectively, at a cutoff value of 12.7 mm Hg for SBP SD, with an area under the receiver operating characteristic curve of 0.73. Conclusions Bilaterally deficient oVEMP responses may be associated with OH regardless of 24-h BP variability, reflecting the integrity of the otolith-autonomic reflex during orthostasis. Alternatively, 24-h BP variability is predominantly regulated by the baroreflex, which also participates in securing orthostatic tolerance complementary to the vestibulo-autonomic reflex.