Purpose: This study aimed to evaluate the natural growth of subepithelial tumors of the small bowel detected on CT. Materials and Methods: Consecutive patients who were suspected of having subepithelial tumors of the small bowel between January 2005 and December 2020 were reviewed. Eligible patients with suspected small (< 30 mm) subepithelial tumors on at least two CT evaluations were included in the analysis. The patients’ data on demographic characteristics, tumoral characteristics, and tumoral size changes during the follow-up were collected. Results: This study included 64 patients with suspected small subepithelial tumors (n = 64) of the small bowel. After a median follow-up of 15.8 months, the diameter and volume growth rates were 0.02 mm/month and 1.5 mm3/month, respectively. A significant correlation was observed between the initial size and the growth rate of the small bowel subepithelial tumors. The group of large-sized tumors (initial diameter ≥ 10 mm) tended to show lobulated contours, heterogeneous enhancement, and necrotic changes more frequently than the group of small-sized tumors (initial diameter < 10 mm). Conclusion Small bowel subepithelial tumors measuring less than 10 mm grew more slowly than those measuring 10–30 mm.

Background: Sarcopenia, characterized by a progressive decline in muscle mass, strength, and function, is primarily attributable to aging. DNA methylation, influenced by both genetic predispositions and environmental exposures, plays a significant role in sarcopenia occurrence. This study employed machine learning (ML) methods to identify differentially methylated probes (DMPs) capable of diagnosing sarcopenia in middle-aged individuals.We also investigated the relationship between muscle strength, muscle mass, age, and sarcopenia risk as reflected in methylation profiles. Methods: Data from 509 male participants in the urban cohort of the Korean Genome Epidemiology Study_Health Examinee study were categorized into quartile groups based on the sarcopenia criteria for appendicular skeletal muscle index (ASMI) and handgrip strength (HG). To identify diagnostic biomarkers for sarcopenia, we used recursive feature elimination with cross validation (RFECV), to pinpoint DMPs significantly associated with sarcopenia.An ensemble model, leveraging majority voting, was utilized for evaluation. Furthermore, a methylation risk score (MRS) was calculated, and its correlation with muscle strength, function, and age was assessed using likelihood ratio analysis and multinomial logistic regression. Results: Participants were classified into two groups based on quartile thresholds:sarcopenia (n = 37) with ASMI and HG in the lowest quartile, and normal ranges (n = 48) in the highest. In total, 238 DMPs were identified and eight probes were selected using RFECV.These DMPs were used to build an ensemble model with robust diagnostic capabilities for sarcopenia, as evidenced by an area under the receiver operating characteristic curve of 0.94. Based on eight probes, the MRS was calculated and then validated by analyzing age, HG, and ASMI among the control group (n = 424). Age was positively correlated with high MRS (coefficient, 1.2494; odds ratio [OR], 3.4882), whereas ASMI and HG were negatively correlated with high MRS (ASMI coefficient, −0.4275; OR, 0.6521; HG coefficient, −0.3116;OR, 0.7323). Conclusion Overall, this study identified key epigenetic markers of sarcopenia in Korean males and developed a ML model with high diagnostic accuracy for sarcopenia. The MRS also revealed significant correlations between these markers and age, HG, and ASMI. These findings suggest that both diagnostic models and the MRS can play an important role in managing sarcopenia in middle-aged populations.

Background: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to changes in movement patterns, which can increase the risk of falls and other injuries. Methods: Older women participants aged ≥65 years who could walk independently were recruited and classified into two groups based on knee extension strength (KES). Participants with low KES scores were assigned to the possible sarcopenia group (PSG; n=7) and an 8-week exercise intervention was implemented. Healthy seniors with high KES scores were classified as the reference group (RG; n=4), and a 3-week exercise intervention was conducted. Kinematic movement data were recorded during the intervention period. All participants' exercise repetitions were used in the data analysis (number of data points=1,128). Results: The PSG showed significantly larger movement patterns in knee rotation during wide squats compared to the RG, attributed to weakened lower limb strength. The voting classifier, trained on the movement patterns from wide squats, determined that significant differences in overall movement patterns between the two groups persisted until the end of the exercise intervention. However, after the exercise intervention, significant improvements in lower limb strength in the PSG resulted in reduced knee rotation range of motion and max, thereby stabilizing movements and eliminating significant differences with the RG. Conclusion This study suggests that exercise interventions can modify the movement patterns in older individuals with possible sarcopenia. These findings provide fundamental data for developing an exercise management system that remotely tracks and monitors the movement patterns of older adults during exercise activities.

Background: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to changes in movement patterns, which can increase the risk of falls and other injuries. Methods: Older women participants aged ≥65 years who could walk independently were recruited and classified into two groups based on knee extension strength (KES). Participants with low KES scores were assigned to the possible sarcopenia group (PSG; n=7) and an 8-week exercise intervention was implemented. Healthy seniors with high KES scores were classified as the reference group (RG; n=4), and a 3-week exercise intervention was conducted. Kinematic movement data were recorded during the intervention period. All participants' exercise repetitions were used in the data analysis (number of data points=1,128). Results: The PSG showed significantly larger movement patterns in knee rotation during wide squats compared to the RG, attributed to weakened lower limb strength. The voting classifier, trained on the movement patterns from wide squats, determined that significant differences in overall movement patterns between the two groups persisted until the end of the exercise intervention. However, after the exercise intervention, significant improvements in lower limb strength in the PSG resulted in reduced knee rotation range of motion and max, thereby stabilizing movements and eliminating significant differences with the RG. Conclusion This study suggests that exercise interventions can modify the movement patterns in older individuals with possible sarcopenia. These findings provide fundamental data for developing an exercise management system that remotely tracks and monitors the movement patterns of older adults during exercise activities.

Background: Sarcopenia is a muscle-wasting condition that affects older individuals. It can lead to changes in movement patterns, which can increase the risk of falls and other injuries. Methods: Older women participants aged ≥65 years who could walk independently were recruited and classified into two groups based on knee extension strength (KES). Participants with low KES scores were assigned to the possible sarcopenia group (PSG; n=7) and an 8-week exercise intervention was implemented. Healthy seniors with high KES scores were classified as the reference group (RG; n=4), and a 3-week exercise intervention was conducted. Kinematic movement data were recorded during the intervention period. All participants' exercise repetitions were used in the data analysis (number of data points=1,128). Results: The PSG showed significantly larger movement patterns in knee rotation during wide squats compared to the RG, attributed to weakened lower limb strength. The voting classifier, trained on the movement patterns from wide squats, determined that significant differences in overall movement patterns between the two groups persisted until the end of the exercise intervention. However, after the exercise intervention, significant improvements in lower limb strength in the PSG resulted in reduced knee rotation range of motion and max, thereby stabilizing movements and eliminating significant differences with the RG. Conclusion This study suggests that exercise interventions can modify the movement patterns in older individuals with possible sarcopenia. These findings provide fundamental data for developing an exercise management system that remotely tracks and monitors the movement patterns of older adults during exercise activities.

Abiotrophia defectiva, a nutritionally variant streptococci can cause bacteremia, brain abscess, septic arthritis and in rare cases, infective endocarditis, which accounts for 5-6% of all cases. A. defectiva is characteristically difficult to diagnose and the mortality, morbidity and complication rates are high. Here, we discuss a case of infective endocarditis caused by A. defectiva. A 62-year-old female had previously undergone prosthetic valve replacement 6 years prior to admission. She developed infective endocarditis after tooth extraction. Her endocarditis was successfully treated with antimicrobial therapy and mitral valve replacement surgery. This is the first case of infective endocarditis caused by A. defectiva reported in Korea. This case shows that A. defectiva could be considered as a causative organism of infective endocarditis in Korea.
Abiotrophia* ; Arthritis, Infectious ; Bacteremia ; Brain Abscess ; Endocarditis* ; Female ; Humans ; Korea* ; Middle Aged ; Mitral Valve ; Mortality ; Tooth Extraction