Accurate lesion size measurement is essential in endoscopic practice as it influences treatment strategies, surveillance decisions, and clinical outcomes, especially in colorectal polyps. Traditional measurement techniques, including visual estimation and biopsy forceps, have significant interobserver variability and procedural inefficiencies. Recent advancements in digital measurement technologies, including virtual scale endoscopy (VSE) and artificial intelligence (AI)-assisted virtual rulers, have addressed these limitations. VSE projects a virtual scale onto endoscopic images, enhancing measurement precision and reducing variability. Several studies have demonstrated its superior accuracy compared with conventional methods; however, limitations such as increased procedure time and operator training requirements persist. AI-assisted virtual rulers utilize deep learning algorithms to automate lesion size estimation, significantly improving reproducibility and diagnostic reliability. Although these technologies offer promising improvements, challenges remain, including real-time integration, standardization, and regulatory approval. Future research should focus on refining AI models, expanding validation studies, and optimizing their usability in routine practice. A hybrid approach that combines AI automation with real-time digital tools may enhance the precision and efficiency of endoscopic lesion assessment, ultimately improving patient outcomes.

Secondary rhabdoid tumors (RTs) with atypical teratoid/rhabdoid tumor-like features rarely arise from, or coexist with, pleomorphic xanthoastrocytomas (PXAs), and their clinicopathological and molecular characteristics remain poorly understood. We report a 17-year-old girl with a temporal lobe mass that, upon gross total resection, pathologically contained both RT and PXA components. Immunohistochemistry revealed loss of INI1 expression restricted to the RT component, while the PXA area retained INI1. Next-generation sequencing identified a shared BRAF::TRIM24 fusion and homozygous deletion of CDKN2A/2B in both components, indicating a shared clonal origin. Additionally, a germline ATM frameshift mutation (c.5288_5289insGA) was identified in both tumor components, making the first such report in central nervous system tumors. SMARCB1 loss was confined to the RT component, further supporting the hypotheses of clonal evolution and secondary transformation. Despite gross total resection, craniospinal irradiation, and chemotherapy, the patient developed rapid leptomeningeal dissemination and died 5 months after surgery. This case provides clinicopathological and molecular evidence for clonal evolution and secondary transformation of PXA into an RT. The presence of germline ATM mutation may have therapeutic and biological relevance. Further studies are required to clarify the pathogenesis and optimal management of these rare and aggressive tumors.

Background: and Purpose: To assess the long-term effectiveness, safety, and economic viability of recently approved Alzheimer’s disease (AD) therapies, as well as to evaluate the real-world application of novel diagnostics among AD patients with diverse comorbidities, comprehensive real-world data (RWD) analysis is essential. The Korean JOint RegistrY for ALZheimer’s Treatment and Diagnostics (JOY-ALZ) endeavors to create a registry of RWD derived from clinical practice on new diagnostic methods and therapeutic agents for AD introduced in Korea since 2021. Methods: Participants must fulfill all the following: 1) be at least 19 years old; 2) be actively receiving, scheduled to initiate, or undergoing evaluation for any AD disease-modifying treatment; 3) have completed amyloid positron emission tomography or cerebrospinal fluid AD immunoassay (a positive result is not essential for participation); 4) have a clinical classification of cognitively unimpaired, mild cognitive impairment, or probable AD dementia. Data generated during routine care is segmented into a minimum dataset, extended dataset, and research-only dataset requiring extra consent. Assessments encompass clinical, cognitive, functional, neurobehavioral, neuroimaging, and biomarker evaluations, in addition to systematic monitoring of new AD treatments and their safety.Data are collected and monitored at baseline, at semiannual intervals during the initial 2 years, and then annually up to 2034. To date, 46 medical centers will participate in JOY-ALZ. Conclusions JOY-ALZ is expected to promote understanding of the long-term clinical outcomes, safety, and cost-effectiveness of recently introduced diagnostics and treatments for AD, thereby supporting the progress of precision medicine in AD care and diagnosis.

Background: and Purpose: Tailored physical exercise interventions have the potential to promote cognitive health in older adults and offer significant advantages for those more vulnerable to decline. The specific relationship between physical fitness and cognition among the elderly has not been clearly established. The purpose of this investigation was to assess the relationship between physical fitness and cognitive function in older Korean adults. Methods: Eighty-four community-dwelling older adults (mean age: 70.7±5.3 years; 81.0% female) completed a standardized physical fitness battery assessing handgrip strength, sit-and-reach, 30-second sit-to-stand, 2-minute stationary march, 3-m sit-walk-and-return, figure-8-walk, and T-wall response time. Cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Descriptive statistics, partial correlation analyses, and stepwise multiple linear regression were conducted. Results: Slower T-wall response time was significantly correlated with lower RBANS total index, immediate memory, and delayed memory scores. In regression models, slower T-wall response time was independently associated with lower RBANS total index (β=−0.234, p=0.026) and delayed memory scores (β=−0.295, p=0.029). The regression model for immediate memory was not statistically significant overall; therefore, no predictive conclusion was drawn for this domain. Higher education showed a significant positive association with cognitive performance. Conclusions Coordination, as measured by T-wall response time, emerged as the only physical fitness component consistently associated with cognitive performance in older adults. Coordination-related fitness may be an important correlate of cognitive function in older adults and a promising target for future exercise interventions.

Background/Aims: Cardiovascular disease remains a major cause of mortality in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). This study evaluated the association between subclinical carotid atherosclerosis (SCA) and MASLD or MASLD and increased alcohol intake (MetALD) in asymptomatic individuals. Methods: This cross-sectional study included 56,889 adults undergoing health check-ups in South Korea. Hepatic steatosis was diagnosed by ultrasound, and SCA was defined by carotid plaques or increased intima-media thickness. Liver fibrosis was evaluated using the fibrosis-4 index and elastography. Results: SCA was identified in 13.5%. MASLD and MetALD were significantly associated with SCA in models adjusted for demographic and lifestyle factors (adjusted odds ratio [aOR], 1.26;95% confidence interval [CI], 1.19 to 1.33; aOR, 1.43; 95% CI, 1.30 to 1.58; respectively, p<0.001for both). However, these associations attenuated and lost statistical significance when metabolic risk factors were further adjusted. The risk of SCA increased with greater hepatic steatosis and liver fibrosis severity. In patients with MASLD, aORs were 1.70 (hepatic steatosis index >36),1.23 (fibrosis-4 index ≥1.3), and 1.78 (liver stiffness measurement ≥5.6 kPa), compared to indi-viduals without MASLD. Similar trends were observed in the MetALD group. Additionally, hyper-tension and clustering of ≥3 cardiometabolic risk factors were significantly associated with SCA inthe MASLD group, supporting the role of metabolic burden in SCA development. Conclusions MASLD and MetALD were associated with increased SCA risk, particularly in individuals with hepatic steatosis and fibrosis. These findings suggest that metabolic burden and liver disease severity jointly contribute to subclinical atherosclerosis risk.

Background/Aims: Chronic kidney disease (CKD) is a significant health problem worldwide, and identifying risk factors for CKD is crucial. We investigated the association between steatotic liver disease (SLD) and the incidence of CKD. Methods: This longitudinal cohort study involved 70,361 adults who did not have CKD at baseline and who underwent at least two health checkups. SLD status was assessed via ultrasonography. The severity of SLD was determined using the Fibrosis-4 score. CKD was defined as an estimated glomerular filtration rate <60 mL/min/1.73 m 2 . Results: Over 475,835 person-years (mean 6.8 years), 2,723 participants developed CKD.The adjusted hazard ratio (aHR) for development of CKD in participants with SLD compared to those without SLD was 1.17 (95% confidence interval [CI], 1.08 to 1.27), with the risk increasing with SLD severity. The aHR (95% CI) for incident CKD was 0.84 (0.51 to 1.37) for cryptogenic SLD, 1.25 (1.16 to 1.36) for metabolic dysfunction-associated SLD (MASLD), and 1.32 (1.01 to 1.73) for metabolic dysfunction-associated alcoholic liver disease (MetALD) compared with participants without SLD. Within these SLD subclassifications, the risk of CKD development was increased as disease severity advanced. Conclusions SLD was linked to a higher incidence of CKD, with the CKD risk increasing sequentially from cryptogenic SLD to MASLD and MetALD. Advanced fibrosis in each SLD subclassification further increases the risk of CKD. Stratifying SLD according to metabolic dysfunction, significant alcohol intake, and fibrosis severity may help identify and monitor individuals at high risk of developing CKD.

This study aimed to develop a predictive model for the early identification of patients at risk of sepsis, using routinely available clinical information and laboratory test results collected during the initial phase of patient care. Methods: This retrospective analysis included electronic medical records of 22,400 adult patients who presented with suspected infection to a tertiary care university hospital in Korea between January 2013 and May 2024. Patients were classified according to Systemic Inflammatory Response Syndrome (score ≥ 2) or Quick Sequential Organ Failure Assessment (score ≥ 2), in combination with sepsis-related International Classification of Diseases, 10th revision codes. Four different machine learning models were trained and validated using five-fold cross-validation. In addition, Shapley additive explanations analysis was performed to interpret the contribution and clinical relevance of key predictive variables. Results: Among the evaluated models, CatBoost demonstrated the strongest predictive performance. Notably, platelet distribution width, alveolar–arterial oxygen difference, procalcitonin, and the arterial/alveolar oxygen ratio consistently emerged as major predictors. Importantly, several variables that did not reach statistical significance in univariate analysis nevertheless contributed substantially to overall model performance, highlighting the importance of complex, multidimensional interactions among clinical factors. Conclusion: These findings indicate that a model based on simple, routinely collected clinical data can achieve high predictive accuracy and strong generalizability. Such a tool may support early clinical decision-making by multidisciplinary teams, including nurses, across diverse real-world care settings. Further prospective studies are warranted to validate its clinical utility and to assess its potential effects on patient outcomes.

Objective: The NOD-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome has been proposed to be a downstream mediator of neuroinflammation in individuals with Parkinson’s disease (PD). However, its involvement across disease stages and related synucleinopathies, such as multiple system atrophy (MSA), remains unclear. We aimed to analyze the peripheral mRNA expression of NLRP3-related genes and cytokines across individuals with isolated REM sleep behavior disorder (iRBD), early-stage PD, late-stage PD, and MSA. Methods: Peripheral blood mononuclear cells (PBMCs) were collected from 151 participants: 35 healthy controls (HCs), 31 patients with iRBD, 41 patients with early-stage PD, 21 patients with late-stage PD, and 23 patients with MSA. mRNA expression was measured using quantitative real-time polymerase chain reaction. Statistical comparisons were performed using analysis of variance (ANOVA) or Welch’s ANOVA, and associations with clinical variables were analyzed through stepwise multiple linear regression. Results: NLRP3 expression was significantly lower in patients with iRBD (p=0.0263) and patients with early-stage PD (p= 0.0101) than in HCs. NIMA-related kinase 7 (NEK7) expression progressively decreased across the disease spectrum (HCs vs. patients with early-stage PD, p=0.0008; vs. patients with late-stage PD, p<0.0001). In contrast, apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC) and caspase-1 were elevated in patients with PD, especially those in the late stages. Levels of patients with MSA resembled those of HCs but differed from those of patients with PD. Interleukin (IL)-1β and IL-18 levels were not significantly different. In patients with early-stage PD, NLRP3 expression was negatively correlated with disease duration, the Movement Disorder Society-Unified Parkinson’s Disease Rating Scale Part II score, and the cognitive score. Conclusion Our findings challenge the prevailing hypothesis that NLRP3 inflammasome activation directly contributes to PD pathogenesis. Instead, the observed increase in ASC and caspase-1 expression suggests the potential involvement of alternative inflammasome pathways during disease progression.

BACKGROUND: Implant supporting materials are currently used in breast reconstruction. However, when used in humans, they are associated with several problems. To address these issues, a new mesh called TissueDerm was created by combining a collagen sponge with a 3D printed polycaprolactone (PCL) mesh. It has shown promising results in pig experiments and could potentially replace the most commonly used acellular dermal matrix (ADM) for breast reconstruction. METHODS: Four 12-month-old minipigs were used in this experiment. Silicone implants were wrapped with ADM or TissueDerm, and the breast tissue was excised and implanted along with the wrapped implants. Three months later, the minipigs were sacrificed and the skin and mammary gland tissue surrounding the implants were harvested for further analysis. Histological analyses and immunostaining were performed. RESULTS: Although there was no significant difference in capsule thickness between the ADM and TissueDerm groups, collagen was more involved in TissueDerm, leading to better tissue regeneration. TissueDerm also induced lower levels of inflammatory markers TNF-a and IL-6 compared to ADM. However, capsules induced with ADM had significantly higher collagen fiber alignment and alpha-smooth muscle actin (a-SMA) positive immunoreactivity, suggesting that TissueDerm may be less likely to cause spherical contractures in the porcine model compared to ADM. CONCLUSIONS The study found that TissueDerm has advantages over ADM in terms of easier tissue invasion and reduced spheroidization in a porcine model. The results showed that TissueDerm is a promising new mesh for implantbased breast reconstruction (IBBR) and could potentially replace ADM.