Background: Nonalcoholic fatty liver disease, a progressive condition caused by the accumulation of fat in the liver, begins with simple steatosis and can potentially progress to metabolic dysfunction-associated steatohepatitis (MASH) in the presence of inflammation and fibrosis, ultimately leading to cirrhosis or hepatocellular carcinoma. Increasing evidence indicates that sodiumglucose cotransporter 2 (SGLT2) inhibitors effectively alleviate MASH in mouse models. However, there is a lack of research on the effects of enavogliflozin on liver disease. In the present study, we investigated the effects of SGLT2 inhibitors on MASH induced by a high-fat, high-cholesterol (HFHC) diet in mice. Methods: Male C57BL/6 mice were fed a normal chow diet, HFHC diet, or HFHC diet with enavogliflozin for 12 weeks. LX-2 and HepG2 cells were treated with enavogliflozin in the presence of various pathological stimuli. Results: The HFHC diet induced excessive hepatic lipid accumulation, inflammation, and severe fibrosis. Administration of enavogliflozin not only ameliorated hepatic steatosis and fibrotic conditions but also suppressed the production of inflammatory cytokines. Positive outcomes were also observed in in vitro experiments, where enavogliflozin demonstrated the ability to impede the activation of hepatic stellate cells and alleviate lipid accumulation in hepatocytes. The potential pathway through which enavogliflozin attenuated liver fibrosis development may be associated with the transforming growth factor β1/Smad signaling pathway. Conclusion Our results suggest that enavogliflozin is effective in a mouse model of MASH by attenuating hepatic steatosis, suppressing inflammation, and improving liver fibrosis.

Background/Aims: Recent advances in computer-aided diagnosis (CADx) systems have demonstrated expert-level accuracy in the optical diagnosis of colorectal polyps. High-confidence (HC) diagnoses have been defined as those made within 3 seconds without hesitation, and these systems have been shown to improve diagnostic accuracy. We aimed to evaluate the performance of endoscopists with varying levels of experience in diagnosing colorectal polyps with the assistance of a new CADx system applying the 3-second rule and without artificial intelligence assistance. Methods: In this multicenter ex vivo study, 35 endoscopists assessed 100 polyps (51 adenomas, 39 hyperplastic polyps, 10 sessile serrated lesions) using narrow-band imaging video clips on an online platform. Assessments consisted of individual endoscopist diagnosis and CADx-assisted diagnosis. HC assignments followed the 3-second rule in both phases. Performance metrics included HC accuracy, HC rate, and adherence to the Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) and Simple Optical Diagnosis Accuracy (SODA) thresholds. Results: HC diagnostic accuracy improved from 78.3% (95% confidence interval [CI], 76.6% to 80.0%) to 89.8% (95% CI, 88.6% to 90.9%) with CADx assistance (p<0.001). The proportion of HC predictions increased from 64.2% to 75.4% (p<0.001). Novice endoscopists showed marked improvement with CADx (74.1% vs 88.8%; p<0.001). CADx-assisted diagnoses nearly met SODA and PIVI thresholds under the 3-second rule. Additional analysis demonstrated that CADx assistance significantly improved interobserver agreement and ground truth, particularly for novices (κ=0.37 to κ=0.65; p<0.001). Conclusions Integrating CADx with the 3-second rule significantly enhances the performance of endoscopists in the optical diagnosis of colorectal polyps, with the greatest benefit observed among novice endoscopists.

Objectives: Large language models (LLMs) demonstrate remarkable potential in healthcare communication. However, whether they can process complex, high-volume medical information, such as stroke-related content, remains insufficiently validated. This study aimed to evaluate the natural language processing capabilities of LLMs in handling such content and to develop an evaluation instrument. Methods: A survey compared educational materials generated by two LLMs (ChatGPT 4.0 and Claude 3) with neurologist-authored content on stroke. The materials were based on two clinical scenarios representing distinct stroke etiologies: cardioembolism and large-artery atherosclerosis. They were evaluated in terms of accuracy, legality, ethics, comprehensiveness, and information delivery. Scores for comprehensiveness and information delivery were compared according to participants’ agreement with the use of LLMs in healthcare. Results: ChatGPT received the highest scores across all domains, except for legality in Scenario 2. In Scenario 1, the ranking for accuracy and summarization of clinical information was, from highest to lowest, ChatGPT, Claude, and the neurologist (η2 = 0.140, p < 0.001; η2 = 0.175, p < 0.001). The same hierarchy was observed in Scenario 2 for accuracy (η2 = 0.077, p < 0.001) and summarization (η2 = 0.194, p < 0.001). Participants who agreed with the use of LLMs in healthcare assigned higher scores for the comprehensiveness (Scenario 1, p = 0.005; Scenario 2, p = 0.007) and information delivery (Scenario 1, p = 0.003; Scenario 2, p = 0.026) of ChatGPT-generated materials than participants who did not agree. Conclusions LLMs demonstrated adequate capability to convey complex content, such as stroke-related information, in an accessible and understandable manner for non-experts.

Janus kinase (JAK) inhibitors are an important treatment option for ulcerative colitis, providing rapid onset of action, oral administration, and efficacy even after biologic failure. The 3 approved agents—tofacitinib, filgotinib, and upadacitinib—differ in JAK isoform selectivity, leading to clinically meaningful differences in efficacy and safety. Evidence from network meta-analyses, clinical trials, and real-world studies consistently shows that upadacitinib provides the highest efficacy for induction and maintenance of remission, whereas filgotinib demonstrates the most favorable safety profile. The strong efficacy of upadacitinib and tofacitinib is particularly relevant in patients with severe disease, including acute severe ulcerative colitis, and upadacitinib maintains high efficacy regardless of prior advanced therapy exposure. JAK inhibitors also benefit extraintestinal manifestations. Although risks such as herpes zoster, serious infection, thromboembolism, and major cardiovascular events differ among agents, long-term data suggest generally acceptable safety when used appropriately. Intraclass JAK-to-JAK cycling is feasible, with about half of patients achieving steroid-free clinical remission in retrospective cohorts. Based on mechanistic, clinical, and real-world evidence, filgotinib may be a first-line option for patients with lower disease activity or when safety is a priority, whereas upadacitinib or tofacitinib may be preferred in higher disease activity. Strategically selecting agents may improve durability and outcomes.

Compound muscle action potential (CMAP) recording provides an objective electrophysiological assessment of facial nerve function after injury. In rodent models, vibrissal CMAPs serve as quantitative surrogates of facial nerve integrity; however, practical descriptions of CMAP recording setups using widely available systems remain limited. In this study, we detail a practical and reproducible method for recording vibrissal CMAPs following direct stimulation of the facial nerve trunk in rats, using a BIOPAC-based system. CMAPs were recorded before and after unilateral facial nerve crush injury, followed by transection and epineural repair. Direct nerve trunk stimulation reliably elicited stable CMAP waveforms and supramaximal stimulation produced consistent responses suitable for longitudinal assessment. Baseline CMAP amplitudes were comparable to previously reported values. After facial nerve injury, CMAPs on the injured side were absent at 1 week, reappeared at 2 weeks, and increased further by 4 weeks. Because absolute CMAP amplitudes varied across recording sessions despite intact contralateral nerves, functional recovery was evaluated using left/right amplitude ratios. Single-peak CMAP amplitude was used to minimize waveform variability and stimulus-related artifacts. This method provides a straightforward and accessible approach for the electrophysiological assessment of facial nerve injury and recovery in experimental rodent models.

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.

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.

The sixth edition of the Korean Medication Algorithm Project for Depressive Disorder (KMAP-DD) was published in 2025. This review compared KMAP-DD 2025 with four major international clinical practice guidelines: Canadian Network for Mood and Anxiety Treatments Clinical Guidelines for the Management of Major Depressive Disorders, National Institute for Health and Care Excellence Depression Guideline, Royal Australian and New Zealand College of Psychiatrists Clinical Practice Guidelines for Mood Disorders, and British Association for Psychopharmacology Guideline. While KMAP-DD is based on expert consensus, and others on evidence-based methods, overall treatment strategies for depressive episodes were fairly consistent. Especially, KMAP-DD 2025 offers more structured recommendations in areas lacking strong evidence, such as premenstrual dysphoric disorder, perinatal depression, and depression with medical comorbidities. KMAP-DD 2025 also reflected Korean clinical practice patterns emphasizing rapid symptom relief and early use of combination strategies. Despite limitations as a consensus-based guideline, KMAP-DD 2025 complements evidence-based approaches and provides practical, situation-specific guidance for real-world clinical decision-making in Korea.

OBJECTIVES: This study aimed to evaluate a fixed-duration algorithm for gestational age (GA) estimation according to pregnancy outcomes and to describe the GA distribution of pregnancy-related codes in Korea. METHODS: We included 351,055 pregnancy episodes (2019–2022) from linked data between the National Health Insurance Service and the Korea Immunization Registry Information System (KIRIS). GA from claims data was estimated by subtracting fixed durations from the delivery date (algorithm-based GA), and GA derived from KIRIS was defined as the gold standard. Accuracy was evaluated as the proportion of episodes in which the difference between the estimated GA and the reference standard fell within ±2 weeks. We described the distributions of the GA at which each prenatal test, pregnancy complication, and diagnostic code was recorded. RESULTS: Algorithm-based GA estimation showed high accuracy for live births (92.2% within ±2 weeks) but markedly lower accuracy for non-live birth outcomes, including stillbirth (3.3%), termination (7.2%), spontaneous abortion (45.2%), and ectopic pregnancy (20.0%). In additional analyses aimed at identifying potential indicators for improving GA estimation, most events occurred within clinically expected timeframes, although some individual codes exhibited poor temporal alignment. CONCLUSIONS Algorithm-based GA estimation using claims data performed well for live births but demonstrated limited accuracy for non-live birth outcomes. Incorporating information from prenatal tests and pregnancy complications may enhance GA estimation.