Background: Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is among the most important multidrug-resistant pathogens causing bloodstream infections (BSIs).Cefotaximase (CTX-M) enzymes are the most common and highly diverse ESBL family in E.coli. CTX-M-15 in group CTX-M-1 and CTX-M-14 in group CTX-M-9 are the most extensively disseminated enzymes. Multidrug-resistant E. coli strains complicate empirical therapy and increase healthcare burden globally and in Korea. We investigated the molecular epidemiology, sequence types (STs), and ESBL genotypes of E. coli bloodstream isolates in Korea and identified clinical risk factors for cefotaxime resistance. Methods: We collected all non-duplicated isolates of E. coli and related clinical information from patients with BSIs at eight sentinel hospitals in the Korean Global Antimicrobial Resistance Surveillance System (Kor-GLASS) collection network during 2017–2021. Duplicate isolates were removed to ensure representativeness of the data. Antimicrobial susceptibility was tested using disk diffusion tests, and multilocus sequence typing and betalactamase genotyping were performed. Results: Among 9,232 E. coli blood isolates, resistance rates to cefotaxime and ceftazidime were 36.4% and 11.4%, respectively. Among the clinical factors, age > 65 yrs (adjusted odds ratio [aOR], 1.36), hospital-origin infection (aOR, 2.55), and admission type (intensive care unit [ICU] vs. general ward; aOR, 1.34) were significant cefotaxime resistance risk factors. ST131 was the most prevalent among cefotaxime-resistant E. coli (64.8%, 2,180/3,363), followed by ST1193 (5.3%, N = 177), and ST69 (5.1%, N = 170).ST131, ST648, ST405, and ST410 cefotaxime-resistant E. coli isolates frequently harbored blaCTX-M-15, whereas ST1193 and ST68 showed a high proportion of blaCTX-M-27 carriers, and most ST457 and ST5150 isolates carried blaCTX-M-55. Conclusions Continuous monitoring of ESBL-producing E. coli is required to prevent further dissemination, guide empirical therapy, inform infection control policies, and ensure early detection of multidrug-resistant clones with the potential for widespread transmission.

Purpose: Despite the global paradigm emphasizing earlier and more aggressive intervention for youth-onset type 2 diabetes mellitus (T2DM), metformin and insulin are the only drugs approved for Korean adolescents. We investigated the incidence of complications, changes in glycemic control during the transition period, the effect of second-line antidiabetic agents on glycemic control in young adults with youth-onset T2DM. Methods: Eighty-four patients diagnosed with T2DM at Seoul National University Children's Hospital between January 2001 and July 2023, before age 18 (47 males; mean age, 14 years) with available glycated hemoglobin (HbA1c) data from at least 2 distinct ages between 19 and 22 years old were retrospectively enrolled. Results: At the last follow-up (mean age, 24.9 years; median follow-up, 9.6 years), complications were found in 33.7% (nephropathy, 25.3%; eye disease, 20.6%), and 83% required insulin or second-line agents. During the transition period, HbA1c levels decreased from 8.2% at age 19 to 7.7% at age 22 (P<0.01), with greater improvements in females, those diagnosed before age 15, and those with HbA1c levels ≥7% at age 19. HbA1c level decreased significantly at 1 year after the addition of second-line medications (P=0.03) and at the last visit (P=0.03) compared with baseline. Conclusion Glycemic control improved during the transition period among youth-onset T2DM patients. Given the high incidence of complications and the beneficial effects of second-line agents on glycemic control, there is an urgent need to expand the range of approved second-line agents, along with broader insurance coverage in adolescence.

Objective: This study aimed to evaluate the accuracy of predicting final adult height (FAH) in Korean girls with central precocious puberty (CPP) using artificial intelligence (AI)-derived bone age assessments integrated into the Bayley–Pinneau (BP) or Korean National Growth Chart (KGC) prediction models. Materials and Methods: This single-center, retrospective study included 122 Korean girls with CPP who received gonadotropinreleasing hormone agonist (GnRHa) treatment for at least two years between January 2000 and November 2022. We assessed bone age and predicted adult height at the initiation and completion of GnRHa treatment. We used three bone age assessment methods: human expert assessment based on the Greulich-Pyle (GP) atlas (Human-GP), AI-derived GP (AI-GP), and AI-weighted GP scoring (AI-GPw). We calculated predicted adult heights (PAHs) using both the BP and KGC models, generating 12 PAH estimates per patient (2 time points x 3 bone-age methods x 2 height-prediction models). We assessed prediction accuracy and agreement with FAH using linear regression analysis and Bland–Altman plots and performed multivariable analysis to identify significant predictors of FAH. Results: Human-GP, AI-GP, and AI-GPw demonstrated comparable overall performance in predicting FAH (R 2 : 0.470–0.646 and 0.691–0.822 for treatment initiation and completion, respectively). AI-GPw combined with BP yielded slightly better point estimates but showed no statistically significant differences. At both time points, the BP model demonstrated consistently narrower 95% limits of agreement (LoA) than the KGC model. Multivariable analysis identified AI-GPw-BP and height percentile score as significant predictors of FAH at both time points; mid-parental height was significant only at treatment initiation. Conclusion Human-GP, AI-GP, and AI-GPw demonstrated comparable accuracy in predicting FAH. The BP model demonstrated consistently narrower 95% LoA than did the KGC model. AI-GPw-BP was an independent predictor of FAH. These findings support the clinical utility of AI-derived bone age assessments for individualized FAH prediction in patients with CPP.

Background: Despite advancements in laboratory animal facility management, pinworm infections remain a persistent issue in immunodeficient mouse colonies. Rapid diagnosis and treatment are crucial to mitigating potential scientific and economic consequences. Effective control requires both the administration of anthelmintic agents and rigorous environmental decontamination. However, the safety and efficacy of these treatments in genetically modified mouse models remains uncertain.Case presentation Aspiculuris tetraptera infestation was identified in multiple immunodeficient mouse models housed in a laboratory facility. Diagnosis was confirmed through fecal flotation for egg detection and necropsy for adult worm examination in the large intestines. Mice received three subcutaneous ivermectin injections at two-week intervals, coupled with environmental decontamination using ivermectin spray for four consecutive weeks. Following treatment, all colonies tested negative for A. tetraptera without any mortality. Conclusions A combination of subcutaneous ivermectin injection and environmental spray application effectively eradicated A. tetraptera infestation in immunodeficient mouse colonies. The treatment protocol led to the complete elimination of eggs and adult worms, offering a practical strategy for managing pinworm infections in genetically modified mouse models. Limitations include the small sample size, and the lack of a comprehensive evaluation of physiological and metabolic safety in immunodeficient mice. Further validation will be required to confirm the broader applicability of this approach.

Punica granatum L. has been widely used in traditional medicine and is known to contain bioactiveellagitannins with potential antidiabetic properties. The primary objective of this study was to develop and validate a reliable HPLC-DAD method for the quantitative analysis of major compounds isolated from stems and pericarpium of P. granatum, namely pedunculagin (1), flavogallonic acid (2), casuarinin (3), isocorilagin (4), methyl brevifolincarboxylate (5), eschweilenol C (6), ellagic acid-4-O-β-D-xylopyranoside (7), ellagic acid (8), and quercitrin (9), and to futher evaluate their α-glucosidase inhibitory activity. The analytical method demonstrated linearity with correlation coefficients (R²) exceeding 0.9991. The limits of detection (LOD) and limits of quantification (LOQ) ranged from 2.75 to 7.44 μg/mL and 8.33 to 22.54 μg/mL, respectively. Intra-day and inter-day precision showed relative standard deviation (RSD) values below 2.85% and 2.72%, while recovery values ranged from 96.87% to 107.72%, confirming the accuracy and reliability of the method.Quantitative results revealed that ellagitannins were the predominant constituents in both stems and pericarpium of P. granatum. Biological evaluation demonstrated that several isolated compounds exhibited strong αglucosidase inhibitory activity, with compounds 1–3 showing significantly stronger activity than the reference inhibitor acarbose. Enzyme kinetic studies and molecular docking analyses were conducted to clarify their inhibition mechanisms, revealing mixed, uncompetitive and competitive inhibition modes associated with binding to catalytic or allosteric sites of the enzyme. This study integrates quantitative analysis with mechanistic enzyme inhibition evaluation, providing a practical analytical tool for quality control of P. granatum and scientific evidence supporting its potential application in antidiabetic therapy.

Background: Left bundle branch block (LBBB) significantly increases the risk of left ventricular systolic dysfunction (LVSD) due to cardiac dyssynchrony. Although artificial intelligence–enabled electrocardiography (AI-ECG) mod‑ els show promise in detecting LVSD, their performance in LBBB patients remains underexplored. We hypothesized that an AI-ECG model clinically validated for detecting LVSD would accurately detect LVSD and predict future clinical outcomes in LBBB patients. Methods: In this retrospective multicenter study, 5,689 expert-validated LBBB ECGs collected from 2,813 patients between 2016 and 2024 were analyzed using a previously developed and validated AI-ECG model. LVSD was defined as an ejection fraction of ≤ 40%. Model performance was assessed using the area under the receiver operating char‑ acteristic curve (AUROC), the area under the precision-recall curve (AUPRC), sensitivity, and specificity. Patients were stratified into high- and low-risk groups based on a threshold that achieved 90% sensitivity. A Kaplan–Meier analysis was used to compare clinical outcomes. Results: Among the 2,813 LBBB patients (mean age, 70.7 years; male sex, 43.7%), hypertension and a history of heart failure were common. The AiTiALVSD model showed strong diagnostic performance for LVSD (AUROC, 0.930 [95% CI, 0.924–0.937]; AUPRC, 0.913 [95% CI, 0.902–0.923]; sensitivity, 0.979; specificity, 0.473). During the mean follow-up of 4.1 years, high-risk patients had significantly higher hazards than low-risk patients for all-cause mortality (adjusted hazard ratio [HR], 1.87; 95% CI, 1.53–2.28), implantable cardioverter defibrillator/cardiac resynchronization therapy implantation (adjusted HR, 15.2; 95% CI, 7.51–30.77), and cardiovascular hospitalization (adjusted HR, 1.11; 95% CI, 0.96–1.28). Conclusions AiTiALVSD effectively detects LVSD and stratifies long-term cardiovascular risk in LBBB patients, support‑ ing its clinical utility for early detection and patient management.

Objective: This study aimed to evaluate the survival of removable partial dentures (RPDs) abutment teeth that had undergone root canal treatment (RCT) and to identify the factors influencing survival. Materials and Methods: Records from the Veterans Health Service Medical Center were reviewed to identify patients who received RPDs between 2014 and 2015 and had root canal-treated abutment teeth. Preoperative variables included patient demographics, tooth location, and periapical radiolucency, while postoperative variables included RPD classification, opposing dentition, crown-root ratio (CRR), root canal filling quality, post placement, and restoration type. Statistical analysis was performed using the Kaplan-Meier method and Cox proportional hazards models. Results: A total of 776 root canal-treated abutment teeth from 341 patients using RPDs (mean age, 72.03 years) were included. In the multivariate analysis, tooth-related conditions such as arch type and tooth location, presence of a periapical lesion, and presence of a core were significantly associated with poor prognosis. Kaplan-Meier survival analysis revealed that the 3-, 5-, 7-, and 10-year survival rates for all teeth were 93.5%, 84.4%, 77.1%, and 60.0%, respectively. Conclusion Arch type and tooth position, preoperative periapical radiolucency, and type of restoration are significantly associated with prognosis in patients with RPDs in whom the abutment teeth have previously undergone RCT.

Background: The effects of propofol, a commonly used intravenous anesthetic, on the breast cancer tumor microenvironment are not well understood. This study examined the influence of propofol on natural killer group 2, member D (NKG2D) ligand expression, matrix metalloproteinase (MMP)-mediated immune evasion, and natural killer (NK) cell-mediated cytotoxicity in breast cancer cells. Methods: We studied three human breast cancer cell lines representing distinct receptor subtypes: MCF-7 (estrogen receptor - and progesterone receptor-positive), MDA-MB-453 (human epidermal growth factor receptor 2-positive), and HCC-70 (triple-negative). Cells were treated with propofol at concentrations of 0 μg/ml (control; C), 4 μg/ml (P4), or 8 μg/ml (P8). Assessments included mRNA and protein expression of NKG2D ligands, NK cell cytotoxicity, protein levels of MMP-1 and MMP-2, and concentrations of soluble NKG2D ligands. Results: In MCF-7 and HCC-70 cell lines, propofol upregulated the mRNA and protein expression of NKG2D ligands in a dose-dependent manner, enhancing NK cell-mediated lysis. In contrast, in MDA-MB-453 cell lines, propofol downregulated the mRNA and protein expression of NKG2D ligands, resulting in diminished NK cell-mediated lysis. Across all receptor subtypes, propofol did not affect the expression of MMP-1 or MMP-2 or the concentration of soluble NKG2D ligands. Conclusions Our results demonstrate that propofol exerts receptor subtype-dependent effects on NK cell-mediated immunosurveillance in breast cancer cell lines, potentially mediated by changes in the transcription of NKG2D ligands rather than by alterations in MMP expression or their proteolytic activity.