Characterization of the host specificity of the SH3 cell wall binding domain of the staphylococcal phage 88 endolysin.

Bacteriophages produce endolysins at the end of the lytic cycle, which are crucial for lysing the host cells and releasing virion progeny. This lytic feature allows endolysins to act as effective antimicrobial alternatives when applied exogenously. Staphylococcal endolysins typically possess a modular structure with one or two enzymatically active N-terminal domains (EADs) and a C-terminal cell wall binding domain (CBD).

Baseline Alpha-Fetoprotein Elevation and the Risk of Hepatocellular Carcinoma in Chronic Hepatitis B: A Multicentre Cohort Study.

Alpha-fetoprotein (AFP) level and its changes in chronic hepatitis B (CHB) may influence the risk of future hepatocellular carcinoma (HCC). This study aims to evaluate the HCC risk in CHB patients with no overt HCC but with elevated AFP level and to explore the prognostic role of longitudinal changes in AFP and liver-related laboratory values. This multicentre cohort study included 10,639 CHB patients without a history of HCC from seven medical facilities in South Korea.

Tranexamic dosing for major joint arthroplasty in adult patients with chronic kidney disease: A pharmacokinetic study and new dosing regimen.

Background: Tranexamic acid is an anti-fibrinolytic agent routinely used during hip and knee joint replacement surgery to minimize bleeding. Chronic kidney disease is a common chronic health problem seen among adults requiring major arthroplasty surgery. Tranexamic acid is renally cleared and may accumulate in chronic kidney disease.

Ligand-Shell Cooperativity in a Bilayer Silica-Sandwiched Mixed-Metals Nanocatalyst Design for Absolute Selectivity Switch.

Unlike homogeneous metal complexes, achieving absolute control over reaction selectivity in heterogeneous catalysts remains a formidable challenge due to the unguided molecular adsorption/desorption on metal-surface sites. Conventional organic surface modifiers or ligands and rigid inorganic and metal-organic porous shells are not fully effective. Here, we introduce the concept of "ligand-porous shell cooperativity" to desirably reaction selectivity in heterogeneous catalysis.

Optically Transparent Carbon Electrodes for Single Entity Electrochemistry.

We demonstrate the application and benefit of optically transparent carbon electrodes (OTCEs) for single entity nanoelectrochemistry. OTCEs are prepared by pyrolyzing thin photoresist films on fused quartz coverslips to create conductive, transparent, thin films. Optical, electrical, topographical, and electrochemical properties of OTCEs are characterized to evaluate their suitability for single entity electrochemistry.

Elastomer-assisted graphene transfer technique for enhanced resonance characteristics in chemisorption-based graphene resonant mass sensors.

A process technology was developed for transferring strained graphene sheets using an elastomer nanosheet to enhance the resonance characteristics of a graphene resonator. The strain-induced graphene resonator demonstrated a 1.80-fold improvement in the product of resonant frequency and -factor compared to the unstrained resonator.

Cross-cultural validation of plasma p-tau217 and p-tau181 as precision biomarkers for amyloid PET positivity: An East Asian study in Taiwan and Korea.

Introduction: Plasma phosphorylated tau (p-tau) biomarkers have improved Alzheimer's disease (AD) diagnosis, but data from diverse Asian populations are limited. This study evaluated plasma p-tau217 and p-tau181 levels in Korean and Taiwanese populations.

Methods: All participants (n = 270) underwent amyloid positron emission tomography (PET) and blood tests.

Neuromodulatory effect of transcranial direct current stimulation on cue reactivity and craving in young adults with internet gaming disorder: an event-related potential study.

Objective: This study assessed the effects of transcranial direct current stimulation (tDCS) on cue reactivity and craving for game-related cues using event-related potentials (ERPs) in internet gaming disorder (IGD) patients.

Methods: At baseline, a series of game-related and neutral pictures were shown to both IGD and healthy controls (HCs) while ERPs were recorded. Late positive potentials (LPP) were used to investigate cue reactivity.

A preliminary study of linear accelerator-based spatially fractionated radiotherapy.

Purpose: This study aimed to provide quantitative information for implementing Lattice radiotherapy (LRT) using a medical linear accelerator equipped with the Millennium 120 multi-leaf collimator (MLC). The research systematically evaluated the impact of varying vertex diameters and separations on dose distribution, peak-to-valley dose ratio (PVDR), and normal tissue dose.

Methods: A cylindrical Virtual Water™ phantom was used to create LRT treatments using the Eclipse version 16.

Wide-area topography using reflection phase microscopy for surface inspection.

In this study, we demonstrated an inspection system utilizing reflection phase microscopy to enhance both depth range and field of view (FOV). By implementing a dual-wavelength method, we achieved a maximum expected depth range of 7.7 µm.

Fourier coupled modal method for parallel modal analysis of photonic structures.

We present the Fourier coupled modal method (FCMM) as a solution for large-scale photonic structure analysis, emphasizing its inherent parallelism, facilitated by spatial partitioning and Fourier modal field computation. The parallelism of the FCMM is achieved by integrating the coupled mode theory (CMT) within the Fourier modal method (FMM). The proposed numerical framework of the FCMM is detailed and validated through a comparative study with the conventional FMM.

Description of STRIVE-ON Study Protocol: Safety and Tolerability of GTX-104 (Nimodipine Injection for IV Infusion) Compared with Oral Nimodipine in Patients Hospitalized for Aneurysmal Subarachnoid Hemorrhage (aSAH): A Prospective, Randomized, Phase III Trial (STRIVE-ON).

Oral nimodipine is the only drug approved in North America for patients with aneurysmal subarachnoid hemorrhage (aSAH). However, bioavailability is variable and frequently poor, leading to fluctuations in peak plasma concentrations that cause dose-limiting hypotension. Furthermore, administration is problematic in patients who cannot swallow.

A pediatric emergency prediction model using natural language process in the pediatric emergency department.

This study developed a predictive model using deep learning (DL) and natural language processing (NLP) to identify emergency cases in pediatric emergency departments. It analyzed 87,759 pediatric cases from a South Korean tertiary hospital (2012-2021) using electronic medical records. Various NLP models, including four machine learning (ML) models with Term Frequency-Inverse Document Frequency (TF-IDF) and two DL models based on the KM-BERT framework, were trained to differentiate emergency cases using clinician transcripts.

Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting.

Electric load forecasting is crucial in the planning and operating electric power companies. It has evolved from statistical methods to artificial intelligence-based techniques that use machine learning models. In this study, we investigate short-term load forecasting (STLF) for large-scale electricity usage datasets.

Epidemiologic survey for work-related idiopathic interstitial pneumonias focusing on idiopathic pulmonary fibrosis in Korea, 2010-2022.

Objective: This study aimed to share the process of epidemiologic survey and demonstrate the decisive factors for evaluating work-related Idiopathic interstitial pneumonias (IIPs) in Korea.

Methods: Data and reports of epidemiologic surveys were investigated and completed during 2010-2022.

Results: A total of 228 idiopathic pulmonary fibrosis (IPF) cases requested for an epidemiologic survey, of which 153 (67.

A novel clinical investigation using deep learning and human-in-the-loop approach in orbital volume measurement.

Orbital volume assessment is crucial for surgical planning. Traditional methods lack efficiency and accuracy. Recent studies explore AI-driven techniques, but research on their clinical effectiveness is limited.

Receptor-ligand interactions for optimized endocytosis in targeted therapies.

Receptor-mediated endocytosis plays a crucial role in the success of numerous therapies and remains central to advancing drug development. This process begins with ligand binding to specific receptors, triggering the internalization and intracellular trafficking of receptor-ligand complexes. These complexes are subsequently directed into distinct routes, either toward lysosomal degradation or recycling to the cell surface, with implications for therapeutic outcomes.

The potential of lazertinib and amivantamab combination therapy as a treatment strategy for uncommon EGFR-mutated NSCLC.

Uncommon epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) pose therapeutic challenge due to limited response to EGFR tyrosine kinase inhibitors (TKIs). This study presents preclinical evidence and mechanistic insights into the combination of lazertinib, a third-generation EGFR-TKI; and amivantamab, an EGFR-MET bispecific antibody, for treating NSCLC with uncommon EGFR mutations. The lazertinib-amivantamab combination demonstrates significant antitumor activity in patient-derived models with uncommon EGFR mutations either before treatment or after progressing on EGFR-TKIs.

Psychiatric disorders in adolescent and young adult cancer survivors in Korea.

Background: Although adolescent and young adult (AYA) cancer survivors have an increased risk of psychiatric disorders, limited evidence has been suggested. We aimed to determine the risk of psychiatric disorders among AYA cancer survivors.

Materials And Methods: A retrospective population-based cohort study based on the Korea National Health Insurance Service database was carried out.

Improving flood-prone areas mapping using geospatial artificial intelligence (GeoAI): A non-parametric algorithm enhanced by math-based metaheuristic algorithms.

Flooding presents substantial dangers to human lives and infrastructure, underscoring the need to map flood-prone areas to implement effective mitigation measures precisely. Although machine learning algorithms have made great strides, their accuracy in flood susceptibility mapping (FSM) remains limited due to data dependence, interpretability, and explainability issues, overfitting, generalization difficulties, and hyperparameter tuning. This study suggests combining the Decision Tree (DT) algorithm with advanced, math-based metaheuristic optimization algorithms to address these limitations.

Health-related quality of life across menopausal stages among middle-aged Korean women.

Objectives: We examined the health-related quality of life (HRQoL) during menopause transition (MT) among middle-aged Korean women.

Methods: This cross-sectional study comprised 2,290 middle-aged women who completed web-based questionnaires between 2020 and 2022. Based on self-reported menstrual cycle patterns, menopause status was classified as premenopausal, early or late transition, or postmenopausal.

Intraindividual Comparison of Image Quality Between Low-Dose and Ultra-Low-Dose Abdominal CT With Deep Learning Reconstruction and Standard-Dose Abdominal CT Using Dual-Split Scan.

Objective: The aim of this study was to intraindividually compare the conspicuity of focal liver lesions (FLLs) between low- and ultra-low-dose computed tomography (CT) with deep learning reconstruction (DLR) and standard-dose CT with model-based iterative reconstruction (MBIR) from a single CT using dual-split scan in patients with suspected liver metastasis via a noninferiority design.

Materials And Methods: This prospective study enrolled participants who met the eligibility criteria at 2 tertiary hospitals in South Korea from June 2022 to January 2023. The criteria included (a) being aged between 20 and 85 years and (b) having suspected or known liver metastases.

(NH)CdClF and (NH)CdBrF: The First Fluoride-Containing d Metal Mixed Halides Exhibiting Superior Ultraviolet Nonlinear Optical Properties.

In the search for new ultraviolet (UV) nonlinear optical (NLO) materials, two novel cadmium mixed halide compounds, (NH)CdClF and (NH)CdBrF, are successfully synthesized via hydrothermal methods. These compounds crystallize in the noncentrosymmetric (NCS) space group, R32, and are composed of distorted octahedral [CdXF] (X═Cl or Br) units, which extend into a 3D framework. Remarkably, both compounds demonstrate strong second-harmonic generation (SHG) efficiencies-3.