Prediction of Phenoconversion into Alpha-Synucleinopathy in Patients with isolated REM Sleep Behavior Disorder Using Event-Related Potentials During Visuospatial Attention Tasks.

Study Objectives: Isolated REM sleep behavior disorder (iRBD) is recognized as a prodromal stage of alpha-synucleinopathies. Predicting phenoconversion in iRBD patients remains a key challenge. We aimed to investigate whether event-related potentials (ERPs) recorded during visuospatial attention task can serve as predictors of phenoconversion in iRBD patients.

Staged versus immediate complete revascularization for non-culprit arteries in acute myocardial infarction: a post-hoc analysis of FRAME-AMI.

Background And Objectives: The optimal timing for complete revascularization (CR) in patients with acute myocardial infarction (AMI) and multivessel disease (MVD) remain uncertain.

Methods: This post-hoc analysis of the FRAME-AMI trial included AMI patients with MVD ( = 549). They were classified into immediate ( = 329) and staged CR ( = 220) groups.

Development of a multi-scale nanofiber scaffold platform for structurally and functionally replicated artificial perforating arteries.

Experimental models for exploring abnormal brain blood vessels, including ischemic stroke, are crucial in neuroscience; recently, significant attention has been paid to artificial tissues through tissue engineering. Nanofibers, although commonly used as tissue engineering scaffolds, undergo structural deformations easily, making it challenging to create uniform tissue, especially for the smallest-diameter ones such as perforating arteries. This study focused on the development of a platform capable of reconstructing structurally and functionally replicated perforating arteries.

Correlation between individual thigh muscle volume and grip strength in relation to sarcopenia with automated muscle segmentation.

Introduction: Grip strength serves as a significant marker for diagnosing and assessing sarcopenia, particularly in elderly populations. The study aims to explore the relationship between individual thigh muscle volumes and grip strength, leveraging advanced AI-based UNETR segmentation techniques for accurate muscle volume assessment.

Methods: The study included 49 participants from a cohort of 478 patients diagnosed with hip fractures at Gyeongsang National University Hospital.

Factors Associated With Medical Expenses Among Long-Term Care Insurance Recipients Aged 65 Years or Older in Korea.

This study examined the factors associated with medical expenses among LTCI (long-term care insurance) recipients in Korea. Secondary data analysis was performed using the 2019 Korea National Health Insurance (KNHI) reimbursement data of I metropolitan city. Data from 52 434 older adults who were LTCI recipients and living in I metropolitan city areas were included.

Peroxiredoxin 1-Toll-like receptor 4-p65 axis inhibits receptor activator of nuclear factor kappa-B ligand-mediated osteoclast differentiation.

Peroxiredoxin 1 (PRDX1), an intracellular antioxidant enzyme, has emerged as a regulator of inflammatory responses via Toll-like receptor 4 (TLR4) signaling. Despite this, the mechanistic details of the PRDX1-TLR4 axis and its impact on osteoclast differentiation remain elusive. Here, we show that PRDX1 suppresses RANKL-induced osteoclast differentiation.

High-Performance InP Quantum-Dot Light-Emitting Diodes with a NiO Nanoparticle-Embedded Hybrid Emissive Layer.

Quantum-dot (QD) light-emitting diodes (QLEDs) are garnering significant attention owing to their superb optoelectrical properties, but the overinjection of electrons compared to holes into the emissive layer (EML) is still a critical obstacle to be resolved. Current approaches, such as inserting a charge-balancing interlayer and mixing p-type organic additives into the EML, face issues of process complexity and poor miscibility. In this work, we demonstrate efficient InP QLEDs by simply embedding NiO nanoparticles (NPs) into the EML which forms a homogeneous QD-metal oxide hybrid EML.

Revealing systematic changes in the transcriptome during the transition from exponential growth to stationary phase.

Unlabelled: The composition of bacterial transcriptomes is determined by the transcriptional regulatory network (TRN). The TRN regulates the transition from one physiological state to another. Here, we use independent component analysis to monitor the composition of the transcriptome during the transition from the exponential growth phase to the stationary phase.

Survivorship concerns among posttreatment cancer survivors in South Korea: A secondary analysis of a cross-sectional survey.

Background: Cancer survivors may have a variety of survivorship concerns despite their cancer treatment having ended, with some negatively affecting their health-related quality of life. An in-depth understanding of survivorship concerns is essential for the development of survivorship care programs. However, previous findings have been limited to Western countries, and evidence from Asian countries is lacking.

Cryoballoon Pulmonary Vein Isolation With Versus Without Additional Right Atrial Linear Ablation for Persistent Atrial Fibrillation: The CRALAL Randomized Clinical Trial.

Background: Pulmonary vein isolation (PVI) alone is less effective in patients with persistent atrial fibrillation (AF) compared with those with paroxysmal AF. We investigate whether additional linear ablation from the superior vena cava to the right atrial septum and cavotricuspid isthmus ablation improves the rhythm outcome of patients with persistent AF undergoing cryoballoon PVI (Cryo-PVI).

Methods: In this investigator-initiated, multicenter, randomized clinical trial, 289 patients with persistent AF refractory to antiarrhythmic drug therapy were randomized 1:1 to either Cryo-PVI with additional right atrium (RA) linear ablation or Cryo-PVI alone.

Sticky Polyelectrolyte Shield for Enhancing Biological Half-Life of Growth Factors.

Delivery of secretomes, which includes growth factors, cytokines, and mRNA, is critical in regenerative medicine for cell-to-cell communication. However, the harsh in vivo environment presents significant challenges for secretome delivery. Proteolytic enzymes shorten secretomes' half-lives, and secretomes tend to rapidly diffuse at defect sites.

Neurally adjusted ventilatory assist improves survival, and its early application accelerates weaning in preterm infants.

Background: Evidence to show that neurally adjusted ventilatory assist (NAVA) improves clinical outcomes is lacking. We aimed to analyze whether NAVA improves respiratory outcomes in preterm infants who require invasive mechanical ventilation.

Methods: A retrospective cohort study was conducted in 122 very low birthweight infants who required invasive mechanical ventilation for more than 24 h at one tertiary neonatal intensive care unit in Korea from January 2016 to June 2023.

Changes in retail cigarette price after tax increase: Findings from the 2018-2020 ITC Vietnam surveys.

Introduction: No longitudinal study has investigated the impact of cigarette tax increases on retail prices in Vietnam. This study aims to describe changes in the purchase price of cigarettes following an excise tax increase from 70% to 75% in January 2019.

Methods: Data were collected from people who currently smoke cigarettes in the longitudinal ITC Vietnam surveys: 1870 participants in Wave 1 (pre-increase), 1564 in Wave 2 (post-increase), and 1308 in Wave 3 (post-increase).

Development of Marine-Degradable Poly(Ester Amide)s with Strong, Up-Scalable, and Up-Cyclable Performance.

Biodegradable polyesters provide an attractive alternative to non-degradable plastics but often encounter a tradeoff between biodegradability and mechanical properties because esters are rotational and lack hydrogen bonds. Conversely, natural polyamides, i.e.

AI-powered decision making for road safety optimization under probabilistic linguistic Sugeno-Weber aggregation information.

Traffic accidents, a global concern, pose threats to lives and carry substantial economic and societal burdens. This paper explores the innovative integration of artificial intelligence (AI) into the ambiance of Multi Criteria Decision Making (MCDM) to address the challenge. We investigate AI's potential to enhance road safety globally, utilizing data analysis, predictive modeling, and intelligent traffic management systems.

Deep-Learning and Dynamic Time Warping-Based Approaches for the Diagnosis of Reactor Systems.

The degradation of clamping force in the core support barrel, which forms the internal structure of a nuclear power plant, has the potential to significantly impact the plant's safety and reliability. Previous studies have concentrated on the detection of clamping force degradation but have been constrained in their ability to identify the precise size and position. This study proposes a novel methodology for diagnosing the size and position of clamping force degradation in core support barrels, combining deep-learning techniques and dynamic time warping (DTW) algorithms.

Construction of Electrospun ZnO-NiO Nanofibers for Enhanced Ethanol Gas Sensing.

Semiconducting metal oxides with nanofiber (NF) morphologies are among the most promising materials for the realization of gas sensors. In this study, we have prepared electrospun ZnO-NiO composite NFs with different amounts of NiO (0, 20, 40, 60 and 80% wt%) for the systematic study of ethanol gas sensing. The fabricated composite NFs were annealed at 600 °C for crystallization.

Combinatorial Effects of Terpene, Chenodeoxycholic Acid, and Ursodeoxycholic Acid on Common Bile Duct Stone Recurrence and Gallbladder Stone Dissolution.

Ursodeoxycholic acid (UDCA), chenodeoxycholic acid (CDCA) plus UDCA (C&U), and terpene are widely administered to prevent common bile duct (CBD) stone recurrence and dissolve gallbladder (GB) stones. We evaluated and compared the combined effects of these agents on CBD stone recurrence and GB stone resolution. This study included patients who underwent endoscopic retrograde cholangiopancreatography (ERCP) at six referral centers, retrospectively.

Comparative Analysis of M4CXR, an LLM-Based Chest X-Ray Report Generation Model, and ChatGPT in Radiological Interpretation.

This study investigated the diagnostic capabilities of two AI-based tools, M4CXR (research-only version) and ChatGPT-4o, in chest X-ray interpretation. M4CXR is a specialized cloud-based system using advanced large language models (LLMs) for generating comprehensive radiology reports, while ChatGPT, built on the GPT-4 architecture, offers potential in settings with limited radiological expertise. This study evaluated 826 anonymized chest X-ray images from Inha University Hospital.

Validation of Artificial Intelligence Computer-Aided Detection on Gastric Neoplasm in Upper Gastrointestinal Endoscopy.

Background/objectives: Gastric cancer ranks fifth for incidence and fourth in the leading causes of mortality worldwide. In this study, we aimed to validate previously developed artificial intelligence (AI) computer-aided detection (CADe) algorithm, called ALPHAON in detecting gastric neoplasm.

Methods: We used the retrospective data of 500 still images, including 5 benign gastric ulcers, 95 with gastric cancer, and 400 normal images.

Deterministic reflection contrast ellipsometry for thick multilayer two-dimensional heterostructures.

Optical spectroscopy is a powerful tool for characterizing the properties of two-dimensional (2D) heterostructures. However, extracting the permittivity information of each 2D layer in optically thick heterostructures is challenging because of interference. To accurately measure the optical permittivity of each 2D layer in a heterostructure or on a substrate with a thick insulating spacer, such as oxides, we propose deterministic reflection contrast ellipsometry (DRCE).

From waste to wealth: Exploring the effect of particle size on biopolymer harvesting from aerobic granular sludge.

This study aimed to examine the impact of aerobic granular sludge (AGS) sizes on its properties and alginate-like exopolymers (ALE) recovery potential. The AGS was cultivated in a lab-scale bioreactor and categorized into six size classes with 200 μm intervals. There appeared a critical size (400-800 μm) for developing stable AGS structure and excellent ALE recovery.

Exploring diabetes through the lens of AI and computer vision: Methods and future prospects.

Early diagnosis and timely initiation of treatment plans for diabetes are crucial for ensuring individuals' well-being. Emerging technologies like artificial intelligence (AI) and computer vision are highly regarded for their ability to enhance the accessibility of large datasets for dynamic training and deliver efficient real-time intelligent technologies and predictable models. The application of AI and computer vision techniques to enhance the analysis of clinical data is referred to as eHealth solutions that employ advanced approaches to aid medical applications.

In Vivo Bioluminescence Imaging of Tumor Progression in the Lewis Lung Carcinoma Orthotopic Mouse Model: A Comparison Between the Tail Vein Injection and Intranasal Instillation Methods.

Metastasis remains a leading cause of cancer-related mortality, yet its study has been constrained by the lack of reliable animal models that faithfully replicate this complex process. Syngeneic models for studying lung cancer metastasis are limited, with the Lewis lung carcinoma (LLC) model being the most commonly employed. The conventional LLC orthotopic model involves injecting LLC cells intravenously (i.