Comparison of early warning scoring systems for predicting stroke occurrence among hospitalized patients: A study using smart clinical data warehouse.

Background: This study aimed to evaluate the predictive ability of two widely used early warning scoring systems, the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS), for predicting stroke occurrence in hospitalized patients.

Methods: The study enrolled 5,474 patients admitted to the intensive care unit from the general ward using data from the Smart Clinical Data Warehouse (CDW). MEWS and NEWS were calculated based on vital signs and clinical parameters within four hours of stroke onset.

Transcriptomic Changes in Human Tonsil-Derived Mesenchymal Stem Cells Across Culture Passages.

Background/objectives: Tonsil-derived mesenchymal stem cells (TMSCs) are in the limelight in regenerative medicine due to their high proliferation and differentiation potential. It is important to conduct studies to determine the optimal conditions for achieving the maximum yield while maintaining the optimal differentiation capacity of TMSCs.

Methods: This study explores the impact of serial subculture on TMSCs by analyzing gene expression at passages 2, 4, 6, and 8.

Association between laboratory data-based frailty index and clinical health outcomes in critically ill older patients: A retrospective correlational study.

Background: Although frailty assessment is crucial for understanding critically ill patients' prognosis, traditional frailty measures require substantial efforts and time from health care professionals. To address this limitation, the laboratory frailty index (FI-LAB) based on laboratory clinical data was developed. However, knowledge regarding its correlation with health outcomes among critically ill older patients is limited.

Edge Artificial Intelligence Device in Real-Time Endoscopy for Classification of Gastric Neoplasms: Development and Validation Study.

Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge computing devices.

Large Language Models in Gastroenterology: Systematic Review.

Background: As health care continues to evolve with technological advancements, the integration of artificial intelligence into clinical practices has shown promising potential to enhance patient care and operational efficiency. Among the forefront of these innovations are large language models (LLMs), a subset of artificial intelligence designed to understand, generate, and interact with human language at an unprecedented scale.

Objective: This systematic review describes the role of LLMs in improving diagnostic accuracy, automating documentation, and advancing specialist education and patient engagement within the field of gastroenterology and gastrointestinal endoscopy.

An AIE-based fluorescent dye for selective staining of polyamide microplastics without pretreatment: Applications to environmental samples and zebrafish.

A novel staining dye, BEM ((1E,1'E)-1,1'-([2,2'-bithiophene]-5,5'-diyl)bis(N-(9-ethyl-9H-carbazol-3-yl)methanimine)) was synthesized for selective identification of polyamide (PA) micrplastics. BEM showed unique photophysical properties such as solvatochromism, intramolecular charge transfer (ICT), and aggregation induced emission (AIE) which were demonstrated through spectroscopic analysis and density functional theory (DFT) calculations. The optimal staining conditions for selective staining of PA by BEM were established by evaluating the staining efficiency according to the variation of the solvent compositions, concentrations of BEM, and staining durations.

In Vitro Susceptibility and Synergistic Effect of Bismuth Against .

Bismuth is commonly used in () eradication therapy. However, few studies have examined the in vitro susceptibility of to bismuth. Moreover, the exact mechanism of action of bismuth on remains unclear.

Association between Dietary Antioxidants and Atherosclerotic Cardiovascular Disease in South Korea: Insights from a Comprehensive Cross-Sectional Analysis.

: The multifactorial nature of atherosclerotic cardiovascular disease (ASCVD) implicates genetic, environmental, and dietary habits. Antioxidants found in foods have garnered attention for their potential role in mitigating ASCVD risk by combating oxidative stress. This study seeks to confirm the findings of previous research through a large-scale cross-sectional analysis performed in a unique population with Korea National Health and Nutrition Examination Survey data to explore the association between the composite dietary antioxidant index (CDAI) and ASCVD prevalence among middle- and old-aged individuals in South Korea.

Ensemble Fusion Models Using Various Strategies and Machine Learning for EEG Classification.

Electroencephalography (EEG) helps to assess the electrical activities of the brain so that the neuronal activities of the brain are captured effectively. EEG is used to analyze many neurological disorders, as it serves as a low-cost equipment. To diagnose and treat every neurological disorder, lengthy EEG signals are needed, and different machine learning and deep learning techniques have been developed so that the EEG signals could be classified automatically.

Design of multi-modal antenna arrays for microwave hyperthermia and 1H/1⁹F MRI monitoring of drug release.

This simulation-based study presented a novel hybrid RF antenna array designed for neck cancer treatment within a 7T MRI system. The proposed design aimed to provide microwave hyperthermia to release 19F-labeled anticancer drugs from thermosensitive liposomes, facilitating drug concentration monitoring through 19F imaging and enabling 1H anatomical imaging and MR thermometry for temperature control. The design featured a bidirectional microstrip for generating the magnetic |B1|-fields required for 1H and 19F MR imaging, along with a patch antenna for localized RF heating.

Machine Learning Predictions and Identifying Key Predictors for Safer Intubation: A Study on Video Laryngoscopy Views.

This study develops a predictive model for video laryngoscopic views using advanced machine learning techniques, aiming to enhance airway management's efficiency and safety. A total of 212 participants were involved, with 169 in the training set and 43 in the test set. We assessed outcomes using the percentage of glottic opening (POGO) score and considered factors like the modified Mallampati classification, thyromental height and distance, sternomental distance, mouth opening distance, and neck circumference.

Tuberculous Pleural Effusion-Derived Exosomal miR-130b-3p and miR-423-5p Promote the Proliferation of Lung Cancer Cells via Cyclin D1.

Epidemiologic studies have shown an association between tuberculosis and lung cancer. The altered tumor microenvironment after tuberculosis infection appears to contribute to cancer progression. Pleural effusions are enriched in exosomes, which act as mediators of intercellular communication.

Lifestyle risk behavior and atherosclerotic cardiovascular risk: An analysis using the Korea National Health and Nutrition Examination Survey.

Background: Clustering lifestyle risk behaviors is important for predicting cardiovascular disease risk. However, it is unclear which behavior mediates other ones to influence cardiovascular disease risk. We aimed to assess the causal inference of each lifestyle risk behavior for the atherosclerotic cardiovascular disease (ASCVD) risk of the general population.

Association of liver function markers and apolipoprotein E ε4 with pathogenesis and cognitive decline in Alzheimer's disease.

Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder influenced by various factors, including liver function, which may impact the clearance of amyloid-β (Aβ) in the brain. This study aimed to explore how the apolipoprotein E () ε4 allele affects the relationship of liver function markers with AD pathology and cognition.

Methods: We analyzed data from two independent cohorts, including 732 participants from the Hallym University Medical Center and 483 from the Alzheimer's Disease Neuroimaging Initiative, each group consisting of individuals with and without the ε4 allele.

Therapeutic Effect of Donepezil on Neuroinflammation and Cognitive Impairment after Moderate Traumatic Brain Injury.

Background: Despite the important clinical issue of cognitive impairment after moderate traumatic brain injury (TBI), there is currently no suitable treatment. Here, we used in vitro and in vivo models to investigate the effect of Donepezil-an acetylcholinesterase (AChE) inhibitor-on cognitive impairment in the acute period following injury, while focusing on neuroinflammation and autophagy- and mitophagy-related markers.

Methods: The purpose of the in vitro study was to investigate potential neuroprotective effects in TBI-induced cells after donepezil treatment, and the in vivo study, the purpose was to investigate therapeutic effects on cognitive impairment in the acute period after injury by analyzing neuroinflammation and autophagy- and mitophagy-related markers.

Longitudinal Genome-Wide Association Study of Cognitive Impairment after Subarachnoid Hemorrhage.

Objectives: The occurrence of cognitive deficits after subarachnoid hemorrhage (SAH) is highly possible, leading to vascular dementia. We performed a novel longitudinal genome-wide association study (GWAS) to identify genetic modifications associated with cognitive impairment following SAH in a long-term prospective cohort study.

Materials And Methods: This GWAS involved 153 patients with SAH sharing 5,971,372 markers after high-throughput imputation.

Diabetes Mellitus as a Risk Factor for Spontaneous Preterm Birth in Women with a Short Cervix after Ultrasound-Indicated Cerclage.

Preterm birth (PTB) is a significant challenge in contemporary obstetrics, affecting over one in ten infants worldwide and accounting for 75% of perinatal mortality. Short cervical length during mid-trimester is well known to be associated with an increased risk of spontaneous preterm birth (sPTB). Ultrasound-indicated cerclage (UIC) is recommended to prevent sPTB in women with a short cervix at mid-trimester and a history of sPTB.

expHRD: an individualized, transcriptome-based prediction model for homologous recombination deficiency assessment in cancer.

Background: Homologous recombination deficiency (HRD) stands as a clinical indicator for discerning responsive outcomes to platinum-based chemotherapy and poly ADP-ribose polymerase (PARP) inhibitors. One of the conventional approaches to HRD prognostication has generally centered on identifying deleterious mutations within the BRCA1/2 genes, along with quantifying the genomic scars, such as Genomic Instability Score (GIS) estimation with scarHRD. However, the scarHRD method has limitations in scenarios involving tumors bereft of corresponding germline data.

Development and validation of risk prediction model for post-donation renal function in living kidney donors.

This study aimed to create and validate a predictive model for renal function following live kidney donation, using pre-donation factors. Accurately predicting remaining renal function post live kidney donation is currently insufficient, necessitating an effective assessment tool. A multicenter retrospective study of 2318 live kidney donors from two independent centers (May 2007-December 2019) was conducted.