Temperamental and Neurocognitive Predictors in Korean Basketball League Draft Selection.

Objective: This study hypothesized that physical status, temperament and characteristics, and neurocognitive functions of basketball players could predict the result of Korean Basketball League (KBL) draft selection.

Methods: We recruited the number of 89 college elite basketball players (KBL selection, n=44; non-KBL selection, n=45), and the number of 82 age-matched healthy comparison subjects who major in sports education in college. All participants were assessed with the Temperament and Character Inventory, Sports Anxiety Scales, Beck Depression Inventory, Perceived Stress Scale-10, Trail Making Test, and Computerized Neuro-cognitive Test for Emotional Perception and Mental Rotation.

Diabetes Is Positively Associated With High Risk of Depression in Korean Cervical Cancer Patients: Korean National Health and Nutrition Examination Survey 2010-2021.

Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients.

Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups-high risk of depression and non-depression-based on their answers to survey items related to depression.

The Moderating Effect of Internet Ethics on the Relationship Between Cyberbullying Victimization and Perpetration Among Korean Adults.

Objective: Cyberbullying is increasing every year and poses a serious problem worldwide; although the rate of adult cyberbullying is increasing every year, still cyberbullying studies mainly focused on youths. This study examined the moderating effect of Internet ethics on the relationship between cyberbullying victimization and perpetration among adults.

Methods: An online self-report survey was conducted with 601 participants aged 20 to 59.

Healing Through Loss: Exploring Nurses' Post-Traumatic Growth After Patient Death.

Objective: This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.

Methods: An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited.

A New Agenda for Optimizing Roles and Infrastructure in a Mental Health Service Model for South Korea.

Objective: As the demand for community mental health services continues to grow, the need for well-equipped and organized services has become apparent. This study aimed to optimize the roles and infrastructure of mental health services, by establishing, among other initiatives, standardized operating models.

Methods: The study was conducted in multiple phases from May 12, 2021, to December 29, 2021.

Memory Decline and Aberration of Synaptic Proteins in X-Linked Moesin Knockout Male Mice.

Objective: This study aims to investigate may moesin deficiency resulted in neurodevelopmental abnormalities caused by negative impact on synaptic signaling ultimately leading to synaptic structure and plasticity.

Methods: Behavioral assessments measured neurodevelopment (surface righting, negative geotaxis, cliff avoidance), anxiety (open field test, elevated plus maze test), and memory (passive avoidance test, Y-maze test) in moesin-knockout mice (KO) compared to wild-type mice (WT). Whole exome sequencing (WES) of brain (KO vs.

Rapid and Sensitive Detection: Integration of SERS and Acoustofluidics in a Lysis-Free Microfluidic Platform.

Bacterial infections, such as sepsis, require prompt and precise identification of the causative bacteria for appropriate antibiotics treatment. Traditional methods such as culturing take 2-5 days, while newer techniques such as reverse transcription-polymerase chain reaction and mass spectrometry are hindered by blood impurities. Consequently, this study developed a surface-enhanced Raman scattering (SERS)-based acoustofluidic technique for rapid bacterial detection without culturing or lysing.

Enhancing neural stem cell integration in the injured spinal cord through targeted PTEN modulation.

Spinal cord injury results in permanent loss of neurological functions due to severance of neural networks. Transplantation of neural stem cells holds promise to repair disrupted connections. Yet, ensuring the survival and integration of neural stem cells into the host neural circuit remains a formidable challenge.

Dyad System of BOAHY-BODIPY Conjugates as Novel Photoswitchable Photosensitizers for Photodynamic Therapy.

Photodynamic therapy (PDT) offers minimally invasive and repeatable cancer treatment options. Despite advancements in photosensitizer (PS) design, the optical control of PS activation remains unexplored. Here, we present the first photoswitchable PS based on a BOAHY-BODIPY dyad system.

Extracellular vesicle surface engineering with integrins (ITGAL & ITGB2) to specifically target ICAM-1-expressing endothelial cells.

Extracellular vesicles (EVs) are taken up by most cells, however specific or preferential cell targeting remains a hurdle. This study aims to develop an EV that targets cells involved in inflammation, specifically those expressing intercellular adhesion molecule-1 (ICAM-1). To target these cells, we overexpress the ICAM-1 binding receptor "lymphocyte function-associated antigen-1" (LFA-1) in HEK293F cells, by sequential transfection of plasmids of the two LFA-1 subunits, ITGAL and ITGB2 (CD11a and CD18).

MiCML: a causal machine learning cloud platform for the analysis of treatment effects using microbiome profiles.

Background: The treatment effects are heterogenous across patients due to the differences in their microbiomes, which in turn implies that we can enhance the treatment effect by manipulating the patient's microbiome profile. Then, the coadministration of microbiome-based dietary supplements/therapeutics along with the primary treatment has been the subject of intensive investigation. However, for this, we first need to comprehend which microbes help (or prevent) the treatment to cure the patient's disease.

Longitudinal association between hemoglobin and lung function with insights into the incidence of airflow obstruction: an observational study.

Background/aims: Evidence regarding the long-term association between hemoglobin (Hb) levels and lung function in individuals from the general population is scarce. This study aimed to determine the longitudinal association between Hb levels and lung function in a community-based population cohort in South Korea.

Methods: We used linear mixed regression analysis to evaluate the longitudinal associations between Hb levels and lung function parameters, including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV), and FEV/FVC.

Decoding pan-cancer treatment outcomes using multimodal real-world data and explainable artificial intelligence.

Despite advances in precision oncology, clinical decision-making still relies on limited variables and expert knowledge. To address this limitation, we combined multimodal real-world data and explainable artificial intelligence (xAI) to introduce AI-derived (AID) markers for clinical decision support. We used xAI to decode the outcome of 15,726 patients across 38 solid cancer entities based on 350 markers, including clinical records, image-derived body compositions, and mutational tumor profiles.

Hierarchical image classification using transfer learning to improve deep learning model performance for amazon parrots.

Numerous studies have proven the potential of deep learning models for classifying wildlife. Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade. Although deep learning models typically perform better with more input data, the available wildlife data are ordinarily limited, specifically for rare or endangered species.

A single-cell RNA sequencing dataset of peripheral blood cells in long COVID patients on herbal therapy.

Following the coronavirus disease 2019 (COVID-19) pandemic, the rise of long COVID, characterized by persistent respiratory and cognitive dysfunctions, has become a significant health concern. This leads to an increased role of complementary and alternative medicine in addressing this condition. However, our comprehension of the effectiveness and safety of herbal medicines for long COVID remains limited.

A deep learning based model for diabetic retinopathy grading.

Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Existing methods to detect this disease often rely on handcrafted features which limit the adaptability and classification accuracy.

Enhanced multifaceted model for plasmon-driven Schottky solar cells with integrated thermal effects.

This paper explores the development of an opto-thermal-electrical model for plasmonic Schottky solar cells (PSSCs) using a comprehensive multiphysics approach. We simulated the optical properties, power conversion efficiencies, and energy yield of PSSCs with varying nanoparticle (NP) configurations and sizes. Our spectral analysis focused on the absorption characteristics of these solar cells, examining systems sized 3 × 3, 5 × 5, and 7  × 7, with NP radii ranging from 10 to 150 nm.

Effects of Limosilactobacillus fermentum KBL375 on Immune Enhancement and Gut Microbiota Composition in Cyclophosphamide-Induced Immunosuppressed Mice.

This study evaluated the immune-enhancing efficacy of Limosilactobacillus fermentum KBL375 isolated from the feces of healthy Koreans. KBL375-treated splenocytes showed enhancement of cytotoxicity against YAC-1 cells, the target of natural killer (NK) cells, with an increase in CD335, granzyme B, perforin, and interferon-gamma (IFN-γ). Oral administration of KBL375 in mice with cyclophosphamide (CP)-induced immunosuppression improved body weight and immune functions, including immune organ indices, lymphocyte proliferations, and immunoglobulin (Ig) A levels.

Isolation of Natural Products Using Preparative TLC.

Known for their diverse and potent physiological activities, natural products continue to be essential for the discovery and development of new drugs. This chapter explores the pivotal role of preparative thin-layer chromatography (Prep-TLC) in the isolation of natural products. This chapter begins with an understanding of the historical significance and structural complexity of natural products, and discusses the problems caused by complex mixtures present in extracts, as well as the multifunctionality, cost-effectiveness, and compatibility with different sample types of Prep-TLC to address these challenges.

Extraction, Isolation, and Structural Elucidation of Acylated Triterpene Saponins from Asteraceae Family.

Saponins represent specialized (secondary) metabolites primarily sourced from plants, typically characterized by an aglycone component of triterpenoids or steroids, often referred to as sapogenin, coupled with sugar moieties. Their structural intricacy and diversity, along with their manifold pharmacological properties, have garnered significant interest among researchers. Notwithstanding this interest, the study of saponins has been encumbered by challenges in their isolation, purification, and structural characterization.

Identification of Lignans.

Lignans have garnered significant interest in various fields of pharmaceuticals, nutrition, and pesticides due to their diverse biological activities. This chapter primarily focuses on the extraction and purification methods of lignans from Schisandra, followed by an extensive examination of qualitative and quantitative analytical techniques, including thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC). Additionally, methods for structural analysis using nuclear magnetic resonance (NMR) are briefly summarized.

Identification and Profiling of Primary Metabolites Through GC-MS and Associated Data Processing.

This chapter presents a comprehensive approach to profiling plant-derived primary metabolites using metabolomics, highlighting its critical role in decoding the biosynthesis of bioactive plant compounds. It details the utilization of gas chromatography-mass spectrometry (GC-MS) for the effective analysis and profiling of these metabolites. The process, encompassing extraction methods, chemical derivatization, and data processing, is thoroughly outlined.

Isolation of Natural Products from Marine Invertebrates.

Marine invertebrates such as sponges, cnidarians, bryozoans, and tunicates are considered to be prolific sources of novel biologically active natural products. Specimens from these organisms are composed of soft tissues with a high water and inorganic salt content compared to those from terrestrial counterparts. In addition, some of the secondary metabolites from these organisms tend to be more polar than those of terrestrial.

Optimizing Extraction Solvents for Plant Chemical Analysis Using H NMR and Principal Component Analysis.

Natural products, particularly plants, remain a vital source of bioactive compounds owing to their unparalleled metabolic diversity across pharmaceuticals, cosmetics, foods, and agriculture. However, this diversity, encompassing not only a multitude of compounds but also their varying chemical and physical properties, presents a challenge in their effective utilization. Targeted analysis of specific metabolites, as well as untargeted approaches covering a wide metabolite range, necessitate optimal extraction solvents tailored to meet diverse requirements.