A Narrative Review with Strategic Analysis of Home Care Services for Older Adults in Seoul, South Korea: Toward a Comprehensive Care Approach.

Purpose: This study aimed to establish a role framework and organizational redesign for home care services in response to the evolving internal and external environments in South Korea. The specific objectives were: (1) to perform a Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis based on the external and internal factors related to home care services; (2) to propose key ideas for restructuring services and human resources; and (3) to suggest strategies for enhancing the quality of home-based care services.

Patients And Methods: The policy landscape for older adult healthcare in Seoul, South Korea along with the current state and challenges of home care services were reviewed.

Age and sex differences in the relationship of body weight changes with colon cancer risks: A nationwide cohort study.

Colon cancer is a significant health concern, and obesity is a well-established risk factor. However, previous studies have mainly focused on assessing body weight as a risk factor for colon cancer at a specific time point. This nationwide cohort study investigated the association between body weight changes, which can fluctuate throughout an individual's lifespan, and the incidence of colon cancer using the South Korean population database provided by the National Health Insurance Service (NHIS).

Augmented prediction of vertebral collapse after osteoporotic vertebral compression fractures through parameter-efficient fine-tuning of biomedical foundation models.

Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.

Electrochemical and quantum chemical investigation on the adsorption behavior of a schiff base and its metal complex for corrosion protection of mild steel in 15 wt% HCl solution.

This work evaluates the effectiveness of Schiff base derivatives, namely, 2,2'-((1E,1'E)-((2,2-dimethylpropane-1,3-diyl)bis(azaneylylidene))bis(methaneylylidene))diphenol (DAMD) and (2-((E)-((3-(((E)-2-hydroxybenzylidene)amino)-2,2dimethylpropyl)imino)methyl)phenoxy) zinc (HDMZ), as corrosion inhibitors for mild steel in a 15 % HCl solution. By employing a blend of experimental assessments and theoretical computations, such as electrochemical tests, morphological observations, and theoretical simulations, the study achieved an impressive up to 94.6 % inhibition efficiency.

Comparative Analysis of Rhizosphere Fungal Communities in Korean Fir Trees.

The Korean fir (), a native coniferous species of Korea, predominantly inhabits the subalpine zone. Recently, this species has experienced a significant population decline, primarily attributed to environmental changes in the subalpine zone driven by global warming. Efforts to prevent the extinction of the Korean fir are underway, with a predominant focus on abiotic factors contributing to its decline.

Sites of Metastasis and Survival in Metastatic Renal Cell Carcinoma: Results From the Korean Renal Cancer Study Group Database.

Background: In patients with metastatic renal cell carcinoma (mRCC), sites of metastatic involvement have been reported to be associated with a difference in survival. However, the frequency and survival according to different sites of metastases in Korean patients with mRCC remain unclear. Therefore, this study aimed to assess the frequency of metastatic site involvement and the association between sites of metastatic involvement and survival in Korean patients with mRCC.

Insights into an indolicidin-derived low-toxic anti-microbial peptide's efficacy against bacterial cells while preserving eukaryotic cell viability.

Antimicrobial peptides (AMPs) are a current solution to combat antibiotic resistance, but they have limitations, including their expensive production process and the induction of cytotoxic effects. We have developed novel AMP candidate (peptide 3.1) based on indolicidin, among the shortest naturally occurring AMP.

Reduction-immobilizing strategy of polymer-embedded sub-2 nm Cu nanoparticles with uniform size and distribution responsible for robust catalytic reactions.

Polymer-embedded metal nanoparticles are in great demand owing to their unique features, leading to their use in various important applications, including catalysis reactions. However, particle sintering and aggregation are serious drawbacks, resulting in a drastic loss of catalytic activity and recyclability. Herein, a reduction-immobilizing strategy of polymer-embedded sub-2 nm Cu nanoparticles offered highly controlled distribution and nanoparticle size within polymer structures with high fidelity.

Efficient multifunctional PPy-NTs/PEI@alginate@NiFeO magnetic beads for heavy metals removal: Experimental design and optimization interpretations.

A highly effective magnetic nanocomposite alginate beads (PPy-NTs/PEI@Alg@NiFeO) were synthesized using alginate as the encapsulation reagent and polypyrrole/polyethylene imine with nano NiFeO as a functional filler to remove toxic Zn and Pb from polluted water. A response surface methodology (RSM) was used to statistically assess the influences of pH and the adsorbent dose on the adsorption performance. PPy-NTs/PEI@Alg@NiFeO magnetic microbeads exhibited the optimal adsorption capacity q (18.

WISE: Efficient WSI selection for active learning in histopathology.

Deep neural network (DNN) models have been applied to a wide variety of medical image analysis tasks, often with the successful performance outcomes that match those of medical doctors. However, given that even minor errors in a model can impact patients' life, it is critical that these models are continuously improved. Hence, active learning (AL) has garnered attention as an effective and sustainable strategy for enhancing DNN models for the medical domain.

Intracalvariosseous administration of donepezil microspheres protects against cognitive impairment by virtue of long-lasting brain exposure in mice.

Recent studies have demonstrated the direct connections between the skull bone marrow, meninges, and brain. In an effort to explore these connections for the purpose of brain drug delivery, we previously proposed the direct application of CNS drugs into the diploic space between the outer and inner cortex of the skull, namely, intracalvariosseous administration (ICO). It was successfully demonstrated that small molecular to large colloidal drugs can readily reach the brain after ICO in mice and rabbits.

Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.

Context.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic biopsy (EB) slides for incorrect diagnoses.

Objective.

Refinement and Validation of the Team Effectiveness Scale for Nursing Units.

Purpose: Understanding that the complexity and dynamic nature of the nursing care setting creates diverse conditions for teamwork is important when developing tools to measure nursing unit team effectiveness. The Team Effectiveness Scale for Nursing Units (TES-NU), based on the Integrated Team Effectiveness Model, was developed without confirmatory factor analysis and only tested on one nursing organization. It needs further research to prove its validity and reliability.

The relationship between social frailty and cognitive impairment among older adults: the role of various types of internet use.

Introduction: This study aimed to explore the role of internet use in the relationship between social frailty and cognitive function among Korean older adults.

Methods: A nationally representative survey of community-dwelling older adults in Korea was used in the analysis ( = 8,639).

Results: All types of internet use were significantly associated with cognitive impairment and played a significant role in the relationship between social frailty and cognitive impairment.

Caffeine consumption of medical students in Korea: amount and symptoms based on a 2023 survey.

Purpose: To investigate the form and level of daily caffeine intake recommended above 400 mg in medical students expected to consume caffeinated beverages to enhance their performance.

Methods: From May to June 2023, freshman through senior medical students at a medical school in Korea were administered a seven-item questionnaire designed to measure the amount of caffeine-containing foods consumed, the weekly interval between consumption, the reason for consumption, and the level of caffeine-induced symptoms experienced.

Results: Out of 443 students, 361 responded (81.

Post-Modification Approach for Self-Exfoliated Synthesis of Pyridinium Sulfobetaine Covalent Organic Frameworks for Enhanced Lithium-Ion Conductivity.

While covalent organic frameworks (COFs) have been extensively investigated in the field of organic electrolyte materials, there is potential for further enhancement of their room-temperature ionic conductivity. This study introduces a novel methodology to induce self-exfoliation in the parent COF during synthesis through a postmodification technique. This process yields covalent organic nanosheets that feature pyridinium sulfobetaine groups, referred to as PS-CON.

Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology Imaging.

Tumor Cellularity (TC) is an important metric for assessing organ tumor burden. However, manual cell counting is not feasible due to large volumes of pathology images and inconsistent measurements between pathologists. The PAIP 2023 Challenge aimed to solve this problem using AI.

RESP2: An uncertainty aware multi-target multi-property optimization AI pipeline for antibody discovery.

Discovery of therapeutic antibodies against infectious disease pathogens presents distinct challenges. Ideal candidates must possess not only the properties required for any therapeutic antibody (e.g.

Dual-Action Protein-siRNA Conjugates for Targeted Disruption of CD47-Signal Regulatory Protein α Axis in Cancer Therapy.

A series of successes in RNA interference (RNAi) therapies for liver diseases using lipid nanoparticles and -acetylgalactosamine have heralded a current era of RNA therapeutics. However, alternative delivery strategies are required to take RNAi out of the comfort zone of hepatocytes. Here we report SIRPα IgV/anti-CD47 siRNA (vS-siCD47) conjugates that selectively and persistently disrupt the antiphagocytic CD47/SIRPα axis in solid tumors.

Systemic Brain Delivery of Oligonucleotide Therapeutics Enhanced by Protein Corona-Assisted DNA Cubes.

The systemic delivery of oligonucleotide therapeutics to the brain is challenging but highly desirable for the treatment of brain diseases undruggable with traditional small-molecule drugs. In this study, a set of DNA nanostructures is prepared and screened them to develop a protein corona-assisted platform for the brain delivery of oligonucleotide therapeutics. The biodistribution analysis of intravenously injected DNA nanostructures reveals that a cube-shaped DNA nanostructure (D-Cb) can penetrate the brain-blood barrier (BBB) and reach the brain tissue.

Exploring the Role of Social Factors in Cognitive Frailty among South Korean Older Adults.

Cognitive frailty, which is characterized by the co-occurrence of physical frailty and cognitive impairment, poses significant risks to the well-being and independence of elderly individuals. Previous research has established that demographic, health-related, and social factors contribute to both physical frailty and cognitive decline. However, the role of social factors in influencing cognitive frailty remains unclear.

TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction.

Protein-protein interactions (PPIs) are important for many biological processes, but predicting them from sequence data remains challenging. Existing deep learning models often cannot generalize to proteins not present in the training set and do not provide uncertainty estimates for their predictions. To address these limitations, we present TUnA, a Transformer-based uncertainty-aware model for PPI prediction.