DCB-HBR trial is prospective, multi-center, open-label, randomized controlled, noninferiority trial.
The aim of the study is to compare clinical outcomes of drug-coated balloon (DCB) with drug-eluting stent (DES) for treatment of de-novo coronary lesion in patients with high bleeding risk (HBR).

开始日期2022-07-29

申办/合作机构

Samsung Medical Center

[+11]

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2025-01-01·Journal of Affective Disorders

Longitudinal analysis of anxiety and sleep disorders in the Korean population with disabilities, from 2006 to 2017: Incidence, prevalence, and association with disability type and severity

Article

作者: Kim, S.Y. ; Kim, Y Y ; Park, J H ; Kim, S Y ; Lee, H.-Y. ; Yeob, K E ; Lee, H-Y ; Yeob, K.E. ; Kim, Y.Y. ; Park, J.-H.

BACKGROUNDIndividuals with disabilities often face a higher risk of concurrent psychological problems, yet comprehensive assessments of the anxiety and sleep disorders in this population remain limited. This study examined longitudinal trends in the incidence and prevalence of anxiety and sleep disorders among people with disabilities and explored their associations with disability type and severity.METHODSUtilizing claim data from the National Health Insurance database and the National Disability Registry, which cover the entire Korean population, we estimated the age-standardized incidence and prevalence of anxiety and sleep disorders between 2006 and 2017. Logistic regression was used to analyze the associations between disability type and severity and these disorders.RESULTSThe unadjusted incidence and prevalence of anxiety and sleep disorders were consistently higher among individuals with disabilities during the study period. A significant gap in the prevalence of these disorders persisted between individuals with and without disabilities in both sexes, even after accounting for socioeconomic status and comorbidities. However, the incidence showed mixed results, with some categories of disabilities showing lower likelihood of developing the conditions compared to individuals without disabilities.CONCLUSIONSActions should also be taken to identify undiagnosed cases of anxiety and sleep disorders among individuals with disabilities. Moreover, individuals with disabilities who are diagnosed with these disorders should be more actively managed to avert the progression to the chronic stage.

2025-01-01·Current Bioinformatics

Relational Graph Convolution Network with Multi Features for Anti- COVID-19 Drugs Discovery using 3CL^pro Potential Target

作者: Jo, Kyuri ; Kim, Young Jin ; Jeong, Young-Seob ; Ndomba, Goodwill Erasmo ; Mswahili, Medard Edmund

Background:The potential of graph neural networks (GNNs) to revolutionize the analysis of non-Euclidean data has gained attention recently, making them attractive models for deep machine learning. However, insufficient compound or molecular graphs and feature representations might significantly impair and jeopardize their full potential. Despite the devastating impacts of ongoing COVID-19 across the globe, for which there is no drug with proven efficacy that has been shown to be effective. As various stages of drug discovery and repositioning require the accurate prediction of drug-target interactions (DTI), here, we propose a relational graph convolution network (RGCN) using multi-features based on the developed drug compound-coronavirus target graph data representation and combination of features. During the implementation of the model, we further introduced the use of not only the feature module to understand the topological structure of drugs but also the structure of the proven drug target (i.e., 3CLpro) for SARS-CoV-2 that shares a genome sequence similar to that of other members of the betacoronavirus group such as SARS-CoV, MERS-CoV, bat coronavirus. Our feature comprises topological information in molecular SMILES and local chemical context in the SMILES sequence for the drug compound and drug target. Our proposed method prevailed with high and compelling performance accuracy of 97.30% which could be prioritized as the potential and promising prediction route for the development of novel oral antiviral medicine for COVID- 19 drugs.Objective:Forecasting DTI stands as a pivotal aspect of drug discovery. The focus on computational methods in DTI prediction has intensified due to the considerable expense and time investment associated with conducting extensive in vitro and in vivo experiments. Machine learning (ML) techniques, particularly deep learning, have found broad applications in DTI prediction. We are convinced that this study could be prioritized and utilized as the promising predictive route for the development of novel oral antiviral treatments for COVID-19 and other variants of coronaviruses.Methods:This study addressed the problem of COVID-19 drugs using proposed RGCN with multifeatures as an attractive and potential route. This study focused mainly on the prediction of novel antiviral drugs against coronaviruses using graph-based methodology, namely RGCN. This research further utilized the features of both drugs and common potential drug targets found in betacoronaviruses group to deepen understanding of their underlying relation.Results:Our suggested approach prevailed with a high and convincing performance accuracy of 97.30%, which may be utilized as a top priority to support and advance this field in the prediction and development of novel antiviral treatments against coronaviruses and their variants.Conclusion:We recursively performed experiments using the proposed method on our constructed DCCCvT graph dataset from our collected dataset with various single and multiple combinations of features and found that our model had achieved comparable best-averaged accuracy performance on T7 features followed by a combination of T7, R6, and L8. The proposed model implemented in this investigation turns out to outperform the previous related works.

2025-01-01·Separation and Purification Technology

Mechanically stable and highly permeable porous alumina foam with immobilized copper hexacyanoferrate (Cu-HCF@AF) for the removal of radioactive cesium (137Cs) from seawater

作者: Park, Chan Woo ; Park, Chaerin ; Hong, Hye-Jin ; Kim, Chaelin ; Song, Jihee

Copper hexacyanoferrate (Cu-HCF) is a highly effective adsorbent known for its selective and efficient removal of ¹³⁷Cs⁺ ions from seawater.To advance its practical application for seawater remediation, it is essential to granulate Cu-HCF.However, the use of polymer binders presents significant stability challenges in seawater because of their propensity to swell under high osmotic pressure and tendency to decompose when exposed to the radioactivity of ¹³⁷Cs.This study explores a highly durable and efficient form of Cu-HCF immobilized on alumina foam (Cu-HCF@AF) for the remediation of seawater contaminated with ¹³⁷Cs⁺.The Cu-HCF@AF was prepared by first coating copper(II) oxide (CuO) onto alumina foam (AF), then converting it to Cu-HCF through a 1,3,5-benzenetricarboxylic acid (H₃BTC)-catalyzed reaction with K₃Fe(CN)₆ solutionAnal. by SEM showed that spherical CuO particles formed on the AF surface and that 100 nm cubic Cu-HCF crystals developed on these spheres.The synthesis conditions for the Cu-HCF@AF, including the pore size of the AF, the Cu precursor concentration, the number of precursor coatings, and the Cu/reactant ratio, were systematically optimized to achieve optimal Cs⁺ adsorption performance.Thermogravimetric anal. indicated that the amount of Cu-HCF immobilized on the AF was 3.24 % of the total sample mass.The maximum Cs⁺ adsorption capacity was determined to be 30.36 mg/g, and the Langmuir isotherm model was found to well fit the adsorption data, suggesting a homogeneous Cs⁺ adsorption process.The Cu-HCF@AF exhibited outstanding adsorption performance, exceeding 35 mg/g, at pH levels from 7 to 12, making it suitable for use not only in seawater but also in highly alk. waste streams.In seawater, monovalent ions such as Na⁺ and K⁺, which have an ionic radius similar to that of hydrated Cs⁺, interfered more significantly with Cs⁺ adsorption compared with divalent ions such as Mg²⁺ and Ca²⁺.Finally, we demonstrated the removal of radioactive ¹³⁷Cs⁺ in actual seawater, confirming the feasibility of using Cu-HCF@AF in practical applications.

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