Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/gwat.12844 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Barriers and facilitators of the implementation for the antimicrobial Social Norm Feedback (SNF) intervention strategy in primary care institutions: a qualitative study based on the Consolidated Framework for Implementation Research (CFIR).
Antimicrob Resist Infect Control
September 2025
School of Medicine and Health Management, Guizhou Province, Guizhou Medical University, GUI'an New District, 6 Ankang Avenue, Guiyang, People's Republic of China.
Background: Although current evidence supports the effectiveness of social norm feedback (SNF) interventions, their sustained integration into primary care remains limited. Drawing on the elements of the antimicrobial SNF intervention strategy identified through the Delphi-based evidence applicability evaluation, this study aims to explore the barriers and facilitators to its implementation in primary care institutions, thereby informing future optimization.
Methods: Based on the five domains of the Consolidated Framework for Implementation Research (CFIR), we developed semi-structured interview and focus group discussion guides.
Whole genome sequence analysis of low-density lipoprotein cholesterol across 246 K individuals.
Genome Biol
September 2025
Center for Genomic Medicine, Cardiovascular Research Center, , Massachusetts General Hospital Simches Research Center, 185 Cambridge Street, CPZN 5.238,, Boston, MA, 02114, USA.
Background: Rare genetic variation provided by whole genome sequence datasets has been relatively less explored for its contributions to human traits. Meta-analysis of sequencing data offers advantages by integrating larger sample sizes from diverse cohorts, thereby increasing the likelihood of discovering novel insights into complex traits. Furthermore, emerging methods in genome-wide rare variant association testing further improve power and interpretability.
View Article and Find Full Text PDFComparative analysis of machine learning based dissolved oxygen predictions in the Yellow River Basin: The role of diverse environmental predictors.
J Environ Manage
September 2025
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
Dissolved oxygen (DO) is a key water quality indicator reflecting river health. Modeling and understanding the spatiotemporal dynamics of DO and its influencing factors are crucial for effective river management. Machine learning (ML) models have gained popularity in water quality prediction; however, their accuracy strongly depends on the predictor variables.
View Article and Find Full Text PDFDecoding the functional roles of multimetallic constituents in high-entropy prussian blue analogues for sodium-ion batteries.
J Colloid Interface Sci
August 2025
School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China. Electronic address:
Prussian blue analogues (PBAs) have emerged as promising cathode materials for sodium-ion batteries (SIBs) due to their low cost, simple preparation, and high theoretical specific capacity. The integration of high-entropy concepts with framework-structured PBAs has pioneered a new pathway for performance optimization in SIBs cathodes. However, most scholars have only studied the five elements constituting high entropy as a whole, while challenges such as the role of each element and optimization of the proportions among constituent elements remain unresolved.
View Article and Find Full Text PDFKG-MACNF: A nonlinear cross-modal fusion model for predicting drug-target interactions via multi-relational embedding and fine-grained structure.
PLoS One
September 2025
School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, Shandong, China.
Drug-target interaction (DTI) prediction is essential for the development of novel drugs and the repurposing of existing ones. However, when the features of drug and target are applied to biological networks, there is a lack of capturing the relational features of drug-target interactions. And the corresponding multimodal models mainly depend on shallow fusion strategies, which results in suboptimal performance when trying to capture complex interaction relationships.
View Article and Find Full Text PDF