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Data and data visualization are integral parts of (clinical) decision-making in general and stewardship (antimicrobial stewardship, infection control, and institutional surveillance) in particular. However, systematic research on the use of data visualization in stewardship is lacking. This study aimed at filling this gap by creating a visual dictionary of stewardship through an assessment of data visualization (i.e., graphical representation of quantitative information) in stewardship research. A random sample of 150 data visualizations from published research articles on stewardship were assessed (excluding geographical maps and flowcharts). The visualization vocabulary (content) and design space (design elements) were combined to create a visual dictionary. Additionally, visualization errors, chart junk, and quality were assessed to identify problems in current visualizations and to provide improvement recommendations. Despite a heterogeneous use of data visualization, distinct combinations of graphical elements to reflect stewardship data were identified. In general, bar ( = 54; 36.0%) and line charts ( = 42; 28.1%) were preferred visualization types. Visualization problems comprised color scheme mismatches, double -axis, hidden data points through overlaps, and chart junk. Recommendations were derived that can help to clarify visual communication, improve color use for grouping/stratifying, improve the display of magnitude, and match visualizations to scientific standards. Results of this study can be used to guide data visualization creators in designing visualizations that fit the data and visual habits of the stewardship target audience. Additionally, the results can provide the basis to further expand the visual dictionary of stewardship toward more effective visualizations that improve data insights, knowledge, and clinical decision-making.
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http://dx.doi.org/10.3389/fmicb.2021.743939 | DOI Listing |
World Neurosurg
September 2025
Department of Anaesthesiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. Electronic address:
Objective: The present study intends to conduct a comprehensive bibliometric analysis of the research pertaining to the treatment of vertebral artery stenosis, with the objective of elucidating the evolution and trends in therapeutic strategies.
Methods: A bibliometric analysis of publications spanning between January 1, 1980, and August 13, 2024, was conducted utilizing the Web of Science Core Collection database. The analysis and visualization of the data were performed using VOSviewer, CiteSpace, and R package "bibliometrix" software.
Cell Rep
September 2025
Department of Biochemistry, University of Colorado, Boulder, CO 80303, USA. Electronic address:
RNA polymerase II (RNAPII) is regulated by sequence-specific transcription factors (TFs) and the pre-initiation complex (PIC): TFIIA, TFIIB, TFIID, TFIIE, TFIIF, TFIIH, and Mediator. TFs, Mediator, and RNAPII contain intrinsically disordered regions (IDRs) and form phase-separated condensates, but how IDRs control RNAPII function remains poorly understood. Using purified PIC factors, we developed a real-time in vitro fluorescence transcription (RIFT) assay for second-by-second visualization of transcription at hundreds of promoters simultaneously.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
Key Laboratory of Micro-nano Sensing and IoT of Wenzhou, Wenzhou Institute of Hangzhou Dianzi University, Wenzhou 325038, China.
Transcription factors (TFs) are essential proteins that regulate gene expression by specifically binding to transcription factor binding sites (TFBSs) within DNA sequences. Their ability to precisely control the transcription process is crucial for understanding gene regulatory networks, uncovering disease mechanisms, and designing synthetic biology tools. Accurate TFBS prediction, therefore, holds significant importance in advancing these areas of research.
View Article and Find Full Text PDFJ Neurosci Methods
September 2025
European Laboratory for Non-linear Spectroscopy, via Nello Carrara 1, 50019 Sesto Fiorentino, Italy; National Institute of Optics -National Research Council (CNR-INO), 50125 Sesto Fiorentino, Italy. Electronic address:
Background: Tissue clearing techniques combined with light-sheet fluorescence microscopy (LSFM) enable high-resolution 3D imaging of biological structures without physical sectioning. While widely used in neuroscience to determine brain architecture and connectomics, their application for spinal cord mapping remains more limited, posing challenges for studying demyelinating diseases like multiple sclerosis. Myelin visualization in cleared tissues is particularly difficult due to the lipid-removal nature of most clearing protocols, and alternative immunolabeling approaches failed to reach satisfying results.
View Article and Find Full Text PDFPediatr Surg Int
September 2025
Department of Women's and Children's Health, University of Padova, Padua, Italy.
Artificial intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, with growing interest in their application to rare pediatric surgical conditions. In these settings, limited data availability often brakes traditional research. Although pediatric surgery has historically been slower than other specialties in adopting ML, recent years have seen an increase in AI-driven tools designed for surgical care.
View Article and Find Full Text PDF