This study aimed to evaluate the filter paper as a means to transport inactivated Gram-negative non-fermentative (GNNF) bacteria and Haemophilus spp. for analysis using MALDI-TOF MS. A total of 133 isolates were evaluated and the analysis of each isolate was performed directly from original bacterial colony and in filter paper after the processing. To evaluate the agreement between the identification performed directly from the colony and after impregnation in filter paper, we assign the scores: >2·3 as excellent (E); 2·0 to 2·3 as very good (VG); 1·7-1·99 as good (G); <1·7 as unidentified (U). The divergences were classified as: Minor Divergence, Intermediate Divergence and Major Divergence. A total of 80 isolates transported in the filter paper disks presented full category concordance; 39 isolates presented Minor Divergence; 4 isolates present Intermediate Divergence; 4 isolates present Major Divergence and 6 isolates present better results after impregnation in filter paper. The proposed methodology of bacteria transportation presented a sensitivity of 96·9% and a specificity of 100%. The filter paper as a means to transport and storage of inactivated GNNF and Haemophilus spp. may be considered a potential tool for faster, more accurate, biosafe and less-expensive identification.
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http://dx.doi.org/10.1111/lam.13695 | DOI Listing |
Heliyon
January 2025
Institute of Genomic Medicine Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
Objectives: Alzheimer's disease (AD) is a complex neurodegenerative disorder that primarily affects elderly individuals. This study aimed to elucidate the intricate mechanisms underlying AD in elderly patients compared with healthy aged individuals using high-throughput RNA sequencing (RNA-seq) data and next-generation knowledge discovery methods (NGKD), with a focus on identifying potential therapeutic agents.
Methods: High-throughput RNA-seq data were obtained from the Gene Expression Omnibus (GEO) database (accession number: GSE104704).
Sci Rep
January 2025
Physics Department, Faculty of Science, TH-PPM Group, Beni-Suef University, Beni Suef, 62514, Egypt.
In this paper, the transfer matrix method is used to study the dispersion of acoustic waves in a finite periodic expansion chambers system with a defect. Two kinds of structures are studied. The first one is formed by expansion chambers, which are symmetrical concerning a defect, and the second one is asymmetrical with a defect.
View Article and Find Full Text PDFBMJ Open
January 2025
Lancaster Medical School, Lancaster University, Lancaster, UK.
Introduction: Congenital colour vision deficiency (CVD), known as colour blindness, is a common visual problem affecting around 1 in 12 men and 1 in 200 women. It is known that people who have red-green CVD, the most common phenotype, can have difficulty differentiating colours and this can impact the ability to perform clinical tasks related to patient care. The objective of this scoping review is to understand the extent and type of evidence and the impact on clinical practice and patient safety arising from congenital CVD in healthcare professionals.
View Article and Find Full Text PDFBMJ Health Care Inform
January 2025
Hamad Bin Khalifa University College of Science and Engineering, Doha, Qatar.
Background: Loneliness and insomnia are mutually occurring conditions. This paper investigates whether keywords depicting loneliness and insomnia are expressed together on social media. Understanding loneliness through data fills the gaps or validates the literature on loneliness from sociological and psychological perspectives.
View Article and Find Full Text PDFJ Biomed Inform
January 2025
Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384, China; National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology), China. Electronic address:
Objective: The application of artificial intelligence (AI) in health care has led to a surge of interest in surgical process modeling (SPM). The objective of this study is to investigate the role of deep learning in recognizing surgical workflows and extracting reliable patterns from datasets used in minimally invasive surgery, thereby advancing the development of context-aware intelligent systems in endoscopic surgeries.
Methods: We conducted a comprehensive search of articles related to SPM from 2018 to April 2024 in the PubMed, Web of Science, Google Scholar, and IEEE Xplore databases.
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