In this study, we compared the occurrence, relative abundance (RA), and density (RD) of simple sequence repeats (SSRs) among the lineages of human pathogenic Cryptococcus gattii using an in-silico approach to gain a deeper understanding of the structure and evolution of their genomes. C. gattii isolate MF34 showed the highest RA and RD of SSRs in both the genomic and transcriptomic sequences, followed by isolate WM276.
View Article and Find Full Text PDFIntroduction: E-health services offer potential benefits for healthcare delivery, especially for older adults, yet their adoption remains suboptimal due to various barriers. Understanding the environmental and contextual factors influencing e-health use among this demographic is crucial for enhancing their health outcomes.
Aim: This rapid review aims to explore the various environmental and contextual factors affecting the use of e-health among older adults, focusing on identifying strategies to enhance acceptance and usefulness.
Antonie Van Leeuwenhoek
January 2024
To better understand the structure and evolution of the genomes of four plant pathogenic species of Zymoseptoria, we analyzed the occurrence, relative abundance (RA), and density (RD) of simple sequence repeats (SSRs) in their whole genome and transcriptome sequences. In this study, SSRs are defined as repeats of more than 12 bases in length. The genome and transcriptome sequences of Zymoseptoria ardabiliae show the highest RA (201.
View Article and Find Full Text PDFIn a longitudinal design, four arterial segments in mice were followed by positron emission tomography/computed tomography (PET/CT) imaging. We aimed to determine how the tracers reflected the development of atherosclerosis via the uptake of 2-deoxy-2-[F]fluoro-D-glucose ([F]FDG) for imaging inflammation and [F]-sodium fluoride (Na[F]F) for imaging active microcalcification in a murine model of atherosclerosis. Apolipoprotein E knock-out (ApoE) mice and C57 BL/6NtaC (B6) mice were divided into four groups.
View Article and Find Full Text PDFElectroencephalography (EEG) signals offer invaluable insights into diverse activities of the human brain, including the intricate physiological and psychological responses associated with mental stress. A major challenge, however, is accurately identifying mental stress while mitigating the limitations associated with a large number of EEG channels. Such limitations encompass computational complexity, potential overfitting, and the prolonged setup time for electrode placement, all of which can hinder practical applications.
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