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Understanding the local-level variations in seasonality of human respiratory syncytial virus infection: a systematic analysis.
BMC Med
January 2025
Department of Epidemiology, National Vaccine Innovation Platform, School of Public Health, Nanjing Medical University, Nanjing, China.
Background: While previous reports characterised global and regional variations in RSV seasonality, less is known about local variations in RSV seasonal characteristics. This study aimed to understand the local-level variations in RSV seasonality and to explore the role of geographical, meteorological, and socio-demographic factors in explaining these variations.
Methods: We conducted a systematic literature review to identify published studies reporting data on local-level RSV season onset, offset, or duration for at least two local sites.
Management options for vascular anomalies in the distal extremities.
Curr Probl Diagn Radiol
January 2025
Division of Vascular and Interventional Radiology, University of Alabama Birmingham, Birmingham, Alabama, USA. Electronic address:
Vascular anomalies arise during embryologic development due to errors in vasculogenesis. They are associated with sporadic or inherited mutations in receptors, growth factors or enzymes within various vasculogenic pathways such as mTOR, VEGF, and PI3K. Vascular anomalies have the capability to cause significant symptoms and disability, especially when located in the distal extremities.
View Article and Find Full Text PDFBiological activities observed in living systems occur as the output of which nanometer-, submicrometer-, and micrometer-sized structures and tissues non-linearly and dynamically behave through chemical reaction networks, including the generation of various molecules and their assembly and disassembly. To understand the essence of the dynamic behavior in living systems, simpler artificial objects that exhibit cell-like non-linear phenomena have been recently constructed. However, most objects exhibiting cell-like dynamics have been found through trial-and-error experiments, and there are no strategies for designing them as molecular systems.
View Article and Find Full Text PDFMachine learning web application for predicting varicose veins utilizing global prevalence data.
Phlebology
January 2025
Department of Vascular Surgery, University Hospital Leipzig, Leipzig, Germany.
Aim: This study aimed to develop a web-based machine learning (ML) model to predict the lifetime likelihood of developing varicose veins using global disease prevalence data.
Methods: We utilized data from a systematic review, registered under PROSPERO (CRD42021279513), which included 81 studies on varicose vein prevalence across various geographic regions. The data used to build the ML model included disease prevalence as the outcome (%), along with the following predictors: mean age, gender distribution (%), mean body mass index (BMI) of the study cohort, and the mean gravity field of the study region (mGal), representing variations in Earth's underground mass distribution that influence blood and fluid redistribution in the human body, affecting disease prevalence.
CompositIA: an open-source automated quantification tool for body composition scores from thoraco-abdominal CT scans.
Eur Radiol Exp
January 2025
Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Background: Body composition scores allow for quantifying the volume and physical properties of specific tissues. However, their manual calculation is time-consuming and prone to human error. This study aims to develop and validate CompositIA, an automated, open-source pipeline for quantifying body composition scores from thoraco-abdominal computed tomography (CT) scans.
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