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Congenital Pulmonary Vascular Anomalies and Disease.
Radiol Clin North Am
March 2025
Division of Cardiothoracic Imaging, Department of Radiology, New York-Presbyterian Hospital, Weill Cornell Medical Center, 525 East 68th Street, New York, NY 10065, USA. Electronic address: https://twitter.com/JoannaEscalonMD.
Congenital pulmonary vascular disease is a daunting and diverse topic spanning both pulmonary arterial and venous anomalies. Given advancements in treatment, patients with congenital anomalies have longer life expectancies into adulthood and practicing radiologists are bound to come across these patients during their daily practice. Additionally, many anomalies are discovered incidentally on imaging, yet may still have implications for patient care.
View Article and Find Full Text PDFEpidemiology of metabolic syndrome.
Pflugers Arch
January 2025
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany.
The global increase of overweight and obesity in children and adults is one of the most prominent public health threats, often accompanied by insulin resistance, hypertension, and dyslipidemia. The simultaneous occurrence of these health problems is referred to as metabolic syndrome. Various criteria have been proposed to define this syndrome, but no general consensus on the specific markers and the respective cut-offs has been achieved yet.
View Article and Find Full Text PDFDeep Learning Approaches for the Prediction of Protein Functional Sites.
Molecules
January 2025
Computational Systems Biology Group, National Center for Biotechnology (CNB-CSIC), 28049 Madrid, Spain.
Knowing which residues of a protein are important for its function is of paramount importance for understanding the molecular basis of this function and devising ways of modifying it for medical or biotechnological applications. Due to the difficulty in detecting these residues experimentally, prediction methods are essential to cope with the sequence deluge that is filling databases with uncharacterized protein sequences. Deep learning approaches are especially well suited for this task due to the large amounts of protein sequences for training them, the trivial codification of this sequence data to feed into these systems, and the intrinsic sequential nature of the data that makes them suitable for language models.
View Article and Find Full Text PDFOverview and Prospects of DNA Sequence Visualization.
Int J Mol Sci
January 2025
School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China.
Due to advances in big data technology, deep learning, and knowledge engineering, biological sequence visualization has been extensively explored. In the post-genome era, biological sequence visualization enables the visual representation of both structured and unstructured biological sequence data. However, a universal visualization method for all types of sequences has not been reported.
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