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http://dx.doi.org/10.1093/eurheartj/ehi762 | DOI Listing |
Invest Radiol
January 2025
From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany (D.B.M., J.O.K., J.B., A.K., J.M., J.L.H., C.R., M.T., B.H., M.R.M.); Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany (D.B.M., J.O.K., J.B., A.K., L.C.A., M.R.M.); Department of Chemistry, Humboldt-Universität zu Berlin, Berlin, Germany (J.O.K.); Division 1.5 Protein Analysis, Federal Institute for Materials Research and Testing, Berlin, Germany (J.O.K., M.G.W.); Department of Biology, Chemistry, and Pharmacy, Institute of Biology, Freie Universität Berlin, Berlin, Germany (A.K.); Department of Veterinary Medicine, Institute of Animal Welfare, Animal Behavior and Laboratory Animal Science, Freie Universität Berlin, Berlin, Germany (J.L.H.); Institute of Inorganic and Analytical Chemistry, University of Münster, Münster, Germany (C.V., P.N., U.K.); Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Berlin, Germany (A.L.); DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany (A.L.); and Division of Cardiology, Massachusetts General Hospital, Harvard University, Boston, MA (W.C.P.).
Introduction: Atherosclerosis is the underlying cause of multiple cardiovascular pathologies. The present-day clinical imaging modalities do not offer sufficient information on plaque composition or rupture risk. A disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS4) is a strongly upregulated proteoglycan-cleaving enzyme that is specific to cardiovascular diseases, inter alia, atherosclerosis.
View Article and Find Full Text PDFNeural Comput
January 2025
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200437, China
Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificial neural networks, which produce results in a single step, SNNs require multiple steps during inference to achieve a desired accuracy level, resulting in a burden in real-time response and energy efficiency. Inspired by the tradeoff between speed and accuracy in human and animal decision-making processes, which exhibit correlations among reaction times, task complexity, and decision confidence, an inquiry emerges regarding how an SNN model can benefit by implementing these attributes.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Life and Allied Health Sciences, MS Ramiah University of Applied Sciences (RUAS), MSR Nagar, New BEL Road, Bangalore, 560054, India.
Background Breast cancer represents a significant public health concern in India, accounting for 28% of all cancer diagnoses and imposing a substantial economic burden. This study introduces a novel approach to forecasting the number of breast cancer cases (based on prevalence rates) and estimating the associated economic impact in India using the autoregressive integrated moving average (ARIMA) model. Methods Data on the prevalence of breast cancer in India from 2000 to 2021 were obtained from the Global Burden of Disease (GBD) database.
View Article and Find Full Text PDFNeuroimage
January 2025
Key Laboratory of Ultra-Weak Magnetic Field Measurement Technology, Ministry of Education, School of Instrumentation and Optoelectronic Engineering, Beihang University, 100191, Beijing, China; Hangzhou Institute of Extremely-Weak Magnetic Field Major National Science and Technology Infrastructure, Hangzhou, 310051, China; State Key Laboratory of Traditional Chinese Medicine Syndrome/Health Construction Center, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, 510120, China; Hefei National Laboratory, Hefei, 230088, China. Electronic address:
The optically pumped magnetometer (OPM) based magnetoencephalography (MEG) system offers advantages such as flexible layout and wearability. However, the position instability or jitter of OPM sensors can result in bad channels and segments, which significantly impede subsequent preprocessing and analysis. Most common methods directly reject or interpolate to repair these bad channels and segments.
View Article and Find Full Text PDFTheranostics
January 2025
Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany.
To establish the extent, distribution and frequency of in-vivo vessel wall [Ga]Ga-PentixaFor uptake and to determine its relationship with calcified atherosclerotic plaque burden (CAP) and cardiovascular risk factors (CVRF). 65 oncological patients undergoing [Ga]Ga-PentixaFor PET/CT were assessed. Radiotracer uptake (target-to-background ratio [TBR]) and CAP burden (including number of CAP sites, calcification circumference and thickness) in seven major vessel segments per patient were determined.
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