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Quantification of ivermectin in veterinary products consumed off-label as a treatment for COVID-19.
Pharmazie
December 2024
Centre of Excellence for Pharmaceutical Sciences (Pharmacen™), North-West University, Potchefstroom, Republic of South Africa.
The COVID-19 pandemic caused global pandemonium, and due to an unprecedented global response, the popularity and use of (veterinary) ivermectin, amongst many other conceivable 'treatments', experienced a meteoric rise. Ivermectin is a macrocyclic lactone compound belonging to the avermectin drug class and is a registered medicine in many countries, although the most common use is as veterinary medicine. In this study, a fast HPLC method was developed and validated for the quantification of ivermectin in veterinary products that were used off-label by a substantial number of people during COVID-19.
View Article and Find Full Text PDFBrain Midline Approximation to Improve Symmetry Analysis of Brain CT Scans.
J Imaging Inform Med
January 2025
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Analysis of the symmetry of the brain hemispheres at the level of individual structures and dominant tissue features has been the subject of research for many years in the context of improving the effectiveness of imaging methods for the diagnosis of brain tumor, stroke, and Alzheimer's disease, among others. One useful approach is to reliably determine the midline of the brain, which allows comparative analysis of the hemispheres and uncovers information on symmetry/asymmetry in the relevant planes of, for example, CT scans. Therefore, an effective method that is robust to various geometric deformations, artifacts, varying noise characteristics, and natural anatomical variability is sought.
View Article and Find Full Text PDFPrognostic factors for overall survival in castration-resistant metastatic prostate cancer treated with docetaxel (MeProCSS): results from a German real-world cohort.
Int Urol Nephrol
January 2025
Department of Urology and Urosurgery, Medical Faculty Mannheim, University Medical Centre Mannheim (UMM), University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Baden-Württemberg, Germany.
Purpose: To identify prognostic factors for overall survival (OS) and develop a prognostic score in patients receiving docetaxel in metastatic castration-resistant prostate cancer (mCRPC).
Methods: Retrospective analysis was conducted on mCRPC patients treated with docetaxel at a German tertiary center between March 2010 and November 2023. Prognostic clinical and laboratory factors were analyzed using uni- and multivariable logistic regression.
Design and Validation of a High-Fidelity Left Atrial Cardiac Simulator for the Study and Advancement of Left Atrial Appendage Occlusion.
Cardiovasc Eng Technol
January 2025
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, MA, Cambridge, USA.
Purpose: Atrial fibrillation (AF) is the most common chronic cardiac arrhythmia that increases the risk of stroke, primarily due to thrombus formation in the left atrial appendage (LAA). Left atrial appendage occlusion (LAAO) devices offer an alternative to oral anticoagulation for stroke prevention. However, the complex and variable anatomy of the LAA presents significant challenges to device design and deployment.
View Article and Find Full Text PDFExploring the role of multimodal [F]F-PSMA-1007 PET/CT and multiparametric MRI data in predicting ISUP grading of primary prostate cancer.
Eur J Nucl Med Mol Imaging
January 2025
The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, China.
Purpose: The study explores the role of multimodal imaging techniques, such as [F]F-PSMA-1007 PET/CT and multiparametric MRI (mpMRI), in predicting the ISUP (International Society of Urological Pathology) grading of prostate cancer. The goal is to enhance diagnostic accuracy and improve clinical decision-making by integrating these advanced imaging modalities with clinical variables. In particular, the study investigates the application of few-shot learning to address the challenge of limited data in prostate cancer imaging, which is often a common issue in medical research.
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