The polarity parameter model previously developed: log k=(log k)(0) + p(P(m)(N) - P(s)(N)) has been successfully applied to study several chromatographic systems involving new generation RPLC columns (Luna C18, Resolve C18, XTerra MSC18, and XTerra RP18). In this model the retention of the solutes (log k) is related to a solute parameter (p), a mobile phase parameter (P(m)(N)) and two chromatographic system parameters [P(s)(N) and (log k)(0)]. The studied systems have been characterized with different acetonitrile-water and methanol-water mobile phases, using a set of 12 neutral solutes of different chemical nature. The polarity parameter model allows prediction of retention of any solute in any mobile phase composition just using the retention data obtained in one percentage of organic modifier and the polarity parameters established in the characterization of the chromatographic systems. This model also allows the solute polarity data transference between RPLC characterized systems, so it is possible to predict the retention in various RPLC systems working experimentally with just one of them. Moreover, the global solvation parameter model has also been applied to the same chromatographic systems using a wide set of solutes in order to compare its predictive ability with the one of the polarity parameter model. The results clearly show that both models predict retention with very similar accuracy but the polarity parameter model requires much less preliminary experimental measurements to achieve equivalent results than the global solvation approach.
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http://dx.doi.org/10.1016/j.chroma.2009.05.006 | DOI Listing |
Med Phys
January 2025
Department of Engineering Physics, Tsinghua University, Beijing, China.
Background: X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.
View Article and Find Full Text PDFBrain Imaging Behav
January 2025
Macquarie Medical School, Macquarie University, Sydney, NSW, Australia.
Magnetic resonance imaging (MRI) is frequently used to monitor disease progression in multiple sclerosis (MS). This study aims to systematically evaluate the correlation between MRI measures and histopathological changes, including demyelination, axonal loss, and gliosis, in the central nervous system of MS patients. We systematically reviewed post-mortem histological studies evaluating myelin density, axonal loss, and gliosis using quantitative imaging in MS.
View Article and Find Full Text PDFJ 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 PDFInt 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.
Med Phys
January 2025
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
Background: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in such treatments.
Purpose: This study seeks to address this gap by developing a DL model for independent MC dose (MCDose) prediction, aiming to facilitate OART and rapid QA implementation for HIT.
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