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http://dx.doi.org/10.1002/lt.26397 | DOI Listing |
Mol Divers
September 2025
Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, Nanjing, 211198, China.
Drug absorption significantly influences pharmacokinetics. Accurately predicting human oral bioavailability (HOB) is essential for optimizing drug candidates and improving clinical success rates. The traditional method based on experiment is a common way to obtain HOB, but the experimental method is time-consuming and costly.
View Article and Find Full Text PDFBiomater Sci
September 2025
Department of Pharmaceutics and Pharmaceutical Technology, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates.
Colorectal cancer (CRC) remains a major global health burden, necessitating more effective and selective therapeutic approaches. Nanocarrier-based drug delivery systems offer significant advantages by enhancing drug accumulation in tumors, reducing off-target toxicity, and overcoming resistance mechanisms. This review provides a comprehensive overview of recent advancements in nanocarriers for CRC therapy, including passive targeting the enhanced permeability and retention (EPR) effect, and active targeting strategies that exploit specific tumor markers using ligands such as antibodies, peptides, and aptamers.
View Article and Find Full Text PDFPatterns (N Y)
July 2025
Department of Methodology and Statistics, Faculty of Social and Behavioral Sciences, Utrecht University, Utrecht, the Netherlands.
ASReview LAB v.2 introduces an advancement in AI-assisted systematic reviewing by enabling collaborative screening with multiple experts ("a crowd of oracles") using a shared AI model. The platform supports multiple AI agents within the same project, allowing users to switch between fast general-purpose models and domain-specific, semantic, or multilingual transformer models.
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July 2025
University of Washington, Department of Astronomy, Seattle, WA, USA.
Machine learning and artificial intelligence promise to accelerate research and understanding across many scientific disciplines. Harnessing the power of these techniques requires aggregating scientific data. In tandem, the importance of open data for reproducibility and scientific transparency is gaining recognition, and data are increasingly available through digital repositories.
View Article and Find Full Text PDFMed Phys
September 2025
School of Computer, Electronics and Information, Guangxi University, Nanning, China.
Background: Deformable medical image registration is a critical task in medical imaging-assisted diagnosis and treatment. In recent years, medical image registration methods based on deep learning have made significant success by leveraging prior knowledge, and the registration accuracy and computational efficiency have been greatly improved. Models based on Transformers have achieved better performance than convolutional neural network methods (ConvNet) in image registration.
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