Computer aided prediction of biological activity spectra by the computer program PASS was applied to a set of 89 new thiazole derivatives. Experimentally tested activities (NSAID, local anaesthetic and antioxidant) coincide with the experiment in 70.8% cases, that exceeds significantly the random guess-work (approximately 0.1%). Therefore, computer aided prediction using the Prediction of Activity Spectra for Substances (PASS) system (http://www.ibmh.msk.su/PASS) provides a reliable basis for planning of synthesis and experimental study for new compounds. New psychotropic activities are predicted for some compounds from the series under study. In particular, 7, 44 and 55 compounds likely have anxiolytic, anticonvulsant and cognition enhancer effects, respectively. Most of these compounds have the estimated values of probability to be active (Pa) less than 60%. Therefore, if their activity will be confirmed by the experiment, they might occur to be New Chemical Entities.
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http://dx.doi.org/10.1080/10629360290014322 | DOI Listing |
PLoS One
January 2025
Department of Advanced General Dentistry, College of Dentistry, Yonsei University, Seoul, Korea.
Polylactic acid (PLA) has garnered attention for use in interim dental restorations due to its biocompatibility, biodegradability, low cost, ease of fabrication, and moderate strength. However, its performance under intraoral conditions, particularly under heat and moisture, remains underexplored. This study evaluated the mechanical properties of PLA interim crowns compared with those of polymethylmethacrylate (PMMA) and bisphenol crowns under simulated intraoral conditions with thermocycling.
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January 2025
Shanghai Xinhao Information Technology Co., Ltd., Shanghai, China.
Machine learning techniques and computer-aided methods are now widely used in the pre-discovery tasks of drug discovery, effectively improving the efficiency of drug development and reducing the workload and cost. In this study, we used multi-source heterogeneous network information to build a network model, learn the network topology through multiple network diffusion algorithms, and obtain compressed low-dimensional feature vectors for predicting drug-target interactions (DTIs). We applied the metropolis-hasting random walk (MHRW) algorithm to improve the performance of the random walk with restart (RWR) algorithm, forming the basis by which the self-loop probability of the current node is removed.
View Article and Find Full Text PDFInt J Cardiovasc Imaging
January 2025
Cardiology, Endeavor NorthShore Cardiovascular Institute, Evanston, IL, USA.
This study aims to evaluate the implementation of concomitant CAD assessment on pre-TAVI (transcatheter aortic valve implantation) planning CTA (CT angiography) aided by CT-FFR (CT-fractional flow reserve) [The CT2TAVI protocol] and investigates the incremental value of CT-FFR to coronary CT angiography (CCTA) alone in the evaluation of patients undergoing CT2TAVI. This is a prospective observational real-world cohort study at an academic health system on consecutive patients who underwent CTA for TAVI planning from 1/2021 to 6/2022. This represented a transition period in our health system, from not formally reporting CAD on pre-TAVI planning CTA (Group A) to routinely reporting CAD on pre-TAVI CTA (Group B; CT2TAVI protocol).
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy, Baltimore, Maryland 21201, United States.
Despite its importance in understanding biology and computer-aided drug discovery, the accurate prediction of protein ionization states remains a formidable challenge. Physics-based approaches struggle to capture the small, competing contributions in the complex protein environment, while machine learning (ML) is hampered by the scarcity of experimental data. Here, we report the development of p ML (KaML) models based on decision trees and graph attention networks (GAT), exploiting physicochemical understanding and a new experiment p database (PKAD-3) enriched with highly shifted p's.
View Article and Find Full Text PDFJ Anus Rectum Colon
January 2025
Department of Gastroenterology, Hiroshima University Hospital, Hiroshima, Japan.
Objectives: Studies have suggested that computer-aided polyp detection using artificial intelligence improves adenoma identification during colonoscopy. However, its real-world effectiveness remains unclear. Therefore, this study evaluated the usefulness of computer-aided detection during regular surveillance colonoscopy.
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