This paper describes DARAN (Defined Approach for Risk Assessment of New Nitrosamines), an new defined approach that uses lines of reasoning based on structure-activity relationship (SAR) patterns and Read-Across (RAx) to set transparent and acceptable limits for new N-nitrosamines for which no toxicological data exist. We selected the compound 1-methyl-4-nitrosopiperazine (MeNP) as a target to calculate a new acceptable limit on the basis of a more transparent and scientifically reasoned RAx. We used publicly available databases and datasets to retrieve experimental in vitro mutagenicity and in vivo carcinogenicity data for N-nitrosopiperazine compounds and to form the chemical category for an RAx. We carried out SAR analyses to try to understand patterns and to obtain interpretable inferences of variation in carcinogenic potency among the N-nitrosopiperazines compounds and their differences with the potent nitrosamines NDMA (N-nitrosodimethylamine) and NDEA (N-nitrosodiethylamine). To estimate an acceptable limit for the target MeNP, we used the scientifically based hypotheses and the evidence lines of about the influence of structural attributes for a robust RAx. On the basis of the criteria proposed in the Assessment Report EMA/369136/20202 and by using the SAR hypotheses obtained by the analysis, we obtained a robust RAx, scientifically supported assumptions, which resulted in TD values predicted from the closest structurally related compounds and a worst-case approach.
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http://dx.doi.org/10.1016/j.yrtph.2022.105288 | DOI Listing |
Sci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
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January 2025
Institute for System Dynamics, University of Stuttgart, Waldburgstr. 19, 70563, Stuttgart, Germany.
Including sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove.
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January 2025
College of Computer and Information Engineering, Nanjing Tech University, Nanjing, 211800, China.
Graph data is essential for modeling complex relationships among entities. Graph Neural Networks (GNNs) have demonstrated effectiveness in processing low-order undirected graph data; however, in complex directed graphs, relationships between nodes extend beyond first-order connections and encompass higher-order relationships. Additionally, the asymmetry introduced by edge directionality further complicates node interactions, presenting greater challenges for extracting node information.
View Article and Find Full Text PDFActa Neuropathol Commun
January 2025
Department of Biological Sciences, Purdue University, 915 Mitch Daniels Blvd, West Lafayette, IN, USA.
Dementia refers to an umbrella phenotype of many different underlying pathologies with Alzheimer's disease (AD) being the most common type. Neuropathological examination remains the gold standard for accurate AD diagnosis, however, most that we know about AD genetics is based on Genome-Wide Association Studies (GWAS) of clinically defined AD. Such studies have identified multiple AD susceptibility variants with a significant portion of the heritability unexplained and highlighting the phenotypic and genetic heterogeneity of the clinically defined entity.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Socio-Medical Sciences Department, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
Background: Rehabilitation technology is a growing field, but the sustainable implementation of these technologies, particularly in home settings, is lacking. The aim of this study was to explore the factors influencing the uptake of stroke rehabilitation technology among various stakeholders, including developers, healthcare professionals, individuals who had strokes, strategic experts, management and innovation staff, health insurers, and the National Health Care Institute.
Methods: In total, 22 semi-structured interviews were conducted with a purposive stakeholder sample.
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