Continuous potency assessment is crucial for conducting quantitative risk assessment (QRA) of sensitizers. Quantitative regression models, based on in vitro methods, have been developed to calculate points of departure for use in skin sensitization QRA. These models calculate a point of departure as a predicted value for Local Lymph Node Assay (LLNA) EC3 or potency value (PV), integrating data from the kinetic Direct Peptide Reactivity Assay (kDPRA), KeratinoSens (KS) assay, and human Cell Line Activation Test (h-CLAT). The goal of this study was to determine how in vitro predicted EC3s and PVs compare to published reference data. In vitro data were combined in point of departure regression models to predict EC3s and PVs. These points of departure were then grouped into sensitization potency categories, such as extreme, strong, moderate, weak, very weak, or non-sensitizer, as previously described. Trends in potency distribution and high concordance between predicted EC3 and PV categories and published potency categories were observed. Furthermore, the median absolute fold-misprediction ranged between 1.8 and 2.5 for models predicting EC3 and between 1.7 and 3.4 for those predicting PVs. These regression models are a promising animal alternative for determining sensitization quantitative potency for fragrance ingredients, thereby facilitating QRA.
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http://dx.doi.org/10.1016/j.fct.2024.114998 | DOI Listing |
Int J Radiat Biol
January 2025
Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, ON, Canada.
Background: Recent advancements in omics and benchmark dose (BMD) modeling have facilitated identifying the dose required for a predetermined change in a response (e.g. gene or protein change) that can be used to establish acceptable dose levels for hazardous exposures.
View Article and Find Full Text PDFEnviron Int
December 2024
Institute of Food Safety and Health Risk Assessment, College of Pharmaceutical Sciences, National Yang Ming Chiao Tung University, Taipei 112, Taiwan; National Institute of Environmental Health Sciences, National Health Research Institutes, Miaoli County 350, Taiwan. Electronic address:
The substitution of bisphenol A (BPA) with structurally similar analogs has raised concerns due to their comparable estrogenic activities. Considering the high consumption of plant-based foods, assessing the risks posed by bisphenols (BPs) in such dietary sources is essential. However, limited exposure and animal toxicological data on BP analogs hinder comprehensive risk assessments.
View Article and Find Full Text PDFThe unquestionable importance of social networks as a means of communication in the 21st century leads us to analyze the behavior of a sample of X accounts representing people and firms who have shown a link with the world of economics at an international level. We analyze these agents in-depth and their behavior in this social network. We conclude that significant differences exist in how women, men, and companies interact on X.
View Article and Find Full Text PDFToxicol In Vitro
December 2024
Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Canada. Electronic address:
There is growing scientific and regulatory interest in transcriptomic points of departure (tPOD) values from high-throughput in vitro experiments. To further help democratize tPOD research, here we outline 'TPD-seq' which links microplate-based exposure methods involving cell lines for human (Caco-2, Hep G2) and environmental (rainbow trout RTgill-W1) health, with a commercially available RNA-seq kit, with a cloud-based bioinformatics tool (ExpressAnalyst.ca).
View Article and Find Full Text PDFBehav Processes
December 2024
Department of Biology, Faculty of Science, Hokkaido University, Sapporo, Japan; Faculty of Pharmaceutical Science, Health Science University of Hokkaido, Tobetsu, Japan; Centre for Mind/Brain Sciences, University of Trento, Rovereto, Italy.
The marginal value theorem (MVT) predicts that optimal foragers leave a patch when the instantaneous gain rate decreases to the average long-term gain rate. However, various animals systematically deviate from this optimum by staying too long or overharvesting relative to this optimum. We hypothesised that animals do not represent their optimal stay time but instead determine their departure point probabilistically.
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