Publications by authors named "Joseph Swintek"

Chemical safety evaluation is in the midst of a transition from traditional whole-animal toxicity testing to molecular pathway-based in vitro assays and in silico modeling. However, to facilitate the shift in reliance on apical effects for risk assessment to predictive surrogate metrics having characterized linkages to chemical mechanisms of action, targeted in vivo testing is necessary to establish these predictive relationships. In this study, we demonstrate a means to predict thyroid-related metamorphic success in the model amphibian Xenopus laevis using relevant biochemical measurements during early prometamorphosis.

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Cancer potencies of mineral and synthetic elongated particle mixtures, including asbestos fibers, are influenced by changes in fiber dose composition, bioavailability, and biodurability in combination with relevant cytotoxic dose-response relationships. An extensive rat intrapleural dose characterization data set with a wide variety of elongated particles physicochemical properties facilitated statistical analyses of pleural mesothelioma response data combined from several studies for evaluation of alternative dose-response models. Utilizing logistic regression of individual elongated particle dimensional variations within each test sample, four major findings emerged: (1) Mild acid leaching provides superior prediction of tumor incidence compared to samples that were not leached; (2) sum of the elongated particle surface areas from mildly acid-leached samples provides the optimum holistic dose-response model; (3) progressive removal of dose associated with very short and/or thin elongated particles significantly degrades the resultant particle count and surface area dose-based predictive model fits; and (4) alternative biologically plausible model adjustments provide evidence for reduced potency of elongated particles with aspect ratios less than 8 and lengths greater than 80 µm.

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Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.

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