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Results from application of Approximate Probabilistic Analysis to incidence of nasal lesions from acrolein exposure
For estimating the distribution of the target human dose for magnitude of effect M and human incidence I (abbreviated “HDMI”) in the Approximate Probabilistic Analysis (APROBA) software tool, using the default assumptions in APROBA (primary analysis) and specific case adjustments (sensitivity analyses): 1) Confidence limits of the HDMI components that were input in APROBA for each analysis, and the confidence limits for the estimated HDMI distributions that were output, along with some supplementary calculations on the outputs. Also included for each analysis are the percents contribution of the HDMI components to HDMI uncertainty. 2) Results of Bayesian model averaging dose-response analysis of incidence of nasal lesions in the lateral wall at level II, used for the sensitivity analysis in which dose-response modeling was used to determine the point of departure. 3) Parameters of the HDMI distribution for varying values of human incidence I. This dataset is associated with the following publication: Blessinger, T., A. Davis, W. Chiu, J. Stanek, G. Woodall, J. Gift, K. Thayer, and D. Bussard. Application of a Unified Probabilistic Framework to the Dose-Response Assessment of Acrolein. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 143: 105953, (2020).
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Multipollutant health effect simulations
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Resulting betas (health effects) from a variety of copollutant epidemiologic models used to analyze the impact of exposure measurement error on health effect estimates. This dataset is associated with the following publication: Dionisio , K., H.H. Chang, and L. Baxter. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.. ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 15: 114, (2016).
Reconstructing population exposures to acrylamide from human monitoring data using a pharmacokinetic framework dataset
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Publicly available dataset containing chemical exposure data. This dataset is associated with the following publication: Lin, Y., V. Morozov, A. Kadry, J. Caffrey , and W. Chou. Reconstructing population exposures to acrylamide from human monitoring data using a pharmacokinetic framework. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, 331: 138798, (2023).
Respiratory Effects and Systemic Stress Response Following Acute Acrolein Inhalation in Rats
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This data set is an Excel file pertaining to the study that examined nasal, pulmonary, and systemic effects of acrolein in rats acutely exposed to a range of concentrations. The different tabs of the spreadsheet pertain to each figure found in the manuscript. This dataset is associated with the following publication: Snow, S., M. McGee, A. Henriquez, J. Richards, M. Schladweiler, A. Ledbetter, and U. Kodavanti. Respiratory Effects and Systemic Stress Response Following Acute Acrolein Inhalation in Rats#. TOXICOLOGICAL SCIENCES. Society of Toxicology, 158(2): 454-464, (2017).
Chemical Exposure Pathway Prediction for Screening and Priority-Setting
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We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. This dataset is associated with the following publication: Ring, C., J. Arnot, D. Bennett, P. Egeghy, P. Fantke, L. Huang, K. Isaacs, O. Jolliet, K. Phillips, P. Price, H. Shin, J. Westgate, R. Setzer, and J. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 719-732, (2019).
Chemical Exposure Pathway Prediction for Screening and Priority-Setting
공공데이터포털
We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. This dataset is associated with the following publication: Ring, C., J. Arnot, D. Bennett, P. Egeghy, P. Fantke, L. Huang, K. Isaacs, O. Jolliet, K. Phillips, P. Price, H. Shin, J. Westgate, R. Setzer, and J. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 53(2): 719-732, (2019).
Derivation of new Threshold of Toxicological Concern values for exposure via inhalation for environmentally-relevant chemicals
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An effort was made to derive new inhalation TTC values using the EPA’s Toxicity Values database, ToxValDB. A total of 4703 substances captured in ToxValDB were assigned into their respective TTC categories using the Kroes module within the Toxtree software tool and custom profilers developed in Nelms et al (2019) and Patlewicz et al (2018). For the substances assigned into the 3 Cramer classes, the 5th percentiles were calculated from the empirical cumulative distributions of No observed (adverse) effect level (concentration) values. The 5th percentiles were converted to their respective TTC values and compared with published values reported by Escher et al (2010) and Carthew et al (2009). The TTC values derived from ToxValDB were orders of magnitude more conservative, further Cramer classification was not found to be effective at discriminating potencies. This dataset is associated with the following publication: Nelms, M., and G. Patlewicz. Derivation of New Threshold of Toxicological Concern Values for Exposure via Inhalation for Environmentally-Relevant Chemicals. Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 2: 580347, (2020).
Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies
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Dataset for "Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies". This dataset is associated with the following publication: Lowe, K., J. Dawson, K. Phillips, J. Minucci, J. Wambaugh, H. Qian, T. Ramanarayanan, P. Egeghy, B. Ingle, R. Brunner, E. Mendez, M. Embry, and C. Tan. Incorporating human exposure information in a weight of evidence approach to inform design of repeated dose animal studies. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 127: 105073, (2021).
Excel spreadsheet of data used in Figure 3
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Distribution of doses of a volatile organic compound from inhalation of one consumer product, other near -field sources, far-field sources, and aggregate (total) exposure. In this instance, far-field scenarios account for several orders of magnitude of less of the predicted dose compared to near-field scenarios. This dataset is associated with the following publication: Vallero, D. Air Pollution Monitoring Changes to Accompany the Transition from a Control to a Systems Focus. Sustainability. MDPI AG, Basel, SWITZERLAND, 8(12): 1216, (2016).
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