RESUMEN
This report provides a summary of deliberations conducted under the charge for members of Module D participating in the Naphthalene State-of-the-Science Symposium (NS(3)), Monterey, CA, October 9-12, 2006. The charge directed the panel to ascertain to the best of its ability a consensus judgment of the state-of-the-science concerning the potential for a genotoxic mode of action for naphthalene and its metabolites, with implications for low-dose extrapolations of cancer risk estimates for exposed populations. Where scientific uncertainties remained, the panel was asked to identify which scientific uncertainties (if any) could be resolved through targeted, timely, cost-effective research. The report provides a brief summary of naphthalene genotoxicity; identifies those areas where there is a general scientific consensus regarding the effects of naphthalene; identifies areas of uncertainty regarding the effects of naphthalene; and key questions that currently limit our ability to assess the genotoxic risks of naphthalene. The report also outlines a set of six studies that could resolve some of these key uncertainties.
Asunto(s)
Contaminantes Atmosféricos/toxicidad , Carcinógenos Ambientales/toxicidad , Mutágenos/toxicidad , Naftalenos/toxicidad , Neoplasias/inducido químicamente , Neoplasias/genética , Contaminantes Atmosféricos/metabolismo , Animales , Carcinógenos Ambientales/metabolismo , Consenso , ADN/efectos de los fármacos , Aductos de ADN , Daño del ADN , Humanos , Exposición por Inhalación , Pruebas de Mutagenicidad , Mutágenos/metabolismo , Naftalenos/metabolismo , Neoplasias/metabolismo , Medición de RiesgoRESUMEN
Chemical speciation modeling is a vital tool for assessing the bioavailability of inorganic species, yet significant uncertainties in thermodynamic parameters and model form limit its potential for decision-making. In this paper we present a novel method for the quantification of thermodynamic parameter uncertainty and ionic strength correction model uncertainty using Bayesian Markov Chain Monte Carlo (MCMC) estimation methods. These methods allow for the inclusion of correlation modeling, which has not been present in previous work. The MCMC simulations are used to model a natural river water to determine the uncertainty in the calculated environmental speciation of ethylenediamenetetraacetate, a chelating agent that has attracted considerable environmental interest. The results indicate that incorporating correlation among related thermodynamic parameters into the uncertainty model is necessary to correctly quantify the overall system uncertainty. This result indicates the superiority of MCMC estimation methods overtraditional Monte Carlo methods when available data are used to estimate parameter uncertainty in systems with closely related model parameters.