Public reporting burden for this collection of information is estimated to average I hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden to Department of Defense, Washington Headquarters Services, Directorate for Information Operations and Reports (0704-0188), 1215 Jefferson Davis Highway, Suite 1204, Arlington, VA 22202-4302, Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. REPORT DATE (DD-MM-YYYY)2 Approved for public release; distribution unlimited. SUPPLEMENTARY NOTESCleared by AFRL/PA on 11 July 2006, case number is AFRLNVS-06-1724.14. ABSTRACT 'A physiologically based pharmacokinetic (PBPK) model was developed which provides a comprehensive description of the kinetics of trichloroethylene (TCE) and its metabolites, trichloroethanol (TCOH), and trichloroacetic acid (TCA), in the mouse, rat, and human, for both oral and inhalation exposure. The model includes descriptions of the three principal target tissues for cancer identified in animal bioassays: liver, lung, and kidney. Dose metrics that can be calculated with the model for cancer risk assessment include the area under the concentration curve (AUC) for TCA in the plasma or liver, the peak concentration and AUC for chloral (CHL) in the tracheo-bronchial region of the lung, and the production of a thioacetylating intermediate from dichlorovinylcysteine (DCVC) in the kidney. Additional dose metrics that can be calculated for noncancer risk assessment include the peak concentrations and AUCs for TCE and TCOH in the blood, as well as the total metabolism of TICE divided by the body weight. There is currently no adequate data available with which to confidently parameterize a description for another metabolite of interest, dichloroacetic acid (DCA). Model predictions of TCE, TCA, and TCOH concentrations in rodents and humans are consistent with a variety of experimental data, suggesting that the model should provide a useful basis for evaluating cross-species differences in pharmacokinetics for these chemicals. In the case of the lung and kidney target tissues, however, only limited data are available for establishing cross-species pharmacokinetics. As a result, PBPK model calculations for these dose metncs are highly uncertain.

An analysis of the uncertainty in guidelines for the ingestion of methylmercury (MeHg) due to human pharmacokinetic variability was conducted using a physiologically based pharmacokinetic (PBPK) model that describes MeHg kinetics in the pregnant human and fetus. Two alternative derivations of an ingestion guideline for MeHg were considered: the U.S. Environmental Protection Agency reference dose (RfD) of 0.1 microgram/kg/day derived from studies of an Iraqi grain poisoning episode, and the Agency for Toxic Substances and Disease Registry chronic oral minimal risk level (MRL) of 0.5 microgram/kg/day based on studies of a fish-eating population in the Seychelles Islands. Calculation of an ingestion guideline for MeHg from either of these epidemiological studies requires calculation of a dose conversion factor (DCF) relating a hair mercury concentration to a chronic MeHg ingestion rate. To evaluate the uncertainty in this DCF across the population of U.S. women of child-bearing age, Monte Carlo analyses were performed in which distributions for each of the parameters in the PBPK model were randomly sampled 1000 times. The 1st and 5th percentiles of the resulting distribution of DCFs were a factor of 1.8 and 1.5 below the median, respectively. This estimate of variability is consistent with, but somewhat less than, previous analyses performed with empirical, one-compartment pharmacokinetic models. The use of a consistent factor in both guidelines of 1.5 for pharmacokinetic variability in the DCF, and keeping all other aspects of the derivations unchanged, would result in an RfD of 0.2 microgram/kg/day and an MRL of 0.3 microgram/kg/day.

In recent years, there have been growing concerns that due to differences, both pharmacokinetic and pharmacodynamic, between children and adults, children could be at greater risk of adverse effects following chemical exposure. The specific goal of this study was to demonstrate an approach for using physiologically based pharmacokinetic (PBPK) modeling to compare inhalation dosimetry in the adult and the child of both males and females. Three categories of gases were considered: rapidly and irreversibly reactive in the respiratory tract (ozone), relatively water-soluble and nonreactive (isopropanol), and relatively water-insoluble and nonreactive (styrene, vinyl chloride, and perchloroethylene). The nonreactive chemicals were also selected because they are metabolized in the respiratory tract. The age-related changes observed for the estimated dose metrics were a function of the physiochemical properties of the inhaled vapor and their interactions in the body. Blood concentrations estimated for all vapors, either poorly metabolized (e.g., PERC), moderately metabolized (e.g., ST), or highly metabolized vapors (e.g., IPA and VC), varied less than a factor of two between infants and adults. These changes, moreover, were confined to the first year after birth, a relatively short window compared to the total lifespan of the individual. In contrast, circulating metabolite concentrations estimated in the blood, as well as amounts metabolized in the liver and lung, appeared to be a strong function of age, due to their dependence on the maturity of the pertinent metabolic enzyme systems.

No abstract

A comprehensive literature search was conducted to identify information on gene expression changes following exposures to inorganic arsenic compounds. This information was organized by compound, exposure, dose/concentration, species, tissue, and cell type. A concentration-related hierarchy of responses was observed, beginning with changes in gene/protein expression associated with adaptive responses (e.g., preinflammatory responses, delay of apoptosis). Between 0.1 and 10 microM, additional gene/protein expression changes related to oxidative stress, proteotoxicity, inflammation, and proliferative signaling occur along with those related to DNA repair, cell cycle G2/M checkpoint control, and induction of apoptosis. At higher concentrations (10-100 microM), changes in apoptotic genes dominate. Comparisons of primary cell results with those obtained from immortalized or tumor-derived cell lines were also evaluated to determine the extent to which similar responses are observed across cell lines. Although immortalized cells appear to respond similarly to primary cells, caution must be exercised in using gene expression data from tumor-derived cell lines, where inactivation or overexpression of key genes (e.g., p53, Bcl-2) may lead to altered genomic responses. Data from acute in vivo exposures are of limited value for evaluating the dose-response for gene expression, because of the transient, variable, and uncertain nature of tissue exposure in these studies. The available in vitro gene expression data, together with information on the metabolism and protein binding of arsenic compounds, provide evidence of a mode of action for inorganic arsenic carcinogenicity involving interactions with critical proteins, such as those involved in DNA repair, overlaid against a background of chemical stress, including proteotoxicity and depletion of nonprotein sulfhydryls. The inhibition of DNA repair under conditions of toxicity and proliferative pressure may compromise the ability of cells to maintain the integrity of their DNA.