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C J Portier

Publications and source records attributed to C J Portier.

At least 37 records · Page 2Linked to original sources
PubMed1999

Quantitative mechanistically based dose-response modeling with endocrine-active compounds.

A wide range of toxicity test methods is used or is being developed for assessing the impact of endocrine-active compounds (EACs) on human health. Interpretation of these data and their quantitative use in human and ecologic risk assessment will be enhanced by the availability of mechanistically based dose-response (MBDR) models to assist low-dose, interspecies, and (italic)in vitro(/italic) to (italic)in vivo(/italic) extrapolations. A quantitative dose-response modeling work group examined the state of the art for developing MBDR models for EACs and the near-term needs to develop, validate, and apply these models for risk assessments. Major aspects of this report relate to current status of these models, the objectives/goals in MBDR model development for EACs, low-dose extrapolation issues, regulatory inertia impeding acceptance of these approaches, and resource/data needs to accelerate model development and model acceptance by the research and the regulatory community.

Dose-Response Relationship, Drug↗
PubMed1998

Genetic susceptibility: significance in risk assessment.

Polymorphisms in metabolism and DNA-repair genes can increase the risks of cancer associated with exposure to chemical and physical agents in the environment. These types of gene-environment interactions may alter our view of dose-response patterns and how to characterize risk in an exposed population. Depending upon the action of the different forms of these genes, differing patterns of dose-response may be seen in a study population and these patterns can effect our interpretation of the degree of hazard as well as the risk in the general population. This short report describes some of the key issues associated with how variation in genetic make-up can result in different dose-response patterns for cancer following exposure to environmental agents.

Arylamine N-Acetyltransferase↗
PubMed1998

Using structural information to create physiologically based pharmacokinetic models for all polychlorinated biphenyls. II. Rates of metabolism.

Physiologically based pharmacokinetic (PBPK) models are useful in describing the distribution, metabolism, and fate of xenobiotics across multiple species. The eventual goal of the present research is to create PBPK models for all 209 polychlorinated biphenyls (PCBs). Key parameters in any PBPK model are the metabolic rates. Data on metabolic rates of PCBs were derived from in vitro experiments and from fitting of PBPK models to in vivo data. The rate of metabolism was assumed to be a linear function of PCB concentration. Structural descriptors suggested by the literature were used in a stepwise regression to find an expression for the metabolic rate of PCBs as a function of five structural descriptors related to the degree and pattern of chlorine substitution. R2 for the fit of the model to the data is 0.9606.

Animals↗
PubMed1998

Characterizing dose-response: I: Critical assessment of the benchmark dose concept.

We present a critical assessment of the benchmark dose (BMD) method introduced by Crump as an alternative method for setting a characteristic dose level for toxicant risk assessment. The no-observed-adverse-effect-level (NOAEL) method has been criticized because it does not use all of the data and because the characteristic dose level obtained depends on the dose levels and the statistical precision (sample sizes) of the study design. Defining the BMD in terms of a confidence bound on a point estimate results in a characteristic dose that also varies with the statistical precision and still depends on the study dose levels. Indiscriminate choice of benchmark response level may result in a BMD that reflects little about the dose-response behavior available from using all of the data. Another concern is that the definition of the BMD for the quantal response case is different for the continuous response case. Specifically, defining the BMD for continuous data using a ratio of increased effect divided by the background response results in an arbitrary dependence on the natural background for the endpoint being studied, making comparison among endpoints less meaningful and standards more arbitrary. We define a modified benchmark dose as a point estimate using the ratio of increased effect divided by the full adverse response range which enables consistent placement of the benchmark response level and provides a BMD with a more consistent relationship to the dose-response curve shape.

Animals↗
PubMed1998

Physiologically based pharmacokinetics model of primidone and its metabolites phenobarbital and phenylethylmalonamide in humans, rats, and mice.

Physiologically based pharmacokinetic modeling of the parent chemical primidone and its two metabolites phenobarbital and phenylethylmalonamide (PEMA) was applied to investigate the differences of primidone metabolism among humans, rats, and mice. The model simulated previously published pharmacokinetic data of the parent chemical and its metabolites in plasma and brain tissues from separate studies of the three species. Metabolism of primidone and its metabolites varied widely among a sample of three human subjects from two separate studies. Estimated primidone metabolism, as expressed by the maximal velocity Vmax, ranged from 0 to 0.24 mg. min-1.kg-1 for the production of phenobarbital and from 0.003 to 0. 02 mg.min-1.kg-1 for the production of PEMA among three human subjects. Further model simulations indicated that rats were more efficient at producing and clearing phenobarbital and PEMA than mice. However, the overall metabolism profile of primidone and its metabolites in mice indicated that mice were at higher risk of toxicity owing to higher residence of phenobarbital in their tissues and owing to the carcinogenic potential of phenobarbital as illustrated in long-term bioassays. This result was in agreement with a recently finished National Toxicology Program (NTP) carcinogenicity study of primidone in rats and mice.

Animals↗
PubMed1997

Evaluation of chemicals with endocrine modulating activity in a yeast-based steroid hormone receptor gene transcription assay.

There is a concern that chemicals in our environment are affecting human health by disrupting normal endocrine function. Much of the concern has focused on chemicals that can interact directly with steroid hormone receptors. We have used a yeast-based assay to assess chemical interactions with the estrogen, androgen, and progesterone receptors. The yeast transformants used in this study contained the human estrogen, androgen, or progesterone receptor along with the appropriate steroid responsive elements upstream of the beta-galactosidase reporter gene. Chemicals were added to yeast cultures in doses ranging from 10(-12) to 10(-4) M and following incubation, the yeasts were then lysed and assayed for beta-galactosidase activity. Diethylstilbesterol and 17-beta estradiol were most active in the estrogen receptor assay, followed by the phytoestrogen, coumestrol. p-Nonylphenol and bisphenol A were approximately 5000- and 15,000-fold less active, respectively, than estradiol. Methoxychlor, DDT and its metabolites, o,p'-DDD, and o,p'-DDE ranged in potency from 5 to 24 X 10(6) less potent than estradiol. Testosterone and dihydrotestosterone were most potent in the androgen receptor assay, followed by estradiol and progesterone. p,p'-DDE was approximately 10(6)-fold less potent than testosterone. None of the industrial chemicals tested interacted with the progesterone receptor. These data demonstrate the utility of using yeast-based receptor assays for detecting chemical interaction with steroid receptors and these assays should serve as a useful component of an in vitro-in vivo strategy to assess the effects of chemicals on endocrine function.

DDT↗
PubMed1997

Using structural information to create physiologically based pharmacokinetic models for all polychlorinated biphenyls.

Physiologically based pharmacokinetic (PBPK) models are useful in describing the distribution, metabolism, and fate of xenobiotics across multiple species. The eventual goal of the present research is to create PBPK models for all 209 polychlorinated biphenyls (PCBs). Key parameters in any PBPK model are the tissue-to-blood partition coefficients. Tissue:blood partition coefficients relate the compound's concentration in a target tissue to its concentration in blood under equilibrium conditions. Data on the adipose:plasma partition coefficients of 24 PCBs were used in a regression analysis to find an expression for the adipose:plasma partition coefficient as a function of molecular structure. Using stepwise regression, it was found that three simple structural descriptors were sufficient to predict adipose:plasma partition coefficients for all 209 PCB congeners. Data on the distribution of PCBs among blood components were used to derive the adipose:blood partition coefficient from the adipose:plasma partition coefficient. The lipid contents of liver, muscle, and skin were used to derive the tissue:blood partition coefficient for those tissues from the adipose:blood partition coefficient. These results allow for the calculation of tissue:blood partition coefficients for liver, skin, muscles, and fat for all 209 PCB congeners.

Adipose Tissue↗
PubMed1997

A mathematical model of production, distribution, and metabolism of melatonin in mammalian systems.

Melatonin is a neuroendocrine hormone which is currently receiving considerable attention as a treatment for jet lag, a treatment for insomnia and, by some, a possible "magic bullet" for delaying the effects of aging and preventing cancer. Production of melatonin is focused primarily in the pineal gland with very wide daily shifts in production controlled by the day/night cycle. The potential for increased disease as a consequence of lower or higher than average production of this hormone has not been well studied, although potential environmental agents may modulate circulating levels (e.g., electric and magnetic fields). In this manuscript, a physiologically realistic mathematical model for the production, distribution, and metabolism of melatonin is developed as a precursor to a future study of the role of chemicals and environmental agents in altering this system. Values for key aspects of the system (e.g., diurnal rates of production of the hormone in the pineal gland) were obtained from the literature and the model was validated against data on circulating levels. The mathematical equations and model parameters are presented.

Animals↗
PubMed1997

The two-stage model of carcinogenesis: overcoming the nonidentifiability dilemma.

The two-stage mathematical model of carcinogenesis has been shown to be nonidentifiable whenever tumor incidence data alone is used to fit the model (Hanin and Yakovlev, 1996). This lack of identifiability implies that more than one parameter vector satisfies the optimization criteria for parameter estimation, e.g., maximum likelihood estimation. A question of greater concern to persons using the two-stage model of carcinogenesis is under what conditions can identifiable parameters be obtained from the observed experimental data. We outline how to obtain identifiable parameters for the two-stage model.

Animals↗
PubMed1996

Calculating tumor incidence rates in stochastic models of carcinogenesis.

Multistage models of carcinogenesis are increasingly used in the estimation of risks from exposure to environmental agents. The two-stage model of carcinogenesis is routinely used because it agrees with much of the existing tumor incidence data, parallels the biological two-stage model, and has much of its mathematical details derived. However, recent findings on the mechanisms of carcinogenesis has led researchers to believe that there are a greater number of stages and a more complex structure to these models than a single pathway. In this paper, a method for readily computing tumor incidence rates for arbitrarily complex multistage models is derived. The formulas for the two-stage model with time-varying rates are given explicitly. Simple rules for more complicated models are given, and computer code able to implement these formulas are provided.

Animals↗
PubMed1996

Workshop overview. National Toxicology Program Studies: principles of dose selection and applications to mechanistic based risk assessment.

A workshop entitled "NTP Studies: Principles of Dose Selection and Applications to Mechanistic Based Risk Assessment" was held at the 34th Annual Meeting of the Society of Toxicology in Baltimore, Maryland. The purpose of the workshop was to provide an overview of factors currently considered important in the selection of doses for NTP studies, to describe some of the confounding factors that can result from the indiscriminate use of bioassay data in quantitative risk assessment, and to suggest ways in which information from mechanistic studies or studies of biomarkers of exposure or effect might be used to better advantage in risk assessment.

Biomarkers↗
PubMed1996

A mechanistic model of effects of dioxin on thyroid hormones in the rat.

A physiological dosimetric model of the disposition of TCDD in the rat (Kohn et al., Toxicol. Appl. Pharmacol. 120, 138-154, 1993) was extended to include effects of dioxin on serum concentrations of thyroid hormones in the rat. The extended model included distribution of blood among major vessels and tissue capillary beds and resorption of TCDD released into the gut lumen from the liver by cell lysis consequent to cytotoxicity. TCDD metabolism was represented by Hill kinetics. Parameter values were estimated by fitting time-course data for a single oral subcutaneous injection of TCDD and dose-response data for biweekly oral dosing. The extended model included new compartments for the thyroid and thyroxine-sensitive tissues (e.g., pituitary, kidney, and brown fat), secretion and tissue uptake of thyroid hormones, binding of 3,5,3'-triiodothyronine (T3) and 3,5,3',5'-tetraiodothyronine (thyroxine, T4) to proteins in blood and tissues, deiodination of iodothyronines, and glucuronidation of T4 by the hepatic UDP-glucuronosyltransferase (UGT) activity induced by TCDD. Secretion of thyroid hormones was modeled as regulated by thyrotropin (TSH), whose secretion was modeled as regulated by the hypothalamic factors thyrotropin releasing hormone and somatostatin. Release of the hypothalamic factors was modeled as under feedback control by the blood T4 level. Induction of UGT was modeled as stimulated by the Ah receptor-TCDD complex. The extended model fit the observed dose-response of P450 isozymes and Ah and estrogen receptors following repeated oral doses with comparable accuracy as the earlier model. The fit to liver and fat TCDD levels following single and repeated oral and subcutaneous doses was improved over the earlier model. The revised model's predicted liver TCDD concentrations at very low doses were verified experimentally. The model reproduced the responses observed for blood T3, T4, and TSH after 31 weeks of biweekly oral dosing of rats with TCDD. The model also predicted responses of UGT mRNA and UGT enzymatic activity comparable to those observed in TCDD-treated rats in experiments whose data were not used in constructing the model. Calculated increases in blood TSH levels are consistent with prolonged stimulation of the thyroid and may represent an early stage in the induction of thyroid tumors identified in previous two-year bioassays. Thus, increases in UGT activity may be useful as a biomarker for tumorigenic changes in hormone levels subsequent to TCDD exposure.

Adipose Tissue↗
PubMed1996

Modeling the number and size of hepatic focal lesions following exposure to 2,3,7,8-TCDD.

Data on the size and number of placental glutathione S-transferase-positive (PGST+) foci were collected from a two-stage hepatocarcinogenesis model in female Sprague-Dawley rats. the study consisted of multiple 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-exposed dose groups including both diethylnitrosomine (DEN)-initiated and uninitiated animals. Groups were observed after 15 or 31 weeks of TCDD exposure. The parameters in the first half of a two-stage mathematical model of carcinogenesis were estimated from these data. If the model is valid, the results suggest that TCDD stimulates the production of PGST+ foci and promotes the growth of PGST+ foci. This finding suggests a complicated mechanism for TCDD-induced production of Hepatic foci that we refer to as activation, labeling TCDD as an activator. The analysis also indicates that there is an interaction between DEN and TCDD which results in dose-related formation of initiated cells throughout the study period. Best-fitting curves (using maximum likelihood methods) for TCDD-induced activation and promotion reached saturation levels at low doses of TCDD. In summary, the model fit the data well, but leads to an interpretation of the data which either questions the validity of the model or implies that our understanding of the effects of TCDD and DEN is incomplete.

Adenosine Triphosphate↗
PubMed1996

Stochastic simulation of a multistage model of carcinogenesis.

Stochastic mathematical models of carcinogenesis have been used to quantify cancer risks for about 40 years. As more detailed data of the cancer process are obtained, mathematical models try to incorporate this information and as a result become more complex and sometimes analytically and numerically intractable. Simulation studies have become an important tool for examining the operating characteristics of the models of interest. The many quantities one can examine using this tool include bias in parameter estimates, adequacy of approximation methods, and the appropriateness of large sample generalizations to small studies. This manuscript describes a general method of stochastic simulation that may be carried out for arbitrarily complicated stochastic models of carcinogenesis.

Cell Division↗