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Christopher J Portier

Publications and source records attributed to Christopher J Portier.

17 recordsLinked to original sources
PubMed2006

Report of an ISRTP workshop: progress and barriers to incorporating alternative toxicological methods in the U.S.

The workshop objectives were to explore progress in implementing new, revised and alternative toxicological test methods across regulatory evaluation frameworks and decision-making programs in the United States, to identify barriers and to develop recommendations to further promote adoption of approaches that reduce, refine, or replace the use of animal methods. The workshop included sessions on: (1) current research, development, and validation of alternative methods within the U.S. federal government; (2) emerging alternative methodologies with potential applications to a broad spectrum of toxicity evaluation strategies; (3) tiered evaluation ("intelligent testing") strategies; and (4) identification of, and recommendations to address, critical barriers that affect adoption and use of new, revised alternative toxicological test methods by U.S. regulatory agencies. Through facilitated discussion, a list of barriers and recommendations were developed and grouped into categories of economic/financial, scientific/technical, and regulatory/policy. Overall, participants from all sectors collectively supported catalyzing actions to promote more meaningful and rapid progress for research to develop alternative methods focused for use in regulatory programs, accelerated lab investigations to validate such alternative methods and adoption of regulatory frameworks which embrace and incorporate these validated alternatives.

Animal Testing Alternatives↗
PubMed2006

Gene interaction network analysis suggests differences between high and low doses of acetaminophen.

Bayesian networks for quantifying linkages between genes were applied to detect differences in gene expression interaction networks between multiple doses of acetaminophen at multiple time points. Seventeen (17) genes were selected from the gene expression profiles from livers of rats orally exposed to 50, 150 and 1500 mg/kg acetaminophen (APAP) at 6, 24 and 48 h after exposure using a variety of statistical and bioinformatics approaches. The selected genes are related to three biological categories: apoptosis, oxidative stress and other. Gene interaction networks between all 17 genes were identified for the nine dose-time observation points by the TAO-Gen algorithm. Using k-means clustering analysis, the estimated nine networks could be clustered into two consensus networks, the first consisting of the low and middle dose groups, and the second consisting of the high dose. The analysis suggests that the networks could be segregated by doses and were consistent in structure over time of observation within grouped doses. The consensus networks were quantified to calculate the probability distribution for the strength of the linkage between genes connected in the networks. The quantifying analysis showed that, at lower doses, the genes related to the oxidative stress signaling pathway did not interact with the apoptosis-related genes. In contrast, the high-dose network demonstrated significant interactions between the oxidative stress genes and the apoptosis genes and also demonstrated a different network between genes in the oxidative stress pathway. The approaches shown here could provide predictive information to understand high- versus low-dose mechanisms of toxicity.

Acetaminophen↗
PubMed2005

Variation in the hepatic gene expression in individual male Fischer rats.

A new tool beginning to have wider application in toxicology studies is transcript profiling using microarrays. Microarrays provide an opportunity to directly compare transcript populations in the tissues of chemical-exposed and unexposed animals. While several studies have addressed variation between microarray platforms and between different laboratories, much less effort has been directed toward individual animal differences especially among control animals where RNA samples are usually pooled. Estimation of the variation in gene expression in tissues from untreated animals is essential for the recognition and interpretation of subtle changes associated with chemical exposure. In this study hepatic gene expression as well as standard toxicological parameters were evaluated in 24 rats receiving vehicle only in 2 independent experiments. Unsupervised clustering demonstrated some individual variation but supervised clustering suggested that differentially expressed genes were generally random. The level of hepatic gene expression under carefully controlled study conditions is less than 1.5-fold for most genes. The impact of individual animal variability on microarray data can be minimized through experimental design.

Animals↗
PubMed2005

Dose-additive carcinogenicity of a defined mixture of "dioxin-like compounds".

Use of the dioxin toxic equivalency factor (TEF) approach in human risk assessments assumes that the combined effects of dioxin-like compounds in a mixture can be predicted based on a potency-adjusted dose-additive combination of constituents of the mixture. In this study, we evaluated the TEF approach in experimental 2-year rodent cancer bioassays with female Harlan Sprague-Dawley rats receiving 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 3,3 ,4,4 ,5-pentachlorobiphenyl (PCB-126), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), or a mixture of the three compounds. Statistically based dose-response modeling indicated that the shape of the dose-response curves for hepatic, lung, and oral mucosal neoplasms was the same in studies of the three individual chemicals and the mixture. In addition, the dose response for the mixture could be predicted from a combination of the potency-adjusted doses of the individual compounds. Finally, we showed that use of the current World Health Organization dioxin TEF values adequately predicted the increased incidence of liver tumors (hepatocellular adenoma and cholangiocarcinoma) induced by exposure to the mixture. These data support the use of the TEF approach for dioxin cancer risk assessments.

Animals↗
PubMed2004

Evaluation of toxic equivalency factors for induction of cytochromes P450 CYP1A1 and CYP1A2 enzyme activity by dioxin-like compounds.

The toxic equivalency factor (TEF) method has been used to characterize the toxicity of human mixtures of dioxin-like compounds and is being considered for use with other classes of potentially toxic agents. TEFs are estimated by examining the relative potencies of the various congeners for a series of biological and toxicological effects. In this paper, we consider changes in activity for two enzymes, cytochrome P450 1A1 (CYP1A1)-associated 7-ethoxyresorufin-O-deethylase (EROD) and CYP1A2-associated acetanilide-4-hydroxylase (A4H) activity, resulting from exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 3,3',4,4',5-pentachlorobiphenyl (PCB), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF) or a mixture of these agents. The ratio of median effective dose (ED50) is one way to estimate the relative potencies, especially for gene expression and protein endpoints. ED50's were estimated with a nonlinear regression model in which dose-related changes in mean responses are described by a Hill function. ED50's along with other model parameters were estimated by fitting this model to a given data set. Significant differences in estimated model parameters were tested by likelihood ratio methods. The estimated parameters indicated that congener-specific dose-response shapes were significantly different, that additivity failed for these congeners, and that the ratios of ED50's did not predict the response seen for the mixture. These results indicate that for some biological responses, the use of a single relative potency factor (RPF) is not appropriate for the comparison of the dose response behavior of different dioxin-like congeners.

Animals↗
PubMed2004

Gene interaction network suggests dioxin induces a significant linkage between aryl hydrocarbon receptor and retinoic acid receptor beta.

Gene expression arrays (gene chips) have enabled researchers to roughly quantify the level of mRNA expression for a large number of genes in a single sample. Several methods have been developed for the analysis of gene array data including clustering, outlier detection, and correlation studies. Most of these analyses are aimed at a qualitative identification of what is different between two samples and/or the relationship between two genes. We propose a quantitative, statistically sound methodology for the analysis of gene regulatory networks using gene expression data sets. The method is based on Bayesian networks for direct quantification of gene expression networks. Using the gene expression changes in HPL1A lung airway epithelial cells after exposure to 2,3,7,8-tetrachlorodibenzo-(Italic)p(/Italic)-dioxin at levels of 0.1, 1.0, and 10.0 nM for 24 hr, a gene expression network was hypothesized and analyzed. The method clearly demonstrates support for the assumed network and the hypothesis linking the usual dioxin expression changes to the retinoic acid receptor system. Simulation studies demonstrated the method works well, even for small samples.

Animals↗
PubMed2004

The TAO-Gen algorithm for identifying gene interaction networks with application to SOS repair in E. coli.

One major unresolved issue in the analysis of gene expression data is the identification and quantification of gene regulatory networks. Several methods have been proposed for identifying gene regulatory networks, but these methods predominantly focus on the use of multiple pairwise comparisons to identify the network structure. In this article, we describe a method for analyzing gene expression data to determine a regulatory structure consistent with an observed set of expression profiles. Unlike other methods this method goes beyond pairwise evaluations by using likelihood-based statistical methods to obtain the network that is most consistent with the complete data set. The proposed algorithm performs accurately for moderate-sized networks with most errors being minor additions of linkages. However, the analysis also indicates that sample sizes may need to be increased to uniquely identify even moderate-sized networks. The method is used to evaluate interactions between genes in the SOS signaling pathway in Escherichia coli using gene expression data where each gene in the network is over-expressed using plasmids inserts.

Algorithms↗
PubMed2003

Development of a biologically-based controlled growth and differentiation model for developmental toxicology.

Amathematical model is developed with a highly controlled birth and death process for precursor cells. This model is both biologically- and statistically-based. The controlled growth and differentiation (CGD) model limits the number of replications allowed in the development of a tissue or organ and thus, more closely reflects the presence of a true stem cell population. Leroux et al. (1996) presented a biologically-based dose-response model for developmental toxicology that was derived from a partial differential equation for the generating function. This formulation limits further expansion into more realistic models of mammalian development. The same formulae for the probability of a defect (a system of ordinary differential equations) can be derived through the Kolmogorov forward equations due to the nature of this Markov process. This modified approach is easily amenable to the expansion of more complicated models of the developmental process such as the one presented here. Comparisons between the Leroux et al. (1996) model and the controlled growth and differentiation (CGD) model as developed in this paper are also discussed.

Animals↗
PubMed2003

Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver.

Daily measures of maximum temperature, particulate matter less than or equal to 10 micro m in aerodynamic diameter (PM10), and gaseous pollution (ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide) were collected in Denver, Colorado, in July and August between 1993 and 1997. We then compared these exposures with concurrent data on the number of daily hospital admissions for cardiovascular diseases in men and women > 65 years of age. Generalized linear models, assuming a Poisson error structure for the selected cardiovascular disease hospital admissions, were constructed to evaluate the associations with air pollution and temperature. After adjusting the admission data for yearly trends, day-of-week effects, ambient maximum temperature, and dew point temperature, we studied the associations of the pollutants in single-pollutant models with lag times of 0-4 days. The results suggest that O3 is associated with an increase in the risk of hospitalization for acute myocardial infarction, coronary atherosclerosis, and pulmonary heart disease. SO2 appears to be related to increased hospital stays for cardiac dysrhythmias, and CO is significantly associated with congestive heart failure. No association was found between particulate matter or NO2 and any of the health outcomes. Males tend to have higher numbers of hospital admissions than do females for all of the selected cardiovascular diseases, except for congestive heart failure. Higher temperatures appear to be an important factor in increasing the frequency of hospitalization for acute myocardial infarction and congestive heart failure, and are associated with a decrease in the frequency of visits for coronary atherosclerosis and pulmonary heart disease.

Aged↗
PubMed2002

Impact of physiologically based pharmacokinetic modeling on benchmark dose calculations for TCDD-induced biochemical responses.

In risk assessment, noncancer risk is currently estimated using a no observed adverse effect level (NOAEL) from an experimental dose-response study, divided by uncertainty factors, to estimate a presumably safe level of human exposure. A benchmark dose approach, in which an effective dose (ED) resulting in a specified percentage increase over background for effects is estimated by empirical modeling, has been proposed as a replacement for the NOAEL methodology. The aim of this analysis is to compare methods for estimation of body burden resulting in a 1 or 10% maximum increase over background (BB(01) or BB(10)) for biochemical responses following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in female Sprague-Dawley rats. In one method, an ED resulting in a prespecified increase in response over background was estimated using average daily doses and an empirical Hill model. The ED was then converted to an equivalent body burden by a simple kinetic model assuming steady-state conditions, half-life of TCDD in the rat, and 100% absorption of TCDD. Alternatively, a mechanistic physiologically based pharmacokinetic (PBPK) model of TCDD in the rat was used to predict body burdens for administered doses. These PBPK-modeled body burdens were then used directly by the Hill model to calculate a BB(01) or BB(10). In general, the body burden values derived from EDs were within five-fold of BB(01) or BB(10) calculated from the PBPK model. BB(01) and BB(10) values from both methods were within two orders of magnitude of current human general population exposure to all dioxin-like compounds.

Animals↗
PubMed2002

Toxicogenomics: the new frontier in risk analysis.

Risk assessment involves the identification of potential human health hazards, the assessment of the level of exposure by humans to these hazards and the evaluation of the relationship between exposure and response in humans. Research is currently underway to improve the scientific basis of risk assessment through the incorporation of new technologies such as transgenic animals, molecular epidemiology, toxicogenomics, alternative models to animals and mechanism-based mathematical modeling into the estimation of risk in a quantitative manner. This paper briefly discusses these technologies and how each is being employed for more scientifically sound risk assessments.

Animals↗
PubMed2002

Pharmacokinetics of sodium nitrite-induced methemoglobinemia in the rat.

A biologically based mathematical model was created to characterize time and dose-dependent relationships between exposure to nitrite and induction of methemoglobinemia. The model includes mass action equations for processes known to occur: oral absorption of nitrite, elimination from the plasma, partitioning between plasma and erythrocytes, binding of nitrite to hemoglobin and methemoglobin, and the free radical chain reaction for hemoglobin oxidation. The model also includes Michaelis-Menten kinetics for methemoglobin reductase-catalyzed regeneration of hemoglobin. Body weight-scaled rate constants for absorption (k(a)) and elimination (k(e)), the effective erythrocyte/plasma partition coefficient (P), and the apparent K(m) for methemoglobin reductase were the only parameters estimated by formal optimization to reproduce the observed time course data. Time courses of plasma nitrite concentrations and blood levels of hemoglobin and methemoglobin in male and female rats that had received single intravenous or oral doses of sodium nitrite were measured. Peak plasma levels of nitrite were achieved in both sexes approximately 30 min after oral exposure, and peak methemoglobin levels were achieved after 100 min. The model predicts that 10% of the hemoglobin is oxidized to the ferric form after oral doses of 15.9 mg/kg in male rats and 11.0 mg/kg in female rats and after intravenous doses of 8.9 and 7.1 mg/kg in male and female rats, respectively. The t(1/2) for recovery from methemoglobinemia was 60 to 120 min depending on dose and route of administration. A sensitivity analysis of the model was performed to identify to which parameters the predictions of the model were most sensitive and guide attempts to simplify the model. Replacement of the V(max) of methemoglobin reductase with a value representative of humans predicted a 10% methemoglobinemia following an intravenous dose of 5.8 mg/kg, in close agreement with an observed value of 5.7 mg/kg for humans.

Animals↗
PubMed2002

Inhibition of human and pig ureter motility in vitro and in vivo by the K(+) channel openers PKF 217-744b and nicorandil.

The relaxing property of the K(+) channel opener and nitric oxide donor nicorandil and the new K(+) channel opener PKF 217-744b was investigated on isolated human ureteral tissue in vitro and in intact ureters of anesthetized pigs in vivo. In addition, nicorandil and its antagonists, glibenclamide and methylene blue, were tested on isolated pig ureter tissue in vitro. Nicorandil decreased the frequency of spontaneous contractions in isolated pig ureter rings. This effect was antagonized by glibenclamide and methylene blue suggesting that the nicorandil induced relaxation of the ureter is mediated by activation of ATP-sensitive K(+) channels and involvement of soluble guanylate cyclase. Moreover, nicorandil and PKF 217-744b reduced the amplitude of electrically induced contractions in isolated human ureter rings. Calculations of EC(50) values showed that PKF 217-744b [EC(50) = 4.83 x 10(-8) M] was more potent than nicorandil [EC(50) = 4.38 x 10(-5) M]. Both drugs reduced the contraction frequency of the pig ureter after intravenous and topical administration in vivo. Intravenous, but not topical, administration of nicorandil and PKF 217-744b significantly decreased arterial blood pressure but did not affect the heart rate. The in vitro findings suggest that K(+) channel opening and nitric oxide release mediate the effect of nicorandil. Our in vivo results indicate that PKF 217-744b and nicorandil are promising drugs for clinical application in patients with acute stone colic to relieve obstruction and facilitate stone passage or to relax the ureter before ureteroscopy.

Animals↗
PubMed2002

The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population.

Population-based estimates of environmental exposures using biomarkers can be difficult to obtain for a variety of reasons, including problems with limits of detection, undersampling of key strata, time between exposure and sampling, variation across individuals, variation within individuals, and the ability to find and interpret a given biomarker. In this article, we apply statistical likelihoods, weighted sampling, and regression methods for censored data to the analysis of biomarker data. Urinary metabolites for seven phthalates, reported by Blount et al., are analyzed using these methods. In the case of the phthalates data, we assumed the underlying model to be a log-normal distribution with the mean of the distribution defined as a function of a number of demographic variables that might affect phthalate levels in individuals. Included as demographic variables were age, sex, ethnicity, residency, family income, and education level. We conducted two analyses: an unweighted analysis where phthalate distributions were estimated with changes in the means of these distributions as a function of demographic variables, and a weighted prediction for the general population in which weights were assigned for a subset of the population depending on the frequency of their demographic variables in the general U.S. population. We used statistical tests to determine whether any of the demographic variables affected mean phthalate levels. Individuals with only a high school education had higher levels of di-n-butyl phthalate than individuals with education beyond high school. Subjects who had family income less than $1,500 in the month before sampling and/or only high school education had higher levels of n-butyl benzyl phthalate levels than other groupings. Di(2-ethylhexyl) phthalate was higher in males and/or in urban populations and/or in people who had family income less than $1,500 per month. Our findings suggest that there may be significant demographic variations in exposure and/or metabolism of phthalates and that health-risk assessments for phthalate exposure in humans should consider different potential risk groups.

Adult↗
PubMed2002

Endocrine dismodulation and cancer.

OBJECTIVE: Carcinogenesis has generally been viewed as a genomic disease resulting from genetic mutations occurring at critical locations in the genome in a particular sequence. In the last 10 years, scientists have increasingly identified changes in the levels, frequency and types of endocrine hormones as important contributors to the major cancers faced by western populations such as breast cancer (estrogen, progesterone, prolactin), prostate cancer (estrogen, testosterone), endometrial cancer (estrogen) and thyroid cancer (TSH, T3, T4). This manuscript summarizes cancer mechanisms linked to changes in endocrine function and discusses tools for analyzing and understanding the associated data. DISCUSSION: A number of chemicals in the environment mimic the role of hormones to bind to receptors (e.g. phytoestrogens as estrogen mimics), alter signaling pathways (e.g. retinoids), inhibit steroid hormone synthesis (such as some fungicides) or alter steroid hormone metabolism (such as TCDD altering the metabolism of both estrogen and thyroid hormones). Genomic and non-genomic endocrine signaling pathways are extensively present in the body and function in a complicated fashion. In order to fully understand the basis for endocrine-induced cancers, one must simultaneously study the various receptors, ligands, enzymes, other proteins within different organs which all contribute to endocrine system function. Also, cross-talk between endocrine systems is common and is key to understanding a potential role of light-dark cycles on human cancer risks. CONCLUSION: Mechanism-based mathematical models are the only analysis tool available to address all aspects of these complicated networks.

Animals↗
PubMed2002

Comments on the International Symposium on Light, Endocrine Systems and Cancer.

A conference was held at the University of Cologne on May 2-3, 2002, to discuss the strength-of-the-evidence supporting a linkage between light, endocrine systems and cancer. This overview of the conference is intended to summarize some of the key elements of the conference and to indicate both conclusions and research gaps identified by this reviewer.

Animals↗