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Rory B Conolly

Publications and source records attributed to Rory B Conolly.

18 recordsLinked to original sources
PubMed2006

Binary gene induction and protein expression in individual cells.

BACKGROUND: Eukaryotic gene transcription is believed to occur in either a binary or a graded fashion. With binary induction, a transcription activator (TA) regulates the probability with which a gene template is switched from the inactive to the active state without affecting the rate at which RNA molecules are produced from the template. With graded, also called rheostat-like, induction the gene template has continuously varying levels of transcriptional activity, and the TA regulates the rate of RNA production. Support for each of these two mechanisms arises primarily from experimental studies measuring reporter proteins in individual cells, rather than from direct measurement of induction events at the gene template. METHODS AND RESULTS: In this paper, using a computational model of stochastic gene expression, we have studied the biological and experimental conditions under which a binary induction mode operating at the gene template can give rise to differentially expressed "phenotypes" (i.e., binary, hybrid or graded) at the protein level. We have also investigated whether the choice of reporter genes plays a significant role in determining the observed protein expression patterns in individual cells, given the diverse properties of commonly-used reporter genes. Our simulation confirmed early findings that the lifetimes of active/inactive promoters and half-lives of downstream mRNA/protein products are important determinants of various protein expression patterns, but showed that the induction time and the sensitivity with which the expressed genes are detected are also important experimental variables. Using parameter conditions representative of reporter genes including green fluorescence protein (GFP) and beta-galactosidase, we also demonstrated that graded gene expression is more likely to be observed with GFP, a longer-lived protein with low detection sensitivity. CONCLUSION: The choice of reporter genes may determine whether protein expression is binary, graded or hybrid, even though gene induction itself operates in an all-or-none fashion.

Computer Simulation↗
PubMed2006

Use of a physiologically based pharmacokinetic model to identify exposures consistent with human biomonitoring data for chloroform.

Biomonitoring data provide evidence of human exposure to environmental chemicals by quantifying the chemical or its metabolite in a biological matrix. To better understand the correlation between biomonitoring data and environmental exposure, physiologically based pharmacokinetic (PBPK) modeling can be of use. The objective of this study was to use a combined PBPK model with an exposure model for showering to estimate the intake concentrations of chloroform based on measured blood and exhaled breath concentrations of chloroform. First, the predictive ability of the combined model was evaluated with three published studies describing exhaled breath and blood concentrations in people exposed to chloroform under controlled showering events. Following that, a plausible exposure regimen was defined combining inhalation, ingestion, and dermal exposures associated with residential use of water containing typical concentrations of chloroform to simulate blood and exhaled breath concentrations of chloroform. Simulation results showed that inhalation and dermal exposure could contribute substantially to total chloroform exposure. Next, sensitivity analysis and Monte Carlo analysis were performed to investigate the sources of variability in model output. The variability in exposure conditions (e.g., shower duration) was shown to contribute more than the variability in pharmacokinetics (e.g., body weight) to the predicted variability in blood and exhaled breath concentrations of chloroform. Lastly, the model was used in a reverse dosimetry approach to estimate distributions of exposure consistent with concentrations of chloroform measured in human blood and exhaled breath.

Chloroform↗
PubMed2005

Population variability in biological adaptive responses to DNA damage and the shapes of carcinogen dose-response curves.

Carcinogen dose-response curves for both ionizing radiation and chemicals are typically assumed to be linear at environmentally relevant doses. This assumption is used to ensure protection of the public health in the absence of relevant dose-response data. A theoretical justification for the assumption has been provided by the argument that low dose linearity is expected when an exogenous agent adds to an ongoing endogenous process. Here, we use computational modeling to evaluate (1) how two biological adaptive processes, induction of DNA repair and cell cycle checkpoint control, may affect the shapes of dose-response curves for DNA-damaging carcinogens and (2) how the resulting dose-response behaviors may vary within a population. Each model incorporating an adaptive process was capable of generating not only monotonic dose-responses but also nonmonotonic (J-shaped) and threshold responses. Monte Carlo analysis suggested that all these dose-response behaviors could coexist within a population, as the spectrum of qualitative differences arose from quantitative changes in parameter values. While this analysis is largely theoretical, it suggests that (a) accurate prediction of the qualitative form of the dose-response requires a quantitative understanding of the mechanism, (b) significant uncertainty is associated with human health risk prediction in the absence of such quantitative understanding and (c) a stronger experimental and regulatory focus on biological mechanisms and interindividual variability would allow flexibility in regulatory treatment of environmental carcinogens without compromising human health.

Adaptation, Physiological↗
PubMed2005

New directions in incidence-dose modeling.

Many cellular responses are quantal; that is, they either take place or they do not. Examples of "either-or" responses include cell replication, differentiation and apoptosis. Surprisingly, induction of suites of genes and coordinated phenotypic changes in cells are also often quantal, where embedded molecular circuitry creates on-off switches. Mechanistic incidence-dose (ID) models need to account for the quantal characteristics of cellular switches that contribute, in turn, to dose thresholds and to the incidence of biological responses in individuals. Interdisciplinary systems biology approaches create mechanistic ID models based on: (i) detailed knowledge of the cellular circuitry controlling signal transduction; (ii) evolving biological modeling tools describing cellular circuits and their perturbations by chemicals and (iii) high throughput, high coverage "omic" screens for examining cell signaling pathways and biological responses. These interdisciplinary approaches should produce novel, quantitative ID models for biological responses and greatly improve the biological basis of safety and risk assessments.

Incidence↗
PubMed2005

Improving predictive modeling in pediatric drug development: pharmacokinetics, pharmacodynamics, and mechanistic modeling.

A workshop was conducted on November 18-19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adult-like in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.

Adult↗
PubMed2004

Dose-dependent transitions in mechanisms of toxicity.

Scientists and decision makers from all sectors agree that risk assessments should be based on the best available science. Several years ago, the Health and Environmental Sciences Institute (HESI), a global branch of the International Life Sciences Institute (ILSI), identified the need for better scientific understanding of dose-dependent transitions in mechanisms of toxicity as one avenue by which the best and latest science can be integrated into the decision making process. In July 2001, the HESI Project Committee on Dose-Dependent Transitions in Mechanisms of Toxicity established a group of academic, government, and industry scientists to engage in active technical discourse on the issue of dose-dependent transitions in mechanisms of toxicity. Over the next 18 months, case studies were examined. These case studies included acetaminophen, butadiene, ethylene glycol, formaldehyde, manganese, methylene chloride, the peroxisome proliferator-activated receptor, progesterone/hydroxyflutamide, propylene oxide, vinyl acetate, vinyl chloride, vinylidene chloride, and zinc (Slikker, W., Jr., Andersen, M.E., Bogdanffy, M.S., Bus, J.S., Cohen, S.D., Conolly, R.B., David, R.M., Doerrer, N.G., Dorman, D.C., Gaylor, D.W., Hattis, D., Rogers, J.M., Setzer, R.W., Swenberg, J.A., Wallace, K., 2004. Dose-dependent transitions in mechanisms of toxicity: case studies. Toxicol. Appl. Pharmacol. 201(3), 226-294 (this issue)). The HESI Project Committee sponsored two technical workshops in 2003. The first of these workshops took place on February 12-13, 2003, and was co-sponsored by the Agency for Toxic Substances and Disease Registry, the American Chemistry Council, the National Institute of Environmental Health Sciences, the Society of Toxicology, and the U.S. Environmental Protection Agency. Additional support was provided by Health Canada. Invited experts from government, academia, and industry provided scientific perspectives and recommendations at the workshop. The purpose of the workshop was to examine approaches to dose-response analysis, learn from the case study examples, and gather feedback from invited participants on the impact of dose-dependent transitions on the risk assessment process. The second forum consisted of a workshop in March 2003 at the Society of Toxicology Annual Meeting in Salt Lake City, UT. This paper addresses the issues discussed at both workshops, and presents the consensus conclusions drawn by expert participants.

Animals↗
PubMed2004

Dose-dependent transitions in mechanisms of toxicity: case studies.

Experience with dose response and mechanisms of toxicity has shown that multiple mechanisms may exist for a single agent along the continuum of the full dose-response curve. It is highly likely that critical, limiting steps in any given mechanistic pathway may become overwhelmed with increasing exposures, signaling the emergence of new modalities of toxic tissue injury at these higher doses. Therefore, dose-dependent transitions in principal mechanisms of toxicity may occur, and could have significant impact on the interpretation of reference data sets for risk assessment. To illustrate the existence of dose-dependent transitions in mechanisms of toxicity, a group of academic, government, and industry scientists, formed under the leadership of the ILSI Health and Environmental Sciences Institute (HESI), developed a series of case studies. These case studies included acetaminophen, butadiene, ethylene glycol, formaldehyde, manganese, methylene chloride, peroxisome proliferator-activated receptor (PPAR), progesterone/hydroxyflutamide, propylene oxide, vinyl acetate, vinyl chloride, vinylidene chloride, and zinc. The case studies formed the basis for technical discourse at two scientific workshops in 2003.

Acetaminophen↗
PubMed2004

Human respiratory tract cancer risks of inhaled formaldehyde: dose-response predictions derived from biologically-motivated computational modeling of a combined rodent and human dataset.

Formaldehyde inhalation at 6 ppm and above causes nasal squamous cell carcinoma (SCC) in F344 rats. The quantitative implications of the rat tumors for human cancer risk are of interest, since epidemiological studies have provided only equivocal evidence that formaldehyde is a human carcinogen. Conolly et al. (Toxicol. Sci. 75, 432-447, 2003) analyzed the rat tumor dose-response assuming that both DNA-reactive and cytotoxic effects of formaldehyde contribute to SCC development. The key elements of their approach were: (1) use of a three-dimensional computer reconstruction of the rat nasal passages and computational fluid dynamics (CFD) modeling to predict regional dosimetry of formaldehyde; (2) association of the flux of formaldehyde into the nasal mucosa, as predicted by the CFD model, with formation of DNA-protein cross-links (DPX) and with cytolethality/regenerative cellular proliferation (CRCP); and (3) use of a two-stage clonal growth model to link DPX and CRCP with tumor formation. With this structure, the prediction of the tumor dose response was extremely sensitive to cell kinetics. The raw dose-response data for CRCP are J-shaped, and use of these data led to a predicted J-shaped dose response for tumors, notwithstanding a concurrent low-dose-linear, directly mutagenic effect of formaldehyde mediated by DPX. In the present work the modeling approach used by Conolly et al. (ibid.) was extended to humans. Regional dosimetry predictions for the entire respiratory tract were obtained by merging a three-dimensional CFD model for the human nose with a one-dimensional typical path model for the lower respiratory tract. In other respects, the human model was structurally identical to the rat model. The predicted human dose response for DPX was obtained by scale-up of a computational model for DPX calibrated against rat and rhesus monkey data. The rat dose response for CRCP was used "as is" for the human model, since no preferable alternative was identified. Three sets of baseline parameter values for the human clonal growth model were obtained through separate calibrations against respiratory tract cancer incidence data for nonsmokers, smokers, and a mixed population of nonsmokers and smokers, respectively. Additional risks of respiratory tract cancer were predicted to be negative up to about one ppm for all three cases when the raw CRCP data from the rat were used. When a hockey-stick-shaped model was fit to the rat CRCP data and used in place of the raw data, positive maximum likelihood estimates (MLE) of additional risk were obtained. These MLE estimates were lower, for some comparisons by as much as 1,000-fold, than MLE estimates from previous cancer dose-response assessments for formaldehyde. Breathing rate variations associated with different physical activity levels did not make large changes in predicted additional risks. In summary, this analysis of the human implications of the rat SCC data indicates that (1) cancer risks associated with inhaled formaldehyde are de minimis (10(-6) or less) at relevant human exposure levels, and (2) protection from the noncancer effects of formaldehyde should be sufficient to protect from its potential carcinogenic effects.

Animals↗
PubMed2003

Nonmonotonic dose-response relationships: mechanistic basis, kinetic modeling, and implications for risk assessment.

Dose-response curves for the first interaction of a chemical with a biochemical target molecule are usually monotonic; i.e., they increase or decrease over the entire dose range. However, for reactions of a complex biological system to a toxicant, nonmonotonic (biphasic) dose-effect relationships can be observed, showing a decrease at low dose followed by an increase at high dose, or vice versa. We present four examples to demonstrate that nonmonotonic dose-response relationships can result from superimposition of monotonic dose responses of component biological reactions. Examples include (i) a membrane-receptor model with receptor subtypes of different ligand affinity and opposing downstream effects (adenosine receptors A1 vs. A2), (ii) androgen receptor-mediated gene expression driven by homodimers, but not mixed-ligand dimers, (iii) repair of background DNA damage by enzymatic activity induced by adducts formed by a xenobiotic, (iv) rate of mutation as a consequence of DNA damage times rate of cell division, the latter being modulated by cell-cycle delay at low-level DNA damage, and cell-cycle acceleration due to regenerative hyperplasia at cytotoxic dose levels. Quantitative analyses based on biological models are shown, and factors that affect the degree of nonmonotonicity are identified. It is noted that threshold-type dose-response curves could in fact be nonmonotonic. Our analysis should promote a scientific discussion of biphasic dose responses and the concept termed "hormesis," and of default procedures for low-dose extrapolation in toxicological risk assessment.

Animals↗
PubMed2003

Statistical analysis of nonmonotonic dose-response relationships: research design and analysis of nasal cell proliferation in rats exposed to formaldehyde.

Statistical analyses of nonmonotonic dose-response curves are proposed, experimental designs to detect low-dose effects of J-shaped curves are suggested, and sample sizes are provided. For quantal data such as cancer incidence rates, much larger numbers of animals are required than for continuous data such as biomarker measurements. For example, 155 animals per dose group are required to have at least an 80% chance of detecting a decrease from a 20% incidence in controls to an incidence of 10% at a low dose. For a continuous measurement, only 14 animals per group are required to have at least an 80% chance of detecting a change of the mean by one standard deviation of the control group. Experimental designs based on three dose groups plus controls are discussed to detect nonmonotonicity or to estimate the zero equivalent dose (ZED), i.e., the dose that produces a response equal to the average response in the controls. Cell proliferation data in the nasal respiratory epithelium of rats exposed to formaldehyde by inhalation are used to illustrate the statistical procedures. Statistically significant departures from a monotonic dose response were obtained for time-weighted average labeling indices with an estimated ZED at a formaldehyde dose of 5.4 ppm, with a lower 95% confidence limit of 2.7 ppm. It is concluded that demonstration of a statistically significant bi-phasic dose-response curve, together with estimation of the resulting ZED, could serve as a point-of departure in establishing a reference dose for low-dose risk assessment.

Administration, Inhalation↗
PubMed2003

Biologically motivated computational modeling of formaldehyde carcinogenicity in the F344 rat.

Formaldehyde inhalation at 6 ppm and above causes nasal squamous cell carcinoma (SCC) in F344 rats. The human health implications of this effect are of significant interest since human exposure to environmental formaldehyde is widespread, though at lower concentrations than those that cause cancer in rats. In this article, which is part of a larger effort to predict the human cancer risks of inhaled formaldehyde, we describe biologically motivated quantitative modeling of the exposure-tumor response continuum in the rat. An anatomically realistic, three-dimensional fluid dynamics model of the F344 rat nasal airways was used to predict site-specific flux of formaldehyde from inhaled air into tissue, since both SCC and preneoplastic lesions develop in a characteristic site-specific pattern. Flux into tissue was used as a dose metric for two modes of action, direct mutagenicity and cytolethality-regenerative cellular proliferation (CRCP), which in turn were linked to key parameters of a two-stage clonal growth model. The direct mutagenicity mode of action was represented by a low dose linear dose-response model of DNA-protein cross-link (DPX) formation. An empirical J-shaped dose-response model and a threshold model fit to the empirical data were used for CRCP. In the clonal growth model, the probability of mutation per cell generation was a function of the tissue concentration of DPX while the rate of cell division was calculated from the CRCP data. Maximum likelihood methods were used to estimate parameter values. Survivor (a nontumor outcome) and tumor data for controls from the National Toxicology Program database and from two formaldehyde inhalation bioassays were used for likelihood calculations. The J-shaped dose-response for CRCP provided a better description of the SCC data than did the threshold model. Sensitivity analyses indicated that the rodent tumor response is due to the CRCP mode of action, with the directly mutagenic pathway having little, if any, influence. When evaluated in light of modeling and database uncertainties, particularly the specification of the clonal growth model and the dose-response data for CRCP, this work provides suggestive though not definitive evidence for a J-shaped dose-response for formaldehyde-mediated nasal SCC in the F344 rat.

Administration, Inhalation↗
PubMed2003

Biologically motivated computational modeling of chloroform cytolethality and regenerative cellular proliferation.

Chloroform is a nongenotoxic-cytotoxic carcinogen in rodents. As such, events related to cytotoxicity are the driving force for cancer induction. In this paper we extended an existing physiologically based pharmacokinetic (PBPK) model for chloroform to describe a plausible mechanism linking the hepatic metabolism of chloroform to hepatocellular killing and regenerative proliferation. The key aspects of this mechanism are (1) the production of damage at a rate proportional to the rate of metabolism predicted by the PBPK model, (2) the saturable repair of the damage, (3) the stimulation of the cell death rate by damage, and (4) the stimulation of the cell division rate as a function of the difference between the control and exposed numbers of cells. This extension allows the simulation of the labeling index and comparison with labeling index data. Data from a previously published chloroform-inhalation study with female B6C3F1 mice that determined cytolethality and regenerative cellular proliferation following exposures of varying concentrations and exposure durations were used for model calibration. Both threshold and low-dose linear linkages between chloroform-induced damage and cell death rate provided visually good fits to the labeling index data after formal optimization of the adjustable parameters, and there was no statistical difference between the fits of the two models to the data. Biologically motivated computational modeling of chloroform-induced cytolethality and regenerative proliferation is a necessary step in the quantitative evaluation of the hypothesis that chloroform-stimulated cell proliferation predicts the rodent tumor response.

Administration, Inhalation↗
PubMed2003

Stochastic simulation of hepatic preneoplastic foci development for four chlorobenzene congeners in a medium-term bioassay.

A combination of experimental and simulation approaches was used to analyze clonal growth of glutathione-S-transferase pi (GST-P) enzyme-altered foci during liver carcinogenesis in an initiation-promotion regimen for 1,4-dichlorobenzene (DCB), 1,2,4,5-tetrachlorobenzene (TECB), pentachlorobenzene (PECB), and hexachlorobenzene (HCB). Male Fisher 344 rats, eight weeks of age, were initiated with a single dose (200 mg/kg, ip) of diethylnitrosamine (DEN). Two weeks later, daily dosing of 0.1 mol/kg chlorobenzene was maintained for six weeks. Partial hepatectomy was performed three weeks after initiation. Liver weight, normal hepatocyte division rates, and the number and volume of GST-P positive foci were obtained at 23, 26, 28, 47, and 56 days after initiation. A clonal growth stochastic model separating the initiated cell population into two distinct subtypes (referred to as A and B cells) was successfully used to describe the foci development data for the four chlorobenzenes. The B cells are initiated cells that display a selective growth advantage under conditions that inhibit the growth of initiated A cells or normal hepatocytes. The simulation exercise for the four chlorobenzenes indicates a positive correlation between the estimated net growth rate of B cells during the 2-week regeneration period following partial hepatectomy and final foci volume at the end of the bioassay. This observation is consistent with the sensitivity analysis of model parameters. While TECB, PECB, and HCB all significantly increased foci volume, only HCB increased normal hepatocyte proliferation. Together, these results indicate that examining effects of chemicals on regenerative responses following partial hepatectomy may be a means for understanding the carcinogenicity potential of chlorobenzene compounds.

Administration, Oral↗
PubMed2003

Benchmark dose risk assessment for formaldehyde using airflow modeling and a single-compartment, DNA-protein cross-link dosimetry model to estimate human equivalent doses.

Formaldehyde induced squamous-cell carcinomas in the nasal passages of F344 rats in two inhalation bioassays at exposure levels of 6 ppm and above. Increases in rates of cell proliferation were measured by T. M. Monticello and colleagues at exposure levels of 0.7 ppm and above in the same tissues from which tumors arose. A risk assessment for formaldehyde was conducted at the CIIT Centers for Health Research, in collaboration with investigators from Toxicological Excellence in Risk Assessment (TERA) and the U.S. Environmental Protection Agency (U.S. EPA) in 1999. Two methods for dose-response assessment were used: a full biologically based modeling approach and a statistically oriented analysis by benchmark dose (BMD) method. This article presents the later approach, the purpose of which is to combine BMD and pharmacokinetic modeling to estimate human cancer risks from formaldehyde exposure. BMD analysis was used to identify points of departure (exposure levels) for low-dose extrapolation in rats for both tumor and the cell proliferation endpoints. The benchmark concentrations for induced cell proliferation were lower than for tumors. These concentrations were extrapolated to humans using two mechanistic models. One model used computational fluid dynamics (CFD) alone to determine rates of delivery of inhaled formaldehyde to the nasal lining. The second model combined the CFD method with a pharmacokinetic model to predict tissue dose with formaldehyde-induced DNA-protein cross-links (DPX) as a dose metric. Both extrapolation methods gave similar results, and the predicted cancer risk in humans at low exposure levels was found to be similar to that from a risk assessment conducted by the U.S. EPA in 1991. Use of the mechanistically based extrapolation models lends greater certainty to these risk estimates than previous approaches and also identifies the uncertainty in the measured dose-response relationship for cell proliferation at low exposure levels, the dose-response relationship for DPX in monkeys, and the choice between linear and nonlinear methods of extrapolation as key remaining sources of uncertainty.

Administration, Inhalation↗
PubMed2003

Modeling interindividual variation in physiological factors used in PBPK models of humans.

Modeling interindividual variation in internal doses in humans using PBPK models requires data on the variation in physiological parameters across the population of interest. These data should also reflect the correlations between the values of the various parameters in a person. In this project, we develop a source of data for human physiological parameters where (1) the parameter values for an individual are correlated with one another, and (2) values of parameters capture interindividual variation in populations of a specific gender, race, and age range. The parameters investigated in this project include: (1) volumes of selected organs and tissues; (2) blood flows for the organs and tissues; and (3) the total cardiac output under resting conditions and average daily inhalation rate. These parameters are expressed as records of correlated values for the approximately 30,000 individuals evaluated in the NHANES III survey. A computer program, Physiological Parameters for PBPK Modeling (P3M), is developed that allows records to be retrieved randomly from the database with specification of constraints on age, sex, and ethnicity. P3M is publicly available. The database and accompanying software provide a convenient tool for parameterizating models of interindividual variation in human pharmacokinetics.

Computer Simulation↗
PubMed2002

The use of biologically based modeling in risk assessment.

Technological advances are rapidly leading toxicology and risk assessment to an age where there are advantages of routine use of biologically based modeling as an adjunct to laboratory experiments will be compelling. The biologically based model, a formal representation of the system being studied, serves both the experimentalist and the risk assessor. Benefits of its development include identification of data gaps, optimization of experimental design and, with sufficient validation, quantitative extrapolations between routes of exposure, species and doses. This article focuses on the role of biologically based modeling in support of the dose-response assessment component of risk assessment. The problem of uncertainty in dose-response assessment and the role of mechanistic studies combined with modeling to efficiently reduce uncertainty are discussed. The need for close cooperation between experimentalists, modelers, and risk assessors to achieve this efficiency is emphasized. A model for formaldehyde is briefly described to illustrate key issues.

Animals↗
PubMedDate not supplied

Dose-response modeling in reproductive toxicology in the systems biology era.

Systems biology approaches for modeling cellular signaling networks affected by chemical exposures should soon produce integrated methodologies capable of predicting dose-response relationships for developmental toxicants and for other toxic responses. This paper outlines an emerging strategy for systems biology approaches in dose-response modeling. Genome-wide functional screens, bioinformatic tools, and network mapping technologies together can provide directed graph representations of the cellular signaling networks. The graphical representations can be converted into mathematical models that permit predicting the shapes of dose-response curves for altered cell signaling by test compounds during development. Systems biology approaches require interdisciplinary teams with expertise in reproduction, cell biology, signal transduction, mathematical/biomedical modeling, and risk assessment. In addition to outlining a systems approach for dose-response research, this paper discusses initial stages of application of this strategy to examine inhibition of steroidogenesis in testes by phthalate esters.

Animals↗