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Raymond S H Yang

Publications and source records attributed to Raymond S H Yang.

18 recordsLinked to original sources
PubMed2006

A physiologically based pharmacokinetic model for lactational transfer of PCB 153 with or without PCB 126 in mice.

Chemical exposure via breast milk is one of the great concerns in public health. Previously, we demonstrated that most body burden of PCB 153 can be transferred from the mother to the pups in mice during lactational period. Here we present a physiologically based pharmacokinetic (PBPK) model to describe the lactational transfer of PCB 153 with or without PCB 126 in mice. The model incorporated physiological changes on the volume and the blood flow into mammary tissues, and considered mechanistic information on the movement of PCB 153 from adipose tissue to the mammary gland during lactational period. The mechanistic consideration includes fat volume changes, binding of PCB 153 to very low density lipoprotein (VLDL) and increased uptake of VLDL in mammary tissues. Model parameters depicting physiological changes were obtained from research articles dealing with chemical transfer during lactational period in rodents. Chemical-specific parameters were derived from previous PBPK models focusing on the PCB disposition in rodents. The developed model adequately described the lactational transfer of PCB 153 with or without PCB 126 in mice. Our model will provide a useful mechanistic tool to estimate the disposition of PCBs in diverse experimental designs regarding PCB effects during developmental period and to improve quantitative risk assessment of PCBs in the developing organisms.

Animals↗
PubMed2006

An updated physiologically based pharmacokinetic model for hexachlorobenzene: incorporation of pathophysiological states following partial hepatectomy and hexachlorobenzene treatment.

Physiologically based pharmacokinetic (PBPK) modeling is generally used for describing xenobiotic disposition in animals and humans with normal physiological conditions. We describe here an updated PBPK model for hexachlorobenzene (HCB) in male F344 rats with the incorporation of pathophysiological conditions. Two more features contribute to the distinctness of this model from the earlier published versions. This model took erythrocyte binding into account, and a particular elimination process of HCB, the plasma-to-gastrointestinal (GI) lumen passive diffusion (i.e., exsorption), was incorporated. Our PBPK model was developed using data mined from multiple pharmacokinetic studies in the literature, and then modified to simulate HCB disposition under the conditions of our integrated pharmacokinetics/liver foci bioassay. This model included plasma, erythrocytes, liver, fat, rapidly and slowly perfused compartments, and GI lumen. To account for the distinct characteristics of HCB absorption, the GI lumen was split into an upper and a lower part. HCB was eliminated through liver metabolism and the exsorption process. The pathophysiological changes after partial hepatectomy, such as alterations in the liver and body weights and fat volume, were incorporated in our model. With adjustment of the transluminal diffusion-related parameters, the model adequately described the data from the literature and our bioassay. Our PBPK model simulation suggests that HCB absorption and exsorption processes depend on exposure conditions; different exposure conditions dictate different absorption and exsorption rates. This model forms a foundation for our further exploration of the quantitative relationship between HCB exposure and development of preneoplastic liver foci.

Animals↗
PubMed2005

A novel, sensitive method for determining benzo[a]pyrene-diones using high-performance liquid chromatography with post-column zinc reduction.

A novel and sensitive high-performance liquid chromatography (HPLC) method was developed to analyze dione metabolites of benzo[a]pyrene (BaP). Because BaP-diones do not fluoresce, detection of low concentrations is difficult to achieve when analyzing these chemicals with a simple HPLC system. We developed a method to increase the detection sensitivities for BaP-diones using reduction by zinc after the chromatographic separation. A post-column zinc reducer was used to convert BaP-diones, in-line, to their corresponding fluorescent BaP-hydroquinones, which can be measured by fluorescence detection with high sensitivity. With 20-muL injections, the limits of detection for the BaP-diones tested (BaP-1,6-dione, BaP-3,6-dione, and BaP-6,12-dione) were all below 1.0 nM. In addition to the high detection sensitivity, this HPLC method provides a wide linear dynamic range for BaP-dione detection (1.0-220 nM). We also studied the extraction recovery of BaP-diones from recombinant human cytochrome P450 and epoxide hydrolase. To demonstrate the application of this method, the kinetics of BaP-dione formation was studied by incubating BaP with these recombinant enzymes. The present method enhances the detection sensitivity for BaP-diones by more than two orders of magnitude compared with traditional ultraviolet detection. Moreover, the method avoids the time-consuming derivatization or reduction steps required by other methods.

Benzo(a)pyrene↗
PubMed2005

Biochemical reaction network modeling: predicting metabolism of organic chemical mixtures.

All organisms are exposed to multiple xenobiotics, through food, environmental contamination, and drugs. These xenobiotics often undergo biotransformation, a complex process that plays a critical role in xenobiotic elimination or bioactivation to toxic metabolites. Here we describe the results of a new computer-based simulation tool that predicts metabolites from exposure to multiple chemicals and interconnects their metabolic pathways, using four common drinking water pollutants (trichloroethylene, perchloroethylene, methylchloroform, and chloroform) as a test case. The simulation tool interconnected the metabolic pathways for these compounds, predicted reactive intermediates, such as epoxides and acid chlorides, and uncovered points in the metabolic pathways where typical endogenous compounds, such as glutathione or carbon dioxide, are consumed or generated. Moreover, novel metabolites, not previously reported, were predicted via this methodology. Metabolite prediction is based on a reaction-mechanism-based methodology, which applies fundamental organic and enzyme chemistry. The tool can be used to (a) complement experimental studies of chemical mixtures, (b) aid in risk assessment, and (c) help understand the effects of complex chemical mixtures. Our results indicate that this tool is useful for predictive xenobiotic metabolomics, providing new and important insights into metabolites and the interrelationship between diverse chemicals that hitherto may have remained unnoticed.

Computer Simulation↗
PubMed2005

Pitfalls and related improvements of in vivo gas uptake pharmacokinetic experimental systems.

Gas uptake chamber studies have been widely used to study inhalation pharmacokinetics (PKs) in rodents, often for the ultimate purpose of developing physiologically-based pharmacokinetic (PBPK) models that can be used to describe human PKs and to support risk assessment for the chemical. In the course of our studies of gasoline PKs, we revisited several important issues heretofore not thoroughly addressed. Here, we report several refinements which will significantly improve future studies with this type of system, relating to the understanding of loss rates, the importance of carbon dioxide removal, and sampling of blood and chamber air at the same time. Losses of chemicals in gas uptake systems consist of leakage, adsorption to system components, and adsorption to the hair and skin (fur) of experimental animals. The loss rates were experimentally determined for a series of chemicals and mixtures including n-hexane, benzene, toluene, ethylbenzene, o-xylene, gasoline, and other gasoline components. The rate of loss to the animals' fur was similar to loss rates to system components and involved absorption to both hair and skin. Most of the absorption to fur was reversible when the chamber concentration was low enough. The amount of chemical that desorbed from the animal after an experiment was significant when compared to the amount of chemical in the chamber at the end of a gas uptake experiment, indicating that the rate of decline in concentrations can be influenced by a decrease in the fur absorption rate or desorption of chemicals. A modified gas uptake system design is described in which a steel ring improved the connections to an autosampler and allowed insertion of probes to monitor gases, such as carbon dioxide (CO2), in the chamber. When CO2 absorbent efficiency was inadequate, CO2 concentrations rose to levels that significantly affected the animals' ventilation rate. Using a real-time CO2 probe, an absorbent system was developed that adequately controlled CO2 levels in the chamber. Attention to details of absorptive loss and CO2 scrubbing can improve the reliability of kinetic constants inferred from closed chamber studies. We then describe a method for extending gas uptake experiments by simultaneously collecting blood to be analyzed for chemicals and/or metabolites.

Air Pollutants↗
PubMed2005

Evaluation of potential toxicity from co-exposure to three CNS depressants (toluene, ethylbenzene, and xylene) under resting and working conditions using PBPK modeling.

Under OSHA and American Conference of Governmental Industrial Hygienists (ACGIH) guidelines, the mixture formula (unity calculation) provides a method for evaluating exposures to mixtures of chemicals that cause similar toxicities. According to the formula, if exposures are reduced in proportion to the number of chemicals and their respective exposure limits, the overall exposure is acceptable. This approach assumes that responses are additive, which is not the case when pharmacokinetic interactions occur. To determine the validity of the additivity assumption, we performed unity calculations for a variety of exposures to toluene, ethylbenzene, and/or xylene using the concentration of each chemical in blood in the calculation instead of the inhaled concentration. The blood concentrations were predicted using a validated physiologically based pharmacokinetic (PBPK) model to allow exploration of a variety of exposure scenarios. In addition, the Occupational Safety and Health Administration and ACGIH occupational exposure limits were largely based on studies of humans or animals that were resting during exposure. The PBPK model was also used to determine the increased concentration of chemicals in the blood when employees were exercising or performing manual work. At rest, a modest overexposure occurs due to pharmacokinetic interactions when exposure is equal to levels where a unity calculation is 1.0 based on threshold limit values (TLVs). Under work load, however, internal exposure was 87%higher than provided by the TLVs. When exposures were controlled by a unity calculation based on permissible exposure limits (PELs), internal exposure was 2.9 and 4.6 times the exposures at the TLVs at rest and workload, respectively. If exposure was equal to PELs outright, internal exposure was 12.5 and 16 times the exposure at the TLVs at rest and workload, respectively. These analyses indicate the importance of (1) selecting appropriate exposure limits, (2) performing unity calculations, and (3) considering the effect of work load on internal doses, and they illustrate the utility of PBPK modeling in occupational health risk assessment.

Animals↗
PubMed2004

Development of a physiologically based pharmacokinetic model for volatile fractions of gasoline using chemical lumping analysis.

Physiologically based pharmacokinetic (PBPK) models have often been used to describe the absorption, distribution, metabolism, and excretion of chemicals in animals but have been limited to single chemicals and simple mixtures due to the numerous parameters required in the models. To overcome the barrier to modeling more complex mixtures, we used a chemical lumping approach, used in the past in chemical engineering but not in pharmacokinetic modeling, in a rat PBPK model for gasoline hydrocarbons. Our previous gasoline model consisted of five individual components (benzene, toluene, ethylbenzene, xylene, and hexane) and a lumped chemical that included all remaining components of whole gasoline. Despite being comprised of hundreds of components, the lumped component could be described using a single set of chemical parameters that depended on the blend of gasoline. In the present study, we extend this approach to evaporative fractions of gasoline. The PBPK model described the pharmacokinetics of all of the volatility-weighted fractions of gasoline when differences in partitioning and metabolism between fractions were taken into account. Adjusting the ventilation rate parameter to account for respiratory depression at high exposures also allowed a much improved description of the data. At high exposure levels, gasoline components competitively inhibit each other's metabolism, and the model successfully accounted for binary interactions of this type, including between the lumped component and the five other chemicals. The model serves as a first example of how the engineering concept of chemical lumping can be used in pharmacokinetics.

Adsorption↗
PubMed2003

Gene expression patterns as potential molecular biomarkers for malignant transformation in human keratinocytes treated with MNNG, arsenic, or a metal mixture.

In previous studies, treatment with 1-methyl-3-nitro-1-nitrosoguanidine (MNNG) enhanced malignant transformation of immortal human epidermal (RHEK-1) keratinocytes. In contrast, arsenic (As) alone or in a mixture of As, cadmium (Cd), chromium (Cr), and lead (Pb) inhibited this process. Microarray analysis showed unique gene expression patterns in RHEK-1 exposed to MNNG, As, or the metal mixture. From this analysis, we have selected 16 genes potentially involved in the enhancement or inhibition of transformation. These 16 genes, nine (IFN inducible protein 9-27, MAA A32, CCLB protein, integrin beta4, XRCC1, K8, K18, MT3, MAPKK6) of which were altered in a chemical-specific manner and seven (MIC1, bikunin, MTS1, BMP4, RAD23A, DOC2, vimentin) of which were commonly affected by the MNNG and As or mixture treatments, were examined for expression in detail by real-time RT-PCR. Qualitatively, both microarray and real-time RT-PCR analyses gave comparable results for 15 of 16 genes, i.e., genes were consistently induced or suppressed under the different treatment regimens when measured by either technique. Of the seven genes altered in their expression by multiple chemical treatments, five showed patterns consistent with a role in the transformation process, i.e., they were oppositely regulated in MNNG-transformed RHEK-1 cells (designated as OM3) as compared to the nonmalignant As- and mixture-exposed cells. Through time-course studies, we also identified markers whose expression correlates with acquisition of transformation-associated characteristics in OM3. Identification of a battery of genes altered during progressive transformation of RHEK-1 should aid in developing a mechanistic understanding of this process, as well as strengthening the utility of these genes as biomarkers.

Animals↗
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

Characterization of the pharmacokinetics of gasoline using PBPK modeling with a complex mixtures chemical lumping approach.

Gasoline consists of a few toxicologically significant components and a large number of other hydrocarbons in a complex mixture. By using an integrated, physiologically based pharmacokinetic (PBPK) modeling and lumping approach, we have developed a method for characterizing the pharmacokinetics (PKs) of gasoline in rats. The PBPK model tracks selected target components (benzene, toluene, ethylbenzene, o-xylene [BTEX], and n-hexane) and a lumped chemical group representing all nontarget components, with competitive metabolic inhibition between all target compounds and the lumped chemical. PK data was acquired by performing gas uptake PK studies with male F344 rats in a closed chamber. Chamber air samples were analyzed every 10-20 min by gas chromatography/flame ionization detection and all nontarget chemicals were co-integrated. A four-compartment PBPK model with metabolic interactions was constructed using the BTEX, n-hexane, and lumped chemical data. Target chemical kinetic parameters were refined by studies with either the single chemical alone or with all five chemicals together. o-Xylene, at high concentrations, decreased alveolar ventilation, consistent with respiratory irritation. A six-chemical interaction model with the lumped chemical group was used to estimate lumped chemical partitioning and metabolic parameters for a winter blend of gasoline with methyl t-butyl ether and a summer blend without any oxygenate. Computer simulation results from this model matched well with experimental data from single chemical, five-chemical mixture, and the two blends of gasoline. The PBPK model analysis indicated that metabolism of individual components was inhibited up to 27% during the 6-h gas uptake experiments of gasoline exposures.

Animals↗
PubMed2002

Effects of developmental exposure to lead, magnesium and zinc mixtures on spatial learning and expression of NMDA receptor subunit mRNA in Fischer 344 rats.

The N-methyl-D-aspartate receptor (NMDAR) is important for learning. Lead (Pb) exposure impairs learning ability and affects the NMDAR. This study tested whether developmental exposure to a combination of Pb, zinc (Zn), and magnesium (Mg) would result in effects different from those seen with individual metals. Fischer 344 (F344) rat pups of both genders were exposed from gestation day 5 to post-natal day (PND) 40, either to Pb, Mg, or Zn individually or to a (one-third or full concentration) mixture of the three metals. All Zn-treated pups died before PND7, but half of the litters given the full concentration mixture survived to PND40. Impaired learning in the Morris water maze was seen in the Mg and full concentration mixture groups. There were gender differences in NR2A subunit mRNA expression in the hippocampal CA3 region in the Mg and Pb groups, but combining the three metals in the full concentration showed no gender effect. Our results showed that exposure to all three metals affected mortality, learning ability and gender-dependent expression patterns of an NMDAR subunit in a different way from that seen with exposure to the individual metals.

Animals↗
PubMed2002

Comparison of pharmacokinetic interactions and physiologically based pharmacokinetic modeling of PCB 153 and PCB 126 in nonpregnant mice, lactating mice, and suckling pups.

Polychlorinated biphenyls (PCBs) are ubiquitous environmental contaminants that can induce neurological defects in infants and children via placental and lactational transfer. To investigate the lactational transfer of PCBs and compare pharmacokinetic interactions among nonpregnant, lactating mice and suckling pups, quantitative time-course measurements of PCB accumulation in tissues were performed. On postnatal day 1, nonpregnant and lactating C57BL/6 mice were exposed to PCB 153 (2,2',4,4',5,5'-hexachlorobiphenyl, 20 mg/kg) alone or a mixture of PCB 153 (20 mg/kg) and PCB 126 (3,3',4,4',5-pentachlorobiphenyl, 0.2 mg/kg) by oral gavage. At 1, 3, 6, and 13 days after treatment, PCB 153 and PCB 126 were determined in nonpregnant and maternal tissues as well as in neonatal tissues by gas chromatography (GC). Coadministration of PCB 153 and PCB 126 increased PCB 153 retention in the liver and decreased PCB 153 accumulation in the fat of nonpregnant mice. Lactational transfer was confirmed to be an efficient elimination mechanism for the lactating mice but a major source of exposure in the pups. However, little or no significant pharmacokinetic interactions were observed in lactating mice and suckling pups. To describe pharmacokinetic interactions between PCB 153 and PCB 126, a physiologically based pharmacokinetic model for PCB 153 disposition was developed. The effects of PCB 126 on the fat content in liver and a diffusion permeation constant in fat were incorporated into the physiologically based pharmacokinetic (PBPK) model. This model successfully describes PCB 153 disposition altered by PCB 126 in nonpregnant mice.

Adipose Tissue↗
PubMed2002

In silico toxicology: simulating interaction thresholds for human exposure to mixtures of trichloroethylene, tetrachloroethylene, and 1,1,1-trichloroethane.

In this study, we integrated our understanding of biochemistry, physiology, and metabolism of three commonly used organic solvents with computer simulation to present a new approach that we call "in silico" toxicology. Thus, we developed an interactive physiologically based pharmacokinetic (PBPK) model to predict the individual kinetics of trichloroethylene (TCE), perchloroethylene (PERC), and methylchloroform (MC) in humans exposed to differently constituted chemical mixtures of the three solvents. Model structure and parameterization originate from the literature. We calibrated the single-compound PBPK models using published data and described metabolic interactions within the chemical mixture using kinetic constants estimated in rats. The mixture model was used to explore the general pharmacokinetic profile of two common biomarkers of exposure, peak TCE blood levels and total amount of TCE metabolites generated, in rats and humans. Assuming that a 10% change in the biomarkers corresponds to a significant health effect, we calculated interaction thresholds for binary and ternary mixtures of TCE, PERC, and MC. Increases in the TCE blood levels led to higher availability of the parent compound for glutathione conjugation, a metabolic pathway associated with kidney toxicity/carcinogenicity. The simulated change in production rates of toxic conjugative metabolites exceeded 17% for a corresponding 10% increase in TCE blood concentration, indicating a nonlinear risk increase due to combined exposures to TCE. Evaluation of metabolic interactions and their thresholds illustrates a unique application of PBPK modeling in risk assessment of occupational exposures to chemical mixtures.

Biological Availability↗
PubMed2002

BioMOL: a computer-assisted biological modeling tool for complex chemical mixtures and biological processes at the molecular level.

A chemical engineering approach for the rigorous construction, solution, and optimization of detailed kinetic models for biological processes is described. This modeling capability addresses the required technical components of detailed kinetic modeling, namely, the modeling of reactant structure and composition, the building of the reaction network, the organization of model parameters, the solution of the kinetic model, and the optimization of the model. Even though this modeling approach has enjoyed successful application in the petroleum industry, its application to biomedical research has just begun. We propose to expand the horizons on classic pharmacokinetics and physiologically based pharmacokinetics (PBPK), where human or animal bodies were often described by a few compartments, by integrating PBPK with reaction network modeling described in this article. If one draws a parallel between an oil refinery, where the application of this modeling approach has been very successful, and a human body, the individual processing units in the oil refinery may be considered equivalent to the vital organs of the human body. Even though the cell or organ may be much more complicated, the complex biochemical reaction networks in each organ may be similarly modeled and linked in much the same way as the modeling of the entire oil refinery through linkage of the individual processing units. The integrated chemical engineering software package described in this article, BioMOL, denotes the biological application of molecular-oriented lumping. BioMOL can build a detailed model in 1-1,000 CPU sec using standard desktop hardware. The models solve and optimize using standard and widely available hardware and software and can be presented in the context of a user-friendly interface. We believe this is an engineering tool with great promise in its application to complex biological reaction networks.

Animals↗
PubMed2002

Characterization of gene expression changes associated with MNNG, arsenic, or metal mixture treatment in human keratinocytes: application of cDNA microarray technology.

The identification of molecular markers related to critical biological processes during carcinogenesis may aid in the evaluation of carcinogenic potentials of chemicals and chemical mixtures. Work from our laboratory demonstrated that a single treatment with N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) enhanced spontaneous malignant transformation of the human keratinocyte cell line RHEK-1. In contrast, chronic low-level exposure of cells to arsenic alone or in a mixture containing arsenic, cadmium, chromium, and lead inhibited malignant conversion. To identify changes in gene expression that influence these different outcomes, cDNA microarray technology was used. Analysis of multiple human arrays in MNNG-transformed RHEK-1 cells, designated OM3, and those treated with arsenic or the arsenic-containing metal mixture showed unique patterns of gene expression. Genes that were overexpressed in OM3 included oncogenes, cell cycle regulators, and those involved in signal transduction, whereas genes for DNA repair enzymes and inhibitors of transformation and metastasis were suppressed. In arsenic-treated cells, multiple DNA repair proteins were overexpressed. Mixture-treated cells showed increased expression of a variety of genes including metallothioneins and integrin 4. These cells showed decreased expression of oncogenes, DNA repair proteins, and genes involved in the mitogen-activated protein kinase pathway. For comparison we are currently analyzing gene expression changes in RHEK-1 cells transformed by other means. The goal of these studies is to identify common batteries of genes affected by chemical modulators of the carcinogenic process. Mechanistic studies may allow us to correlate alterations in their expression with sequential stages in the carcinogenic process and may aid in the risk assessment of other xenobiotics.

Arsenic↗
PubMed2002

Application of biologically based computer modeling to simple or complex mixtures.

The complexity and the astronomic number of possible chemical mixtures preclude any systematic experimental assessment of toxicology of all potentially troublesome chemical mixtures. Thus, the use of computer modeling and mechanistic toxicology for the development of a predictive tool is a promising approach to deal with chemical mixtures. In the past 15 years or so, physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been applied to the toxicologic interactions of chemical mixtures. This approach is promising for relatively simple chemical mixtures; the most complicated chemical mixtures studied so far using this approach contained five or fewer component chemicals. In this presentation we provide some examples of the utility of PBPK/PD modeling for toxicologic interactions in chemical mixtures. The probability of developing predictive tools for simple mixtures using PBPK/PD modeling is high. Unfortunately, relatively few attempts have been made to develop paradigms to consider the risks posed by very complex chemical mixtures such as gasoline, diesel, tobacco smoke, etc. However, recent collaboration between scientists at Colorado State University and engineers at Rutgers University attempting to use reaction network modeling has created hope for the possible development of a modeling approach with the potential of predicting the outcome of toxicology of complex chemical mixtures. We discuss the applications of reaction network modeling in the context of petroleum refining and its potential for elucidating toxic interactions with mixtures.

Computer Simulation↗
PubMed2002

Molecular circuits, biological switches, and nonlinear dose-response relationships.

Signaling motifs (nuclear transcriptional receptors, kinase/phosphatase cascades, G-coupled protein receptors, etc.) have composite dose-response behaviors in relation to concentrations of protein receptors and endogenous signaling molecules. "Molecular circuits" include the biological components and their interactions that comprise the workings of these signaling motifs. Many of these molecular circuits have nonlinear dose-response behaviors for endogenous ligands and for exogenous toxicants, acting as switches with "all-or-none" responses over a narrow range of concentration. In turn, these biological switches regulate large-scale cellular processes, e.g., commitment to cell division, cell differentiation, and phenotypic alterations. Biologically based dose-response (BBDR) models accounting for these biological switches would improve risk assessment for many nonlinear processes in toxicology. These BBDR models must account for normal control of the signaling motifs and for perturbations by toxic compounds. We describe several of these biological switches, current tools available for constructing BBDR models of these processes, and the potential value of these models in risk assessment.

Cell Differentiation↗