* National Health and Environmental Effects Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711;
Research Triangle Institute, Research Triangle Park, North Carolina 27709; and
Department of Pharmaceutical and Biomedical Sciences, College of Pharmacy, University of Georgia, Athens, Georgia 30602
Received October 25, 2001; accepted May 28, 2002
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ABSTRACT |
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Key Words: physiologically based pharmacokinetic model; trichloroethylene; Long-Evans rat; Vmaxc.
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INTRODUCTION |
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The National Health and Environmental Effects Research Laboratory of the U.S. EPA is engaged in a research program to develop exposure-dose-response models for priority volatile organic compounds (VOCs) (Boyes et al., 2000). Neurotoxicity is a concern following acute exposure to VOCs; thus, neurotoxicity was selected for the "response" portion of the exposure-dose-response continuum (Boyes et al., 2000
). TCE was selected for investigation because, despite its well-known neurotoxic properties and the fact that its volume of use, release, and potential for human exposure are all high, an exposure-dose-response model for the neurotoxicity of TCE has not been developed. The Long-Evans (LE) rat is the rodent stock in which the relationships between the concentration of TCE in the atmosphere (external exposure concentration), exposure duration, and neurotoxicity have been or are being investigated for three different neurological outcome measures: hearing loss, signal detection behavior, and visual function (Boyes et al., 2000
, in preparation; Bushnell, 1997
; Crofton and Zhao, 1997
).
Based on the results of a computerized literature search (PubMed) LE rats are not as commonly used in neurotoxicity as Sprague-Dawley (SD) rats but are used more frequently than Fischer-344 (F344) rats (the search terms for either SD, LE, or F344 and nervous system resulted in 45,895, 2715, and 1047 citations, respectively). Relative to the SD rat (an albino stock), the LE rat (a pigmented stock) is particularly well suited for investigation of chemically mediated disturbances of the visual system due to its pigmentation. As summarized by Fox and Boyes (2001), it has been estimated that almost half of all neurotoxic chemicals affect some aspect of sensory function, with visual system alterations the most frequently reported sensory system alteration. These authors further make a very strong case for the use of nonalbino rat stocks (e.g., the LE rat) when assessing the neurotoxicity of chemicals, so that defects on the visual system can be identified. Thus, the objective of the present investigation was development of a PBPK model for TCE for the LE rat. As the initial planned use of this model was exploration of the relationship between external exposure concentration, internal dosimetry, and neurological effect, the brain was included as a separate physiological compartment.
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MATERIALS AND METHODS |
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Test chemical.
The test compound was 1,1,2-trichloroethylene (TCE), CAS # 79-01-6. The TCE used in all experiments was spectrophotometric grade, with a purity of 99.5% as specified by the supplier (Aldrich Chemical Co., St. Louis, MO).
Measurement of organ and tissue volumes.
For measurement of tissue volumes, groups of rats were received at 60 ± 2 days of age and held until they were 72 (± 2) days of age; other groups of rats were received at 65 ± 2 and 90 ± 2 days of age and held until they were, respectively, 102 (± 2) and 149 (± 2) days of age. At termination, anoxia was induced by carbon dioxide. The rats were then weighed and bled from the abdominal aorta followed by transection of the diaphragm. The brain and liver were removed and weighed. The remaining carcasses were frozen at 20°C (nominal) prior to measurement of whole body fat by the physical dissection technique described by Anderson et al.(1993). The body and organ/tissue weight data were subjected to Cochrans test for homogeneity of variance (Winer et al., 1991); the significance criterion was 0.01. When the assumption of equality of variance was not met (i.e., for fat and relative fat weight), the data were ranked prior to further analysis. Data (raw and ranked) were analyzed by analysis of variance (PROC GLM, SAS Version 6.08, SAS Institute, Cary, NC). When the minimum significance criterion was met, the data were analyzed further by the Ryan-Einot-Gabriel-Welsh multiple range test. The 0.05 level of probability was selected as the minimum criterion of significance, with lower probability levels reported also to allow an assessment of the likelihood that significant results were due to Type I (false positive) statistical error. Linear (PROC REG, SAS Version 6.08, SAS Institute, Cary, NC) and nonlinear (Sigma-Plot, Version 4.0, SPSS, Chicago, IL) regressions were performed on individual animal values.
Partition coefficients.
TCE partition coefficients (PCs) were determined experimentally in LE rats using the vial equilibration method described by Gargas et al.(1989). Naive rats (i.e., rats that had not been exposed previously to TCE) were used. Anoxia was induced in individual rats by carbon dioxide; blood was then collected from the abdominal aorta in heparinized vacutainer tubes (Becton-Dickinson, Rutherford, NJ) and the diaphragm transected. Samples of liver, muscle, fat, and brain were taken. Following homogenization in 0.9% saline (tissue:saline ratios: liver, 1:3; fat, 1:9; brain and muscle, 1:4), all tissues were placed in sealed head-space vials (Hewlett-Packard, Kennett Square, PA) with all interior surfaces either glass or Teflon-covered. Following injection of TCE into the vials, they were incubated at 37°C for three h in a shaking Vortex Evaporator (Buchler Instruments, Lenexa, KS). After incubation, a head-space sample was removed with a gas-tight constant-rate syringe (CR700-200, Hamilton Co., Reno, NV) and analyzed by gas chromatography. Tissue/air PCs were calculated, assuming a tissue density of 1 gm/ml, from the equations derived by Gargas et al.(1989) and Sato and Nakajima (1979). Calculations are expressed as the mean ± SD of 710 rats.
Exposure to TCE in closed chambers for estimation of metabolic rate.
Rats were exposed individually to TCE in closed vapor-uptake chambers. At each concentration, three rats were exposed to initial concentrations of approximately 500, 1000, and 3000 ppm TCE except that two rats were exposed to an initial concentration of approximately 100 ppm TCE. Rats received no water or feed during TCE exposures. The vapor-uptake exposure techniques have been described in detail previously (Evans et al., 1994; McGee et al., 1995
). Briefly, chambers were considered leak-free and operational when empty-chamber loss rate determinations were
0.05/h (5%/h). The exposure duration was 6 h, except at 100 ppm TCE where exposures were terminated at approximately 4 h when the concentration of TCE in the chamber reached 10 ppm. The total system volume was 10.4 l. The chamber air was recirculated at a rate of 6 l/min. Oxygen in the chamber was monitored continuously with an electron probe (Model 3300, MDA Scientific, Lincolnshire, IL) and maintained between 19 and 21%; C02 was removed by flow of the chamber air through lithium hydroxide (Sigma/Aldrich, St. Louis, MO). Relative humidity in the exposure chambers ranged from 40 to 70% while the mean chamber temperature was 23.3°C and ranged from 22.8 to 23.8°C. Prior to introduction of TCE into the chamber air, a rat was placed into the chamber and allowed to acclimate for 45 to 60 min to permit stabilization of relative humidity and temperature.
Chamber concentration was monitored starting 10 min after injection of the appropriate volume of liquid TCE and then at 10 min intervals for the duration of the exposure. An automatic sampling valve periodically retrieved and delivered 0.25 ml of chamber air to a gas chromatograph. The automatic-sampling-valve gas chromatograph (Hewlett-Packard, Model 5890, Kennett Square, PA) used to measure TCE was equipped with a flame hydrogen ionization detector with helium as the carrier gas at a flow rate of 20 ml/min. The operating conditions were as follows: hydrogen flow, 50 ml/min; air flow, 400 ml/min; GC detector temperature, 250°C; GC injector temperature, 225°C; and oven temperature, 130°C. TCE separation was achieved isothermally via a 6 foot, 1/8 inch stainless-steel packed column (80/100 Carbopack, C/0, 1%, SP-1,000, Supelco, PA). These conditions resulted in an average retention time of 2.9 min for TCE.
Exposure to TCE in flow-through chambers for determination of TCE tissue concentration.
Rats were exposed to TCE in dynamic flow-through chambers by techniques that have been described previously (Bushnell, 1997; Bushnell et al., 1994
). Briefly, exposures were conducted in four 32.9 l test chambers, constructed of stainless steel and glass. Conditioned room air (temperature, 22 ± 2°C, relative humidity, 60 ± 5%) was pulled through each chamber at a rate of 18 l/min. TCE vapors were generated by metering liquid TCE at a rate of 1.5 ml/min into a heated (93 ± 5°C) vertical stainless-steel J-tube (2.4 cm i.d., 71 cm long) through which dry-grade nitrogen gas flowed upward at 3 l/min (Miller et al., 1980
). The resulting TCE vapor was routed into the exposure chambers by mass-flow controllers (Model FC280, Tylan General, Torrance, CA). Chamber concentration was monitored sequentially at 5-min intervals with an infrared spectrophotometer (MIRAN 1A, Foxboro Co., East Bridgewater, MA). The rise time (t95) for TCE in each chamber was approximately 8 min.
For determination of tissue concentrations of TCE, rats were exposed to 200, 2000, or 4000 ppm TCE for either 5, 20, or 60 min. Additionally, these same tissues were sampled in rats that were exposed to TCE for 60 min and then clean air for 60 min. At the designated time intervals, rats were removed from the exposure chambers and terminated by cervical dislocation within 30 s of removal from the chamber. Samples of blood (obtained by cardiac puncture), brain, liver, and fat were taken as quickly as possible, placed in gas-tight vials, and quick-frozen in liquid nitrogen. Samples were held at 80°C (nominal) until they were analyzed.
Exposure to TCE in flow-through chambers for serial sampling of blood.
Inhalation exposures for cannulated rats were conducted in the same exposure system, used for recording pattern-elicited visual-evoked potentials (Boyes, in preparation). Basically, a syringe pump (Model 22, Harvard Apparatus, South Natick, MA) introduced liquid TCE into the air stream of the J-tube through which an upward stream of carbon- and HEPA-filtered air flowed at a rate of 6.6 l/min (McGee et al., 1994). The J-tube was heated to 80°C to vaporize the TCE, and the air stream was then passed through a heat exchanger to cool it to room temperature before introduction into the exposure chamber. The atmosphere in the exposure chamber was monitored continuously with a long-path-length dispersive infrared (IR) spectrophotometer (Miran, 1A, Foxboro Co, East Bridgewater, MA). The exposure monitor system was calibrated using a closed loop system, and TCE levels were confirmed using gas chromatography. The exposure chamber contained separate compartments for the torso and head of the rats. The interior dimensions of the head chamber space were 10 x 10 x 17 cm (width x depth x height). The chamber was constructed of stainless steel with the exception of the front and one side wall, which were constructed of glass.
S27 jugular-vein cannulas (IITC Inc., Woodland Hills, CA) were implanted surgically in 100-day-old male LE rats. Following surgery, the cannulas were flushed with heparinized saline (26.7 mg Na+ heparin [Sigma Chemical Co., St. Louis, MO] per ml of 0.9% sodium chloride [Fisher Scientific, Norcross, GA] 3 times daily for 3 days prior to exposure to TCE. Rats with patent cannulas were restrained in a plastic decapicone® (Braintree Scientific, Braintree MA) with the narrow portion of the cone removed to uncover the eyes, ears, and nose. The rats were placed in the exposure system keeping the cannula lead clear, and a latex gas-tight seal was formed between the upper torso and the wall of the head-only exposure chamber. Room air was moved at a high rate (approximately 300 l/min) through the compartment enclosing the rats body; this compartment was kept under negative pressure to prevent fugitive vapors from entering the open lab space.
Serial blood-sampling experiments were completed on a total of 9 rats, including three rats at each of three exposure concentrations: 200, 2000, and 4000 ppm TCE. Exposures began after the rats settled into the device and lasted for 60 min, after which the TCE was discontinued and rats were exposed to clean air for another 60 min. The nominal times for serial blood sampling included 5, 20, 40, and 60 min (during exposure), and 65, 80, 100, and 120 min (after exposure), with time expressed from the beginning of the experiment.
Analysis of TCE in blood and tissues.
Extracts were prepared from fat, liver, and brain in the following manner. Deionized water (2.0 gm/1.0 gm tissue, Hydro Picotech System, Research Triangle Park, NC) and methyl-t-butyl ether (4.0 mg/1.0 gm tissue, MTBE, Burdick & Jackson, Muskegon, MI, pesticide-grade containing bromochloroethylene [BCE] at a concentration of 500 pg/µl) were added to each tissue sample. Each tissue/solvent mixture was homogenized for 30 s using a Virtis homogenizer (Tempest Virtishear, Virtis, Gardiner, NY) followed by vortexing for 1 min.
Blood was prepared by adding 300 µl deionized water and 600 µl MTBE containing BCE to each 100 µl of blood, followed by vortexing for 1 min. Each sample was then centrifuged to affect phase separation. Recoverable extracts were transferred to gas chromatography (GC) autosampler vials and immediately capped with a Teflon-lined, silicone-septum cap. Reagents were shown to be free of TCE prior to use in the extraction of samples.
Extracts were analyzed using GC in conjunction with electron-capture detection (GC/ECD). Aliquots of 1 µl were injected (30 s splitless/split) into a Fisons 8360 GC (Thermo Finnigan, San Jose, CA) equipped with an electron-capture detector and a CE Instruments AS800 autosampler (Thermo Finnigan, San Jose, CA). The chromatographic column was 30 m by 0.32 mm i.d. (1.8 µm film) DB-624 (J&W Scientific, Folsom, CA) and was temperature programmed from 35°C (1 min hold) to 160°C at 7°/min (10 min hold). A 3-meter section of deactivated fused silica (0.32 µm i.d.) retention gap was installed.
Calibration solutions of TCE (1000 µg/ml in methanol, Ultra Scientific, North Kingstown, RI) were prepared in MTBE containing BCE to provide concentrations of 0.3, 0.89, 3, 9, 30, 75, 150, 300, 750, 1500, and 3000 ng/µl. The ratios of the area of TCE to BCE were calculated and used to generate calibration curves from which TCE concentrations in unknown samples were calculated. Curves generated using solvent standards agreed very well with those generated by analyzing extracts from tissue and blood samples to which known amounts of TCE were added. The assay precisions for TCE measured as standards or spiked into biological media (n = 3) ranged from 0.2 to 5.2% (percent relative SD). The percent recovery of TCE from tissues spiked with TCE to achieve nominal concentrations of either 20, 40, 100, 200, 400, or 800 ppb ranged from 95121% for blood, 98106% for brain, 98103% for liver, and 103120% for fat. Method detection limits (3 times the deviation of the low curve point, 20 ppb, prepared by spiking and extracting each matrix) were 3.1 ppb, blood; 1.4 ppb, brain; 1.0 ppb, liver; and 2.4 ppb, fat. Method quantitation limits (10 times the SD of analysis of 20 ppb spikes) were 10 ppb, blood; 4.8 ppb, brain; 3.2 ppb, liver; and 8.1 ppb, fat.
PBPK modeling.
The PBPK model constructed and used was based on the model structure presented by Ramsey and Andersen (1984). A brain compartment was added to the liver, slowly perfused tissue, rapidly perfused tissue, and fat compartments described by Ramsey and Andersen (1984). The simulation modeling package was Simusolv® (Version 3.0, 1993). To estimate Vmaxc, all model input parameters, except for Vmaxc, were defined, and Vmaxc was optimized based on the mean, at each concentration and time point, of the closed-chamber data. Vmax was calculated according to the equation, Vmax = Vmaxc(BW)0.74. Once Vmaxc was estimated, all model input parameters, including Vmaxc, were fixed and the completed model used to simulate tissue concentrations at various times for several concentrations (200, 2000, and 4000 ppm) of TCE.
To the extent possible, the physiological input parameters used were measured in LE rats. The volumes of the liver, brain, and fat compartments were calculated for each rat that was used in the estimation of Vmaxc (the rats exposed to TCE in the vapor uptake experiments) and each rat in which TCE tissue concentrations were measured (flow-through inhalation exposure of cannulated and noncannulated rats) using the regression equations developed in the present study. Based on the statistical strengths of the linear/nonlinear relationships, the linear regression equations for absolute liver weight and relative brain weight (brain weight as a percentage of body weight) and the cubic equation for absolute fat weight were used in the model. Tissue/blood PCs were calculated within the PBPK model as the ratio of the tissue/air to tissue/blood PCs.
A computerized literature search (PubMed) did not locate LE-specific blood flow values. However, blood-flow data measured in awake, nonrestrained animals by use of the microsphere technique were available for male SD rats (Delp et al., 1991) and for male F344 rats (Delp et al., 1998
). With no information to indicate which rodent strain (F344) or stock (SD) might more closely resemble the LE rat, a decision was made to model each TCE data set gathered in the LE rat twiceonce with SD-specific blood-flow data and once with F344-specific blood-flow data. In both cases, the other physiological inputs, with the exception of the volumes of the slowly and rapidly perfused compartments, were LE specific. Typically, models from this laboratory set alveolar ventilation rate (QPC) equal to cardiac output (QCC). In the present case, QCC was initially set at the respective F344 (13.2 l/h/kg) or SD (15.4 l/h/kg) value and QPC set accordingly. Based on the report (Dallas et al., 1991
) that, relative to 50 ppm TCE, exposure to 500 ppm TCE resulted in a 20% decrease in the rate of alveolar ventilation, QPC was decreased 20% from the initial value. Under the assumption that alterations in QPC would not result in directly corresponding alterations in QCC, the relationship between the two was set as QPC = 0.94 QCC, a ratio used in previous models (Gargas et al., 1986
). The fits of the model simulations to the experimentally determined tissue concentrations of TCE were evaluated with the index developed by Krishnan et al.(1995) to quantitate the discrepancy between PBPK model simulations and experimental data.
Sensitivity analyses.
After the PBPK model equations and input parameters were specified, the normalized sensitivity coefficients for tissue concentrations of TCE were calculated with Simusolv®. Sensitivity coefficients (SCs) were derived, with a fixed simulation interval of 2 h, for the concentrations of TCE in blood, liver, fat, and brain resulting from the inhalation exposures in flow-through chambers described above. These were exposure to either 200, 2000, or 4000 ppm TCE for 5, 20, or 60 min as well as exposure to these concentrations for 60 min followed by 60 min of clearance. Default settings were used, except that the method of finite differences was selected. Based on the PBPK modeling results, the LE model that used F344 blood flows and the Vmaxc developed from use of the combination of LE and F344 values was selected for sensitivity analysis. The impacts of physiological and physiochemical parameters as well as the volume of the inhalation chamber and its flow rate were examined. A positive SC indicates that an increase in the value of the parameter will result in an increase in the tissue concentration of TCE, while a negative SC indicates that an increase in the value of the parameter will result in a decrease in the tissue concentration of TCE. The criterion used for ranking the effect of a particular parameter is based on the absolute magnitude of the SC at any given time (Yetter et al., 1985).
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RESULTS |
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Estimation of Vmaxc with the Closed Chamber Data
The PBPK model input parameters are listed in Table 3. The decline of TCE in the closed chamber was described successfully by a single saturable pathway represented by the metabolic constants, Vmax and Km. In the present study, Km was held constant at 0.25 mg/l, as varying Km, in a preliminary version of the model, by more than 25% in either direction (0.18, 0.36) had no visible effect on the fit of the model simulations to the experimental data (simulations not shown). The data representing the average chamber concentration at each time point for the 4 initial chamber concentrations (100, 500, 1000, and 3000 ppm TCE) are summarized in Figure 1
. Optimization for Vmaxc using the LE-specific physiological and physiochemical input parameters coupled with the F344-specific blood flows resulted in the simulations shown in Figure 1A
and an optimized value of 8.68 mg/h/kg for Vmaxc. Optimization for Vmaxc using the LE-specific physiological and physiochemical input parameters coupled with the SD-specific blood flows resulted in the simulations shown in Figure 1B
and an optimized value of 7.34 mg/h/kg for Vmaxc. Visual examination of Figures 1A and 1B
indicated that, in both cases, the simulations closely matched the experimental data over the duration of the experiment. Visually, the greatest difference between the simulations with F344 blood flows and those with SD blood flows was at 100 ppm, where, beginning at 3 h, the simulations based on SD flows underestimated the experimental data. The indices representing a more quantitative estimate of the discrepancy between the simulations and the experimental data are shown in Table 4
. The index was 0.05 when the model was parameterized with F344 blood-flow values and also 0.05 when the model was parameterized with SD blood-flow values, indicating that the overall fits of the model simulations to the vapor uptake data from the two sets of blood flow values were equivalent.
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Although the model simulations correctly matched the shape of the fat data (Fig. 5), use of either F344 or SD values resulted in overprediction of the experimental data at 60 and 120 min at the two higher concentrations (2000 and 4000 ppm TCE). Use of either F344 or SD flows resulted in the same value, 0.98, for the index of fit.
Simulation of TCE Blood Concentration in Serial Blood Samples from Cannulated Rats
The experimental data and model simulations resulting from incorporation of either F344 or SD blood flows are shown in Figure 6. As seen with the blood data from noncannulated animals, the model simulations captured the shape (rise and fall) of the experimental data. With either F344 or SD flows, the model tended to overpredict the concentration of TCE in blood at the two higher concentrations, particularly at 2000 ppm. For all three concentrations of TCE, the best correspondence between the model simulations and the experimental data was at 5 min, the earliest time point at which blood was sampled. At 200 ppm TCE, use of the F344 blood-flow values resulted in a better visual fit to the experimental data than use of the SD blood-flow values. Based on the index of fit (Table 4
), the simulations of the data were improved with F344 blood flows when compared to SD flows.
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The impact of cardiac output on tissue TCE concentration varied across the tissues and across both time and the inhalation concentration of TCE. The impacts of cardiac output on blood and brain TCE were negative, except at 120 min (60 min after the end of the 60 min exposure period) for 2000 ppm TCE. The negative SCs indicate that, for these times and external exposure concentrations, an increase in cardiac output would lead to a decrease in the concentration of TCE in the blood. The impact of cardiac output on liver TCE concentration also depended on time and external exposure concentration.
Among the compartment volumes, the volume of the fat compartment and the volume of the slowly perfused compartment had the greatest impacts on TCE tissue concentration. The SCs for the slowly perfused compartment were large at 5 min for both 200 and 2000 ppm TCE for all 4 tissues, blood, brain, liver, and fat. The SCs for the fat compartment were large for the concentration of TCE in fat across time and concentration. Liver volume and brain volume had relatively little impact on the concentration of TCE in any of the 4 tissues of concern.
Among the tissue blood flows, the perfusion rates of the slowly perfused compartment and the brain had relatively little impact on TCE concentration in blood, brain, liver, and fat. The SCs for fat blood flow on TCE fat concentration were large at both 200 and 2000 ppm TCE during exposure. At 200 ppm TCE, fat blood flow had a large impact on blood, brain, and liver concentrations of TCE during clearance (120 min).
With regard to the impact of the PCs, fat PC had a similar influence on TCE concentration in blood, brain, and liver: little or no influence at 5 and 20 min, with a negative effect at 60 min that becomes stronger at 120 min. Other than during clearance at 200 ppm TCE, the fat PC had little impact on the concentration of TCE in fat. The brain PC and liver PC had little or no impact on TCE concentration in any tissue other than brain and liver, respectively, where their respective effects were similar across time and external TCE concentration. The greatest impacts of the blood/air PC were on the concentrations of TCE in blood at either 200 or 2000 ppm TCE and on the concentration of TCE in brain at 200 ppm TCE.
The SCs for Vmax were consistently negative across tissue, time, and external exposure concentration. The impact of Vmax on TCE tissue concentration was most evident at 60 and 120 min at 200 ppm TCE. Except for its impact on liver TCE concentration at 200 ppm TCE, Km had little or no impact on TCE concentration in brain, blood and fat and liver.
The influence of chamber flow and chamber volume on tissue TCE concentration was similar for all examined tissues (SCs not shown). At both 200 and 2000 ppm TCE concentration, the influence of chamber volume and chamber flow was greatest at 5 min (ranging from absolute values of 0.31 to 0.50), decreasing to little/no impact at 60 and 120 min. The absolute values of the SCs for these parameters were remarkably similar but with opposing direction. The SCs for chamber volume were either negative or only slightly positive whereas the SCs for chamber flow were positive or only slightly negative.
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DISCUSSION |
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Given that its volume of use, its volume of environmental release, and its potential for human exposure are all high, it is not surprising that a number of PBPK models for TCE have been developed. PBPK models for TCE in the rat include models for male F344 rats (Andersen et al., 1987), male SD rats (Dallas et al., 1991
), female F344 rats (Fisher et al., 1989
), pregnant F344 rats (Fisher et al., 1989
), lactating F344 rats (Fisher et al., 1990
), and nursing F344 pups (Fisher et al., 1990
). Although rodent PBPK models already existed for TCE, our rationale for developing a PBPK model for TCE in the male LE rat was as follows: (1) significant differences in the pharmacokinetics of TCE have been observed among rat strains/stocks (Warren et al., 1994
), (2) none of the existing models included a brain compartment, and (3) none of the existing models was developed to account for the changes in the pharmacokinetic behavior of TCE that might occur in the weight-maintained rats used to assess the neurotoxic effects of chemicals on learning and memory. A future goal of our group is adapting the present model, developed in rats fed ad libitum, to weight-maintained rats.
The tissue to air PCs reported here for the male LE rat are similar to those reported previously for blood, fat, liver, and muscle in the male F344 rat (Andersen et al., 1987; Gargas et al., 1989
). With the exception of the liver to air PC (27.2, Andersen, Gargas; 21.34, this report), the previous values fall well within the range created by the mean ± SD of the values reported here. A comparison between partition coefficients for TCE in LE and SD rats was not possible, as coefficients for TCE specific to this rat stock were not found. Although a PBPK model has been used to simulate the concentration of TCE in the blood and exhaled air of male SD rat (Dallas et al., 1991
), that effort used PCs measured in F344 rats.
The Vmaxc values reported here were developed by optimization for Vmaxc using LE-specific physiological and physiochemical input parameters coupled with either F344-specific blood flows or SD-specific blood flows. Use of F344 blood flows and SD blood flows resulted in optimized values of Vmaxc of 8.68 and 7.34 mg/h/kg, respectively. Both of these estimates are lower than the Vmaxc of 11.0 and 9.58 mg/h/kg, respectively, reported by Andersen et al.(1987) for the male F344 rat and by Dallas et al.(1991) for the male SD rat. Based on the size of the SCs, an accurate estimate of Vmax is most important for estimation of the hepatic concentration of TCE at lower exposure concentrations. It was also important for estimation of blood and brain TCE at 60 and 120 min.
Comparison of physiological values, measured in the same laboratory in the same relative time frame, identified that organ/tissue volumes for either F344 rats or SD rats could not be described or inferred from knowledge of the other (Schoeffner et al., 1999). The conclusion was drawn that strain/stock specific data are needed for PBPK models (Schoeffner et al., 1999
). The liver, fat, and brain weights and corresponding regression equations across three ages of male LE rats should prove useful in the development of LE-specific PBPK models for other chemicals. Similarly, the inclusion of the range of values should be useful to researchers employing Monte Carlo techniques. As the LE rat is an outbred stock, it might be expected to change more rapidly over time than an inbred strain. Also, the variability among animals of an outbred stock might be greater than among animals of an inbred strain. The degree of change that may be expected either over time or supplier might be illustrated by comparison of the present values with those reported by Kozma et al.(1969). Thus, the values presented here will need periodic updating to remain useful.
Where and when possible, the physiological and physiochemical PBPK model input parameters should reflect the organism in question for such variables as species, strain/stock, gender, age, nutritional status, and disease status. This holds true when the model is being used to simulate experimental data, where the input parameter values should reflect the animal in which the experimental data were gathered. It holds equally when the model is not being compared to experimental data but is being used to extrapolate to situations where experimental data are not available. To the extent possible based on the technical capabilities of our laboratories, we have measured the physiological and physiochemical input parameters needed to develop a PBPK model for TCE with specificity for the overtly disease-free, male LE rat provided ad libitum, nutritionally adequate feed and water. A notable limitation was the lack of cardiac output and organ blood-flow data in awake, nonrestrained LE rats. In the absence of LE-specific blood-flow data, the experimental data were modeled twice, once with F344 blood flow data and then again with SD blood flow data. For the data generated in the present study, better fits to the experimental data were obtained when F344 flows were used in combination with the LE-specific input parameters. This conclusion is based on the numerical value of the combined index of model fit (Table 4). Thus, until LE-specific blood flows are available, use of F344 flows are recommended.
Given the large number of PBPK models that exist for TCE, it is reasonable to ask if development of yet another TCE model, in this case for a specific rodent stock, was needed. One way to address this question is to select an existing model, use the model to simulate the experimental data and compare the fits of those simulations to the data with the data fits of the simulations generated with the model presented here. Given its broad utility, the TCE model presented by Andersen et al.(1987) was selected for this exercise. A brain compartment was added to the Andersen et al.(1987) model, as it was not included in that model as a separate compartment. The indices of fit of the simulations resulting from use of the Andersen et al.(1987) model are presented in Table 4 for ready comparison with the present model. The discrepancy indices for the Andersen model were greater than either the present model or the preliminary model. The combined index for the Andersen et al. model was
2-fold greater than for the present model with F344 blood flows. In particular, the index of fit for the brain was
3-fold greater for the Andersen et al. model than for the present model. These results demonstrate an improved accuracy by the present model for estimation of TCE concentration in the tissues of LE rats.
Sensitivity analysis allows for a quantitative assessment of the impact of input parameters on the model simulations of TCE tissue concentration. The present results indicate that the influence of PBPK model input parameters on TCE tissue dosimetry varies, as expected, across parameter. Additionally, the impact of parameters on model outcome is dependent on time and the external exposure concentration of TCE. Comparison of the absolute magnitude of the SCs may help guide decisions regarding the usefulness of data collection efforts to further refine/define specific parameters. For example, based on the present results, development of LE specific data on alveolar ventilation would prove more useful than improvements in our knowledge of brain volume, liver volume, or brain blood flow. Interest in the hepatic concentration of TCE at low exposure concentrations would lead to research designed to improve the estimate of Vmax. Interest in tissue concentrations after short periods of exposure would lead to data collection to refine the estimate of the volume of the slowly perfused compartment. Experiments to refine the brain PC would be of greater benefit to an improved estimate of the concentration of TCE in the brain than would experiments to improve our understanding of brain blood flow, which would provide little benefit.
The model presented here differs from an earlier, preliminary version of this model (Boyes et al., 2000) in that alveolar ventilation is decreased in the present model. The effort to refine the model within the limits of biological plausibility was prompted primarily by the marked lack of fit of the simulations from the preliminary model to the blood data (from both cannulated and noncannulated rats) and fat data. This can be seen in the preliminary model indices of fit shown in Table 4
. Applying a 20% decrease in ventilation to the present model appears conservative and reasonable, given that Dallas et al.(1991) noted a 20% decrease in ventilation in SD rats between 50 and 500 ppm TCE and the TCE exposures in the present study ranged from 100 to 4000 ppm TCE. An alternative approach was adopted by Greenberg et al.(1999), when faced with PBPK model predictions that overestimated the concentration of TCE in the blood of male B6C3F1 mice. These authors incorporated a term for fractional uptake of TCE based on analogy to published data on the fractional pulmonary uptake of inhaled ethanol and methanol in rodents.
The present research developed a strain-specific PBPK model for the LE rat. As the LE rat is used in assessment of the neurotoxic potential of environmental chemicals as well as in reproductive/developmental toxicity studies, development of strain-specific input parameters may prove useful in development of refined PBPK models for other toxic chemicals. Relative to other TCE models that have been developed, unique features of the present model include: (1) the addition of the brain compartment; (2) incorporation of strain-specific tissue volumes; (3) use of a more quantitative measure of model fit to guide selection of input parameter values when strain-specific information was not available; (4) analysis of the impact of model input parameters on tissue concentration of TCE across multiple tissues, external exposure concentrations, and times; and (5) use of the model to aid in determination of a measure of internal dose that correlates with several measures of neurotoxicity (Boyes et al., 2000, in preparation).
A preliminary version of the present model has been used to explore the relationship between internal dosimetry and neurological effect (Boyes et al., 2000); in that effort the concentration of TCE in the blood at the time of neurological assessment was shown to correlate with TCE-mediated alterations in signal detection and visual function. Although the concentration of TCE in blood is a useful internal surrogate for the concentration of TCE in brain, linkage of neurological effects to brain TCE is an important step in development of exposure-dose-response models. The model presented in this article, employing LE input parameters to the extent possible and F344 blood flows, was used to explore the relationship between two measures of internal dose of TCE and decrements in visual evoked potentials (VEPs) (Boyes et al., in preparation). The area under the curve (AUC) of TCE brain concentration did not correlate with the effects of TCE on VEPs. In contrast, the momentary concentration of TCE in the brain at the time of VEP assessment appeared to forecast accurately the magnitude of TCE-mediated effects on VEP. The next phase of this exposure-dose-response modeling effort is development of a PBPK model for TCE in weight-maintained rats (Simmons et al., 2002
) and application of the data and knowledge gained from the present effort to other organic solvents.
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ACKNOWLEDGMENTS |
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NOTES |
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1 To whom correspondence should be addressed at MD-74, NHEERL/U.S. EPA, Research Triangle Park, NC 27711. E-mail: simmons.jane{at}epa.gov.
2 Present address: Guilford Pharmaceuticals Inc., Baltimore, MD 21224.
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