ToxSci Advance Access originally published online on June 4, 2007
Toxicological Sciences 2007 99(1):181-189; doi:10.1093/toxsci/kfm146
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Published by Oxford University Press 2007.
A Dosimetric Analysis of the Acute Behavioral Effects of Inhaled Toluene in Rats
* Neurotoxicology Division
Human Studies Division
Experimental Toxicology Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711
1 To whom correspondence should be addressed. Fax: (919) 541-4849, E-mail: bushnell.philip{at}epa.gov.
Received February 16, 2007; accepted May 25, 2007
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Knowledge of the appropriate metric of dose for a toxic chemical facilitates quantitative extrapolation of toxicity observed in the laboratory to the risk of adverse effects in the human population. Here, we utilize a physiologically based toxicokinetic (PBTK) model for toluene, a common volatile organic compound (VOC), to illustrate that its acute behavioral effects in rats can be quantitatively predicted on the basis of its concentration in the brain. Rats previously trained to perform a visual signal detection task for food reward performed the task while inhaling toluene (0, 1200, 1600, 2000, and 2400 ppm in different test sessions). Accuracy and speed of responding were both decreased by toluene; the magnitude of these effects increased with increasing concentration of the vapor and with increasing duration of exposure. Converting the exposure conditions to brain toluene concentration using the PBTK model yielded a family of overlapping curves for each end point, illustrating that the effects of toluene can be described quantitatively by its internal dose at the time of behavioral assessment. No other dose metric, including inhaled toluene concentration, duration of exposure, the area under the curve of either exposure (ppm h), or modeled brain toluene concentration (mg-h/kg), provided unambiguous predictions of effect. Thus, the acute behavioral effects of toluene (and of other VOCs with a similar mode of action) can be predicted for complex exposure scenarios by simulations that estimate the concentration of the VOC in the brain from the exposure scenario.
Key Words: attention; dose metric; signal detection behavior; toxicokinetics; volatile organic compounds.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Extrapolating results of experimental toxicity studies from the laboratory to the human population is both necessary for risk assessment and fraught with uncertainty. One approach to mitigating the uncertainty involves the use of predictive dose-response models in which the effects in an experimental model (in vivo or in vitro) can be related quantitatively to potential effects in humans. An essential component of these models is the relationship between the applied dose and the target organ dose—that is, the model must account for the kinetic processes that generate an amount of the chemical in an organ sufficient to disrupt the function and/or structure of that organ.
Understanding this relationship requires knowledge of the most appropriate dose metric for the effect of concern. The dose metric for a given effect is the measure of internal dose that best predicts that effect of the chemical. Knowing the dose metric facilitates assessments of dose-response relationships for regulatory purposes and mechanistic studies of the toxicity of the chemicals (Gerrity and Henry, 1990
; Pepelko and Withey, 1985). In addition, if the dose metric is known, then the toxicity of the chemical can be understood as a function of its distribution, metabolism, and elimination, independently of the route of exposure.
For toxicants with reversible effects that are caused by the parent compound, it has been assumed that the appropriate dose metric is the concentration of the chemical in the target organ at the time of measurement. Several lines of evidence support this assumption for volatile organic compounds (VOCs), including (1) results of a meta-analysis which showed a systematic relationship between blood concentrations of toluene and behavior in rats and humans (Benignus et al., 1998); (2) observations that the acute effects of toluene and trichloroethylene (TCE) are dose related at blood concentrations above those that saturate metabolism; and (3) that the metabolites of toluene are either short lived (e.g., benzaldehyde: Cohr and Stockholm, 1979) or have low toxicity (e.g., benzoic acid: Nair, 2001).
Experimental studies of the behavioral effects of toluene have generally supported this assumption. For example, under two different exposure scenarios (4000 ppm for 3 h and 10,600 ppm for 10 min), the degree of narcosis induced by inhaled toluene in mice was closely correlated with each of several metrics of internal dose (Bruckner and Peterson, 1981a,b). In this study, the best correlation was with the concentration of toluene in the brain—both during exposure, when internal doses were rising, and after exposure, when they were falling. Similarly, rates of lever pressing were correlated with concentrations of toluene in the brain in behavioral tests conducted both during exposure (Kishi et al., 1988) and during elimination of toluene after termination of exposure (Miyagawa et al., 1984, 1986).
However, not all studies support this relationship. For example, modeled concentrations of toluene in the brains of rats were not clearly correlated with conditioned behavior in rats tested after a complex 7.5-h exposure with a cumulative exposure of 10,000 or 20,000 ppm h (van Asperen et al., 2003). In a study of inhaled 1,1,1-trichloroethane, both the maximum concentration and the area under the curve (AUC) of concentrations in blood and brain accurately predicted its effects on rats' performance of a variable-interval schedule of reinforcement (Warren et al., 1998). Finally, effects of oral perchloroethylene (PCE) (160 or 480 mg/kg in an aqueous vehicle) on rats performing a fixed-ratio schedule were unrelated to measured internal doses of the compound (Warren et al., 1996).
These studies suggest the possibility that the momentary concentration of toluene in brain may not be the best dose metric for its acute neurobehavioral effects in particular, the Warren et al. (1998) study indicates that the AUC of brain toluene concentration may be as predictive as the brain toluene concentration itself. Here we experimentally compare the degree to which the acute behavioral effects of toluene can be predicted by five dose metrics: the concentration (C) of inhaled toluene; the duration of exposure (t); the area under the exposure curve (AUCAir, or C x t product); the concentration of toluene in the brain of the subject ([TolBr]); and the AUC for the brain toluene concentration in the subject (AUCBr).
The acute behavioral effects of toluene were assessed in rats performing an appetitively motivated test of visual signal detection (Bushnell, 1998; Bushnell et al., 1994, 1997). Internal doses of toluene (concentrations in blood and brain) were estimated using a physiologically based toxicokinetic (PBTK) model (Kenyon et al., in press). The signal detection task (SDT) was chosen because of its demonstrated validity as a test of sustained attention (Burk, 2004; Bushnell, 1999; Bushnell et al., 2003; McGaughy and Sarter, 1995) and its sensitivity to toluene (Bushnell et al., 1994; Oshiro et al., 2007), TCE (Bushnell, 1997), and a number of centrally acting drugs (Bushnell et al., 1997, 2001; Geller et al., 2001; McGaughy and Sarter, 1995; Rezvani and Levin, 2003a,b) and toxicants (Bushnell et al., 2001; Geller et al., 2001).
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Subjects.
Sixteen male Long-Evans rats (Charles River, Portage, ME) were housed individually in suspended plastic cages on heat-treated pine shavings in a housing facility fully accredited by the Association for Assessment and Accreditation of Laboratory Animal Care International (AAALAC). As required by AAALAC, animal care conformed to the guidelines provided by National Institutes of Health. Lighting followed a 12 h:12 h photoperiod with lights turned on at 6 A.M.; all behavioral testing occurred in the light phase of the cycle. Each animal was maintained at 350 ± 10 g body weight by scheduled home cage feeding (Ralston Purina, St Louis, MO) after daily test sessions (Ali et al., 1992
); tap water was available ad libitum in the home cage. Rats were 90 days old on receipt from the supplier and about 4 months old at the start of behavioral training.
Apparatus.
Four 32.9-L operant inhalation chambers were constructed of stainless steel, aluminum, and glass for the assessment of operant performance of rats inhaling solvent vapors (Bushnell, 1997, 1999; Bushnell et al., 1994). As shown in Figure 1, the front wall of each chamber contained two retractable omnidirectional response levers; a food cup with a hinged, clear plastic door, centered between the levers; a houselight; an incandescent signal light; and a 5-cm cone loudspeaker. The house and signal lights were mounted 15 cm above the floor of the chamber; the signal light was centered above the food cup between the houselight and the loudspeaker. Background white noise of 65 dB(A) was generated in each chamber. Access to the chamber was gained by removal of a red-tinted transparent rear panel, so the animals could be observed with minimal intrusion. The four chambers and solvent vapor generator (described below) were located in a quiet room which was darkened during all behavioral tests. The apparatus is illustrated in Figure 1, and the generator is depicted schematically in Figure 2.
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Signals of varying intensity were presented as described previously (Bushnell, 1997
; Oshiro et al., 2004). Each intensity was presented quasi-randomly during each test session. Signals were 300 ms in duration and ranged from 0.09 to 1.66 lux, above a background illumination of 0.11 lux. Signal intensities were calibrated for each chamber with a photometer as described previously (Oshiro et al., 2007). SKED-11 software (State Systems, Kalamazoo, MI) running on PDP11/70 computers (Digital Equipment, Maynard, MA) recorded the vapor concentration data and controlled behavioral testing (see below).
Signal detection task.
All rats were trained to perform the SDT as previously described (Bushnell, 1997, 1999; Bushnell and Rice, 1999). The SDT schedule was programmed as follows: after a variable intertrial interval averaging 7 s (range, 0.3–24.4 s), rats were required to report the occurrence or nonoccurrence of a signal stimulus (a 300-ms light flash) by pressing one of the two response levers. Signal and blank trials were intermixed unpredictably in equal number during each test session and differed only in that no signal occurred during the signal period on a blank trial. Each correct response (a press on the signal lever on a signal trial or a press on the blank lever on a blank trial), caused illumination of the food cup light on every trial and delivery of a food pellet (PJ Noyes Co., Lancaster, NH) on 80% of these trials. After each incorrect response (a press on the signal lever on a blank trial or a press on the blank lever on a signal trial), or after a response failure (no press on either lever during the response hold period), the houselight was turned off for 3 s and no food was delivered. Trials lacking a lever press were not repeated.
The task was conducted in daily 60-min test sessions, each of which was preceded by a 10-min pretest interval during which the toluene vapor concentration rose to its target level. The test session was divided into five 12-min blocks which, at five trials per minute, yielded approximately 300 trials per session. To inhibit somnolence during the 10-min pretest interval, food pellets were made available during three 1-min periods, signaled by illumination of the food cup light, on a progressive ratio schedule of openings of the food cup door. Rats required 74 test sessions to reach criterion performance, defined as P(hit) 
0.80 and P(false alarm) 
0.20 (see below for definitions of these parameters).
Behavioral measures.
The number of "hits" (signal-lever presses on signal trials), "correct rejections" (blank-lever presses on blank trials), "false alarms" (signal-lever presses on blank trials), and "misses" (blank-lever presses on signal trials) were recorded in each time block during each test session. The proportion of correct responses [P(Cor) = (number of hits) + (number of correct rejections)/(total number of responses)] was calculated from the frequencies of each response in each time block. Response time (RT) was measured for each response type as the time between insertion of the levers into the chamber and the time at which a lever press was recorded; these values were averaged across response types. P(Cor) and RT were also averaged across signal intensities for this analysis to focus on the temporal aspects of the effects of toluene rather than effects of signal parameters. Previous work showed that accuracy depends greatly on signal intensity, but RTs are relatively independent of it (Bushnell et al., 1994). In addition, intensity-dependent effects of both toluene (Bushnell et al., 1994) and TCE (Oshiro et al., 2001) have been reported previously.
Statistical analysis of P(Cor) and RT used a mixed model (PROC NLMIXED (SAS, 2002)) to determine the significance of effects of the inhaled concentration of toluene and trial block (time). Both independent variables were treated as random variables and repeated measures. This model was used because toluene increased the probability of response failure, and mixed models accommodate occasional empty cells. Statistical significance was confirmed with a type I error rate of 0.05 for each ANOVA.
Changes in both P(Cor) and RT normally occur during tests in air. In particular, low accuracy in the first trial block (0–12 min) reflects an apparent "warm-up" effect, which also reduces accuracy during the first block of trials during exposure to toluene vapor. This effect is characteristic of baseline behavior under control conditions in this test and complicates interpretation of the effects of acutely acting treatments. To remove the influence of the warm-up effect and other fluctuations in performance under control conditions, each rat's score in each test condition (i.e., in each trial block at each toluene concentration) was adjusted by the amount that it scores in each of the corresponding trial blocks of the air condition differed from its mean score in the air condition. In other words, deviations from the rat's mean score at each time point in air were subtracted from its scores at each time point in each toluene condition. This adjustment makes the reasonable assumption that the variations in behavior observed in air influence behavior equally in toluene vapor. The adjustment yielded constant values for P(Cor) and RT across blocks in air, altered the temporal pattern of effects in the toluene conditions, and preserved the between-subject variance (and SEM) under all conditions.
Given a statistically significant toluene concentration by time interaction, values of P(Cor) measured during toluene exposure that fell below the lower 95% confidence limit of the air control mean were defined as significantly different from the air condition. Similarly, RT values that fell above the upper 95% confidence limit of the mean RT were defined as significant.
Toluene exposure.
Toluene (99.5% spectrophotometric grade, Sigma-Aldrich, St Louis, MO) vapor was generated within each chamber using methods previously described for TCE (Bushnell, 1997; Oshiro et al., 2001). As shown schematically in Figure 2, liquid toluene was dispensed by a syringe pump into a heated stream of zero-grade nitrogen gas, yielding concentrated toluene vapor that was mixed with filtered air. Target concentrations of toluene (0, 1200, 1600, 2000, and 2400 ppm) in each chamber were determined by the rate of delivery of the liquid toluene, which was set for each concentration in each chamber independently. The rise time (t95) of toluene vapor concentrations was 6 min; test sessions began 10 min after the start of exposure. An infrared spectrophotometer (MIRAN 1A, The Foxboro Co., Bridgewater, MA) was used to monitor toluene vapor concentrations sequentially in the four exposure test chambers, yielding two or three samples per chamber per session. The meter was calibrated for toluene vapor at the beginning of the study as previously described (Bushnell et al., 1994; Bushnell, 1997; Oshiro et al., 2007). Concentrations of toluene varied among locations in each chamber by less than 1%. The target vapor concentrations included the nominal concentration ± 10%.
Each rat was always tested and exposed in the same chamber and received each concentration of toluene once. The 16 rats in the study were exposed and tested each day in four cohorts of four rats each. The order of exposure conditions was counterbalanced across cohorts, so that four of the five exposure conditions were delivered to the four rats in each cohort each day. Five exposure days were needed to complete the 80 exposures necessary to complete the design.
Estimating internal doses.
A PBTK model (Kenyon et al., in press) was used to estimate the concentration of toluene in the brain [TolBr] during each trial block (12-min period) of each toluene exposure session and the cumulative amount of toluene in the brain across the duration of exposure (AUCBr). The model parameters used for the simulations were derived from published data (Brown et al., 1997; DeJongh and Blaauboer, 1996; Tardif et al., 2002; Thrall et al., 2002) with adjustment as necessary for the physically active, weight-maintained Long-Evans rats used here. [TolBr] and AUCBr were computed at the median time point of each trial block.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Exposure
Mean (± SD) concentrations of toluene in the inhaled air are shown in Table 1. Data from one rat were eliminated from analysis of the 1600- and 2400-ppm conditions due to inadequate exposure. Of the 158 other measurements of toluene concentrations taken, one value exceeded the nominal value by more than 10% and seven values fell more than 10% below their nominal values.
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Behavior
Response failure in the last trial block at 2400 ppm toluene by one rat caused elimination of one accuracy value from the data set. P(Cor) decreased with increasing concentration and duration of inhaled toluene (Fig. 3A). The effects of concentration [F(4,58) = 20.2, p < 0.001)] and time [F(4,60) = 8.9, p < 0.001)] were both significant, as was the concentration by time interaction [F(16,232) = 1.79, p < 0.04)]. RT increased with increasing concentration and duration of inhaled toluene (Fig. 3C). The effects of concentration [F(4,58) = 31.4, p < 0.001)], time [F(4,60) = 34.6, p < 0.001)] and the concentration by time interaction [F(16,232) = 6.87, p < 0.001)] were all significant.
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As expected, P(Cor) increased from trial block 1 (0–12 min) to trial block 2 (13–24 min) when the animals were tested in clean air (Fig. 3A) and varied slightly across the remaining trial blocks. RT was less variable (Fig. 3C) but was higher in block 1 than in block 2. Adjusting the values to yield a constant score across blocks in the air condition slightly altered pattern of effects in the toluene conditions (Figs. 3B and 3D). The 95% confidence limits below the mean air P(Cor) value and above the mean air RT value are shown as horizontal lines in Figures 3B and 3D and in Figure 4. Values from toluene exposures that fell below the line for P(Cor) or above the line for RT were deemed to differ significantly from the air condition.
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The adjusted behavioral data are plotted in Figure 4A for P(Cor) and Figure 4D for RT as a function of AUCAir (i.e., the C x t product of exposure). In these plots, all control values are zero, and points connected by a common line represent consecutive measurements at a given exposure concentration. These plots show that AUCAir provides a better prediction of the magnitude of the effect on behavior than does either C or t of exposure alone.
Simulations of the kinetics of inhaled toluene yielded estimates of the concentration of toluene in the brain ([TolBr]) at each inhaled concentration and duration of exposure and of the AUC of [TolBr] at each time point, AUCBr. Replotting the adjusted P(Cor) and RT data as a function of [TolBr] yielded relationships in Figures 4B and 4E. Plotting the behavioral results as a function of AUCBr yielded the relationships in Figures 4C and 4F, which resemble those for AUCAir.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The major finding of this experiment is that the acute behavioral effects of toluene on signal detection behavior can be determined unambiguously from the estimated concentration of toluene in the brain of the animal at the time the behavior is assessed. Previous work demonstrated that these behavioral changes reflect deficits in sustained attention in both rats (Bushnell, 1997
, 1998, 1999; Bushnell et al., 1994, 1997) and humans (Bushnell et al., 2003). Combined with recent findings from this laboratory (Oshiro et al., 2007), this work also extends previous observations of behavioral effects of toluene in animals to include impairment of a visually based cognitive function necessary for adequate performance of many occupations and personal activities.
The data also show that these effects are clearly a function of the concentration and duration of exposure, both of which increase the concentration of toluene in the brain. In terms of exposure, knowledge of both concentration and duration are necessary to determine the effects on behavior (Figs. 1A and 1C). Univariate predictors of the behavioral effects (AUCAir, [TolBr], and AUCBr) derived from these relationships show that only [TolBr] is unambiguously related to these acute effects of toluene. Thus, the most appropriate dose metric for the acute behavioral effects of inhaled toluene is the concentration of the compound in the brain at the time the effect is measured. Because a constant ratio of brain and blood toluene concentration has been consistently observed in adult animals (Ameno et al., 1992; Benignus et al., 1981, 1984; Pyykko et al., 1977), predictions of these effects based on blood toluene concentration would be equally certain, with only the tissue concentration differing. In the present studies, the brain:blood ratio of toluene concentrations was approximately 2.4:1 (Kenyon et al., in press).
This study supports and extends most previous work relating internal doses of VOCs to their effects on behavior (Bruckner and Peterson, 1981a,b; Kishi et al., 1988; Miyagawa et al., 1984, 1986). Similar studies of 1,1,1-trichloroethane (TCA) in mice (You et al., 1994) and in rats (Warren et al., 1998) also demonstrate strong relationships between internal dose and operant behavior as assessed by variable-interval schedules of reinforcement. In the rat study (Warren et al., 1998), response rate ratios (exposed per air), averaged across the test session, decreased with increasing concentration of TCA in both brain and in blood and were linearly related to both the maximum observed internal dose (Cmax, in brain or blood) and to the AUC of tissue TCA concentration across the duration of the exposure session (AUC). These two dose metrics accounted for the effects equally well in that study because the effect was averaged across the exposure period. The present study demonstrates that the estimated AUCBr does not predict effects of ongoing behavior unambiguously but the estimated [TolBr] does.
On the other hand, complex inhalation exposure scenarios with high concentrations of VOCs may produce effects that are less tightly associated with the concurrent concentration in the brain. For example, the behavioral effects of inhaled toluene were greater after termination of a 7.5-h exposure at a constant concentration than they were after a series of episodic exposures with the same AUCair, and the effects did not correlate with estimated brain toluene concentration (van Asperen et al., 2003). Also, inhaled toluene at 4000 ppm caused a greater effect on visual evoked potentials during exposure than after exposure, across an overlapping range of [TolBr], whereas at 3000 ppm, there was no difference in effect at equivalent estimated [TolBr] during or after exposure (Boyes et al., unpublished data). These effects suggest that toluene may induce acute functional tolerance, a phenomenon well documented for ethanol and some barbiturates (Erwin et al., 2000; LeBlanc et al., 1974; Mellanby, 1919; Tabakoff et al., 1986) but not for inhaled solvents.
Rats can also develop a long-term tolerance to the acute effects of inhaled toluene (Oshiro et al., 2007) and TCE (Bushnell and Oshiro, 2000; Oshiro et al., 2001) if they are trained to do so. This tolerance was acquired over three consecutive days of SDT testing in the presence of 1600 ppm toluene; in tolerant rats, toluene no longer decreased accuracy but continued to increase RTs (Oshiro et al., 2007). Tolerance to TCE developed with a similar amount of training and was more pronounced for accuracy than RT (Bushnell and Oshiro, 2000; Oshiro et al., 2001). Because the design of the TCE studies strongly suggested that this tolerance does not involve increased metabolism of the compound, the relationship between internal dose and acute effects in tolerant animals is likely to be different from the relationship in naive animals.
Whereas it has not been well studied, the relationship between internal doses and acute effects of orally administered VOCs is less clear than for inhaled VOCs. For example, responding by rats trained on a fixed-ratio operant schedule for milk reinforcers was not related to the concentration of PCE in blood or brain when the compound was given by gavage immediately prior to testing (Warren et al., 1996). Apparently other factors, including perhaps introduction of a large bolus of solvent into the stomach or the detergent vehicle used (alkamuls), played a role in the variable behavioral patterns that followed dosing in that study. A similar lack of correspondence between toluene administered orally in corn oil and effects on signal detection has also been observed (Bushnell et al., 2005a; Samsam et al., 2005).
A PBTK model facilitates predicting internal doses of a toxicant under varied exposure scenarios. The kinetics of metabolites of a toxicant can also be modeled by including appropriate pathways and parameters, but these properties were not necessary for describing the acute neurotoxicity of toluene. Whereas all PBTK models involve assumptions and approximations (Clewell et al., 2002; Kenyon et al., in press), they do yield quantitatively comparable estimates of internal dose for a range of exposure concentrations and times within a study or among a set of studies that meet those assumptions. The model used for this analysis was parameterized for the subjects that provided the behavioral data: weight-maintained male Long-Evans rats working at activity levels comparable to those necessary to perform the behavioral task (Kenyon et al., in press). This specificity increases the accuracy of the estimates of internal dose.
The concentrations at which toluene disrupts neuronal ion channel function in vitro range from a low of about 0.1µM in voltage-sensitive calcium channels (Shafer et al., 2005) to a high of about 10,000µM in N-methyl-D-aspartate receptors expressed in Xenopus oocytes (Bale et al., 2005b). Effective [TolBr] in the present experiment ranged from about 20 to 120 mg/l or 220 to 1300µM. Thus, the behavioral effects in the present study were associated with brain toluene concentrations in the range over which toluene-induced changes in ion flux through neuronal ion channels have been measured. The curves in Figures 4B and 4E suggest that concentrations lower than this range would not be effective, and observations of the rats indicated that concentrations above this range inhibit responding altogether. The exposures thus spanned the range of internal doses useful for quantifying these effects of toluene.
The effects of toluene on this task confirm most aspects of our earlier observations that toluene disrupts both visual (Oshiro et al., 2007) and auditory signal detection in rats (Bushnell et al., 1994); they also extend observations of similar effects with TCE (Bushnell, 1997; Bushnell and Oshiro, 2000; Oshiro et al., 2001). The fact that both auditory and visual signal detection are disrupted by toluene suggests that the deficits in performance are unlikely to have a sensory origin. The lack of a sensory threshold shift due to solvent exposure in any of these studies and the observation that P(fa) increases with exposure (Bushnell and Oshiro, 2000) support that suggestion. The generality of these findings across solvents suggests that these compounds exert a common suite of effects and support findings in vitro that the compounds act via similar actions on neuronal ion channels (e.g. Bale et al., 2002, 2005a,b; Bushnell et al., 2005b; Cruz et al., 1998, 2000; Shafer et al., 2005).
On the other hand, it must be noted that whereas the decrease in P(Cor) observed here involved both decreased P(hit) and increased P(fa), most of the change was due to a decrease in P(hit). A subsequent study of toluene revealed a very similar dose-response relationship for accuracy, but in that case, the major contribution was an increase in P(fa) (Bushnell). The reasons for this difference in response pattern are not immediately obvious but contrast somewhat with the effects of TCE, which were typically more consistently symmetric: that is, TCE both reduced P(hit) and increased P(fa) in most animals (Bushnell, 1997; Bushnell and Oshiro, 2000).
In summary, inhaled toluene vapor impaired visual signal detection in rats by reducing accuracy and increasing RT. These effects depended on both the concentration of the vapor and the duration of exposure. Converting the exposures to estimated concentrations of toluene in the brain at the time of behavioral assessment by means of a PBTK model yielded a dose metric that unambiguously predicted the magnitude of the effects, whereas metrics based on the AUC of exposure or on the AUC of brain toluene concentration did not.
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NOTES |
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Disclaimer: This manuscript has been reviewed by the National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency and approved for publication. Approval does not signify that the contents necessarily reflect the policies of the Agency nor does mention of trade names or commercial products constitute endorsement or recommendation for use.
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ACKNOWLEDGMENTS |
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We thank Drs W.K. Boyes, T.J. Shafer, and S.E. Bowen for reviews of an early draft of this paper; K. Rigsbee for dedicated animal care; C.W. Hamm, E.B. Bailey, and Q.T. Krantz for expert technical support; and J.M. Havel for the illustrations of the apparatus.
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