Developing an exposure–dose–response model for the acute neurotoxicity of organic solvents: overview and progress on in vitro models and dosimetry
2005
Abstract We are developing an exposure–dose–response (EDR) model for volatile organic compounds (VOCs) to predict acute effects of VOCs on nervous system function from exposure data (concentration and duration of inhalation). This model contains both toxicokinetic and toxicodynamic components. One advantage of the EDR model will be its ability to relate in vitro effects of solvents on cellular ion channels (putative targets) to in vivo effects, using a combination of physiologically-based toxicokinetic (PBTK) modeling (to estimate VOC concentrations in the blood and brain) and in vitro studies to clarify the mode of action of the VOCs. Recent work in vitro has focused on quantifying the inhibitory effects of toluene, trichloroethylene (TCE) and perchloroethylene (PERC) on ion channel currents. All three VOCs inhibit current through voltage-sensitive calcium channels (VSCCs) in pheochromocytoma cells; PERC blocked calcium currents and altered the current–voltage relationship at lower concentrations than did toluene or TCE. Recombinant nicotinic acetylcholine receptors (nAChRs), expressed in Xenopus oocytes, were also inhibited by PERC and toluene in a concentration-dependent manner. PERC inhibited α7 receptors more than α4β2 receptors in recombinant human and rat nAChRs. However, human and rat α7 receptors were equally sensitive to PERC and TOL. These in vitro studies will be used to identify an appropriate neuronal receptor system to serve as an index of acute effects of VOCs in vivo. The PBTK model incorporates physiological input parameters derived from radiotelemetered heart rate data from rats performing operant tests of cognitive and motor functions. These studies should improve predictions of target organ concentrations of inhaled VOCs in subjects actively performing behavioral tests over a range of physical activity levels.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
78
References
39
Citations
NaN
KQI