@article{yokley_tran_schlosser_2008, title={Sensory irritation response in rats: Modeling, analysis and validation}, volume={70}, ISSN={["0092-8240"]}, DOI={10.1007/s11538-007-9268-z}, abstractNote={Inhaled gases can cause respiratory depression by irritating (stimulating) nerves in the nasal cavity. Respiratory depression, in turn, decreases the rate of delivery of those gases to the stimulated nerves, potentially leading to a complex feedback response. In order to better understand how the nervous system responds to such chemicals, a mathematical model is created to describe how the presence of irritants affects respiration in the rat. The ordinary differential equation model describes the dosimetry of these reactive gases in the respiratory tract, with particular focus on the physiology of the upper respiratory tract, and on the neurological control of respiration rate due to signaling from the irritant-responsive nerves in the nasal cavity. The ventilation equation is altered to account for an apparent change in dynamics between the initial ventilation decrease and the recovery to steady state as seen in formaldehyde exposure data. Further, the model is evaluated and improved through optimization of particular parameters to describe formaldehyde-induced respiratory response data and through sensitivity analysis. The model predicts the formaldehyde data well, and hence the model is thought to be a reasonable description of the physiological system of sensory irritation. The model is also expected to translate well to other irritants.}, number={2}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Yokley, Karen A. and Tran, Hien and Schlosser, Paul M.}, year={2008}, month={Feb}, pages={555–588} }
 @article{yokley_tran_pekari_rappaport_riihimaki_rothman_waidyanatha_schlosser_2006, title={Physiologically-based pharmacokinetic modeling of benzene in humans: A Bayesian approach}, volume={26}, ISSN={["0272-4332"]}, DOI={10.1111/j.1539-6924.2006.00789.x}, abstractNote={Benzene is myelotoxic and leukemogenic in humans exposed at high doses (>1 ppm, more definitely above 10 ppm) for extended periods. However, leukemia risks at lower exposures are uncertain. Benzene occurs widely in the work environment and also indoor air, but mostly below 1 ppm, so assessing the leukemia risks at these low concentrations is important. Here, we describe a human physiologically‐based pharmacokinetic (PBPK) model that quantifies tissue doses of benzene and its key metabolites, benzene oxide, phenol, and hydroquinone after inhalation and oral exposures. The model was integrated into a statistical framework that acknowledges sources of variation due to inherent intra‐ and interindividual variation, measurement error, and other data collection issues. A primary contribution of this work is the estimation of population distributions of key PBPK model parameters. We hypothesized that observed interindividual variability in the dosimetry of benzene and its metabolites resulted primarily from known or estimated variability in key metabolic parameters and that a statistical PBPK model that explicitly included variability in only those metabolic parameters would sufficiently describe the observed variability. We then identified parameter distributions for the PBPK model to characterize observed variability through the use of Markov chain Monte Carlo analysis applied to two data sets. The identified parameter distributions described most of the observed variability, but variability in physiological parameters such as organ weights may also be helpful to faithfully predict the observed human‐population variability in benzene dosimetry.}, number={4}, journal={RISK ANALYSIS}, author={Yokley, Karen and Tran, Hien T. and Pekari, Kaija and Rappaport, Stephen and Riihimaki, Vesa and Rothman, Nat and Waidyanatha, Suramya and Schlosser, Paul M.}, year={2006}, month={Aug}, pages={925–943} }