@article{breen_villeneuve_ankley_bencic_breen_watanabe_lloyd_conolly_2013, title={Developing Predictive Approaches to Characterize Adaptive Responses of the Reproductive Endocrine Axis to Aromatase Inhibition: II. Computational Modeling}, volume={133}, ISSN={["1096-0929"]}, DOI={10.1093/toxsci/kft067}, abstractNote={Endocrine-disrupting chemicals can affect reproduction and development in humans and wildlife. We developed a computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course (DRTC) behaviors for endocrine effects of the aromatase inhibitor, fadrozole (FAD). The model describes adaptive responses to endocrine stress involving regulated secretion of a generic gonadotropin (LH/FSH) from the hypothalamic-pituitary complex. For model development, we used plasma 17β-estradiol (E2) concentrations and ovarian cytochrome P450 (CYP) 19A aromatase mRNA data from two time-course experiments, each of which included both an exposure and a depuration phase, and plasma E2 data from a third 4-day study. Model parameters were estimated using E2 concentrations for 0, 0.5, and 3 µg/l FAD exposure concentrations, and good fits to these data were obtained. The model accurately predicted CYP19A mRNA fold changes for controls and three FAD doses (0, 0.5, and 3 µg/l) and plasma E2 dose response from the 4-day study. Comparing the model-predicted DRTC with experimental data provided insight into how the feedback control mechanisms in the HPG axis mediate these changes: specifically, adaptive changes in plasma E2 levels occurring during exposure and "overshoot" occurring postexposure. This study demonstrates the value of mechanistic modeling to examine and predict dynamic behaviors in perturbed systems. As this work progresses, we will obtain a refined understanding of how adaptive responses within the vertebrate HPG axis affect DRTC behaviors for aromatase inhibitors and other types of endocrine-active chemicals and apply that knowledge in support of risk assessments.}, number={2}, journal={TOXICOLOGICAL SCIENCES}, author={Breen, Miyuki and Villeneuve, Daniel L. and Ankley, Gerald T. and Bencic, David C. and Breen, Michael S. and Watanabe, Karen H. and Lloyd, Alun L. and Conolly, Rory B.}, year={2013}, month={Jun}, pages={234–247} }
 @article{villeneuve_breen_bencic_cavallin_jensen_makynen_thomas_wehmas_conolly_ankley_2013, title={Developing predictive approaches to characterize adaptive responses of the reproductive endocrine axis to Aromatase inhibition: I. Data generation in a small fish model}, volume={133}, number={2}, journal={Toxicological Sciences}, author={Villeneuve, D. L. and Breen, M. and Bencic, D. C. and Cavallin, J. E. and Jensen, K. M. and Makynen, E. A. and Thomas, L. M. and Wehmas, L. C. and Conolly, R. B. and Ankley, G. T.}, year={2013}, pages={225–233} }
 @article{breen_breen_terasaki_yamazaki_lloyd_conolly_2011, title={Mechanistic Computational Model of Steroidogenesis in H295R Cells: Role of Oxysterols and Cell Proliferation to Improve Predictability of Biochemical Response to Endocrine Active Chemical-Metyrapone}, volume={123}, ISSN={["1096-6080"]}, DOI={10.1093/toxsci/kfr167}, abstractNote={The human adrenocortical carcinoma cell line H295R is being used as an in vitro steroidogenesis screening assay to assess the impact of endocrine active chemicals (EACs) capable of altering steroid biosynthesis. To enhance the interpretation and quantitative application of measurement data in risk assessments, we are developing a mechanistic computational model of adrenal steroidogenesis in H295R cells to predict the synthesis of steroids from cholesterol (CHOL) and their biochemical response to EACs. We previously developed a deterministic model that describes the biosynthetic pathways for the conversion of CHOL to steroids and the kinetics for enzyme inhibition by the EAC, metyrapone (MET). In this study, we extended our dynamic model by (1) including a cell proliferation model supported by additional experiments and (2) adding a pathway for the biosynthesis of oxysterols (OXY), which are endogenous products of CHOL not linked to steroidogenesis. The cell proliferation model predictions closely matched the time-course measurements of the number of viable H295R cells. The extended steroidogenesis model estimates closely correspond to the measured time-course concentrations of CHOL and 14 adrenal steroids both in the cells and in the medium and the calculated time-course concentrations of OXY from control and MET-exposed cells. Our study demonstrates the improvement of the extended, more biologically realistic model to predict CHOL and steroid concentrations in H295R cells and medium and their dynamic biochemical response to the EAC, MET. This mechanistic modeling capability could help define mechanisms of action for poorly characterized chemicals for predictive risk assessments.}, number={1}, journal={TOXICOLOGICAL SCIENCES}, author={Breen, Miyuki and Breen, Michael S. and Terasaki, Natsuko and Yamazaki, Makoto and Lloyd, Alun L. and Conolly, Rory B.}, year={2011}, month={Sep}, pages={80–93} }
 @inproceedings{nichols_breen_denver_distefano_edwards_hoke_volz_zhang_2011, title={Predicting chemical impacts on vertebrate endocrine systems}, volume={30}, number={1}, booktitle={Environmental Toxicology and Chemistry}, author={Nichols, J. W. and Breen, M. and Denver, R. J. and Distefano, J. J. and Edwards, J. S. and Hoke, R. A. and Volz, D. C. and Zhang, X. W.}, year={2011}, pages={39–51} }
 @article{breen_breen_terasaki_yamazaki_conolly_2010, title={Computational model of steroidogenesis in humanH295R cells to predict biochemical response to endocrine-active chemicals: Model development for metyrapone}, volume={118}, number={2}, journal={Environmental Health Perspectives}, author={Breen, M. S. and Breen, M. and Terasaki, N. and Yamazaki, M. and Conolly, R. B.}, year={2010}, pages={265–272} }
 @article{breen_breen_williams_schultz_2010, title={Predicting Residential Air Exchange Rates from Questionnaires and Meteorology: Model Evaluation in Central North Carolina}, volume={44}, ISSN={["0013-936X"]}, DOI={10.1021/es101800k}, abstractNote={A critical aspect of air pollution exposure models is the estimation of the air exchange rate (AER) of individual homes, where people spend most of their time. The AER, which is the airflow into and out of a building, is a primary mechanism for entry of outdoor air pollutants and removal of indoor source emissions. The mechanistic Lawrence Berkeley Laboratory (LBL) AER model was linked to a leakage area model to predict AER from questionnaires and meteorology. The LBL model was also extended to include natural ventilation (LBLX). Using literature-reported parameter values, AER predictions from LBL and LBLX models were compared to data from 642 daily AER measurements across 31 detached homes in central North Carolina, with corresponding questionnaires and meteorological observations. Data was collected on seven consecutive days during each of four consecutive seasons. For the individual model-predicted and measured AER, the median absolute difference was 43% (0.17 h−1) and 40% (0.17 h−1) for the LBL and LBLX models, respectively. Additionally, a literature-reported empirical scale factor (SF) AER model was evaluated, which showed a median absolute difference of 50% (0.25 h−1). The capability of the LBL, LBLX, and SF models could help reduce the AER uncertainty in air pollution exposure models used to develop exposure metrics for health studies.}, number={24}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Breen, Michael S. and Breen, Miyuki and Williams, Ronald W. and Schultz, Bradley D.}, year={2010}, month={Dec}, pages={9349–9356} }
 @article{breen_breen_butts_chen_saidel_wilson_2007, title={MRI-guided thermal ablation therapy: Model and parameter estimates to predict cell death from MR thermometry images}, volume={35}, ISSN={["1573-9686"]}, DOI={10.1007/s10439-007-9300-3}, abstractNote={Solid tumors and other pathologies can be treated using laser thermal ablation under interventional magnetic resonance imaging (iMRI) guidance. A model was developed to predict cell death from magnetic resonance (MR) thermometry measurements based on the temperature-time history, and validated using in vivo rabbit brain data. To align post-ablation T2-weighted spin-echo MR lesion images to gradient-echo MR images, from which temperature is derived, a registration method was used that aligned fiducials placed near the thermal lesion. The outer boundary of the hyperintense rim in the post-ablation MR lesion image was used as the boundary for cell death, as verified from histology. Model parameters were simultaneously estimated using an iterative optimization algorithm applied to every interesting voxel in 328 images from multiple experiments having various temperature histories. For a necrotic region of 766 voxels across all lesions, the model provided a voxel specificity and sensitivity of 98.1 and 78.5%, respectively. Mislabeled voxels were typically within one voxel from the segmented necrotic boundary with median distances of 0.77 and 0.22 mm for false positives (FP) and false negatives (FN), respectively. As compared to the critical temperature cell death model and the generalized Arrhenius model, our model typically predicted fewer FP and FN. This is good evidence that iMRI temperature maps can be used with our model to predict therapeutic regions in real-time during treatment.}, number={8}, journal={ANNALS OF BIOMEDICAL ENGINEERING}, author={Breen, Michael S. and Breen, Miyuki and Butts, Kim and Chen, Lili and Saidel, Gerald M. and Wilson, David L.}, year={2007}, month={Aug}, pages={1391–1403} }