This proposal is for the 12th through 16th years of the Simulation Resource Facility for Circulatory Mass Transport and Exchange at the University of Washington. Investigators from Michigan State University, University of Wisconsin, University of Southern California, Yale University, McGill, Mayo Clinic, the Netherlands, and the University of Washington collaborate in the development of computer models and/or the analysis of data from experimental studies. The modeling analysis efforts of about 20 investigators are focused on the kinetics of blood-tissue exchanges in well-perfused organs such as the normal heart, lung, and brain, and on approaches to assessment of both physiologic and pathophysiologic states such as ischemia, injury, and abnormalities of function and metabolism. Particular emphasis is on the development and application of methods of interpreting data from positron emission tomography (PET) and from multiple tracer indicator dilution studies. The proposed program has three sections. Section I concerns the development of analysis techniques for investigator-managed simulation analysis tools such as XSIM, a graphical simulation interface that runs under X-windows, NetSim, a simulation interface that uses the network to distribute the processing of models that exhibit coarse-grained parallelism, improved optimization software for the simultaneous fitting of large data sets, and new numerical approaches to the solution of convection-diffusion-reaction equations. Section II focuses on the development of models for mass transport and exchange. It has four sections: biochemical reactions in intact cells, non-linear membrane transport models, capillary-tissue exchange models, and fractal vascular networks & flow distributions. Section III contains 10 projects for which no funding is requested. These projects exemplify the application of the technology developed in the Resource to the analysis of experimental and clinical data. Included are projects on metabolic imaging of tumors and of regional cardiopulmonary metabolism and flows, heterogeneity of lung ventilation and perfusion, the metabolism of adenosine, amino acids, and fatty adds in the heart, oxygen consumption in the heart, and heterogeneity of myocardial perfusion. The projects are supported by four Cores: computational facility, software development and maintenance, dissemination and training, and administration. The approaches to simulation analysis and the software technology being developed by the Resource are having impact in physiologic and radiological disciplines.
| Bassingthwaighte, James B; Butterworth, Erik; Jardine, Bartholomew et al. (2012) Compartmental modeling in the analysis of biological systems. Methods Mol Biol 929:391-438 |
| Dash, Ranjan K; Bassingthwaighte, James B (2010) Erratum to: Blood HbO2 and HbCO2 dissociation curves at varied O2, CO2, pH, 2,3-DPG and temperature levels. Ann Biomed Eng 38:1683-701 |
| Bassingthwaighte, James B; Raymond, Gary M; Butterworth, Erik et al. (2010) Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs. Ann N Y Acad Sci 1188:111-20 |
| Dash, Ranjan K; Bassingthwaighte, James B (2006) Simultaneous blood-tissue exchange of oxygen, carbon dioxide, bicarbonate, and hydrogen ion. Ann Biomed Eng 34:1129-48 |
| Dash, Ranjan K; Bassingthwaighte, James B (2004) Blood HbO2 and HbCO2 dissociation curves at varied O2, CO2, pH, 2,3-DPG and temperature levels. Ann Biomed Eng 32:1676-93 |
| Kellen, Michael R; Bassingthwaighte, James B (2003) Transient transcapillary exchange of water driven by osmotic forces in the heart. Am J Physiol Heart Circ Physiol 285:H1317-31 |
| Kellen, Michael R; Bassingthwaighte, James B (2003) An integrative model of coupled water and solute exchange in the heart. Am J Physiol Heart Circ Physiol 285:H1303-16 |
| Wang, C Y; Bassingthwaighte, J B (2001) Capillary supply regions. Math Biosci 173:103-14 |
| Swanson, K R; True, L D; Lin, D W et al. (2001) A quantitative model for the dynamics of serum prostate-specific antigen as a marker for cancerous growth: an explanation for a medical anomaly. Am J Pathol 158:2195-9 |
| Swanson, K R; Alvord Jr, E C; Murray, J D (2000) A quantitative model for differential motility of gliomas in grey and white matter. Cell Prolif 33:317-29 |
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