@article{Chen_Nicholson00,
	author = {K. C. Chen and C. Nicholson},
	address = {Department of Physiology and Neuroscience, New York University Medical School, 550 First Avenue, New York, NY 10016, USA.},
	title = {Changes in brain cell shape create residual extracellular space volume and explain tortuosity behavior during osmotic challenge},
	month = {Jul},
	volume = {97},
	number = {15},
	abstract = {Diffusion of molecules in brain extracellular space is constrained by two macroscopic parameters, tortuosity factor lambda and volume fraction alpha. Recent studies in brain slices show that when osmolarity is reduced, lambda increases while alpha decreases. In contrast, with increased osmolarity, alpha increases, but lambda attains a plateau. Using homogenization theory and a variety of lattice models, we found that the plateau behavior of lambda can be explained if the shape of brain cells changes nonuniformly during the shrinking or swelling induced by osmotic challenge. The nonuniform cellular shrinkage creates residual extracellular space that temporarily traps diffusing molecules, thus impeding the macroscopic diffusion. The paper also discusses the definition of tortuosity and its independence of the measurement frame of reference.},
	pages = {8306-8311},
	journal = {Proc. Natl. Acad. Sci. USA},
	keywords = {Animal | Brain/cytology | Cell Size | Extracellular Space | Models, Biological | Models, Statistical | Numerical Analysis, Computer-Assisted | Osmosis},
	year = {2000}
}

@article{el-Kareh_etal93,
	address = {Department of Physiology, University of Arizona, Tucson 85724.},
	volume = {64},
	year = {1993},
	pages = {1638-1646},
	number = {5},
	journal = {Biophys. J.},
	abstract = {We present theoretical calculations relating the effective diffusivity of monoclonal antibodies in tissue (Deff) to the actual diffusivity in the interstitium (Dint) and the interstitial volume fraction phi. Measured diffusivity values are effective values, deduced from concentration profiles with the tissue treated as a continuum. By using homogenization theory, the ratio Deff/Dint is calculated for a range of interstitial volume fractions from 10 to 65\%. It is assumed that only diffusion in the interstitial spaces between cells contributes to the effective diffusivity. The geometries considered have cuboidal cells arranged periodically, with uniform gaps between cells. Deff/Dint is found to generally be between (2/3) phi and phi for these geometries. In general, the pathways for diffusion between cells are not straight. The effect of winding pathways on Deff/Dint is examined by varying the arrangement of the cells, and found to be slight. Also, the estimates of Deff/Dint are shown to be insensitive to typical nonuniformities in the widths of gaps between cells. From our calculations and from published experimental measurements of the effective diffusivity of an IgG polyclonal antibody both in water and in tumor tissue, we deduce that the diffusivity of this molecule in the interstitium is one-tenth to one-twentieth its diffusivity in water. We also conclude that exclusion of molecules from cells (an effect independent of molecular weight) contributes as much as interstitial hindrance to the reduction of effective diffusivity, for small interstitial volume fractions (around 20\%). This suggests that the increase in the rate of delivery to tissues resulting from the use of smaller molecular-weight molecules (such as antibody fragments or bifunctional antibodies) may be less than expected.},
	title = {Effect of cell arrangement and interstitial volume fraction on the diffusivity of monoclonal antibodies in tissue},
	author = {A. W. el-Kareh and S. L. Braunstein and T. W. Secomb},
	month = {May},
	keywords = {Animal | Antibodies, Monoclonal/metabolism/therapeutic use | Biophysics | Cell Size | Diffusion | Extracellular Space/metabolism | Human | Models, Biological | Neoplasms/metabolism/pathology/therapy | Tissue Distribution}
}

@book{Callaghan91,
	edition = {First},
	publisher = {Clarendon Press},
	year = {1991},
	address = {Oxford},
	title = {Principles of Nuclear Magnetic Resonance Microscopy},
	author = {P. T. Callaghan}
}

@incollection{Stiles_Bartol01,
	publisher = {CRC Press},
	editor = {E. De Schutter},
	pages = {87-127},
	address = {Boca Raton},
	year = {2001},
	author = {J. R. Stiles and T. M. Bartol},
	booktitle = {Computational Neuroscience: Realistic Modeling for Experimentalists},
	title = {Monte {C}arlo methods for simulating realistic synaptic microphysiology using {MC}ell}
}

@incollection{Stiles_etal04,
	year = {2004},
	address = {Amsterdam},
	editor = {G. Joubert},
	pages = {In press},
	title = {Spatially realistic computational physiology: Past, present, and future},
	booktitle = {Parallel Computing: Software Technology, Algorithms, Architectures and Applications},
	author = {J. R. Stiles and W. C. Ford and J. M. Pattillo and T. E. Deerinck and M. H. Ellisman and T. M. Bartol and T. J. Sejnowski},
	publisher = {Elsevier}
}

@inproceedings{Tao_etal02,
	title = {Effect of brain extracellular space geometry on molecular diffusion revealed by {M}onte {C}arlo simulation},
	address = {Washington, DC},
	publisher = {Society for Neuroscience},
	year = {2002},
	author = {L. Tao and S. Hrabetova and C. Nicholson},
	pages = {763.1},
	note = {Online},
	booktitle = {Abstract Viewer/Itinerary Planner}
}