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Unified model of brain tissue microstructure dynamically binds diffusion and osmosis with extracellular space geometry

Yousefnezhad, M ; Sharif University of Technology | 2016

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  1. Type of Document: Article
  2. DOI: 10.1103/PhysRevE.94.032411
  3. Publisher: American Physical Society , 2016
  4. Abstract:
  5. We present a universal model of brain tissue microstructure that dynamically links osmosis and diffusion with geometrical parameters of brain extracellular space (ECS). Our model robustly describes and predicts the nonlinear time dependency of tortuosity (λ=D/D∗) changes with very high precision in various media with uniform and nonuniform osmolarity distribution, as demonstrated by previously published experimental data (D = free diffusion coefficient, D∗ = effective diffusion coefficient). To construct this model, we first developed a multiscale technique for computationally effective modeling of osmolarity in the brain tissue. Osmolarity differences across cell membranes lead to changes in the ECS dynamics. The evolution of the underlying dynamics is then captured by a level set method. Subsequently, using a homogenization technique, we derived a coarse-grained model with parameters that are explicitly related to the geometry of cells and their associated ECS. Our modeling results in very accurate analytical approximation of tortuosity based on time, space, osmolarity differences across cell membranes, and water permeability of cell membranes. Our model provides a unique platform for studying ECS dynamics not only in physiologic conditions such as sleep-wake cycles and aging but also in pathologic conditions such as stroke, seizure, and neoplasia, as well as in predictive pharmacokinetic modeling such as predicting medication biodistribution and efficacy and novel biomolecule development and testing. © 2016 American Physical Society
  6. Keywords:
  7. Body fluids ; Brain ; Cells ; Diffusion ; Dynamics ; Geometry ; Homogenization method ; Microstructure ; Numerical methods ; Osmosis ; Tissue ; Analytical approximation ; Coarse grained models ; Development and testing ; Effective diffusion coefficients ; Homogenization techniques ; Pathologic conditions ; Pharmacokinetic model ; Physiologic conditions ; Cytology
  8. Source: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics ; Volume 94, Issue 3 , 2016 ; 15393755 (ISSN)
  9. URL: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.94.032411