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Alexander Yelshin

Publications and source records attributed to Alexander Yelshin.

2 recordsLinked to original sources

Changes in diffusion through the brain extracellular space.

ECS (extracellular space) works as the microenvironment of brain cells. Diffusion through ECS may be described through an effective diffusion coefficient, D (e), which in turn depends on ECS porosity, epsilon, and tortuosity, T. In the present research, diffusion data together with epsilon and T were collected from the specialized literature and analysed to seek a correlation of T versus epsilon. On the basis of D (e) data, upper and lower T boundaries were defined and related to topologically 'dense' and 'loose' cell arrangement. A possible range for T variation was obtained for ECS, with epsilon ranging from 0.05 to 0.6. A tortuosity index ( n ) in the form of T and epsilon logarithmic ratio was introduced. This index may be adopted for recalculation of T or epsilon if only one of these parameters is known. As a result of data analysis and modelling, it was concluded that, upon different external conditions, for instance oxygen depletion, the ECS porosity decreases and cells (presumably through membrane rearrangements) adjust the void space to keep the diffusion within a defined range, which gives the living tissue the ability to maintain the diffusion level up to two or more times higher than in conventional granular bed packing. Thus, even with a dramatic ECS decrease, the cellular system is still able to support a given diffusion by decreasing the value of T. The obtained results clearly show the existence of three data clusters: a region of normal brain functioning, both for young and adult brains, for values of epsilon comprised between 0.15 and 0.30, and two regions of abnormal brain behaviour to the left and to the right of the normal region, corresponding to different states (aging, tumours, anoxia, brain death, etc.). The present approach allows defining the optimal range of epsilon and T to assure the best ECS diffusion efficiency for a specified macromolecule. This might be important in brain clinical treatment.

Animals↗

Immobilized particles in gel matrix-type porous media. Nonhomogeneous cell distribution.

The conventional random pore model assumes a homogeneous cell distribution in the gel matrix used to immobilize cells. However, the validity of this model is restricted to values of the exponent alpha, between 1.8 and 2.25, of a model power function relating the diffusivity coefficient in the matrix with the overall cell volume fraction in the system. Based on the analysis of published data for diffusion in gels with immobilized cells and on the homogeneous approach for the random pore model developed in a previous work, a new, nonhomogeneous approach is proposed for alpha values outside the range 1.8-2.25. To explain these data, two main types of nonhomogeneous cell distribution were considered: (1) nonhomogeneous cell distribution in the gel for alpha > 2.25 (type 1) and (2) nonhomogeneity related with anisotropy of cell space orientation when alpha < 1.8 (type 2). In the case of nonhomogeneity of type 1, the cell volume fraction in the layers occupied by cells must be considered in place of the concept previously used for homogeneous distribution, viz., the average cell volume fraction. This model underlines that accumulation of cells in a thin layer close to the surface improves their nutrient intake. For nonhomogeneity of type 2, the tortuosity of such a system is smaller than should be expected if spherical cells were considered, thereby changing the effective diffusion. The model proposed in this work proved to fit into several real cases reported in the literature.

Anisotropy↗