Abstract
Multiple sets of experimental data have shown that the red blood cell (RBC) consumes nitric oxide (NO) about 600–1000-fold slower than the equivalent concentration of cell-free hemoglobin (Hb). Diffusion barriers of various sources have been suggested to explain this observation. In this work, a multicellular, spatially distributed, two-dimensional model, that describes the production, transport, and consumption of NO in blood vessels and the surrounding tissue, is developed. The model is used to assess the relative significance of NO transport barriers that reduce the rate of NO consumption in the blood. Unlike previous models of this system, the model developed here accounts explicitly for the presence of, and interactions among, a population of RBCs inside the lumen of the blood vessel and is, therefore, better suited to analyze, quantitatively, the contribution of each transport barrier as NO diffuses from its site of synthesis to the interior of the RBCs where it interacts with Hb. The model, which uses experimentally derived parameters, shows that extracellular unstirred boundary layer diffusion alone cannot account for the reduced NO consumption by RBC compared to an equivalent concentration of cell-free Hb. Since this result is reached using a two-dimensional representation of the RBCs, which overestimates the importance of the boundary layer diffusion resistance, it would be expected that in the real three-dimensional case, diffusion through the extracellular boundary layer would contribute even less to the overall mass transfer resistance. Consistent with recent experimental findings, the results of our model suggest that, under physiological conditions, transmembrane (membrane and its associated cytoskeleton layer) diffusion limitations in RBCs represent a key source of resistance for NO uptake by RBCs. © 2003 Biomedical Engineering Society.
PAC2003: 8716Uv, 8714Ee, 8715Vv, 8717Aa
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El-Farra, N.H., Christofides, P.D. & Liao, J.C. Analysis of Nitric Oxide Consumption by Erythrocytes in Blood Vessels using a Distributed Multicellular Model. Annals of Biomedical Engineering 31, 294–309 (2003). https://doi.org/10.1114/1.1553454
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DOI: https://doi.org/10.1114/1.1553454