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Objective: Hct in narrow vessels is reduced due to concentration of fast-flowing RBCs in the center, and of slower flowing plasma along the wall of the vessel, which in combination with plasma skimming at bifurcations leads to the striking heterogeneity of local Hct in branching capillary networks known as the network Fåhraeus effect. We analyzed the influence of feeding Hct and perfusion pressure on the Fåhraeus effect in an AMVN., Methods: RBC suspensions in plasma with Hcts between 20% and 70% were perfused at pressures of 5-60 cm H 2 O through the AMVN. A microscope and high-speed camera were used to measure RBC velocity and Hct in microchannels of height of 5 μm and widths of 5-19 μm., Results: Channel Hcts were reduced compared with Hct feeding in 5 and 7 μm microchannels, but not in larger microchannels. The magnitude of Hct reduction increased with decreasing Hct feeding and decreasing ΔP (flow velocity), showing an about sevenfold higher effect for 40% Hct feeding and low pressure/flow velocity than for 60% Hct feeding and high pressure/flow velocity., Conclusions: The magnitude of the network Fåhraeus effect in an AMVN is inversely related to Hct feeding and ΔP., (© 2017 John Wiley & Sons Ltd.)

Background: Higher hematocrit increases the oxygen-carrying capacity of blood but also increases blood viscosity, thus decreasing blood flow through the microvasculature and reducing the oxygen delivery to tissues. Therefore, an optimal value of hematocrit that maximizes tissue oxygenation must exist., Study Design and Methods: We used viscometry and an artificial microvascular network device to determine the optimal hematocrit in vitro. Suspensions of fresh red blood cells (RBCs) in plasma, normal saline, or a protein-containing buffer and suspensions of stored red blood cells (at Week 6 of standard hypothermic storage) in plasma with hematocrits ranging from 10 to 80% were evaluated., Results: For viscometry, optimal hematocrits were 10, 25.2, 31.9, 37.1, and 37.5% for fresh RBCs in plasma at shear rates of 3.2 or less, 11.0, 27.7, 69.5, and 128.5 inverse seconds. For the artificial microvascular network, optimal hematocrits were 51.1, 55.6, 59.2, 60.9, 62.3, and 64.6% for fresh RBCs in plasma and 46.4, 48.1, 54.8, 61.4, 65.7, and 66.5% for stored RBCs in plasma at pressures of 2.5, 5, 10, 20, 40, and 60 cm H 2 O., Conclusion: Although exact optimal hematocrit values may depend on specific microvascular architecture, our results suggest that the optimal hematocrit for oxygen delivery in the microvasculature depends on perfusion pressure. Therefore, anemia in chronic disorders may represent a beneficial physiological response to reduced perfusion pressure resulting from decreased heart function and/or vascular stenosis. Our results may help explain why a therapeutically increasing hematocrit in such conditions with RBC transfusion frequently leads to worse clinical outcomes., (© 2017 AABB.)

Objective: RBCs suspended in plasma form multicellular aggregates under low-flow conditions, increasing apparent blood viscosity at low shear rates. It has previously been unclear, however, if RBC aggregation affects microvascular perfusion. Here, we analyzed the impact of RBC aggregation on perfusion and 'capillary' hematocrit in an AMVN at driving pressures ranging from 5 to 60 cm H 2 O to determine if aggregation could improve tissue oxygenation., Methods: RBCs were suspended at 30% hematocrit in either 46.5 g/L dextran 40 (D40, non-aggregating medium) or 35 g/L dextran 70 (D70, aggregating medium) solutions with equal viscosity., Results: Aggregation was readily observed in the AMVN for RBCs suspended in D70 at driving pressures ≤40 cm H 2 O. The AMVN perfusion rate was the same for RBCs suspended in aggregating and non-aggregating medium, at both 'venular' and 'capillary' level. Estimated 'capillary' hematocrit was higher for D70 suspensions than for D40 suspensions at intermediate driving pressures (5-40 cm H 2 O)., Conclusions: We conclude that although RBC aggregation did not affect the AMVN perfusion rate independently of the driving pressure, a higher hematocrit in the 'capillaries' of the network for D70 suspensions suggested a better oxygen transport capacity in the presence of RBC aggregation., (© 2016 John Wiley & Sons Ltd.)

Previous computational studies have suggested that the capillary blood flow oscillations frequently observed in vivo can originate spontaneously from the non-linear rheological properties of blood, without any regulatory input. Testing this hypothesis definitively in experiments involving real microvasculature has been difficult because in vivo the blood flow in capillaries is always actively controlled by the host. The objective of this study was to test the hypothesis experimentally and to investigate the relative contribution of different blood cells to the capillary blood flow dynamics under static boundary conditions and in complete isolation from the active regulatory mechanisms mediated by the blood vessels in vivo. To accomplish this objective, we passed whole blood and re-constituted blood samples (purified red blood cells suspended in buffer or in autologous plasma) through an artificial microvascular network (AMVN) comprising completely inert, microfabricated vessels with the architecture inspired by the real microvasculature. We found that the flow of blood in capillaries of the AMVN indeed oscillates with characteristic frequencies in the range of 0-0.6 Hz, which is in a very good agreement with previous computational studies and in vivo observations. We also found that the traffic of leukocytes through the network (typically neglected in computational modeling) plays an important role in generating the oscillations. This study represents the key piece of experimental evidence in support of the hypothesis that spontaneous, self-sustained oscillations of capillary blood flow can be generated solely by the non-linear rheological properties of blood flowing through microvascular networks, and provides an insight into the mechanism of this fundamentally important microcirculatory phenomenon., (Copyright © 2012 Elsevier Inc. All rights reserved.)