An Experimental-Computational Approach to Quantify Blood Rheology in Sickle Cell Disease

Feature tracking microfluidic analysis reveals differential roles of viscosity and friction in sickle cell blood

“…We observed variability in the effective resistances of blood between patients, in agreement with previous studies linking variations in patient hematologic profiles, such as differences in quantities of sickle hemoglobin (HbS) and fetal hemoglobin (HbF), to variations in blood flow properties. 15 Our results suggest that patient-specific treatments may be more effective than population-averaged treatment strategies in ameliorating symptoms while reducing treatment-related complications. For example, further evaluation of how these resistances connect to vaso-occlusive risk in a range of patients may help with the identification of targeted values that conform to patients' specific needs, preventing common transfusion issues such as alloimmunization and iron overload.…”

“…The bulk component is calculated by subtracting the wall velocity from the average velocity (obtained by integrating eqn (7)), then multiplying by the cross-sectional area. Q slip = V wall × w × h Q bulk = ( V avg − V wall ) × w × h These calculations assume that the observed velocity profile approximately corresponds to a height-averaged velocity profile across the height of the device. 15 Finally, effective resistances can be calculated from the flow rates by obtaining the pressure drop Δ P in the experimental channel via a linear network model of the device 42 (see ESI† Text and Fig. S1a).…”

“…Our current understanding of whole-blood dynamics in SCD has been informed by numerous studies that have characterized macroscopic rheological properties using methodologies including specialized microfluidic devices and viscometers. [12][13][14][15][16][17] Typically, such studies have measured only total flow resistances, which provide a crude estimate of the pressure required to drive flow through blood vessels. However, because blood in SCD patients (SCD blood) is a complex suspension, a more accurate characterization of its rheology should also capture non-Newtonian effects, such as shear thinning, and frictional effects arising from the interactions of RBCs with walls.…”

Experimental and Mouse-Specific Computational Models of the Fbln4SMKO Mouse to Identify Potential Biomarkers for Ascending Thoracic Aortic Aneurysm

“…The parameters a , n , and λ describe the power-law region between the two plateaus. Parameter values were based on our previous analysis of healthy human blood [ 33 ], which is similar to mouse blood rheology for the shear rate range of the interest [ 34 ] ( Supplemental Table S1 ): η ∞ = 2 cP , η 0 = 11 cP , λ = 1.5, a = 0.2, n = 0.71.…”

Biophysical and rheological biomarkers of red blood cell physiology and pathophysiology

“…Advances in microelectromechanical systems and microfabrication methods have enabled microfluidic platforms that can probe single-cell behavior under precisely controlled biological, biophysical, and flow conditions, mimicking physiology at baseline and with disease [2,4,8 ▪ ,11,14,17–22]. Microfluidic technologies integrated with biomolecular probes [23], high-throughput microscopic imaging, and data analysis methods [20] are ideal for studying blood cell biophysics, interactions, and adhesion dynamics (Fig.…”