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Presence of rigid red blood cells in blood flow interfere with the vascular wall adhesion of leukocytes. Mario Gutierrez, Margaret B Fish, Alexander W Golinski, and Omolola Eniola-Adefeso Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.7b03890 • Publication Date (Web): 18 Jan 2018 Downloaded from http://pubs.acs.org on January 19, 2018
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Presence of rigid red blood cells in blood flow
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interfere with the vascular wall adhesion of
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leukocytes.
4 Mario Gutierrez,1 Margaret B. Fish,1 Alexander W. Golinski,1 Omolola Eniola-Adefeso1,2,3*
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Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109.
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109.
Macromolecular Science and Engineering Program, University of Michigan, Ann Arbor, MI 48109.
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KEYWORDS: Rigid Red Blood Cells, Inflammation, Leukocyte Adhesion, Neutrophils
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ABSTRACT: The symptoms of many blood diseases can often be attributed to irregularities in
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cellular dynamics produced by abnormalities in blood cells, particularly red blood cells (RBCs).
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Contingent on the disease and its severity, RBCs can be afflicted with increased membrane rigidity
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as seen in malaria and sickle cell disease. Despite this understanding, little experimental work has
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been conducted towards understanding the effect of RBC rigidity on cellular dynamics in
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physiologic blood flow. Though many have computationally modeled complex blood flow to
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postulate how RBC rigidity may disrupt normal hemodynamics, to date, there lacks a clear
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understanding of how rigid RBCs affect the blood cell segregation behavior in blood flow, known
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as margination, and the resulting change in the adhesion of white blood cells (WBCs). In this work,
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we utilized an in vitro blood flow model to examine how different RBC rigidities and volume
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fractions of rigid RBCs impact cell margination and the downstream effect on white blood cell
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(WBC) adhesion in blood flow. Healthy RBC membranes were rigidified and reconstituted into
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whole blood and then perfused over activated endothelial cells under physiologically relevant
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shear conditions. Rigid RBCs were shown to reduce WBC adhesion by up to 80%, contingent on
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the RBC rigidity and the fraction of treated RBCs present in blood flow. Furthermore, the RBC
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core was found to be slightly expanded with the presence of rigid RBCs, by up to ~30% in size
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fully comprised of rigid RBCs. Overall, the obtained results demonstrate an impact of RBC rigidity
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on cellular dynamics and WBC adhesion, which possibly contributes to the pathological
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understanding of diseases characterized with significant RBC rigidity.
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INTRODUCTION:
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Blood related diseases remain common today and are difficult to manage due to their complex
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nature.1 Blood cell diseases, in particular, have proven difficult to understand and treat, despite
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decades of research, specifically those diseases involving the loss of red blood cell (RBC)
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deformability.2 Diseases involving rigid RBCs are typically of genetic origin and have been studied
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mostly from this biological perspective, with their genetic nature limiting treatment options and
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efficacy.3 Patients inflicted with Sickle Cell Disease (SCD), hereditary spherocytosis, iron-
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deficient anemia, pyruvate kinase deficiency, human immunodeficiency virus (HIV), malaria,
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sepsis, and even natural aging have less deformable (rigid) RBCs than healthy patients.3–6 It is well
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known that rigid RBCs cause major physical damage when travelling through the body by
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occluding microvasculature, depriving tissues of nutrients, and damaging walls of the spleen, liver,
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and lungs.7,8 This damage produces further complications such as pulmonary hypertension, and
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cardiac dysfunction.8,9 However, to date, there is little understanding of the direct impact of RBC
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rigidity on the functionality of other blood cells and the downstream contribution to disease
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manifestation beyond the occlusion of microvasculature.10
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Blood is a highly concentrated, non-Newtonian suspension of RBCs, white blood cells (WBCs),
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platelets, and plasma.11 Healthy RBCs are disc-shaped (6-8 µm diameter) and highly flexible,
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which allows RBCs to squeeze through capillaries.11 In healthy humans, RBCs constitute anywhere
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from 30%-45% v/v of blood, which is defined as hematocrit (Hct).11 Blood flow properties are
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influenced by multiple physical factors: cell to cell collisions, shear rate of flow, RBC
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deformability, and vessel geometry.12 The RBC core occupies the center of flow and the red blood
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cell-free layer (RBC-FL/CFL) develops near the walls of the vessel, which aids in pushing stiffer
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objects, e.g. WBCs and platelets, to the vessel wall to constantly sample the endothelium for
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disease and rupture.13–24 The distribution of blood components in flow, as described, is founded
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upon hydrodynamic interactions that generate varying levels of lift force.25 The lift force is a
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product of the interaction between deformable cells, e.g. RBCs, and the wall of the vessel in a
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process deemed wall-induced migration; this specific interaction produces the RBC-FL.25 Stiffer
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cells, e.g. WBCs and platelets, are less affected by the lift force and thus do not populate the core
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of flow as densely as RBCs.25 Hemodynamic, heterogeneous collisions between the highly
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deformable RBCs and stiffer WBCs and platelets also promote the distribution of latter to the
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vascular wall.26–28 Specifically, when relatively rigid WBCs collide with deformable RBCs, the
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RBCs deform and the stiffer cells are displaced farther towards the wall – a process referred to as
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margination. This deformability and shape driven arrangement of cells in blood flow is essential
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for maintaining homeostasis and for providing rapid immune responses in the body.29 Interestingly,
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despite the widely known impact of deformability on cellular margination in blood flow, little
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experimental work exists specifically focusing on the effects of RBC rigidity, i.e. loss of
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deformability, on margination.26 Recent computational works have begun to elucidate the transport
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mechanisms of cell types with different physical properties in blood flow and have underlined the
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major impact of cell size and rigidity on blood margination.27,28,30 However, there are many
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challenges to modeling such highly complex fluid flow as human blood accurately, e.g. selection
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of appropriate boundary conditions and appropriately modeling the multiphase composition of
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blood. The ability to fully elucidate the effects of cellular rigidity and shape on hemodynamic
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blood margination can offer useful insight into the pathology of the many diseases in which RBC
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rigidity has been implicated,3–6 including in SCD that is the most described disease associated with
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altered RBC deformability.
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SCD is a hereditary multisystem disease,3 which affects millions worldwide; estimates suggest that
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~100,000 Americans are affected.3 The polymerization of mutated hemoglobin (Hbs) produces
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long chains, which results in the sickling shape of the RBC, loss of membrane flexibility, reduced
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cell lifespan, and impaired blood flow to limbs.3,31 Treatments for SCD are limited and highly
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invasive, e.g. use of narcotics, blood transfusions, and bone-marrow transplants.3,32 However, little
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is known about the potential direct impact of the altered RBCs on the margination functionality of
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other blood cells, particularly WBCs. Indeed, SCD patients are known to have compromised
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immune responses to infections, which is largely attributed to splenic dysfunctions.33 However, it
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is possible that RBCs significantly alter cellular distribution in blood flow, and hence WBC
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margination, which would affect the natural immune response.
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To address the research gaps highlighted, we experimentally probe the direct effects of rigidified
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RBCs on the resulting margination of WBCs from bulk blood flow to the vessel wall via a parallel
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plate flow chamber (PPFC) and human blood flow with the presence of rigidified RBCs. Our
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results show that rigid RBCs in flow produced varying effects contingent on the level of RBC
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rigidity, the concentration of rigid RBC, and the magnitude of the blood flow shear rate. Overall,
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this work experimentally bypasses challenges including difficulty in accurately modeling
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hemodynamics, translating computational work into realistic in vitro models, and obtaining blood
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from disease inflicted patients. Ultimately, findings gained from a comprehensive investigation of
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cellular dynamics in blood flow can lead to profound advances in the understanding the pathology
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of many diseases.
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EXPERIMENTAL SECTION:
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Study Approvals and Preparation of Human blood:
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Fresh human blood is obtained the day of experiments via venipuncture according to a protocol
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approved by the University of Michigan Internal Review Board (IRB-MED). Informed, written
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consent was obtained from all subjects before blood collection. Blood was obtained from healthy
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subjects and drawn into a syringe containing citric acid-sodium citrate- dexterose (ACD) as an
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anticoagulant and stored at 37 ºC as described in Onyskiw et al.34 RBCs were isolated from whole
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blood by adding 6% dextran to anticoagulated blood in an inverted syringe, which sediments the
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RBCs from WBCs and plasma. WBC-rich plasma was then stored at 37 °C until recombination
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with RBCs at specified Hct (% vol/vol). RBCs were washed by suspending in phosphate-buffered
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saline (PBS) (-/-) and centrifugation.
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Red Blood Cell Rigidification and Characterization:
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Separated RBCs were treated at 2% Hct in PBS (-/-) with varying amounts of Tert-butyl
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hydroperoxide (TBHP) for 30 minutes, to induce oxidative stress on cellular membranes, and thus
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rigidify cell membranes. Four concentrations of TBHP (1.0, 0.75, 0.5, and 0.25 mM) were used to
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treat healthy human RBCs and examine RBC deformability. The rigid cells were then washed with
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PBS (-/-) and reconstituted with healthy RBCs and WBC rich plasma at the desired final hematocrit
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for use in adhesion assays. RBC deformability was analyzed using an ektacytometer, a laser-
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assisted optical rotational cell analyzer (LORRCA; Mechatronics, Hoorn, The Netherlands), which
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measures the elongation of the cells at increasing shear stress.35 RBC sample was diluted in 0.14
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M polyvinylpyrrolidone (PVP, MW 360,000) in PBS (overall viscosity, 30 mPa/s) to 200 times
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and was transferred into the LORRCA measuring cup for exposure to standardized inputs of
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increasing shear stress. Cell deformation was expressed as an elongation index (EI), Equation (1),
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as derived from the resulting ellipsoid laser diffraction pattern, where the major and minor axes of
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the elongated RBC are represented by A and B, respectively. The calculated values for the
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elongation index was plotted versus shear stress (Pa) to obtain the deformability curve.
𝐸𝐼 =
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𝐴−𝐵 𝐴+𝐵
(1)
Preparation of Endothelial Cell Monolayer:
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Human umbilical vein endothelial cells (HUVECs) used in all assays were isolated from healthy
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umbilical cords (Mott Children’s Hospital, Ann Arbor, MI) via a collagenase perfusion method,
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as described by Onyskiw et al.34,36 Briefly, isolated HUVEC were cultured in T75 flasks and seeded
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onto 30 mm glass coverslips coated with 1% gelatin and cross linked with 0.5% glutaraldehyde.37,38
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Coverslips were seeded with HUVEC and incubated at 37°C and 5% CO2 with standard media
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until confluent density was reached.37–39 For all studies, HUVECs were only used through the
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fourth passage. Confluent coverslips were activated with 1 ng/mL interleukin-1β (IL-1β) for 4
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hours to induce inflammation and cell adhesion molecule expression for WBC adhesion assays.
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Parallel Plate Flow Chamber Laminar Blood Flow Assays:
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Laminar blood flow assays were conducted as previously described in Namdee et al.34,40
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Coverslips with confluent monolayer were held by vacuum to the parallel plate flow chamber
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(PPFC, Glycotech, Inc.). The PPFC was fitted with a rectangular gasket (0.25 cm x 2 cm, heights:
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254 µm, 127 µm). Additionally, a microfluidic device was fabricated and employed to achieve a
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lower channel height of 50 µm. Briefly, the 50 µm channel was designed using AutoCAD software,
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and a template was fabricated on silicon wafers via a soft photolithography method, as described
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by Namdee et al.40 Polydimethylsiloxane (PDMS) channels were then made with the use of the
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silicon wafer template. Blood samples were prepared to have distinct rigid RBC concentrations,
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e.g., 10% of the total RBC volume were treated, and 90% were healthy cells. RBCs were treated
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with TBHP independently, i.e. in isolation from other blood components, thoroughly washed, and
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then reconstituted into the whole blood at the desired concentrations. The rigid RBC volume
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percentages examined were 10%, 20%, 30%, 50%, 70%, 90%, and 100%; all labels in figures
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represent the percent rigidified RBCs. The control experiment consists of a healthy blood flow
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assays, also reconstituted but lacks any TBHP-treated RBCs, and denoted as a healthy condition.
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Individual blood samples containing the rigid RBCs concentrations were perfused through the
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PPFC in a laminar flow profile for 5 min at physiological WSRs of 200 s-1, 500 s-1, 1,000 s-1 by
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controlling the volumetric flow rate. The volumetric flow rate through the channel (Q) was
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controlled via a syringe pump (Harvard Apparatus), which dictates the WSR (𝛾) ), as shown in
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Equation (2),
𝛾) =
6𝑄 23 ;𝑠 ℎ. 𝑤
(2)
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where h is the channel height (cm), w the channel width (cm), and Q the volumetric flow rate
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(mL/sec). The chamber was flushed with PBS buffer containing 1% BSA at the end of the
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experiment, and the WBCs adherent to the HUVEC monolayer were quantified using
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Metamorph®. All WBC experiments were expressed in terms of percent reduction relative to the
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healthy control of that specific donor, thus normalized for WBC variability across donors. All
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experiments were quantified as number of bound WBCs/mm2 HUVEC.
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Flow Distribution Studies (Confocal Microscope):
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Blood samples were perfused through a ~100 µm ibidi channel similar to the PPFC setup as
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previously described.41 Roughly 10% of total rigid RBCs per sample were stained with wheat germ
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agglutinin (WGA-488) and incubated for 10 minutes before examination; a higher staining
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percentage of RBC would saturate the fluorescence. For the healthy controls, 10% of total RBCs
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in the sample were stained with WGA 488. Images were taken using confocal microscopy with a
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488-nm laser at 80% power, with the photo-multiplier tube (PMT) voltage set at 700V, 1X gain,
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and 0% offset. The microscope was run in a round-trip 0.488 ms/line using a 2x digital zoom and
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a 20x water immersive objective. A total of 52 images were collected per trial by adjusting the
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focal plane 2 µm height per image. Fluorescently-tagged RBCs were processed and counted using
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ImageJ by setting a constant threshold and the "Analyze Particle" function. Laser, PMT, and ACS Paragon Plus Environment
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threshold settings were optimized for blank samples (no fluorescent RBCs) to contain less than
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1% count of fluorescent RBC positive trials. The shutter speed was set to allow for visualization
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of individual fluorescent RBCs in the flow. The inside of the channel was marked with a red
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fluorescent protein (RPF) marker to facilitate the calibration of the starting height (inside-top of
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the channel) for the scan to begin. Results presented represent the number of detected fluorescent
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RBCs in each scanned plane, not simply the mean fluorescent intensity, and thus rendered RBC
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distribution in channel height. RBC distributions of each flow condition were condensed for
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comparison using Interquartile Range (IQR) analysis. All experiments were normalized to
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corresponding healthy control, i.e. no rigid RBCs present.
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Statistics:
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Ektacytometry represents the average of three blood donors, with technical replicates of each.
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PPFC flow experiment data is an average of 10 pictures from each trial, with n=3 blood donors for
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each data point presented. Flow distribution experiments were repeated with n=3 blood donors for
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each perfusion condition. For all studies, all data points were included in the analyses and
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calculations of means or statistical significance. Data are plotted with standard error bars and
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analyzed as indicated in figure legends. Specifically, the ten brightfield images obtained for each
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data point (n =1) were average and the standard error calculated. The average values obtained for
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each “n” are averaged over multiple donors (n = 3) and standard error obtained by error
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propagation calculations. A 2-way ANOVA integrated package on GraphPad Prism was used to
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analyze any statistical difference between rigid and healthy conditions. Asterisks indicate p values
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of *
