ORIGINAL RESEARCH published: 21 October 2021 doi: 10.3389/fphys.2021.761411 Blood Rheological Characterization of β-Thalassemia Trait and Iron Deficiency Anemia Using Front Microrheometry Lourdes Méndez-Mora 1* , Maria Cabello-Fusarés 2 , Josep Ferré-Torres 1 , Carla Riera-Llobet 1 , Elena Krishnevskaya 3 , Claudia Trejo-Soto 4 , Salvador Payán-Pernía 5 , Inés Hernández-Rodríguez 6 , Cristian Morales-Indiano 7 , Tomas Alarcón 2,8,9 , Joan-Lluis Vives-Corrons 3 and Aurora Hernandez-Machado 1,2,10 Edited by: 1 Paola Bianchi, Department of Condensed Matter Physics, University of Barcelona, Barcelona, Spain, 2 Centre de Recerca Matemàtica, IRCCS Ca’ Granda Foundation Barcelona, Spain, 3 Red Cell Pathology and Hematopoietic Disorders (Rare Anemias) Unit, Josep Carreras Leukaemia Maggiore Policlinico Hospital, Italy Research Institute, Badalona, Spain, 4 Instituto de Física, Pontificia Universidad Católica de Valparaiso, Valparaiso, Chile, 5 Red Blood Cell Disorders Unit, Hematology Department, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina Reviewed by: de Sevilla (IBIS/CSIC), Seville, Spain, 6 Hematology Service, Institut Català d’Oncologia, Germans Trias i Pujol University Pedro Moura, Hospital, Badalona, Spain, 7 Laboratory Medicine Department, Laboratori Clínic Metropolitana Nord, Hospital Universitari Karolinska Institutet (KI), Sweden Germans Trias i Pujol, Badalona, Spain, 8 Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain, Giovanna Tomaiuolo, 9 Departament de Matemàtiques, Universitat Autónoma de Barcelona, Bellaterra, Spain, 10 Institute of Nanoscience University of Naples Federico II, Italy and Nanotechnology, University of Barcelona, Barcelona, Spain *Correspondence: Lourdes Méndez-Mora lmendemo9@alumnes.ub.edu The purpose of this work is to develop a hematocrit-independent method for the detection of beta-thalassemia trait (β-TT) and iron deficiency anemia (IDA), through Specialty section: the rheological characterization of whole blood samples from different donors. The This article was submitted to Red Blood Cell Physiology, results obtained herein are the basis for the development of a front microrheometry a section of the journal point-of-care device for the diagnosis and clinical follow-up of β-TT patients suffering Frontiers in Physiology hematological diseases and alterations in the morphology of the red blood cell (RBC). Received: 19 August 2021 Accepted: 30 September 2021 The viscosity is calculated as a function of the mean front velocity by detecting the Published: 21 October 2021 sample fluid-air interface advancing through a microfluidic channel. Different viscosity Citation: curves are obtained for healthy donors, β-TT and IDA samples. A mathematical model Méndez-Mora L, is introduced to compare samples of distinct hematocrit, classifying the viscosity curve Cabello-Fusarés M, Ferré-Torres J, Riera-Llobet C, Krishnevskaya E, patterns with respect to the health condition of blood. The viscosity of the fluid at certain Trejo-Soto C, Payán-Pernía S, shear rate values varies depending on several RBC factors such as shape and size, Hernández-Rodríguez I, Morales-Indiano C, Alarcón T, hemoglobin (Hb) content, membrane rigidity and hematocrit concentration. Blood and Vives-Corrons J-L and plasma from healthy donors are used as reference. To validate their potential clinical Hernandez-Machado A (2021) Blood value as a diagnostic tool, the viscosity results are compared to those obtained by the Rheological Characterization of β-Thalassemia Trait and Iron gold-standard method for RBC deformability evaluation, the Laser-Optical Rotational Deficiency Anemia Using Front Red Cell Analyzer (LoRRCA). Microrheometry. Front. Physiol. 12:761411. Keywords: beta-thalassemia trait, iron deficiency (anemia), anemia, hemorheology, rheology, microfluidics, blood doi: 10.3389/fphys.2021.761411 rheology, microrheometer Frontiers in Physiology | www.frontiersin.org 1 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA INTRODUCTION microcytic hypochromic anemia in the Mediterranean region (Galanello and Origa, 2010). Blood is a biological fluid composed of red blood cells (RBCs), Alterations in the deformation capacity of RBCs can produce white blood cells (WBC), and platelets suspended in plasma, changes in the non-linear rheological behavior of the whole a Newtonian fluid containing organic molecules, proteins and blood; these alterations are potentially detectable via a rheometry salts (Baskurt and Meiselman, 2003). The viscosity of plasma is study. Rheological measurements are usually performed with constant; it does not depend on the pressure that is applied onto it rotational rheometers, a type of shear rheometer (Macosko, (Késmárky et al., 2008). Whole blood is a non-Newtonian shear- 1994). However, this type of equipment is expensive, requires a thinning fluid, and its viscosity decreases when an increasing considerable laboratory space and must be operated by trained pressure is applied. WBCs and platelets can affect blood personnel. Moreover, the measurements take several minutes and rheology but, under normal conditions, RBCs represent most need a large sample amount. For these reasons, there is a demand of the cellular components and make the biggest contribution for Point-of-care (PoC) devices for analyzing the rheological to viscosity (Pop et al., 2002). As a result, the viscosity of properties of whole blood. To be efficient and cost-effective, many blood depends mostly on the ability of RBCs to deform under portable PoC devices employ microfluidic devices that generally circulation flow (Baskurt and Meiselman, 2003; Cokelet and consist of low-cost microfluidic chips, that are easy to fabricate Meiselman, 2007; Mehri et al., 2018). and are made of glass, polydimethylsiloxane (PDMS) and other Red blood cells have a characteristic discoid shape with a polymeric materials that are biocompatible and widely available. biconcave profile, under normal physiological conditions; the The microfluidic approach permits to obtain a high precision well-known discocyte shape (Diez-Silva et al., 2010). This shape measurement of blood conditions in motion with only one combines a large area to volume ratio, which is an important drop of blood, in a time and cost-effective way in comparison factor to maximize oxygen diffusion. The erythrocytes have a to rotational rheometers (Davies and Stokes, 2008; Pipe and unique ability to deform and pass through small capillaries McKinley, 2009; Choi and Park, 2010; Galindo-Rosales et al., before rapidly recovering their initial shape. The deformation 2012). Many applications that aim at analyzing the properties capacity of RBCs is mainly due to three factors; their large area of the blood through its rheological characterization, employ to volume ratio; the viscosity of the intracellular fluid that is microfluidic devices that measure the behavior of blood as a dominated by the presence of hemoglobin and the viscoelastic function of the shear rate (Srivastava and Burns, 2006; Fedosov properties of the cell membrane (Lázaro et al., 2013; Tomaiuolo, et al., 2011; Tomaiuolo, 2014; Rico et al., 2018; Rodriguez- 2014). However, the deformability of RBCs is impaired in some Villarreal et al., 2020). In addition, some microfluidic applications pathological conditions as a result of defects in cell membrane permit the observation of the flow of blood under high skeletal architecture (Faustino et al., 2019; Hymel et al., 2020), confinement conditions (Davies and Stokes, 2008; Bartolo and erythrocyte aging (Diez-Silva et al., 2010; Simmonds et al., 2013), Aarts, 2012; Lázaro et al., 2014). PoC diagnostics, including and mechanical damage (Rico et al., 2018). microfluidic tools, are very promising for early detection of β-thalassemia syndromes are a heterogeneous group of different diseases, and for the monitoring of health conditions. genetic conditions characterized by reduced or abolished In this work, a PoC front-microrheometer with electronic synthesis of the hemoglobin subunit beta (hemoglobin beta detection is used to characterize blood samples from different chain). The β-thalassemia carrier state is also referred as donors. The viscosity value as a function of the shear rate of heterozygous β-thalassemia or β-thalassemia trait (β-TT) the blood front is measured, details on the mathematical model (Galanello and Origa, 2010). When β-TT is present, RBCs developed can be found in previous works (Trejo-Soto et al., show rheological abnormalities (Berga et al., 1989). The RBC 2017, Trejo-Soto et al., 2018; Méndez-Mora et al., 2021). Three membrane can be affected due to a selective interaction types of samples are analyzed: control samples from healthy between the α-chain excess and the erythrocyte membrane donors, and blood samples from IDA and β-TT patients. Due cytoskeleton (Rachmilewitz and Kahane, 1980), while other to the morphological and membrane differences of the RBCs in alterations are caused by hemoglobin denaturalization (Fiorelli the three groups, it is expected to obtain a distinctive viscosity et al., 1996). In addition, microcytosis, or decreased mean pattern for each group. As it is expected that RBCs volume has corpuscular volume (MCV) of RBCs, is present in β-TT an impact on blood viscosity, and the microcytosis is present in carriers. Previous works suggest that the decreased RBC IDA and β-TT blood donors, the samples are classified in terms deformability is probably due to microcytosis (Rasia et al., of the MVC of their RBCs, ensuring that microcytosis does not 1986; Iborra et al., 2003). More recently, by comparing mask other rheological effects. two non-healthy sets of samples, of iron deficiency anemia The main purpose of this study is to demonstrate that (IDA) (DeLoughery, 2017) and β-thalassemia trait, a study the micro-rheometer developed can differentiate distinct based on ektacytometry showed two distinct deformation hematological pathologies, regardless their hematocrit patterns, indicating that the observed decrease in the percentage. This is done by the differentiation, through deformability is not only due to microcytosis (Payán-Pernía whole-blood viscosity, between two very common conditions et al., 2021). Osmotic gradient ektacytometry measures that affect RBCs, IDA, and β-TT, beyond the effect of the low RBC deformability under defined shear stress as a function MCV that characterizes both of them, and after hematocrit of suspending medium osmolarity (Llaudet-Planas et al., normalization. The research represents and advancement in the 2018). IDA and β-TT are two very common causes of development of PoC devices for the diagnosis of anemia-related Frontiers in Physiology | www.frontiersin.org 2 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA diseases. This is of global concern, since information about plasma. It consists of establishing a relation between the pressure the precise world distribution and frequency of the inherited versus shear rate fit for plasma and the sample that needs to be and acquired hemoglobin disorders is still limited (Williams normalized (Trejo-Soto and Hernández-Machado, 2021). This is and Weatherall, 2012). It is also an issue of particular interest expressed as follows: in the developing countries, where anemia is more prevalent (Kassebaum et al., 2016). γ̇ Plasma 1PSample ηeff = (3) γ̇ Sample 1PPlasma MATERIALS AND METHODS where 1PSample and 1PPlasma are the pressure inside the microfluidic system for the blood sample and its plasma, Mathematical Model respectively. Analogously, γ̇Sample and γ̇Plasma are the shear rates The method used here to analyze the fluid flow consists of the of the blood and plasma samples, respectively. Finally, (ηeff ) is study of the fluid-air interface advancement. Inside a microfluidic normalized with respect to the maximum hematocrit level ofthe channel, the front velocity ḣ, is the change in position of the studied samples. The hematocrit normalized viscosity ηhct , is fluid, h(t) through time along the microfluidic channel. calculated using the following equation: PThe term h(t) is the average position of the front h (t) = N1 N j=1 hj (t),   φ max where hj (t) is the fluid front position. Shear rate, γ̇ is the ηhct = 1 + ηeff − 1 (4) φ sample normalization of mean front velocity (ḣ) according to the depth of the microchannel, b: where φmax is the maximum hematocrit with respect to which the ḣ different samples need to be normalized. φsample is the hematocrit γ̇ = (1) b of the sample being normalized. According to the Ostwald-De Waele Power-Law model for fluids, the viscosity can be expressed as a function of shear rate: Experimental Method The experimental setup used consists of a microfluidic channel η(γ) = mγ̇n−1 (2) with 24 gold electrodes, a pumping source, and a computer terminal (Méndez-Mora et al., 2021). A series of shear rates is where m is a prefactor obtained experimentally, n is a constant obtained by applying a set of pressures on the sample fluid. that depends on the studied fluid and defines the nature of its The fluid front advancement is detected in a fast and accurate viscosity, being n = 1 for Newtonian fluids. To remove the effects manner by the gold electrodes printed beneath the microfluidic on viscosity caused by distinct hematocrit levels in different channel. The microfluidic chips made of polydimethylsiloxane samples, the first step is to calculate the effective viscosity, (PDMS) attached to glass substrates by oxygen plasma bonding. (ηeff ). This is the viscosity of blood relative to the viscosity of The microfluidic channel and the electrodes have been fabricated FIGURE 1 | Schematics of the microfluidic setup. A micropump is used as a pressure source. The pump is connected to the reservoir with the fluid sample using a tube. The fluid is flowing through the microchannel. The microfluidic consumable is made of PDMS sealed on a glass substrate with electrodes. Frontiers in Physiology | www.frontiersin.org 3 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA using lithography techniques (Qin et al., 2010). The distance Now, the effective pressure inside the system can be calculated as: between electrodes is 350 µm. There are four groups of ωb n     n electrodes, and each has six pairs of electrodes. The distance 1 1 n Peff = m2lt + 3 ḣ between each group of electrodes is 8.5 mm. The channel width πr2 r1+n n is ω = 1000 µm height b = 300 µm and the length from !n  n ωb2  1 1 inlet to outlet is lc = 4 cm. PDMS, glass, and Tygon tubes = m2lt + 3 γ̇ n (7) are biocompatible. πr2 r1+n n Using a tube of an internal diameter of 254 µm and length 20 cm the pump is connected to a closed reservoir The mean front velocity ḣ, at each set pressure is experimentally holding the fluid, and this communicates the reservoir with obtained. By calculating velocity values and the channel the microchannel. The pump is easy to control through the dimensions, shear rate values are obtained. By fitting a curve for computer, using a simple graphic interface. Different pressures the relation between Peff and γ̇, the next relation is obtained: for the Fluika Pump are set to run the experiment, from 1,000 to Peff = K(m, n)γ̇ n−1 (8) 5,000 Pa The electrodes in the microfluidic channel are connected to a data acquisition system by a set of contact pins. As soon as the All the independent variables are grouped in K, which depends pressure starts being applied, the electronic reading is activated on the fluid properties (m and n) and the geometrical parameters thanks to the controller of a myRIO National Instruments card. of the system (ω, b, lt , r), This tool communicates the fluidic pump and the electronic !n  n reading pins, through the computer. The sample fluid comes out ωb2  1 1 of the reservoir at the set pressure and advances through the K (m, n) = m2lt + 3 (9) π r2 r1+n n channel. As the fluid enters the microchannel and contacts the electrodes, it acts as a switch and sets the time required for the Patients and Sample Preparation fluid front to reach each electrode pair. Using the time data and A total of five patients with IDA, 15 patients with β-TT, and 10 the distance between electrodes, it is possible to calculate the fluid normal controls (healthy individuals) were included in the study. front velocity. All these tests are performed at room temperature The ages range for patients was from 18 to 95 years old. None (∼24◦ C). The way these microfluidic elements are connected is of the patients had been transfused in the previous months. IDA displayed in Figure 1. was considered present when serum ferritin (SF) was <15 µg/L, The experimental setup is comprised of a pumping source or when SF was <30 µg/L, and transferrin saturation index (TSI) that connects to a fluid reservoir. The sample stored in the was <20%. IDA is present when (Hb < 12.0 g/dL in non-pregnant reservoir is pushed out through a connecting tube of radius r, and adult women and Hb < 13.0 g/dL in adult men). β-TT was length lt . The tube transporting is connected into the microfluidic diagnosed if mild microcytic anemia was present in absence of channel of rectangular cross-section, of width ω and height b. The iron deficiency and the Hb analysis showed an increase in HbA2 pressures acting on the system depicted in Figure 1, relate to each (>3.5%) with or without an increase in Hb F (if present, <5%). other as: All subjects in the control group had normal Hb levels, RBC indices, and iron parameters. 1P = Pp + PH − 1Pt − Pcap (5) Samples were collected in ethylenediaminetetraacetic acid (EDTA) anticoagulant tubes during the course of routine analysis, shipped and stored at a temperature of 4◦ C, and Here 1P, the pressure drop inside the microchannel, is the processed within 24 h after the extraction. Complete blood count summation of all the pressures involved in the experiment. The (CBC) parameters were assessed on a Sysmex XN-10 (Sysmex set pressure Pp , is the pressure coming from the pumping source. Corporation) analyzer. Total iron-binding capacity (TIBC), and The hydrostatic pressure PH is the product of the density ρ, serum ferritin (SF) were measured on Architect ci16000 System gravity g, and height of the fluid with respect to the channel height (Abbott Laboratories). Serum iron (SI), and (TIBC) by enzymatic H; expressed as PH = ρgH. The pressure drop represented by the methods, and SF by a two-step chemiluminescent micro-particle tube connection is 1Pt . The capillary pressure, Pcap is defined as immunoassay (CMIA). The (TSI) was calculated as the ratio the resistance that the hydrophobic channel walls oppose to the of iron to TIBC. Hb analysis was performed using high- fluid advancement. Pcap is dependent on the contact angle and performance liquid chromatography (HPLC) on a D-10 Dual the surface tension of the fluid, τ . A2/F/A1c (Bio-Rad Laboratories) or capillary electrophoresis Thanks to the mass conservation principle, the flow inside the on a Capillaris-2 Flex Piercing (Sebia). The use of the samples system is Q = Qt → ωbḣ = π r2 vt , where Qt and vt , are the was authorized by the Bioethics Committee of the University flow and velocity inside the tube, respectively, and Q is the flow of Barcelona (IRB 00003099) and the Ethics Committee of IJC inside the channel (Méndez-Mora et al., 2021). The relation vt = ḣωb [Comité Ético de Investigación Clínica (CEIC)]. πr2 is valid for the coupled system and 1Pt can be written as: Samples with different hematocrit concentrations were manually prepared by properly mixing plasma and RBC in n  n the desired ratio. To obtain plasma, whole blood samples were ωb   1 1 n centrifuged at 2,500 rpm for 5 min. The plasma that rests at 1Pt = m2lt +3 ḣ (6) π r2 r1+n n the top is collected with a pipette. The different hematocrit Frontiers in Physiology | www.frontiersin.org 4 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 7000 6000 Effecve Pressure, Peff (Pa) 5000 4000 3000 CN at 35%hct 2000 CN at 30%hct CN at 25%hct 1000 Plasma 0 0 5 10 15 20 25 Shear rate, ̇ (s⁻¹) FIGURE 2 | Effective pressure vs. shear rate for blood from a healthy donor at different hematocrit levels. concentrations hct (%) are prepared by taking plasma previously viscosity for the different hematocrit samples according to their separated from whole blood and then adding to it the desired plasma. The effective viscosity, ηeff is calculated using Eq. 3. The volume of RBCs corresponding to each hematocrit percentage. effective viscosity ηeff depends on plasma viscosity. The result is The sample volume prepared for each individual experiment shown in Figure 3. is 500 µL. The normalization of viscosity according to hematocrit can be done by applying Eq. 4, which takes the highest hematocrit from the sample measured and compares it to the reduced hematocrit RESULTS AND DISCUSSION samples. Since the samples come from the same donor, if the equations were properly deduced, all curves must collapse onto Blood Viscosity Normalization by a single viscosity curve for all the hematocrit levels, meaning Hematocrit that the differences observed before are only due to hematocrit The hematocrit value in blood samples has a high impact on blood viscosity differences between different patients with the same blood conditions (Baskurt and Meiselman, 2003). Heterogeneity across patients regarding blood viscosity is expected to be present, mostly due to variations in hematocrit, hct (%). To observe differences in viscosity caused by blood abnormalities and be able to compare the blood viscosity curve of different patients, blood viscosity needs to be normalized to account for variations in hematocrit. To validate the normalization procedure, we first take a control sample (CN) from a healthy donor and prepare three different hct (%): 35%, 30%, and 25%. Viscosity is calculated for each hematocrit using Eq. 2. By using Eqs. 3, 4, the effects of hematocrit are removed. The effective pressure, Peff as a function of the shear rate, γ̇ for each prepared hematocrit and plasma are presented in Figure 2. As seen in Figure 2, the shear rate, which is the normalization of the front velocity respect to the channel height, increases as the hct (%) value decreases under constant pressure conditions. Plasma has the highest front velocity when the same pressure is FIGURE 3 | Effective viscosity vs. shear rate for different hematocrit of healthy applied. Once the mean front velocity associated with each set blood from a single healthy donor (CN). pressure has been measured, it is possible to calculate the effective Frontiers in Physiology | www.frontiersin.org 5 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA hematocrit percentages (25%, 30%, and 35% hct) from a single 5 β-TT patient are prepared. Note that β-TT samples are tested Hematocrit normalized viscosity, ηhct 4,5 at lower γ̇ to avoid hemolysis. The effective viscosity, ηeff is 4 calculated for each hematocrit using Eq. 3. The resulting curves 3,5 are presented in Figure 5. 3 After calculating ηeff , hematocrit normalized viscosity, ηhct is (mPa·s) 2,5 calculated using Eq. 4. By taking φmax = 35% hct, a normalized curve for β-TT is obtained, it is presented in Figure 6. 2 The results obtained in Figures 4, 6 demonstrate that the 1,5 method presented makes it possible to normalize different CN at 35%hct 1 samples by hematocrit, regardless of their health condition. CN at 30%hct 0,5 Using this normalization, curves for diverse pathologies could be CN at 25%hct 0 compared without the effects of different hematocrit levels. For 0 5 10 15 20 25 comparison purposes, we contrast both curves (healthy donors Shear rate, ̇ (s⁻¹) and β-TT donors) in Figure 7, where the measurements obtained for each patient collapse into well differentiated curves. FIGURE 4 | Hematocrit normalized viscosity vs. shear rate for different Moreover, the method used to measure viscosity allows us hematocrit percentages from a single healthy donor (CN). to obtain points at low shear rates, giving us the advantage to observe the shear-thinning behavior of blood. This also makes it possible to observe that viscosity values are larger at low γ̇ variations. The hematocrit normalized viscosity, ηhct is presented for β-TT than for healthy samples. The hematocrit normalized in Figure 4. viscosity curves obtained in Figure 6 for β-TT show higher The results presented in Figure 4, indicate that the method viscosity than the control samples in Figure 4. employed is useful to remove effects caused by hematocrit differences. Furthermore, it will be helpful to contrast with Study of Beta-Thalassemia Trait Samples samples that show differences related to RBCs count and When beta-thalassemia is present, RBC indices show microcytic abnormalities affecting the cells in suspension. anemia. Thalassemia major is characterized by reduced Hb level The shear rate response for each sample will depend, (<7 g/dl), mean corpuscular volume (MCV) > 50 < 70 fL mostly, on the percentage of RBCs present in suspension. This and mean corpuscular hemoglobin (MCH) > 12 < 20 pg. response can also be affected by the presence of abnormalities Thalassemia intermedia is characterized by Hb levels between 7 developed by the blood cells, such as in β-TT. To validate the and 10 g/dl, MCV between 50 and 80 fL, and MCH between normalization of viscosity for non-healthy donors, the same 16 and 24 pg. Thalassemia minor (BT Trait) is characterized by experiment is conducted with β-TT samples. For validation, three reduced MCV and MCH, with increased Hb A2 level (Galanello 5 4,5 4 Effecve viscosity, ηeff (mPa·s) 3,5 3 2,5 2 1,5 1 β-TT at 35%hct β-TT at 30%hct 0,5 β-TT at 25%hct 0 0 2 4 6 8 10 Shear rate, ̇(s⁻¹) FIGURE 5 | Effective viscosity vs. shear rate from a patient with β-TT at three different RBCs concentrations. Frontiers in Physiology | www.frontiersin.org 6 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA TABLE 1 | Classification of β-TT and CN samples according to their MCV. 5 Hematocrit normalized viscosity, ηhct 4,5 Group Type MCV (fL) 4 Lowest Beta-thalassemia 58–65 3,5 Very low Beta-thalassemia 66–70 3 Low Beta-thalassemia 71–75 (mPa·s) 2,5 Normal volume Healthy blood 90–92 2 1,5 β-TT at 35%hct presented in Figure 8. A tendency line indicating the average 1 β-TT at 30%hct value obtained for each kind of sample is included. 0,5 β-TT at 25%hct As seen in Figure 8, β-TT samples with the smallest MCV 0 (58–65 fL) have a higher viscosity than β-TT samples with higher 0 2 4 6 8 10 MCV (66–70 fL and 71–75 fL). This indicates that the size of the Shear rate, ̇ (s⁻) erythrocyte may be affecting the viscosity measurement results. When two or more samples have equivalent hct (%) and different FIGURE 6 | Hematocrit normalized viscosity vs. shear rate for different MCV, it implies that the number of RBCs is greater as lower hematocrit percentages from a single β-TT donor. is the MCV, which generates a greater number of cell rows in the flow when circulating through the microchannel. This effect, studied in detail for healthy red blood cells in a previous work (Lázaro et al., 2019) implies a stronger RBC interaction which et al., 1989; Galanello and Origa, 2010). To carry out this study, leads to an increase in the magnitude of the viscosity, similar to whole blood samples from healthy donors and patients diagnosed the effect on viscosity observed in Figure 8. The parameters m with β-TT are used. To avoid effects caused by the variation and n describing the viscosity curves, calculated using Eq. 2, for of microcytosis, the samples were classified into three groups, each sample included in Figure 8, are presented in Table 2. according to their MCV, as presented in Table 1. The β-TT samples with the smallest MCV values have the For each MCV group, five samples from different patients highest average m value, which equals the value of viscosity at were tested. The effective viscosity was calculated with Eq. 3. The γ̇ = 1. β-TT samples with MCV between 66 and 75 fL have very ηhct , obtained by using Eq. 4, for all the measured samples are similar rheological parameters. The curves in Figure 8 differ 5 4,5 Hematocrit normalized viscosity, ηhct (mPa·s) 4 3,5 3 2,5 2 1,5 β-TT at 35%hct 1 β-TT at 30%hct β-TT at 25%hct 0,5 CN at 35%hct CN at 30%hct CN at 25%hct 0 0 5 10 15 20 25 Shear rate, ̇ (s⁻¹) FIGURE 7 | Hematocrit normalized viscosity vs. shear rate for β-TT samples and healthy blood samples. Frontiers in Physiology | www.frontiersin.org 7 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 10,0 β-TT MCV 58-65(fL) Hematocrit Normalised Viscosity, ηht (mPa·s) 9,0 β-TT MCV 66-70(fL) 8,0 β-TT MCV 71-75(fL) 7,0 CN MCV 90-92(fL) 6,0 5,0 4,0 3,0 2,0 1,0 0,0 0,0 2,0 4,0 6,0 8,0 10,0 Shear rate , ̇ (s⁻¹) FIGURE 8 | Hematocrit normalized viscosity for β-TT and healthy control blood (CN) classified by MCV in Table 1. Whole blood is used in all cases. TABLE 2 | Average values of m and n for healthy blood and β-TT samples characterized by decreased ferritin, and MCV, while total iron- according to MCV in fL. binding capacity and red blood cell distribution are increased. Type Group m n MCV (fL) Hypochromic red blood cells can be also be observed by visual inspection on a blood smear (Wagley, 1953; DeLoughery, 2017). β-TT Lowest 7.4295 0.872 58–65 To confirm that the alterations seen in the viscosity of β-TT β-TT Very low 5.7582 0.953 66–70 samples are not only attributed to microcytosis, we compared β-TT Low 5.6265 0.955 71–75 results obtained from samples with MCV of 66–75 fL to results CN Normal volume 2.8272 0.880 90–92 of samples of IDA patients, with similar values of MCV. Using Viscosity is normalized by hematocrit. the same method as in Figure 8, we tested ten β-TT samples with MCV between 66 and 75 fL, five IDA samples with MCV from those of healthy blood for two reasons, because the MCV between 66 and 79 fL and five samples from healthy donors is different, and because the mechanical properties of healthy with MCV between 90 and 92 fL. The results are shown in and pathological red blood cells are different. We want to verify Figure 9. that alterations such as the changes in cell morphology and Figure 9 shows that despite having similar MCV, β-TT and rigidity caused by the presence of β-TT, have a direct effect on IDA samples have different viscosity patterns. The m and n the viscosity. The normal reference range for MCV is typically parameters describing the viscosity curve for each group are 80–100 fL, but this value is altered in some conditions. presented in Table 3. Iron deficiency anemia and β-TT curves have a different Comparison of Blood Samples With viscosity pattern even though they have similar MCV, indicating that pathological RBC conditions are reflected in viscosity, and Microcytic Red Blood Cells: Iron they can be differentiated with the micro-rheometer. The IDA Deficiency Anemia and viscosity results show a much less Newtonian behavior; the n Beta-Thalassemia Trait value differs more from 1 than that obtained with the β-TT Anemia is a condition in which the number of red blood cells, samples. Since both diseases present Hb deficiency and RBCs and consequently their oxygen-carrying capacity, is insufficient with similar MCV, we conclude that the difference observed in to meet the physiologic needs of the body, and it is diagnosed as viscosity between the β-TT and IDA cannot be considered a a decrease in the blood hemoglobin concentration (Hb) (Vitamin consequence of differences in RBC size. The higher viscosity and Mineral Nutrition Information System (VMNIS), 2011). Iron obtained for the β-TT samples might be attributed to a greater deficiency limits the synthesis of heme, which in turn limits the rigidity in the RBC membrane. This can be caused by the excess synthesis of hemoglobin (Nagababu et al., 2008; DeLoughery, of α chains that bind to the RBC membrane (DeLoughery, 2017; 2017), as it happens in β-TT as a result of a mutation. It is also Payán-Pernía et al., 2021). Frontiers in Physiology | www.frontiersin.org 8 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA 8,0 β-TT MCV 66-75(fL) Hematocrit Normalized Viscosity, ηhct (mPa·s) 7,0 IDA MCV 66-79(fL) CN WB MCV 90-92(fL) 6,0 5,0 4,0 3,0 2,0 1,0 0,0 0,0 2,0 4,0 6,0 8,0 10,0 Shear rate (s¯¹) FIGURE 9 | Hematocrit normalized viscosity for ten samples of β-TT, five samples of IDA and five samples from healthy donors (CN). Whole blood in all cases. TABLE 3 | Average values of m and n for IDA and samples according to MCV previously described and differences between the three groups after normalizing by hematocrit. were statistically significant, reflecting deformability differences Sample Type m n MCV fL between these three states (Payán-Pernía et al., 2021). When β-TT is present, the ektacytometry curve is displaced to the left β-TT Beta-thalassemia trait 5.6923 0.954 66–75 with respect to healthy RBC, revealing a decrease in the RBC IDA Iron deficiency anemia 4.3391 0.782 66–79 deformability capacity. Control Healthy blood 2.8272 0.880 90–92 The osmotic gradient ektacytometry analysis shown in Figure 11 was performed using the Osmoscan module of the LoRRca MaxSis (RR Mechatronics). By measuring Deformability Changes in elongation index, LoRRCA can detect individual erythrocyte Beta-Thalassemia Trait and Iron deformability in a mixture of RBCs. When β-TT is present, Deficiency Anemia the ektacytometry curve is displaced to the left with respect To verify that the differences in viscosity found between β-TT, to healthy RBC. IDA samples, however, show a shift that put IDA, and healthy donors are caused by changes in the properties them in between β-TT and the control samples. By observing of RBCs, we compare the results obtained with the LoRRCA Figures 9, 11, it is possible to establish that alterations in ektacytometer between the samples. By measuring the elongation RBC wall rigidity can be translated into viscosity changes. index, the LoRRCA can detect elasticity changes in single cells. After normalizing the hct (%), the viscosity of samples for The measurements performed determine elongation of a huge IDA falls below the viscosity of β-TT and over the viscosity of number of RBCs utilizing laser detection, at different osmolarity control samples. As seen in Figure 10, β-TT samples have a values, as illustrated in Figure 10. higher viscosity than control samples. This is consistent with The elongation index (EI) depicted in Figure 10 is determined samples that appear to have a left shift in their ektacytometry by the expression: measurements. Observing the two results together lets us A−B have a bigger picture of the effects of single cell rheology. EI = (10) LoRRCA is very powerful at finding individual differences A+B within cells. The results obtained in this study, demonstrate where A and B are the major and minor dimensions of the RBC, that our method can detect the presence of these alterations respectively. With this test, it is possible to obtain a characteristic through the study of the fluid front rheology of the whole profile of each sample, according to the deformability of the RBCs blood. Therefore, the method proposed can distinguish as a function of osmolarity. These results do not depend on the differences between healthy blood and blood affected by hematocrit value of the samples. pathologies that modify the red blood cell rheology. Changes Figure 11 shows the Osmoscan curve for the healthy in viscosity seem to have a direct relation to individual cells’ subjects, IDA samples and β-TT samples. These results were changes in β-TT. Frontiers in Physiology | www.frontiersin.org 9 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA FIGURE 10 | RBC elongation index evolution as the osmolarity increases using LoRRCA. 0,7 0,6 0,5 0,4 EI 0,3 0,2 Healthy sample 0,1 Beta thalassemia Iron Deficiency Anemia 0 50 100 150 200 250 300 350 400 450 500 550 Osmolarity (mOsm/kg) FIGURE 11 | Osmoscan curve obtained from LoRRCA. Ten samples of β-TT, five samples of IDA and five samples from healthy donors were used. IDA curve adapted from Payán-Pernía et al. (2021). CONCLUSION differentiating three sets of samples, from healthy donors, β-TT and IDA patients. Using a microfluidic method we have Through this study, we have seen that the micro-rheometer been able to distinguish between samples with different RBCs presented here has great potential as a diagnostic tool abnormalities, despite the fact that the donors of each set for hematological diseases. This has been demonstrated by have different ages and distinct hct (%). Comparison with a Frontiers in Physiology | www.frontiersin.org 10 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA standardized red blood cell elasticity characterization method, comparable to those delivered by standard diagnostic techniques, the LoRRCA ektacytometer, has allowed us to verify that our such as LoRRCA, which is the gold standard method for findings were correct. ektacytometry evaluation of RBCs. The results obtained are The sample characterization techniques used in this paper important for the development of a functional point-of-care are based on the use of normalized curves, differentiated diagnosis device for the fast and effective detection of hemolytic for distinct pathologies. Using a mathematical method for anemias such as IDA and β-TT. PoC devices can provide a very hematocrit normalization (Trejo-Soto and Hernández-Machado, positive outcome for populations located in remote areas of the 2021), a single viscosity curve is calculated for healthy donors. world where the access to resources is limited. Diagnostic tools Using the same method, a normalized viscosity curve of β-TT that provide fast and reliable results constitute an easy way to is obtained. The hematocrit normalized viscosity ηhct , does not keep the follow up of patients up to date, without the need of contain the effects caused by hematocrit levels. This was made to commuting and the use of hospital facilities. In the near future, perform an adequate comparison between samples from the same a cheap, easy to use, and small device can be used for both triage or different patients, both in healthy and non-healthy conditions, in hospitals and at home by patients suffering of RBC altering independent of their hct (%). Thanks to this method, we obtained conditions such IDA and β-TT. curves with clearly differentiated parameters for healthy blood, β-TT, and IDA. The experimental results herein obtained, show that the DATA AVAILABILITY STATEMENT MCV seems to affect the viscosity of the samples. Samples with distinct MCV did not follow the normalized curve path. Once The original contributions presented in the study are included the samples were segregated into three groups based on their in the article/supplementary material, further inquiries can be MCV, a clear pattern showed up. As a general observation, lower directed to the corresponding author/s. MCV accounted for higher viscosity values. For this motive, it is reasonable to do a comparison between β-TT and IDA samples with similar MCV only. It was found, however, that ETHICS STATEMENT even at comparable MCV and after hematocrit normalization, β-TT has a higher viscosity than both IDA and control samples. The studies involving human participants were reviewed This difference in viscosity might be caused by differences in and approved by the Ethics Committee of IJC [Comité the affected deformation capability of RBCs and the membrane Ético de Investigación Clínica (CEIC)] and the Bioethics changes caused by the α chains disorders that characterize β-TT Committee of the University of Barcelona (IRB 00003099). The (Payán-Pernía et al., 2021). patients/participants provided their written informed consent to Reasoning on the basis that high blood viscosity might be participate in this study. caused by changes in the RBC wall rigidity, it is plausible to infer that these differences may be reflected in an ektacytometry analysis. It was found that the osmotic gradient curve obtained AUTHOR CONTRIBUTIONS by LoRRCA for IDA samples is shifted to the left of the curve for healthy donors and to the right of the curve for β-TT patients, AH-M and J-LV-C conceived the study. LM-M and MC-F reflecting that the rigidity of RBCs in IDA samples is higher than performed the experiments, processed the data, and wrote the that of healthy donors, and at the same time smaller than the manuscript. CR-L and JF-T helped to interpret the results. rigidity of RBCs in β-TT samples. This is compatible with the EK collected and analyzed the samples prepared by IH-R viscosity results in which IDA samples have a lower viscosity than and CM-I. SP-P, TA, AH-M, MC-F, and CT-S supervised the β-TT patients and higher than healthy donors. The differences research work and revised the results and discussion. All authors observed in viscosity between the samples analyzed could be a contributed to the manuscript revision, read, and approved the result of changes in the rigidity of the RBCs when β-TT is present submitted version. (Payán-Pernía et al., 2021). The general conclusion of this work is that the micro- rheometer is a promising tool for early detection of different FUNDING blood diseases can differentiate between two types of blood diseases, β-TT and IDA, regardless their hematocrit level and LM-M and JF-T received funding from programs Doctorat the presence of microcytosis. It has been also demonstrated Industrial (2018 DI 068) and (2018 DI 064) from AGAUR that blood viscosity is an accurate indicator of the blood health (Generalitat de Catalunya). EK receives funding from Institut condition, especially when the pathology in study targets the RBC Josep Carreras (IJC) under program Equality Plus, project and affects its shape, deformation capacity and size. Furthermore, number 2019-1-TR01-KA202-076789. TA acknowledges funding the samples show a clear difference when compared to healthy under grant numbers MTM2015-71509-C2-1-R and MDM- samples, by using the microrheology technique described. 2014-0445. TA has been partially funded by the CERCA Program A correct characterization on blood has been made through an of the Generalitat de Catalunya. AH-M acknowledges funding adequate setup, without the need of complex equipment and with under project FIS2016-78883-C2-1P, Ministerio de Ciencia e just a small sample. At the same time, the results obtained are Innovacion (Spain) under project PID2019-106063GB-100 and Frontiers in Physiology | www.frontiersin.org 11 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA AGAUR (Generalitat de Catalunya) under project 2017 SGR- ACKNOWLEDGMENTS 1061. CT-S and AH-M acknowledge partial support from ANID/PCI (Chile) under project MEC80180021. The authors thank Rheo D. X. for making this research possible. REFERENCES Lázaro, G. R., Hernández-Machado, A., and Pagonabarraga, I. (2019). Collective behavior of red blood cells in confined channels. Eur. Phys. J. E 42, 1–9. doi: Bartolo, D., and Aarts, D. G. A. L. (2012). Microfluidics and soft matter: 10.1140/epje/i2019-11805-0 small is useful. Soft Matter 8, 10530–10535. doi: 10.1039/c2sm26 Lázaro, G. R., Melzak, K. A., Toca-Herrera, J. L., Pagonabarraga, I., and Hernández- 157j Machado, A. (2013). Elastic energies and morphologies of the first stages of Baskurt, O. K., and Meiselman, H. J. (2003). Blood rheology and the discoechinocyte transition. Soft Matter 9, 6430–6441. doi: 10.1039/c3sm50 hemodynamics. Semin. Thromb. Hemost. 29, 435–450. doi: 10.1055/s-2003- 716e 44551 Llaudet-Planas, E., Vives-Corrons, J. L., Rizzuto, V., Gómez-Ramírez, P., Sevilla Berga, L., Vives Corrons, J. L., Feliu, E., and Woessner, S. (1989). Navarro, J., Coll Sibina, M. T., et al. (2018). Osmotic gradient ektacytometry: Hemorheología. Bases teóricas y Aplicaciones Clínicas. Available online at: a valuable screening test for hereditary spherocytosis and other red blood https://scholar.google.es/scholar?lookup=0&q=Hemorreología+.+Bases+ cell membrane disorders. Int. J. Lab. Hematol. 40, 94–102. doi: 10.1111/ijlh. teóricas+y+aplicaciones+clínicas.+1983.&hl=es&as_sdt=0,5&as_ylo=1970&as 12746 _yhi=1985 (accessed November 15, 2020). Macosko, C. W. (1994). RHEOLOGY Principles, Measurements, and Applications. Choi, S., and Park, J. K. (2010). Microfluidic rheometer for characterization of Hoboken, NY: Wiley. protein unfolding and aggregation in microflows. Small 6, 1306–1310. doi: Mehri, R., Mavriplis, C., and Fenech, M. (2018). Red blood cell aggregates and their 10.1002/smll.201000210 effect on non-Newtonian blood viscosity at low hematocrit in a two-fluid low Cokelet, G. R., and Meiselman, H. J. (2007). “Macro- and micro-rheological shear rate microfluidic system. PLoS One 13:e0199911. doi: 10.1371/journal. properties of blood,” in Handbook of Hemorheology and Hemodynamics, eds pone.0199911 O. K. Baskurt, M. R. Hardeman, M. W. Rampling, and H. J. Meiselman, Méndez-Mora, L., Cabello-Fusarés, M., Ferré-Torres, J., Riera-Llobet, C., Lopez, S., (Amsterdam: IOS Press), 45–71. Trejo-Soto, C., et al. (2021). Microrheometer for biofluidic analysis: electronic Davies, G. A., and Stokes, J. R. (2008). Thin film and high shear rheology of detection of the fluid-front advancement. Micromachines 12:726. doi: 10.3390/ multiphase complex fluids. J. Nonnewton. Fluid Mech. 148, 73–87. doi: 10.1016/ mi12060726 j.jnnfm.2007.04.013 Nagababu, E., Gulyani, S., Earley, C. J., Cutler, R. G., Mattson, M. P., and DeLoughery, T. G. (2017). Iron deficiency anemia. Med. Clin. North Am. 101, Rifkind, J. M. (2008). Iron-deficiency anaemia enhances red blood cell 319–332. doi: 10.1016/j.mcna.2016.09.004 oxidative stress. Free Radic. Res. 42, 824–829. doi: 10.1080/1071576080245 Diez-Silva, M., Dao, M., Han, J., Lim, C. T., and Suresh, S. (2010). Shape and 9879 biomechanics characteristics of human red blood cells in health and disease. Payán-Pernía, S., Krishnevskaya, E., Hernández-Rodríguez, I., Remacha Sevilla, MRS Bull. 35, 382–388. doi: 10.1557/mrs2010.571 ÁF., Ancochea Serra, Á, Morales-Indiano, C., et al. (2021). Distinguishing iron Faustino, V., Rodrigues, R. O., Pinho, D., Costa, E., Santos-Silva, A., Miranda, V., deficiency from beta-thalassemia trait by new generation ektacytometry. Int. J. et al. (2019). A microfluidic deformability assessment of pathological red blood Lab. Hematol. 43, e58–e60. doi: 10.1111/ijlh.13362 cells flowing in a hyperbolic converging microchannel. Micromachines 10:645. Pipe, C. J., and McKinley, G. H. (2009). Microfluidic rheometry. doi: 10.3390/mi10100645 Mech. Res. Commun. 36, 110–120. doi: 10.1016/j.mechrescom.2008. Fedosov, D. A., Pan, W., Caswell, B., Gompper, G., and Karniadakis, G. E. (2011). 08.009 Predicting human blood viscosity in silico. Proc. Natl. Acad. Sci. U.S.A. 108, Pop, G. A. M., Duncker, D. J., Gardien, M., Vranckx, P., Versluis, S., Hasan, D., et al. 11772–11777. doi: 10.1073/pnas.1101210108 (2002). The clinical significance of whole blood viscosity in (cardio)vascular Fiorelli, G., Turrini, F., Mannu, F., Porro, F., Graziadei, G., Tavazzi, D., et al. (1996). medicine. Neth. Heart J. 10, 512–516. Erythrocyte membrane alterations in thalassemia intermedia. Clin. Hemorheol. Qin, D., Xia, Y., and Whitesides, G. M. (2010). Soft lithography for micro- and 16, 789–797. nanoscale patterning. Nat. Protoc. 5, 491–502. Galanello, R., and Origa, R. (2010). Beta-thalassemia. Orphanet J. Rare Dis. 5:11. Rachmilewitz, E. A., and Kahane, I. (1980). The red blood cell membrane in doi: 10.1186/1750-1172-5-11 thalassaemia. Br. J. Haematol. 46, 1–6. doi: 10.1111/j.1365-2141.1980.tb05 Galanello, R., Dessi, E., Melis, M., Addis, M., Sanna, M., Rosatelli, C., et al. (1989). 928.x Molecular analysis of beta zero-thalassemia intermedia in Sardinia. Blood 74, Rasia, R. J., Porta, P. E., and García Rosasco, M. (1986). Shear deformation 823–827. doi: 10.1182/blood.v74.2.823.823 measurement of suspended particles: application to erythrocytes. Rev. Sci. Galindo-Rosales, F. J., Campo-Deaño, L., Pinho, F. T., Van Bokhorst, E., Instrum. 57, 33–35. doi: 10.1063/1.1139113 Hamersma, P. J., Oliveira, M. S. N., et al. (2012). Microfluidic systems for Rico, L. G., Juncà, J., Ward, M. D., Bradford, J. A., Bardina, J., and Petriz, the analysis of viscoelastic fluid flow phenomena in porous media. Microfluid. J. (2018). Acoustophoretic orientation of red blood cells for diagnosis of Nanofluidics 12, 485–498. doi: 10.1007/s10404-011-0890-6 red cell health and pathology. Sci. Rep. 8:15705. doi: 10.1038/s41598-018- Hymel, S. J., Lan, H., and Khismatullin, D. B. (2020). Elongation index as a sensitive 33411-0 measure of cell deformation in high-throughput microfluidic systems. Biophys. Rodriguez-Villarreal, A. I., Ortega-Tana, L., Cid, J., Hernandez-Machado, A., J. 119, 493–501. doi: 10.1016/j.bpj.2020.06.027 Alarcon-Cor, T., Miribel-Catala, P., et al. (2020). An integrated detection Iborra, A., Falcó, J., Moreno, C., and Bolufer, I. (2003). Rheological behaviour of red method for flow viscosity measurements in microdevices. IEEE Trans. Biomed. blood cells in β and δβ thalassemia trait. Clin. Hemorheol. Microcirc. 28, 71–78. Eng. 68, 2049–2057. doi: 10.1109/TBME.2020.3013519 Kassebaum, N. J., Fleming, T. D., Flaxman, A., Phillips, D. E., Steiner, C., Barber, Simmonds, M. J., Meiselman, H. J., and Baskurt, O. K. (2013). Blood rheology and R. M., et al. (2016). The global burden of anemia. Hematol. Oncol. Clin. North aging. J. Geriatr. Cardiol. 10, 291–301. doi: 10.3969/j.issn.1671-5411.2013.03. Am. 30, 247–308. doi: 10.1016/J.HOC.2015.11.002 010 Késmárky, G., Kenyeres, P., Rábai, M., and Tóth, K. (2008). Plasma viscosity: a Srivastava, N., and Burns, M. A. (2006). Analysis of non-Newtonian liquids using forgotten variable. Clin. Hemorheol. Microcirc. 39, 243–246. doi: 10.3233/CH- a microfluidic capillary viscometer. Anal. Chem. 78, 1690–1696. doi: 10.1021/ 2008-1088 ac0518046 Lázaro, G. R., Hernández-Machado, A., and Pagonabarraga, I. (2014). Rheology Tomaiuolo, G. (2014). Biomechanical properties of red blood cells in health of red blood cells under flow in highly confined microchannels: I. Effect of and disease towards microfluidics. Biomicrofluidics 8:051501. doi: 10.1063/1. elasticity. Soft Matter 10, 7195–7206. doi: 10.1039/c4sm00894d 4895755 Frontiers in Physiology | www.frontiersin.org 12 October 2021 | Volume 12 | Article 761411 Méndez-Mora et al. Rheological Characterization of β-TT and IDA Trejo-Soto, C. A., Costa Miracle, E., Rodríguez Villarreal, ÁI., Cid Vidal, J., Conflict of Interest: The authors declare that the research was conducted in the Castro Ponce, M., Alarcón Cor, T., et al. (2018). Front microrheology of absence of any commercial or financial relationships that could be construed as a biological fluids. J. Phys. D. 1043:012058. doi: 10.1088/1742-6596/1043/1/01 potential conflict of interest. 2058 Trejo-Soto, C., and Hernández-Machado, A. (2021). Normalization of Blood The handling editor declared a past collaboration with one of the author, J-LV-C. Viscosity According to the Hematocrit and the Biomechanical Properties of Red Blood Cells. United Kingdom: Physiological Measurement. Publisher’s Note: All claims expressed in this article are solely those of the authors Trejo-Soto, C., Costa-Miracle, E., Rodriguez-Villarreal, I., Cid, J., Castro, M., and do not necessarily represent those of their affiliated organizations, or those of Alarcon, T., et al. (2017). Front microrheology of the non-Newtonian behaviour the publisher, the editors and the reviewers. Any product that may be evaluated in of blood: scaling theory of erythrocyte aggregation by aging. Soft Matter 13, this article, or claim that may be made by its manufacturer, is not guaranteed or 3042–3047. doi: 10.1039/c6sm02412b endorsed by the publisher. Vitamin and Mineral Nutrition Information System (VMNIS) (2011). WHO. Haemoglobin Concentrations For the Diagnosis of Anaemia and Assessment of Copyright © 2021 Méndez-Mora, Cabello-Fusarés, Ferré-Torres, Riera-Llobet, Severity Vitamin and Mineral Nutrition Information System. Geneva: World Krishnevskaya, Trejo-Soto, Payán-Pernía, Hernández-Rodríguez, Morales-Indiano, Health Organization. Alarcón, Vives-Corrons and Hernandez-Machado. This is an open-access article Wagley, P. F. (1953). Iron deficiency anemia. Md. State Med. J. 2, 351–355. doi: distributed under the terms of the Creative Commons Attribution License (CC BY). 10.1016/B978-0-12-801238-3.05104-7 The use, distribution or reproduction in other forums is permitted, provided the Williams, T. N., and Weatherall, D. J. (2012). World distribution, population original author(s) and the copyright owner(s) are credited and that the original genetics, and health burden of the hemoglobinopathies. Cold Spring Harb. publication in this journal is cited, in accordance with accepted academic practice. No Perspect. Med. 2:a011692. doi: 10.1101/cshperspect.a011692 use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Physiology | www.frontiersin.org 13 October 2021 | Volume 12 | Article 761411