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1. The effect of rigid cells on blood viscosity: linking rheology and sickle cell anemia

   https://doi.org/10.1039/d1sm01299a  

   Perazzo, Antonio ; Peng, Zhangli ; Young, Y.-N. ; Feng, Zhe ; Wood, David K. ; Higgins, John M. ; Stone, Howard A. ( January 2022 , Soft Matter)

   Sickle cell anemia (SCA) is a disease that affects red blood cells (RBCs). Healthy RBCs are highly deformable objects that under flow can penetrate blood capillaries smaller than their typical size. In SCA there is an impaired deformability of some cells, which are much stiffer and with a different shape than healthy cells, and thereby affect regular blood flow. It is known that blood from patients with SCA has a higher viscosity than normal blood. However, it is unclear how the rigidity of cells is related to the viscosity of blood, in part because SCA patients are often treated withmore »transfusions of variable amounts of normal RBCs and only a fraction of cells will be stiff. Here, we report systematic experimental measurements of the viscosity of a suspension varying the fraction of rigid particles within a suspension of healthy cells. We also perform systematic numerical simulations of a similar mixed suspension of soft RBCs, rigid particles, and their hydrodynamic interactions. Our results show that there is a rheological signature within blood viscosity to clearly identify the fraction of rigidified cells among healthy deformable cells down to a 5% volume fraction of rigidified cells. Although aggregation of RBCs is known to affect blood rheology at low shear rates, and our simulations mimic this effect via an adhesion potential, we show that such adhesion, or aggregation, is unlikely to provide a physical rationalization for the viscosity increase observed in the experiments at moderate shear rates due to rigidified cells. Through numerical simulations, we also highlight that most of the viscosity increase of the suspension is due to the rigidity of the particles rather than their sickled or spherical shape. Our results are relevant to better characterize SCA, provide useful insights relevant to rheological consequences of blood transfusions, and, more generally, extend to the rheology of mixed suspensions having particles with different rigidities, as well as offering possibilities for developments in the field of soft material composites.« less
2. Rheology of bacterial suspensions under confinement

   https://doi.org/10.1007/s00397-019-01155-x  

   Liu, Zhengyang ; Zhang, Kechun ; Cheng, Xiang ( June 2019 , Rheologica Acta)

   As a paradigmatic model of active fluids, bacterial suspensions show intriguing rheological responses drastically different from their counterpart colloidal suspensions. Although the flow of bulk bacterial suspensions has been extensively studied, the rheology of bacterial suspensions under confinement has not been experimentally explored. Here, using a microfluidic viscometer, we systematically measure the rheology of dilute Escherichia coli suspensions under different degrees of confinement. Our study reveals a strong confinement effect: the viscosity of bacterial suspensions decreases substantially when the confinement scale is comparable or smaller than the run length of bacteria. Moreover, we also investigate the microscopic dynamics of bacterialmore »suspensions including velocity profiles, bacterial density distributions, and single bacterial dynamics in shear flows. These measurements allow us to construct a simple heuristic model based on the boundary layer of upstream swimming bacteria near confining walls, which qualitatively explains our experimental observations. Our study sheds light on the influence of the boundary layer of collective bacterial motions on the flow of confined bacterial suspensions. Our results provide a benchmark for testing different rheological models of active fluids and are useful for understanding the transport of microorganisms in confined geometries.« less
3. Contamination in Sodium Dodecyl Sulfate Solutions: Insights from the Measurements of Surface Tension and Surface Rheology

   https://doi.org/https://pubs.acs.org/doi/10.1021/acs.langmuir.2c00460?goto=supporting-info  

   Elton L. Correia, Nick Brown ( May 2022 , Langmuir)

   The presence of contamination in sodium dodecyl sulfate (SDS) solutions in the form of dodecanol (LOH) is known to drastically affect the resulting interfacial properties such as surface tension (SFT) and rheology. Dodecanol molecules, which are the product of SDS hydrolysis and are inherently present in SDS solutions, have higher surface activity compared to SDS because they are less soluble in water. A characteristic dip in the SFT isotherm is an indicator of the dodecanol contamination in the sample. The presence of an electrolyte in the solution impacts the surface activity of SDS and its critical micelle concentration, and couldmore »yield SFT isotherms that closely match those obtained for pure SDS samples. The interpretation of the isotherms in such cases could thus lead to misinterpretation of the surface purity. In this work, we have examined the SFT isotherms for SDS solutions in both the absence and presence of electrolyte. We have fitted the isotherms to three different thermodynamic adsorption models to estimate the amount of dodecanol present in the sample. We have applied the estimated values for the LOH content in a two-component rheological model to predict the viscoelasticity of such surfactant-laden surfaces. We have compared these results with the experimentally measured interfacial rheological properties. Our findings demonstrate that the presence of impurities can be captured under dynamic expansion and contractions, even for solutions containing background electrolyte.« less
4. Propulsion of an elastic filament in a shear-thinning fluid

   https://doi.org/10.1039/d0sm02130j  

   Qin, Ke ; Peng, Zhiwei ; Chen, Ye ; Nganguia, Herve ; Zhu, Lailai ; Pak, On Shun ( April 2021 , Soft Matter)

   Some micro-organisms and artificial micro-swimmers propel at low Reynolds numbers (Re) via the interaction of their flexible appendages with the surrounding fluid. While their locomotion has been extensively studied with a Newtonian fluid assumption, in realistic biological environments these micro-swimmers invariably encounter rheologically complex fluids. In particular, many biological fluids such as blood and different types of mucus have shear-thinning viscosities. The influence of this ubiquitous non-Newtonian rheology on the performance of flexible swimmers remains largely unknown. Here, we present a first study to examine how shear-thinning rheology alters the fluid-structure interaction and hence the propulsion performance of elastic swimmersmore »at low Re. Via a simple elastic swimmer actuated magnetically, we demonstrate that shear-thinning rheology can either enhance or hinder elastohydrodynamic propulsion, depending on the intricate interplay between elastic and viscous forces as well as the magnetic actuation. We also use a reduced-order model to elucidate the mechanisms underlying the enhanced and hindered propulsion observed in different physical regimes. These results and improved understanding could guide the design of flexible micro-swimmers in non-Newtonian fluids.« less
5. A Deep Learning Framework for Sickle Cell Disease Microfluidic Biomarker Assays

   https://doi.org/10.1182/blood-2020-141693  

   Praljak, Niksa ; Shipley, Brandon ; Gonzales, Ayesha ; Goreke, Utku ; Iram, Shamreen ; Singh, Gundeep ; Hill, Ailis ; Gurkan, Umut A. ; Hinczewski, Michael ( November 2020 , Blood)

   Introduction: Vaso-occlusive crises (VOCs) are a leading cause of morbidity and early mortality in individuals with sickle cell disease (SCD). These crises are triggered by sickle red blood cell (sRBC) aggregation in blood vessels and are influenced by factors such as enhanced sRBC and white blood cell (WBC) adhesion to inflamed endothelium. Advances in microfluidic biomarker assays (i.e., SCD Biochip systems) have led to clinical studies of blood cell adhesion onto endothelial proteins, including, fibronectin, laminin, P-selectin, ICAM-1, functionalized in microchannels. These microfluidic assays allow mimicking the physiological aspects of human microvasculature and help characterize biomechanical properties of adhered sRBCsmore »under flow. However, analysis of the microfluidic biomarker assay data has so far relied on manual cell counting and exhaustive visual morphological characterization of cells by trained personnel. Integrating deep learning algorithms with microscopic imaging of adhesion protein functionalized microfluidic channels can accelerate and standardize accurate classification of blood cells in microfluidic biomarker assays. Here we present a deep learning approach into a general-purpose analytical tool covering a wide range of conditions: channels functionalized with different proteins (laminin or P-selectin), with varying degrees of adhesion by both sRBCs and WBCs, and in both normoxic and hypoxic environments. Methods: Our neural networks were trained on a repository of manually labeled SCD Biochip microfluidic biomarker assay whole channel images. Each channel contained adhered cells pertaining to clinical whole blood under constant shear stress of 0.1 Pa, mimicking physiological levels in post-capillary venules. The machine learning (ML) framework consists of two phases: Phase I segments pixels belonging to blood cells adhered to the microfluidic channel surface, while Phase II associates pixel clusters with specific cell types (sRBCs or WBCs). Phase I is implemented through an ensemble of seven generative fully convolutional neural networks, and Phase II is an ensemble of five neural networks based on a Resnet50 backbone. Each pixel cluster is given a probability of belonging to one of three classes: adhered sRBC, adhered WBC, or non-adhered / other. Results and Discussion: We applied our trained ML framework to 107 novel whole channel images not used during training and compared the results against counts from human experts. As seen in Fig. 1A, there was excellent agreement in counts across all protein and cell types investigated: sRBCs adhered to laminin, sRBCs adhered to P-selectin, and WBCs adhered to P-selectin. Not only was the approach able to handle surfaces functionalized with different proteins, but it also performed well for high cell density images (up to 5000 cells per image) in both normoxic and hypoxic conditions (Fig. 1B). The average uncertainty for the ML counts, obtained from accuracy metrics on the test dataset, was 3%. This uncertainty is a significant improvement on the 20% average uncertainty of the human counts, estimated from the variance in repeated manual analyses of the images. Moreover, manual classification of each image may take up to 2 hours, versus about 6 minutes per image for the ML analysis. Thus, ML provides greater consistency in the classification at a fraction of the processing time. To assess which features the network used to distinguish adhered cells, we generated class activation maps (Fig. 1C-E). These heat maps indicate the regions of focus for the algorithm in making each classification decision. Intriguingly, the highlighted features were similar to those used by human experts: the dimple in partially sickled RBCs, the sharp endpoints for highly sickled RBCs, and the uniform curvature of the WBCs. Overall the robust performance of the ML approach in our study sets the stage for generalizing it to other endothelial proteins and experimental conditions, a first step toward a universal microfluidic ML framework targeting blood disorders. Such a framework would not only be able to integrate advanced biophysical characterization into fast, point-of-care diagnostic devices, but also provide a standardized and reliable way of monitoring patients undergoing targeted therapies and curative interventions, including, stem cell and gene-based therapies for SCD. Disclosures Gurkan: Dx Now Inc.: Patents & Royalties; Xatek Inc.: Patents & Royalties; BioChip Labs: Patents & Royalties; Hemex Health, Inc.: Consultancy, Current Employment, Patents & Royalties, Research Funding.« less