Flows of healthy and hardened RBC suspensions through a micropillar array

Red blood cell (RBC) deformability is an important haemorheological factor; it is impaired in many pathologies leading to microvascular complications. Several microfluidic platforms have been utilized to examine the role of deformability in RBC flows but their geometries tend to be simplified. In the present study, we extend our previous work on healthy RBC flows in micropillar arrays [1] to probe the effect of impaired RBC deformability on the velocity and haematocrit distributions in microscale RBC flows. Healthy and artificially hardened RBC suspensions at 25% haematocrit were perfused through the micropillar array at various flow rates and imaged. RBC velocities were determined by Particle Image Velocimetry (PIV) and haematocrit distributions were inferred from the image intensity distributions. The pillars divide the flow into two distinct RBC streams separated by a cell-depleted region along the centreline and in the rear/front stagnation points. RBC deformability was not found to significantly affect the velocity distributions; the shape of the velocity profiles in the interstitial space remained the same for healthy and hardened RBCs. Time-averaged and spatiotemporal intensity distributions, however, reveal differences in the dynamics and local distributions of healthy and hardened cells; hardened cells appear to enter the cell-depleted regions more frequently and their interstitial distributions are more uniform. The study highlights the importance of local RBC distributions and the impact of RBC deformability on cell transport in complex microscale flows

Machine Learning in Predicting Printable Biomaterial Formulations for Direct Ink Writing

Three-dimensional (3D) printing is emerging as a transformative technology for biomedical engineering. The 3D printed product can be patient-specific by allowing customizability and direct control of the architecture. The trial-and-error approach currently used for developing the composition of printable inks is time- and resource-consuming due to the increasing number of variables requiring expert knowledge. Artificial intelligence has the potential to reshape the ink development process by forming a predictive model for printability from experimental data. In this paper, we constructed machine learning (ML) algorithms including decision tree, random forest (RF), and deep learning (DL) to predict the printability of biomaterials. A total of 210 formulations including 16 different bioactive and smart materials and 4 solvents were 3D printed, and their printability was assessed. All ML methods were able to learn and predict the printability of a variety of inks based on their biomaterial formulations. In particular, the RF algorithm has achieved the highest accuracy (88.1%), precision (90.6%), and F1 score (87.0%), indicating the best overall performance out of the 3 algorithms, while DL has the highest recall (87.3%). Furthermore, the ML algorithms have predicted the printability window of biomaterials to guide the ink development. The printability map generated with DL has finer granularity than other algorithms. ML has proven to be an effective and novel strategy for developing biomaterial formulations with desired 3D printability for biomedical engineering applications

Development of Vortex Bioreactor Technology for Decentralised Water Treatment

The vortex bioreactor (VBR) is a simple decentralised water treatment system (DeWaTS) that sits at the interface between swirl flow, biotechnology and chemical engineering. The device utilises swirl flow and suspended activated beads to achieve downstream water processing and has been tested for applications including centrifugal-driven separation, pathogen neutralisation and metal absorption. The VBR was optimised for the treatment of faecally contaminated effluents in the developing world, and the design features related to the key challenges faced by the wastewater industry are highlighted here. The VBR has two aspects that can be modified to generate different reactor conditions: the impeller, where the swirl flow is modified through alterations of rotation speed, and impeller geometry and the suspended activated beads, which facilitate mixing and alter the reactor surface area. Data from testing for some of the different applications mentioned above are presented here, and future planned developments for the technology are discussed

Bimodal vortex shedding in a perturbed cylinder wake

Cylinder wakes display distinct modes of vortex shedding when perturbed by appropriate means. By investigating experimentally the wake of a circular cylinder perturbed by a periodic fluctuation imposed on the inflow velocity, it is shown that bimodal behavior is possible. During a given experiment, the wake switches back and forth between two different vortex shedding modes, more specifically, a 2S <-> 2P transition is observed. No discernible change in the timing of vortex formation is found to accompany the transition. Modal decomposition of the velocity field is employed to exemplify the interaction of the imposed symmetrical perturbation and the intrinsic antisymmetrical instability of the near wake. (c) 2007 American Institute of Physics

Spatial variation of blood viscosity: Modelling using shear fields measured by a mu PIV based technique

The spatial characteristics of blood viscosity were investigated by combining a newly developed constitutive equation with shear deformation fields calculated from velocity measurements obtained by a mu PIV based technique. Blood at physiological hematocrit levels and in the presence of aggregation was sheared in a narrow gap plate-plate geometry and the velocity and aggregation characteristics were determined from images captured using a high resolution camera. Changes in the microstructure of blood caused by aggregation were observed to affect the flow characteristics. At low shear rates, high aggregation and network formation caused the RBC motion to become essentially two-dimensional. The measured velocity fields were used to estimate the magnitude of shear which was subsequently used in conjunction with the new model to assess the spatial variation of viscosity across the flow domain. It was found that the non-uniform microstructural characteristics of blood influence its viscosity distribution accordingly. The viscosity of blood estimated in the core of the examined flow, using a zero-gradient core velocity profile assumption, was found to be significantly higher than the overall effective viscosity determined using other velocity profile assumptions. (C) 2010 IPEM. Published by Elsevier Ltd. All rights reserved

Coupled human erythrocyte velocity field and aggregation measurements at physiological haematocrit levels

Simultaneous measurement of erythrocyte (RBC) velocity fields and aggregation properties has been successfully performed using an optical shearing microscope and Particle Image Velocimetry (PIV). Blood at 45% haematocrit was sheared at rates of 5.4 or = 54.0 s(-1), while high levels of aggregation and network formation occurred for gamma or = 5.4 s(-1) to deviate markedly from the expected solid body rotation profile. The effect of aggregation level on the PIV accuracy was assessed by monitoring the two-dimensional (2D) correlation coefficients. Lower levels of aggregation result in poorer image correlation, from which it can be inferred that PIV accuracy is reduced. Moreover, aggregation is time-dependent, and consequently PIV accuracy may decrease during recording as the cells break up. It is therefore recommended that aggregation and its effects are taken into account in future when undertaking blood flow studies using PIV. The simplicity of the technique, which requires no lasers, filters, or special pretreatments, demonstrates the potential wide-spread applicability of the data acquisition system for accurate blood flow PIV and aggregation measurement