Intermediate regime and a phase diagram of red blood cell dynamics in a linear flow

Classification of chemically modified red blood cells in microflow using machine learning video analysis

We classify native and chemically modified red blood cells with an AI based video classifier. Using TensorFlow video analysis enables us to capture not only the morphology of the cell but also the trajectories of motion of individual red blood cells and their dynamics. We chemically modify cells in three different ways to model different pathological conditions and obtain classification accuracies for all three classification tasks of more than 90% between native and modified cells. Unlike standard cytometers that are based on immunophenotyping our microfluidic cytometer allows to rapidly categorize cells without any fluorescence labels simply by analysing the shape and flow of red blood cells.

Characterisation of hydrodynamic trapping in microfluidic cross-slot devices for high strain rate applications

Hydrodynamic trapping of a particle or cluster of particles based on contact and non-contact approaches has brought prominent insights to micro-nano scale applications. Of the non-contact methods, image-based real-time control in cross-slot microfluidic devices is one of the most promising potential platform for single cellular assays. Here, we report results from experiments conducted in two cross-slot microfluidic channels of different widths, with varying real-time delay of the control algorithm and different magnification. Sustained trapping of 5 μm diameter particles was achieved with high strain rates, of order 10² s^-1, higher than in any previous studies. Our experiments show that the maximum attainable strain rate is a function of the real-time delay of the control algorithm and the particle resolution (pixel/μm). Therefore, we anticipate that with further reduced time delays and enhanced particle resolution, considerably higher strain rates can be attained, opening the platform to single cellular assay studies where very high strain rates are required.

The stress-free state of human erythrocytes: Data-driven inference of a transferable RBC model

The stress-free state (SFS) of red blood cells (RBCs) is a fundamental reference configuration for the calibration of computational models, yet it remains unknown. Current experimental methods cannot measure the SFS of cells without affecting their mechanical properties, whereas computational postulates are the subject of controversial discussions. Here, we introduce data-driven estimates of the SFS shape and the visco-elastic properties of RBCs. We employ data from single-cell experiments that include measurements of the equilibrium shape of stretched cells and relaxation times of initially stretched RBCs. A hierarchical Bayesian model accounts for these experimental and data heterogeneities. We quantify, for the first time, the SFS of RBCs and use it to introduce a transferable RBC (t-RBC) model. The effectiveness of the proposed model is shown on predictions of unseen experimental conditions during the inference, including the critical stress of transitions between tumbling and tank-treading cells in shear flow. Our findings demonstrate that the proposed t-RBC model provides predictions of blood flows with unprecedented accuracy and quantified uncertainties.

Red blood cell shape transitions and dynamics in time-dependent capillary flows

The dynamics of single red blood cells (RBCs) determine microvascular blood flow by adapting their shape to the flow conditions in the narrow vessels. In this study, we explore the dynamics and shape transitions of RBCs on the cellular scale under confined and unsteady flow conditions using a combination of microfluidic experiments and numerical simulations. Tracking RBCs in a comoving frame in time-dependent flows reveals that the mean transition time from the symmetric croissant to the off-centered, nonsymmetric slipper shape is significantly faster than the opposite shape transition, which exhibits pronounced cell rotations. Complementary simulations indicate that these dynamics depend on the orientation of the RBC membrane in the channel during the time-dependent flow. Moreover, we show how the tank-treading movement of slipper-shaped RBCs in combination with the narrow channel leads to oscillations of the cell's center of mass. The frequency of these oscillations depends on the cell velocity, the viscosity of the surrounding fluid, and the cytosol viscosity. These results provide a potential framework to identify and study pathological changes in RBC properties.