Influence of storage and buffer composition on the mechanical behavior of flowing red blood cells

Impact of anti-coagulant choice on blood elongational behavior

Blood is a highly complex fluid with rheological properties that have a significant impact on various flow phenomena. In particular, it exhibits a non-Newtonian elongational viscosity that is comparable to polymer solutions. In this study, we investigate the effect of three different anticoagulants, namely EDTA (ethylene diamine tetraacetic acid), heparin, and citrate, on the elongational properties of both human and swine blood. We observe a unique two stage thinning process and a strong dependency of the characteristic relaxation time on the chosen anticoagulant, with the longest relaxation time and thus the highest elongational viscosity being found for the case of citrate. Our findings for the latter are consistent with the physiological values obtained from a dripping droplet of human blood without any anticoagulant. Furthermore, our study resolves the discrepancy found in the literature regarding the reported range of characteristic relaxation times, confirming that the elongational viscosity must be taken into account for a full rheological characterization of blood. These results have important implications for understanding blood flow in various physiological, pathological and technological conditions.

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.