Objective assessment of stored blood quality by deep learning

Stored red blood cells (RBCs) are needed for life-saving blood transfusions, but they undergo continuous degradation. RBC storage lesions are often assessed by microscopic examination or biochemical and biophysical assays, which are complex, time-consuming, and destructive to fragile cells. Here we demonstrate the use of label-free imaging flow cytometry and deep learning to characterize RBC lesions. Using brightfield images, a trained neural network achieved 76.7% agreement with experts in classifying seven clinically relevant RBC morphologies associated with storage lesions, comparable to 82.5% agreement between different experts. Given that human observation and classification may not optimally discern RBC quality, we went further and eliminated subjective human annotation in the training step by training a weakly supervised neural network using only storage duration times. The feature space extracted by this network revealed a chronological progression of morphological changes that better predicted blood quality, as measured by physiological hemolytic assay readouts, than the conventional expert-assessed morphology classification system. With further training and clinical testing across multiple sites, protocols, and instruments, deep learning and label-free imaging flow cytometry might be used to routinely and objectively assess RBC storage lesions. This would automate a complex protocol, minimize laboratory sample handling and preparation, and reduce the impact of procedural errors and discrepancies between facilities and blood donors. The chronology-based machine-learning approach may also improve upon humans’ assessment of morphological changes in other biomedically important progressions, such as differentiation and metastasis

Modeling a Hybrid Power System with Intermediate Energy Storage

The purpose of this work is to develop a model for balancing the processes of the generation and consumption of electricity, taking into account the random nature of these processes. The subject of the study is hybrid power systems that use traditional and renewable energy sources and have the properties of a local network. Such systems are sensitive to variable generation modes, and the presence of rapid changes in power requires short time intervals. The presence of wind and solar power plants makes it difficult to ensure a balance of power, which increases the need for intermediate energy storage. The research method is a mathematical modeling of random processes of energy consumption and generation, which allows for the analysis of the current power balancing and the obtaining of the integrated characteristics of the state of energy storage and reuse. The unique goal of the study is to take into account the power gradients and the state of charge of the batteries. The results of the study allow for the comparison of the different configurations of the power system in terms of balance, storage needs, and energy loss. It has been shown that the increase in battery capacity and speed limitations are nonlinearly related to the possibilities of energy conservation and the probability of the incomplete use of the capabilities of the energy storage system

Thrombospondin-1/CD47 signaling modulates transmembrane cation conductance, survival, and deformability of human red blood cells

Background: Thrombospondin-1 (TSP-1), a Ca2+-binding trimeric glycoprotein secreted by multiple cell types, has been implicated in the pathophysiology of several clinical conditions. Signaling involving TSP-1, through its cognate receptor CD47, orchestrates a wide array of cellular functions including cytoskeletal organization, migration, cell-cell interaction, cell proliferation, autophagy, and apoptosis. In the present study, we investigated the impact of TSP-1/CD47 signaling on Ca2+ dynamics, survival, and deformability of human red blood cells (RBCs). Methods: Whole-cell patch-clamp was employed to examine transmembrane cation conductance. RBC intracellular Ca2+ levels and multiple indices of RBC cell death were determined using cytofluorometry analysis. RBC morphology and microvesiculation were examined using imaging flow cytometry. RBC deformability was measured using laser-assisted optical rotational cell analyzer. Results: Exposure of RBCs to recombinant human TSP-1 significantly increased RBC intracellular Ca2+ levels. As judged by electrophysiology experiments, TSP-1 treatment elicited an amiloride-sensitive inward current alluding to a possible Ca2+ influx via non-selective cation channels. Exogenous TSP-1 promoted microparticle shedding as well as enhancing Ca2+- and nitric oxide-mediated RBC cell death. Monoclonal (mouse IgG1) antibody-mediated CD47 ligation using 1F7 recapitulated the cell death-inducing effects of TSP-1. Furthermore, TSP-1 treatment altered RBC cell shape and stiffness (maximum elongation index). Conclusions: Taken together, our data unravel a new role for TSP-1/CD47 signaling in mediating Ca2+ influx into RBCs, a mechanism potentially contributing to their dysfunction in a variety of systemic diseases