The endothelium has a fundamental role in the cardiovascular complications of coronavirus disease 2019 (COVID-19). Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) particularly affects endothelial cells. The virus binds to the angiotensin-converting enzyme 2 (ACE-2) receptor (present on type 2 alveolar cells, bronchial epithelial cells, and endothelial cells), and induces a cytokine storm. The cytokines tumor necrosis factor alpha, interleukin-1 beta, and interleukin-6 have particular effects on endothelial cells—leading to endothelial dysfunction, endothelial cell death, changes in tight junctions, and vascular hyperpermeability. Under normal conditions, apoptotic endothelial cells are removed into the bloodstream. During COVID-19, however, endothelial cells are detached more rapidly, and do not regenerate as effectively as usual. The loss of the endothelium on the luminal surface abolishes all of the vascular responses mediated by the endothelium and nitric oxide production in particular, which results in greater contractility. Moreover, circulating endothelial cells infected with SARS-CoV-2 act as vectors for viral dissemination by forming clusters that migrate into the circulation and reach distant organs. The cell clusters and the endothelial dysfunction might contribute to the various thromboembolic pathologies observed in COVID-19 by inducing the formation of intravascular microthrombi, as well as by triggering disseminated intravascular coagulation. Here, we review the contributions of endotheliopathy and endothelial-cell-derived extracellular vesicles to the pathogenesis of COVID-19, and discuss therapeutic strategies that target the endothelium in patients with COVID-19.

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Introduction HLA antigens are highly polymorphic, and their immunogenicity is dependent on the configurations of polymorphic amino acids. Monitoring anti‐HLA immunization is essential in organ transplantation, as antibodies directed against HLA molecules are a major cause of rejection. Anti‐HLA antibodies are not specific for HLA antigens, but recognize B‐cell epitopes present on HLA molecules. Methods To better understand antibody reactivity patterns, we calculated the Spearman correlation of the mean fluorescence intensity (MFI) of anti‐HLA antibodies identified by a single‐antigen assay performed using a Luminex® immunobeads assay on a large number of samples. Then, we built a computer tool analyzing antibody reactivity patterns with an accessibility by a web browser linked to the International Epitope Registry. We also extended our model to Onelambda® and Lifecodes® single‐antigen class I and class II assays. Results and Discussion The resulting MFI correlations reflect HLA antibody cross‐reactivity and eplets similarity. We built HLA Graph, a computer tool that analyzes the eplets involved in antibody reactivity profiles. HLA Graph is usable with Onelambda® and Lifecodes® single‐antigen class I and class II assays. The interpretation of reactivity against alleles not tested by the antibody assays and against the alpha and beta chains of HLA‐DQ and HLA‐DP loci were also developed. Conclusion HLA Graph is a free and ready‐to‐use bioinformatics tool that can be used by all laboratories performing anti‐HLA antibody identification by immunobead assay.

A hematopoietic chimerism assay is the laboratory test for monitoring engraftment and quantifying the proportions of donor and recipient cells after hematopoietic stem cell transplantation recipients. Flow cytometry is the reference method for determining the purity of CD3+ cells on the chimerism of selected CD3+ cells. In the present study, we developed a single‐step procedure that combines the CD3+ purity assay (using the PCR‐based Non‐T Genomic Detection Kit from Accumol, Calgary, Canada) and the qPCR chimerism monitoring assay (the QTRACE qPCR assay from Jeta Molecular, Utrecht, the Netherlands). First, for the CD3+ purity assay, we used a PCR‐friendly protocol by changing the composition of the ready‐to‐use reaction tubes (buffer and taq polymerase) and obtained a satisfactory calibration plot (R2 = 0.8924) with a DNA reference scale of 2 ng/μl. Next, 29 samples (before and after CD3 positive selection) were analyzed, the mean cell purity was, respectively, 19.6% ± 6.45 and 98.9% ± 1.07 in the flow cytometry assay; 26.8% ± 7.63 and 98.5% ± 1.79 in the PCR‐based non‐T genomic detection assay. Our results showed that the CD3+ purity assay using a qPCR kit is a robust alternative to the flow cytometry assay and is associated with time savings when combined with a qPCR chimerism assay.