Abstract. Endoglin is a homodimeric membrane glycoprotein which can bind the 131 and 133 isoforms of transforming growth factor-13 (TGF-13). We reported previously that endoglin is upregulated during monocyte differentiation. We have now observed that TGF-13 itself can stimulate the expression of endoglin in cultured human monocytes and in the U-937 monocytic line. To study the functional role of endoglin, stable transfectants of U-937 cells were generated which overexpress L-or S-endoglin isoforms, differing in their cytoplasmic domain. Inhibition of cellular proliferation and downregulation of c-myc mRNA which are normally induced by TGF-t31 in U-937 cells were totally abrogated in L-endoglin transfectants and much reduced in the S-endoglin transfectants. Inhibition of proliferation by TGF-132 was not altered in the transfectants, in agreement with the isoform specificity of endoglin. Additional responses of U-937 cells to TGF-131, including stimulation of fibronectin synthesis, cellular adhesion, platelet/endothelial cell adhesion molecule i (PECAM-1) phosphorylation, and homotypic aggregation were also inhibited in the endoglin transfectants. However, modulation of integrin and PECAM-1 levels and stimulation of mRNA levels for TGF-131 and its receptors R-I, R-II, and betaglycan occurred normally in the endoglin transfectants. No changes in total ligand binding were observed in L-endoglin transfectants relative to mock, while a 1.5-fold increase was seen in S-endoglin transfectants. The degradation rate of the ligand was the same in all transfectants. Elucidating the mechanism by which endoglin modulates several cellular responses to TGF-131 without interfering with ligand binding or degradation should increase our understanding of the complex pathways which mediate the effects of this factor.

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After the spread of the SARS-CoV-2 epidemic out of China, evolution in the pandemic worldwide shows dramatic differences among countries. In Europe, the situation of Italy first and later Spain has generated great concen, and despite other countries show better prospects, large uncertainties yet remain on the future evolution and the e, or attack strategies. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we also incorporate effects of varying proportions of containment. We fit data to reported infected populations at the beginning of the first peak of the pandemic to account for the uncertainties in case reporting and study the scenario projections for the individual regions (CCAA). The aim of this model it’s to evaluate the confinement rate at the first stages of the epidemic outbreak in order to evaluate the scenarios that minimize the incidence but also the mortality. Results indicate that with data for March 23, the epidemics follow an evolution similar to the isolation of percent of the population, and if there were no effects of intervention actions it might reach a maximum of over infected around April 27. The effect on the epidemics of the ongoing partial confinement measures is yet unknown (an update of results with data until March 31st is included), but increasing the isolation around ten times more could drastically reduce the peak to over cases by early April, while each day of delay in taking this hard containment scenario represents a 90 percent increase of the infected population at the peak. Dynamics at the sub aggregated levels of CCAA show epidemics at the different levels of progression with the most worrying situation in Madrid and Catalonia. Increasing alpha values up to 10 times, in addition to a drastic reduction in clinical cases, would also more than half the number of deaths. Updates for March 31st simulations indicate a substantial reduction in burden is underway. A similar approach conducted for Italy pre-and post-intervention also begins to suggest a substantial reduction in both infected and deaths has been achieved, showing the efficacy of drastic social distancing interventions. At last we show the real evolution of the pandemic up to the end of May and the beginning of July in order to calculate the real confinement rate from data to compare with the scenarios formulated at March.