a(HM:"erythrocyte-endothelium adhesion")
TPEN also inhibited erythrocyte adhesion, but the effect at 20 mM was weaker compared to that in the HRG (100 mg/mL)- treatment group. PubMed:29544683
We found that a considerable number of erythrocytes were attached to the EA.hy926 cells after Zn2þ-stimulation (Fig. 4A). PubMed:29544683
In addition, we observed that Zn2þ induced the adhesion of erythrocytes to endothelial cells, and this effect was not inhibited by 100 mg/mL of HSA (Fig. 4), suggesting a specific interaction between erythrocytes and HRG. PubMed:29544683
HRG treatment significantly inhibited the attachment of erythrocytes to the vascular endothelial cell monolayer in a concentration dependent manner (Fig. 4A and B), while HSA did not affect the adhesion. PubMed:29544683
HRG treatment significantly inhibited the attachment of erythrocytes to the vascular endothelial cell monolayer in a concentration dependent manner (Fig. 4A and B), while HSA did not affect the adhesion. PubMed:29544683
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
The most common pathological states in which RBCs interact with the endothelium include sickle cell disease [39], malaria [40], and diabetes [41]. PubMed:28458720
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If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.