Anti-EGF monoclonal antibody, clone 4B9 [Biotin]

Endothelial-mesenchymal transition (EndMT) is a major source of transformed cardiac fibroblasts, which is reported to play a key role in cardiac fibrosis (CF), a pathogenesis of cardiovascular diseases such as heart failure, myocardial infarction and atrial fibrillation. Nonetheless, the specific mechanism underlying the progression of EndMT to CF is still largely unknown. In this study, we aimed to investigate the role of milk fat globule-EGF factor 8 (MFGE8), a kind of soluble glycoprotein, in TGF-beta 1-induced EndMT. In animal experiments, the expression of MFGE8 was found down-regulated in the left ventricle and aorta of rats after transverse aortic constriction (TAC) compared with the sham group, especially in endothelial cells (ECs). In in vitro cultured ECs, silencingMFGE8with small interfering RNA (siRNA) was found to promote the process of TGF-beta 1-induced EndMT, whereas administration of recombinant human MFGE8 (rh-MFGE8) attenuated the process. Moreover, activated Smad2/3 signalling pathway after TGF-beta 1 treatment and EndMT-related transcription factors, such as Snail, Twist and Slug, was potentiated byMFGE8knock-down but inhibited by rh-MFGE8. In conclusion, our experiments indicate that MFGE8 might play a protective role in TGF-beta 1-induced EndMT and might be a potential therapeutic target for cardiac fibrosis.

Cellular receptors on the cell membrane can bind ligand molecules in the extra-cellular medium to form ligand-bound monomers. These interactions ultimately determine the fate of a cell through the resulting intra-cellular signalling cascades. Often, several receptor types can bind a shared ligand leading to the formation of different monomeric complexes, and in turn to competition for the common ligand. Here, we describe competition between two receptors which bind a common ligand in terms of a bi-variate stochastic process. The stochastic description is important to account for fluctuations in the number of molecules. Our interest is in computing two summary statistics-the steady-state distribution of the number of bound monomers and the time to reach a threshold number of monomers of a given kind. The matrix-analytic approach developed in this manuscript is exact, but becomes impractical as the number of molecules in the system increases. Thus, we present novel approximations which can work under low-to-moderate competition scenarios. Our results apply to systems with a larger number of population species (i.e., receptors) competing for a common resource (i.e., ligands), and to competition systems outside the area of molecular dynamics, such as Mathematical Ecology.