Nanohydroxyapatite-Blasted Bioactive Surface Drives Shear-Stressed Endothelial Cell Growth and Angiogenesis.

Nanosized crystalline hydroxyapatite coating (HAnano®) accelerates the osteointegration of dental implants which is hypothesized to drive angiogenesis. In order to test this hypothesis, we have subjected shear-stressed human umbilical vein endothelial cells (HUVECs) to a HAnano®-enriched medium, as well as to surface presenting dual acid etching (DAE) as a control. To note, the titanium implants were coated with 10 nm in diameter HA particles using the Promimic HAnano method. Our data reveals that HAnano® modulates higher expression of genes related with endothelial cell performance and viability, such as VEGF, eNOS, and AKT, and further angiogenesis in vitro by promoting endothelial cell migration. Additionally, the data shows a significant extracellular matrix (ECM) remodeling, and this finding seems developing a dual role in promoting the expression of VEGF and control endothelial cell growth during angiogenesis. Altogether, these data prompted us to further validate this phenomenon by exploring genes related with the control of cell cycle and in fact our data shows that HAnano® promotes higher expression of CDK4 gene, while p21 and p15 genes (suppressor genes) were significantly lower. In conjunction, our data shows for the first time that HAnano®-coated surfaces drive angiogenesis by stimulating a proliferative and migration phenotype of endothelial cells, and this finding opens novel comprehension about osseointegration mechanism considering nanosized hydroxyapatite coating dental implants.

Recurrence quantification analysis with wavelet denoising and the characterization of magnetic flux emergence regions in solar photosphere.

Solar systems complexity, multiscale, and nonlinearity are governed by numerous and continuous changes where the sun magnetic fields can successfully represent many of these phenomena. Thus, nonlinear tools to study these challenging systems are required. The dynamic system recurrence approach has been successfully used to deal with this kind challenge in many scientific areas, objectively improving the recognition of state changes, randomness, and degrees of complexity that are not easily identified by traditional techniques. In this work we introduce the use of these techniques in photospheric magnetogram series. We employ a combination of recurrence quantification analysis with a preprocessing denoising wavelet analysis to characterize the complexity of the magnetic flux emergence in the solar photosphere. In particular, with the developed approach, we identify regions of evolving magnetic flux and where they present a large degree of complexity, i.e., where predictability is low, intermittence is high, and low organization is present.