Platelets induce Pai-1 mRNA expression in monocytes through TGF-BETA

Introduction: Plasminogen activator inhibitor type-1 (PAI-1) is a physiological modulator of fibrinolysis. High plasma PAI-1 is associated with the 4G/5G promoter polymorphism and with increased cardiovascular risk. Here we explored the role of platelets in regulating expression of the PAI-1 gene in monocytes. Methods: Blood from PAI-1 4G/5G genotyped volunteers (n=6) was incubated with the platelet GPVI-specific agonist, cross-linked collagen related peptide (CRP-XL), in the presence or absence of Mab 9E1 that blocks the binding of P-selectin to PSGL1. Monocytes were isolated by +ve selection on CD14 beads and monocyte PAI-1 mRNA expression was measured by real-time PCR. Results: Activation of platelets with CRP-XL resulted in platelets binding to >70% of monocytes and was accompanied by >5000-fold induction of PAI-1 mRNA, peaking at 4hrs. PAI-1 expression was independent of the 4G/5G genotype. Blocking the binding of platelets to monocytes enhanced PAI-1 induction (p<0.05 at 4 hrs). Incubation of isolated monocytes with the releasate from CRP-XL stimulated platelets also led to PAI-1 mRNA expression. The platelet secretome contains >100 different proteins. To identify the soluble factor(s) responsible for induction of PAI-1, neutralizing antibodies to likely candidates were added to monocytes incubated with the platelet releasate. Anti- TGF-beta inhibited platelet releasate-mediated PAI-1 mRNA induction by >80%. Monocyte PAI-1 was also induced by stimulation of PSGL-1 with a P-selectin-Fc chimera, in the absence of platelets, which was also blocked by the TGF-beta antibody. Conclusions: These results suggest that platelets induce PAI-1 mRNA in monocytes predominantly via TGF-beta, released from both platelets, and monocytes via activation by PSGL-1 signalling.This stimulation is independent of 4G/5G genotype

Acceleration and visualization of Dynamic Network Optimization

With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.