Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

IMMUNOSENSOR SYSTEMS USING LIPOSOMES AND PLANAR LIPID BILAYER MEMBRANES FOR ION-CHANNEL MODEL SENSORS

For the purpose of constructing a new biosensor which mimics the concept of "ion-channel", two approaches were examined: l)liposome systems, and 2)planar lipid bilayer membrane systems. In both cases, some interaction such as immunoreaction, electrostatruneh dıpole,sand hydrophobic interaction of a stimulus with a model receptor site at the surface of lipid membranes triggers the change in permeation of marker ions across the lipid bilayer membranes. This change in permeation of the marker ions is subsequently monitored electrochemically, which is a direct but much amplified measure of the analyte to be assayed

Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders

Abstract Background Poor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper development of follicles and oocytes through tightly controlled metabolism and cell signaling. Androgens such as dehydroepiandrosterone (DHEA) have been proposed to alter the POR follicular microenvironment, but the impact DHEA imposes on the FF metabolome and cytokine profiles is unknown. Therefore, the objective of this study is to profile and identify metabolomic changes in the FF with DHEA supplementation in POR patients. Methods FF samples collected from 52 POR patients who underwent IVF with DHEA supplementation (DHEA +) and without (DHEA-; controls) were analyzed using untargeted liquid chromatography-tandem mass spectrometry (LC–MS/MS) metabolomics and a large-scale multiplex suspension immunoassay covering 65 cytokines, chemokines and growth factors. Multivariate statistical modelling by partial least squares-discriminant regression (PLSR) analysis was performed for revealing metabolome-scale differences. Further, differential metabolite analysis between the two groups was performed by PLSR β-coefficient regression analysis and Student’s t-test. Results Untargeted metabolomics identified 118 FF metabolites of diverse chemistries and concentrations which spanned three orders of magnitude. They include metabolic products highly associated with ovarian function – amino acids for regulating pH and osmolarity, lipids such fatty acids and cholesterols for oocyte maturation, and glucocorticoids for ovarian steroidogenesis. Four metabolites, namely, glycerophosphocholine, linoleic acid, progesterone, and valine were significantly lower in DHEA + relative to DHEA- (p < 0.05–0.005). The area under the curves of progesterone glycerophosphocholine, linoleic acid and valine are 0.711, 0.730, 0.785 and 0.818 (p < 0.05–0.01). In DHEA + patients, progesterone positively correlated with IGF-1 (Pearson r: 0.6757, p < 0.01); glycerophosphocholine negatively correlated with AMH (Pearson r: -0.5815; p < 0.05); linoleic acid correlated with estradiol and IGF-1 (Pearson r: 0.7016 and 0.8203, respectively; p < 0.01 for both). In DHEA- patients, valine negatively correlated with serum-free testosterone (Pearson r: -0.8774; p < 0.0001). Using the large-scale immunoassay of 45 cytokines, we observed significantly lower MCP1, IFNγ, LIF and VEGF-D levels in DHEA + relative to DHEA. Conclusions In POR patients, DHEA supplementation altered the FF metabolome and cytokine profile. The identified four FF metabolites that significantly changed with DHEA may provide information for titrating and monitoring individual DHEA supplementation

Architecture of mmWave Edge Cloud in 5G-MiEdge

This paper presents the vision of 5G-MiEdge, a research project leveraging the benefits of merging Multi-access Edge Computing (MEC) and millimeter wave (mmWave) technologies. First the three chosen key enabling technologies, i.e. mmWave edge cloud, liquid control-plane (C-plane), and application-/user-centric orchestration, are presented, then the defined use cases and application scenarios are described. Based on those and on re-using 3GPP and ETSI functional blocks, MEC and mmWave are integrated into a unique high- level network architecture. Finally, as a Proof-of- Concept, numerical results using the novel C-plane for Omotenashi services are presented to show the benefit of the proposed architecture

Millimeter-waves, MEC, and network softwarization as enablers of new 5G business opportunities

This paper focuses on analyzing some key business aspects that arise during the deployment of key novel enabling technologies for 5G systems. Results are taken out of two EU-funded ongoing research projects, namely 5G-MiEdge and Superfluidity, which largely exploit mmWave communications and softwarization concepts for 5G networks. We initially provide a stakeholder analysis of the 5G ecosystem, as well as a Strengths Weaknesses Opportunities Threats (SWOT) analysis of a couple of key and most promising 5G use cases. For one use case also a preliminary business model is provided. Then we detail an economic 5G cost model, which is able to provide indications on the profitability of 5G networks. Finally, we highlight the planned future works