Endothelial Glycocalyx as a Regulator of Fibrotic Processes

The endothelial glycocalyx, the gel layer covering the endothelium, is composed of glycosaminoglycans, proteoglycans, and adsorbed plasma proteins. This structure modulates vessels’ mechanotransduction, vascular permeability, and leukocyte adhesion. Thus, it regulates several physiological and pathological events. In the present review, we described the mechanisms that disturb glycocalyx stability such as reactive oxygen species, matrix metalloproteinases, and heparanase. We then focused our attention on the role of glycocalyx degradation in the induction of profibrotic events and on the possible pharmacological strategies to preserve this delicate structure.     

Engineering of Janus-Like Dendrimers with Peptides Derived from Glycoproteins of Herpes Simplex Virus Type 1: Toward a Versatile and Novel Antiviral Platform

Novel antiviral nanotherapeutics, which may inactivate the virus and block it from entering host cells, represent an important challenge to face viral global health emergencies around the world. Using a combination of bioorthogonal copper-catalyzed 1,3-dipolar alkyne/azide cycloaddition (CuAAC) and photoinitiated thiol–ene coupling, monofunctional and bifunctional peptidodendrimer conjugates were obtained. The conjugates are biocompatible and demonstrate no toxicity to cells at biologically relevant concentrations. Furthermore, the orthogonal addition of multiple copies of two different antiviral peptides on the surface of a single dendrimer allowed the resulting bioconjugates to inhibit Herpes simplex virus type 1 at both the early and the late stages of the infection process. The presented work builds on further improving this attractive design to obtain a new class of therapeutics.     

Novel high intrinsic dimensionality estimators

Recently, a great deal of research work has been devoted to the development of algorithms to estimate the intrinsic dimensionality (id) of a given dataset, that is the minimum number of parameters needed to represent the data without information loss. id estimation is important for the following reasons: the capacity and the generalization capability of discriminant methods depend on it; id is a necessary information for any dimensionality reduction technique; in neural network design the number of hidden units in the encoding middle layer should be chosen according to the id of data; the id value is strongly related to the model order in a time series, that is crucial to obtain reliable time series predictions. Although many estimation techniques have been proposed in the literature, most of them fail on noisy data, or compute underestimated values when the id is sufficiently high. In this paper, after reviewing some of the most important id estimators related to our work, we provide a theoretical motivation of the bias that causes the underestimation effect, and we present two id estimators based on the statistical properties of manifold neighborhoods, which have been developed in order to reduce this effect. We exhaustively evaluate the proposed techniques on synthetic and real datasets, by employing an objective evaluation measure to compare their performance with those achieved by state of the art algorithms; the results show that the proposed methods are promising, and produce reliable estimates also in the difficult case of datasets drawn from non-linearly embedded manifolds, characterized by high?id.     

Optical and electrical characterization of carbon nanoparticles produced in laminar premixed flames

Optical and electrical properties of carbonaceous particles produced in laboratory scale, premixed ethylene/air flames are obtained. Light absorption and Raman spectroscopy show that the change in particle nanostructure follows a graphitization trajectory as the flame richness increases. The optical band gap decreases and the size of the aromatic network in the particle increases, while the interlayer spacing between parallel layers decreases. The electrical conductivity of the materials increases by increasing flame richness in agreement to the graphitization trajectory. A non-ohmic behavior has been found and explained in terms of electron tunneling in a percolative network. Our results show that the electrical properties of flame formed carbon nanoparticles are strongly dependent on their nanostructure, and hence they have to be used carefully for the determination of particle concentration with conductometric sensors. Moreover, the dependence of the electrical properties of combustion formed particles might be useful for the development of cheap sensors for the selective detection of different classes of combustion aerosols.     

Power-to-Gas integration in the Transition towards Future Urban Energy Systems

Temperature levels play a key role in the thermal energy demand of urban contexts affecting their associated primary energy consumption and Renewable Energy Fraction. A Smart Heating strategy accounts for those supply features requiring new solutions to be effectively renewable and to solve the RES capacity firming. Power-to-Gas (P2G) is the way to decarbonize the energy supply chain as fraction of Hybrid fuels, combination of fossil ones and Renewable Hydrogen, as immediate responsive storage solution. While, Power-To-Heat is conceived as the strategy to modernize the high and medium temperature heating systems by electricity-driven machines to switch from Fuel-to-Heat to Electricity-to-Heat solutions. The authors investigated on different urban energy scenarios at RES share increase from 25% up to 50% in the energy mix to highlight strengths and weaknesses of the P2G applications. Primary Energy Consumption was chosen as the objective function. Three Reference Cities were chosen as reference scenarios. Moreover, the analytical models of P2G was designed and implemented in the reference energy system. The results of the twelve scenarios, four for each Reference City were evaluated in terms of amount of Renewable Heat delivered. Finally, the interaction between P2G and renewable heat production was evaluated.     

Surface-initiated atom transfer radical polymerization of polyhedral oligomeric silsesquioxane (POSS) methacrylate from flat silicon wafer

A polyhedral oligomeric silsesquioxane (POSS) methacrylate monomer, i.e. 3-(3,5,7,9,11,13,15-heptacyclopentyl-pentacyclo [9.5.1.1.^3,91.^5,151^7,13]-octasiloxane-1-yl) propyl methacrylate (POSS-MA), was directly grafted from flat silicon wafers using surface-initiated atom transfer radical polymerization (ATRP). Two methods were used to improve the system livingness and control of polymer molecular weights. By ‘adding free initiator’ method, a linear relationship between the grafted poly(POSS-MA) layer thickness and monomer conversion was observed. By ‘adding deactivator’ method, the poly(POSS-MA) thickness increased linearly with reaction time. Poly(POSS-MA) layers up to 40 nm were obtained. The chemical compositions measured by X-ray photoelectron spectroscopy (XPS) agreed well with their theoretical values. Water contact angle measurements revealed that the grafted poly(POSS-MA) was extremely hydrophobic. The surface morphologies of the grafted polymer layers were studied by an atom force microscopy (AFM).