Astringency sub-qualities of red wines and the influence of wine–saliva aggregates

Astringency is a sensory attribute, related to the quality and mouthfeel of red wines. However, the origin of astringency sub-qualities, such as the typical drying astringency found in immature grapes, is still unknown. Astringency of red wines with similar tannin content but different astringency sub-qualities, from different harvest dates, is studied. Astringency was characterised in terms of friction coefficient, polyphenol content, sensory analysis and tannin/salivary–proteins aggregates characterisation. A different evolution during ripening was found for both Cabernet Sauvignon and Carménère, and tannin–protein aggregates showed differences in size, shape and surface. The velvety sub-quality appears to be related to aggregates with low precipitation, and with specific surface characteristics as roundness and Feret diameter. Results from this work propose an effect of aggregates on sensory perception and opens the possibility to explore their effect on oral lubrication.     

Application of Coffee Silverskin in cosmetic formulations: physical/antioxidant stability studies and cytotoxicity effects

Context: Currently, there is an increasing interest of cosmetic industry on natural extracts. The inclusion of antioxidants in topical formulations can contribute to minimize oxidative stress in the skin, which has been associated with aging. Also, questions of sustainability are leading to the study of new cosmetic ingredients obtained from food by-products. Coffee Silverskin (CS) is a food by-product with established antioxidant activity that has not yet been incorporated into a topical formulation.

Objective: The aim of this study was to evaluate the physical and microbiological stabilities and antioxidant activity of a hand cream formulation containing 2.5% (w/w) of CS extract upon production and after 6 months of shelf-life and in vitro safety/cytotoxicity on skin cell lines after production.

Materials and methods: The in vitro cytotoxicity was evaluated with MTS and LDH assays, at different concentrations, in HaCaT and HFF-1 cells. Formulations were stored at 25?°C/65% RH and 40?°C/75% RH. Physical, microbiological, and antioxidant stabilities were evaluated by centrifugation, viscosity, total colony count, DPPH and total phenolic content (TPC).

Results: The hand cream containing 2.5% (w/w) of CS extract showed stable physical characteristics independently of the storage conditions. The DPPH activity and TPC of the CS formulation were significantly higher compared with those of the base formulation. However, during storage, the antioxidant activity decreases slightly. Microbiological quality was also confirmed. No cytotoxic effects were observed.

Conclusion: It is possible to suggest that this formulation is stable under extreme conditions and safe for topical use.     

Recent research progress on bio-oil conversion into bio-fuels and raw chemicals: a review

Recent advances in lignocellulosic biomass valorization for producing fuels and commodities (olefins and BTX aromatics) are gathered in this paper, with a focus on the conversion of bio-oil (produced by fast pyrolysis of biomass). The main valorization routes are: (i) conditioning of bio-oil (by esterification, aldol condensation, ketonization, in situ cracking, and mild hydrodeoxygenation) for its use as a fuel or stable raw material for further catalytic processing; (ii) production of fuels by deep hydrodeoxygenation; (iii) ex situ catalytic cracking (in line) of the volatiles produced in biomass pyrolysis, aimed at the selective production of olefins and aromatics; (iv) cracking of raw bio-oil in units designed with specific objectives concerning selectivity; and (v) processing in fluidized bed catalytic cracking (FCC) units. This review deals with the technological evolution of these routes, in terms of catalysts, reaction conditions, reactors, and product yields. A study has been carried out on the current state-of-knowledge of the technological capacity, advantages and disadvantages of the different routes, as well as on the prospects for the implementation of each route within the scope of the Sustainable Refinery. © 2018 Society of Chemical Industry     

Bimodal polypropylene through binary metallocene catalytic systems: comparison between hybrid and mixed heterogeneous catalysts

Polypropylene with wider or bimodal molecular weight distribution is required for numerous applications since low molecular weight chains improve processability and high molecular weight fraction is required to get good mechanical properties. There are several routes to achieve a bimodal resin but the use of a binary catalytic system seems to be the most attractive, particularly with metallocenes combination. From a previous work two metallocenes were selected because they lead to polypropylenes with average molecular weights that differ in one order of magnitude. Two types of binary systems have been investigated, hybrid catalysts (two metallocenes loaded on the same support) and physical mixtures (two independent supported metallocenes that are introduced to the reactor and start the polymerization together), using different ratios, i.e., 25–75, 50–50, 75–25, at three reaction temperatures, i.e., 30, 50 and 70 °C. Most of the binary catalytic systems lead to bimodal molecular weight distributions. Polypropylenes produced by mixed catalysts are greatly influenced by the most active catalyst, while in PP coming from hybrid catalysts, as there is a strong interaction between both metallocenes, each one contributes according to its presence in the hybrid catalyst. Therefore, properties of obtained bimodal polypropylenes are quite influenced by the ratio between both metallocenes.     

Effects of Human and Porcine Adipose Extracellular Matrices Decellularized by Enzymatic or Chemical Methods on Macrophage Polarization and Immunocompetence

The decellularized extracellular matrix (ECM) obtained from human and porcine adipose tissue (AT) is currently used to prepare regenerative medicine bio-scaffolds. However, the influence of these natural biomaterials on host immune response is not yet deeply understood. Since macrophages play a key role in the inflammation/healing processes due to their high functional plasticity between M1 and M2 phenotypes, the evaluation of their response to decellularized ECM is mandatory. It is also necessary to analyze the immunocompetence of macrophages after contact with decellularized ECM materials to assess their functional role in a possible infection scenario. In this work, we studied the effect of four decellularized adipose matrices (DAMs) obtained from human and porcine AT by enzymatic or chemical methods on macrophage phenotypes and fungal phagocytosis. First, a thorough biochemical characterization of these biomaterials by quantification of remnant DNA, lipids, and proteins was performed, thus indicating the efficiency and reliability of both methods. The proteomic analysis evidenced that some proteins are differentially preserved depending on both the AT origin and the decellularization method employed. After exposure to the four DAMs, specific markers of M1 proinflammatory and M2 anti-inflammatory macrophages were analyzed. Porcine DAMs favor the M2 phenotype, independently of the decellularization method employed. Finally, a sensitive fungal phagocytosis assay allowed us to relate the macrophage phagocytosis capability with specific proteins differentially preserved in certain DAMs. The results obtained in this study highlight the close relationship between the ECM biochemical composition and the macrophage’s functional role.     

A fuzzy optimization model for planning integrated terrestrial carbon management networks

Clean Technologies and Environmental Policy - Biochar application and enhanced weathering are negative emission technologies (NETs) with the potential for large-scale deployment for the removal of...     

A review of adaptive online learning for artificial neural networks

In real applications learning algorithms have to address several issues such as, huge amount of data, samples which arrive continuously and underlying data generation processes that evolve over time. Classical learning is not always appropriate to work in these environments since independent and indentically distributed data are assumed. Taking into account the requirements of the learning process, systems should be able to modify both their structures and their parameters. In this survey, our aim is to review the developed methodologies for adaptive learning with artificial neural networks, analyzing the strategies that have been traditionally applied over the years. We focus on sequential learning, the handling of the concept drift problem and the determination of the network structure. Despite the research in this field, there are currently no standard methods to deal with these environments and diverse issues remain an open problem.