Conversion efficiency of glucose/xylose mixtures for ethanol production using Saccharomyces cerevisiae ITV01 and Pichia stipitis NRRL Y‐7124

BACKGROUND: Efficient conversion of glucose/xylose mixtures from lignocellulose is necessary for commercially viable ethanol production. Oxygen and carbon sources are of paramount importance for ethanol yield. The aim of this work was to evaluate different glucose/xylose mixtures for ethanol production using S. cerevisiae ITV‐01 (wild type yeast) and P. stipitis NRRL Y‐7124 and the effect of supplying oxygen in separate and co‐culture processes. RESULTS: The complete conversion of a glucose/xylose mixture (75/30 g L^?1) was obtained using P. stipitis NRRL Y‐7124 under aerobic conditions (0.6 vvm), the highest yield production being Y_p/s = 0.46 g g^?1, volumetric ethanol productivity Q_pmax = 0.24 g L^?1 h^?1 and maximum ethanol concentration P_max = 34.5 g L^?1. In the co‐culture process and under aerobic conditions, incomplete conversion of glucose/xylose mixture was observed (20.4% residual xylose), with a maximum ethanol production of 30.3 g L^?1, ethanol yield of 0.4 g g^?1 and Q_pmax = 1.26 g L^?1 h^?1. CONCLUSIONS: The oxygen present in the glucose/xylose mixture promotes complete sugar consumption by P. stipitis NRRL Y‐7124 resulting in ethanol production. However, in co‐culture with S. cerevisiae ITV‐01 under aerobic conditions, incomplete fermentation occurs that could be caused by oxygen limitation and ethanol inhibition by P. stipitis NRRL Y‐7124; nevertheless the volumetric ethanol productivity increases fivefold compared with separate culture. Copyright © 2011 Society of Chemical Industry     

Advances and Perspectives in Dental Pulp Stem Cell Based Neuroregeneration Therapies

Human dental pulp stem cells (hDPSCs) are some of the most promising stem cell types for regenerative therapies given their ability to grow in the absence of serum and their realistic possibility to be used in autologous grafts. In this review, we describe the particular advantages of hDPSCs for neuroregenerative cell therapies. We thoroughly discuss the knowledge about their embryonic origin and characteristics of their postnatal niche, as well as the current status of cell culture protocols to maximize their multilineage differentiation potential, highlighting some common issues when assessing neuronal differentiation fates of hDPSCs. We also review the recent progress on neuroprotective and immunomodulatory capacity of hDPSCs and their secreted extracellular vesicles, as well as their combination with scaffold materials to improve their functional integration on the injured central nervous system (CNS) and peripheral nervous system (PNS). Finally, we offer some perspectives on the current and possible future applications of hDPSCs in neuroregenerative cell therapies.     

An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation

The ability of an Evolutionary Algorithm (EA) to find a global optimal solution depends on its capacity to find a good rate between exploitation of found-so-far elements and exploration of the search space. Inspired by natural phenomena, researchers have developed many successful evolutionary algorithms which, at original versions, define operators that mimic the way nature solves complex problems, with no actual consideration of the exploration-exploitation balance. In this paper, a novel nature-inspired algorithm called the States of Matter Search (SMS) is introduced. The SMS algorithm is based on the simulation of the states of matter phenomenon. In SMS, individuals emulate molecules which interact to each other by using evolutionary operations which are based on the physical principles of the thermal-energy motion mechanism. The algorithm is devised by considering each state of matter at one different exploration–exploitation ratio. The evolutionary process is divided into three phases which emulate the three states of matter: gas, liquid and solid. In each state, molecules (individuals) exhibit different movement capacities. Beginning from the gas state (pure exploration), the algorithm modifies the intensities of exploration and exploitation until the solid state (pure exploitation) is reached. As a result, the approach can substantially improve the balance between exploration–exploitation, yet preserving the good search capabilities of an evolutionary approach. To illustrate the proficiency and robustness of the proposed algorithm, it is compared to other well-known evolutionary methods including novel variants that incorporate diversity preservation schemes. The comparison examines several standard benchmark functions which are commonly considered within the EA field. Experimental results show that the proposed method achieves a good performance in comparison to its counterparts as a consequence of its better exploration–exploitation balance.     

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.     

A semantic role labelling-based framework for learning ontologies from Spanish documents

Currently, most of the information available in the Web is adapted primarily for human consumption, but there is so much information that can no longer be processed by a person in a reasonable time, either in digital or physical formats. To solve this problem, the idea of the Semantic Web arose. The Semantic Web deals with adding machine-readable information to Web pages. Ontologies represent a very important element of this web, as they provide a valid and robust structure to represent knowledge based on concepts, relations, axioms, etc. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to learn ontologies. In this sense, this paper proposes a new ontology learning methodology based on semantic role labeling from digital Spanish documents. The method makes it possible to represent multiple semantic relations specially taxonomic and partonomic ones in the standardized OWL 2.0. A set of experiments has been performed with the approach implemented in educational domain that show promising results.