Candida molischianaβ-Glucosidase Production by Saccharomyces cerevisiae and its Application in Winemaking

ABSTRACT: A recombinant Saccharomyces cerevisiae wine yeast strain expressing the Candida molischiana bgln gene encoding a β-glucosidase (BGLN) has been used to produce this enzyme. Shaking rate, pH, and aeration rate conditions have been optimized to obtain maximum activity to facilitate enzyme purification. The ability of the heterologous enzyme to efficiently release terpenols and alcohols from a Muscat wine glycoside extract and also directly from wine has been demonstrated. Terpenol glycoside content decreased by 50% after 1 mo of wine storage in agreement with results reported for the β-glucosidase produced by C. molischiana.     

Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with CHRIS/PROBA observations

Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test datasets. Measurements of LAI, FCOVER and FAPAR were achieved over the Barrax (Spain) agricultural site for a range of crop types concurrently to CHRIS/PROBA satellite image acquisition. Results showed that the spectral band selection was specific to LAI, FCOVER and FAPAR variables. The optimal band set provided significantly improved performances for LAI, while only small differences were observed for the other variables. Gaussian distributions of the radiative transfer model input variables performed better than uniform distributions for which no prior information was exploited. Including moderate uncertainties in the reflectance simulations used in the training process improved the flexibility of the neural network in cases where simulations departed slightly from observations. Simple neural network architecture with a single hidden layer of five tangent sigmoid transfer functions was performing as good as more complex architectures if the training dataset was larger than ten times the number of coefficients to tune. Small sensitivity of performances was observed depending on the way the solution was selected when several networks were trained in parallel. Finally, comparison with a NDVI based approach showed the generally better retrieval accuracy of neural networks.     

Effect of the long-term intake of an egg white hydrolysate on the oxidative status and blood lipid profile of spontaneously hypertensive rats

This paper examines the effects of the long-term consumption of egg white hydrolysed with pepsin (hEW) on the antioxidant status and lipid profile of spontaneously hypertensive rats (SHR). The antioxidant capacity was measured by the oxygen radical absorbance capacity (ORAC) and the oxidative status by the malon-dialdehyde (MDA) assay. The lipid profile was analysed spectrophotometrically. The radical-scavenging capacity of the plasma was increased and the MDA concentration in the aorta was decreased in the SHR treated with 0.5 g/kg/day of hEW. Our findings indicate that hEW played an important role in antioxidative defence of SHR and exerted a beneficial effect on the lipid profile, lowering triglycerides and total cholesterol without changing HDL levels. Therefore, hEW may be useful to prevent or reverse abnormalities associated with the metabolic syndrome and its complications, such as hypertension, oxidative stress and hyperlipidemia.     

Detection of toxic gases by a tin oxide multisensor

A tin oxide multisensor with eight sensor elements has been utilized to detect different gases that are emitted from the chemical industry. The different sensors have been prepared using the RF reactive sputtering technique. Some components of this multisensor were doped with Pt and Cr by sputtering. Each sensor has been characterized by electrical measurements for detection of atmospheric pollution (nitrogen dioxide, carbon monoxide, toluene, and propanal). The detected gases are toxic and their extreme concentrations recommended in air oscillate from 1 ppm to hundreds of ppm. Detections were carried out with a single gas or a gas mixture (two gases) in dry air at 250/spl deg/C. The sensitivity and selectivity to these gases were studied. Backpropagation neural networks and their classification results were discussed.     

Impact and visibility of Norwegian,Finnish and Spanish journals in the fields of humanities

Scientometrics - This article analyses the impact and visibility of scholarly journals in the humanities that are publishing in the national languages in Finland, Norway and Spain. Three types of...     

Effect of simulated gastrointestinal digestion on the antihypertensive properties of synthetic beta-lactoglobulin peptide sequences

In this study, the antihypertensive activity in spontaneously hypertensive rats of two peptides isolated from beta-lactoglobulin hydrolysates with thermolysin was evaluated. These peptides, with sequences LLF [beta-lg f(103-105)] and LQKW [beta-lg f(58-61)], showed potent in vitro ACE-inhibitory activity. Two hours after administration, both sequences caused a clear and significant decrease in the blood pressure of these rats. The impact of a simulated gastrointestinal digestion on ACE-inhibitory and antihypertensive activities of these peptides was also studied. The results showed that both fragments were susceptible to proteolytic degradation after incubation with pepsin and Corolase PP. In addition, their in vitro ACE-inhibitory activity decreased after the simulated digestion. It is likely that fragment LQK was the active end product of the gastrointestinal digestion of peptide LQKW. The fragment LL, observed after digestion of peptide LLF, probably exert its antihypertensive effect through a mechanism of action different than ACE-inhibition.     

Foam aptitude of Bobal variety in white sparkling wine elaboration and study of volatile compounds

Fining agents can also have an effect on the flavor components of the must, and other compounds which are important for the sensory characteristics and in the case of sparkling wine, the foam quality. The influence of fining agents and tirage solution, on volatile compounds, and foam characteristics of sparkling wines made from grapes of the Bobal variety was studied. The data obtained show how the fining agent affects the foam properties and the final volatile composition of sparkling wines. In this study, it was bentonite with gelatine that produced amounts of acetates and esters. The use of Colle 2P in the tirage solution means that more aromatic sparkling wines with better foam characteristics can be obtained.     

A Hydrogel Platform that Incorporates Laminin Isoforms for Efficient Presentation of Growth Factors – Neural Growth and Osteogenesis

Laminins (LMs) are important structural proteins of the extracellular matrix (ECM). The abundance of every LM isoform is tissue-dependent, suggesting that LM has tissue-specific roles. LM binds growth factors (GFs), which are powerful cytokines widely used in tissue engineering due to their ability to control stem cell differentiation. Currently, the most commonly used ECM mimetic material in vitro is Matrigel, a matrix of undefined composition containing LM and various GFs, but subjected to batch variability and lacking control of physicochemical properties. Inspired by Matrigel, a new and completely defined hydrogel platform based on hybrid LM-poly(ethylene glycol) (PEG) hydrogels with controllable stiffness (1–25 kPa) and degradability is proposed. Different LM isoforms are used to bind and efficiently display GFs (here, bone morphogenetic protein (BMP-2) and beta-nerve growth factor (β-NGF)), enabling their solid-phase presentation at ultralow doses to specifically target a range of tissues. The potential of this platform to trigger stem cell differentiation toward osteogenic lineages and stimulate neural cells growth in 3D, is demonstrated. These hydrogels enable 3D, synthetic, defined composition, and reproducible cell culture microenvironments reflecting the complexity of the native ECM, where GFs in combination with LM isoforms yield the full diversity of cellular processes.     

A multisensor fusion approach to improve LAI time series

High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. It is applicable to any optical sensor and satellite product. In this study, the potential of this technique was demonstrated for leaf area index (LAI) product based on MODIS and VEGETATION reflectance data. The FUSION product showed an overall good agreement with the original MODIS LAI product but exhibited a reduction of 90% of the missing LAI values with an improved monitoring of vegetation dynamics, temporal smoothness, and better agreement with ground measurements.