Pressure and Chemical Unfolding of an α-Helical Bundle Protein: The GH2 Domain of the Protein Adaptor GIPC1

When combined with NMR spectroscopy, high hydrostatic pressure is an alternative perturbation method used to destabilize globular proteins that has proven to be particularly well suited for exploring the unfolding energy landscape of small single-domain proteins. To date, investigations of the unfolding landscape of all-β or mixed-α/β protein scaffolds are well documented, whereas such data are lacking for all-α protein domains. Here we report the NMR study of the unfolding pathways of GIPC1-GH2, a small α-helical bundle domain made of four antiparallel α-helices. High-pressure perturbation was combined with NMR spectroscopy to unravel the unfolding landscape at three different temperatures. The results were compared to those obtained from classical chemical denaturation. Whatever the perturbation used, the loss of secondary and tertiary contacts within the protein scaffold is almost simultaneous. The unfolding transition appeared very cooperative when using high pressure at high temperature, as was the case for chemical denaturation, whereas it was found more progressive at low temperature, suggesting the existence of a complex folding pathway.     

Epigallocatechin Gallate Ameliorates the Effects of Prenatal Alcohol Exposure in a Fetal Alcohol Spectrum Disorder-Like Mouse Model

Fetal alcohol spectrum disorder is the main preventable cause of intellectual disability in the Western world. Although binge drinking is the most studied prenatal alcohol exposure pattern, other types of exposure, such as the Mediterranean, are common in specific geographic areas. In this study, we analyze the effects of prenatal alcohol exposure in binge and Mediterranean human drinking patterns on placenta and brain development in C57BL/6J mice. We also assess the impact of prenatal treatment with the epigallocatechin-3-gallate antioxidant in both groups. Study experimental groups for Mediterranean or binge patterns: (1) control; (2) ethanol; (3) ethanol + epigallocatechin-3-gallate. Brain and placental tissue were collected on gestational Day 19. The molecular pathways studied were fetal and placental growth, placental angiogenesis (VEGF-A, PLGF, VEGF-R), oxidative stress (Nrf2), and neurodevelopmental processes including maturation (NeuN, DCX), differentiation (GFAP) and neural plasticity (BDNF). Prenatal alcohol exposure resulted in fetal growth restriction and produced imbalances of placental angiogenic factors. Moreover, prenatal alcohol exposure increased oxidative stress and caused significant alterations in neuronal maturation and astrocyte differentiation. Epigallocatechin-3-gallate therapy ameliorated fetal growth restriction, attenuated alcohol-induced changes in placental angiogenic factors, and partially rescued neuronal nuclear antigen (NeuN), (doublecortin) DCX, and (glial fibrillary acidic protein) GFAP levels. Any alcohol consumption (Mediterranean or binge) during pregnancy may generate a fetal alcohol spectrum disorder phenotype and the consequences may be partially attenuated by a prenatal treatment with epigallocatechin-3-gallate.     

Mould growth and mycotoxin production as affected by Equisetum arvense and Stevia rebaudiana extracts

Cereals are very important for human and animal diet. However, agricultural products can be contaminated by moulds and their mycotoxins. On the other hand, natural plant products with antimicrobial properties could be a possibility to control mycotoxigenic fungi in foods and feeds. In this study, Equisetum arvense and Stevia rebaudiana extracts were tested for their efficacy against a range of mycotoxigenic fungi. Maize agar medium (MAM 2%) was used for this study and E. arvense and S. rebaudiana extracts were added at different concentrations (1–3%) under different water activity (a_w) levels (0.85–0.95). Six mycotoxigenic moulds were inoculated and incubated at different temperatures (15–30 °C) during 21 days. In general, no growth was observed with E. arvense extract at 3% in all studied conditions for all isolates. However, with S. rebaudiana extract at 2–3%, growth was not significantly decreased (p < 0.05) in most of the cases. Finally, in terms of toxin production, results were not conclusive. The use of E. arvense extracts as antifungals and antimycotoxigenics and their application should be further explored.     

Rigorous development of component-based systems using component metadata and patterns

In previous work we presented a CSP-based systematic approach that fosters the rigorous design of component-based development. Our approach is strictly defined in terms of composition rules, which are the only permitted way to compose components. These rules guarantee the preservation of properties (particularly deadlock freedom) by construction in component composition. Nevertheless, their application is allowed only under certain conditions whose verification via model checking turned out impracticable even for some simple designs, and particularly those involving cyclic topologies. In this paper, we address the performance of the analysis and present a significantly more efficient alternative to the verification of the rule side conditions, which are improved by carrying out partial verification on component metadata throughout component compositions and by using behavioural patterns. The use of metadata, together with behavioural patterns, demands new composition rules, which allow previous exponential time verifications to be carried out now in linear time. Two case studies (the classical dining philosophers, also used as a running example, and an industrial version of a leadership election algorithm) are presented to illustrate and validate the overall approach.     

Miscibility behavior of epoxy thermosets loaded with an oligophosphonate

In this study, a commercial epoxy resin was mixed with a phosphorus‐containing oligomer and thermally cross‐linked using a mixture of two aliphatic amines as curing agents. The miscibility and the influence of the phosphorus‐containing oligomer on the characteristics of epoxy thermosets were investigated by scanning electron microscopy (SEM), thermogravimetric analysis, differential scanning calorimetry, and dynamic mechanical analysis. SEM revealed that phosphorus‐containing oligomer was well dispersed into the epoxy matrix. Dynamic mechanical analysis indicated an increase in storage modulus as the phosphorus‐containing oligomer content loaded into epoxy matrix increased. Thermogravimetric analysis showed that the onset temperature of phosphorus‐containing epoxy thermosets and the peak corresponding to the temperature of decomposition decreased compared with the ones corresponding to the neat epoxy system, whereas the char yield increased with the increase in phosphorus content added into the epoxy networks. To better understand the mechanism of action of phosphorus‐containing epoxy thermosets, the char residue was investigated by SEM and energy‐dispersive X‐ray spectroscopy. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41822.     

Enhancing information for solar and wind energy technology deployment in Brazil

Brazil's primary energy matrix is based on more than 47% of renewables, and more than 85% of its electricity is generated by hydro power sources. Despite this large fraction of renewable energy resources, less than 0.3% of the national energy supply comes from solar or wind sources. This paper presents a diagnostic review on the penetration of the solar and wind energy technologies in Brazil. It also includes a survey of the latest government policies and incentives for renewable energies deployment by entrepreneurs, industry and commercial and residential consumers. In addition, the paper analyses how to best meet the requirements for policy support and information technology to boost the deployment of solar technology and wind energy in Brazil. This study was mostly based on results of a widely distributed survey covering key issues, and also by personal interviews carried out with key stakeholders in order to better understand the issues highlighted in the survey responses. The study pointed out some of the main obstacles to effectively promote and improve government policies and actions for investment in solar and wind energy market in Brazil.     

Determination of chloride diffusivity through partially saturated Portland cement concrete by a simplified procedure

A recently proposed methodology for measuring the diffusion coefficient of chloride ions through concrete partially saturated with water, has been applied to five high-early-strength Portland cement mortars. The method is based on putting solid NaCl in contact with the concrete surface during the diffusion test. The results obtained indicate a strong dependence of the diffusion coefficient on the water saturation degree. The ionic diffusivities through these mortars are higher than those obtained with the same approach for five pozzolanic cement mortars of similar compositions. It has been also shown that the proposed test methodology and a different one based on the interaction of HCl(g) with the tested concrete surface, can yield comparable results. The D values obtained are of similar magnitude, and the same type of dependence on the water saturation degree is found through both methods, when applied to similar Portland cement concrete mixes with cement content of about 350 kg/m³ and water/cement ratios between 0.5 and 0.6.     

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

Standard simulation in classical mechanics is based on the use of two very different types of equations. The first one, of axiomatic character, is related to balance laws (momentum, mass, energy,...), whereas the second one consists of models that scientists have extracted from collected, natural or synthetic data. Even if one can be confident on the first type of equations, the second one contains modeling errors. Moreover, this second type of equations remains too particular and often fails in describing new experimental results. The vast majority of existing models lack of generality, and therefore must be constantly adapted or enriched to describe new experimental findings. In this work we propose a new method, able to directly link data to computers in order to perform numerical simulations. These simulations will employ axiomatic, universal laws while minimizing the need of explicit, often phenomenological, models. This technique is based on the use of manifold learning methodologies, that allow to extract the relevant information from large experimental datasets.     

Robust contour tracking of nonholonomic mobile robots via adaptive velocity field motion planning scheme

This paper aims at designing a contour tracking scheme based on an adaptive velocity field formulation, for the case of uncertain nonholonomic (differential drive) mobile robots, with its dynamic controller. First, to handle kinematic uncertainties that deviate the map of the velocity field into wheel velocities, a linear parameterization of the uncertain Jacobian operator is proposed to synthesize an adaptive kinematic controller that shapes correctly the velocity field. Then, a robust model‐free dynamic controller is proposed to compensate in finite time for uncertain dynamics and disturbances, enforcing the kinematic reference. Finally, a representative simulation study is discussed to show the reliability of the proposed scheme.