Albumin causes a synergistic increase in the antioxidant activity of green tea catechins in oil-in-water emulsions

Model oil-in-water emulsions containing epicatechin (EC) and epigallocatechin gallate (EGCG) showed a synergistic increase in stability in emulsions containing added albumin. EGCG showed a stronger synergy (35%) with ovalbumin than did EC. Oxidation of the oil was monitored by determining peroxide values and hexanal contents. The effect of bovine serum albumin (BSA) on model oil-in-water emulsions containing each of the green tea catechins [epicatechin gallate (ECG), EGCG, EC and epigallocatechin (EGC)] was studied during storage at 30 degrees C. The green tea catechins showed moderate antioxidant activity in the emulsions with the order of activity being ECG approximate to EGCG > EC > EGC. Although BSA had very little antioxidant activity in the absence of phenolic antioxidants, the combination of BSA with each of the catechins showed strong antioxidant activity. BSA, in combination with EC, EGCG or EGC, showing the strongest antioxidant activity with good stability after 45 days storage. Model experiments with the catechins stored with BSA in aqueous solutions confirmed that protein-catechin adducts with antioxidant activity were formed between the catechins and protein. The antioxidant activity of the separated protein-catechin adducts increased strongly with storage time and was stronger for EGCG and ECG than for EC or EGC. (c) 2006 Elsevier Ltd. All rights reserved.

The psychological, neurochemical and functional neuroanatomical mediators of the effects of positive and negative mood on executive functions

In this review we evaluate the cognitive and neural effects of positive and negative mood on executive function. Mild manipulations of negative mood appear to have little effect on cognitive control processes, whereas positive mood impairs aspects of updating, planning and switching. These cognitive effects may be linked to neurochemistry: with positive mood effects mediated by dopamine while negative mood effects may be mediated by serotonin levels. Current evidence on the effects of mood on regional brain activity during executive functions, indicates that the prefrontal cortex is a recurrent site of integration between mood and cognition. We conclude that there is a disparity between the importance of this topic and awareness of how mood affects, executive functions in the brain. Most behavioural and neuroimaging studies of executive function in normal samples do not explore the potential role of variations in mood, yet the evidence we outline indicates that even mild fluctuations in mood can have a significant influence on neural activation and cognition. (c) 2006 Elsevier Ltd. All rights reserved.

Right hemisphere language functions and schizophrenia: the forgotten hemisphere?

This review highlights the importance of right hemisphere language functions for successful social communication and advances the hypothesis that the core deficit in psychosis is a failure of segregation of right from left hemisphere functions. Lesion studies of stroke patients and dichotic listening and functional imaging studies of healthy people have shown that some language functions are mediated by the right hemisphere rather than the left. These functions include discourse planning/comprehension, understanding humour, sarcasm, metaphors and indirect requests, and the generation/comprehension of emotional prosody. Behavioural evidence indicates that patients with typical schizophrenic illnesses perform poorly on tests of these functions, and aspects of these functions are disturbed in schizo-affective and affective psychoses. The higher order language functions mediated by the right hemisphere are essential to an accurate understanding of someone's communicative intent, and the deficits displayed by patients with schizophrenia may make a significant contribution to their social interaction deficits. We outline a bi-hemispheric theory of the neural basis of language that emphasizes the role of the sapiens-specific cerebral torque in determining the four-chambered nature of the human brain in relation to the origins of language and the symptoms of schizophrenia. Future studies of abnormal lateralization of left hemisphere language functions need to take account of the consequences of a failure of lateralization of language functions to the right as well as the left hemisphere.

Optimization of apodization functions in terahertz transient spectrometry

A quadratic programming optimization procedure for designing asymmetric apodization windows tailored to the shape of time-domain sample waveforms recorded using a terahertz transient spectrometer is proposed. By artificially degrading the waveforms, the performance of the designed window in both the time and the frequency domains is compared with that of conventional rectangular, triangular (Mertz), and Hamming windows. Examples of window optimization assuming Gaussian functions as the building elements of the apodization window are provided. The formulation is sufficiently general to accommodate other basis functions. (C) 2007 Optical Society of America

MARCKS functions as a novel growth/tumour suppressor in cells of melanocyte origin

Protein kinase C (PKC) plays a pivotal role in modulating the growth of melanocytic cells in culture. We have shown previously that a major physiological substrate of PKC, the 80 kDa myristoylated alanine-rich C-kinase substrate (MARCKS), can be phosphorylated in quiescent, non-tumorigenic melanocytes exposed transiently to a biologically active phorbol ester, but cannot be phosphorylated in phorbol ester-treated, syngeneic malignant melanoma cells. Despite its ubiquitous distribution, the function of MARCKS in cell growth and transformation remains to be demonstrated clearly. We report here that MARCKS mRNA and protein levels are down-regulated significantly in the spontaneously derived murine B16 melanoma cell line compared with syngeneic normal Mel-ab melanocytes. In contrast, the tumourigenic v-Ha-ras-transfonned melan-ocytic line, LTR Ras 2, showed a high basal level of MARCKS phosphorylation which was not enhanced by treatment of cells with phorbol ester. Furthermore, protein levels of MARCKS in LTR Ras 2 cells were similar to those expressed in Mel-ab melanocytes. However, in four out of six murine tumour cell lines investigated, levels of MARCKS protein were barely detectable. Transfection of B16 cells with a plasmid containing the MARCKS cDNA in the sense orientation produced two neomycin-resistant clones displaying reduced proliferative capacity and decreased anchorage-independent growth compared with control cells. In contrast, transfection with the antisense MARCKS construct produced many colonies which displayed enhanced growth and transforming potential compared with control cells. Thus, MARCKS appears to act as a novel growth suppressor in the spontaneous transformation of cells of melanocyte origin and may play a more general role in the tumour progression of other carcinomas.

Green noise or green value? Measuring the effects of environmental certification on office values

This study investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and noncertified buildings. These are additional occupier benefits, lower holding costs for investors and a lower risk premium. Drawing upon the CoStar database of U.S. commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. The results suggest that, compared to buildings in the same submarkets, eco-certified buildings have both a rental and sale price premium.

A statistical mechanical approach for the computation of the climatic response to general forcings

The climate belongs to the class of non-equilibrium forced and dissipative systems, for which most results of quasi-equilibrium statistical mechanics, including the fluctuation-dissipation theorem, do not apply. In this paper we show for the first time how the Ruelle linear response theory, developed for studying rigorously the impact of perturbations on general observables of non-equilibrium statistical mechanical systems, can be applied with great success to analyze the climatic response to general forcings. The crucial value of the Ruelle theory lies in the fact that it allows to compute the response of the system in terms of expectation values of explicit and computable functions of the phase space averaged over the invariant measure of the unperturbed state. We choose as test bed a classical version of the Lorenz 96 model, which, in spite of its simplicity, has a well-recognized prototypical value as it is a spatially extended one-dimensional model and presents the basic ingredients, such as dissipation, advection and the presence of an external forcing, of the actual atmosphere. We recapitulate the main aspects of the general response theory and propose some new general results. We then analyze the frequency dependence of the response of both local and global observables to perturbations having localized as well as global spatial patterns. We derive analytically several properties of the corresponding susceptibilities, such as asymptotic behavior, validity of Kramers-Kronig relations, and sum rules, whose main ingredient is the causality principle. We show that all the coefficients of the leading asymptotic expansions as well as the integral constraints can be written as linear function of parameters that describe the unperturbed properties of the system, such as its average energy. Some newly obtained empirical closure equations for such parameters allow to define such properties as an explicit function of the unperturbed forcing parameter alone for a general class of chaotic Lorenz 96 models. We then verify the theoretical predictions from the outputs of the simulations up to a high degree of precision. The theory is used to explain differences in the response of local and global observables, to define the intensive properties of the system, which do not depend on the spatial resolution of the Lorenz 96 model, and to generalize the concept of climate sensitivity to all time scales. We also show how to reconstruct the linear Green function, which maps perturbations of general time patterns into changes in the expectation value of the considered observable for finite as well as infinite time. Finally, we propose a simple yet general methodology to study general Climate Change problems on virtually any time scale by resorting to only well selected simulations, and by taking full advantage of ensemble methods. The specific case of globally averaged surface temperature response to a general pattern of change of the CO2 concentration is discussed. We believe that the proposed approach may constitute a mathematically rigorous and practically very effective way to approach the problem of climate sensitivity, climate prediction, and climate change from a radically new perspective.

Efficient on the fly calculation of time correlation functions in computer simulations

Time correlation functions yield profound information about the dynamics of a physical system and hence are frequently calculated in computer simulations. For systems whose dynamics span a wide range of time, currently used methods require significant computer time and memory. In this paper, we discuss the multiple-tau correlator method for the efficient calculation of accurate time correlation functions on the fly during computer simulations. The multiple-tau correlator is efficacious in terms of computational requirements and can be tuned to the desired level of accuracy. Further, we derive estimates for the error arising from the use of the multiple-tau correlator and extend it for use in the calculation of mean-square particle displacements and dynamic structure factors. The method described here, in hardware implementation, is routinely used in light scattering experiments but has not yet found widespread use in computer simulations.

The influence of ultraviolet radiation on growth, photosynthesis and phenolic levels of green and red lettuce: potential for exploiting effects of ultraviolet radiation in a production system

Studies have shown that natural ultraviolet (UV) radiation increases secondary products such as phenolics but can significantly inhibit biomass accumulation in lettuce plants. In the work presented here, the effect of UV radiation on phenolic concentration and biomass accumulation was assessed in relation to photosynthetic performance in red and green lettuce types. Lettuce plants in polythene clad tunnels were exposed to either ambient (UV transparent film) or UV-free conditions (UV blocking film). The study tested whether growth reduction in lettuce plants exposed to natural UV radiation is because of inhibition of photosynthesis by direct damage to the photosynthetic apparatus or by internal shading by anthocyanins. Ambient levels of UV radiation did not limit the efficiency of photosynthesis suggesting that phenolic compounds may effectively protect the photosynthetic apparatus. Growth inhibition does, however, occur in red lettuce and could be explained by the high metabolic cost of phenolic compounds for UV protection. From a commercial perspective, UV transparent and UV blocking films offer opportunities because, in combination, they could increase plant quality as well as productivity. Growing plants continuously under a UV blocking film, and then 6 days before the final harvest transferring them to a UV transparent film, showed that high yields and high phytochemical content can be achieved complementarily.

Neurofuzzy network model construction using Bézier-Bernstein polynomial functions

Neurofuzzy modelling systems combine fuzzy logic with quantitative artificial neural networks via a concept of fuzzification by using a fuzzy membership function usually based on B-splines and algebraic operators for inference, etc. The paper introduces a neurofuzzy model construction algorithm using Bezier-Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as the non-negativity of the basis functions, and unity of support but with the additional advantages of structural parsimony and Delaunay input space partitioning, avoiding the inherent computational problems of lattice networks. This new modelling network is based on the idea that an input vector can be mapped into barycentric co-ordinates with respect to a set of predetermined knots as vertices of a polygon (a set of tiled Delaunay triangles) over the input space. The network is expressed as the Bezier-Bernstein polynomial function of barycentric co-ordinates of the input vector. An inverse de Casteljau procedure using backpropagation is developed to obtain the input vector's barycentric co-ordinates that form the basis functions. Extension of the Bezier-Bernstein neurofuzzy algorithm to n-dimensional inputs is discussed followed by numerical examples to demonstrate the effectiveness of this new data based modelling approach.