Synergistic effect of BSA on antioxidant activities in model food emulsions

Sunflower oil-in-water emulsions containing TBHQ, caffeic acid, epigallocatechin gallate (EGCG), or 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox), both with and without BSA, were stored at 50 and 30degreesC. Oxidation of the oil was monitored by determination of the PV, conjugated diene content, and hexanal formation. Emulsions containing EGCG, caffeic acid, and, to a lesser extent, Trolox were much more stable during storage in the presence of BSA than in its absence even though BSA itself did not provide an antioxidant effect. BSA did not have a synergistic effect on the antioxidant activity of TBHQ. The BSA structure changed, with a considerable loss of fluorescent tryptophan groups during storage of solutions containing BSA and antioxidants, and a BSA-antioxidant adduct with radical-scavenging activity was formed. The highest radical-scavenging activity observed was for the isolated protein from a sample containing EGCG and BSA incubated at 30degreesC for 10 d. This fraction contained unchanged BSA as well as BSA-antioxidant adduct, but 95.7% of the initial fluorescence had been lost, showing that most of the BSA had been altered. It can be concluded that BSA exerts its synergistic effect with antioxidants because of formation of a protein-antioxidant adduct during storage, which is concentrated at the oil-water interface owing to the surface-active nature of the protein.

M-estimator, and D-optimality model construction using orthogonal forward regression

This correspondence introduces a new orthogonal forward regression (OFR) model identification algorithm using D-optimality for model structure selection and is based on an M-estimators of parameter estimates. M-estimator is a classical robust parameter estimation technique to tackle bad data conditions such as outliers. Computationally, The M-estimator can be derived using an iterative reweighted least squares (IRLS) algorithm. D-optimality is a model structure robustness criterion in experimental design to tackle ill-conditioning in model Structure. The orthogonal forward regression (OFR), often based on the modified Gram-Schmidt procedure, is an efficient method incorporating structure selection and parameter estimation simultaneously. The basic idea of the proposed approach is to incorporate an IRLS inner loop into the modified Gram-Schmidt procedure. In this manner, the OFR algorithm for parsimonious model structure determination is extended to bad data conditions with improved performance via the derivation of parameter M-estimators with inherent robustness to outliers. Numerical examples are included to demonstrate the effectiveness of the proposed algorithm.

Inverting recurrent neural networks for internal model control of nonlinear systems

In this paper, we show how a set of recently derived theoretical results for recurrent neural networks can be applied to the production of an internal model control system for a nonlinear plant. The results include determination of the relative order of a recurrent neural network and invertibility of such a network. A closed loop controller is produced without the need to retrain the neural network plant model. Stability of the closed-loop controller is also demonstrated.

Selecting from amongst non–nested conditional variance models: information criteria and portfolio determination

We consider the finite sample properties of model selection by information criteria in conditionally heteroscedastic models. Recent theoretical results show that certain popular criteria are consistent in that they will select the true model asymptotically with probability 1. To examine the empirical relevance of this property, Monte Carlo simulations are conducted for a set of non–nested data generating processes (DGPs) with the set of candidate models consisting of all types of model used as DGPs. In addition, not only is the best model considered but also those with similar values of the information criterion, called close competitors, thus forming a portfolio of eligible models. To supplement the simulations, the criteria are applied to a set of economic and financial series. In the simulations, the criteria are largely ineffective at identifying the correct model, either as best or a close competitor, the parsimonious GARCH(1, 1) model being preferred for most DGPs. In contrast, asymmetric models are generally selected to represent actual data. This leads to the conjecture that the properties of parameterizations of processes commonly used to model heteroscedastic data are more similar than may be imagined and that more attention needs to be paid to the behaviour of the standardized disturbances of such models, both in simulation exercises and in empirical modelling.

A new method for the determination of Holocene palaeohydrology

This paper describes a new method for the assessment of palaeohydrology through the Holocene. A palaeoclimate model was linked with a hydrological model, using a weather generator to correct bias in the rainfall estimates, to simulate the changes in the flood frequency and the groundwater response through the late Pleistocene and Holocene for the Wadi Faynan in southern Jordan, a site considered internationally important due to its rich archaeological heritage spanning the Pleistocene and Holocene. This is the first study to describe the hydrological functioning of the Wadi Faynan, a meso-scale (241 km2) semi-arid catchment, setting this description within the framework of contemporary archaeological investigations. Historic meteorological records were collated and supplemented with new hydrological and water quality data. The modelled outcomes indicate that environmental changes, such as deforestation, had a major impact on the local water cycle and this amplified the effect of the prevailing climate on the flow regime. The results also show that increased rainfall alone does not necessarily imply better conditions for farming and highlight the importance of groundwater. The discussion focuses on the utility of the method and the importance of the local hydrology to the sustained settlement of the Wadi Faynan through pre-history and history.

Comparative biology of mammalian telomeres: hypotheses on ancestral states and the roles of telomeres in longevity determination

Progressive telomere shortening from cell division (replicative aging) provides a barrier for human tumor progression. This program is not conserved in laboratory mice, which have longer telomeres and constitutive telomerase. Wild species that do ⁄ do not use replicative aging have been reported, but the evolution of different phenotypes and a conceptual framework for understanding their uses of telomeres is lacking. We examined telomeres ⁄ telomerase in cultured cells from > 60 mammalian species to place different uses of telomeres in a broad mammalian context. Phylogeny-based statistical analysis reconstructed ancestral states. Our analysis suggested that the ancestral mammalian phenotype included short telomeres (< 20 kb, as we now see in humans) and repressed telomerase. We argue that the repressed telomerase was a response to a higher mutation load brought on by the evolution of homeothermy. With telomerase repressed, we then see the evolution of replicative aging. Telomere length inversely correlated with lifespan, while telomerase expression co-evolved with body size. Multiple independent times smaller, shorter-lived species changed to having longer telomeres and expressing telomerase. Trade-offs involving reducing the energetic ⁄ cellular costs of specific oxidative protection mechanisms (needed to protect < 20 kb telomeres in the absence oftelomerase) could explain this abandonment of replicative aging. These observations provide a conceptual framework for understanding different uses of telomeres in mammals, support a role for human-like telomeres in allowing longer lifespans to evolve, demonstrate the need to include telomere length in the analysis of comparative studies of oxidative protection in the biology of aging, and identify which mammals can be used as appropriate model organisms for the study of the role of telomeres in human cancer and aging. Key words: evolution of telomeres; immortalization; telomerase; replicative aging; senescence.

On the determination of atmospheric water vapor from GPS measurements

Surface-based GPS measurements of zenith path delay (ZPD) can be used to derive vertically integrated water vapor (IWV) of the atmosphere. ZPD data are collected in a global network presently consisting of 160 stations as part of the International GPS Service. In the present study, ZPD data from this network are converted into IWV using observed surface pressure and mean atmospheric water vapor column temperature obtained from the European Centre for Medium-Range Weather Forecasts' (ECMWF) operational analyses (OA). For the 4 months of January/July 2000/2001, the GPS-derived IWV values are compared to the IWV from the ECMWF OA, with a special focus on the monthly averaged difference (bias) and the standard deviation of daily differences. This comparison shows that the GPS-derived IWV values are well suited for the validation of OA of IWV. For most GPS stations, the IWV data agree quite well with the analyzed data indicating that they are both correct at these locations. Larger differences for individual days are interpreted as errors in the analyses. A dry bias in the winter is found over central United States, Canada, and central Siberia, suggesting a systematic analysis error. Larger differences were mainly found in mountain areas. These were related to representation problems and interpolation difficulties between model height and station height. In addition, the IWV comparison can be used to identify errors or problems in the observations of ZPD. This includes errors in the data itself, e.g., erroneous outlier in the measured time series, as well as systematic errors that affect all IWV values at a specific station. Such stations were excluded from the intercomparison. Finally, long-term requirements for a GPS-based water vapor monitoring system are discussed.

Determination of the gas diffusion coefficient of a peat grassland soil

Peatland habitats are important carbon stocks that also have the potential to be significant sources of greenhouse gases, particularly when subject to changes such as artificial drainage and application of fertilizer. Models aiming to estimate greenhouse gas release from peatlands require an accurate estimate of the diffusion coefficient of gas transport through soil (Ds). The availability of specific measurements for peatland soils is currently limited. This study measured Ds for a peat soil with an overlying clay horizon and compared values with those from widely available models. The Ds value of a sandy loam reference soil was measured for comparison. Using the Currie (1960) method, Ds was measured between an air-filled porosity (ϵ) range of 0 and 0.5 cm3 cm−3. Values of Ds for the peat cores ranged between 3.2 × 10−4 and 4.4 × 10−3 m2 hour−1, for loamy clay cores between 0 and 4.7 × 10−3 m2 hour−1 and for the sandy reference soil they were between 5.4 × 10−4 and 3.4 × 10−3 m2 hour−1. The agreement of measured and modelled values of relative diffusivity (Ds/D0, with D0 the diffusion coefficient through free air) varied with soil type; however, the Campbell (1985) model provided the best replication of measured values for all soils. This research therefore suggests that the use of the Campbell model in the absence of accurately measured Ds and porosity values for a study soil would be appropriate. Future research into methods to reduce shrinkage of peat during measurement and therefore allow measurement of Ds for a greater range of ϵ would be beneficial.

Determination of eddy-diffusivity in the lowermost stratosphere

We present a 2D-advection-diffusion model that simulates the main transport pathways influencing tracer distributions in the lowermost stratosphere (LMS). The model describes slow diabatic descent of aged stratospheric air, vertical (cross-isentropic) and horizontal (along isentropes) diffusion within the LMS and across the tropopause using equivalent latitude and potential temperature coordinates. Eddy diffusion coefficients parameterize the integral effect of dynamical processes leading to small scale turbulence and mixing. They were specified by matching model simulations to observed CO distributions. Interestingly, the model suggests mixing across isentropes to be more important than horizontal mixing across surfaces of constant equivalent latitude, shining new light on the interplay between various transport mechanisms in the LMS. The model achieves a good description of the small scale tracer features at the tropopause with squared correlation coefficients R2 = 0.72…0.94.

Consistent and contrasting decadal Arctic sea ice thickness predictions from a highly optimized sea ice model

[1] Decadal hindcast simulations of Arctic Ocean sea ice thickness made by a modern dynamic-thermodynamic sea ice model and forced independently by both the ERA-40 and NCEP/NCAR reanalysis data sets are compared for the first time. Using comprehensive data sets of observations made between 1979 and 2001 of sea ice thickness, draft, extent, and speeds, we find that it is possible to tune model parameters to give satisfactory agreement with observed data, thereby highlighting the skill of modern sea ice models, though the parameter values chosen differ according to the model forcing used. We find a consistent decreasing trend in Arctic Ocean sea ice thickness since 1979, and a steady decline in the Eastern Arctic Ocean over the full 40-year period of comparison that accelerated after 1980, but the predictions of Western Arctic Ocean sea ice thickness between 1962 and 1980 differ substantially. The origins of differing thickness trends and variability were isolated not to parameter differences but to differences in the forcing fields applied, and in how they are applied. It is argued that uncertainty, differences and errors in sea ice model forcing sets complicate the use of models to determine the exact causes of the recently reported decline in Arctic sea ice thickness, but help in the determination of robust features if the models are tuned appropriately against observations.

Objective determination of feature resolution in two sea surface temperature analyses

Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated “true” SST data and subsampled based on actual infrared and microwave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly ) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious small-scale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (~5 km) infrared satellite data are limited because of cloud cover.

An isotope dilution model for partitioning phenylalanine and tyrosine uptake by the mammary gland of lactating dairy cows

An isotope dilution model for partitioning phenylalanine and tyrosine uptake by the mammary gland of the lactating dairy cow is constructed and solved in the steady state. The model contains four intracellular and four extracellular pools and conservation of mass principles are applied to generate the fundamental equations describing the behaviour of the system. The experimental measurements required for model solution are milk secretion and plasma flow rate across the gland in combination with phenylalanine and tyrosine concentrations and plateau isotopic enrichments in arterial and venous plasma and free and protein bound milk during a constant infusion of [1-(13)C]phenylalanine and [2,3,5,6-(2)H]tyrosine tracer. If assumptions are made, model solution enables determination of steady state flows for phenylalanine and tyrosine inflow to the gland, outflow from it and bypass, and flows representing the synthesis and degradation of constitutive protein and hydroxylation. The model is effective in providing information about the fates of phenylalanine and tyrosine in the mammary gland and could be used as part of a more complex system describing amino acid metabolism in the whole ruminant.

A dynamic mechanistic model of lactic acid metabolism in the rumen

Current feed evaluation systems for ruminants are too imprecise to describe diets in terms of their acidosis risk. The dynamic mechanistic model described herein arises from the integration of a lactic acid (La) metabolism module into an extant model of whole-rumen function. The model was evaluated using published data from cows and sheep fed a range of diets or infused with various doses of La. The model performed well in simulating peak rumen La concentrations (coefficient of determination = 0.96; root mean square prediction error = 16.96% of observed mean), although frequency of sampling for the published data prevented a comprehensive comparison of prediction of time to peak La accumulation. The model showed a tendency for increased La accumulation following feeding of diets rich in nonstructural carbohydrates, although less-soluble starch sources such as corn tended to limit rumen La concentration. Simulated La absorption from the rumen remained low throughout the feeding cycle. The competition between bacteria and protozoa for rumen La suggests a variable contribution of protozoa to total La utilization. However, the model was unable to simulate the effects of defaunation on rumen La metabolism, indicating a need for a more detailed description of protozoal metabolism. The model could form the basis of a feed evaluation system with regard to rumen La metabolism.

Pozzolanic behavior of bamboo leaf ash: Characterization and determination of the kinetic parameters

The paper presents a characterization and study of the pozzolanic behavior between calcium hydroxide (CH) and bamboo leaf ash (BLAsh), which was obtained by calcining bamboo leaves at 600 degrees C for 2 h in a laboratory electric furnace. To evaluate the pozzolanic behavior the conductometric method was used, which is based on the measurement of the electrical conductivity in a BLAsh/CH solution with the reaction time. Later, the kinetic parameters are quantified by applying a kinetic-diffusive model. The kinetic parameters that characterize the process (in particular, the reaction rate constant and free energy of activation) were determined with relative accuracy in the fitting process of the model. The pozzolanic activity is quantitatively evaluated according to the values obtained of the kinetic parameters. Other experimental techniques, such as X-ray diffraction (XRD) and scanning electron microscopy (SEM), were also employed. The results show that this kind of ash is formed by silica with a completely amorphous nature and a high pozzolanic activity. The correlation between the values of free energy of activation (Delta G(#)) and the reaction rate constants (K) are in correspondence with the theoretical studies about the rate processes reported in the literature. (C) 2010 Elsevier Ltd. All rights reserved.

Reactive oxygen and nitrogen species balance in the determination of thyroid hormones-induced cardiac hypertrophy mediated by renin-angiotensin system

Role of reactive oxygen species (ROS)/nitric oxide (NO) balance and renin-angiotensin system in mediating cardiac hypertrophy in hyperthyroidism was evaluated in an in vivo and in vitro experimental model. Male Wistar rats were divided into four groups: control, thyroid hormone, vitamin E (or Trolox, its hydrosoluble analogue), thyroid hormone + vitamin E. Angiotensin II receptor (AT1/AT2) gene expression, immunocontent of AT1/AT2 receptors, angiotensinogen, NADPH oxidase (Nox2), and nitric oxide synthase isoforms, as well as ROS concentration (hydrogen peroxide and superoxide anion) were quantified in myocardium. Thyroid hormone increased ROS and NO metabolites, iNOS, nNOS and eNOS isoforms and it was accompanied by cardiac hypertrophy. AT1/AT2 expression and the immunocontent of angiotensinogen and Nox2 were enhanced by thyroid hormone. Antioxidants reduced ROS levels, Nox2, AT1/AT2, NOS isoforms and cardiac hypertrophy. In conclusion, ROS/NO balance may play a role in the control of thyroid hormone-induced cardiac hypertrophy mediated by renin-angiotensin system. (C) 2011 Elsevier Ireland Ltd. All rights reserved.