The fate and toxicity of the flavonoids naringenin and formononetin in soil

The flavonoid class of plant secondary metabolites play a multifunctional role in below-ground plant-microbe interactions with their best known function as signals in the nitrogen fixing legume-rhizobia symbiosis. Flavonoids enter rhizosphere soil as a result of root exudation and senescence but little is known about their subsequent fate or impacts on microbial activity. Therefore, the present study examined the sorptive behaviour, biodegradation and impact on dehydrogenase activity (as determined by iodonitrotetrazolium chloride reduction) of the flavonoids naringenin and formononetin in soil. Organic carbon normalised partition coefficients, log K-oc, of 3.12 (formononetin) and 3.19 (naringenin) were estimated from sorption isotherms and, after comparison with literature log K-oc values for compounds whose soil behaviour is better characterised, the test flavonoids were deemed to be moderately sorbed. Naringenin (spiked at 50 mu g g(-1)) was biodegraded without a detectable lag phase with concentrations reduced to 0.13 +/- 0.01 mu g g(-1) at the end of the 96 h time course. Biodegradation of formononetin proceeded after a lag phase of similar to 24 with concentrations reduced to 4.5 +/- 1% of the sterile control after 72 h. Most probable number (MPN) analysis revealed that prior to the addition of flavonoids, the soil contained 5.4 x 10(6) MPNg(-1) (naringenin) and 7.9 x 10(5) MPNg(-1) (formononetin) catabolic microbes. Formononetin concentration had no significant (p > 0.05) effect on soil dehydrogenase activity, whereas naringenin concentration had an overall but non-systematic impact (p = 0.045). These results are discussed with reference to likely total and bioavailable concentrations of flavonoids experienced by microbes in the rhizosphere. (c) 2007 Elsevier Ltd. All rights reserved.

Tracer correlations in the northern high latitude lowermost stratosphere: Influence of cross‐tropopause mass exchange

We present an analysis of trace gas correlations in the lowermost stratosphere. In‐situ aircraft measurements of CO, N2O, NOy and O3, obtained during the STREAM 1997 winter campaign, have been used to investigate the role of cross‐tropopause mass exchange on tracer‐tracer relations. At altitudes several kilometers above the local tropopause, undisturbed stratospheric air was found with NOy/NOy * ratios close to unity, NOy/O3 about 0.003–0.006 and CO mixing ratios as low as 20 ppbv (NOy * is a proxy for total reactive nitrogen derived from NOy–N2O relations measured in the stratosphere). Mixing of tropospheric air into the lowermost stratosphere has been identified by enhanced ratios of NOy/NOy * and NOy/O3, and from scatter plots of CO versus O3. The enhanced NOy/O3 ratio in the lowermost stratospheric mixing zone points to a reduced efficiency of O3 formation from aircraft NOx emissions.

Testing the limits of quasi-geostrophic theory: application to observed laboratory flows outside the quasi-geostrophic regime

We compare laboratory observations of equilibrated baroclinic waves in the rotating two-layer annulus, with numerical simulations from a quasi-geostrophic model. The laboratory experiments lie well outside the quasi-geostrophic regime: the Rossby number reaches unity; the depth-to-width aspect ratio is large; and the fluid contains ageostrophic inertia–gravity waves. Despite being formally inapplicable, the quasi-geostrophic model captures the laboratory flows reasonably well. The model displays several systematic biases, which are consequences of its treatment of boundary layers and neglect of interfacial surface tension and which may be explained without invoking the dynamical effects of the moderate Rossby number, large aspect ratio or inertia–gravity waves. We conclude that quasi-geostrophic theory appears to continue to apply well outside its formal bounds.

Unity as a unit

The arguments for regarding the number 1 as a unit of the SI are reviewed. Examples of dimensionless quantities are presented, and problems associated with representing the values of dimensionless quantities of very small magnitude are discussed. The logarithmic ratio units bel, decibel and neper are discussed.

Direct versus indirect sexual selection: genetic basis of colour, size and recruitment in a wild bird

Indirect and direct models of sexual selection make different predictions regarding the quantitative genetic relationships between sexual ornaments and fitness. Indirect models predict that ornaments should have a high heritability and that strong positive genetic covariance should exist between fitness and the ornament. Direct models, on the other hand, make no such assumptions about the level of genetic variance in fitness and the ornament, and are therefore likely to be more important when environmental sources of variation are large. Here we test these predictions in a wild population of the blue tit (Parus caeruleus), a species in which plumage coloration has been shown to be under sexual selection. Using 3 years of cross-fostering data from over 250 breeding attempts, we partition the covariance between parental coloration and aspects of nestling fitness into a genetic and environmental component. Contrary to indirect models of sexual selection, but in agreement with direct models, we show that variation in coloration is only weakly heritable (h(2) < 0.11), and that two components of offspring fitness-nestling size and fledgling recruitment-are strongly dependent on parental effects, rather than genetic effects. Furthermore, there was no evidence of significant positive genetic covariation between parental colour and offspring traits. Contrary to direct benefit models, however, we find little evidence that variation in colour reliably indicates the level of parental care provided by either males or females. Taken together, these results indicate that the assumptions of indirect models of sexual selection are not supported by the genetic basis of the traits reported on here.

An integrated mathematical model to evaluate nutrient partition in dairy cattle between the animal and its environment

In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 2481 on N partition, and a new model of P partition. The second objective was to construct a decision support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original simulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 6791 to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which production and environmental objectives are antagonistic, and it may help to explain and understand the complex mechanisms involved at the ruminal and metabolic levels. A part of the integrated model outputs were the forms of N and P in excreta and methane, which can be used as indices of environmental pollution. (C) 2004 Elsevier B.V All rights reserved.

Chemical composition and in vitro fermentation of tannin-rich tree fruits

Dry and mature tree fruits are a potential source of protein for goats in the semi-arid areas of southern Africa, but their chemical composition and feeding value is largely unknown. This study presents the chemical composition and in vitro fermentation of indehiscent whole fruits and separated seed and hull fractions from Acacia nilotica, Acacia erubescens, Acacia sieberiana, Acacia erioloba, Piliostigma thonningii and Dichrostachys cinerea trees. Results indicate that the N contents of whole fruits ranged between 13.5 g/kg DM (A. nilotica) and 27.1 g/kg DM (A. erubescens). Seeds had a higher N content than hulls for all tree species. A. nilotica, D. cinerea and P thonningii fruits had high levels of extractable phenolics (758, 458 and 299 g/kg DM, respectively). Soluble phenolics (SPh) and ytterbium precipitable phenolics (YbPh) levels were negatively correlated to in vitro gas production but positively correlated to in vitro organic matter degradability (iOMD). Partition factors for whole fruits at 48 h ranged between 3.6 mg/ml for A. erioloba and 7.8 mg/ml for A. nilotica. Seeds of A. erioloba, A. erubescens and P thonningii were consistently fermented more efficiently throughout the incubation period compared to their whole fruits or hulls. Estimating in vitro degradability of phenolic-rich substrates through filtration procedures can give erroneous results due to the loss of soluble phenolics, which are not necessarily degradable. The feeding value of fruits from D. cinerea and A. nilotica tree species may be reduced due to the presence of high levels of phenolics. (C) 2007 Elsevier B.V. All rights reserved.

Evaluation of NRC, UC Davis and ADAS approaches to estimate the metabolizable energy values of feeds at maintenance energy intake from equations utilizing chemical assays and in vitro determinations

Feed samples received by commercial analytical laboratories are often undefined or mixed varieties of forages, originate from various agronomic or geographical areas of the world, are mixtures (e.g., total mixed rations) and are often described incompletely or not at all. Six unified single equation approaches to predict the metabolizable energy (ME) value of feeds determined in sheep fed at maintenance ME intake were evaluated utilizing 78 individual feeds representing 17 different forages, grains, protein meals and by-product feedstuffs. The predictive approaches evaluated were two each from National Research Council [National Research Council (NRC), Nutrient Requirements of Dairy Cattle, seventh revised ed. National Academy Press, Washington, DC, USA, 2001], University of California at Davis (UC Davis) and ADAS (Stratford, UK). Slopes and intercepts for the two ADAS approaches that utilized in vitro digestibility of organic matter and either measured gross energy (GE), or a prediction of GE from component assays, and one UC Davis approach, based upon in vitro gas production and some component assays, differed from both unity and zero, respectively, while this was not the case for the two NRC and one UC Davis approach. However, within these latter three approaches, the goodness of fit (r(2)) increased from the NRC approach utilizing lignin (0.61) to the NRC approach utilizing 48 h in vitro digestion of neutral detergent fibre (NDF:0.72) and to the UC Davis approach utilizing a 30 h in vitro digestion of NDF (0.84). The reason for the difference between the precision of the NRC procedures was the failure of assayed lignin values to accurately predict 48 h in vitro digestion of NDF. However, differences among the six predictive approaches in the number of supporting assays, and their costs, as well as that the NRC approach is actually three related equations requiring categorical description of feeds (making them unsuitable for mixed feeds) while the ADAS and UC Davis approaches are single equations, suggests that the procedure of choice will vary dependent Upon local conditions, specific objectives and the feedstuffs to be evaluated. In contrast to the evaluation of the procedures among feedstuffs, no procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo, suggesting that the quest for an accurate and precise ME predictive approach among and within feeds, may remain to be identified. (C) 2004 Elsevier B.V. All rights reserved.

Analysis of shade and temperature effects on assimilate partitioning in the everbearing strawberry 'Everest' as the basis for optimised long-season fruit production

Growth patterns and cropping were evaluated over the season for the everbearing strawberry 'Everest' at a range of temperatures (15-27degreesC) in two light environments (ambient and 50% shade). The highest yield was recorded for unshaded plants grown at 23degreesC, but the optimum temperature for vegetative growth was 15degreesC. With increasing temperature fruit number increased, but fruit weight decreased. Fruit weight was also significantly reduced by shade, and although 'Everest' showed a degree of shade tolerance in vegetative growth, yield was consistently reduced by shade. Shade also reduced the number of crowns developed by the plants over the course of the season, emphasising that crown number was ultimately the limiting factor for yield potential. We conclude that, in contrast to Junebearers which partition more assimilates to fruit at temperatures around 15degreesC (Le Miere et al., 1998), optimised cropping in the everbearer 'Everest' is achieved at the significantly higher temperature of 23degreesC. These findings have significance for commercial production, in which protection tends to reduce light levels but increase average temperature throughout the season.

High-affinity small molecule-phospholipid complex formation: Binding of siramesine to phosphatidic acid

Siramesine (SRM) is a sigma-2 receptor agonist which has been recently shown to inhibit growth of cancer cells. Fluorescence spectroscopy experiments revealed two distinct binding sites for this drug in phospholipid membranes. More specifically, acidic phospholipids retain siramesine on the bilayer surface due to a high-affinity interaction, reaching saturation at an apparent 1:1 drug-acidic phospholipid stoichiometry, where after the drug penetrates into the hydrocarbon core of the membrane. This behavior was confirmed using Langmuir films. Of the anionic phospholipids, the highest affinity, comparable to the affinities for the binding of small molecule ligands to proteins, was measured for phosphatidic acid (PA, mole fraction Of X-PA = 0.2 in phosphatidylcholine vesicles), yielding a molecular partition coefficient of 240 +/- 80 x 10(6). An MD simulation on the siramesine:PA interaction was in agreement with the above data. Taking into account the key role of PA as a signaling molecule promoting cell growth our results suggest a new paradigm for the development of anticancer drugs, viz. design of small molecules specifically scavenging phospholipids involved in the signaling cascades controlling cell behavior.

Effect of internal partitioning on indoor air quality of rooms with mixing ventilation - basic study

The internal partitioning, which is frequently introduced in open-space planning due to its flexibility, was tested to study its effects on the room air quality as well as ventilation performance. For the study, physical tests using a small model room and numerical modeling using CFD computation were utilized to evaluate different test conditions employing mixing ventilation from the ceiling. The partition parameters, such as its location, height, and the gap underneath, as well as contaminant source location were tested under isothermal conditions. This paper summarizes the results from the study.

Antioxidant properties of Teaw (Cratoxylum formosum Dyer) extract in soybean oil and emulsions

The antioxidant activity of an extract from Teaw (Cratoxylum formosum Dyer) leaves was studied in soybean oil and soybean oil-in-water emulsions. Samples containing the extract or reference antioxidants including chlorogenic acid, which comprises 60% of the Teaw extract, were stored at 60 degrees C and analyzed periodically for peroxide value (PV) and thiobarbituric acid reactive substances (TBARS) to allow both hydroperoxides and hydroperoxide degradation products to be monitored. Chlorogenic acid and the Teaw extract were more effective than a-tocopherol in inhibiting lipid oxidation in bulk oil but were less effective in an oil-in-water emulsion in accordance with the polar paradox. The PV/TBARS ratio for oil samples containing chlorogenic acid was higher than for alpha-tocopherol and BHT because chlorogenic acid inhibits both hydroperoxide formation by radical scavenging and hydroperoxide decomposition by metal chelation. The importance of the metal-chelating activity in retarding hydroperoxide decomposition was confirmed by studying the decomposition of oil samples containing added ferric ions. The PV/TBARS ratio was higher for citric acid than for (x-tocopherol in the presence of added ferric chloride, but the order was reversed in samples lacking ferric chloride. Samples containing added chlorogenic acid gave the highest PV/TBARS ratios both in the presence and absence of ferric ions. The PV/TBARS ratios for the samples containing antioxidants fell rapidly to lower values in a soybean oil-in-water emulsion than in the soybean oil. This was due to increased hydroperoxide decomposition in the emulsion at the same PV. The Teaw extract contained 12% oil-soluble components, which contributed to a slightly higher oil-water partition coefficient than that of chlorogenic acid. The antioxidant activity of the aqueous phase of the Teaw extract was reduced more than that of chlorogenic acid by partitioning of the oil-soluble components into oil, which showed that the less-polar components contributed to the antioxidant activity of the Teaw extract in aqueous media.

Generalized neurofuzzy network modeling algorithms using Bezier-Bernstein polynomial functions and additive decomposition

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bezier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bezier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bezier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bezier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Data based constructive identification - overcoming the curse of dimensionality

The modelling of a nonlinear stochastic dynamical processes from data involves solving the problems of data gathering, preprocessing, model architecture selection, learning or adaptation, parametric evaluation and model validation. For a given model architecture such as associative memory networks, a common problem in non-linear modelling is the problem of "the curse of dimensionality". A series of complementary data based constructive identification schemes, mainly based on but not limited to an operating point dependent fuzzy models, are introduced in this paper with the aim to overcome the curse of dimensionality. These include (i) a mixture of experts algorithm based on a forward constrained regression algorithm; (ii) an inherent parsimonious delaunay input space partition based piecewise local lineal modelling concept; (iii) a neurofuzzy model constructive approach based on forward orthogonal least squares and optimal experimental design and finally (iv) the neurofuzzy model construction algorithm based on basis functions that are Bézier Bernstein polynomial functions and the additive decomposition. Illustrative examples demonstrate their applicability, showing that the final major hurdle in data based modelling has almost been removed.