Effects of cis-9,trans-11 and trans-1 0,cis-12 conjugated linoleic acid on immune cell function in healthy humans

Background: Animal studies have suggested that conjugated linoleic acid (CLA), a natural component of ruminant meat and dairy products, may confer beneficial effects on health. However, little information on the effects of CLA on immune function is available, especially in humans. Furthermore, the effects of individual isomers of CLA have not been adequately investigated. Objective: This study investigated the effects of supplementing the diet with 3 doses of highly enriched cis-9,trans-11 CLA (0.59, 1.19, and 2.38 g/d) or trans-10,cis-12 CLA (0.63, 1.26, and 2.52 g/d) on immune outcomes in healthy humans. Design: The study had a randomized, double-blind, crossover design. Healthy men consumed 1, 2, and 4 capsules sequentially that contained 80% of either cis-9,trans-11 CLA or trans-10,cis-12 CLA for consecutive 8-wk periods. This regimen was followed by a 6-wk washout and a crossover to the other isomer. Results: Both CLA isomers decreased mitogen-induced T lymphocyte activation in a dose-dependent manner. There was a significant negative correlation between mitogen-induced T lymphocyte activation and the proportions of both cis-9,trans-11 CLA and trans-10,cis-12 CLA in peripheral blood mononuclear cell lipids. However, CLA did not affect lymphocyte subpopulations or serum concentrations of C-reactive protein and did not have any consistent effects on ex vivo cytokine production. Conclusion: CLA supplementation results in a dose-dependent reduction in the mitogen-induced activation of T lymphocytes. The effects of cis-9,trans-l I CLA and trans-10,cis-12 CLA were similar, and there was a negative correlation between mitogen-induced T lymphocyte activation and the cis-9,trans-11 CLA and trans-10,cis-12 CLA contents of mononuclear cells.

Differences between the gut microflora of children with autistic spectrum disorders and that of healthy children

Children with autistic spectrum disorders (ASDs) tend to suffer from severe gastrointestinal problems. Such symptoms may be due to a disruption of the indigenous gut flora promoting the overgrowth of potentially pathogenic micro-organisms. The faecal flora of patients with ASDs was studied and compared with those of two control groups (healthy siblings and unrelated healthy children). Faecal bacterial populations were assessed through the use of a culture-independent technique, fluorescence in situ hybridization, using oligonucleotide probes targeting predominant components of the gut flora. The faecal flora of ASD patients contained a higher incidence of the Clostridium histolyticum group (Clostridium clusters I and 11) of bacteria than that of healthy children. However, the non-autistic sibling group had an intermediate level of the C. histolyticum group, which was not significantly different from either of the other subject groups. Members of the C. histolyticum group are recognized toxin-producers and may contribute towards gut dysfunction, with their metabolic products also exerting systemic effects. Strategies to reduce clostridial population levels harboured by ASD patients or to improve their gut microflora profile through dietary modulation may help to alleviate gut disorders common in such patients.

Hypothesis about mechanisms through which nicotine might exert its effect on the interdependence of inflammation and gut barrier function in ulcerative colitis

Ulcerative colitis (UC) is characterized by impairment of the epithelial barrier and the formation of ulcer-type lesions, which result in local leaks and generalized alterations of mucosal tight junctions. Ultimately, this results in increased basal permeability. Although disruption of the epithelial barrier in the gut is a hallmark of inflammatory bowel disease and intestinal infections, it remains unclear whether barrier breakdown is an initiating event of UC or rather a consequence of an underlying inflammation, evidenced by increased production of proinflammatory cytokines. UC is less common in smokers, suggesting that the nicotine in cigarettes may ameliorate disease severity. The mechanism behind this therapeutic effect is still not fully understood, and indeed it remains unclear if nicotine is the true protective agent in cigarettes. Nicotine is metabolized in the body into a variety of metabolites and can also be degraded to form various breakdown products. It is possible these metabolites or degradation products may be the true protective or curative agents. A greater understanding of the pharmacodynamics and kinetics of nicotine in relation to the immune system and enhanced knowledge of out permeability defects in UC are required to establish the exact protective nature of nicotine and its metabolites in UC. This review suggests possible hypotheses for the protective mechanism of nicotine in UC, highlighting the relationship between gut permeability and inflammation, and indicates where in the pathogenesis of the disease nicotine may mediate its effect.

The full-spectrum correlated k method for longwave atmospheric radiative transfer: treatment of gaseous overlap

The correlated k-distribution (CKD) method is widely used in the radiative transfer schemes of atmospheric models, and involves dividing the spectrum into a number of bands and then reordering the gaseous absorption coefficients within each one. The fluxes and heating rates for each band may then be computed by discretizing the reordered spectrum into of order 10 quadrature points per major gas, and performing a pseudo-monochromatic radiation calculation for each point. In this paper it is first argued that for clear-sky longwave calculations, sufficient accuracy for most applications can be achieved without the need for bands: reordering may be performed on the entire longwave spectrum. The resulting full-spectrum correlated k (FSCK) method requires significantly fewer pseudo-monochromatic calculations than standard CKD to achieve a given accuracy. The concept is first demonstrated by comparing with line-by-line calculations for an atmosphere containing only water vapor, in which it is shown that the accuracy of heating-rate calculations improves approximately in proportion to the square of the number of quadrature points. For more than around 20 points, the root-mean-squared error flattens out at around 0.015 K d−1 due to the imperfect rank correlation of absorption spectra at different pressures in the profile. The spectral overlap of m different gases is treated by considering an m-dimensional hypercube where each axis corresponds to the reordered spectrum of one of the gases. This hypercube is then divided up into a number of volumes, each approximated by a single quadrature point, such that the total number of quadrature points is slightly fewer than the sum of the number that would be required to treat each of the gases separately. The gaseous absorptions for each quadrature point are optimized such they minimize a cost function expressing the deviation of the heating rates and fluxes calculated by the FSCK method from line-by-line calculations for a number of training profiles. This approach is validated for atmospheres containing water vapor, carbon dioxide and ozone, in which it is found that in the troposphere and most of the stratosphere, heating-rate errors of less than 0.2 K d−1 can be achieved using a total of 23 quadrature points, decreasing to less than 0.1 K d−1 for 32 quadrature points. It would be relatively straightforward to extend the method to include other gases.

A double-blind, placebo-controlled, crossover-designed probiotic feeding study in children diagnosed with autistic spectrum disorders

There is growing interest in the role of gastrointestinal (GI) pathology and clinical expression of autism. Recent studies have demonstrated differences in the faecal clostridial populations harboured by autistic and non-autistic children. The potential of Lactobacillus plantarum WCSF1 (a probiotic) to modulate the gut microbiota of autistic subjects was investigated during a double-blind, placebo-controlled, crossover-designed feeding study. The faecal microbiota, gut function and behaviour scores of subjects were examined throughout the 12-week study. Lactobacillus plantarum WCFS1 feeding significantly increased Lab158 counts (lactobacilli and enterococci group) and significantly reduced Erec482 counts (Clostridium cluster XIVa) compared to placebo. Probiotic feeding also resulted in significant differences in the stool consistency compared to placebo and behaviour scores (total score and scores for some subscales) compared to baseline. The major finding of this work was the importance of study protocol in relation to the specific considerations of this subject population, with an extremely high dropout rate seen (predominantly during the baseline period). Furthermore, the relatively high inter-individual variability observed suggests that subsequent studies should use defined subgroups of autistic spectrum disorders, such as regressive or late-onset autism. In summary, the current study has highlighted the potential benefit of L. plantarum WCFS1 probiotic feeding in autistic individuals.

A novel method for assessing risks to pollinators from plant protection products using honeybees as a model species

Pollination is one of the most important ecosystem services in agroecosystems and supports food production. Pollinators are potentially at risk being exposed to pesticides and the main route of exposure is direct contact, in some cases ingestion, of contaminated materials such as pollen, nectar, flowers and foliage. To date there are no suitable methods for predicting pesticide exposure for pollinators, therefore official procedures to assess pesticide risk are based on a Hazard Quotient. Here we develop a procedure to assess exposure and risk for pollinators based on the foraging behaviour of honeybees (Apis mellifera) and using this species as indicator representative of pollinating insects. The method was applied in 13 European field sites with different climatic, landscape and land use characteristics. The level of risk during the crop growing season was evaluated as a function of the active ingredients used and application regime. Risk levels were primarily determined by the agronomic practices employed (i.e. crop type, pest control method, pesticide use), and there was a clear temporal partitioning of risks through time. Generally the risk was higher in sites cultivated with permanent crops, such as vineyard and olive, than in annual crops, such as cereals and oil seed rape. The greatest level of risk is generally found at the beginning of the growing season for annual crops and later in June–July for permanent crops.

Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water

We present a novel kinetic multi-layer model for gas-particle interactions in aerosols and clouds (KM-GAP) that treats explicitly all steps of mass transport and chemical reaction of semi-volatile species partitioning between gas phase, particle surface and particle bulk. KM-GAP is based on the PRA model framework (Pöschl-Rudich-Ammann, 2007), and it includes gas phase diffusion, reversible adsorption, surface reactions, bulk diffusion and reaction, as well as condensation, evaporation and heat transfer. The size change of atmospheric particles and the temporal evolution and spatial profile of the concentration of individual chemical species can be modelled along with gas uptake and accommodation coefficients. Depending on the complexity of the investigated system, unlimited numbers of semi-volatile species, chemical reactions, and physical processes can be treated, and the model shall help to bridge gaps in the understanding and quantification of multiphase chemistry and microphysics in atmo- spheric aerosols and clouds. In this study we demonstrate how KM-GAP can be used to analyze, interpret and design experimental investigations of changes in particle size and chemical composition in response to condensation, evaporation, and chemical reaction. For the condensational growth of water droplets, our kinetic model results provide a direct link between laboratory observations and molecular dynamic simulations, confirming that the accommodation coefficient of water at 270 K is close to unity. Literature data on the evaporation of dioctyl phthalate as a function of particle size and time can be reproduced, and the model results suggest that changes in the experimental conditions like aerosol particle concentration and chamber geometry may influence the evaporation kinetics and can be optimized for eðcient probing of specific physical effects and parameters. With regard to oxidative aging of organic aerosol particles, we illustrate how the formation and evaporation of volatile reaction products like nonanal can cause a decrease in the size of oleic acid particles exposed to ozone.

Effect of dextransucrase cellobiose acceptor products on the growth of human gut bacteria

The selective fermentation by human gut bacteria of gluco-oligosaccharides obtained from the reaction between the glucosyl group of sucrose and cellobiose, catalyzed by dextransucrases (DSR) from Leuconostoc mesenteroides, has been evaluated. Oligosaccharides were fractionated according to their molecular weight, and their effect on the growth of different bacterial groups was studied. To determine the structure (position and configuration of glycosidic linkages)�function relationship, their properties were compared to those of DSR maltose acceptor products (DSRMal) and of recognized prebiotic carbohydrates (fructo-oligosaccharides, FOS). Cellobiose acceptor products (DSRCel) showed bifidogenic properties similar to those of FOS. However, no significant differences related to molecular weight or isomeric configurations were found for DSRCel and DSRMal products.

Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water

We present a novel kinetic multi-layer model for gas-particle interactions in aerosols and clouds (KMGAP) that treats explicitly all steps of mass transport and chemical reaction of semi-volatile species partitioning between gas phase, particle surface and particle bulk. KMGAP is based on the PRA model framework (P¨oschl-Rudich- Ammann, 2007), and it includes gas phase diffusion, reversible adsorption, surface reactions, bulk diffusion and reaction, as well as condensation, evaporation and heat transfer. The size change of atmospheric particles and the temporal evolution and spatial profile of the concentration of individual chemical species can be modeled along with gas uptake and accommodation coefficients. Depending on the complexity of the investigated system and the computational constraints, unlimited numbers of semi-volatile species, chemical reactions, and physical processes can be treated, and the model shall help to bridge gaps in the understanding and quantification of multiphase chemistry and microphysics in atmospheric aerosols and clouds. In this study we demonstrate how KM-GAP can be used to analyze, interpret and design experimental investigations of changes in particle size and chemical composition in response to condensation, evaporation, and chemical reaction. For the condensational growth of water droplets, our kinetic model results provide a direct link between laboratory observations and molecular dynamic simulations, confirming that the accommodation coefficient of water at 270K is close to unity (Winkler et al., 2006). Literature data on the evaporation of dioctyl phthalate as a function of particle size and time can be reproduced, and the model results suggest that changes in the experimental conditions like aerosol particle concentration and chamber geometry may influence the evaporation kinetics and can be optimized for efficient probing of specific physical effects and parameters. With regard to oxidative aging of organic aerosol particles, we illustrate how the formation and evaporation of volatile reaction products like nonanal can cause a decrease in the size of oleic acid particles exposed to ozone.

Effects of fermentation products of pro- and prebiotics on trans-epithelial electrical resistance in an in vitro model of the colon

Evidence from in vivo and in vitro studies suggests that the consumption of pro- and prebiotics may inhibit colon carcinogenesis; however, the mechanisms involved have, thus far, proved elusive. There are some indications from animal studies that the effects are being exerted during the promotion stage of carcinogenesis. One feature of the promotion stage of colorectal cancer is the disruption of tight junctions, leading to a loss of integrity across the intestinal barrier. We have used the Caco-2 human adenocarcinoma cell line as a model for the intestinal epithelia. Trans-epithelial electrical resistance measurements indicate Caco-2 monolayer integrity, and we recorded changes to this integrity following exposure to the fermentation products of selected probiotics and prebiotics, in the form of nondigestible oligosaccharides (NDOs). Our results indicate that NDOs themselves exert varying, but generally minor, effects upon the strength of the tight junctions, whereas the fermentation products of probiotics and NDOs tend to raise tight junction integrity above that of the controls. This effect was bacterial species and oligosaccharide specific. Bifidobacterium Bb 12 was particularly effective, as were the fermentation products of Raftiline and Raftilose. We further investigated the ability of Raftilose fermentations to protect against the negative effects of deoxycholic acid (DCA) upon tight junction integrity. We found protection to be species dependent and dependent upon the presence of the fermentation products in the media at the same time as or after exposure to the DCA. Results suggest that the Raftilose fermentation products may prevent disruption of the intestinal epithelial barrier function during damage by tumor promoters.

A study on orthogonality sampling.

The goal of this paper is to study and further develop the orthogonality sampling or stationary waves algorithm for the detection of the location and shape of objects from the far field pattern of scattered waves in electromagnetics or acoustics. Orthogonality sampling can be seen as a special beam forming algorithm with some links to the point source method and to the linear sampling method. The basic idea of orthogonality sampling is to sample the space under consideration by calculating scalar products of the measured far field pattern , with a test function for all y in a subset Q of the space , m = 2, 3. The way in which this is carried out is important to extract the information which the scattered fields contain. The theoretical foundation of orthogonality sampling is only partly resolved, and the goal of this work is to initiate further research by numerical demonstration of the high potential of the approach. We implement the method for a two-dimensional setting for the Helmholtz equation, which represents electromagnetic scattering when the setup is independent of the third coordinate. We show reconstructions of the location and shape of objects from measurements of the scattered field for one or several directions of incidence and one or many frequencies or wave numbers, respectively. In particular, we visualize the indicator function both with the Dirichlet and Neumann boundary condition and for complicated inhomogeneous media.

(Non-)ergodicity of a degenerate diffusion modeling the fiber lay down process

We analyze the large time behavior of a stochastic model for the lay down of fibers on a moving conveyor belt in the production process of nonwovens. It is shown that under weak conditions this degenerate diffusion process has a unique invariant distribution and is even geometrically ergodic. This generalizes results from previous works [M. Grothaus and A. Klar, SIAM J. Math. Anal., 40 (2008), pp. 968–983; J. Dolbeault et al., arXiv:1201.2156] concerning the case of a stationary conveyor belt, in which the situation of a moving conveyor belt has been left open.

The sample autocorrelation function and the detection of long-memory processes

The detection of long-range dependence in time series analysis is an important task to which this paper contributes by showing that whilst the theoretical definition of a long-memory (or long-range dependent) process is based on the autocorrelation function, it is not possible for long memory to be identified using the sum of the sample autocorrelations, as usually defined. The reason for this is that the sample sum is a predetermined constant for any stationary time series; a result that is independent of the sample size. Diagnostic or estimation procedures, such as those in the frequency domain, that embed this sum are equally open to this criticism. We develop this result in the context of long memory, extending it to the implications for the spectral density function and the variance of partial sums of a stationary stochastic process. The results are further extended to higher order sample autocorrelations and the bispectral density. The corresponding result is that the sum of the third order sample (auto) bicorrelations at lags h,k≥1, is also a predetermined constant, different from that in the second order case, for any stationary time series of arbitrary length.

The Empirical Forcing Function as a tool for the diagnosis of large-scale atmospheric anomalies

The time-mean quasi-geostrophic potential vorticity equation of the atmospheric flow on isobaric surfaces can explicitly include an atmospheric (internal) forcing term of the stationary-eddy flow. In fact, neglecting some non-linear terms in this equation, this forcing can be mathematically expressed as a single function, called Empirical Forcing Function (EFF), which is equal to the material derivative of the time-mean potential vorticity. Furthermore, the EFF can be decomposed as a sum of seven components, each one representing a forcing mechanism of different nature. These mechanisms include diabatic components associated with the radiative forcing, latent heat release and frictional dissipation, and components related to transient eddy transports of heat and momentum. All these factors quantify the role of the transient eddies in forcing the atmospheric circulation. In order to assess the relevance of the EFF in diagnosing large-scale anomalies in the atmospheric circulation, the relationship between the EFF and the occurrence of strong North Atlantic ridges over the Eastern North Atlantic is analyzed, which are often precursors of severe droughts over Western Iberia. For such events, the EFF pattern depicts a clear dipolar structure over the North Atlantic; cyclonic (anticyclonic) forcing of potential vorticity is found upstream (downstream) of the anomalously strong ridges. Results also show that the most significant components are related to the diabatic processes. Lastly, these results highlight the relevance of the EFF in diagnosing large-scale anomalies, also providing some insight into their interaction with different physical mechanisms.

Multiscale geostatistical analysis of AVHRR, SPOT-VGT, and MODIS global NDVI products

Global NDVI data are routinely derived from the AVHRR, SPOT-VGT, and MODIS/Terra earth observation records for a range of applications from terrestrial vegetation monitoring to climate change modeling. This has led to a substantial interest in the harmonization of multisensor records. Most evaluations of the internal consistency and continuity of global multisensor NDVI products have focused on time-series harmonization in the spectral domain, often neglecting the spatial domain. We fill this void by applying variogram modeling (a) to evaluate the differences in spatial variability between 8-km AVHRR, 1-km SPOT-VGT, and 1-km, 500-m, and 250-m MODIS NDVI products over eight EOS (Earth Observing System) validation sites, and (b) to characterize the decay of spatial variability as a function of pixel size (i.e. data regularization) for spatially aggregated Landsat ETM+ NDVI products and a real multisensor dataset. First, we demonstrate that the conjunctive analysis of two variogram properties – the sill and the mean length scale metric – provides a robust assessment of the differences in spatial variability between multiscale NDVI products that are due to spatial (nominal pixel size, point spread function, and view angle) and non-spatial (sensor calibration, cloud clearing, atmospheric corrections, and length of multi-day compositing period) factors. Next, we show that as the nominal pixel size increases, the decay of spatial information content follows a logarithmic relationship with stronger fit value for the spatially aggregated NDVI products (R2 = 0.9321) than for the native-resolution AVHRR, SPOT-VGT, and MODIS NDVI products (R2 = 0.5064). This relationship serves as a reference for evaluation of the differences in spatial variability and length scales in multiscale datasets at native or aggregated spatial resolutions. The outcomes of this study suggest that multisensor NDVI records cannot be integrated into a long-term data record without proper consideration of all factors affecting their spatial consistency. Hence, we propose an approach for selecting the spatial resolution, at which differences in spatial variability between NDVI products from multiple sensors are minimized. This approach provides practical guidance for the harmonization of long-term multisensor datasets.