Effect of hydrolyzed milk on the adhesion of Lactobacilli to intestinal cells

Milk is an essential part of the human diet and is undoubtedly a major calcium source in human nutrition, accepted well by most individuals. Knowledge on how the components from dairy products support or reduce the adherence of probiotics to the intestinal epithelium is limited. The purpose of this study was to investigate the effect of acid-hydrolyzed milk on the adhesion ability of two potentially probiotic strains (Lactobacillus plantarum S2, Lactobacillus gasseri R) to in vitro human intestinal epithelial model consisting of Caco-2 and mucus-secreting HT29-MTX co-culture. The adhesion of our tested strains L. gasseri and L. plantarum was 4.74 and 7.16%, respectively, when using inoculum of 2 × 108 CFU ml–1. Addition of acid-hydrolyzed milk to co-culture decreased the adherence by 53.7% for L. gasseri R and by 62.2% for L. plantarum S2. The results of this study evidently indicate the potential importance of the food matrix as a factor influencing probiotic colonization of the gut

Seasonal variation in uterotonic activity of Rhoicissus tridentata extracts

Background. Rhoicissus tridentata lignotubers are widely used in southern African traditional pregnancy-related remedies.Objectives. To determine the seasonal variation in contractile activity of extracts from different parts of the plant.Methods. Isolated rat uterus tissue was used to compare the contractile activity of crude aqueous extracts of R. tridentata made from plant material harvested every 3 months over a period of 2 years.Results and conclusions. The activity of the plant extracts from plants harvested in summer and autumn were 4 - 5- fold higher than extracts from plants harvested in winter or spring. The tubers stimulated the greatest degree of contractions, followed by the stems, roots and leaves. These results highlight the need to standardise the timing of harvesting R. tridentata

Global High-resolution Land-use Change Projections: A Bayesian Multinomial Logit Downscaling Approach Incorporating Model Uncertainty and Spatial Effects

Using econometric models to estimate land-use change has a long tradition in scientific literature. Recent contributions show the importance of including spatial information and of using a multinomial framework to take into account the interdependencies between the land-use classes. Few studies, however, agree on the relevant determinants of land-use change and there are no contributions so far comparing determinants on a global scale. Using multiple 5 arc minute resolution datasets of land-use change between 2000 and 2010 and taking into account the transitions between forest, cropland, grassland and all other land covers, we estimate a Bayesian multinomial logit model, using the efficient Pólya-Gamma sampling procedure introduced by Polson et al. (2013). To identify and measure the determinants of land-use change and the strength of spatial separation, our model implements Bayesian model selection through stochastic search variable selection (SSVS) priors and spatial information via Gaussian Process (GP) priors. Our results indicate that spatial proximity is of central importance in land-use change, in all regions except the pacific islands. We also show that infrastructure policy, proxied by mean time to market, seems to have a significant impact on deforestation throughout most regions. In a second step we use aggregate, supra national land-use change results from the partial equilibrium agricultural model GLOBIOM as a framework for projecting our model in ten-year intervals up to 2100 on a spatially explicit scale along multiple shared socioeconomic pathways

Malaria at Johannesburg Hospital A retrospective study

A total of 43 patients diagnosed as having malaria were admitled to Johannesburg Hospital during 1988; 40 (94%) were infected with Plasmodium falciparum. Only 26 patients (60%) were recorded as having used prophylaxis of any kind; chloroquine alone and in combination was used as prophylaxis by 17:. Patients were treated with quinine (alone or in combination) in 67% of cases. In 42% of patients chloroquine- resistant malaria was considered a possibility

Highlighting continued uncertainty in global land cover maps for the user community

In the last 10 years a number of new global datasets have been created and new, more sophisticated alorithms have been designed to classify land cover. GlobCover and MODIS v.5 are the most recent global land cover products available, where GlobCover (300 m) has the finest spatial resolution of other comparable products such as MODIS v.5 (50 m) and GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has decreased when comparing these two latest products. This disagreement is also evident spatially when examining maps of cropland and forest disargeement between GLC-2000, MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding these prducts, with a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This letter suggests that data sharing efforts and the provision of more 'in situ' data for training, calibration and validation are very important conditions for improving future global land cover products

The European Forest and Agriculture Optimisation Model -- EUFASOM

Land use is a key factor to social wellbeing and has become a major component in political negotiations. This paper describes the mathematical structure of the European Forest and Agricultural Sector Optimization Model. The model represents simultaneously observed resource and technological heterogeneity, global commodity markets, and multiple environmental qualities. Land scarcity and land competition between traditional agriculture, forests, nature reserves, pastures, and bioenergy plantations is explicitly captured. Environmental change, technological progress, and policies can be investigated in parallel. The model is well-suited to estimate competitive economic potentials of land based mitigation, leakage, and synergies and trade-offs between multiple environmental objectives.Land Use Change Optimization, Resource Scarcity, Market Competition, Welfare Maximization, Bottom-up Partial Equilibrium Analysis, Agricultural Externality Mitigation, Forest Dynamics, Global Change Adaptation, Environmental Policy Simulation, Integrated Assessment, Mathematical Programming, GAMS

Seasonality constraints to livestock grazing intensity

Increasing food production is essential to meet the future food demand of a growing world population. In the light of pressing sustainability challenges like climate change and the importance of the global livestock system for food security as well as GHG emissions, finding ways to increasing food production sustainably and without increasing competition for food crops is essential. Yet, many unknowns relate to livestock grazing, in particular grazing intensity, an essential variable to assess the sustainability of livestock systems. Here we explore ecological limits to grazing intensity (GI; i.e., the fraction of Net Primary Production consumed by grazing animals) by analysing the role of seasonality in natural grasslands. We estimate seasonal limitations to GI by combining monthly Net Primary Production data and a map of global livestock distribution with assumptions on the length of non-favourable periods that can be bridged by livestock (e.g., by browsing dead standing biomass, storage systems or biomass conservation). This allows us to derive a seasonality-limited potential GI, which we compare with the GI prevailing in 2000. We find that GI in 2000 lies below its potential on 39% of the total global natural grasslands, which has a potential for increasing biomass extraction of up to 181 MtC/yr. In contrast, on 61% of the area GI exceeds the potential, made possible by management. Mobilizing this potential could increase milk production by 5%, meat production by 4%, or contribute to free up to 2.8 Mio km² of grassland area at the global scale if the numerous socio-ecological constraints can be overcome. We discuss socio-ecological trade-offs, which may reduce the estimated potential considerably and require the establishment of sound monitoring systems and an improved understanding of livestock system’s role in the Earth system

Spatially explicit estimates of N2O emissions from croplands suggest climate mitigation opportunities from improved fertilizer management

With increasing nitrogen (N) application to croplands required to support growing food demand, mitigating N2O emissions from agricultural soils is a global challenge. National greenhouse gas emissions accounting typically estimates N2O emissions at the country scale by aggregating all crops, under the assumption that N2O emissions are linearly related to N application. However, field studies and meta-analyses indicate a nonlinear relationship, in which N2O emissions are relatively greater at higher N application rates. Here we apply a super-linear emissions response model to crop-specific, spatially-explicit synthetic N fertilizer and manure N inputs to provide subnational accounting of global N2O emissions from croplands. We estimate 0.66 Tg of N2O-N direct global emissions circa 2000, with 50% of emissions concentrated in 13% of harvested area. Compared to estimates from the IPCC Tier 1 linear model, our updated N2O emissions range from 20-40% lower throughout Sub-Saharan Africa and Eastern Europe, to >120% greater in some Western European countries. At low N application rates, the weak non-linear response of N2O emissions suggests that relatively large increases in N fertilizer application would generate relatively small increases in N2O emissions. Since aggregated fertilizer data generate underestimation bias in nonlinear models, high-resolution N application data are critical to support accurate N2O emissions estimates