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

Towards Sustainable Livestock Production Systems: Analyzing Ecological Constraints to Grazing Intensity

Increasing food production from cropland and grassland is essential to meet the future food demand of a growing world population without further land-use expansion. It is estimated that until 2050, food production has to increase strongly to meet future food demands. Increasing food production from grasslands in a sustainable way (e.g., by not degrading essential ecosystem services) is important, yet requires a good understanding of the major determinants and constraints of the global livestock production systems and the associated socio-economic and ecological patterns. The spatially explicit analysis of grazing intensity (GI; e.g., the fraction of available Net Primary Production (NPP) that is consumed by grazing animals in a year) using monthly data allow us to analyse the role of seasonality for limits to grazing intensity. Seasonality creates in many regions of the world shortage and surplus periods of NPP, which can (partly) be overcome by social organization, such as the employment of storage technologies or by imports. By comparing the current livestock density to the ecologically maximum density (EMD) determined by biomass availability during shortage periods we show that management has contributed to substantial higher livestock density in many world-regions whereas in others it is still close to the EMD. Our analysis shows to which expense (e.g., length of shortage period to overcome) the increase in livestock-density comes in different world regions and where potential for further biomass extraction exists. This study contributes to an improved understanding of the systemic inter-linkages between GI, seasonal biomass supply, and socioeconomic and ecological trade-offs, and provides essential information for analyzing intensification potentials of grasslands

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

Heat recovery from biomass drying in energy systems

[EN] his paper deals with energy savings by the heat recovery of waste vapour from moist biomass drying in energy systems. Drying is an energy-intensive process. Energy consumption can be reduced by using indirect drying by recuperating the heat of waste vapour generated in the process; however the vapour is polluted by air and small mechanical particles. Experiments with green wood chips were realized on an indirect dryer with a condensing heat exchanger to experimentally verify the grade and conditions of heat recovery from waste vapour. On the basis of the experimental results, the potential of the heat recovery from waste vapour was evaluated.This work has been supported by the Technology Agency of the Czech Republic, project no. TJ01000192.Havlik, J.; Dlouhý, T. (2018). Heat recovery from biomass drying in energy systems. En IDS 2018. 21st International Drying Symposium Proceedings. Editorial Universitat Politècnica de València. 1229-1236. https://doi.org/10.4995/IDS2018.2018.7300OCS1229123

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

Inclusive climate change mitigation and food security policy under 1.5°C climate goal

Climate change mitigation to limit warming to 1.5°C or well below 2°C, as suggested by the Paris Agreement, can rely on large-scale deployment of land-related measures (e.g., afforestation, or bioenergy production). This can increase food prices, and hence raises food security concerns. Here we show how an inclusive policy design can avoid these adverse side-effects. Food-security support through international aid, bioenergy tax, or domestic reallocation of income can shield impoverished and vulnerable people from the additional risk of hunger that would be caused by the economic effects of policies narrowly focussing on climate objectives only. In absence of such support, 35% more people might be at risk of hunger by 2050 (i.e. 84 million additional people) in a 2°C-consistent scenario. The additional global welfare changes due to inclusive climate policies are small (<0.1%) compared to the total climate mitigation cost (3.7% welfare loss), and the financial costs of international aid amount to about half a percent of high-income countries' GDP. This implies that climate policy should treat this issue carefully. Although there are challenges to implement food policies, options exist to avoid the food security concerns often linked to climate mitigation

Assessing global resource use and greenhouse emissions to 2050, with ambitious resource efficiency and climate mitigation policies

Achieving sustainable development requires the decoupling of natural resource use and environmental pressures from economic growth and improvements in living standards. G7 leaders and others have called for improved resource efficiency, along with inclusive economic growth and deep cuts in global greenhouse emissions. However, the outlooks for and interactions between global natural resource use, resource efficiency, economic growth and greenhouse emissions are not well understood. We use a novel multi-regional modeling framework to develop projections to 2050 under existing trends and three policy scenarios. We find that resource efficiency could provide pro-growth pro-environment policies with global benefits of USD $2.4 trillion in 2050, and ease the politics of shifting towards sustainability. Under existing trends, resource extraction is projected to increase 119% from 2015 to 2050, from 84 to 184 billion tonnes per annum, while greenhouse gas emissions increase 41%, both driven by the value of global economic activity more than doubling. Resource efficiency and greenhouse abatement slow the growth of global resource extraction, so that in 2050 it is up to 28% lower than in existing trends. Resource efficiency reduces greenhouse gas emissions by 15–20% in 2050, with global emissions falling to 63% below 2015 levels when combined with a 2 °C emissions pathway. In contrast to greenhouse abatement, resource efficiency boosts near-term economic growth. These economic gains more than offset the near-term costs of shifting to a 2 °C emissions pathway, resulting in emissions in 2050 well below current levels, slower growth in resource extractions, and faster economic growth

Integrated Management of Land-use Systems under Systemic Risks and Food-(bio)energy-water-environmental Security Targets: A Stochastic Global Biosphere Management Model

Interdependencies among land-use systems resemble a complex network connected through demand–supply relations, and disruption of the network may catalyze systemic risks affecting food, energy, water, and environmental security (FEWES) worldwide. This paper describes the conceptual development, expansion, and practical application of a stochastic version of the Global Biosphere Management Model (GLOBIOM), a model that is used to assess competition for land use between agriculture, bioenergy, and forestry at regional and global scales. In the stochastic version of the model, systemic risks of various kinds are explicitly covered and can be analyzed and mitigated in all their interactions. While traditional deterministic scenario analysis produces sets of often contradictory outcomes, stochastic GLOBIOM explicitly derives robust decisions that leave the systems better off, independently of what scenario occurs. Stochastic GLOBIOM is formulated as a stochastic optimization model that is central for evaluating portfolios of robust interdependent decisions: ex ante strategic decisions (production allocation, storage capacities) and ex post adaptive (demand, trading, storage control) decisions. For example, the model is applied to the case of increased storage facilities, which can be viewed as catastrophe pools to buffer production shortfalls and fulfill regional and global FEWES requirements when extreme events occur. Expected shortfalls and storage capacities have a close relation with Value-at-Risk and Conditional Value-at-Risk risk measures. The Value of Stochastic Solutions is calculated to present the benefits of the stochastic over the deterministic model

Robust Rescaling Methods for Integrated Water, Food, and Energy Security Management under Systemic Risks and Uncertainty

The aim of this presentation is to discuss robust, non-Bayesian, probabilistic, cross-entropy-based disaggregation (downscaling) techniques. Systems analysis of global change (including climate) processes requires new approaches to integrating and rescaling of models, data, and decision-making procedures between various scales. For example, in the analysis of water security issues, the hydrological models require inputs that are much finer than the resolution of, say, the economic or climatic models generating those inputs. In relation to food security, aggregate national or regional land-use projections derived with global economic land-use planning models give no insights into potentially critical heterogeneities of local trends. Many practical studies analyzing regional developments use cross-entropy minimization as an underlying principle for estimation of local processes. However, the traditional cross-entropy approach relies on a single prior distribution. In reality, we can identify a set of feasible priors. This is relevant, in particular, for land-cover data. Existing global land cover maps (GLC2000, MODIS2000, GLOBCOVER2000) differ in terms of spatially resolved estimates of land use, (e.g., crop, forest, and grass lands). We present novel general approach to achieving downscaling results that are robust with respect to a set of potential prior distributions reflecting non-Bayesian uncertainties, that is, data that are incomplete or not directly observable. The robust downscaling problem is formulated as a probabilistic inverse problem (from aggregate to local data) generally in the form of a non-convex, cross-entropy minimization model. The approach will be illustrated by sequential downscaling aggregate model projections of land-use changes using the Global Biosphere Management Model, with case studies from Africa, Brazil, China, and Ukraine. The approach is being used to harmonize alternative land-cover maps and to develop hybrid maps

Tackling food consumption inequality to fight hunger without pressuring the environment

Ending hunger is a Sustainable Development Goal of the UN. However, feeding a growing world population by increasing food production without implementing more sustainable consumption will threaten the environment. We explore alternative hunger eradication scenarios that do not compromise environmental protection. We find that an economy-growth-oriented scenario, which ignores inequitable food distribution and is aimed at ending hunger by increasing overall food availability, would require about 20% more food production, 48 Mha of additional agricultural land and would increase greenhouse gas emissions by 550 Mt of CO2 equivalents yr−1 in 2030, compared with the business-as-usual scenario. If hunger eradication efforts were focused solely on the under-nourished, food demand would increase by only 3%, and the associated environmental trade-offs would be largely reduced. Moreover, a combined scenario that targets the under-nourished while also reducing over-consumption, food waste, agricultural intensification and other environmental impacts would reduce food demand by 9% compared with the business-as-usual scenario and would lead to the multiple benefits of reducing hunger and contributing to environmental sustainability