747 resultados para Diabetes and challenges


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Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean–atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.

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This paper considers the potential contribution of secondary quantitative analyses of large scale surveys to the investigation of 'other' childhoods. Exploring other childhoods involves investigating the experience of young people who are unequally positioned in relation to multiple, embodied, identity locations, such as (dis)ability, 'class', gender, sexuality, ethnicity and race. Despite some possible advantages of utilising extensive databases, the paper outlines a number of methodological problems with existing surveys which tend to reinforce adultist and broader hierarchical social relations. It is contended that scholars of children's geographies could overcome some of these problematic aspects of secondary data sources by endeavouring to transform the research relations of large scale surveys. Such endeavours would present new theoretical, ethical and methodological complexities, which are briefly considered.

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The discovery of new molecular targets and the subsequent development of novel anticancer agents are opening new possibilities for drug combination therapy as anticancer treatment. Polymer-drug conjugates are well established for the delivery of a single therapeutic agent, but only in very recent years their use has been extended to the delivery of multi-agent therapy. These early studies revealed the therapeutic potential of this application but raised new challenges (namely, drug loading and drugs ratio, characterisation, and development of suitable carriers) that need to be addressed for a successful optimisation of the system towards clinical applications.

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Objectives: To conduct it detailed evaluation, with meta-analyses, of the published evidence on milk and dairy consumption and the incidence of vascular diseases and diabetes. Also to summarise the evidence on milk and dairy consumption and cancer reported by the World Cancer Research Fund and then to consider the relevance of milk and dairy consumption to survival in the UK, a typical Western community. Finally, published evidence on relationships with whole milk and fat-reduced milks was examined. Methods: Prospective cohort studies of vascular disease and diabetes with baseline data on milk or dairy consumption and a relevant disease outcome were identified by searching MEDLINE, and reference lists in the relevant published reports. Meta-analyses of relationships in these reports were conducted. The likely effect of milk and dairy consumption on survival was then considered, taking into account the results of published overviews of relationships of these foods with cancer. Results: From meta-analysis of 15 studies the relative risk of stroke and/or heart disease in subjects with high milk or dairy consumption was 0.84 (95% CI 0.76, 0,93) and 0.79 (0.75, 0.82) respectively, relative to the risk in those with low consumption. Four studies reported incident diabetes as an outcome, and the relative risk in the Subjects with the highest intake of milk or diary foods was 0.92 (0.86, 0.97). Conclusions: Set against the proportion of total deaths attributable to the life-threatening diseases in the UK, vascular disease, diabetes and cancer, the results of meta-analyses provide evidence of an overall survival advantage from the consumption of milk and dairy foods.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

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This paper critically examines the challenges with, and impacts of, adopting the models in place for fair trade agriculture in the artisanal gold mining sector. Over the past two years, an NGO-led 'fair trade gold' movement has surfaced, its crystallization fuelled by a burgeoning body of evidence that points to impoverished artisanal miners in developing countries receiving low payments for their gold, as well as working in hazardous and unsanitary conditions. Proponents of fair trade gold contest that increased interaction between artisanal miners and Western jewellers could facilitate the former receiving fairer prices for gold, accessing support services, and ultimately, improving their quality of life. In the case of sub-Saharan Africa, however, the gold being mined on an artisanal scale does not supply Western retailers as perhaps believed; it is rather an important source of foreign exchange, which host governments employ buyers to collect for their coffers. It is maintained here that if the underlying purpose of fair trade is to improve the livelihoods and well-being of subsistence producers in developing countries, then the models that have proved so successful in alleviating the hardships of agro-producers of 'tropical' commodities such as coffee, tea, bananas and cocoa, should be adapted to artisanal gold mining in sub-Saharan Africa. Campaigns promoting 'fair trade gold' in the region should view host governments, and not Western retailers, as the 'end consumer', and focus on improving governance at the grassroots, organizing informal operators into working cooperatives, and addressing complications with purchasing arrangements - all of which would go a long way toward improving the livelihoods of subsistence artisanal miners. A case study of Noyem, Ghana, the location of a sprawling illegal gold mining community, is presented, which magnifies these challenges further and provides perspective on how they can be overcome. (c) 2007 Elsevier Ltd. All rights reserved.

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Methodology used to measure in vitro gas production is reviewed to determine impacts of sources of variation on resultant gas production profiles (GPP). Current methods include measurement of gas production at constant pressure (e.g., use of gas tight syringes), a system that is inexpensive, but may be less sensitive than others thereby affecting its suitability in some situations. Automated systems that measure gas production at constant volume allow pressure to accumulate in the bottle, which is recorded at different times to produce a GPP, and may result in sufficiently high pressure that solubility of evolved gases in the medium is affected, thereby resulting in a recorded volume of gas that is lower than that predicted from stoichiometric calculations. Several other methods measure gas production at constant pressure and volume with either pressure transducers or sensors, and these may be manual, semi-automated or fully automated in operation. In these systems, gas is released as pressure increases, and vented gas is recorded. Agitating the medium does not consistently produce more gas with automated systems, and little or no effect of agitation was observed with manual systems. The apparatus affects GPP, but mathematical manipulation may enable effects of apparatus to be removed. The amount of substrate affects the volume of gas produced, but not rate of gas production, provided there is sufficient buffering capacity in the medium. Systems that use a very small amount of substrate are prone to experimental error in sample weighing. Effect of sample preparation on GPP has been found to be important, but further research is required to determine the optimum preparation that mimics animal chewing. Inoculum is the single largest source of variation in measuring GPP, as rumen fluid is variable and sampling schedules, diets fed to donor animals and ratios of rumen fluid/medium must be selected such that microbial activity is sufficiently high that it does not affect rate and extent of fermentation. Species of donor animal may also cause differences in GPP. End point measures can be mathematically manipulated to account for species differences, but rates of fermentation are not related. Other sources of inocula that have been used include caecal fluid (primarily for investigating hindgut fermentation in monogastrics), effluent from simulated rumen fermentation (e.g., 'Rusitec', which was as variable as rumen fluid), faeces, and frozen or freeze-dried rumen fluid (which were both less active than fresh rumen fluid). Use of mixtures of cell-free enzymes, or pure cultures of bacteria, may be a way of increasing GPP reproducibility, while reducing reliance on surgically modified animals. However, more research is required to develop these inocula. A number of media have been developed which buffer the incubation and provide relevant micro-nutrients to the microorganisms. To date, little research has been completed on relationships between the composition of the medium and measured GPP. However, comparing GPP from media either rich in N or N-free, allows assessment of contributions of N containing compounds in the sample. (c) 2005 Published by Elsevier B.V.

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Consumers increasingly demand convenience foods of the highest quality in terms of natural flavor and taste, and which are freedom additives and preservatives. This demand has triggered the need for the development of a number of nonthermal approaches to food processing, of which high-pressure technology has proven to be very valuable. A number of recent publications have demonstrated novel and diverse uses of this technology. Its novel features, which include destruction of microorganisms at room temperature or lower, have made the technology commerically attractive. Enzymes forming bacteria can be by the application of pressure-thermal combinations. This review aims to identify the opportunities and challenges associated with this technology. In addition to discussing the effects of high pressure on food components, this review covers the combined effects of high pressure processing with: gamma irradiation, alternating current, ultrasound, and carbon dioxide or anti-microbial treatment. Further, the applications of this technology in various sectors-fruits and vegetables, dairy and meat processing-have been dealt with extensively. The integration of high-pressure with other matured processing operations such as blanching, dehydration, osmotic dehydration, rehyrdration, frying, freezing/thawing and solid-liquid extraction has been shown to open up new processing options. The key challenges identified include: heat transfer problems and resulting non-uniformity in processing, obtaining reliable and reproducible data, for process validation, lack of detailed knowledge about the interaction between high pressure, and a number of food constituents, packaging and statutory issues.

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Food proteins such as milk and soy are a rich source of bioactive peptides. In the last decade, research into this area has intensified and new bioactive peptide sequences have been discovered with a range of apparent biological functions; for example, antihypertensive, antioxidant, and antimicrobial effects and opiate-like qualities have been reported. These peptides could therefore lead to the development of important functional food products and ingredients for the prevention and even treatment of chronic diseases such as cardiovascular disease and cancer. Peptides can be produced by fermentation with dairy starters for instance, and by enzymatic hydrolysis with pancreatic and microbial enzymes. Further purification is typically carried out by membrane filtration and/or chromatographic methods. The production of novel bioactive peptides and their incorporation into functional food products poses several technological challenges as well as regulatory and marketing issues. Proof of efficacy is of paramount importance; this should be verified by conducting appropriate tests in vivo in animals and in humans. In addition, tests for cytotoxicity and allergenicity must be conducted. Despite all of these hurdles, scientific evidence is increasingly demonstrating the health benefits of diet-based disease prevention, and therefore new developments in this area are likely to continue both at the research and the commercialisation level.