SCAMP:standardised, concentrated, additional macronutrients, parenteral nutrition in very preterm infants: a phase IV randomised, controlled exploratory study of macronutrient intake, growth and other aspects of neonatal care

<p>Abstract</p> <p>Background</p> <p>Infants born <29 weeks gestation are at high risk of neurocognitive disability. Early postnatal growth failure, particularly head growth, is an important and potentially reversible risk factor for impaired neurodevelopmental outcome. Inadequate nutrition is a major factor in this postnatal growth failure, optimal protein and calorie (macronutrient) intakes are rarely achieved, especially in the first week. Infants <29 weeks are dependent on parenteral nutrition for the bulk of their nutrient needs for the first 2-3 weeks of life to allow gut adaptation to milk digestion. The prescription, formulation and administration of neonatal parenteral nutrition is critical to achieving optimal protein and calorie intake but has received little scientific evaluation. Current neonatal parenteral nutrition regimens often rely on individualised prescription to manage the labile, unpredictable biochemical and metabolic control characteristic of the early neonatal period. Individualised prescription frequently fails to translate into optimal macronutrient delivery. We have previously shown that a standardised, concentrated neonatal parenteral nutrition regimen can optimise macronutrient intake.</p> <p>Methods</p> <p>We propose a single centre, randomised controlled exploratory trial of two standardised, concentrated neonatal parenteral nutrition regimens comparing a standard macronutrient content (maximum protein 2.8 g/kg/day; lipid 2.8 g/kg/day, dextrose 10%) with a higher macronutrient content (maximum protein 3.8 g/kg/day; lipid 3.8 g/kg/day, dextrose 12%) over the first 28 days of life. 150 infants 24-28 completed weeks gestation and birthweight <1200 g will be recruited. The primary outcome will be head growth velocity in the first 28 days of life. Secondary outcomes will include a) auxological data between birth and 36 weeks corrected gestational age b) actual macronutrient intake in first 28 days c) biomarkers of biochemical and metabolic tolerance d) infection biomarkers and other intravascular line complications e) incidence of major complications of prematurity including mortality f) neurodevelopmental outcome at 2 years corrected gestational age</p> <p>Trial registration</p> <p>Current controlled trials: <a href="http://www.controlled-trials.com/ISRCTN76597892">ISRCTN76597892</a>; EudraCT Number: 2008-008899-14</p

Comparing Models for Early Warning Systems of Neglected Tropical Diseases

Early Warning Systems (EWS) are management tools to predict the occurrence of epidemics. They are based on the dependence of a given infectious disease on environmental variables. Although several neglected tropical diseases are sensitive to the effect of climate, our ability to predict their dynamics has been barely studied. In this paper, we use several models to determine if the relationship between cases and climatic variability is robust—that is, not simply an artifact of model choice. We propose that EWS should be based on results from several models that are to be compared in terms of their ability to predict future number of cases. We use a specific metric for this comparison known as the predictive R2, which measures the accuracy of the predictions. For example, an R2 of 1 indicates perfect accuracy for predictions that perfectly match observed cases. For cutaneous leishmaniasis, R2 values range from 72% to77%, well above predictions using mean seasonal values (64%). We emphasize that predictability should be evaluated with observations that have not been used to fit the model. Finally, we argue that EWS should incorporate climatic variables that are known to have a consistent relationship with the number of observed cases

A New (Old), Invasive Ant in the Hardwood Forests of Eastern North America and Its Potentially Widespread Impacts

Biological invasions represent a serious threat for the conservation of biodiversity in many ecosystems. While many social insect species and in particular ant species have been introduced outside their native ranges, few species have been successful at invading temperate forests. In this study, we document for the first time the relationship between the abundance of the introduced ant, Pachycondyla chinensis, in mature forests of North Carolina and the composition, abundance and diversity of native ant species using both a matched pair approach and generalized linear models. Where present, P. chinensis was more abundant than all native species combined. The diversity and abundance of native ants in general and many individual species were negatively associated with the presence and abundance of P. chinensis. These patterns held regardless of our statistical approach and across spatial scales. Interestingly, while the majority of ant species was strongly and negatively correlated with the abundance and presence of P. chinensis, a small subset of ant species larger than P. chinensis was either as abundant or even more abundant in invaded than in uninvaded sites. The large geographic range of this ant species combined with its apparent impact on native species make it likely to have cascading consequences on eastern forests in years to come, effects mediated by the specifics of its life history which is very different from those of other invasive ants. The apparent ecological impacts of P. chinensis are in addition to public health concerns associated with this species due to its sometimes, deadly sting

Diversity analysis of cotton (Gossypium hirsutum L.) germplasm using the CottonSNP63K Array

Cotton germplasm resources contain beneficial alleles that can be exploited to develop germplasm adapted to emerging environmental and climate conditions. Accessions and lines have traditionally been characterized based on phenotypes, but phenotypic profiles are limited by the cost, time, and space required to make visual observations and measurements. With advances in molecular genetic methods, genotypic profiles are increasingly able to identify differences among accessions due to the larger number of genetic markers that can be measured. A combination of both methods would greatly enhance our ability to characterize germplasm resources. Recent efforts have culminated in the identification of sufficient SNP markers to establish high-throughput genotyping systems, such as the CottonSNP63K array, which enables a researcher to efficiently analyze large numbers of SNP markers and obtain highly repeatable results. In the current investigation, we have utilized the SNP array for analyzing genetic diversity primarily among cotton cultivars, making comparisons to SSR-based phylogenetic analyses, and identifying loci associated with seed nutritional traits. (Résumé d'auteur