Evaluating the Impact of Biofortification: A Meta-analysis of Community-level Studies on Quality Protein Maize (QPM)

Biofortification, or the genetic improvement of the nutritional quality of food crops, is a promising strategy to combat undernutrition, particularly among the rural poor in developing countries. However, traditional methods of impact assessment do not apply to biofortified crops as little or no yield increases are expected. Significant progress has been made to develop maize varieties with improved protein quality, collectively known as quality protein maize (QPM). Evidence for the impact of QPM at the community level, as demonstrated by randomized, controlled studies, was evaluated using meta-analysis. A new and generalizable effect size was proposed to quantify the impact of QPM on a key outcome, child growth. The results indicated that consumption of QPM instead of conventional maize leads to an 8% (95% CI: 4-12%) increase in the rate of growth in height and a 9% (95% CI: 4-12%) increase in the rate of growth in weight in infants and young children with mild to moderate undernutrition from populations in which maize is a significant part of the diet. These results are the first step in evaluating the potential economic impact of QPM by establishing and quantifying a link between use of the improved crop and nutritional outcomes. QPM can serve as a model for other biofortification efforts, and in particular, the conceptual framework and methodologies for impact assessment are directly applicable to other biofortified crops.Impact assessment, biofortification, meta-analysis, Crop Production/Industries, Food Security and Poverty,

The Five Factor Model of personality and evaluation of drug consumption risk

The problem of evaluating an individual's risk of drug consumption and misuse is highly important. An online survey methodology was employed to collect data including Big Five personality traits (NEO-FFI-R), impulsivity (BIS-11), sensation seeking (ImpSS), and demographic information. The data set contained information on the consumption of 18 central nervous system psychoactive drugs. Correlation analysis demonstrated the existence of groups of drugs with strongly correlated consumption patterns. Three correlation pleiades were identified, named by the central drug in the pleiade: ecstasy, heroin, and benzodiazepines pleiades. An exhaustive search was performed to select the most effective subset of input features and data mining methods to classify users and non-users for each drug and pleiad. A number of classification methods were employed (decision tree, random forest, $k$-nearest neighbors, linear discriminant analysis, Gaussian mixture, probability density function estimation, logistic regression and na{\"i}ve Bayes) and the most effective classifier was selected for each drug. The quality of classification was surprisingly high with sensitivity and specificity (evaluated by leave-one-out cross-validation) being greater than 70\% for almost all classification tasks. The best results with sensitivity and specificity being greater than 75\% were achieved for cannabis, crack, ecstasy, legal highs, LSD, and volatile substance abuse (VSA).Comment: Significantly extended report with 67 pages, 27 tables, 21 figure

Power as a function of reliability

Many studies employ multiple measurement instruments such as human raters, observers, judges, or mechanical gauges to record subject data. It is well known that the consistency of these instruments, commonly called rater reliability, limits the extent to which conclusions should be drawn from the observed data. However, the degree to which rater reliability limits conclusions has traditionally been assessed in only subjective manners. In this paper, a method is developed for objectively quantifying the impact of rate reliability on the statistical analysis of data from a commonly used collection scheme. This method allows the inclusion of a reliability index in statistical power calculations and is an invaluable tool in the planning of experiments

Evaluating the Impact of Biofortification: A Meta-analysis of Community-level Studies on Quality Protein Maize (QPM)

Biofortification, or the genetic improvement of the nutritional quality of food crops, is a promising strategy to combat undernutrition, particularly among the rural poor in developing countries. However, traditional methods of impact assessment do not apply to biofortified crops as little or no yield increases are expected. Significant progress has been made to develop maize varieties with improved protein quality, collectively known as quality protein maize (QPM). Evidence for the impact of QPM at the community level, as demonstrated by randomized, controlled studies, was evaluated using meta-analysis. A new and generalizable effect size was proposed to quantify the impact of QPM on a key outcome, child growth. The results indicated that consumption of QPM instead of conventional maize leads to an 8% (95% CI: 4-12%) increase in the rate of growth in height and a 9% (95% CI: 4-12%) increase in the rate of growth in weight in infants and young children with mild to moderate undernutrition from populations in which maize is a significant part of the diet. These results are the first step in evaluating the potential economic impact of QPM by establishing and quantifying a link between use of the improved crop and nutritional outcomes. QPM can serve as a model for other biofortification efforts, and in particular, the conceptual framework and methodologies for impact assessment are directly applicable to other biofortified crops

Principal Component Analysis on a LES of a Squared Ribbed Channel

info:eu-repo/semantics/publishe

Association of adenovirus 36 infection with adiposity and inflammatory-related markers in children

CONTEXT: Although animal studies suggest that adenovirus 36 (Ad36) infection is linked to obesity and systemic inflammation, human data are scant and equivocal. OBJECTIVE: Associations of Ad36 infection with total body adiposity and inflammatory-related markers were determined in 291 children aged 9-13 years (50% female, 49% black). DESIGN: Fasting blood samples were measured for presence of Ad36-specific antibodies and TNF-α, IL-6, vascular endothelial growth factor (VEGF), and monocyte chemoattractant protein-1 (MCP-1). Fat mass and fat-free soft tissue mass were measured by dual-energy X-ray absorptiometry. RESULTS: The overall prevalence of Ad36 seropositivity [Ad36(+)] was 42%. There was a higher percentage of Ad36(+) children in the highest tertiles of TNF-α and IL-6 compared with their respective middle and lowest tertiles (both P .05). CONCLUSIONS: In children, our data suggest that Ad36(+) may be associated with biomarkers implicated in inflammation but not with greater levels of fat mass