Exponent

About: Exponent is a company organization based out in Menlo Park, California, United States. It is known for research contribution in the topics: Population & Risk assessment. The organization has 1589 authors who have published 2680 publications receiving 88140 citations.

Fortification: new findings and implications

Abstract: This article reviews the current landscape regarding food fortification in the United States; the content is based on a workshop sponsored by the North American Branch of the International Life Sciences Institute. Fortification of the food supply with vitamins and minerals is a public health strategy to enhance nutrient intakes of the population without increasing caloric intake. Many individuals in the United States would not achieve recommended micronutrient intakes without fortification of the food supply. The achievement and maintenance of a desirable level of nutritional quality in the nation's food supply is, thus, an important public health objective. While the addition of nutrients to foods can help maintain and improve the overall nutritional quality of diets, indiscriminate fortification of foods could result in overfortification or underfortification in the food supply and nutrient imbalances in the diets of individuals. Any changes in food fortification policy for micronutrients must be considered within the context of the impact they will have on all segments of the population and of food technology and safety applications and their limitations. This article discusses and evaluates the value of fortification, the success of current fortification efforts, and the future role of fortification in preventing or reversing nutrient inadequacies.

Simulating pH effects in an algal‐growth hydrodynamics model1

Abstract: Models and numerical simulations are relatively inexpensive tools that can be used to enhance economic competitiveness through operation and system optimization to minimize energy and resource consumption, while maximizing algal oil yield. This work uses modified versions of the U.S. Environmental Protection Agency's Environmental Fluid Dynamics Code (EFDC) in conjunction with the U.S. Army Corp of Engineers' water-quality code (CE-QUAL) to simulate flow hydrodynamics coupled to algal growth kinetics. The model allows the flexibility of manipulating a host of variables associated with algal growth such as temperature, light intensity, and nutrient availability. pH of the medium is a newly added operational parameter governing algal growth that affects algal photosynthesis, differential availability of inorganic forms of carbon, enzyme activity in algae cell walls, and oil production rates. A single-layer algal-growth/hydrodynamic model without pH limitation was verified by comparing solution curves of algal biomass and phosphorus concentrations to an analytical solution. Media pH, now included in the model as a growth-limiting factor, can be entered as a measured value or calculated based on CO2 concentrations. Upon adding the ability to limit growth due to pH, physically reasonable results have been obtained from the model both with and without pH limitation. When the model was used to simulate algal growth from a pond experiment in the greenhouse, a least-squares fitting technique yielded a maximum algal production (subsequently modulated by limitation factors) of 1.05 d(-1) . Overall, the measured and simulated biomass concentrations in the greenhouse pond were in close agreement.

Resting energy expenditure and adiposity accretion among children with Down syndrome: a 3-year prospective study.

Abstract: Down syndrome (DS), or trisomy 21, is associated with intellectual disability, and many medical conditions1–3. Up to 30% of children with DS are obese (BMI-for-age ≥95th percentile)4, 5, representing a higher prevalence than children without DS (17%)6 and children with other intellectual disabilities (12 – 30%)4, 7. One recent population based study in the Netherlands found that children with DS were twice as likely to be obese as children who did not have DS (4.2% vs 1.8% for boys; 5.1% vs 2.2% for girls)8. Anecdotal studies provide estimates of obesity among children with DS ranging from 18.8 to 31%9, 10. As life expectancy has increased for individuals with DS over the past decades, the health complications associated with excess adiposity such as type 2 diabetes and cardiovascular disease are becoming more significant concerns11, 12. Furthermore, individuals with disabilities, in general, suffer from significant disparities in obesity burden and medical management, and there is less research conducted with this population13. Therefore, it is important to understand the factors that lead to obesity among people with DS. Lower resting energy expenditure (REE) relative to body size and composition is one mechanism that may predispose individuals to excessive weight gain. Small differences in REE could potentially accumulate over time and contribute to significant excessive weight gain, but previous studies of REE and weight gain for children have yielded mixed results9, 14–22. Previous studies suggesting lower REE in children with DS23–25 had some limitations, such as small sample size, lack of a control group, not controlling for other family factors related to obesity, possible recruitment bias of control families without DS (control families with no children with DS may participate for different reasons than families of a child with DS), and technical difficulties in REE measurements (excess movement during measurement procedure). Furthermore, with the exception of one study with a one year follow-up24, these studies were cross-sectional and did not investigate whether lower REE was predictive of weight and adiposity gain over time. The primary aim of this study was to examine whether children with DS showed differences in baseline REE that contributed to changes in fat mass (FM) over a three-year follow up. We hypothesized that: 1) REE, adjusted for FFM, would be lower in children with DS than in sibling controls, 2) changes in FM over the three year period would be associated with baseline REE, adjusted for baseline FFM, baseline FM, sex, and age. A secondary aim was to explore potential mechanisms that could explain why children with DS have a lower REE such as higher FM and lower thyroid function that are typical of children with DS compared with children without DS1, 2, 4, 7, 26. While FFM is the primary contributor to REE, FM does explain some additional variance in REE, especially in obese subjects27–29.