Grant Abstract: Mathematical Modeling In Nutrition
Grant Number: 1R13DK064822-01
PI Name: James Hargrove
Project Title: Mathematical Modeling In Nutrition
Abstract: DESCRIPTION (provided by applicant): A healthful diet and balanced energy intake are important for normal growth, development, and prevention of chronic diseases. In addition to the essential nutrients, many phytochemicals and non-essential food components prevent disease or modify its course. Federal advisory panels are called upon to define adequate levels of intake of vitamins, minerals, and other dietary constituents such as choline. Mathematical modeling can assist in defining minimal needs for nutrients and also can generate predictive models for control points in diseases such as diabetes mellitus. A conference is proposed that will update and/or train participants in the use of mathematical modeling and new computational methods in experimental nutrition as related to chronic disease. The program will include presentations and tutorials in the areas of nutrient and phytochemical metabolism, diabetes, obesity and cancer. The specific aims of the proposed conference are: 1) To disseminate information about the use of mathematical modeling and new computer software to scientists in nutrition and related health sciences; 2) To train young scientists in applications of modeling in the study of diabetes, cancer, and chemoprevention of disease; 3) To explore the use of kinetic modeling in defining Dietary Reference Intakes (DRI's) and healthful intakes of phytochemicals; and 4) To encourage collaborations and development of grant proposals among scientists in disciplines that range from nutrition to molecular and computational biology. Sessions will include traditional aspects of modeling in relation to vitamin, mineral, and tissue metabolism, and guided workshops in which participants are taught to use modeling software. New topics will include the use of modeling for estimating risk for cancer as a result of exposure to environmental agents, and computational methods for testing hypotheses about how changes in gene expression affect phenotype. One session will explore the use of modeling to assess uptake, distribution and effects of phytochemicals consumed in foods. A workshop will focus on writing successful grants and publications that use modeling, with leadership provided by current holders of federal grants. Lastly, a panel will discuss the use of modeling in undergraduate and graduate education, and will make recommendations for appropriate activities of a new Research Interest Section on Mathematical Modeling.
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