This book developed from a series of conferences to facilitate the application of mathematical modeling to experimental nutrition. As nutrition science moves from prevention of gross deficiencies to identifying requirements for optimum long term health, more sophisticated methods of nutritional assessment will be needed. Collection and evaluation of kinetic data may be one such method.This books opens with chapters giving specific examples of the application of modeling techniques to vitamin A, carotenoids, folate, vitamin b-6, glycogen phosphorylase, transthyretin, amino acids, and energy metabolism. Obtaining kinetic data on internal processes is a major challenge; therefore, the text includes chapters on the use of microdialysis and ultrafiltration, use of membrane vesicles, and culture of mammary tissue.Many of the authors use the Simulation, Analysis and Modeling program which allows compartmental models to be described without specifying the required differential equations. The final sections of the book, however, present some more mathematical descriptions of physiological processes, including bioperiodicity, metabolic control, and membrane transport; discussions of some computational aspects of modeling such as parameter distributions, linear integrators and identifiability; and alternative mathematical approaches such as neural networks and graph theory. - Specific, detailed examples of applications of modeling to vitamins, proteins, amino acids, and energy metabolism - Novel methods for collecting kinetic data--microdialysis, ultrafiltration, membrane vesicles, and the culture of mammary tissue - Mathematical treatment of complex metabolic processes including bioperiodicity, metabolic control, and membrane transport - Computational approaches to distribution of kinetic parameters, evaluation of linear integrators, and identifiability - Alternative mathematical approaches--neural networks and graph theory - Detailed descriptions of the application of modeling to a variety of nutrients

Nutrients have been recognized as essential for maximum growth, successful reproduction, and infection prevention since the 1940s; since that time, the lion's share of nutrient research has focused on defining their role in these processes. Around 1990, however, a major shift began in the way that researchers viewed some nutrients particularly the vitamins. This shift was motivated by the discovery that modest declines in vitamin nutritional status are associated with an increased risk of ill-health and disease (such as neural tube defects, heart disease, and cancer), especially in those populations or individuals who are genetically predisposed. In an effort to expand upon this new understanding of nutrient action, nutritionists are increasingly turning their focus to the mathematical modeling of nutrient kinetic data. The availability of suitably-tagged (isotope) nutrients (such as B-carotene, vitamin A, folate, among others), sensitive analytical methods to trace them in humans (mass spectrometry and accelerator mass spectrometry), and powerful software (capable of solving and manipulating differential equations efficiently and accurately), has allowed researchers to construct mathematical models aimed at characterizing the dynamic and kinetic behavior of key nutrients in vivo in humans at an unparalleled level of detail.

This is a cumulative index of Volumes 1-45 of the Advances in Food and Nutrition Research series, established in 1948. This ecclectic serial recognizes the integral relationship between the food and nutritional sciences and brings together outstanding and comprehensive reviews that highlight this relationship. Contributions detail the scientific developments in the broad areas encompassed by the fields of food science and nutrition and are intended to ensure that food scientists in academia and industry, as well as professional nutritionists and dieticians, are kept informed concerning emerging research and developments in these important disciplines. Series established in 1948 Advisory Board consists of 8 respected scientists Unique as it combines food science and nutrition research together

This book and CD-ROM package integrates the use of STELLA software into the teaching of health, nutrition and physiology, and may be used on its own in nutrition and physiology courses, or can serve as a supplement to introduce the role that simulation modelling can play. The author presents key subjects ranging from the theory of metabolic control, through weight regulation to bone metabolism, and gives readers the tools to simulate these using the STELLA software. Topics include methods for simulation of gene expression, a multi-stage model of tumour development, theories of ageing, circadian rhythms and physiological time, as well as a model for managing weight loss and preventing obesity.

The present text sets itself in relief to other titles on the subject in that it addresses the means and methodologies versus a narrow specific-task oriented approach. Concepts and their developments which evolved to meet the changing needs of applications are addressed. This approach provides the reader with a general tool-box to apply to their specific needs. Two important tools are presented: dimensional analysis and the similarity analysis methods. The fundamental point of view, enabling one to sort all models, is that of information flux between a model and an original expressed by the similarity and abstraction Each chapter includes original examples and applications. In this respect, the models can be divided into several groups. The following models are dealt with separately by chapter; mathematical and physical models, physical analogues, deterministic, stochastic, and cybernetic computer models. The mathematical models are divided into asymptotic and phenomenological models. The phenomenological models, which can also be called experimental, are usually the result of an experiment on an complex object or process. The variable dimensionless quantities contain information about the real state of boundary conditions, parameter (non-linearity) changes, and other factors. With satisfactory measurement accuracy and experimental strategy, such models are highly credible and can be used, for example in control systems.