Modeling the relationship between body weight and energy intake: A molecular diffusion-based approach

Biology Direct

Zhejun Gong²  Zhefeng Gong¹ 

[1] School of Medicine, Zhejiang University, Hangzhou, Zhejiang, 310058, China

[2] College of Logistics Engineering, Wuhan University of Technology, Wuhan, Hubei Province, 430063, China

关键词: Choice making;    Model;    Body weight;    Molecular diffusion;   

Others  :  796956
DOI  :  10.1186/1745-6150-7-19

 received in 2012-03-22, accepted in 2012-06-13,  发布年份 2012

【 摘 要 】

Background

Body weight is at least partly controlled by the choices made by a human in response to external stimuli. Changes in body weight are mainly caused by energy intake. By analyzing the mechanisms involved in food intake, we considered that molecular diffusion plays an important role in body weight changes. We propose a model based on Fick's second law of diffusion to simulate the relationship between energy intake and body weight.

Results

This model was applied to food intake and body weight data recorded in humans; the model showed a good fit to the experimental data. This model was also effective in predicting future body weight.

Conclusions

In conclusion, this model based on molecular diffusion provides a new insight into the body weight mechanisms.

Reviewers

This article was reviewed by Dr. Cabral Balreira (nominated by Dr. Peter Olofsson), Prof. Yang Kuang and Dr. Chao Chen.

【 授权许可】

   
2012 Gong and Gong; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

【 参考文献 】

• [1]Richards MP, Proszkowiec-Weglarz M: Mechanisms regulating feed intake, energy expenditure, and body weight in poultry. Poult Sci 2007, 86:1478-1490.
• [2]Vogels N, Westerterp-Plantenga MS: Categorical strategies based on subject characteristics of dietary restraint and physical activity, for weight maintenance. Int J Obes 2005, 29:849-857.
• [3]Hill JO: Understanding and addressing the epidemic of obesity: an energy balance perspective. Endocr Rev 2006, 27:750-761.
• [4]Rowland NE, Vaughan CH, Mathes CM, Mitra A: Feeding behavior, obesity, and neuroeconomics. Physiol Behav 2008, 93:97-109.
• [5]Guo J, Hall KD: Estimating the continuous-time dynamics of energy and fat metabolism in mice. PLoS Comput Biol 2009, 5:e1000511.
• [6]Guo J, Hall KD: Predicting changes of body weight, body fat, energy expenditure and metabolic fuel selection in C57BL/6 mice. PLoS One 2011, 6:e15961.
• [7]Chow CC, Hall KD: The dynamics of human body weight change. PLoS Comput Biol 2008, 4:e1000045.
• [8]Guo J, Jou W, Gavrilova O, Hall KD: Persistent diet-induced obesity in male C57BL/6 mice resulting from temporary obesigenic diets. PLoS One 2009, 4:e5370.
• [9]Takahashi T: Toward molecular neuroeconomics of obesity. Med Hypotheses 2010, 75:393-396.
• [10]Gortari PD, Joseph-Bravo P: Neuroendocrine regulation of energy homeostasis. Molecular Endocrinology 2006, 65:65-85.
• [11]Grill HJ: Distributed neural control of energy balance: contributions from hindbrain and hypothalamus. Obesity (Silver Spring) 2006, 5(Suppl):216S-221S.
• [12]Shioda S, Takenoya F, Yagi M, Wang L, Hori Y, Kageyama H: Neural networks of several novel neuropeptides involved in feeding regulation. Nutrition 2008, 24:848-853.
• [13]Siegel GJ, Agranoff BW, Albers RW, Fisher SK, Uhler MD: Basic Neurochemistry: Molecular, Cellular and Medical Aspects. 6th edition. Philadelphia: Lippincott-Raven; 1999.
• [14]Ludwig M, Leng G: Dendritic peptide release and peptide-dependent behaviours. Nat Rev Neurosci 2006, 7:126-136.
• [15]Nässel DR: Neuropeptide signaling near and far: how localized and timed is the action of neuropeptides in brain circuits? Invert Neurosci 2009, 9:57-75.
• [16]Smith WF: Foundations of Materials Science and Engineering,3rd edition. New York: McGraw-Hill; 2004.
• [17]Kyle UG, Genton L, Hans D, Karsegard L, Slosman DO, Pichard C: Age-related differences in fat-free mass, skeletal muscle, body cell mass and fat mass between 18 and 94 years. European Journal Clinical Nutrition 2001, 55:663-672.
• [18]Gong Z, Gong Z: A molecular diffusion based utility model for Drosophila larval phototaxis. Theoretical Biology and Medical Modelling 2012, 9:3. BioMed Central Full Text
• [19]Hargrove JL, Heinz G, Heinz O: Modeling transitions in body composition: the approach to steady state for anthropometric measures and physiological functions in the Minnesota human starvation study. Dynamic Medicine 2008, 7:16. BioMed Central Full Text
• [20]Ball EJ, O’Connor J, Abbott R, Steinbeck KS, Davies PSW, Wishart C, Gaskin KJ, Baur LA: Total energy expenditure, body fatness, and physical activity in children aged 6–9 y. Am J Clin Nutr 2001, 74:524-8.
• [21]McARDLE WD, et al.: Essentials of Exercise Physiology. 2nd edition. USA: Lippincott Williams and Wilkins; 2000.
• [22]Vrugt JA, Gupta HV, Bouten W, Sorooshian S: A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrological model parameters. Water Resour Res 2003, 39:1201-1216.