Skip to main content

Advertisement

Log in

Systemic investigation of a brain-centered model of the human energy metabolism

  • Original Paper
  • Published:
Theory in Biosciences Aims and scope Submit manuscript

Abstract

The regulation of the human energy metabolism is crucial to ensure the functionality of the entire organism. Deregulations may lead to severe pathologies such as diabetes mellitus and obesity. The decisive role of the brain as active controller and heavy consumer in the complex whole-body energy metabolism is the object of recent research. Latest studies suggest the priority of the brain energy supply in the competition between brain and body periphery for the available energy resources. In this paper, a systemic investigation of the human energy metabolism is presented which consists of a compartment model including periphery, blood, and brain as well as signaling paths via insulin, appetite, and ingestion. The presented dynamical system particularly contains the competition for energy between brain and body periphery. Characteristically, the hormone insulin is regarded as central feedback signal of the brain. The model realistically reproduces the qualitative behavior of the energy metabolism. Short-time observations demonstrate the physiological periodic food intake generating the typical oscillating blood glucose variations. Integration over the daily cycle yields a long-term model which shows a stable behavior in accordance with the homeostatic regulation of the energy metabolism on a long-time scale. Two types of abstract constitutive equations describing the interaction between compartments and signals are taken into consideration. These are nonlinear and linear representatives from the class of feasible relations. The robustness of the model against the choice of the representative relation is linked to evolutionary stability of existing organisms.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Ackerman E (1964) A mathematical model of the glucose-tolerance test. Phys Med Biol 9:203–213

    Article  Google Scholar 

  • Barnsley M (1993) Fractals everywhere. Morgan Kaufmann, San Francisco

    Google Scholar 

  • Bergman R, Phillips L, Cobelli C (1981) Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. J Clin Invest 68:1456–1467

    Article  CAS  PubMed  Google Scholar 

  • Bobbert T, Wegewitz U, Brechtel L, Freudenberg M, Mai K, Moehlig M, Diederich S, Ristow M, Rochlitz H, Pfeiffer AFH, Spranger J (2007) Adiponectin oligomers in human serum during acute and chronic exercise: Relation to lipid metabolism and insulin sensitivity. Int J Sports Med 28:1–8

    Article  CAS  PubMed  Google Scholar 

  • Clark D, Sokoloff L (1999) Basic neurochemistry: molecular, cellular and medical aspects. Lippincott Williams & Wilkins, Philadelphia

    Google Scholar 

  • Conrad M, Hubold C, Fischer B, Peters A (2009) Modeling the hypothalamus–pituitary–adrenal system: homeostasis by interacting positive and negative feedback. J Biol Phys 35:149–162

    Article  CAS  PubMed  Google Scholar 

  • Göbel B, Langemann D, Oltmanns K, Chung M (2010) Compact energy metabolism model: brain controlled energy supply. J Theor Biol 264:1214–1224

    Article  PubMed  Google Scholar 

  • Guckenheimer J, Holmes P (2002) Nonlinear oscillations, dynamical systems and bifurcations of vector fields. Springer, New York

    Google Scholar 

  • Hubbard JH, West BH (1995) Differential equations: a dynamical systems approach—higher-dimensional systems. Springer, New York

    Google Scholar 

  • Jost J (2005) Dynamical systems. Examples of complex behaviour. Springer, Berlin

    Google Scholar 

  • Kennedy G (1953) The role of depot fat in the hypothalamic control of food intake in the rat. Proc R Soc Lond B Biol Sci 140:578–592

    Article  CAS  PubMed  Google Scholar 

  • Khalil HK (2002) Nonlinear systems. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Krieger M (1921) Über die Atrophie menschlicher Organe bei Inanition (German: about the atrophy of human organs under inanition). Z Angew Anat Konstitutionsl 7:87–134

    Google Scholar 

  • Langemann D (2007) Selfish-brain theory: mathematical challenges in the top-down analysis of metabolic supply chains. In: Grundy J et al (eds) Proceedings of the tutorials, posters, panels and industrial contributions at the 26th International Conference on Conceptual Modeling—ER 2007 Auckland, New Zealand, CRPIT 83, ACS, pp 39–49

  • Langemann D, Peters A (2008) Deductive functional assignment of elements in appetite regulation. J Biol Phys 34:413–424

    Article  PubMed  Google Scholar 

  • Langemann D, Pellerin L, Peters A (2008) Making sense of AMPA receptor trafficking by modeling molecular mechanisms of synaptic plasticity. Brain Res 1207:60–72

    Article  CAS  PubMed  Google Scholar 

  • Maren S (1999) Long-term potentiation in the amygdala: a mechanism for emotional learning and memory. Trends Neurosci 22:561–567

    Article  CAS  PubMed  Google Scholar 

  • Mayer J (1953) Glucostatic mechanism of regulation of food intake. N Engl J Med 249:13–16

    Article  CAS  PubMed  Google Scholar 

  • Morton G, Cummings D, Baskin D, Barsh GS, Schwartz M (2006) Central nervous system control of food intake and body weight. Nature 443:289–295

    Article  CAS  PubMed  Google Scholar 

  • Perko L (2001) Differential equations and dynamical systems. Springer, New York

    Google Scholar 

  • Peters A, Langemann D (2009) Build-ups in the supply of the brain: on neuroenergetic cause of obesity and type 2 diabetes. Front Neuroenergetics 1(2):1–15

    Google Scholar 

  • Peters A, Schweiger U, Pellerin L, Hubold C, Oltmanns K, Conrad M, Schultes B, Born J, Fehm H (2004) The selfish brain: competition for energy resources. Neurosci Biobehav Rev 28:143–180

    Article  CAS  PubMed  Google Scholar 

  • Peters A, Pellerin L, Dallmann M, Oltmanns K, Schweiger U, Born J, Fehm H (2007) Causes of obesity—looking beyond the hypothalamus. Prog Neurobiol 81:134–143

    Article  Google Scholar 

  • Reilly T, Secher N, Snell P, Williams C (eds) (1990) Physiology of sports. E and FN Spon, London

  • Stanley S, Wynne K, McGowan B, Bloom S (2005) Hormonal regulation of food intake. Physiol Rev 85:1131–1158

    Article  CAS  PubMed  Google Scholar 

  • Vatov L, Kizner Z, Ruppin E, Meilin S, Manor T, Mayevsky A (2006) Modeling brain energy metabolism and function: a multiparametric monitoring approach. Bull Math Biol 68:275–291

    Article  PubMed  Google Scholar 

  • Walter W (1970) Differential and integral inequalities. Springer, Berlin

    Google Scholar 

  • Zhang Y, Proenca R, Maffei N, Barone M, Leopold L, Friedman J (1994) Positional cloning of the mouse obese gene and its human homologue. Nature 372:425–432

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors thank Dr. Matthias Conrad and Prof. Dr. med. Kerstin M. Oltmanns for their invaluable expertise in the development of the investigated models. This work was supported by the Graduate School for Computing in Medicine and Life Sciences funded by the German Research Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Britta Göbel.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Göbel, B., Langemann, D. Systemic investigation of a brain-centered model of the human energy metabolism. Theory Biosci. 130, 5–18 (2011). https://doi.org/10.1007/s12064-010-0105-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12064-010-0105-9

Keywords

Navigation