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Mathematical Modelling of Endocrine Systems

Hormone rhythms are ubiquitous and essential to sustain normal physiological functions. Combined mathematical modelling and experimental approaches have shown that these rhythms result from regulatory processes occurring at multiple levels of organisation and require continuous dynamic equilibration...

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Detalles Bibliográficos
Autores principales: Zavala, Eder, Wedgwood, Kyle C.A., Voliotis, Margaritis, Tabak, Joël, Spiga, Francesca, Lightman, Stafford L., Tsaneva-Atanasova, Krasimira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Pub. Co 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425086/
https://www.ncbi.nlm.nih.gov/pubmed/30799185
http://dx.doi.org/10.1016/j.tem.2019.01.008
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author Zavala, Eder
Wedgwood, Kyle C.A.
Voliotis, Margaritis
Tabak, Joël
Spiga, Francesca
Lightman, Stafford L.
Tsaneva-Atanasova, Krasimira
author_facet Zavala, Eder
Wedgwood, Kyle C.A.
Voliotis, Margaritis
Tabak, Joël
Spiga, Francesca
Lightman, Stafford L.
Tsaneva-Atanasova, Krasimira
author_sort Zavala, Eder
collection PubMed
description Hormone rhythms are ubiquitous and essential to sustain normal physiological functions. Combined mathematical modelling and experimental approaches have shown that these rhythms result from regulatory processes occurring at multiple levels of organisation and require continuous dynamic equilibration, particularly in response to stimuli. We review how such an interdisciplinary approach has been successfully applied to unravel complex regulatory mechanisms in the metabolic, stress, and reproductive axes. We discuss how this strategy is likely to be instrumental for making progress in emerging areas such as chronobiology and network physiology. Ultimately, we envisage that the insight provided by mathematical models could lead to novel experimental tools able to continuously adapt parameters to gradual physiological changes and the design of clinical interventions to restore normal endocrine function.
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spelling pubmed-64250862019-04-01 Mathematical Modelling of Endocrine Systems Zavala, Eder Wedgwood, Kyle C.A. Voliotis, Margaritis Tabak, Joël Spiga, Francesca Lightman, Stafford L. Tsaneva-Atanasova, Krasimira Trends Endocrinol Metab Article Hormone rhythms are ubiquitous and essential to sustain normal physiological functions. Combined mathematical modelling and experimental approaches have shown that these rhythms result from regulatory processes occurring at multiple levels of organisation and require continuous dynamic equilibration, particularly in response to stimuli. We review how such an interdisciplinary approach has been successfully applied to unravel complex regulatory mechanisms in the metabolic, stress, and reproductive axes. We discuss how this strategy is likely to be instrumental for making progress in emerging areas such as chronobiology and network physiology. Ultimately, we envisage that the insight provided by mathematical models could lead to novel experimental tools able to continuously adapt parameters to gradual physiological changes and the design of clinical interventions to restore normal endocrine function. Elsevier Science Pub. Co 2019-04 /pmc/articles/PMC6425086/ /pubmed/30799185 http://dx.doi.org/10.1016/j.tem.2019.01.008 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zavala, Eder
Wedgwood, Kyle C.A.
Voliotis, Margaritis
Tabak, Joël
Spiga, Francesca
Lightman, Stafford L.
Tsaneva-Atanasova, Krasimira
Mathematical Modelling of Endocrine Systems
title Mathematical Modelling of Endocrine Systems
title_full Mathematical Modelling of Endocrine Systems
title_fullStr Mathematical Modelling of Endocrine Systems
title_full_unstemmed Mathematical Modelling of Endocrine Systems
title_short Mathematical Modelling of Endocrine Systems
title_sort mathematical modelling of endocrine systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425086/
https://www.ncbi.nlm.nih.gov/pubmed/30799185
http://dx.doi.org/10.1016/j.tem.2019.01.008
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