Literature DB >> 15011272

Short-term autonomic control of cardiovascular function: a mini-review with the help of mathematical models.

Mauro Ursino1, Elisa Magosso.   

Abstract

In this work the main aspects of the short-term regulation of the cardiovascular system are reviewed and critically discussed, laying special emphasis on the role of the autonomic neural mechanisms involved, on their mutual interrelationships and complex integration. All these aspects are summarized with the help of mathematical models developed by the authors in past years. The main characteristics of the uncontrolled system (i.e., the heart and vessels) and of the efferent neural branches (sympathetic and vagal) working on it are first described. Then, the afferent pathways which participate in feedback mechanisms (baroreceptors, chemoreceptors, lung-stretch receptors, direct CNS response), and the feedforward mechanisms anticipating cardiovascular requirements are introduced, and their role discussed with reference to various cardiovascular perturbations (hemorrhage or posture changes, hypoxia, asphyxia, dynamic exercise). Analysis of physiological data via mathematical equations, and results of computer simulations, emphasize the great complexity, richness and variability of the autonomic cardiovascular control, including redundant mechanisms and antagonistic requirements. The use of mathematical models is essential to capture this richness, and to summarize apparent contradictory data into a coherent and comprehensive theoretical setting.

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Year:  2003        PMID: 15011272     DOI: 10.1142/s0219635203000275

Source DB:  PubMed          Journal:  J Integr Neurosci        ISSN: 0219-6352            Impact factor:   2.117


  5 in total

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Authors:  Limei Cheng; Olga Ivanova; Hsing-Hua Fan; Michael C K Khoo
Journal:  Respir Physiol Neurobiol       Date:  2010-06-11       Impact factor: 1.931

Review 2.  The relationship between ambient carbon monoxide and heart rate variability-a systematic world review-2015.

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Journal:  Environ Sci Pollut Res Int       Date:  2016-09-13       Impact factor: 4.223

3.  Current computational models do not reveal the importance of the nervous system in long-term control of arterial pressure.

Authors:  John W Osborn; Viktoria A Averina; Gregory D Fink
Journal:  Exp Physiol       Date:  2009-04       Impact factor: 2.969

Review 4.  Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure.

Authors:  Limei Cheng; Yuchi Qiu; Brian J Schmidt; Guo-Wei Wei
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-10-12       Impact factor: 2.745

5.  Relationship between stroke volume and pulse pressure during blood volume perturbation: a mathematical analysis.

Authors:  Ramin Bighamian; Jin-Oh Hahn
Journal:  Biomed Res Int       Date:  2014-05-20       Impact factor: 3.411

  5 in total

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