Linked Life Data

15011272

Source:http://linkedlifedata.com/resource/pubmed/id/15011272

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2004-3-10
pubmed:abstractText
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.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0219-6352
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
219-47
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Short-term autonomic control of cardiovascular function: a mini-review with the help of mathematical models.
pubmed:affiliation
Department of Electronics, Computer Science and Systems, University of Bologna, Cesena, Italy. mursino@deis.unibo.it
pubmed:publicationType
Journal Article, Review