Linked Life Data

8559276

Source:http://linkedlifedata.com/resource/pubmed/id/8559276

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1996-2-28
pubmed:abstractText
Prolactin (PRL) circadian profiles were analyzed using methods of nonlinear dynamics, directly from the experimental data, by combining in a single time-series (432 measurements), six individual 24-hour PRL profiles (72 measurements per profile, sampling interval = 20 min), obtained from young healthy human volunteers (4 males, 2 females), under basal conditions. Significant autocorrelation exists between any given point of the time series and a limited number of its successors. Fourier analysis showed a dominant frequency of 1 cycle/24 h, without sub-24-hour harmonics. Poincaré section indicated the presence of a fractal attractor and a sketch of the attractor revealed a highly convoluted geometric structure with a conical contour. The box-counting dimension (D0), information dimension (D1) and correlation dimension (D2) of the attractor had low, fractal values, did not differ significantly from each other, and exhibited saturation at an embedding dimension of 2. The evidence taken together suggests that, under basal conditions, the daily changes in the peripheral blood levels of PRL are governed by nonlinear deterministic dynamics, with a dominant rhythm of 1 cycle/day mixed with a higher-frequency, low-amplitude signal.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0028-3835
pubmed:author
pubmed:issnType
Print
pubmed:volume
62
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
444-53
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
Pattern of prolactin diurnal secretion in normal humans: evidence for nonlinear dynamics.
pubmed:affiliation
Department of Endocrinology, Faculty of Medicine University of Crete, Heraklion, Greece.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't