Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis
Braz. j. med. biol. res
;
47(1): 70-79, 01/2014. tab, graf
Article
in English
| LILACS
| ID: lil-697675
ABSTRACT
Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Energy Intake
/
Dietary Fats
/
Energy Metabolism
/
Diet, High-Fat
Type of study:
Diagnostic study
/
Prognostic study
/
Screening study
Limits:
Animals
Language:
English
Journal:
Braz. j. med. biol. res
Journal subject:
Biology
/
Medicine
Year:
2014
Type:
Article
/
Project document
Affiliation country:
Brazil
Institution/Affiliation country:
Universidade Estadual de Campinas/BR
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