Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Medical and Biological Research |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2014000100070 |
Resumo: | 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. |
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Brazilian Journal of Medical and Biological Research |
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Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysisTime series temperatureThermal homeostasisHigh-fat dietMetabolic disorder predictorAutoregressive modelsMaintenance 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.Associação Brasileira de Divulgação Científica2014-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2014000100070Brazilian Journal of Medical and Biological Research v.47 n.1 2014reponame:Brazilian Journal of Medical and Biological Researchinstname:Associação Brasileira de Divulgação Científica (ABDC)instacron:ABDC10.1590/1414-431X20133097info:eu-repo/semantics/openAccessLutaif,N.A.Palazzo Jr,R.Gontijo,J.A.R.eng2015-09-04T00:00:00Zoai:scielo:S0100-879X2014000100070Revistahttps://www.bjournal.org/https://old.scielo.br/oai/scielo-oai.phpbjournal@terra.com.br||bjournal@terra.com.br1414-431X0100-879Xopendoar:2015-09-04T00:00Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)false |
dc.title.none.fl_str_mv |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
title |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
spellingShingle |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis Lutaif,N.A. Time series temperature Thermal homeostasis High-fat diet Metabolic disorder predictor Autoregressive models |
title_short |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
title_full |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
title_fullStr |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
title_full_unstemmed |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
title_sort |
Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis |
author |
Lutaif,N.A. |
author_facet |
Lutaif,N.A. Palazzo Jr,R. Gontijo,J.A.R. |
author_role |
author |
author2 |
Palazzo Jr,R. Gontijo,J.A.R. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Lutaif,N.A. Palazzo Jr,R. Gontijo,J.A.R. |
dc.subject.por.fl_str_mv |
Time series temperature Thermal homeostasis High-fat diet Metabolic disorder predictor Autoregressive models |
topic |
Time series temperature Thermal homeostasis High-fat diet Metabolic disorder predictor Autoregressive models |
description |
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. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2014000100070 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2014000100070 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1414-431X20133097 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
dc.source.none.fl_str_mv |
Brazilian Journal of Medical and Biological Research v.47 n.1 2014 reponame:Brazilian Journal of Medical and Biological Research instname:Associação Brasileira de Divulgação Científica (ABDC) instacron:ABDC |
instname_str |
Associação Brasileira de Divulgação Científica (ABDC) |
instacron_str |
ABDC |
institution |
ABDC |
reponame_str |
Brazilian Journal of Medical and Biological Research |
collection |
Brazilian Journal of Medical and Biological Research |
repository.name.fl_str_mv |
Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC) |
repository.mail.fl_str_mv |
bjournal@terra.com.br||bjournal@terra.com.br |
_version_ |
1754302942535483392 |