scholarly journals Effects of Different Light Intensities during the Daytime on Circadian Rhythm of Core Temperature in Humans.

1998 ◽  
Vol 17 (6) ◽  
pp. 253-257 ◽  
Author(s):  
Shin-Jung Park ◽  
Hiromi Tokura
2021 ◽  
Vol 97 ◽  
pp. 102807
Author(s):  
Leonardo M.T. de Rezende ◽  
Leandro C. Brito ◽  
Anselmo G. Moura ◽  
Alexandre J.L.D. Costa ◽  
Tiago F. Leal ◽  
...  

2000 ◽  
Vol 279 (4) ◽  
pp. R1316-R1320 ◽  
Author(s):  
Mary D. Coyne ◽  
Christina M. Kesick ◽  
Tammy J. Doherty ◽  
Margaret A. Kolka ◽  
Lou A. Stephenson

The purpose of this study was to determine whether core temperature (Tc) telemetry could be used in ambulatory women to track changes in the circadian Tc rhythm during different phases of the menstrual cycle and, more specifically, to detect impending ovulation. Tcwas measured in four women who ingested a series of disposable temperature sensors. Data were collected each minute for 2–7 days and analyzed in 36-h segments by automated cosinor analysis to determine the mesor (mean temperature), amplitude, period, acrophase (time of peak temperature), and predicted circadian minimum core temperature (Tc-min) for each cycle. The Tcmesor was higher ( P ≤ 0.001) in the luteal (L) phase (37.39 ±0.13°C) and lower in the preovulatory (P) phase (36.91 ±0.11°C) compared with the follicular (F) phase (37.08 ±0.13°C). The predicted Tc-min was also greater in L (37.06 ± 0.14°C) than in menses (M; 36.69 ± 0.13°C), F (36.6 ± 0.16°C), and P (36.38 ± 0.08°C) ( P ≤ 0.0001). During P, the predicted Tc-min was significantly decreased compared with M and F ( P ≤ 0.0001). The amplitude of the Tc rhythm was significantly reduced in L compared with all other phases ( P ≤ 0.005). Neither the period nor acrophase was affected by menstrual cycle phase in ambulatory subjects. The use of an ingestible temperature sensor in conjunction with fast and accurate cosinor analysis provides a noninvasive method to mark menstrual phases, including the critical preovulatory period.


2005 ◽  
Vol 22 (2) ◽  
pp. 207-225 ◽  
Author(s):  
Jim Waterhouse ◽  
Barry Drust ◽  
Dietmar Weinert ◽  
Benjamin Edwards ◽  
Warren Gregson ◽  
...  

2015 ◽  
pp. 55-59
Author(s):  
P De Remigis ◽  
P Cugini ◽  
F Halberg ◽  
S Sensi ◽  
D Scavo

1981 ◽  
Vol 36 (1) ◽  
pp. 28-30 ◽  
Author(s):  
J. Halberg ◽  
E. Halberg ◽  
P. Regal ◽  
F. Halberg

2000 ◽  
Vol 279 (3) ◽  
pp. E669-E683 ◽  
Author(s):  
Emery N. Brown ◽  
Yong Choe ◽  
Harry Luithardt ◽  
Charles A. Czeisler

We formulate a statistical model of the human core-temperature circadian rhythm in which the circadian signal is modeled as a van der Pol oscillator, the thermoregulatory response is represented as a first-order autoregressive process, and the evoked effect of activity is modeled with a function specific for each circadian protocol. The new model directly links differential equation-based simulation models and harmonic regression analysis methods and permits statistical analysis of both static and dynamical properties of the circadian pacemaker from experimental data. We estimate the model parameters by using numerically efficient maximum likelihood algorithms and analyze human core-temperature data from forced desynchrony, free-run, and constant-routine protocols. By representing explicitly the dynamical effects of ambient light input to the human circadian pacemaker, the new model can estimate with high precision the correct intrinsic period of this oscillator (∼24 h) from both free-run and forced desynchrony studies. Although the van der Pol model approximates well the dynamical features of the circadian pacemaker, the optimal dynamical model of the human biological clock may have a harmonic structure different from that of the van der Pol oscillator.


2002 ◽  
Vol 12 (3) ◽  
pp. 170-173 ◽  
Author(s):  
Sabina Cevoli ◽  
Giulia Pierangeli ◽  
Fabiola Magnifico ◽  
Giuseppe Bonavina ◽  
Giorgio Barletta ◽  
...  

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