Phase Analysis of Ultradian Rhythms of Body Temperature in Laboratory Mice Maintained under Constant Illumination at Different Longitudinal Locations

Author(s):  
M. E. Diatroptov ◽  
S. M. Slesarev ◽  
T. A. Zenchenko
SLEEP ◽  
2021 ◽  
Author(s):  
Yi-Ge Huang ◽  
Sarah J Flaherty ◽  
Carina A Pothecary ◽  
Russell G Foster ◽  
Stuart N Peirson ◽  
...  

Abstract Study objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG) and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of NREM sleep, REM sleep and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally-hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.


2020 ◽  
Author(s):  
Azure D. Grant ◽  
Mark Newman ◽  
Lance J. Kriegsfeld

AbstractThe human menstrual cycle is characterized by predictable patterns of physiological change across timescales, yet non-invasive anticipation of key events is not yet possible at individual resolution. Although patterns of reproductive hormones across the menstrual cycle have been well characterized, monitoring these measures repeatedly to anticipate the preovulatory luteinizing hormone (LH) surge is not practical for fertility awareness. In the present study, we explored whether non-invasive and high frequency measures of distal body temperature (DBT), sleeping heart rate (HR), sleeping heart rate variability (HRV), and sleep timing could be used to anticipate the preovulatory LH surge in women. To test this possibility, we used signal processing to examine these measures across the menstrual cycle. Cycles were examined from both pre- (n=45 cycles) and perimenopausal (n=10 cycles) women using days of supra-surge threshold LH and dates of menstruation for all cycles. For a subset of cycles, urinary estradiol and progesterone metabolites were measured daily around the time of the LH surge. Wavelet analysis revealed a consistent inflection point of ultradian rhythm (2-5 h) power of DBT and HRV that enabled anticipation of the LH surge at least 2 days prior to its onset in 100% of individuals. In contrast, the power of ultradian rhythms in heart rate, circadian rhythms in body temperature, and metrics of sleep duration and sleep timing were not predictive of the LH surge. Together, the present findings reveal fluctuations in distal body temperature and heart rate variability that consistently anticipate the LH surge and may aid in fertility awareness.Key PointsUltradian (2-5 h) rhythm power of distal body temperature and heart rate variability (RMSSD) exhibits a stereotyped inflection point and peak in the days leading up to the LH surge in premenopausal women.Circadian rhythms of distal body temperature and single time-point/day metrics do not permit anticipation of the LH surge.Measurement of continuous metabolic and autonomic outputs, enabling assessment of ultradian rhythms, may be of value to the fertility awareness method.


2019 ◽  
Vol 168 (2) ◽  
pp. 291-294
Author(s):  
M. E. Diatroptov ◽  
M. V. Rutovskaya ◽  
E. V. Kuznetsova ◽  
M. A. Diatroptova ◽  
A. M. Kosyreva ◽  
...  

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