Home About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Login 
    Users Online: 22
Home Print this page Email this page Small font size Default font size Increase font size


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 9  |  Issue : 3  |  Page : 236-242

Models of modern-day circadian rhythm disruption and their diabetogenic potentials in adult male Wistar rats


1 Department of Human Physiology, Faculty of Basic Medical Sciences, College of Health Sciences, Bayero University, Kano, Kano State, Nigeria
2 Department of Human Physiology, Faculty of Basic Medical Sciences, College of Medical Sciences, Ahmadu Bello University, Zaria, Kaduna State, Nigeria

Date of Submission07-Jun-2020
Date of Decision22-Jul-2020
Date of Acceptance23-Aug-2020
Date of Web Publication07-Nov-2020

Correspondence Address:
Mahdi Gambo Dissi
Department of Human Physiology, Faculty of Basic Medical Sciences, College of Health Sciences, Bayero University, Kano, Kano State
Nigeria
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/sjhs.sjhs_69_20

Rights and Permissions
  Abstract 


Background: Light at night (LAN) threatens metabolic health by delaying our sleep timing and allowing us to eat at odds with our circadian clocks. Circadian research interests are majorly focused on jet lags, shift work, and the non-24-h days. Since exposure to LAN, sleep loss, and late night eating are common scenarios of modern-day circadian rhythm disruption, developing an animal model that better mirrors these scenarios and investigation of their diabetogenic potentials is a research priority. Materials and Methods: Over the course of 6 weeks, we developed chronic LAN exposure (LAN), sleep restriction (SR), abnormal feeding (AF), rural social jetlag (RSJ), night shift work (NSW), and urban social jetlag (USJ) models, using male Wistar rats. Gentle handling was used to induce SR, while LAN was instituted using a customized light rack system. Circadian and blood glucose rhythms were, respectively, determined using 4 hourly temperature and blood glucose measurements. Statistical analysis was done using SPSS V20.0 and ÒCosinor SoftwareÓ. The data were summarized using mean ± standard deviation as well as MESoRs, amplitudes, and acrophases. Statistical significance was considered as P ≤ 0.05. Results: Our findings have revealed a significantly (P < 0.01) higher average nocturnal glucose (126 mg/dL) and temperature (36.53°C) rhythms compared to diurnal glucose (108 mg/dL) and temperature (35.50°C) rhythms in the controls rats. All the developed models are noted to have a distorted light: dark glucose and temperature rhythms with acrophases of the core body temperature in controls, RSJ and USJ models occurring at 08:16 pm, 2:43 pm, and 7:48 pm local time, respectively. The vector components of the phase changes revealed 5 h phase delay in the LAN model and 28 min, 1 h, and 4.5 h phase advancements among the USJ, AF, and SR models, respectively. These indicate circadian disruption and blood glucose dysrhythmia among the SR, AF, LAN, RSJ, USJ, and NSW models. Conclusion: Our findings have suggested the circadian disruptive and diabetogenic nature of our widespread modern-day social behaviors.

Keywords: Circadian rhythm, glucose dysrhythmia, night shift work, sleep restriction, social jetlag


How to cite this article:
Dissi MG, Ibrahim SA, Tanko Y, Mohammed A. Models of modern-day circadian rhythm disruption and their diabetogenic potentials in adult male Wistar rats. Saudi J Health Sci 2020;9:236-42

How to cite this URL:
Dissi MG, Ibrahim SA, Tanko Y, Mohammed A. Models of modern-day circadian rhythm disruption and their diabetogenic potentials in adult male Wistar rats. Saudi J Health Sci [serial online] 2020 [cited 2021 Jan 19];9:236-42. Available from: https://www.saudijhealthsci.org/text.asp?2020/9/3/236/300292




  Introduction Top


For the almost 1.8 million years of planetary human existence,[1] the earth has been under conditions of dark nights and bright days, which our circadian system evolved through in order to optimize our physiology, fitness, and survival.[2] The circadian system, derived from a Latin phrase “circa diem” which means “about a day,” is a collection of peripheral clocks controlled by a master clock within the suprachiasmatic nucleus (SCN) of the anterior hypothalamus.[3] Upon synchronization by the environmental light dark (12 L: 12D) cycle, the SCN adjusts peripheral clocks and temporally coordinates sleep:wake and fasting:feeding cycles to align with downstream body tissues and as well with the external environmental light: dark cycle.[3],[4] Without the SCN, peripheral tissue functions would continue to oscillate independently, over the 24 h circadian rhythm, but would, however, gradually become out of phase with one another and also with the external environment, thus exhibiting a state of circadian desynchrony or misalignment.[4]

In the recent world, electric lighting of the environment for work, security, recreational, and other purposes allows us to construct our own L: D cycle, thus challenging the evolutionary adaptation of our circadian system of bright days and dark nights. About 75%[5] or more[6] of the world's population are exposed to artificial light at night (LAN), which, consequently, alters circadian clock[7] and disrupts sleep[6] and feeding behavior.[8]

Research interests in circadian physiology are majorly focused on mimicking jet lags,[3] shift work,[3],[9] and the non-24-h days.[3],[10] While these models have demonstrated the importance of circadian synchrony and metabolic health, they are, however, not the most common scenarios of circadian disruption in modern societies.[4],[6] Since exposure to LAN,[7] meal timing,[11],[12] and sleep loss or deprivation[13] could change the phase relationship of circadian rhythms and cause metabolic diseases including type-2-diabetes,[14] the need to develop an animal model that better mirrors these as scenarios of modern-day human circadian disruption and to investigate their diabetogenic potentials has become a research priority. The aim of the present study is, therefore, to develop models of modern-day circadian rhythm disruption and to investigate their possible diabetogenic potentials.


  Materials and Methods Top


Experimental animals and animal handling

Forty male Wistar rats (8-10 weeks old, weighing 88-112 g) were randomly grouped into 5 (n = 8) and kept in metallic cages (38 cm × 46 cm × 24 cm) with saw-dust as beddings. They were acclimatized for 2 weeks, during which they were maintained under the prevailing natural conditions of temperature and light conditions with free access to feeds and water during the dark (activity) periods only.

Research protocol/experimental design

After the 2 weeks of acclimation, the animals were maintained on their respective groupings. Group 1 (controls) were maintained under the natural 12 L/12D condition and had an unrestricted access to feeds and water during the dark portion of the day only. Groups 2, 3, 4, and 5 were sleep restricted (SR); Groups 3 and 5 were additionally allowed to feed during the SR window; and Groups 4 and 5 were, in addition, exposed to (LAN) for 5 h daily. SR and exposure to LAN were done over the first 5 h of photophase and scotophase (lights on at 18:30; lights off at 23:30), respectively, to simulate 5 h of SR and 5 h of LAN exposure in the early biological night of humans.[6] LAN exposure was instituted using a customized light rack system,[15] while SR was employed by means of gentle handling as previously reported.[13] The intervention period lasted for 6 weeks after which the research exposure was terminated and all groups were returned to the acclimation protocol 24 h before temperature and glucose measurements were undertaken. During this period, 4 hourly rectal temperature and blood glucose levels were measured. Temperature measurements were done at 03:00, 07:00, 11:00, 15:00, 19:00 and 23:00 while blood glucose measurements were done 30 minutes after each temperature point measurement accordingly. To measure the rectal temperature, animals were individually removed from their home cages and hand fixed, while a lubricated thermometer probe was gently inserted into the rectum more toward the ventral surface until a stable temperature read-out was achieved,[16] usually within less than a minute. Using a drop of blood obtained by pricking the rat's tail, blood glucose was determined using a digital glucometer (Accu-Check Active® Roche Diagnostics, GMBH 68298; Germany). Animal handling and measurements during the dark phase (from 18:30 through 06:30) were performed under a dim red light, while ethical clearance for the study protocol was granted by the Animal Research Ethics Committee, Ahmadu Bello University, Zaria, Nigeria.

Models and simulation of modern-day circadian disruption

The first model (SR model) was intended to mimic people who stay devoid of electric lighting, perhaps in the rural areas, but habitually stay late at night (SR). Rats in this model were SR, maintained under the prevailing natural 12 L/12D condition, and had free access to feeds and water during the dark portion of the L/D cycle only. The second model is intended to simulate people who are not exposed to LAN, but eats and sleep late at night (rural social jetlag [RSJ] model). Rats in this model were SR, maintained under the prevailing 12 L/12D condition, and were freely allowed to feeds and water during the dark portion of the day and during the SR window, accordingly. The third model was meant to simulate people who stay engaged under lightened environment long into the night (SR), but do not eat late at night (night shift work model). Rats in this model were maintained on a constructed 17 L/7D cycle. They were SR and were freely allowed to feeds and water, exclusively, during the dark hours of the day. The fourth model was to mimic individuals who stay socially engaged in a lightened environment and concurrently eat at late night (urban social jetlag [usj] model). Rats in this model were SR, maintained on a constructed 17 L/7D cycle, and allowed free access to feeds during the dark portion of the day and, concomitantly, during their SR period. The fifth (abnormal feeding [AF]) and the sixth (LAN exposure) models were deducted to explore the individual circadian disruption tendencies of (AF) times and LAN exposure from model groups.

Assessment of circadian rhythms, circadian phases, and blood glucose rhythms

Circadian rhythm and circadian phases were determined using the rectal temperature assessment method.[17] Significant variation of core body temperature and blood glucose levels by time points (observed in at least 3 time points) as a main factor (using a repeated measures ANOVA) was considered as the presence of a strong circadian rhythm or glucose rhythmicity,[16] while significant levels of timing by group interactions using a mixed model ANOVA were used for assessing circadian desynchrony or glucose arrhythmia within models accordingly. Circadian phases were assessed using the Cosinor analysis and phase relationships were deducted as differences between phase positions in a given model.

Statistical analysis

The data were analyzed using the Statistical Package for the Social Sciences (IBM SPSS version 20.0) and ÒCosinor SoftwareÓ (COSINOR 2.4 release; 2000 SEPTMR, © 1998–2001 Didier CUGY). One-way repeated measures and mixed-model ANOVA as well as Student's t-test were used to validate rhythmicity and circadian variation as well as to investigate difference between models with data being summarized as mean ± standard deviation. Data for the 24 h circadian temperature and blood glucose rhythms were summarized as MESoRs, amplitudes and acrophases. In all cases, P ≤ 0.05 was considered statistically significant.


  Results Top


Circadian rhythm, phase assessment, and relationships

In order to gain insight regarding the impact of our interventions on the circadian rhythm of the experimental models, we compared, using a paired samples t-test, the averages of their rectal (core body) temperature during the light and dark periods, respectively. The result revealed a significantly (P = 0.009) higher average nocturnal temperature among the controls (36.53°C vs. 35.50°C), indicating a preserved nocturnality of the rats. RSJ models were, however, observed to display a significantly (P = 0.008) higher diurnal core body temperature much in keeping with diurnality (35.59°C vs. 34.78°C). SR model has a marginal preservation (P = 0.054) of nocturnality of their core body temperature (36.24°C vs. 35.73°C). The other models are similarly noted to have an insignificant (P > 0.05) distortion of their light: dark temperature rhythms.

Further data appraisal using a one-way ANOVA and Bonferroni's correction for multiple comparisons revealed that LAN and night shift work (NSW) models have significantly raised temperatures at 11:00 pm and 7:00 am. This is indicative that their subjective night might have spanned through 11:00 pm to 7:00 am, thus signifying a delay in the beginning of their biological night. Similarly, urban social jetlag (USJ) models were noted to have a significant rise in their core body temperature at 11:00 pm and lower temperature at 3:00 am, indicating, perhaps, a resting period between 3:00 am and 7:00 am assumptive of an advancement toward the light:dark transition. A similar finding is also observed among the AF as well as RSJ models accordingly. In general, our observation was that of a circadian shift in the temperature rhythm of the models.

To investigate these circadian shifts, we subjected the data of the intervention groups to analysis using repeated measures ANOVA and the findings indicated a preservation of rhythmicity of the core body temperature among the intervention groups. Subsequently, we conducted a population mean Cosinor analysis to estimate the circadian phases (Acrophases) of the core body temperature rhythms of the intervention groups. We noted the circadian phase of the control animals to occur at 20:16 while that of the RSJ and USJ models occurred at 14:43 and 19:48 local time, respectively [Table 1]. In addition, we observed the midline estimating statistic of rhythm (MESoR) for the RSJ models to be substantially lower than that of the controls (35.1°C Vs. 36.0°C). On the other hand, amplitude of the core body temperature among the RSJ model rats was 3 times higher than that of the controls (0.4°C), indicating a higher excursion or, perhaps, an erratic pattern of the core body temperature [Table 1]. In general, the result of the Cosinor analysis revealed a substantial difference in acrophases, thus confirming a shift in the circadian phases of the model groups.
Table 1: Cosinor analysis of the 24-h core body temperature rhythm among the groups

Click here to view


In order to gain further insight and estimate the vector component of the phase changes, deductive comparison of the acrophases within models was made. A 5 h phase delay was observed in the LAN model, whereas a 1 h phase advancement was noted among the AF model. SR model, on the other hand, exhibited 4.5 h phase advancement [Table 2]. Interestingly, the USJ models (who were concomitantly exposed to SR, AF and LAN protocols) were observed to have the lowest circadian phase shifts compared to SR, AF or LAN exposure models [Table 2]. This demonstrate that, in the USJ models, sleep restriction and abnormal feeding might have interacted, or acted independently, to negate the phase delaying effects of LAN exposure.
Table 2: Circadian phase relationship between control and the various models

Click here to view


Accordingly, to investigate whether these phase shifting effects are significant, we ran a mixed model ANOVA, which revealed highly significant (P < 0.001) timing × group interactions in all the models, except for the SR model. This indicates that except for the SR model, all the other models exhibit significant phase shift and circadian rhythm disruption.

Rhythmicity of blood glucose level

To investigate the effect of the various model interventions on blood glucose rhythm, we also compared the average blood glucose level of the groups during the light and dark periods, respectively. It was observed that the blood glucose level of the control rats was significantly (P = 0.0001) higher in the dark (126 mg/dL) than in the light period (108 mg/dL), indicating that the blood glucose level of the control rats is higher during their activity period. Interestingly, all the models appeared to have (using Student's t-test) statistically similar diurnal and nocturnal blood glucose levels [Table 3], signifying an abnormal glucose metabolism with diminished day: night rhythms. To investigate further, we ran a mixed-model ANOVA, which revealed a significant statistical variance in the rhythm of blood glucose level of all the models, indicating a significant arrhythmia in the blood glucose level of the models. To estimate the magnitude and determine the direction of the abnormal blood glucose rhythms, we conducted a Cosinor analysis and deductive comparison of the acrophases within models groups. The result showed an acrophase of blood glucose rhythm occurring at 21:11 (HH:MM) in the controls with remarkable shifts in acrophases noted in all the models [Table 4]. It could be notably observed that all models associated with SR exhibit a delay in their glucose rhythm phases with higher values toward the end of their biological day and the beginning of their biological night (hyperglycemia during the resting period). AF and LAN models, however, exhibit 2.2 and 3.5 advancement in the phases of their glucose rhythms, respectively. This means that their blood glucose rhythm is highest toward the end of their biological night. In general, we have demonstrated that the blood glucose rhythm of all the models has a distorted day: night rhythm, significant phase shifts, and dysrhythmias.
Table 3: Differences in the average blood glucose levels for the light and dark phases among the groups

Click here to view
Table 4: Magnitude and direction of glucose rhythm phases of models

Click here to view



  Discussion Top


The purpose of the present study was to develop models of modern-day circadian rhythm disruption and to investigate their possible diabetogenic potentials. Our finding indicated that LAN-exposed models exhibited a significantly raised nocturnal core body temperature that is not dissimilar to the availably reported patterns. For example, LAN has been reported to induce an increased nocturnal body temperature in mice.[18] More recently, a gradual increase in the body temperature of rats exposed to a constant light was reported.[19] The increase was noted to reach its maximum in 73 days after which it gradually decreases.[19] Similarly, the substantial circadian rhythm disruption noted among our LAN-exposed models is in consonant with the effective decoupling of human circadian physiology observed following a constructed longer photoperiod.[20] In addition, the 5 h phase delay observed among our LAN models corroborates the intensity-dependent phase delaying effect of light exposure near habitual bedtime reported.[7] In more recent studies, light exposure at nights and/or before bedtime is observed to shift the circadian phase to a later time.[20] It has been suggested that LAN-induced body temperature increment is via immunomodulatory and pro-inflammatory processes,[18],[19] while temperature rhythm disruption is believed to occur via SCN's multisynaptic projections to the preoptic area and through direct effects of melatonin on peripheral vasodilation.[17]

Our observed 4.5 h phase advancement among the SR models could be due to increased hypothalamic serotonin content,[21] which has been reported to decrease the entraining effects of light on the SCN.[22] In a contrary finding, even though no detectable circadian phase shifts was reported in mice housed under constant darkness, it was observed, however, that sleep deprivation reduced the phase delaying effect of a 10-min light pulse by 30%.[21] In addition, previous works found little or no phase-shifting effect following single 3-h bouts of sleep deprivation in the usual rest period of mice[23] or following 24-h sleep deprivation in hamsters.[24] These differences could be due to the different methodologies employed. As our finding corroborates a recent human study,[14] a finding of circadian phase advancement in Syrian hamsters subjected to 3 h sleep restriction during the mid resting period,[25] also agrees with our finding.

Our observed significant decrease in total and nocturnal core body temperature among the AF models adds to the growing body of literature pointing to the contributory role of mistimed feeding in circadian disruption and its induced metabolic impairments.[14] This finding is likely similar to the reported dampening of temperature rhythm in mice[26] and rats exposed to higher energy intakes.[27] The reduced total and nocturnal core temperature observed among our abnormally feed models could be due to the reported ability of ad libitum feeding to cause a reduced nocturnal activity compared to night feeding.[28] Therefore, the possibility of our abnormally fed rats to exhibit a reduced nocturnal activity[28] could cause decreased body temperature, since body temperature is known to be rhythmically associated with activity levels.[29] In support of our finding, the total core body temperature of mice feed exclusively during the night has been reported as only 96% of that recorded in ad libitum[30] and diurnally feed mice.[31] Feeding during the resting phase is reported to alter the temporal organization of hypothalamo–pituitary–adrenal axis and reset circadian clocks phases,[12] thus explaining the observed circadian disruption and phase advancement in our AF models. The findings of the present study are not different from the 4-h phase advancement[11] and the 3-h shift toward the light phase[28] reported following food restriction in rats. The seemingly larger phase advancements reported in these[11],[29] studies could have been due to their nonfactoring of sleep loss associated with their interventions, which we have reported herein as causing phase advancement among our models.

This deduction was confirmed by our observation of increased magnitude of phase advancement in the temperature rhythm of our RSJ models. In contrast, we noted a larger phase delay in the core temperature rhythms of the NSW models as compared to LAN exposure models, indicating that SR additively accentuates the phase delaying effects of LAN exposure, perhaps, because effects of SR on circadian system have been blamed on changes in light exposure associated with closing of eyes,[21] which is viewed as gating light exposure such that SR provides an opportunity for LAN exposure,[32] hence facilitating a delay in the timing of the circadian clock. This further buttressed our observation that SR alone did not bring about significant circadian desynchrony.

We observed our USJ models to have exhibited a significant circadian rhythm desynchrony and 28 min phase advancement, which suggests that, independent of SR, feeding during the resting period could also dampen the phase delaying effects of LAN. This may be because, although energy intake is not a strong synchronizer for the SCN under normal light: dark conditions,[27] food timing influences the circadian regulation of SCN[11] as well as counteract its synchronization effect on peripheral clocks.[31] As our AF models mimicked shifting of meals into the subjective resting phase which has been reported to attenuate nocturnal temperature rhythm,[31] the observed dampening of LAN's delaying effect by AF among our USJ models could not have been unexpected.

While glucose is required to sustain life by nearly all living organisms, its blood levels fluctuate in a time of the day dependent manner.[33] In nocturnal animals, such as rats, its blood concentration attains a higher level during the night and a lower level during the day.[33] This circadian fluctuation ensures optimal energy delivery as well as metabolic health and is controlled by the circadian system.[33] Our finding of significant circadian desynchrony as well as disrupted glucose rhythm is highly alarming because phase advancement of glucose rhythm has been described as an early sign of prediabetic metabolic state,[34] while blood glucose arrhythmia is a classical finding in diabetes mellitus.[34],[35] As circadian expressions of pancreatic islets are essential for proper beta-cell survival and function,[36] its disruption would accelerate diabetes development via pancreatic beta-cell damage and dysfunction.[33],[36] This altered pancreatic islets function has been reported to occur as a consequence of disrupted function of SCN[36] due to LAN exposure,[2],[33],[36] mistimed feeding,[2],[29] or SR.[37] Our finding could therefore be viewed in these lights as it corroborates findings from animal models of shift work[29],[36] and also observations among sleep deprived[37],[38] as well as circadian desynchronized[34] humans.


  Conclusion Top


Our findings have demonstrated that all our developed models exhibited a disrupted core body temperature rhythm, substantial circadian phase shifts, and blood glucose dysrhythmias, raising fear that circadian rhythm disruption could be as widespread and common phenomenon of modern-day humans as never anticipated. This stands to pose a significant threat to physiology that may accentuate the global pandemic of metabolic diseases.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Brunstrom JM, Cheon BK. Do humans still forage in an obesogenic environment? Mechanisms and implications for weight maintenance. Physiol Behav 2018;193:261-7.  Back to cited text no. 1
    
2.
Nelson RJ, Chbeir S. Dark matters: Effects of light at night on metabolism. Proc Nutr Soc 2018;77:223-9.  Back to cited text no. 2
    
3.
Evans JA, Davidson AJ. Health consequences of circadian disruption in humans and animal models. Prog Mol Biol Transl Sci 2013;119:283-323.  Back to cited text no. 3
    
4.
Arble DM, Ramsey KM, Bass J, Turek FW. Circadian disruption and metabolic disease: Findings from animal models. Best Pract Res Clin Endocrinol Metab 2010;24:785-800.  Back to cited text no. 4
    
5.
Cinzano P, Falchi F, Elvidge CD. The first World Atlas of the artificial night sky brightness. Mon Not R Astron Soc 2001;328:689-707.  Back to cited text no. 5
    
6.
Dissi GM, AbdusSalam AA. Sleep timing, light at night exposure and it's health effects among staff and students of Bayero University, Kano. DUJOPAS 2019;5:223-30.  Back to cited text no. 6
    
7.
Zeitzer JM, Dijk DJ, Kronauer R, Brown E, Czeisler C. Sensitivity of the human circadian pacemaker to nocturnal light: Melatonin phase resetting and suppression. J Physiol 2000;526 Pt 3:695-702.  Back to cited text no. 7
    
8.
Dissi GM, Muhammad A. Modifiable risk factors for metabolic-related diseases among staff and students of basic medical sciences faculty, Bayero University, Kano. BJMLS 2019;4:1-7.  Back to cited text no. 8
    
9.
Salgado-Delgado RC, Saderi N, Basualdo Mdel C, Guerrero-Vargas NN, Escobar C, Buijs RM. Shift work or food intake during the rest phase promotes metabolic disruption and desynchrony of liver genes in male rats. PLoS One 2013;8:e60052.  Back to cited text no. 9
    
10.
de la Iglesia HO, Cambras T, Schwartz WJ, Díez-Noguera A. Forced desynchronization of dual circadian oscillators within the rat suprachiasmatic nucleus. Curr Biol 2004;14:796-800.  Back to cited text no. 10
    
11.
Challet E, Pßvet P, Vivien-Roels B, Malan A. Phase-advanced daily rhythms of melatonin, body temperature, and locomotor activity in food-restricted rats fed during daytime. J Biol Rhythms 1997;12:65-79.  Back to cited text no. 11
    
12.
Challet E. The circadian regulation of food intake. Nat Rev Endocrinol 2019;15:393-405.  Back to cited text no. 12
    
13.
Bodosi B, Gardi J, Hajdu I, Szentirmai E, Obal F Jr, Krueger JM. Rhythms of ghrelin, leptin, and sleep in rats: Effects of the normal diurnal cycle, restricted feeding, and sleep deprivation. Am J Physiol Regul Integr Comp Physiol 2004;287:R1071-9.  Back to cited text no. 13
    
14.
Poggiogalle E, Jamshed H, Peterson CM. Circadian regulation of glucose, lipid, and energy metabolism in humans. Metabolism 2018;84:11-27.  Back to cited text no. 14
    
15.
Melanson EL, Ritchie HK, Dear TB, Catenacci V, Shea K, Connick E, et al. Daytime bright light exposure, metabolism, and individual differences in wake and sleep energy expenditure during circadian entrainment and misalignment. Neurobiol Sleep Circadian Rhythms 2018;4:49-56.  Back to cited text no. 15
    
16.
Christiansen SL, Højgaard K, Wiborg O, Bouzinova EV. Disturbed diurnal rhythm of three classical phase markers in the chronic mild stress rat model of depression. Neurosci Res 2016;110:43-8.  Back to cited text no. 16
    
17.
Broussard JL, Reynolds AC, Depner CM, Ferguson SA, Dawson D, Wright KP. Circadian rhythms versus daily patterns in human physiology and behavior. In: Kumar V, editor. Biological Timekeeping: Clocks, Rhythms and Behaviour. New Delhi: Springer; 2017. p. 279-95.  Back to cited text no. 17
    
18.
Fonken LK, Weil ZM, Nelson RJ. Mice exposed to dim light at night exaggerate inflammatory responses to lipopolysaccharide. Brain Behav Immun 2013;34:159-63.  Back to cited text no. 18
    
19.
Kang X, Jia L, Zhang X, Li Y, Chen Y, Shen X, et al. Long-term continuous light exposure affects body weight and blood glucose associated with inflammation in female rats. J Biosci Med 2016;4:11-24.  Back to cited text no. 19
    
20.
Czeisler CA. Perspective: Casting light on sleep deficiency. Nature 2013;497:S13.  Back to cited text no. 20
    
21.
Challet E, Turek FW, Laute M, Van Reeth O. Sleep deprivation decreases phase-shift responses of circadian rhythms to light in the mouse: Role of serotonergic and metabolic signals. Brain Res 2001;909:81-91.  Back to cited text no. 21
    
22.
Bradbury MJ, Dement WC, Edgar DM. Serotonin-containing fibers in the suprachiasmatic hypothalamus attenuate light-induced phase delays in mice. Brain Res 1997;768:125-34.  Back to cited text no. 22
    
23.
Marchant EG, Mistlberger RE. Entrainment and phase shifting of circadian rhythms in mice by forced treadmill running. Physiol Behav 1996;60:657-63.  Back to cited text no. 23
    
24.
Mistlberger RE, Landry GJ, Marchant EG. Sleep deprivation can attenuate light-induced phase shifts of circadian rhythms in hamsters. Neurosci Lett 1997;238:5-8.  Back to cited text no. 24
    
25.
Antle MC, Mistlberger RE. Circadian clock resetting by sleep deprivation without exercise in the Syrian hamster. J Neurosci 2000;20:9326-32.  Back to cited text no. 25
    
26.
Mendoza J, Pßvet P, Challet E. High-fat feeding alters the clock synchronization to light. J Physiol 2008;586:5901-10.  Back to cited text no. 26
    
27.
Goh GH, Mark PJ, Maloney SK. Altered energy intake and the amplitude of the body temperature rhythm are associated with changes in phase, but not amplitude, of clock gene expression in the rat suprachiasmatic nucleus in vivo. ChronobiolInt 2016;33:85-97.  Back to cited text no. 27
    
28.
de Goede P, Sen S, Oosterman JE, Foppen E, Jansen R, la Fleur SE, et al. Differential effects of diet composition and timing of feeding behavior on rat brown adipose tissue and skeletal muscle peripheral clocks. Neurobiol Sleep Circadian Rhythms 2018;4:24-33.  Back to cited text no. 28
    
29.
Salgado-Delgado R, Angeles-Castellanos M, Saderi N, Buijs RM, Escobar C. Food intake during the normal activity phase prevents obesity and circadian desynchrony in a rat model of night work. Endocrinology 2010;151:1019-29.  Back to cited text no. 29
    
30.
Nelson W, Halberg F. Meal-timing, circadian rhythms and life span of mice. J Nutr 1986;116:2244-53.  Back to cited text no. 30
    
31.
Damiola F, Le Minh N, Preitner N, Kornmann B, Fleury-Olela F, Schibler U. Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes Dev 2000;14:2950-61.  Back to cited text no. 31
    
32.
Khalsa SB, Jewett ME, Cajochen C, Czeisler CA. A phase response curve to single bright light pulses in human subjects. J Physiol 2003;549:945-52.  Back to cited text no. 32
    
33.
Kumar Jha P, Challet E, Kalsbeek A. Circadian rhythms in glucose and lipid metabolism in nocturnal and diurnal mammals. Mol Cell Endocrinol 2015;418 Pt 1:74-88.  Back to cited text no. 33
    
34.
Gubin DG, Nelaeva AA, Uzhakova AE, Hasanova YV, Cornelissen G, Weinert D. Disrupted circadian rhythms of body temperature, heart rate and fasting blood glucose in prediabetes and type 2 diabetes mellitus. Chronobiol Int 2017;34:1136-48.  Back to cited text no. 34
    
35.
Ramos-Lobo AM, Buonfiglio DC, Cipolla-Neto J. Streptozotocin-induced diabetes disrupts the body temperature daily rhythm in rats. Diabetol Metab Syndr 2015;7:39.  Back to cited text no. 35
    
36.
Qian J, Block GD, Colwell CS, Matveyenko AV. Consequences of exposure to light at night on the pancreatic islet circadian clock and function in rats. Diabetes 2013;62:3469-78.  Back to cited text no. 36
    
37.
Reynolds AC, Dorrian J, Liu PY, van Dongen HP, Wittert GA, Harmer LJ, et al. Impact of five nights of sleep restriction on glucose metabolism, leptin and testosterone in young adult men. PLoS One 2012;7:e41218.  Back to cited text no. 37
    
38.
Spiegel K, Knutson K, Leproult R, Tasali E, Van Cauter E. Sleep loss: A novel risk factor for insulin resistance and Type 2 diabetes. J Appl Physiol (1985) 2005;99:2008-19.  Back to cited text no. 38
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Materials and Me...
Results
Discussion
Conclusion
References
Article Tables

 Article Access Statistics
    Viewed268    
    Printed11    
    Emailed0    
    PDF Downloaded31    
    Comments [Add]    

Recommend this journal