Mathematical modeling of sleep state dynamics in a rodent model of shift work

Millions of people worldwide are required to work when their physiology is tuned for sleep. By forcing wakefulness out of the body’s normal schedule, shift workers face numerous adverse health consequences, including gastrointestinal problems, sleep problems, and higher rates of some diseases, including cancers. Recent studies have developed protocols to simulate shift work in rodents with the intention of assessing the effects of night-shift work on subsequent sleep (Grønli et al., 2017). These studies have already provided important contributions to the understanding of the metabolic consequences of shift work (Arble et al., 2015; Marti et al., 2016; Opperhuizen et al., 2015) and sleep-wake-specific impacts of night-shift work (Grønli et al., 2017). However, our understanding of the causal mechanisms underlying night-shift-related sleep disturbances is limited. In order to advance toward a mechanistic understanding of sleep disruption in shift work, we model these data with two different approaches. First we apply a simple homeostatic model to quantify differences in the rates at which sleep need, as measured by slow wave activity during slow wave sleep (SWS) rises and falls. Second, we develop a simple and novel mathematical model of rodent sleep and use it to investigate the timing of sleep in a simulated shift work protocol (Grønli et al., 2017). This mathematical framework includes the circadian and homeostatic processes of the two-process model, but additionally incorporates a stochastic process to model the polyphasic nature of rodent sleep. By changing only the time at which the rodents are forced to be awake, the model reproduces some key experimental results from the previous study, including correct proportions of time spent in each stage of sleep as a function of circadian time and the differences in total wake time and SWS bout durations in the rodents representing night-shift workers and those representing day-shift workers. Importantly, the model allows for deeper insight into circadian and homeostatic influences on sleep timing, as it demonstrates that the differences in SWS bout duration between rodents in the two shifts is largely a circadian effect. Our study shows the importance of mathematical modeling in uncovering mechanisms behind shift work sleep disturbances and it begins to lay a foundation for future mathematical modeling of sleep in rodents

Modafinil as a catecholaminergic agent: empirical evidence and unanswered questions

Modafinil, in its two clinical formulations (Provigil® and Nuvigil®), is a widely prescribed wake-promoting therapeutic agent. It binds competitively to the cell membrane dopamine transporter and is dependent on catecholaminergic (dopaminergic and adrenergic) signaling for its wake-promoting effects. The clinical spectrum of effects for modafinil is distinct from the effects seen with other catecholaminergic agents. Relative to other commonly used agents that act through catecholaminergic mechanisms, modafinil has a relatively low abuse potential, produces wakefulness with an attenuated compensatory sleep recovery thereafter, and does not ameliorate cataplexy in narcolepsy. These clinically relevant phenomenological differences between modafinil and agents such as amphetamines and cocaine do not eliminate catecholaminergic effects as a possible mediator of its wake-promoting action; they merely reflect its unique pharmacological profile. Modafinil is an exceptionally weak, but apparently very selective, dopamine transporter inhibitor. The pharmacodynamic response to modafinil, as measured by dopamine levels in brain microdialysate, is protracted relative to other agents that act via catecholaminergic mechanisms. The conformational constraints on the interaction of modafinil with the dopamine transporter—and probably, as a consequence, its effects on trace amine receptor signaling in the catecholaminergic cell—are unique among catecholaminergic agents. These unique pharmacological properties of modafinil should be considered both in seeking to thoroughly understand its putatively elusive mechanism of action and in the design of novel therapeutic agents

A metabolic-transcriptional network links sleep and cellular energetics in the brain

This review proposes a mechanistic link between cellular metabolic status, transcriptional regulatory changes and sleep. Sleep loss is associated with changes in cellular metabolic status in the brain. Metabolic sensors responsive to cellular metabolic status regulate the circadian clock transcriptional network. Modifications of the transcriptional activity of circadian clock genes affect sleep/wake state changes. Changes in sleep state reverse sleep loss-induced changes in cellular metabolic status. It is thus proposed that the regulation of circadian clock genes by cellular metabolic sensors is a critical intermediate step in the link between cellular metabolic status and sleep. Studies of this regulatory relationship may offer insights into the function of sleep at the cellular level

Multi-Modal Regulation of Circadian Physiology by Interactive Features of Biological Clocks

The circadian clock is a fundamental biological timing mechanism that generates nearly 24 h rhythms of physiology and behaviors, including sleep/wake cycles, hormone secretion, and metabolism. Evolutionarily, the endogenous clock is thought to confer living organisms, including humans, with survival benefits by adapting internal rhythms to the day and night cycles of the local environment. Mirroring the evolutionary fitness bestowed by the circadian clock, daily mismatches between the internal body clock and environmental cycles, such as irregular work (e.g., night shift work) and life schedules (e.g., jet lag, mistimed eating), have been recognized to increase the risk of cardiac, metabolic, and neurological diseases. Moreover, increasing numbers of studies with cellular and animal models have detected the presence of functional circadian oscillators at multiple levels, ranging from individual neurons and fibroblasts to brain and peripheral organs. These oscillators are tightly coupled to timely modulate cellular and bodily responses to physiological and metabolic cues. In this review, we will discuss the roles of central and peripheral clocks in physiology and diseases, highlighting the dynamic regulatory interactions between circadian timing systems and multiple metabolic factors

Sleep-active cells in the cerebral cortex and their role in slow-wave activity

We recently identified neurons in the cerebral cortex that become activated during sleep episodes with high slow-wave activity (SWA). The distinctive properties of these neurons are the ability to produce nitric oxide and their long-range projections within the cortex. In this review, we discuss how these characteristics of sleep-active cells could be relevant to SWA production in the cortex. We also discuss possible models of the role of nNOS cells in SWA production

Sleep homeostasis and night work: a polysomnographic study of daytime sleep following three consecutive simulated night shifts

Purpose: Millions of people work at times that overlap with the habitual time for sleep. Consequently, sleep often occurs during the day. Daytime sleep is, however, characterized by reduced sleep duration. Despite preserved time spent in deep NREM sleep (stage N3), daytime sleep is subjectively rated as less restorative. Knowledge on how night work influences homeostatic sleep pressure is limited. Therefore, we aimed to explore the effect of three consecutive simulated night shifts on daytime sleep and markers of sleep homeostasis. Patients and Methods: We performed continuous EEG, EMG and EOG recordings in the subjects’ home setting for one nighttime sleep opportunity, and for the daytime sleep opportunities following three consecutive simulated night shifts. Results: For all daytime sleep opportunities, total sleep time was reduced compared to nighttime sleep. While time spent in stage N3 was preserved, sleep pressure at sleep onset, measured by slow wave activity (1– 4 Hz), was higher than nighttime sleep and higher on day 3 than on day 1 and 2. Elevated EEG power during daytime sleep was sustained through 6 h of time in bed. Slow wave energy was not significantly different from nighttime sleep after 6 h, reflecting a less efficient relief of sleep pressure. Conclusion: Adaptation to daytime sleep following three consecutive simulated night shifts is limited. The increased homeostatic response and continuation of sleep pressure relief even after 6 h of sleep, are assumed to reflect a challenge for appropriate homeostatic reduction to occur.publishedVersio