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Title: Brain activity of diving seals reveals short sleep cycles at depth
Elephant seals sleep 2 hours a day while diving for months at sea, rivaling the record for the least sleep among mammals.  more » « less
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Page Range / eLocation ID:
260 to 265
Medium: X
Sponsoring Org:
National Science Foundation
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  1. null (Ed.)
    Sleep has many roles, from strengthening new memories to regulating mood and appetite. While we might instinctively think of sleep as a uniform state of reduced brain activity, the reality is more complex. First, over the course of the night, we cycle between a number of different sleep stages, which reflect different levels of sleep depth. Second, the amount of sleep depth is not necessarily even across the brain but can vary between regions. These sleep stages consist of either rapid eye movement (REM) sleep or non-REM (NREM) sleep. REM sleep is when most dreaming occurs, whereas NREM sleep is particularly important for learning and memory and can vary in duration and depth. During NREM sleep, large groups of neurons synchronize their firing to create rhythmic waves of activity known as slow waves. The more synchronous the activity, the deeper the sleep. Vaidyanathan et al. now show that brain cells called astrocytes help regulate NREM sleep. Astrocytes are not neurons but belong to a group of specialized cells called glia. They are the largest glia cell type in the brain and display an array of proteins on their surfaces called G-protein-coupled receptors (GPCRs). These enable them to sense sleep-wake signals from other parts of the brain and to generate their own signals. In fact, each astrocyte can communicate with thousands of neurons at once. They are therefore well-poised to coordinate brain activity during NREM sleep. Using innovative tools, Vaidyanathan et al. visualized astrocyte activity in mice as the animals woke up or fell asleep. The results showed that astrocytes change their activity just before each sleep–wake transition. They also revealed that astrocytes control both the depth and duration of NREM sleep via two different types of GPCR signals. Increasing one of these signals (Gi-GPCR) made the mice sleep more deeply but did not change sleep duration. Decreasing the other (Gq-GPCR) made the mice sleep for longer but did not affect sleep depth. Sleep problems affect many people at some point in their lives, and often co-exist with other conditions such as mental health disorders. Understanding how the brain regulates different features of sleep could help us develop better – and perhaps more specific – treatments for sleep disorders. The current study suggests that manipulating GPCRs on astrocytes might increase sleep depth, for example. But before work to test this idea can begin, we must first determine whether findings from sleeping mice also apply to people. 
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  2. Background Shift workers are at high risk of developing sleep disorders such as shift worker sleep disorder or chronic insomnia. Cognitive behavioral therapy (CBT) is the first-line treatment for insomnia, and emerging evidence shows that internet-based CBT is highly effective with additional features such as continuous tracking and personalization. However, there are limited studies on internet-based CBT for shift workers with sleep disorders. Objective This study aimed to evaluate the impact of a 4-week, physician-assisted, internet-delivered CBT program incorporating machine learning–based well-being prediction on the sleep duration of shift workers at high risk of sleep disorders. We evaluated these outcomes using an internet-delivered CBT app and fitness trackers in the intensive care unit. Methods A convenience sample of 61 shift workers (mean age 32.9, SD 8.3 years) from the intensive care unit or emergency department participated in the study. Eligible participants were on a 3-shift schedule and had a Pittsburgh Sleep Quality Index score ≥5. The study comprised a 1-week baseline period, followed by a 4-week intervention period. Before the study, the participants completed questionnaires regarding the subjective evaluation of sleep, burnout syndrome, and mental health. Participants were asked to wear a commercial fitness tracker to track their daily activities, heart rate, and sleep for 5 weeks. The internet-delivered CBT program included well-being prediction, activity and sleep chart, and sleep advice. A job-based multitask and multilabel convolutional neural network–based model was used for well-being prediction. Participant-specific sleep advice was provided by sleep physicians based on daily surveys and fitness tracker data. The primary end point of this study was sleep duration. For continuous measurements (sleep duration, steps, etc), the mean baseline and week-4 intervention data were compared. The 2-tailed paired t test or Wilcoxon signed rank test was performed depending on the distribution of the data. Results In the fourth week of intervention, the mean daily sleep duration for 7 days (6.06, SD 1.30 hours) showed a statistically significant increase compared with the baseline (5.54, SD 1.36 hours; P=.02). Subjective sleep quality, as measured by the Pittsburgh Sleep Quality Index, also showed statistically significant improvement from baseline (9.10) to after the intervention (7.84; P=.001). However, no significant improvement was found in the subjective well-being scores (all P>.05). Feature importance analysis for all 45 variables in the prediction model showed that sleep duration had the highest importance. Conclusions The physician-assisted internet-delivered CBT program targeting shift workers with a high risk of sleep disorders showed a statistically significant increase in sleep duration as measured by wearable sensors along with subjective sleep quality. This study shows that sleep improvement programs using an app and wearable sensors are feasible and may play an important role in preventing shift work–related sleep disorders. International Registered Report Identifier (IRRID) RR2-10.2196/24799. 
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  3. Abstract

    The photoperiod has been evidenced to influence sleep regulation in the rat. Nevertheless, lengthening of the photoperiod beyond 30 days seems to have little effect on the 24‐hr baseline level of sleep and the response to total sleep deprivation. We studied the effects of 12:12 (habitual) and 16:8 (long) light–dark photoperiods on sleep, locomotor activity and body core temperature, before and after 24 hr of total sleep deprivation. Eight rats were submitted for 14 days to light–dark 12:12 (lights on: 08:00 hours–20:00 hours) followed by total sleep deprivation, and then for 14 days to light–dark 16:8 (light extended to 24:00 hours) followed by total sleep deprivation. Rats were simultaneously recorded for electroencephalogram, locomotor activity and body core temperature for 24 hr before and after total sleep deprivation. At baseline before total sleep deprivation, total sleep time and non‐rapid eye movement sleep per 24 hr and during extended light hours (20:00 hours–24:00 hours) were higher (13% for total sleep time) after light–dark exposure compared with habitual photoperiod, while percentage delta power in non‐rapid eye movements and rapid eye movements were unchanged. Locomotor activity and body core temperature were lower, particularly during extended light hours (20:00 hours–24:00 hours). Following total sleep deprivation, total sleep time and non‐rapid eye movements were significantly lower after long photoperiod between 20:00 hours and 24:00 hours, and between 10:00 hours and 12:00 hours, and unchanged per 24 hr. The percentage delta power in non‐rapid eye movements was lower between 08:00 hours and 11:00 hours. Total sleep deprivation decreased locomotor activity and body core temperature after habitual photoperiod exposure only. Fourteen days under long photoperiod (light–dark 16:8) increased non‐rapid eye movements sleep, and decreased sleep rebound related to total sleep deprivation (lower non‐rapid eye movements duration and delta power). This may create a model of sleep extension for the rat that has been found to favour anabolism in the brain and the periphery.

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  4. Abstract

    Animals respond to sleep loss with compensatory rebound sleep, and this is thought to be critical for the maintenance of physiological homeostasis. Sleep duration varies dramatically across animal species, but it is not known whether evolutionary differences in sleep duration are associated with differences in sleep homeostasis. The Mexican cavefish,Astyanax mexicanus, has emerged as a powerful model for studying the evolution of sleep. While eyed surface populations ofA. mexicanussleep approximately 8 hr each day, multiple blind cavefish populations have converged on sleep patterns that total as little as 2 hr each day, providing the opportunity to examine whether the evolution of sleep loss is accompanied by changes in sleep homeostasis. Here, we examine the behavioral and molecular response to sleep deprivation across four independent populations ofA. mexicanus. Our behavioral analysis indicates that surface fish and all three cavefish populations display robust recovery sleep during the day following nighttime sleep deprivation, suggesting sleep homeostasis remains intact in cavefish. We profiled transcriptome‐wide changes associated with sleep deprivation in surface fish and cavefish. While the total number of differentially expressed genes was not greater for the surface population, the surface population exhibited the highest number of uniquely differentially expressed genes than any other population. Strikingly, a majority of the differentially expressed genes are unique to individual cave populations, suggesting unique expression responses are exhibited across independently evolved cavefish populations. Together, these findings suggest sleep homeostasis is intact in cavefish despite a dramatic reduction in overall sleep duration.

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