We characterize the effects of sleep deprivation on sleep-wake behavior, neurogenesis and stress in adult zebrafish, and describe light-induced changes in gene expression. Sleep deprivation was performed using two stimuli: mild electroshock and light. Comparisons were made between five groups of fish: naïve; electroshock sleep-deprived and yoked-control; fish exposed to constant light (increasing wakefulness); and fish exposed to constant darkness (increasing sleep). Behavioral parameters assessed were sleep percentage, number of sleep-wake transitions, and sleep and wake bout length. Using microarray technology, light-dark modulation of gene expression was examined. In parallel with gene expression, neurogenesis was measured and stress following sleep deprivation was assessed behaviorally and physiologically. Our results indicate that sleep duration is most effectively altered by varying exposure to ambient light. Further, while the sleep-wake dynamics are comparable to those observed in mammals, zebrafish may exhibit weaker sleep homeostasis and sleep pressure than do mammals; and sleep deprivation does not significantly alter their stress responses. Finally, modulation of gene expression by light and dark was observed. Genes upregulated during the dark period are broadly related to growth, morphogenesis, energy balance, and lipid synthesis. Genes upregulated during light are broadly related to synaptic plasticity and cell proliferation.
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http://dx.doi.org/10.1016/j.bbr.2013.08.032 | DOI Listing |
Chronobiol Int
January 2025
Research Center for Overwork-Related Disorders, National Institute of Occupational Safety and Health, Kawasaki, Japan.
In modern society, many workers struggle with sleep deprivation due to their work schedules and excessive workloads. Accurate self-awareness and self-monitoring abilities are crucial for workers to adopt risk-coping strategies and protective behaviors when fatigued. The current study examined the relationship between chronotypes and self-monitoring performance during 24 h of sleep deprivation.
View Article and Find Full Text PDFJ Sleep Res
January 2025
Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, South Australia, Australia.
Sleepiness-related errors are a leading cause of driving accidents, requiring drivers to effectively monitor sleepiness levels. However, there are inter-individual differences in driving performance after sleep loss, with some showing poor driving performance while others show minimal impairment. This research explored if there are differences in self-reported sleepiness and driving performance in healthy drivers who exhibited vulnerability or resistance to objective driving impairment following extended wakefulness.
View Article and Find Full Text PDFSleep Breath
January 2025
Faculty of Medicine, Institute of Health Sciences, Department of Public Health, University of Hacettepe, Ankara, Türkiye.
Background: Fatigue, sleep disorders, and daytime sleepiness are interconnected, posing significant risks to occupational health and workplace safety. However, the literature on their relationships remains fragmented, with notable gaps, particularly concerning working populations. This descriptive cross-sectional study aimed to evaluate sleep quality (SQ), daily sleep time in hours (DST), daytime sleepiness, fatigue levels among employees in an automotive workplace, and their interrelationships.
View Article and Find Full Text PDFStudy Objectives: The Psychomotor Vigilance Task (PVT) is widely recognized as the gold standard for measuring vigilance, providing a rapid and objective measure of this state. While driving simulations are also used, they typically require longer administration times. This study examines the sensitivity of driving simulation variables to sleep deprivation throughout the task.
View Article and Find Full Text PDFSleep Biol Rhythms
January 2025
Sleep Research Institute, Edogawa University, 474 Komagi, Nagareyama, Chiba 270-0198 Japan.
To examine whether the effects of low sleep quality, sleep deprivation, and chronotype on daytime cognitive function varied by age group. All data were collected online. We obtained the data from 366 employed people in their 20s, 40s, or 60s.
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