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Usmani IM, Dijk DJ, Skeldon AC. Mathematical Analysis of Light-sensitivity Related Challenges in Assessment of the Intrinsic Period of the Human Circadian Pacemaker. J Biol Rhythms 2024; 39:166-182. [PMID: 38317600 PMCID: PMC10996302 DOI: 10.1177/07487304231215844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
Accurate assessment of the intrinsic period of the human circadian pacemaker is essential for a quantitative understanding of how our circadian rhythms are synchronized to exposure to natural and man-made light-dark (LD) cycles. The gold standard method for assessing intrinsic period in humans is forced desynchrony (FD) which assumes that the confounding effect of lights-on assessment of intrinsic period is removed by scheduling sleep-wake and associated dim LD cycles to periods outside the range of entrainment of the circadian pacemaker. However, the observation that the mean period of free-running blind people is longer than the mean period of sighted people assessed by FD (24.50 ± 0.17 h vs 24.15 ± 0.20 h, p < 0.001) appears inconsistent with this assertion. Here, we present a mathematical analysis using a simple parametric model of the circadian pacemaker with a sinusoidal velocity response curve (VRC) describing the effect of light on the speed of the oscillator. The analysis shows that the shorter period in FD may be explained by exquisite sensitivity of the human circadian pacemaker to low light intensities and a VRC with a larger advance region than delay region. The main implication of this analysis, which generates new and testable predictions, is that current quantitative models for predicting how light exposure affects entrainment of the human circadian system may not accurately capture the effect of dim light. The mathematical analysis generates new predictions which can be tested in laboratory experiments. These findings have implications for managing healthy entrainment of human circadian clocks in societies with abundant access to light sources with powerful biological effects.
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Affiliation(s)
- Imran M. Usmani
- Department of Mathematics, University of Surrey, Guildford, UK
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Department of Clinical and Experimental Medicine, University of Surrey, Guildford, UK
- UK Dementia Research Institute Care Research & Technology Centre, Imperial College London and the University of Surrey, Guildford, UK
| | - Anne C. Skeldon
- Department of Mathematics, University of Surrey, Guildford, UK
- UK Dementia Research Institute Care Research & Technology Centre, Imperial College London and the University of Surrey, Guildford, UK
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Stowe SR, LeBourgeois MK, Behn CD. Modeling the Effects of Napping and Non-napping Patterns of Light Exposure on the Human Circadian Oscillator. J Biol Rhythms 2023; 38:492-509. [PMID: 37427666 PMCID: PMC10524998 DOI: 10.1177/07487304231180953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
In early childhood, consolidation of sleep from a biphasic to a monophasic sleep-wake pattern, that is, the transition from sleeping during an afternoon nap and at night to sleeping only during the night, represents a major developmental milestone. Reduced napping behavior is associated with an advance in the timing of the circadian system; however, it is unknown if this advance represents a standard response of the circadian clock to altered patterns of light exposure or if it additionally reflects features of the developing circadian system. Using a mathematical model of the human circadian pacemaker, we investigated the impact of napping and non-napping patterns of light exposure on entrained circadian phases. Simulated light schedules were based on published data from 20 children (34.2 ± 2.0 months) with habitual napping or non-napping sleep patterns (15 nappers). We found the model predicted different circadian phases for napping and non-napping light patterns: both the decrease in afternoon light during the nap and the increase in evening light associated with napping toddlers' later bedtimes contributed to the observed circadian phase difference produced between napping and non-napping light schedules. We systematically quantified the effects on phase shifting of nap duration, timing, and light intensity, finding larger phase delays occurred for longer and earlier naps. In addition, we simulated phase response curves to a 1-h light pulse and 1-h dark pulse to predict phase and intensity dependence of these changes in light exposure. We found the light pulse produced larger shifts compared with the dark pulse, and we analyzed the model dynamics to identify the features contributing to this asymmetry. These findings suggest that napping status affects circadian timing due to altered patterns of light exposure, with the dynamics of the circadian clock and light processing mediating the effects of the dark pulse associated with a daytime nap.
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Affiliation(s)
- Shelby R. Stowe
- Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado
| | | | - Cecilia Diniz Behn
- Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado
- Division of Endocrinology, Department of Pediatrics, University of Colorado Denver Anschutz Medical Campus, Aurora, Colorado
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Li L, Liang T, Jiang T, Li Y, Yang L, Wu L, Yang J, Ding Y, Wang J, Chen M, Zhang J, Xie X, Wu Q. Gut microbiota: Candidates for a novel strategy for ameliorating sleep disorders. Crit Rev Food Sci Nutr 2023:1-17. [PMID: 37477274 DOI: 10.1080/10408398.2023.2228409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/22/2023]
Abstract
The aim of this review was to evaluate the feasibility of treating sleep disorders using novel gut microbiota intervention strategies. Multiple factors can cause sleep disorders, including an imbalance in the gut microbiota. Studies of the microbiome-gut-brain axis have revealed bidirectional communication between the central nervous system and gut microbes, providing a more comprehensive understanding of mood and behavioral regulatory patterns. Changes in the gut microbiota and its metabolites can stimulate the endocrine, nervous, and immune systems, which regulate the release of neurotransmitters and alter the activity of the central nervous system, ultimately leading to sleep disorders. Here, we review the main factors affecting sleep, discuss possible pathways and molecular mechanisms of the interaction between sleep and the gut microbiota, and compare common gut microbiota intervention strategies aimed at improving sleep physiology.
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Affiliation(s)
- Longyan Li
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
- College of Food Science, South China Agricultural University, Guangzhou, China
| | - Tingting Liang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Tong Jiang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Ying Li
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Lingshuang Yang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
- College of Food Science, South China Agricultural University, Guangzhou, China
| | - Lei Wu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Juan Yang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Yu Ding
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Juan Wang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
- College of Food Science, South China Agricultural University, Guangzhou, China
| | - Moutong Chen
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Jumei Zhang
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Xinqiang Xie
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
| | - Qingping Wu
- Guangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Key Laboratory of Agricultural Microbiomics and Precision Application, Ministry of Agriculture and Rural Affairs, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou, People's Republic of China
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Psarellis YM, Kavousanakis M, Henson MA, Kevrekidis IG. Limits of entrainment of circadian neuronal networks. CHAOS (WOODBURY, N.Y.) 2023; 33:013137. [PMID: 36725649 PMCID: PMC9883082 DOI: 10.1063/5.0122744] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 12/19/2022] [Indexed: 06/07/2023]
Abstract
Circadian rhythmicity lies at the center of various important physiological and behavioral processes in mammals, such as sleep, metabolism, homeostasis, mood changes, and more. Misalignment of intrinsic neuronal oscillations with the external day-night cycle can disrupt such processes and lead to numerous disorders. In this work, we computationally determine the limits of circadian synchronization to external light signals of different frequency, duty cycle, and simulated amplitude. Instead of modeling circadian dynamics with generic oscillator models (e.g., Kuramoto-type), we use a detailed computational neuroscience model, which integrates biomolecular dynamics, neuronal electrophysiology, and network effects. This allows us to investigate the effect of small drug molecules, such as Longdaysin, and connect our results with experimental findings. To combat the high dimensionality of such a detailed model, we employ a matrix-free approach, while our entire algorithmic pipeline enables numerical continuation and construction of bifurcation diagrams using only direct simulation. We, thus, computationally explore the effect of heterogeneity in the circadian neuronal network, as well as the effect of the corrective therapeutic intervention of Longdaysin. Last, we employ unsupervised learning to construct a data-driven embedding space for representing neuronal heterogeneity.
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Affiliation(s)
- Yorgos M. Psarellis
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Michail Kavousanakis
- School of Chemical Engineering, National Technical University of Athens, Zografou, Athens 15780, Greece
| | - Michael A. Henson
- Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
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Liao G, Bose A. Entrainment within hierarchical circadian oscillator networks. Math Biosci 2022; 351:108883. [PMID: 35907509 DOI: 10.1016/j.mbs.2022.108883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 07/15/2022] [Accepted: 07/18/2022] [Indexed: 11/24/2022]
Abstract
Circadian rhythms are endogenous oscillations, widely found across biological species, that have the capability of entraining to the 24-h light-dark cycle. Circadian systems often consist of both central oscillators that receive direct light-dark input and peripheral oscillators that receive input from the central oscillators. In this paper, we address questions related to what governs the time to and pattern of entrainment of these hierarchical circadian systems after an abrupt switch in the light-dark phasing. For a network consisting of a single central oscillator coupled to a chain of N feed-forward peripheral oscillators, we introduce a systematic way to derive an N-dimensional entrainment map whose fixed points correspond to entrained solutions. Using the map, we explain that the direction of reentrainment can involve fairly complicated phase advancing and delaying behavior as well as reentrainment times that depend sensitively on the nature of the perturbation. We also study the dynamics of a hierarchical system in which the peripheral oscillators are mutually coupled. We study how reentrainment times vary as a function of the degree to which the oscillators are desynchronized at the time of the change in light-dark phasing. We show that desynchronizing the peripheral oscillators can, in some circumstances, speed up their ultimate reentrainment following perturbations.
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Affiliation(s)
- Guangyuan Liao
- Key Laboratory of Intelligent Analysis and Decision on Complex Systems, School of Science, Chongqing University of Posts and Telecommunications, Chongwen Road, Nan'an, 400065, Chongqing, China
| | - Amitabha Bose
- Department of Mathematical Sciences, NJIT, Newark, NJ, 07102, USA.
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