Human sleep‐wake cycles in the high arctic: Effects of unusual photoperiodicity in a natural setting

Abstract

Studies of human circadian rhythms are typically conducted in artificial environments that are low in ecological validity. In the current study, six subjects and the field director lived in temporal isolation in a completely natural environment with constant daylight (a high Arctic research camp) for six weeks. Detailed daily sleep logs were kept. In keeping with past findings, five of the six subjects developed a free‐running sleep‐wake cycle longer than 24 hours. Unlike past results, the isolated subjects did not exhibit any synchronicity in their rhythms. There was a high degree of intersubject variability in circadian patterns. The findings have important implications for the comparison of the results of laboratory and field investigations of sleep‐wake cycles.     

The influence of the sleep-wake cycle on primary monosymptomatic nocturnal enuresis: a non-randomized comparative study

Backround: Enuresis implies severe stress in affected children, and impairs quality of life and sleep. Children with enuresis experience difficulties in their arousal from sleep, possibly associated with disturbances of the circadian rhythm. In this study, we aimed to evaluate the sleep–wake cycle and sleep disturbances in children with monosymptomatic enuresis nocturna (MEN). Method: The study comprised 70 children with MEN who were admitted to the pediatrics and urology outpatients department and 94 age-matched healthy controls. Parents completed “Strengths and Difficulties Questionnaire,” Children’s Sleep Habits Questionnaire (CSHQ), Children’s Chronotype Questionnaire scale. Results: Children with enuresis had significantly more sleep and psychological problem. Enuresis group reported higher bedtime resistance, parasomnias, breathing-related problems, and daytime sleepiness in CHSQ (p < 0.05). Although circadian preference did not differ statistically between the groups (p > 0.05), sleep duration on school days and awakening and mid-sleep points, both on scheduled and free days, were found to be significantly different in the enuretic group (p < 0.05). In logistic regression analysis, age, sleep period on scheduled days, sleep inertia on scheduled and free days were significant predictor for enuresis. Discussion: Children with enuresis were more likely to experience problematic sleep. This may reflect that enuretic children have impaired sleep–wake cycles, leading to dysregulation of daily functional changes of bladder capacity and related hormones such as ADH. These findings might imply a sleep–wake disturbance in enuresis.     

Rhythmic oscillations in KaiC1 phosphorylation and ATP/ADP ratio in nitrogen-fixing cyanobacterium Cyanothece sp. ATCC 51142

Cyanobacterial circadian clock composed of the Kai oscillator has been unraveled in the model strain Synechococcus elongatus PCC 7942. Recent studies with nitrogen-fixing Cyanothece sp. ATCC 51142 show rhythmic oscillations in the cellular program even in continuous light albeit with a cycle time of ~11 h. In the present study, we investigate correlation between cellular rhythms, KaiC1 phosphorylation cycle, ATP/ADP ratio, and the redox state of plastoquinone pool in Cyanothece. KaiC1 phosphorylation cycle of Cyanothece was similar to that of Synechococcus under diurnal cycles. However, under continuous light, the cycle time was shorter (11 h), in agreement with physiological and gene expression studies. Interestingly, the ATP/ADP ratio also oscillates with an 11 h period, peaking concomitantly with the respiratory burst. We propose a mathematical model with C/N ratio as a probable signal regulating the clock in continuous light and emphasize the existence of a single timing mechanism regardless of the cycle time.     

The identification of similarities between biological networks: application to the metabolome and interactome

The increasing interest in systems biology has resulted in extensive experimental data describing networks of interactions (or associations) between molecules in metabolism, protein-protein interactions and gene regulation. Comparative analysis of these networks is central to understanding biological systems. We report a novel method (PHUNKEE: Pairing subgrapHs Using NetworK Environment Equivalence) by which similar subgraphs in a pair of networks can be identified. Like other methods, PHUNKEE explicitly considers the graphical form of the data and allows for gaps. However, it is novel in that it includes information about the context of the subgraph within the adjacent network. We also explore a new approach to quantifying the statistical significance of matching subgraphs. We report similar subgraphs in metabolic pathways and in protein-protein interaction networks. The most similar metabolic subgraphs were generally found to occur in processes central to all life, such as purine, pyrimidine and amino acid metabolism. The most similar pairs of subgraphs found in the protein-protein interaction networks of Drosophila melanogaster and Saccharomyces cerevisiae also include central processes such as cell division but, interestingly, also include protein sub-networks involved in pre-mRNA processing. The inclusion of network context information in the comparison of protein interaction networks increased the number of similar subgraphs found consisting of proteins involved in the same functional process. This could have implications for the prediction of protein function.     

Systemic approaches to biodegradation

Biodegradation, the ability of microorganisms to remove complex chemicals from the environment, is a multifaceted process in which many biotic and abiotic factors are implicated. The recent accumulation of knowledge about the biochemistry and genetics of the biodegradation process, and its categorization and formalization in structured databases, has recently opened the door to systems biology approaches, where the interactions of the involved parts are the main subject of study, and the system is analysed as a whole. The global analysis of the biodegradation metabolic network is beginning to produce knowledge about its structure, behaviour and evolution, such as its free-scale structure or its intrinsic robustness. Moreover, these approaches are also developing into useful tools such as predictors for compounds' degradability or the assisted design of artificial pathways. However, it is the environmental application of high-throughput technologies from the genomics, metagenomics, proteomics and metabolomics that harbours the most promising opportunities to understand the biodegradation process, and at the same time poses tremendous challenges from the data management and data mining point of view.