The Effects of Genetic Background for Diurnal Preference on Sleep Development in Early Childhood

Purpose: No previous research has examined the impact of the genetic background of diurnal preference on children's sleep. Here, we examined the effects of genetic risk score for the liability of diurnal preference on sleep development in early childhood in two population-based cohorts from Finland.Participants and Methods: The primary sample (CHILD-SLEEP, CS) comprised 1420 infants (695 girls), and the replication sample (FinnBrain, FB; 962 girls) 2063 infants. Parent-reported sleep duration, sleep-onset latency and bedtime were assessed at three, eight, 18 and 24 months in CS, and at six, 12 and 24 months in FB. Actigraphy-based sleep latency and efficiency were measured in CS in 365 infants at eight months (168 girls), and in 197 infants at 24 months (82 girls). Mean standard scores for each sleep domain were calculated in both samples. Polygenic risk scores (PRS) were used to quantitate the genetic risk for eveningness (PRSBestFit) and momingness (PRS10kBest).Results: PRSBestFit associated with longer sleep-onset latency and later bedtime, and PRS10kBest related to shorter sleep-onset latency in CS. The link between genetic risk for diurnal preference and sleep-onset latency was replicated in FB, and meta-analysis resulted in associations (P<0.0005) with both PRS-values (PRSBestFit: Z=3.55; and PRS10kBest: Z= -3.68). Finally, PRSBestFit was related to actigraphy-based lower sleep efficiency and longer sleep latency at eight months.Conclusion: Genetic liability to diurnal preference for eveningness relates to longer sleeponset during the first two years of life, and to objectively measured lowered sleep efficiency. These findings enhance our understanding on the biological factors affecting sleep development, and contribute to clarify the physiological sleep architecture in early childhood

Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

<p>Abstract</p> <p>Background</p> <p>While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species.</p> <p>Results</p> <p>We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (<it>MLH1</it>, <it>PMS2</it>, <it>EPHB4 </it>) and could confirm more than 73% of them based on evidence in the literature.</p> <p>Conclusions</p> <p>The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.</p

Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

Sleep spindles are discrete, intermittent patterns of brain activity observed in human electroencephalographic data. Increasingly, these oscillations are of biological and clinical interest because of their role in development, learning and neurological disorders. We used an Internet interface to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects

Democratizing production through open source knowledge: from open software to open hardware

The commercial success of open source software, along with a broader socio-cultural shift towards participation in media and cultural production, have inspired attempts to extend and expand open source practices. These include expansions from software into general culture through 'Free Culture' movements and, more recently, expansions from software into hardware and design. This article provides a critical perspective on the democratic potential of these broader 'open' contribution structures by examining how open source contributions to both software and hardware increase the opportunities for democratic participation in production, governance and knowledge exchange. By analysing attempts to 'open source' the sharing of hardware designs, it also notes the limitations of this democratization. The insights developed in the article nuance the relationship between open source cultures and commercial and market structures, identifying how the generative opportunities created by certain aspects of open source contribution structures increase the potential for democratizing production of communication tools, but also how incongruities across different open-source cultures and communities of practice limit the democratic potential of these processes