Summary The discovery of hypocretins (orexins) and their causal implication in narcolepsy is the most important advance in sleep research and sleep medicine since the discovery of rapid eye movement ...sleep. Narcolepsy with cataplexy is caused by hypocretin deficiency owing to destruction of most of the hypocretin-producing neurons in the hypothalamus. Ablation of hypocretin or hypocretin receptors also leads to narcolepsy phenotypes in animal models. Although the exact mechanism of hypocretin deficiency is unknown, evidence from the past 20 years strongly favours an immune-mediated or autoimmune attack, targeting specifically hypocretin neurons in genetically predisposed individuals. These neurons form an extensive network of projections throughout the brain and show activity linked to motivational behaviours. The hypothesis that a targeted immune-mediated or autoimmune attack causes the specific degeneration of hypocretin neurons arose mainly through the discovery of genetic associations, first with the HLA-DQB1*06:02 allele and then with the T-cell receptor α locus. Guided by these genetic findings and now awaiting experimental testing are models of the possible immune mechanisms by which a specific and localised brain cell population could become targeted by T-cell subsets. Great hopes for the identification of new targets for therapeutic intervention in narcolepsy also reside in the development of patient-derived induced pluripotent stem cell systems.
Diagnosis of sleep-disordered breathing requires overnight recordings, such as polygraphy or polysomnography. Considering the cost and low availability of these procedures, preselection of patients ...at high risk is recommended. We aimed to develop a screening tool allowing identification of individuals at risk of sleep-disordered breathing.
We used the participants from the population-based HypnoLaus cohort in Lausanne, Switzerland, who had a clinical assessment and polysomnography at home, to build a clinical score (the NoSAS score) using multiple factor analysis and logistic regression to identify people likely to have clinically significant sleep-disordered breathing. The NoSAS score was externally validated in an independent sleep cohort (EPISONO). We compared its performance to existing screening scores (STOP-Bang and Berlin scores).
We used the 2121 participants from the HypnoLaus cohort who were assessed between Sept 1, 2009, and June 30, 2013. The NoSAS score, which ranges from 0 to 17, allocates 4 points for having a neck circumference of more than 40 cm, 3 points for having a body-mass index of 25 kg/m(2) to less than 30 kg/m(2) or 5 points for having a body-mass index of 30 kg/m(2) or more, 2 points for snoring, 4 points for being older than 55 years of age, and 2 points for being male. Using a threshold of 8 points or more, the NoSAS score identified individuals at risk of clinically significant sleep-disordered breathing, with an area under the curve (AUC) of 0·74 (95% CI 0·72-0·76). It showed an even higher performance in the EPISONO cohort, with an AUC of 0·81 (0·77-0·85). The NoSAS score performed significantly better than did the STOP-Bang (AUC 0·67 95% CI 0·65-0·69; p<0·0001) and Berlin (0·63 0·61-0·66; p<0·0001) scores.
The NoSAS score is a simple, efficient, and easy to implement score enabling identification of individuals at risk of sleep-disordered breathing. Because of its high discrimination power, the NoSAS score can help clinicians to decide which patients to further investigate with a nocturnal recording.
Faculty of Biology and Medicine of the University of Lausanne, Lausanne University Hospital, Swiss National Science Foundation, Leenaards Foundation, GlaxoSmithKline, and Vaud Pulmonary League.
Abstract Sleep disorders commonly involve genetic susceptibility, environmental effects, and interactions between these factors. The heritability of sleep patterns has been shown in studies of ...monozygotic twins, and sleep electroencephalogram patterns offer a unique genetic fingerprint which may assist in the identification of genes involved in the regulation of sleep. Genetic factors are also thought to play a role in sleep disorders; narcolepsy is a disabling sleep condition and research has revealed the complexity of underlying genetic and environmental influences in the development of this disorder. An understanding of sleep regulation at the molecular level is essential in the identification of new targets for the treatment of sleep disorders, and genome-wide association studies for both normal sleep and sleep disorders may shed new light on the molecular architecture of mechanisms regulating these behaviours.
Loss of muscle tone triggered by emotions is called cataplexy and is the pathognomonic symptom of narcolepsy, which is caused by hypocretin deficiency. Cataplexy is classically considered to be an ...abnormal manifestation of REM sleep and is treated by selective serotonin (5HT) reuptake inhibitors. Here we show that deleting the 5HT transporter in hypocretin knockout mice suppressed cataplexy while dramatically increasing REM sleep. Additionally, double knockout mice showed a significant deficit in the buildup of sleep need. Deleting one allele of the 5HT transporter in hypocretin knockout mice strongly increased EEG theta power during REM sleep and theta and gamma powers during wakefulness. Deleting hypocretin receptors in the dorsal raphe neurons of adult mice did not induce cataplexy but consolidated REM sleep. Our results indicate that cataplexy and REM sleep are regulated by different mechanisms and both states and sleep need are regulated by the hypocretinergic input into 5HT neurons.
One of the important issues related to road safety is the continuous monitoring of road conditions with the aim of preserving and maintaining the quality of roads. Considering the increasing use of ...smart phones, a practical solution based on smart phone sensors is proposed in this article to control the safety status of roads. This solution includes the implementation of a centralized traffic information system that monitors the dynamic behavior of vehicles while moving on the roads and collects trip-related information for further processing. To evaluate the system, a 42-kilometer route on a highway in Iran was monitored. A total of 7 parameters comprising speed, three-dimensional instantaneous acceleration and acceleration changes were examined. An event classification approach was adopted to detect accident-black spots based on the pattern of those parameter changes. The classified dataset was trained and modeled using two types of neural network models namely, Multilayer Perceptron (MLP) and Radial Basis Function (RBF). These two neural networks models were trained, tested and validated using MATLAB software and the collected dataset. The predicted error rate was obtained for 700 samples for each output. The mean square error index for RBF and MLP neural networks was obtained as 0.0066 and 0.1399, respectively, indicating acceptable prediction accuracy.
Wakefulness is accompanied by experience-dependent synaptic plasticity and an increase in activity-regulated gene transcription. Wake-induced genes are certainly markers of neuronal activity and may ...also directly regulate the duration of and need for sleep. We stimulated murine cortical cultures with the neuromodulatory signals that are known to control wakefulness in the brain and found that norepinephrine alone or a mixture of these neuromodulators induced activity-regulated gene transcription. Pharmacological inhibition of the various signaling pathways involved in the regulation of gene expression indicated that the extracellular signal-regulated kinase (ERK) pathway is the principal one mediating the effects of waking neuromodulators on gene expression. In mice, ERK phosphorylation in the cortex increased and decreased with wakefulness and sleep. Whole-body or cortical neuron-specific deletion of Erk1 or Erk2 significantly increased the duration of wakefulness in mice, and pharmacological inhibition of ERK phosphorylation decreased sleep duration and increased the duration of wakefulness bouts. Thus, this signaling pathway, which is highly conserved from Drosophila to mammals, is a key pathway that links waking experience-induced neuronal gene expression to sleep duration and quality.
Objective
Periodic limb movements during sleep (PLMS) are sleep phenomena characterized by periodic episodes of repetitive stereotyped limb movements. The aim of this study was to describe the ...prevalence and determinants of PLMS in a middle to older aged general population.
Methods
Data from 2,162 subjects (51.2% women, mean age = 58.4 ± 11.1 years) participating in a population‐based study (HypnoLaus, Lausanne, Switzerland) were collected. Assessments included laboratory tests, sociodemographic data, personal and treatment history, and full polysomnography at home. PLMS index (PLMSI) was determined, and PLMSI > 15/h was considered as significant.
Results
Prevalence of PLMSI > 15/h was 28.6% (31.3% in men, 26% in women). Compared to subjects with PLMSI ≤ 15/h, subjects with PLMSI > 15/h were older (p < 0.001), were predominantly males (p = 0.007), had a higher proportion of restless legs syndrome (RLS; p < 0.001), had a higher body mass index (p = 0.001), and had a lower mean glomerular filtration rate (p < 0.001). Subjects with PLMSI > 15/h also had a higher prevalence of diabetes, hypertension, and beta‐blocker or hypnotic treatments. The prevalence of antidepressant use was higher, but not statistically significant (p = 0.07). Single nucleotide polymorphisms (SNPs) within BTBD9 (rs3923809), TOX3 (rs3104788), and MEIS1 (rs2300478) genes were significantly associated with PLSMI > 15/h. Conversely, mean hemoglobin and ferritin levels were similar in both groups. In the multivariate analysis, age, male gender, antidepressant intake, RLS, and rs3923809, rs3104788, and rs2300478 SNPs were independently associated with PLMSI > 15/h.
Interpretation
PLMS are highly prevalent in our middle‐aged European population. Age, male gender, RLS, antidepressant treatment, and specific BTBD9, TOX3, and MEIS1 SNP distribution are independent predictors of PLMSI > 15/h. ANN NEUROL 2016;79:464–474
The final sections of main access roads to the cities require especial attention as the frequency of accidents in these road sections are considerably higher than other parts of interurban roads. ...These road sections operate as an interface between the rural roads and urban streets. The previous researches available on this subject are limited and they have also mainly focused on a narrow range of factors contributing to the accidents in these areas. The main contribution of this research is to consider a relatively comprehensive range of potential factors , and to examine their impacts through the development and comparison of both conventional probabilistic models and Artificial Neural Network (ANN) models. For this purpose, information related to the main access roads of three major Iranian cities were collected. This information consisted of accident frequency data together with the field observations of traffic characteristics, road-way conditions and roadside features of these roads. Various ANN and probabilistic models were developed. The frequency of accidents, i.e. fatal, injured, or damaged accidents, was considered as the output of the developed models. The results indicated that a hybrid of ANN models, each comprised of 10 input variables representing traffic, roadway and roadside conditions, outperformed several probabilistic models, i.e. Poisson, Negative binomial, Zero-truncated Poisson, and Zero-truncated Negative Binomial models, also developed under similar conditions in this study. Moreo-ver, effective roadway width, roadway lighting condition, the standard deviation of vehicles speed, percentage of drivers violating the speed limit, average annual daily traffic, percentage of heavy goods vehicles, the density of road-side commercial and industrial landuses, the density of median U-turns, the density of local access roads, and the effective width of the left-side shoulder were identified as the most effective factors contributing to the accidents in these areas. The developed ANN model can be used as a tool to predict accident rates in these road sections, and to estimate a potential reduction in the accident rates, following any improvements in the major factors contributing to the traffic accidents in these areas.
Prioritization of pathways to perform asphalt pavement operations has always been one of the most important concerns for municipalities, for which, currently there is no specific planning and ...pattern. In the present study, using (Unmanned Aerial Vehicle) UAV images, a land cover map of the case study was prepared. For this purpose, the accuracy of various object-based classification methods including the Bayes method, the Support Vector Machine (SVM), the K nearest neighbor (KNN), the Decision tree (DT), and the Random tree (RT) was investigated. Findings of the study showed that by increasing heterogeneity in the composition of the studied phenomenon in the image, different classification algorithms offer results different from each other. The obtained results of the accuracy evaluation of classification methods indicate that the SVM method with 80% kappa coefficient and 89% overall accuracy had the best performance compared to other methods. As a result, built-up land covers, bare land, vegetation cover, and paved roads were separated using this method. Then, the exact boundary of pathways was prepared using Google Earth images, and then, using the land-use map prepared from the case study, the roads were divided into two categories: paved and unpaved. To determine the prioritization of unpaved roads for applying asphalt, the proportion of built-up lands (BUL) to bare (non-built-up) lands (BL) was used in each path. Based on the obtained results, 1% of the roads in the case study was placed on a very high level of asphalt, and then 9%, 3%, 49%, 38%, were placed on a high priority to low priority, respectively.
Prolonged wakefulness leads to a homeostatic response manifested in increased amplitude and number of electroencephalogram (EEG) slow waves during recovery sleep. Cortical networks show a slow ...oscillation when the excitatory inputs are reduced (during slow wave sleep, anesthesia), or absent (in vitro preparations). It was recently shown that a homeostatic response to electrical stimulation can be induced in cortical cultures. Here we used cortical cultures grown on microelectrode arrays and stimulated them with a cocktail of waking neuromodulators. We found that recovery from stimulation resulted in a dose-dependent homeostatic response. Specifically, the inter-burst intervals decreased, the burst duration increased, the network showed higher cross-correlation and strong phasic synchronized burst activity. Spectral power below <1.75 Hz significantly increased and the increase was related to steeper slopes of bursts. Computer simulation suggested that a small number of clustered neurons could potently drive the behavior of the network both at baseline and during recovery. Thus, this in vitro model appears valuable for dissecting network mechanisms of sleep homeostasis.
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