Sleep fragmentation affects glymphatic system through the different expression of AQP4 in wild type and 5xFAD mouse models.

Alzheimer's disease (AD) is characterized by genetic and multifactorial risk factors. Many studies correlate AD to sleep disorders. In this study, we performed and validated a mouse model of AD and sleep fragmentation, which properly mimics a real condition of intermittent awakening. We noticed that sleep fragmentation induces a general acceleration of AD progression in 5xFAD mice, while in wild type mice it affects cognitive behaviors in particular learning and memory. Both these events may be correlated to aquaporin-4 (AQP4) modulation, a crucial player of the glymphatic system activity. In particular, sleep fragmentation differentially affects aquaporin-4 channel (AQP4) expression according to the stage of the disease, with an up-regulation in younger animals, while such change cannot be detected in older ones. Moreover, in wild type mice sleep fragmentation affects cognitive behaviors, in particular learning and memory, by compromising the glymphatic system through the decrease of AQP4. Nevertheless, an in-depth study is needed to better understand the mechanism by which AQP4 is modulated and whether it could be considered a risk factor for the disease development in wild type mice. If our hypotheses are going to be confirmed, AQP4 modulation may represent the convergence point between AD and sleep disorder pathogenic mechanisms.

Assessing REM Sleep Behaviour Disorder: From Machine Learning Classification to the Definition of a Continuous Dissociation Index.

Objectives: Rapid Eye Movement Sleep Behaviour Disorder (RBD) is regarded as a prodrome of neurodegeneration, with a high conversion rate to α-synucleinopathies such as Parkinson's Disease (PD). The clinical diagnosis of RBD co-exists with evidence of REM Sleep Without Atonia (RSWA), a parasomnia that features loss of physiological muscular atonia during REM sleep. The objectives of this study are to implement an automatic detection of RSWA from polysomnographic traces, and to propose a continuous index (the Dissociation Index) to assess the level of dissociation between REM sleep stage and atonia. This is performed using Euclidean distance in proper vector spaces. Each subject is assigned a dissociation degree based on their distance from a reference, encompassing healthy subjects and clinically diagnosed RBD patients at the two extremes. Methods: Machine Learning models were employed to perform automatic identification of patients with RSWA through clinical polysomnographic scores, together with variables derived from electromyography. Proper distance metrics are proposed and tested to achieve a dissociation measure. Results: The method proved efficient in classifying RSWA vs. not-RSWA subjects, achieving an overall accuracy, sensitivity and precision of 87%, 93% and 87.5%, respectively. On its part, the Dissociation Index proved to be promising in measuring the impairment level of patients. Conclusions: The proposed method moves a step forward in the direction of automatically identifying REM sleep disorders and evaluating the impairment degree. We believe that this index may be correlated with the patients' neurodegeneration process; this assumption will undergo a robust clinical validation process involving healthy, RSWA, RBD and PD subjects.

Sleep on a high heat capacity mattress increases conductive body heat loss and slow wave sleep.

Environmental temperature can strongly affect sleep. The habitual sleep phase is usually located between evening decline and morning rise of the circadian rhythm of core body temperature (CBT). However, the thermophysiological mechanisms promoting or disturbing sleep are not yet fully understood. The purpose of this study was to examine the effects of a high heat capacity mattress (HHCM) on CBT, skin temperatures and sleep in comparison to a conventional low heat capacity mattress (LHCM). Based on the higher heat capacity of HHCM an increase in conductive body heat loss enhances the nocturnal decline in CBT can be expected. Based on previous findings this may then be accompanied by an increase in slow wave sleep (SWS). The mattresses were studied in a randomized single-blind crossover design in fifteen healthy young men (Age: 26.9±2.1yr, BMI: 22.2±0.4kg/m2) by overnight in laboratory standard video-polysomnography in a temperature stabilized setting. CBT, room temperature, and skin and mattress surface temperatures were continuously recorded in order to get information about inner and outer body heat flow. Additionally, subjective sleep quality was estimated by visual analogue scale. In comparison to LHCM sleep on HHCM exhibited a selective increase in SWS (16%, p<0.05), increased subjective sleep quality and sleep stability [reduced cyclic alternating pattern (CAP) rate; 5.3%, p<0.01]. Additionally, analyses of the sleep stages showed in the second part of the night a significant increase in SWS and a decrease in REMS. In addition, HHCM induced a greater reduction in CBT (maximally by -0.28°C), reduced the increase in proximal skin temperatures on the back (PROBA; maximally by -0.98°C), and delayed the increase in mattress surface temperature (maximal difference LHCM-HHCM: 6.12°C). Thus, the CBT reduction can be explained by an increase in conductive heat loss to the mattress via proximal back skin regions. Regression analysis identified PROBA as the critical variable to predict inner conductive heat transfer from core to shell and SWS. In conclusion, the study expands the previous findings that a steeper nocturnal decline in CBT increases SWS and subjective sleep quality, whereas inner conductive heat transfer could be identified as the crucial thermophysiological variable, and not CBT.