Improving adjustment to daylight saving time transitions with light.

Daylight saving time (DST) is currently utilized in many countries with the rationale that it enhances the alignment between daylight hours and activity peaks in the population. The act of transitioning into and out of DST introduces disruptions to the circadian rhythm, thereby impacting sleep and overall health. Despite the substantial number of individuals affected, the consequences of this circadian disruption have often been overlooked. Here, we employ a mathematical model of the human circadian pacemaker to elucidate how the biological clock interacts with daytime and evening exposures to both natural and electrical light. This interaction plays a crucial role in determining the adaptation to the 1 hour time zone shift imposed by the transition to or from DST. In global discussions about DST, there is a prevailing assumption that individuals easily adjust to DST transitions despite a few studies indicating that the human circadian system requires several days to fully adjust to a DST transition. Our study highlights that evening light exposure changes can be the main driving force for re-entrainment, with chronobiological models predicting that people with longer intrinsic period (i.e. later chronotype) entrain more slowly to transitions to or from DST as compared to people with a shorter intrinsic period (earlier chronotype). Moreover, the model forecasts large inter-individual differences in the adaptation speed, in particular during the spring transition. The predictions derived from our model offer circadian biology-based recommendations for light exposure strategies that facilitate a more rapid adaptation to DST-related transitions or travel across a single time zone. As such, our study contributes valuable insights to the ongoing discourse on DST and its implications for human circadian rhythms.

Comparing Sleep Quality, Duration, and Efficiency Among Low-Income Community-Dwelling Older Adults With and Without Physical Disabilities.

PURPOSE: Physical disabilities may exacerbate the natural decline in sleep quality that occurs with aging. In the current study, we assessed sleep quality and medicinal sleep aid use among 87 community-dwelling older adults with (n = 24) and without (n = 63) physical disabilities. METHOD: Sleep quality, duration, and efficiency were assessed subjectively with the Pittsburgh Sleep Quality Index. Sleep duration and efficiency were objectively measured with actigraphy. Participants self-reported medicinal sleep aid use. RESULTS: Significant group differences were observed in sleep duration measured objectively (p = 0.01) and subjectively (p = 0.04). No other group differences were observed for sleep factors (p > 0.05) or medicinal sleep aid use (p = 0.41). CONCLUSION: Findings show that physical disability may be a factor in sleep duration; however, physical disability was not found to be associated with worsened sleep perception or greater reliance on medicinal sleep aids. Future research should consider longer objective actigraphy assessment windows and explore potential subgroup differences in sex and race/ethnicity. [Journal of Gerontological Nursing, 50(7), 12-18.].

Accelerometer-Measured Daily Behaviors That Mediate the Association Between Refractive Status and Depressive Disorders.

Purpose: To identify the accelerometer-measured daily behaviors that mediate the association of refractive status with depressive disorders and enhance the understanding of behavioral differences in depression. Methods: Participants with baseline mean spherical equivalent (MSE) and 7-day accelerometer measurements from the UK Biobank were included in this cohort study. Refractive status was categorized as hyperopia and non-hyperopia. Four daily behaviors, including moderate to vigorous intensity physical activity (MVPA), light physical activity (LPA), sedentary, and sleep were recorded between 2013 and 2015. We also assessed 24-hour behavior patterns. Depression cases were defined through both questionnaires and hospital records over 10 years of follow-up. Results: Among 20,607 individuals, every 0.5-diopter increase in MSE was associated with a 6% higher risk of depressive disorders, with hyperopia participants at a higher risk than non-hyperopia participants (odds ratio, 1.14; 95% confidence interval, 1.05-1.23; P = 0.001). MVPA and sleep time significantly correlated with depressive disorders, with odds ratios of 0.79 and 1.14 (P < 0.05). MSE showed significant correlations with all four behaviors. The effects of MVPA and sleep duration on MSE and depressive disorders varied throughout the day. Mediation analyses showed that MVPA and sleep partially mediated the relationship between MSE and depressive disorders, with 35.2% of the association between moderate to high hyperopia and depression mediated by MVPA. Conclusions: Physical activity and sleep significantly mediate the relationship between MSE and depressive disorders. Translational Relevance: The mediation effect of MVPA highlights its therapeutic potential in reducing the risk of depression among individuals with moderate to severe hyperopia. Interventions aimed at increasing daytime MVPA and decreasing daytime sleep could enhance mental health in this vulnerable group.

Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram.

BACKGROUND: Sedatives are commonly used to promote sleep in intensive care unit patients. However, it is not clear whether sedation-induced states are similar to the biological sleep. We explored if sedative-induced states resemble biological sleep using multichannel electroencephalogram (EEG) recordings. METHODS: Multichannel EEG datasets from two different sources were used in this study: (1) sedation dataset consisting of 102 healthy volunteers receiving propofol (N = 36), sevoflurane (N = 36), or dexmedetomidine (N = 30), and (2) publicly available sleep EEG dataset (N = 994). Forty-four quantitative time, frequency and entropy features were extracted from EEG recordings and were used to train the machine learning algorithms on sleep dataset to predict sleep stages in the sedation dataset. The predicted sleep states were then compared with the Modified Observer's Assessment of Alertness/ Sedation (MOAA/S) scores. RESULTS: The performance of the model was poor (AUC = 0.55-0.58) in differentiating sleep stages during propofol and sevoflurane sedation. In the case of dexmedetomidine, the AUC of the model increased in a sedation-dependent manner with NREM stages 2 and 3 highly correlating with deep sedation state reaching an AUC of 0.80. CONCLUSIONS: We addressed an important clinical question to identify biological sleep promoting sedatives using EEG signals. We demonstrate that propofol and sevoflurane do not promote EEG patterns resembling natural sleep while dexmedetomidine promotes states resembling NREM stages 2 and 3 sleep, based on current sleep staging standards.

Sleep-wake changes and incident depressive symptoms in midlife women.

Our study aimed to investigate the relationship between sleep-wake changes and depressive symptoms events among midlife women. We enrolled 1579 women aged 44-56 years who had no clinically relevant depressive symptoms at baseline. Depressive symptoms were assessed at each visit using the Center for Epidemiologic Studies Depression scale. At the third and fourth follow-up visits, women reported their sleep habits. The sleep midpoint was defined as the time to fall asleep plus one-half of the sleep duration. Sleep-wake changes were determined by the difference in the midpoint of sleep between the third and fourth visits, which were 1 year apart. The median follow-up time was 7 years (range 1-7 years). Cox proportional hazard models were fitted to calculate hazard ratios and 95% confidence intervals for the incidence of depressive symptoms associated with sleep-wake changes. After adjusting for potential confounding factors, the hazard ratio (95% confidence interval) of depressive symptoms for severe sleep midpoint changes was 1.51 (1.12, 2.05) compared with mild sleep midpoint changes. This relationship remained statistically significant and changed little when additionally controlling for sleep duration, sleep quality, insomnia symptoms, use of sleep medications, use of nervous medications, glucose, insulin, lipids, dietary energy intake, and C-reactive protein. Our findings indicate that exposure to long-term severe sleep-wake changes increases the risk of depressive symptoms in midlife women.

Reallocating just 10 min to moderate-to-vigorous physical activity from other components of 24-hour movement behaviors improves cardiovascular health in adults.

BACKGROUND: As components of a 24-hour day, sedentary behavior (SB), physical activity (PA), and sleep are all independently linked to cardiovascular health (CVH). However, insufficient understanding of components' mutual exclusion limits the exploration of the associations between all movement behaviors and health outcomes. The aim of this study was to employ compositional data analysis (CoDA) approach to investigate the associations between 24-hour movement behaviors and overall CVH. METHODS: Data from 581 participants, including 230 women, were collected from the 2005-2006 wave of the US National Health and Nutrition Examination Survey (NHANES). This dataset included information on the duration of SB and PA, derived from ActiGraph accelerometers, as well as self-reported sleep duration. The assessment of CVH was conducted in accordance with the criteria outlined in Life's Simple 7, encompassing the evaluation of both health behaviors and health factors. Compositional linear regression was utilized to examine the cross-sectional associations of 24-hour movement behaviors and each component with CVH score. Furthermore, the study predicted the potential differences in CVH score that would occur by reallocating 10 to 60 min among different movement behaviors. RESULTS: A significant association was observed between 24-hour movement behaviors and overall CVH (p < 0.001) after adjusting for potential confounders. Substituting moderate-to-vigorous physical activity (MVPA) for other components was strongly associated with favorable differences in CVH score (p < 0.05), whether in one-for-one reallocations or one-for-remaining reallocations. Allocating time away from MVPA consistently resulted in larger negative differences in CVH score (p < 0.05). For instance, replacing 10 min of light physical activity (LPA) with MVPA was related to an increase of 0.21 in CVH score (95% confidence interval (95% CI) 0.11 to 0.31). Conversely, when the same duration of MVPA was replaced with LPA, CVH score decreased by 0.67 (95% CI -0.99 to -0.35). No such significance was discovered for all duration reallocations involving only LPA, SB, and sleep (p > 0.05). CONCLUSIONS: MVPA seems to be as a pivotal determinant for enhancing CVH among general adult population, relative to other movement behaviors. Consequently, optimization of MVPA duration is an essential element in promoting overall health and well-being.

Restricted linear association between night sleep duration and diabetes risk in middle-aged and older adults: a 7-year follow-up analysis from the China health and retirement longitudinal study.

Background: A rapid increase in the prevalence of diabetes is an urgent public health concern among older adults, especially in developing countries such as China. Despite several studies on lifestyle factors causing diabetes, sleep, a key contributor, is understudied. Our study investigates the association between night sleep duration and diabetes onset over a 7-year follow-up to fill information gaps. Method: A population-based cohort study with 5437 respondents used 2011-2018 China Health and Retirement Longitudinal Study data. Using self-reported night sleep duration from the 2011 baseline survey, information on new-onset diabetes was collected in follow-up surveys. Baseline characteristics of participants with vs. without new-onset diabetes were compared using Chi-square and Mann-Whitney U tests. Multivariable Cox regression models estimated the independent relationship between night sleep and new-onset diabetes. The addictive Cox regression model approach and piece-wise regression described the nonlinear relationship between night sleep and new-onset diabetes. Subgroup analysis was also performed by age, gender, body measurement index, dyslipidemia, drinking status, smoking, hypertension, and afternoon napping duration. Result: 549 respondents acquired diabetes during a median follow-up of 84 months. After controlling for confounders, night sleep duration was substantially linked with new-onset diabetes in the multivariable Cox regression model. The risk of diabetes is lower for respondents who sleep longer than 5 hours, except for those who sleep over 8 hours [5.1-6h Hazard ratios (HR) [95% confidence intervals (CI)] = 0.71 (0.55, 0.91); 6.1-7h HR = 0.69 (0.53, 0.89); 7.1-8h HR = 0.58 (0.45, 0.76)]. Nonlinear connections were delineated by significant inflection points at 3.5 and 7.5 hours, with a negative correlation observed only between these thresholds. With one hour more night sleep, the risk of diabetes drops 15%. BMI and dyslipidemia were identified as modifiers when only consider the stand linear effect of sleep duration on diabetes. Conclusion: This study establishes a robust association between night sleep and new-onset diabetes in middle-aged and older Chinese individuals within the 3.5-7.5-hour range, offering a foundation for early glycemic management interventions in this demographic. The findings also underscore the pivotal role of moderate night sleep in preventing diabetes, marking a crucial juncture in community medical research.

Association between bedtime and female infertility: a secondary analysis from a cross-sectional study.

Objective: To evaluate the association between bedtime and infertility and to identify the optimal bedtime for women of reproductive age. Methods: We conducted a cross-sectional study using data from 3,903 female participants in the National Health and Nutrition Examination Survey (NHANES) from 2015 to 2020. The effect of bedtime on female infertility was assessed using the binary logistic regression in different models, including crude model and adjusted models. To identify the non-linear correlation between bedtime and infertility, generalized additive models (GAM) were utilized. Subgroup analyses were conducted by age, body mass index (BMI), waist circumference, physical activity total time, marital status, smoking status, drinking status and sleep duration. Results: After adjusting for potential confounders (age, race, sleep duration, waist circumference, marital status, education, BMI, smoking status, drinking status and physical activity total time), a non-linear relationship was observed between bedtime and infertility, with the inflection point at 22:45. To the left side of the inflection point, no significant association was detected. However, to the right of it, bedtime was positively related to the infertility (OR: 1.22; 95% CI: 1.06 to 1.39; P = 0.0049). Subgroup analyses showed that late sleepers with higher BMI were more prone to infertility than those with a lower BMI (BMI: 25-30 kg/m2: OR: 1.26; 95% CI: 1.06 to 1.51; P = 0.0136; BMI ≥ 30 kg/m²: OR: 1.21, 95% CI: 1.09 to 1.34; P = 0.0014). Conclusion: Bedtime was non-linearly associated with infertility, which may provide guidance for sleep behavior in women of childbearing age.

Moderation by better sleep of the association among childhood maltreatment, neuroticism, and depressive symptoms in the adult volunteers: A moderated mediation model.

BACKGROUND: Previously, we demonstrated that childhood maltreatment could worsen depressive symptoms through neuroticism. On the one hand, some studies report that sleep disturbances are related to childhood maltreatment and neuroticism and worsens depressive symptoms. But, to our knowledge, no reports to date have shown the interrelatedness between childhood maltreatment, neuroticism, and depressive symptoms, and sleep disturbance in the one model. We hypothesized that sleep disturbance enhances the influence of maltreatment victimization in childhood or neuroticism on adulthood depressive symptoms and the mediation influence of neuroticism between maltreatment victimization in childhood and adulthood depressive symptoms. SUBJECTS AND METHODS: Total 584 Japanese volunteer adults recruited through convenience sampling from 4/2017 to 4/2018 were assessed regarding their characteristics of demographics, history of childhood maltreatment, sleep disturbance, neuroticism, and depressive symptoms with questionnaires self-administered. Survey data were analyzed using simple moderation models and a moderating mediation model. RESULTS: The interaction of sleep disturbance with childhood maltreatment or neuroticism on depressive symptoms was significantly positive. Furthermore, the moderating effect of sleep disturbance on the indirect effect of childhood maltreatment to depressive symptoms through neuroticism was significantly positive. LIMITATIONS: Because this was a cross-sectional study, a causal relationship could not be confirmed. CONCLUSIONS: Our findings indicate that individuals with milder sleep disturbance experience fewer depressive symptoms attributable to neuroticism and childhood maltreatment. Additionally, people with less sleep disturbance have fewer depressive symptoms arising from neuroticism owing to childhood maltreatment. Therefore, improvement of sleep disturbance will buffer the aggravating effect of childhood maltreatment, neuroticism caused by various factors, and neuroticism resulting from childhood maltreatment on depressive symptoms.

Cross-sectional study assessing sleep behavior and musculoskeletal symptoms in elite junior badminton athletes.

Sleep inadequacy has previously been associated with increased risk of injury and reduced performance. It is unclear if sleep disorders are associated with musculoskeletal symptoms, which may be a predictor of serious injury and affect performance. The aim was therefore to assess sleep behavior in elite junior badminton players and its association to musculoskeletal symptoms. In 2018, players at the World Junior Badminton Championship completed the Athlete Sleep Behavior Questionnaire and a modified version of the World Olympic Association Musculoskeletal Health Questionnaire. Participants were categorized with poor or moderate/good sleep behavior as the independent variable. Musculoskeletal symptoms were the primary outcome and was categorized using yes/no questions. Relevant musculoskeletal symptoms were defined as pain higher than 30 mm Numeric Rating Scale pain score or more than 30 minutes of joint stiffness a day. Group comparison was performed using chi-square analysis and logistic regression for primary outcome adjusted for age, sex, ethnicity, previous injury, training load, and resting days. Of the 153 participants, 28% reported poor sleep scores. There was no difference between poor and moderate/good sleep score concerning demographic variables such as sex, age, ethnicity, previous injury, training load, and resting days. There were 27% with current musculoskeletal symptoms but with no difference in groups between poor and moderate/good sleep score (P = .376). This yielded an adjusted odds ratio of 1.23 (95% confidence intervals 0.52; 2.90). Twenty-eight percent of the participants reported poor sleep behavior. Twenty-seven percent experienced current musculoskeletal symptoms. We found no statistical differences in reported musculoskeletal symptoms when comparing athletes with poor sleep behavior to athletes with moderate/good sleep behavior.

A method for calculating vector forces at human-mattress interface during sleeping positions utilizing image registration.

The vector forces at the human-mattress interface are not only crucial for understanding the distribution of vertical and shear forces exerted on the human body during sleep but also serves as a significant input for biomechanical models of sleeping positions, whose accuracy determines the credibility of predicting musculoskeletal system loads. In this study, we introduce a novel method for calculating the interface vector forces. By recording indentations after supine and lateral positions using a vacuum mattress and 3D scanner, we utilize image registration techniques to align body pressure distribution with the mattress deformation scanning images, thereby calculating the vector force values for each unit area (36.25 mm × 36.25 mm). This method was validated through five participants attendance from two perspectives, revealing that (1) the mean summation of the vertical force components is 98.67% ± 7.21% body weight, exhibiting good consistency, and mean ratio of horizontal component force to body weight is 2.18% ± 1.77%. (2) the predicted muscle activity using the vector forces as input to the sleep position model aligns with the measured muscle activity (%MVC), with correlation coefficient over 0.7. The proposed method contributes to the vector force distribution understanding and the analysis of musculoskeletal loads during sleep, providing valuable insights for mattress design and evaluation.

The effect of perceived social support on fatigue in mothers having twin infants: the mediating role of sleep quality.

The aim of this study is to investigate the mediating role of sleep quality in the relationship between multidimensional perceived social support and fatigue among mothers of twin infants. One hundred and six (106) twin mothers participated in this cross-sectional study, who completed the Descriptive Information Form, Multidimensional Scale of Perceived Social Support, Pittsburgh Sleep Quality Index, and Checklist Individual Strength. The scale score averages of the mothers in the study are as follows: social support, 61.41 ± 23.86; fatigue, 77.64 ± 28.68; and sleep quality, 8.26 ± 2.38. According to the path model, perceived social support has a negative effect on poor sleep quality (p = .001, Beta = -0.411), and poor sleep quality has a positive effect on fatigue (p = .001, Beta = 0.335). Sleep quality also mediates the effect of multidimensional perceived social support on mothers' fatigue levels (p = .001, Beta = -0.138). The study results suggest that the perceived social support and fatigue levels of twin mothers are moderate, while their sleep quality is poor. Therefore, mothers of twin infants may benefit from increased social support to alleviate fatigue and enhance sleep quality.

Determinants of Perceived Comfort: Multi-Dimensional Thinking in Smart Bedding Design.

Sleep quality is an important issue of public concern. This study, combined with sensor application, aims to explore the determinants of perceived comfort when using smart bedding to provide empirical evidence for improving sleep quality. This study was conducted in a standard sleep laboratory in Quanzhou, China, from March to April of 2023. Perceived comfort was evaluated using the Subjective Lying Comfort Evaluation on a seven-point rating scale, and body pressure distribution was measured using a pressure sensor. Correlation analysis was employed to analyze the relationship between perceived comfort and body pressure, and multiple linear regression was used to identify the factors of perceived comfort. The results showed that body pressure was partially correlated with perceived comfort, and sleep posture significantly influenced perceived comfort. In addition, height, weight, and body mass index are common factors that influence comfort. The findings highlight the importance of optimizing the angular range of boards based on their comfort performance to adjust sleeping posture and equalize pressure distribution. Future research should consider aspects related to the special needs of different populations (such as height and weight), as well as whether users are elderly and whether they have particular diseases. The design optimization of the bed board division and mattress softness, based on traditional smart bedding, can improve comfort and its effectiveness in reducing health risks and enhancing health status.

An Inertial-Based Wearable System for Monitoring Vital Signs during Sleep.

This study explores the feasibility of a wearable system to monitor vital signs during sleep. The system incorporates five inertial measurement units (IMUs) located on the waist, the arms, and the legs. To evaluate the performance of a novel framework, twenty-three participants underwent a sleep study, and vital signs, including respiratory rate (RR) and heart rate (HR), were monitored via polysomnography (PSG). The dataset comprises individuals with varying severity of sleep-disordered breathing (SDB). Using a single IMU sensor positioned at the waist, strong correlations of more than 0.95 with the PSG-derived vital signs were obtained. Low inter-participant mean absolute errors of about 0.66 breaths/min and 1.32 beats/min were achieved, for RR and HR, respectively. The percentage of data available for analysis, representing the time coverage, was 98.3% for RR estimation and 78.3% for HR estimation. Nevertheless, the fusion of data from IMUs positioned at the arms and legs enhanced the inter-participant time coverage of HR estimation by over 15%. These findings imply that the proposed methodology can be used for vital sign monitoring during sleep, paving the way for a comprehensive understanding of sleep quality in individuals with SDB.

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms.

Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is polysomnography (PSG). A major challenge associated with this method is all the cables needed to connect the recording devices, making the examination more intrusive and usually requiring a clinical environment. This can have potential consequences on the test results and their accuracy. One simple way to assess the state of the central nervous system (CNS), a well-known indicator of sleep disorder, could be the use of a portable medical device. With this in mind, we implemented a simple model using both the RR interval (RRI) and its second derivative to accurately predict the awake and napping states of a subject using a feature classification model. For training and validation, we used a database providing measurements from nine healthy young adults (six men and three women), in which heart rate variability (HRV) associated with light-on, light-off, sleep onset and sleep offset events. Results show that using a 30 min RRI time series window suffices for this lightweight model to accurately predict whether the patient was awake or napping.

Effects of Short-Term Nighttime Carbohydrate Restriction Method on Exercise Performance and Fat Metabolism.

BACKGROUND: The sleep-low method has been proposed as a way to sleep in a low-glycogen state, increase the duration of low glycogen availability and sleep and temporarily restrict carbohydrates to improve exercise performance. However, long-term dietary restriction may induce mental stress in athletes. Therefore, if it can be shown that the effects of the sleep-low method can be achieved by restricting the carbohydrate intake at night (the nighttime carbohydrate restriction method), innovative methods could be developed to reduce weight in individuals with obesity and enhance athletes' performance with reduced stress and in a shorter duration when compared with those of previous studies. With this background, we conducted a study with the purpose of examining the intervention effects of a short-term intensive nighttime carbohydrate restriction method. METHODS: A total of 22 participants were recruited among university students participating in sports club activities. The participants were assigned at random to groups, including a nighttime carbohydrate restriction group of 11 participants (6 males, 5 females; age 22.3 ± 1.23) who started a carbohydrate-restricted diet and a group of 11 participants (5 males, 6 females; age 21.9 ± 7.9) who continued with their usual diet. The present study had a two-group parallel design. In the first week, no dietary restrictions were imposed on either group, and the participants consumed their own habitual diets. In the second week, the total amount of calories and carbohydrate intake measured in the first week were divided by seven days, and the average values were calculated. These were used as the daily calorie and carbohydrate intakes in the second week. Only the nighttime carbohydrate restriction group was prohibited from consuming carbohydrates after 4:00 p.m. During the two-week study period, all participants ran for one hour each day before breakfast at a heart rate of 65% of their maximum heart rate. RESULTS: The results obtained from young adults participating in sports showed significant differences in peak oxygen consumption (V·O2peak), work rate max, respiratory quotient (RQ), body weight and lean body mass after the intervention when compared with before the intervention in the nighttime carbohydrate restriction group (p < 0.05). CONCLUSIONS: Our findings suggest that the nighttime carbohydrate restriction method markedly improves fat metabolism even when performed for a short period. This method can be used to reduce body weight in individuals with obesity and enhance athletes' performance. However, it is important to consider the intake of nutrition other than carbohydrates.

Photobiomodulation under Electroencephalographic Controls of Sleep for Stimulation of Lymphatic Removal of Toxins from Mouse Brain.

The meningeal lymphatic vessels (MLVs) play an important role in the removal of toxins from the brain. The development of innovative technologies for the stimulation of MLV functions is a promising direction in the progress of the treatment of various brain diseases associated with MLV abnormalities, including Alzheimer's and Parkinson's diseases, brain tumors, traumatic brain injuries, and intracranial hemorrhages. Sleep is a natural state when the brain's drainage processes are most active. Therefore, stimulation of the brain's drainage and MLVs during sleep may have the most pronounced therapeutic effects. However, such commercial technologies do not currently exist. This study presents a new portable technology of transcranial photobiomodulation (tPBM) under electroencephalographic (EEG) control of sleep designed to photo-stimulate removal of toxins (e.g., soluble amyloid beta (Aß)) from the brain of aged BALB/c mice with the ability to compare the therapeutic effectiveness of different optical resources. The technology can be used in the natural condition of a home cage without anesthesia, maintaining the motor activity of mice. These data open up new prospects for developing non-invasive and clinically promising photo-technologies for the correction of age-related changes in the MLV functions and brain's drainage processes and for effectively cleansing brain tissues from metabolites and toxins. This technology is intended both for preclinical studies of the functions of the sleeping brain and for developing clinically relevant treatments for sleep-related brain diseases.