Low-cost, open-source device for simultaneously subjecting rodents to different circadian cycles of light, food, and temperature.

Exposure of experimental rodents to controlled cycles of light, food, and temperature is important when investigating alterations in circadian cycles that profoundly influence health and disease. However, applying such stimuli simultaneously is difficult in practice. We aimed to design, build, test, and open-source describe a simple device that subjects a conventional mouse cage to independent cycles of physiologically relevant environmental variables. The device is based on a box enclosing the rodent cage to modify the light, feeding, and temperature environments. The device provides temperature-controlled air conditioning (heating or cooling) by a Peltier module and includes programmable feeding and illumination. All functions are set by a user-friendly front panel for independent cycle programming. Bench testing with a model simulating the CO2 production of mice in the cage showed: a) suitable air renewal (by measuring actual ambient CO2), b) controlled realistic illumination at the mouse enclosure (measured by a photometer), c) stable temperature control, and d) correct cycling of light, feeding, and temperature. The cost of all the supplies (retail purchased by e-commerce) was <300 US$. Detailed technical information is open-source provided, allowing for any user to reliably reproduce or modify the device. This approach can considerably facilitate circadian research since using one of the described low-cost devices for any mouse group with a given light-food-temperature paradigm allows for all the experiments to be performed simultaneously, thereby requiring no changes in the light/temperature of a general-use laboratory.

Patient profiles and success rates under different sedation techniques in a tertiary care center.

OBJECTIVES: Sedation is commonly utilized for individuals otherwise unable to receive dental treatment, such as those with disabilities, medically complex conditions, and dentophobics. The aim was to characterize the profiles of patients receiving various types of sedation and assess the corresponding success rates. METHOD AND MATERIALS: This was a 5-year records-based retrospective study. Data regarding the indication for sedation, medical history, sedation type, and treatments performed were recorded. RESULTS: In total, 103 patients underwent 389 treatment sessions under sedation; 42.7% of the patients were disabled. The most commonly administered sedation was moderate sedation, (49.4%), followed by deep (36.8%) and inhaled sedation (13.9%). Successful treatment results were achieved in 96.1% of sessions, with no adverse effects noted during recovery. The high success rates were independent of patient age, sex, and sedation type. There was a positive association between the indication for sedation and the type of sedation. The medically complex patients and the dentophobic patients received mainly moderate sedation (85.3% and 58.2%, respectively), whereas the disabled patients received deep sedation (51.2%). In total, 94% of patients were returning (re-visiting) patients. A statistically significant association was found between the type of sedation administered and the success rate during the first and last sessions (P < .001). The success rate at the first session may be predictive of the success in subsequent sessions. CONCLUSION: A significant positive correlation was found between patient characteristics and the chosen sedation type leading to a high success rate across the various sedation modalities.

Sleep fragmentation disrupts Lyme arthritis resolution in mice.

STUDY OBJECTIVES: Lyme arthritis is a common late-stage complication of infection by Borrelia burgdorferi, the agent of Lyme disease. Patients with Lyme arthritis report increased levels of sleep disturbance associated with pain. Using a mouse model of experimental Lyme arthritis, we investigated the effect of disrupted sleep on the development and resolution of joint inflammation. METHODS: Lyme arthritis-susceptible C3H/HeJ mice (n = 10/group) were infected with B. burgdorferi and were left either alone (control) or subjected to sleep fragmentation (SF). Arthritis development or resolution were monitored. The impact of SF on immune and inflammatory parameters such as arthritis severity scores, anti-borrelia antibody production, and bacterial clearance was measured. We also determined the effect of SF on arthritis resolution in C3H mice deficient in leukotriene (LT) B4 signaling (BLT1/2-/-) who display delayed Lyme arthritis resolution. RESULTS: SF had no significant impact on Lyme arthritis development or inflammatory parameters regardless of whether SF treatment began 1 week prior to or congruent with infection. However, initiation of SF at the peak of arthritis resulted in a significant delay in arthritis resolution as measured by joint edema, arthritis severity scores, and decreased bacterial clearance from the joint. This was accompanied by significant changes in joint cytokine transcription levels (e.g., increased TNFα and decreased IL-4). SF has no significant impact on Lyme arthritis resolution in the BLT1/2-/- mice. CONCLUSIONS: Poor sleep, especially near the peak of arthritis inflammation, may delay initiation of resolution programs possibly through altering cytokine production and host immune responses, leading to defects in spirochete clearance and prolonged disease.

Distribution and morphology of calcitonin gene-related peptide (CGRP) innervation in flat mounts of whole rat atria and ventricles.

Calcitonin gene-related peptide (CGRP) is widely used as a marker for nociceptive afferent axons. However, the distribution of CGRP-IR axons has not been fully determined in the whole rat heart. Immunohistochemically labeled flat-mounts of the right and left atria and ventricles, and the interventricular septum (IVS) in rats for CGRP were assessed with a Zeiss imager to generate complete montages of the entire atria, ventricles, and septum, and a confocal microscope was used to acquire detailed images of selected regions. We found that 1) CGRP-IR axons extensively innervated all regions of the atrial walls including the sinoatrial node region, auricles, atrioventricular node region, superior/inferior vena cava, left pre-caval vein, and pulmonary veins. 2) CGRP-IR axons formed varicose terminals around individual neurons in some cardiac ganglia but passed through other ganglia without making appositions with cardiac neurons. 3) Varicose CGRP-IR axons innervated the walls of blood vessels. 4) CGRP-IR axons extensively innervated the right/left ventricular walls and IVS. Our data shows the rather ubiquitous distribution of CGRP-IR axons in the whole rat heart at single-cell/axon/varicosity resolution for the first time. This study lays the foundation for future studies to quantify the differences in CGRP-IR axon innervation between sexes, disease models, and species.

The role of lncRNAs in intermittent hypoxia and sleep Apnea: A review of experimental and clinical evidence.

In this narrative review, we present a comprehensive assessment on the putative roles of long non-coding RNAs (lncRNAs) in intermittent hypoxia (IH) and sleep apnea. Collectively, the evidence from cell culture, animal, and clinical research studies points to the functional involvement of lncRNAs in the pathogenesis, diagnosis, and potential treatment strategies for this highly prevalent disorder. Further research is clearly warranted to uncover the mechanistic pathways and to exploit the therapeutic potential of lncRNAs, thereby improving the management and outcomes of patients suffering from sleep apnea.

Positive Airway Pressure Therapy Predicts Lower Mortality and Major Adverse Cardiovascular Events Incidence in Medicare Beneficiaries with Obstructive Sleep Apnea.

Background: Obesity is associated with obstructive sleep apnea (OSA) and cardiovascular risk. Positive airway pressure (PAP) is the first line treatment for OSA, but evidence on its beneficial effect on major adverse cardiovascular events (MACE) prevention is limited. Using claims data, the effects of PAP on mortality and incidence of MACE among Medicare beneficiaries with OSA were examined. Methods: A cohort of Medicare beneficiaries with ≥2 distinct OSA claims was defined from multi-state, state-wide, multi-year (2011-2020) Medicare fee-for-service claims data. Evidence of PAP initiation and utilization was based on PAP claims after OSA diagnosis. MACE was defined as a composite of myocardial infarction, heart failure, stroke, or coronary revascularization. Doubly robust Cox proportional hazards models with inverse probability of treatment weights estimated treatment effects controlling for sociodemographic and clinical factors. Results: Among 888,835 beneficiaries with OSA (median age 73 years; 43.9% women; median follow-up 1,141 days), those with evidence of PAP initiation (32.6%) had significantly lower all-cause mortality (HR [95%CI]: 0.53 [0.52-0.54]) and MACE incidence risk (0.90 [0.89-0.91]). Higher quartiles of annual PAP claims were progressively associated with lower mortality (Q2: 0.84 [0.81-0.87], Q3: 0.76 [0.74-0.79], Q4: 0.74 [0.72-0.77]) and MACE incidence risk (Q2: 0.92 [0.89-0.95], Q3: 0.89 [0.86-0.91], Q4: 0.87 [0.85-0.90]). Conclusion: PAP utilization was associated with lower all-cause mortality and MACE incidence among Medicare beneficiaries with OSA. Results might inform trials assessing the importance of OSA therapy towards minimizing cardiovascular risk and mortality in older adults.

Senolytic-facilitated Reversal of End-Organ Dysfunction in a Murine Model of Obstructive Sleep Apnea.

Rationale: Obstructive sleep apnea (OSA) is a highly prevalent condition that is associated with accelerated biological aging and multiple end-organ morbidities. Current treatments, such as continuous positive airway pressure (CPAP), have shown limited cognitive, metabolic, and cardiovascular beneficial outcomes despite adherence. Thus, adjunct therapies aiming to reduce OSA burden, such as senolytics, could improve OSA outcomes.Objectives: To assess if targeting senescence in addition to partial normoxia mimicking "good" CPAP adherence can improve physiological outcomes in mice exposed to chronic intermittent hypoxia.Methods: We compared the effects of 6 weeks of therapy with either partial normoxic recovery alone or combined with the senolytic navitoclax after 16 weeks of intermittent hypoxia exposures, a hallmark of OSA, on multiphenotypic cardiometabolic and neurocognitive parameters.Measurements and Main Results: Our findings indicate that only when combined with navitoclax, partial normoxic recovery significantly improved sleepiness (sleep in the dark phase: 34% ± 4% vs. 26% ± 3%; P < 0.01), cognition (preference score: 51% ± 19% vs. 70% ± 11%; P = 0.048), coronary artery function (response to acetylcholine [vasodilation]: 56% ± 13% vs. 72% ± 10%; P < 0.001), glucose, and lipid metabolism and reduced intestinal permeability and senescence in multiple organs.Conclusions: These findings indicate that the reversibility of end-organ morbidities induced by OSA is not only contingent on restoration of normal oxygenation patterns but can be further enhanced by targeting other OSA-mediated detrimental cellular processes, such as accelerated senescence.

Persistent sleep-disordered breathing independently contributes to metabolic syndrome in prepubertal children.

BACKGROUND: Obstructive sleep apnea (OSA) is a risk factor for metabolic syndrome (MetS) in adults, but its association in prepubertal children is still questionable due to the relatively limited cardiometabolic data available and the phenotypic heterogeneity. OBJECTIVE: To identify the role of OSA as a potential mediator of MetS in prepubertal children. METHODS: A total of 255 prepubertal children from the Childhood Adenotonsillectomy Trial were included, with standardized measurements taken before OSA treatment and 7 months later. MetS was defined if three or more of the following criteria were present: adiposity, high blood pressure, elevated glycemia, and dyslipidemia. A causal mediation analysis was conducted to assess the effect of OSA treatment on MetS. RESULTS: OSA treatment significantly impacted MetS, with the apnea-hypopnea index emerging as mediator (p = .02). This mediation role was not detected for any of the individual risk factors that define MetS. We further found that the relationship between MetS and OSA is ascribable to respiratory disturbance caused by the apnea episodes, while systemic inflammation as measured by C-reactive protein, is mediated by desaturation events and fragmented sleep. In terms of evolution, patients with MetS were significantly more likely to recover after OSA treatment (odds ratio = 2.56, 95% confidence interval [CI] 1.20-5.46; risk ratio = 2.06, 95% CI 1.19-3.54) than the opposite, patients without MetS to develop it. CONCLUSION: The findings point to a causal role of OSA in the development of metabolic dysfunction, suggesting that persistent OSA may increase the risk of MetS in prepubertal children. This mediation role implies a need for developing screening for MetS in children presenting OSA symptoms.

Chronic intermittent hypoxia remodels catecholaminergic nerve innervation in mouse atria.

Chronic intermittent hypoxia (CIH, a model for sleep apnoea) is a major risk factor for several cardiovascular diseases. Autonomic imbalance (sympathetic overactivity and parasympathetic withdrawal) has emerged as a causal contributor of CIH-induced cardiovascular disease. Previously, we showed that CIH remodels the parasympathetic pathway. However, whether CIH induces remodelling of the cardiac sympathetic innervation remains unknown. Mice (male, C57BL/6J, 2-3 months) were exposed to either room air (RA, 21% O2 ) or CIH (alternating 21% and 5.7% O2 , every 6 min, 10 h day-1 ) for 8-10 weeks. Flat-mounts of their left and right atria were immunohistochemically labelled for tyrosine hydroxylase (TH, a sympathetic marker). Using a confocal microscope (or fluorescence microscope) and Neurlocudia 360 digitization and tracing system, we scanned both the left and right atria and quantitatively analysed the sympathetic axon density in both groups. The segmentation data was mapped onto a 3D mouse heart scaffold. Our findings indicated that CIH significantly remodelled the TH immunoreactive (-IR) innervation of the atria by increasing its density at the sinoatrial node, the auricles and the major veins attached to the atria (P < 0.05, n = 7). Additionally, CIH increased the branching points of TH-IR axons and decreased the distance between varicosities. Abnormal patterns of TH-IR axons around intrinsic cardiac ganglia were also found following CIH. We postulate that the increased sympathetic innervation may further amplify the effects of enhanced CIH-induced central sympathetic drive to the heart. Our work provides an anatomical foundation for the understanding of CIH-induced autonomic imbalance. KEY POINTS: Chronic intermittent hypoxia (CIH, a model for sleep apnoea) causes sympathetic overactivity, cardiovascular remodelling and hypertension. We determined the effect of CIH on sympathetic innervation of the mouse atria. In vivo CIH for 8-10 weeks resulted in an aberrant axonal pattern around the principal neurons within intrinsic cardiac ganglia and an increase in the density, branching point, tortuosity of catecholaminergic axons and atrial wall thickness. Utilizing mapping tool available from NIH (SPARC) Program, the topographical distribution of the catecholaminergic innervation of the atria were integrated into a novel 3D heart scaffold for precise anatomical distribution and holistic quantitative comparison between normal and CIH mice. This work provides a unique neuroanatomical understanding of the pathophysiology of CIH-induced autonomic remodelling.

A deep learning model based on the combination of convolutional and recurrent neural networks to enhance pulse oximetry ability to classify sleep stages in children with sleep apnea.

Characterization of sleep stages is essential in the diagnosis of sleep-related disorders but relies on manual scoring of overnight polysomnography (PSG) recordings, which is onerous and labor-intensive. Accordingly, we aimed to develop an accurate deep-learning model for sleep staging in children suffering from pediatric obstructive sleep apnea (OSA) using pulse oximetry signals. For this purpose, pulse rate (PR) and blood oxygen saturation (SpO2) from 429 childhood OSA patients were analyzed. A CNN-RNN architecture fed with PR and SpO2 signals was developed to automatically classify wake (W), non-Rapid Eye Movement (NREM), and REM sleep stages. This architecture was composed of: (i) a convolutional neural network (CNN), which learns stage-related features from raw PR and SpO2 data; and (ii) a recurrent neural network (RNN), which models the temporal distribution of the sleep stages. The proposed CNN-RNN model showed a high performance for the automated detection of W/NREM/REM sleep stages (86.0% accuracy and 0.743 Cohen's kappa). Furthermore, the total sleep time estimated for each children using the CNN-RNN model showed high agreement with the manually derived from PSG (intra-class correlation coefficient = 0.747). These results were superior to previous works using CNN-based deep-learning models for automatic sleep staging in pediatric OSA patients from pulse oximetry signals. Therefore, the combination of CNN and RNN allows to obtain additional information from raw PR and SpO2 data related to sleep stages, thus being useful to automatically score sleep stages in pulse oximetry tests for children evaluated for suspected OSA.Clinical Relevance-This research establishes the usefulness of a CNN-RNN architecture to automatically score sleep stages in pulse oximetry tests for pediatric OSA diagnosis.

Recovery Mimicking “Ideal” CPAP Adherence Does Not Improve Wakefulness or Cognition in Chronic Murine Models of OSA: Effect of Wake-Promoting Agents

Introduction: Obstructive sleep apnea (OSA) is a chronic condition characterized by intermittent hypoxia (IH) and sleep fragmentation (SF). OSA can induce excessive daytime sleepiness (EDS) and is associated with impaired cognition and anxiety. Solriamfetol (SOL) and modafinil (MOD) are widely used wake-promoting agents in OSA patients with EDS. Methods: Male C57Bl/6J mice were exposed to SF along with sleep controls (SC) or to IH and room air (RA) controls during the light (inactive) phase for 4 and 16 weeks, respectively. Both IH and SF exposures were then discontinued to mimic “ideal” continuous positive airway pressure (CPAP) adherence. All groups were then randomly assigned to receive once daily intraperitoneal injections of SOL, MOD, or vehicle (VEH) for 6 days. Sleep/wake activity was assessed along with tests of explicit memory, anxiety and depression were performed before and after treatments. Results: IH and SF exposures increased sleep percentage in the dark phase and reduced wake bouts lengths (i.e., EDS), and induced cognitive deficits and impulsivity in mice. Both SOL and MOD treatments effectively mitigated EDS when combined with recovery, while recovery alone did not improve EDS over the 6-day period. Furthermore, improvements explicit memory emerged only after SOL. Conclusion: Chronic IH and SF induce EDS in young adult mice that is not ameliorated by recovery except when combined with either SOL or MOD. SOL, but not MOD, significantly improves IH-induced cognitive deficits. Thus, SOL emerges as a viable adjuvant medication for residual EDS in OSA along with its positive impact on cognition. (AU)

ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis.

Obstructive sleep apnea (OSA) is a prevalent respiratory condition in children and is characterized by partial or complete obstruction of the upper airway during sleep. The respiratory events in OSA induce transient alterations of the cardiovascular system that ultimately can lead to increased cardiovascular risk in affected children. Therefore, a timely and accurate diagnosis is of utmost importance. However, polysomnography (PSG), the standard diagnostic test for pediatric OSA, is complex, uncomfortable, costly, and relatively inaccessible, particularly in low-resource environments, thereby resulting in substantial underdiagnosis. Here, we propose a novel deep-learning approach to simplify the diagnosis of pediatric OSA using raw electrocardiogram tracing (ECG). Specifically, a new convolutional neural network (CNN)-based regression model was implemented to automatically predict pediatric OSA by estimating its severity based on the apnea-hypopnea index (AHI) and deriving 4 OSA severity categories. For this purpose, overnight ECGs from 1,610 PSG recordings obtained from the Childhood Adenotonsillectomy Trial (CHAT) database were used. The database was randomly divided into approximately 60%, 20%, and 20% for training, validation, and testing, respectively. The diagnostic performance of the proposed CNN model largely outperformed the most accurate previous algorithms that relied on ECG-derived features (4-class Cohen's kappa coefficient of 0.373 versus 0.166). Specifically, for AHI cutoff values of 1, 5, and 10 events/hour, the binary classification achieved sensitivities of 84.19%, 76.67%, and 53.66%; specificities of 46.15%, 91.39%, and 98.06%; and accuracies of 75.92%, 86.96%, and 91.97%, respectively. Therefore, pediatric OSA can be readily identified by our proposed CNN model, which provides a simpler, faster, and more accessible diagnostic test that can be implemented in clinical practice.

Multi-Omics Analysis of Circulating Exosomes in Adherent Long-Term Treated OSA Patients.

Obstructive sleep apnea (OSA) is a highly prevalent chronic disease affecting nearly a billion people globally and increasing the risk of multi-organ morbidity and overall mortality. However, the mechanisms underlying such adverse outcomes remain incompletely delineated. Extracellular vesicles (exosomes) are secreted by most cells, are involved in both proximal and long-distance intercellular communication, and contribute toward homeostasis under physiological conditions. A multi-omics integrative assessment of plasma-derived exosomes from adult OSA patients prior to and after 1-year adherent CPAP treatment is lacking. We conducted multi-omic integrative assessments of plasma-derived exosomes from adult OSA patients prior to and following 1-year adherent CPAP treatment to identify potential specific disease candidates. Fasting morning plasma exosomes isolated from 12 adult patients with polysomnographically-diagnosed OSA were analyzed before and after 12 months of adherent CPAP therapy (mean ≥ 6 h/night) (OSAT). Exosomes were characterized by flow cytometry, transmission electron microscopy, and nanoparticle tracking analysis. Endothelial cell barrier integrity, wound healing, and tube formation were also performed. Multi-omics analysis for exosome cargos was integrated. Exosomes derived from OSAT improved endothelial permeability and dysfunction as well as significant improvement in tube formation compared with OSA. Multi-omic approaches for OSA circulating exosomes included lipidomic, proteomic, and small RNA (miRNAs) assessments. We found 30 differentially expressed proteins (DEPs), 72 lipids (DELs), and 13 miRNAs (DEMs). We found that the cholesterol metabolism (has04979) pathway is associated with lipid classes in OSA patients. Among the 12 subjects of OSA and OSAT, seven subjects had complete comprehensive exosome cargo information including lipids, proteins, and miRNAs. Multi-omic approaches identify potential signature biomarkers in plasma exosomes that are responsive to adherent OSA treatment. These differentially expressed molecules may also play a mechanistic role in OSA-induced morbidities and their reversibility. Our data suggest that a multi-omic integrative approach might be useful in understanding how exosomes function, their origin, and their potential clinical relevance, all of which merit future exploration in the context of relevant phenotypic variance. Developing an integrated molecular classification should lead to improved diagnostic classification, risk stratification, and patient management of OSA by assigning molecular disease-specific therapies.

Snoring, obstructive sleep apnea, and upper respiratory tract infection in elementary school children in Japan.

PURPOSE: Both obstructive sleep apnea (OSA) and the common cold are disorders of the upper respiratory tract, and may be associated. However, studies on the association between OSA and upper respiratory tract infections (URTI) in children are scarce. The aim of this study was to investigate possible associations between snoring, the severity of OSA, and URTI in elementary school children. METHODS: This was a cross-sectional study in a community cohort of elementary school children (first and second graders) in Japan. Information on sleep habits, history of URTI, and OSA risk was obtained from a parental questionnaire. Children underwent overnight tracheal sound recordings from which apnea-hypopnea index was estimated. Multivariable logistic analysis was employed to define the association between snoring, OSA, and URTI ≥ 3 episodes over six months. RESULTS: Of the 922 potential enrollees, 653 children and their parents (71%) agreed to participate in the study. Multivariable-adjusted ORs for URTI were 1.73 (95%CI: 1.16 to 2.59) in children who snored 1 to 4 nights per week and 2.82 (95%CI: 1.26 to 6.28) in snoring ≥ 5 nights per week compared with never snoring (reference). Likewise, subjectively reported louder snoring, as well as objectively defined louder sound levels, were significantly associated with URTI. In addition, OR for URTI in children with an estimated apnea-hypopnea index ≥ 2.0 events/hour was 2.65 (95%CI: 1.32 to 5.31) compared to children with apnea-hypopnea index less than 1.0 events/hour (reference). CONCLUSIONS: Snoring and severity of OSA as measured by nocturnal tracheal sound recordings were associated with increased susceptibility to URTI in elementary school children.

Prediction of the Sleep Apnea Severity Using 2D-Convolutional Neural Networks and Respiratory Effort Signals.

The high prevalence of sleep apnea and the limitations of polysomnography have prompted the investigation of strategies aimed at automated diagnosis using a restricted number of physiological measures. This study aimed to demonstrate that thoracic (THO) and abdominal (ABD) movement signals are useful for accurately estimating the severity of sleep apnea, even if central respiratory events are present. Thus, we developed 2D-convolutional neural networks (CNNs) jointly using THO and ABD to automatically estimate sleep apnea severity and evaluate the central event contribution. Our proposal achieved an intraclass correlation coefficient (ICC) = 0.75 and a root mean square error (RMSE) = 10.33 events/h when estimating the apnea-hypopnea index, and ICC = 0.83 and RMSE = 0.95 events/h when estimating the central apnea index. The CNN obtained accuracies of 94.98%, 79.82%, and 81.60% for 5, 15, and 30 events/h when evaluating the complete apnea hypopnea index. The model improved when the nature of the events was central: 98.72% and 99.74% accuracy for 5 and 15 events/h. Hence, the information extracted from these signals using CNNs could be a powerful tool to diagnose sleep apnea, especially in subjects with a high density of central apnea events.