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Search Results (656)

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Keywords = sleep physiology

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11 pages, 576 KiB  
Article
Phasic REM: Across Night Behavior and Transitions to Wake
by Giuseppe Barbato and Thomas A. Wehr
Brain Sci. 2025, 15(8), 840; https://doi.org/10.3390/brainsci15080840 - 6 Aug 2025
Abstract
Background/Objectives: Rapid eye movements (REMs) during sleep were initially associated with dreaming, suggesting a relationship between REMs and dream content; however, this hypothesis was questioned by their differences with the REMs during wakefulness and the evidence that REMs are also present in blind [...] Read more.
Background/Objectives: Rapid eye movements (REMs) during sleep were initially associated with dreaming, suggesting a relationship between REMs and dream content; however, this hypothesis was questioned by their differences with the REMs during wakefulness and the evidence that REMs are also present in blind individuals with no visual dreaming. Successive studies have focused on the phenomenology and physiological significance of REMs during sleep. REMs are categorized as expressions of the phasic REM component, which is characterized by bursts of eye movements, whereas the tonic REM component is characterized by quiescent periods without eye movements. Methods: The study is a retrospective analysis of 105 sleep records from 15 subjects. We analyzed the two components, tonic and phasic REM, across the sleep period, the REM activity in the first 5 min and in the last 5 min of each REM period were also assessed. Results: Phasic epochs were more represented than tonic epochs across the whole night period. REM activity in the first and last five minutes of an REM period presented different, although non-significant, patterns across the night. REM activity in the first 5 min showed a curvilinear profile, whereas REM activity in the last 5 min showed a linear increasing trend. A significant correlation was found between the REM activity in the first 5 min of the REM period and the total duration of the REM period. Conclusions: According to our results, the analysis of REM activity and the focus on segments of an REM period could provide more information both on the temporal evolution of REM activity within an REM period and on the possible role of REMs in REM sleep regulation and its significance in psychiatric and neurological disorders. Full article
(This article belongs to the Section Sleep and Circadian Neuroscience)
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22 pages, 1820 KiB  
Article
Can a Commercially Available Smartwatch Device Accurately Measure Nighttime Sleep Outcomes in Individuals with Knee Osteoarthritis and Comorbid Insomnia? A Comparison with Home-Based Polysomnography
by Céline Labie, Nils Runge, Zosia Goossens, Olivier Mairesse, Jo Nijs, Anneleen Malfliet, Dieter Van Assche, Kurt de Vlam, Luca Menghini, Sabine Verschueren and Liesbet De Baets
Sensors 2025, 25(15), 4813; https://doi.org/10.3390/s25154813 - 5 Aug 2025
Abstract
Sleep is a vital physiological process for recovery and health. In people with knee osteoarthritis (OA), disrupted sleep is common and linked to worse clinical outcomes. Commercial sleep trackers provide an accessible option to monitor sleep in this population, but their accuracy for [...] Read more.
Sleep is a vital physiological process for recovery and health. In people with knee osteoarthritis (OA), disrupted sleep is common and linked to worse clinical outcomes. Commercial sleep trackers provide an accessible option to monitor sleep in this population, but their accuracy for detecting sleep, wake, and sleep stages remains uncertain. This study compared nighttime sleep data from polysomnography (PSG) and Fitbit Sense in individuals with knee OA and insomnia. Data were collected from 53 participants (60.4% women, mean age 51 ± 8.2 years) over 62 nights using simultaneous PSG and Fitbit recording. Fitbit Sense showed high accuracy (85.76%) and sensitivity (95.95%) for detecting sleep but lower specificity (50.96%), indicating difficulty separating quiet wakefulness from sleep. Agreement with PSG was higher on nights with longer total sleep time, higher sleep efficiency, shorter sleep onset, and fewer awakenings, suggesting better performance when sleep is less fragmented. The device showed limited precision in classifying sleep stages, often misclassifying deep and REM sleep as light sleep. Despite these issues, Fitbit Sense may serve as a useful complementary tool for monitoring sleep duration, timing, and regularity in this population. However, sleep stage and fragmentation data should be interpreted cautiously in both clinical and research settings. Full article
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34 pages, 1544 KiB  
Review
The Crucial Interplay Between the Lungs, Brain, and Heart to Understand Epilepsy-Linked SUDEP: A Literature Review
by Mohd Yaqub Mir, Bilal A. Seh, Shabab Zahra and Adam Legradi
Brain Sci. 2025, 15(8), 809; https://doi.org/10.3390/brainsci15080809 - 28 Jul 2025
Viewed by 420
Abstract
Sudden Unexpected Death in Epilepsy (SUDEP) is a leading cause of mortality among individuals with epilepsy, particularly those with drug-resistant forms. This review explores the complex multisystem mechanisms underpinning SUDEP, integrating recent findings on brain, cardiac, and pulmonary dysfunctions. Background/Objectives: The main objective [...] Read more.
Sudden Unexpected Death in Epilepsy (SUDEP) is a leading cause of mortality among individuals with epilepsy, particularly those with drug-resistant forms. This review explores the complex multisystem mechanisms underpinning SUDEP, integrating recent findings on brain, cardiac, and pulmonary dysfunctions. Background/Objectives: The main objective of this review is to elucidate how seizures disrupt critical physiological systems, especially the brainstem, heart, and lungs, contributing to SUDEP, with emphasis on respiratory control failure and autonomic instability. Methods: The literature from experimental models, clinical observations, neuroimaging studies, and genetic analyses was systematically examined. Results: SUDEP is frequently preceded by generalized tonic–clonic seizures, which trigger central and obstructive apnea, hypoventilation, and cardiac arrhythmias. Brainstem dysfunction, particularly in areas such as the pre-Bötzinger complex and nucleus tractus solitarius, plays a central role. Genetic mutations affecting ion channels (e.g., SCN1A, KCNQ1) and neurotransmitter imbalances (notably serotonin and GABA) exacerbate autonomic dysregulation. Risk is compounded by a prone sleeping position, reduced arousal capacity, and impaired ventilatory responses. Conclusions: SUDEP arises from a cascade of interrelated failures in respiratory and cardiac regulation initiated by seizure activity. The recognition of modifiable risk factors, implementation of monitoring technologies, and targeted therapies such as serotonergic agents may reduce mortality. Multidisciplinary approaches integrating neurology, cardiology, and respiratory medicine are essential for effective prevention strategies. Full article
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25 pages, 946 KiB  
Review
Airway Management in Obstructive Sleep Apnea: A Comprehensive Review of Assessment Strategies, Techniques, and Technological Advances
by Mario Giuseppe Bellizzi, Annalisa Pace, Giannicola Iannella, Antonino Maniaci, Daniele Salvatore Paternò, Simona Tutino, Massimiliano Sorbello, Salvatore Maria Ronsivalle, Giuseppe Magliulo, Antonio Greco, Armando De Virgilio, Patrizia Mancini, Enrica Croce, Giulia Molinari, Daniela Lucidi, Jerome R. Lechien, Antonio Moffa, Alberto Caranti and Luigi La Via
Healthcare 2025, 13(15), 1823; https://doi.org/10.3390/healthcare13151823 - 26 Jul 2025
Viewed by 199
Abstract
Background: Airway management in patients with obstructive sleep apnea (OSA) presents unique challenges for anesthesiologists and other airway practitioners. This comprehensive review examines current evidence and clinical practices for managing difficult airways in this high-risk population. OSA is characterized by specific anatomical [...] Read more.
Background: Airway management in patients with obstructive sleep apnea (OSA) presents unique challenges for anesthesiologists and other airway practitioners. This comprehensive review examines current evidence and clinical practices for managing difficult airways in this high-risk population. OSA is characterized by specific anatomical and physiological alterations that increase both the likelihood of encountering difficult intubation and the risk of rapid desaturation during airway manipulation. Methods: Preoperative assessment of OSA patients requires integration of traditional difficult airway evaluation with OSA-specific considerations, including severity indices, oxygen desaturation patterns, and continuous positive airway pressure dependency. Conventional direct laryngoscopy often proves inadequate in these patients, prompting the development and refinement of alternative approaches. Videolaryngoscopy has emerged as a particularly valuable technique in OSA patients, offering improved glottic visualization while maintaining physiologic positioning. Flexible endoscopic techniques, particularly awake flexible bronchoscopic intubation, remain essential for high-risk scenarios, though they require considerable expertise. Results: Recent technological innovations have produced hybrid devices combining multiple modalities to address the specific challenges presented by OSA patients. Adjunctive tools and techniques, including specialized introducers, exchange catheters, and high-flow nasal oxygen, play critical roles in extending safe apnea time and facilitating successful intubation. Professional society guidelines now incorporate OSA-specific recommendations, emphasizing thorough preparation, appropriate device selection, and comprehensive monitoring. Conclusions: Effective management ultimately requires not only appropriate technology but also systematic preparation, strategic device selection, and meticulous execution. As OSA prevalence continues to rise globally, optimizing airway management approaches for this challenging population remains a critical priority for patient safety. Full article
(This article belongs to the Special Issue New Developments in Endotracheal Intubation and Airway Management)
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20 pages, 1480 KiB  
Review
Molecular Pathways Potentially Involved in Hallucinatory Experiences During Sleep Paralysis: The Emerging Role of β-Arrestin-2
by Lena M. Rudy and Michał M. Godlewski
Int. J. Mol. Sci. 2025, 26(15), 7233; https://doi.org/10.3390/ijms26157233 - 26 Jul 2025
Viewed by 486
Abstract
Sleep paralysis (SP), an REM parasomnia, can be characterized as one of the symptoms of narcolepsy. The SP phenomenon involves regaining meta-consciousness by the dreamer during REM, when the physiological atonia of skeletal muscles is accompanied by visual and auditory hallucinations that are [...] Read more.
Sleep paralysis (SP), an REM parasomnia, can be characterized as one of the symptoms of narcolepsy. The SP phenomenon involves regaining meta-consciousness by the dreamer during REM, when the physiological atonia of skeletal muscles is accompanied by visual and auditory hallucinations that are perceived as vivid and distressing nightmares. Sensory impressions include personification of an unknown presence, strong chest pressure sensation, and intense fear resulting from subjective interaction with the unfolding nightmare. While the mechanism underlying skeletal muscle atonia is known, the physiology of hallucinations remains unclear. Their complex etiology involves interactions among various membrane receptor systems and neurotransmitters, which leads to altered neuronal functionality and disruptions in sensory perception. According to current knowledge, serotonergic activation of 5-hydroxytryptamine-receptor-2A (5-HT2A)-associated pathways plays a critical role in promoting hallucinogenesis during SP. Furthermore, they share similarities with psychedelic-substance-induced ones (i.e., LSD, psilocybin, and 2,5-dimethoxy-4-iodoamphetamine). These compounds also target the 5-HT2A receptor; however, their molecular mechanism varies from serotonin-induced ones. The current review discusses the intracellular signaling pathways responsible for promoting hallucinations in SP, highlighting the critical role of β-arrestin-2. We propose that the β-arrestin-2 signaling pathway does not directly induce hallucinations but creates a state of network susceptibility that facilitates their abrupt emergence in sensory areas. Understanding the molecular basis of serotonergic hallucinations and gaining better insight into 5-HT2A-receptor-dependent pathways may prove crucial in the treatment of multifactorial neuropsychiatric disorders associated with the dysfunctional activity of serotonin receptors. Full article
(This article belongs to the Section Molecular Neurobiology)
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35 pages, 638 KiB  
Review
The Influence of Circadian Rhythms on Transcranial Direct Current Stimulation (tDCS) Effects: Theoretical and Practical Considerations
by James Chmiel and Agnieszka Malinowska
Cells 2025, 14(15), 1152; https://doi.org/10.3390/cells14151152 - 25 Jul 2025
Viewed by 591
Abstract
Transcranial direct current stimulation (tDCS) can modulate cortical excitability in a polarity-specific manner, yet identical protocols often produce inconsistent outcomes across sessions or individuals. This narrative review proposes that much of this variability arises from the brain’s intrinsic temporal landscape. Integrating evidence from [...] Read more.
Transcranial direct current stimulation (tDCS) can modulate cortical excitability in a polarity-specific manner, yet identical protocols often produce inconsistent outcomes across sessions or individuals. This narrative review proposes that much of this variability arises from the brain’s intrinsic temporal landscape. Integrating evidence from chronobiology, sleep research, and non-invasive brain stimulation, we argue that tDCS produces reliable, polarity-specific after-effects only within a circadian–homeostatic “window of efficacy”. On the circadian (Process C) axis, intrinsic alertness, membrane depolarisation, and glutamatergic gain rise in the late biological morning and early evening, whereas pre-dawn phases are marked by reduced excitability and heightened inhibition. On the homeostatic (Process S) axis, consolidated sleep renormalises synaptic weights, widening the capacity for further potentiation, whereas prolonged wakefulness saturates plasticity and can even reverse the usual anodal/cathodal polarity rules. Human stimulation studies mirror this two-process fingerprint: sleep deprivation abolishes anodal long-term-potentiation-like effects and converts cathodal inhibition into facilitation, while stimulating at each participant’s chronotype-aligned (phase-aligned) peak time amplifies and prolongs after-effects even under equal sleep pressure. From these observations we derive practical recommendations: (i) schedule excitatory tDCS after restorative sleep and near the individual wake-maintenance zone; (ii) avoid sessions at high sleep pressure or circadian troughs; (iii) log melatonin phase, chronotype, recent sleep and, where feasible, core temperature; and (iv) consider mild pre-heating or time-restricted feeding as physiological primers. By viewing Borbély’s two-process model and allied metabolic clocks as adjustable knobs for plasticity engineering, this review provides a conceptual scaffold for personalised, time-sensitive tDCS protocols that could improve reproducibility in research and therapeutic gain in the clinic. Full article
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27 pages, 464 KiB  
Review
Caffeine in Aging Brains: Cognitive Enhancement, Neurodegeneration, and Emerging Concerns About Addiction
by Manuel Glauco Carbone, Giovanni Pagni, Claudia Tagliarini, Icro Maremmani and Angelo Giovanni Icro Maremmani
Int. J. Environ. Res. Public Health 2025, 22(8), 1171; https://doi.org/10.3390/ijerph22081171 - 24 Jul 2025
Viewed by 630
Abstract
This narrative review examines the effects of caffeine on brain health in older adults, with particular attention to its potential for dependence—an often-overlooked issue in geriatric care. Caffeine acts on central adenosine, dopamine, and glutamate systems, producing both stimulating and rewarding effects that [...] Read more.
This narrative review examines the effects of caffeine on brain health in older adults, with particular attention to its potential for dependence—an often-overlooked issue in geriatric care. Caffeine acts on central adenosine, dopamine, and glutamate systems, producing both stimulating and rewarding effects that can foster tolerance and habitual use. Age-related pharmacokinetic and pharmacodynamic changes prolong caffeine’s half-life and increase physiological sensitivity in the elderly. While moderate consumption may enhance alertness, attention, and possibly offer neuroprotective effects—especially in Parkinson’s disease and Lewy body dementia—excessive or prolonged use may lead to anxiety, sleep disturbances, and cognitive or motor impairment. Chronic exposure induces neuroadaptive changes, such as adenosine receptor down-regulation, resulting in tolerance and withdrawal symptoms, including headache, irritability, and fatigue. These symptoms, often mistaken for typical aging complaints, may reflect a substance use disorder yet remain under-recognized due to caffeine’s cultural acceptance. The review explores caffeine’s mixed role in neurological disorders, being beneficial in some and potentially harmful in others, such as restless legs syndrome and frontotemporal dementia. Given the variability in individual responses and the underestimated risk of dependence, personalized caffeine intake guidelines are warranted. Future research should focus on the long-term cognitive effects and the clinical significance of caffeine use disorder in older populations. Full article
(This article belongs to the Section Behavioral and Mental Health)
15 pages, 2317 KiB  
Article
An Ensemble-Based AI Approach for Continuous Blood Pressure Estimation in Health Monitoring Applications
by Rafita Haque, Chunlei Wang and Nezih Pala
Sensors 2025, 25(15), 4574; https://doi.org/10.3390/s25154574 - 24 Jul 2025
Viewed by 449
Abstract
Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system [...] Read more.
Continuous blood pressure (BP) monitoring provides valuable insight into the body’s dynamic cardiovascular regulation across various physiological states such as physical activity, emotional stress, postural changes, and sleep. Continuous BP monitoring captures different variations in systolic and diastolic pressures, reflecting autonomic nervous system activity, vascular compliance, and circadian rhythms. This enables early identification of abnormal BP trends and allows for timely diagnosis and interventions to reduce the risk of cardiovascular diseases (CVDs) such as hypertension, stroke, heart failure, and chronic kidney disease as well as chronic stress or anxiety disorders. To facilitate continuous BP monitoring, we propose an AI-powered estimation framework. The proposed framework first uses an expert-driven feature engineering approach that systematically extracts physiological features from photoplethysmogram (PPG)-based arterial pulse waveforms (APWs). Extracted features include pulse rate, ascending/descending times, pulse width, slopes, intensity variations, and waveform areas. These features are fused with demographic data (age, gender, height, weight, BMI) to enhance model robustness and accuracy across diverse populations. The framework utilizes a Tab-Transformer to learn rich feature embeddings, which are then processed through an ensemble machine learning framework consisting of CatBoost, XGBoost, and LightGBM. Evaluated on a dataset of 1000 subjects, the model achieves Mean Absolute Errors (MAE) of 3.87 mmHg (SBP) and 2.50 mmHg (DBP), meeting British Hypertension Society (BHS) Grade A and Association for the Advancement of Medical Instrumentation (AAMI) standards. The proposed architecture advances non-invasive, AI-driven solutions for dynamic cardiovascular health monitoring. Full article
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13 pages, 287 KiB  
Review
Cytisinicline vs. Varenicline in Tobacco Addiction: A Literature Review Focused on Emotional Regulation, Psychological Symptoms, and Mental Health
by Óscar Fraile-Martínez, Cielo García-Montero, Miguel A. Ortega, Andrea Varaona, Luis Gutiérrez-Rojas, Melchor Álvarez-Mon and Miguel Ángel Álvarez-Mon
Healthcare 2025, 13(15), 1783; https://doi.org/10.3390/healthcare13151783 - 23 Jul 2025
Viewed by 299
Abstract
Tobacco use disorder remains a leading cause of preventable mortality, with nicotine playing a central role in the development and maintenance of dependence, mainly through its action on α4β2 nicotinic acetylcholine receptors (nAChRs). Smoking cessation treatments must address both physiological withdrawal and the [...] Read more.
Tobacco use disorder remains a leading cause of preventable mortality, with nicotine playing a central role in the development and maintenance of dependence, mainly through its action on α4β2 nicotinic acetylcholine receptors (nAChRs). Smoking cessation treatments must address both physiological withdrawal and the affective disturbances (such as anxiety, irritability, and mood lability) which often facilitate relapses. This review compares two pharmacotherapies used in smoking cessation, varenicline and cytisinicline (cytisine), with particular focus on their impact on emotional regulation, psychological symptoms, and neuropsychiatric safety. Varenicline, a high-affinity partial agonist at α4β2 nAChRs, has demonstrated superior efficacy in maintaining abstinence and is well-supported by robust clinical data, including in psychiatric populations. However, its use may be limited by adverse effects such as nausea and sleep disorders. Cytisinicline, a structurally similar but less potent partial agonist, has recently gained renewed interest due to its lower cost, favorable tolerability profile, and comparable effectiveness in the general population. Although less extensively studied in patients with serious mental illness, preliminary data suggest cytisinicline may offer a better side effect profile, particularly regarding sleep disturbances and emotional reactivity. Both agents appear to ameliorate withdrawal-related affective symptoms without significantly increasing psychiatric risk. Ultimately, pharmacotherapy choice should be guided by individual clinical features, mental health status, treatment tolerability, and resource availability. Further research is needed to establish cytisinicline’s efficacy and safety across diverse clinical contexts, particularly among individuals with severe psychiatric comorbidities. Full article
17 pages, 1738 KiB  
Article
Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis
by Songlu Lin, Renzheng Tang, Yuzhe Wang and Zhihong Wang
Appl. Sci. 2025, 15(14), 8077; https://doi.org/10.3390/app15148077 - 20 Jul 2025
Viewed by 524
Abstract
Accurate sleep staging and sleep-disordered breathing (SDB) severity prediction are critical for the early diagnosis and management of sleep disorders. However, real-world polysomnography (PSG) data often suffer from modality heterogeneity, label scarcity, and non-independent and identically distributed (non-IID) characteristics across institutions, posing significant [...] Read more.
Accurate sleep staging and sleep-disordered breathing (SDB) severity prediction are critical for the early diagnosis and management of sleep disorders. However, real-world polysomnography (PSG) data often suffer from modality heterogeneity, label scarcity, and non-independent and identically distributed (non-IID) characteristics across institutions, posing significant challenges for model generalization and clinical deployment. To address these issues, we propose a federated multi-task learning (FMTL) framework that simultaneously performs sleep staging and SDB severity classification from seven multimodal physiological signals, including EEG, ECG, respiration, etc. The proposed framework is built upon a hybrid deep neural architecture that integrates convolutional layers (CNN) for spatial representation, bidirectional GRUs for temporal modeling, and multi-head self-attention for long-range dependency learning. A shared feature extractor is combined with task-specific heads to enable joint diagnosis, while the FedAvg algorithm is employed to facilitate decentralized training across multiple institutions without sharing raw data, thereby preserving privacy and addressing non-IID challenges. We evaluate the proposed method across three public datasets (APPLES, SHHS, and HMC) treated as independent clients. For sleep staging, the model achieves accuracies of 85.3% (APPLES), 87.1% (SHHS_rest), and 79.3% (HMC), with Cohen’s Kappa scores exceeding 0.71. For SDB severity classification, it obtains macro-F1 scores of 77.6%, 76.4%, and 79.1% on APPLES, SHHS_rest, and HMC, respectively. These results demonstrate that our unified FMTL framework effectively leverages multimodal PSG signals and federated training to deliver accurate and scalable sleep disorder assessment, paving the way for the development of a privacy-preserving, generalizable, and clinically applicable digital sleep monitoring system. Full article
(This article belongs to the Special Issue Machine Learning in Biomedical Applications)
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13 pages, 691 KiB  
Review
Sleep and Risk of Multiple Sclerosis: Bridging the Gap Between Inflammation and Neurodegeneration via Glymphatic Failure
by Mariateresa Buongiorno, Carmen Tur, Darly Milena Giraldo, Natalia Cullell, Jerzy Krupinski, Roberta Lanzillo and Gonzalo Sánchez-Benavides
Brain Sci. 2025, 15(7), 766; https://doi.org/10.3390/brainsci15070766 - 19 Jul 2025
Viewed by 501
Abstract
Epidemiological studies identified insufficient and poor-quality sleep as independent risk factors for multiple sclerosis (MS). The glymphatic system, active during slow-wave sleep, clears brain waste through perivascular astrocytic aquaporin-4 (AQP4) channels. The presence of antigens induces a transient, physiological lowering of glymphatic flux [...] Read more.
Epidemiological studies identified insufficient and poor-quality sleep as independent risk factors for multiple sclerosis (MS). The glymphatic system, active during slow-wave sleep, clears brain waste through perivascular astrocytic aquaporin-4 (AQP4) channels. The presence of antigens induces a transient, physiological lowering of glymphatic flux as a first step of an inflammatory response. A possible hypothesis linking infection with the Epstein–Barr virus, a well identified causal step in MS, and the development of the disease is that mechanisms such as poor sleep or less functional AQP4 polymorphisms may sustain glymphatic flow reduction. Such chronic glymphatic reduction would trigger a vicious circle in which the persistence of antigens and an inflammatory response maintains glymphatic dysfunction. In addition, viral proteins that persist in demyelinated plaques can depolarize AQP4, further restricting waste elimination and sustaining local inflammation. This review examines the epidemiological evidence connecting sleep and MS risk, and the mechanistic findings showing how poor sleep and other glymphatic modulators heighten inflammatory signaling implicated in MS pathogenesis. Deepening knowledge of glymphatic functioning in MS could open new avenues for personalized prevention and therapy. Full article
(This article belongs to the Section Neurodegenerative Diseases)
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17 pages, 2244 KiB  
Article
Associations Between Daily Heart Rate Variability and Self-Reported Wellness: A 14-Day Observational Study in Healthy Adults
by James Hannon, Adrian O’Hagan, Rory Lambe, Ben O’Grady and Cailbhe Doherty
Sensors 2025, 25(14), 4415; https://doi.org/10.3390/s25144415 - 15 Jul 2025
Viewed by 950
Abstract
Heart rate variability (HRV), particularly the root mean square of successive differences (RMSSD), is widely used as a non-invasive indicator of autonomic nervous system activity and physiological recovery. This study examined whether daily short-term HRV, measured under standardised morning conditions, was associated with [...] Read more.
Heart rate variability (HRV), particularly the root mean square of successive differences (RMSSD), is widely used as a non-invasive indicator of autonomic nervous system activity and physiological recovery. This study examined whether daily short-term HRV, measured under standardised morning conditions, was associated with self-reported wellness in a non-clinical adult population. Over a 14-day period, 41 participants completed daily five-minute HRV recordings using a Polar H10 chest sensor and the Kubios mobile app, followed by ratings of sleep quality, fatigue, stress, and physical recovery. Bayesian ordinal mixed-effects models revealed that higher RMSSD values were associated with better self-reported sleep (β = 0.510, 95% HDI: 0.239 to 0.779), lower fatigue (β = 0.281, 95% HDI: 0.020 to 0.562), and reduced stress (β = 0.353, 95% HDI: 0.059 to 0.606), even after adjusting for covariates. No association was found between RMSSD and perceived muscle soreness. These findings support the interpretability of RMSSD as a physiological marker of daily recovery and stress in real-world settings. While the effect sizes were modest and individual variability remained substantial, results suggest that consistent HRV monitoring may offer meaningful insight into subjective wellness—particularly when contextualised and tracked over time. Full article
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19 pages, 1237 KiB  
Review
Circadian Biomarkers in Humans: Methodological Insights into the Detection of Melatonin and Cortisol
by Cene Skubic, Urša Zevnik, Katarina Nahtigal, Leja Dolenc Grošelj and Damjana Rozman
Biomolecules 2025, 15(7), 1006; https://doi.org/10.3390/biom15071006 - 14 Jul 2025
Viewed by 832
Abstract
Circadian rhythms are intrinsic, with roughly 24 h oscillations that coordinate many physiological functions and are increasingly recognized as key determinants of human health. When these rhythms become misaligned, there is an increased risk for neurodegenerative and psychiatric disorders, metabolic syndrome, sleep disturbances, [...] Read more.
Circadian rhythms are intrinsic, with roughly 24 h oscillations that coordinate many physiological functions and are increasingly recognized as key determinants of human health. When these rhythms become misaligned, there is an increased risk for neurodegenerative and psychiatric disorders, metabolic syndrome, sleep disturbances, and even certain cancers. The hormones, melatonin that rises in the evening and cortisol that peaks shortly after awakening, represent crucial biochemical markers of the circadian phase. This review systematically evaluates contemporary techniques for quantifying melatonin and cortisol, comparing biological matrices (blood, saliva, urine) alongside analytical platforms. Special focus is placed on two clinically informative markers: Dim Light Melatonin Onset (DLMO) and the Cortisol Awakening Response (CAR). We compared immunoassays with liquid chromatography tandem mass spectrometry (LC MS/MS), highlighting differences in sensitivity, specificity, and laboratory feasibility. Potential confounders, including ambient light, body posture, and exact sampling times—are discussed in detail, to show the capacity of providing the most reliable results. By emphasizing the need for standardized protocols and controlled sampling conditions, this review provides essential guidance for researchers and clinicians aiming to assess the circadian biomarkers melatonin and cortisol with precision since they can be used in clinical practice as diagnostic and prognostic tools for assessing numerous pathologies. Full article
(This article belongs to the Special Issue Melatonin in Normal Physiology and Disease, 2nd Edition)
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16 pages, 1714 KiB  
Article
MCAF-Net: Multi-Channel Temporal Cross-Attention Network with Dynamic Gating for Sleep Stage Classification
by Xuegang Xu, Quan Wang, Changyuan Wang and Yaxin Zhang
Sensors 2025, 25(14), 4251; https://doi.org/10.3390/s25144251 - 8 Jul 2025
Viewed by 356
Abstract
Automated sleep stage classification is essential for objective sleep evaluation and clinical diagnosis. While numerous algorithms have been developed, the predominant existing methods utilize single-channel electroencephalogram (EEG) signals, neglecting the complementary physiological information available from other channels. Standard polysomnography (PSG) recordings capture multiple [...] Read more.
Automated sleep stage classification is essential for objective sleep evaluation and clinical diagnosis. While numerous algorithms have been developed, the predominant existing methods utilize single-channel electroencephalogram (EEG) signals, neglecting the complementary physiological information available from other channels. Standard polysomnography (PSG) recordings capture multiple concurrent biosignals, where sophisticated integration of these multi-channel data represents a critical factor for enhanced classification accuracy. Conventional multi-channel fusion techniques typically employ elementary concatenation approaches that insufficiently model the intricate cross-channel correlations, consequently limiting classification performance. To overcome these shortcomings, we present MCAF-Net, a novel network architecture that employs temporal convolution modules to extract channel-specific features from each input signal and introduces a dynamic gated multi-head cross-channel attention mechanism (MCAF) to effectively model the interdependencies between different physiological channels. Experimental results show that our proposed method successfully integrates information from multiple channels, achieving significant improvements in sleep stage classification compared to the vast majority of existing methods. Full article
(This article belongs to the Section Sensor Networks)
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15 pages, 1291 KiB  
Article
Multifactorial Influences on Oxygen Consumption Recovery Post-High-Intensity Exercise in Adults: A Case-Control Study
by Monira I. Aldhahi, Rawan I. Alahmed, Reem H. Almutairi, Haya A. Alqahtani, Hatoon M. Alawad, Rania S. Alkabeer, Leena K. Alqhtani and Mohanad S. Aljubairi
Medicina 2025, 61(7), 1213; https://doi.org/10.3390/medicina61071213 - 3 Jul 2025
Viewed by 505
Abstract
Background and Objectives: Oxygen consumption (VO2) recovery plays a critical role in reestablishing homeostasis within multiple physiological processes. This study aimed to assess the differences in the fitness profiles, fatigability, patterns of VO2 recovery, and sleep quality among individuals [...] Read more.
Background and Objectives: Oxygen consumption (VO2) recovery plays a critical role in reestablishing homeostasis within multiple physiological processes. This study aimed to assess the differences in the fitness profiles, fatigability, patterns of VO2 recovery, and sleep quality among individuals with different body fat percentages. Thus, we evaluated the predictive effects of body fat percentage, CRF, fatigability, and sleep quality on VO2 recovery patterns following exercise. Materials and Methods: Eighty healthy participants aged 18–52 years were included in this case-control study. The participants were divided into two groups based on body fat percentage: normal-fat (CON; n = 40) and high-fat (HFG; n = 40) groups. The PSQI questionnaire was used to assess sleep efficiency, and a 10 min walk test was performed to assess fatigability. Both groups underwent a symptom-limited treadmill exercise test to assess VO2 using a modified bulk protocol, followed by 6 min of passive recovery. Results: The participants in the CON group had a higher mean VO2 peak than those in the high-fat-percentage group (p = 0.0003). The half-time recovery (T1 and T2) demonstrated higher amounts of VO2 in the CON group compared to the HFG group (p = 0.0007 and p = 0.0005), respectively. Those in the HFG reported greater performance fatigability (p = 0.01) and poorer sleep quality compared to the CON group (p < 0.001). The multiple linear regression model indicated that a higher recovery amount of VO2 was associated with the fat percentage, VO2 peak, and fatigability index and explained 72% of the variance (F = 39.58, p < 0.001). Conclusions: The findings of this study revealed that the participants with higher fat percentages exhibited increased performance fatigability and a reduced peak VO2 and reported poor sleep quality compared to the normal group. CPF, body fat, and performance fatigability were associated with VO2 recovery after high-intensity exercise. The interplay between body fat, fatigability, sleep quality, and VO2 recovery highlights the need for a holistic approach to healthcare. Full article
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