Search Results (709)

Background/Objectives: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by dopaminergic neuronal loss, oxidative stress, and mitochondrial dysfunction. Although levodopa (L-Dopa) remains the main symptomatic treatment, prolonged administration can lead to adverse effects. Safranal, a bioactive constituent of Crocus sativus, has antioxidant and anti-apoptotic properties. This study evaluated the neuroprotective potential of L-Dopa and safranal, individually and in combination, in an in vitro cell-culture PD model. Methods: SH-SY5Y human neuroblastoma cells were treated with 6-hydroxydopamine (6-OHDA, 50 µM) to induce cytotoxicity. Cells were pretreated with L-Dopa (5–500 µM) and safranal (1–500 µM and 1–5 mM) for 4 or 24 h. Cell viability was assessed using 3-(4, 5-dimethylthiazol-2-yl)2,5-diphenyl-tetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays. Mitochondrial membrane potential (MMP), caspase-3/7 activity, and autophagy markers were also evaluated. Synergy was analyzed using Combination Index (CI) analysis. Furthermore, mRNA levels of circadian rhythm associated genes were also evaluated. Results: 6-OHDA significantly impaired cell viability and mitochondrial function. Pretreatment with low doses of L-Dopa and safranal partially improved cell viability and reduced apoptosis and showed a tendency to decrease autophagy-associated marker levels. Higher L-Dopa concentrations caused mild cytotoxicity, while high-dose safranal exhibited pronounced concentration-dependent toxicity. CI analysis confirmed synergistic interaction between both drugs in mitigating 6-OHDA-induced toxicity. Combined treatment markedly improved cell survival preserved mitochondrial function, and reduced caspase-3/7 activity compared with monotherapy. A significant increase in the mRNA levels of Per1, Clock, Bmal1 and Cry1 genes was observed in groups treated with L-Dopa and safranal together. Conclusions: L-Dopa and safranal exerted concentration-dependent neuroprotective effects in SH-SY5Y cells. Their combination enhanced cytoprotection, which was associated with modulation of mitochondrial function, oxidative stress, apoptosis, and autophagy-related responses. Full article

Daylight Saving Time (DST) creates abrupt, externally imposed circadian disruptions that can impair sleep regulation, hormonal balance, cognitive performance, and emotional stability. Although these effects are known in the general population, individuals with chronic mental illness, whose circadian systems are often intrinsically dysregulated, may face increased neuropsychological consequences. This comprehensive review synthesizes evidence from chronobiology, psychiatry, neuroscience, and population health to examine how DST-related circadian misalignment impacts cognitive functioning, mood regulation, suicidality risk, and symptom exacerbation across psychological disorders such as depression, anxiety disorders, bipolar disorder, post-traumatic stress disorder, attention-deficit/hyperactivity disorder, and psychotic disorders. Following the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines, a search of PubMed, PsycINFO, Scopus, and Google Scholar was conducted to identify studies published from 2000–2026 examining DST, circadian rhythm disruption, neuropsychological outcomes, and chronic mental illness. Empirical, theoretical, and mechanistic studies were included to ensure comprehensive synthesis. Across conditions, DST, particularly spring forward transitions, is associated with increased sleep disturbance, impaired executive functioning, reduced attention and working memory, heightened emotional reactivity, increased depressive symptoms, elevated risk of manic episodes, and short-term increases in suicidality. Neurobiological mechanisms include altered melatonin secretion, cortisol dysregulation, Hypothalamus Pituitary Axis (HPA-axis) activation, and clock-gene desynchrony. DST may function as a modifiable negative environmental influence capable of affecting neuropsychological functioning in vulnerable populations. These findings underscore the need for clinical awareness, preventive strategies, and policy reconsiderations, including calls to eliminate seasonal time changes. Standardizing DST-related research outcomes and expanding longitudinal, multi-site studies will be essential for advancing this emerging field. Full article

Parkinson’s disease (PD) is traditionally defined by dopaminergic loss in the substantia nigra, yet its heterogeneous phenotypes and prodromal trajectories challenge a linear, dopamine-centered model. The α-synuclein origin and connectome (SOC) model proposes two major trajectories: a brain-first pathway, with the pathology initiating in limbic and brainstem structures and spreading ipsilaterally to the nigrostriatal system, and a body-first pathway, with the pathology originating in enteric and peripheral autonomic nerves before ascending to the brain. In this review, we integrate the SOC model into a broader framework, reconceptualizing PD as a progressive disorder of spatial–temporal symmetry. Spatial symmetry encompasses left–right and cranio-caudal balance of neural and musculoskeletal systems, whereas temporal symmetry denotes the coherence of biological rhythms from circadian and autonomic cycles, coupled with metabolic health and mitochondrial function, to sub-second timing governed by dopaminergic and basal ganglia–cortical network dynamics. We outline how systemic insulin resistance and mitochondrial stress erode temporal symmetry, while cranio-cervical malalignment and temporomandibular disorders perturb spatial symmetry. We discuss the neurobiological implementation of these symmetry axes via large-scale networks and dopaminergic modulation of spatial–temporal sensorimotor dynamics, framing PD as a multiscale symmetry-breaking process, and explore the implications for symmetry-oriented biomarkers, subtyping, and future interventions. Full article

Brain and muscle Arnt-like protein 1 (BMAL1) is a transcription factor that forms heterodimers with circadian locomotor output cycles kaput (CLOCK) and drives transcription from E-box elements, thereby regulating the circadian rhythms of gene expression. The kidney expresses numerous rhythmic genes and exhibits circadian physiological function regulation. Circadian rhythm abnormalities, such as sleep disorders and excessive daytime sleepiness, are particularly frequent in patients with chronic kidney disease (CKD). Furthermore, reduced amplitude and phase disruption in clock gene expression rhythms have been reported in mouse CKD models. These results suggest that circadian disruption is associated with renal pathophysiology. However, the role of BMAL1 in the repair process following acute kidney injury (AKI) remains unclear; therefore, this study aimed to elucidate its role in kidney repair following ischemia–reperfusion injury (IRI). We found that the tamoxifen (TAM)-inducible global Bmal1 knockout (BKO) mouse kidneys exhibited increased lipid accumulation, enhanced fibrosis, and delayed kidney repair post-IRI, and that these abnormalities were associated with reduced Peroxisome proliferator-activated receptor alpha (Pparα) expression. Furthermore, treatment with a PPARα agonist reduced these abnormalities in BKO mice. Collectively, our findings demonstrate that the BMAL1–PPARα axis promotes post-AKI kidney repair. Full article

Background: Augmented reality (AR)-based systems offer novel opportunities for digital support in physiotherapy and rehabilitation. This is especially relevant in the context of an aging population and the growing shortage of healthcare professionals. Methods: This study employed a user-centered design with iterative prototype refinement and investigated the perceived usability and user acceptance of a prototype AR-based sports therapy system (“STAR”), developed within an ongoing interdisciplinary research project, from the perspectives of patients and healthcare professionals across one iteration cycle. After an initial needs analysis (T0), participants interacted in an observer role with the system at two time points (T1, T2) using an AR headset (Microsoft HoloLens 2). They did not perform exercises but only interacted with the application by navigating through the system and viewing the exercise demonstrations. Between T1 and T2, a tutorial was integrated, exercise animations and voiceovers were revised, and voiceover controls and navigation were optimized. Usability was measured using the System Usability Scale (SUS), and user acceptance via the Technology Usage Inventory (TUI). Results: A total of 15 participants (10 patients and 5 therapists) completed both testing sessions. The average SUS score across both patients and therapists improved from 54.5 (SD = 18.8) to 71.2 (SD = 13.1), reflecting a statistically significant increase in perceived usability (p < 0.001). The usability rating improved from “ok” to “good” according to the SUS interpretation scale. The TUI subscales skepticism, immersion, accessibility and usability improved significantly, while interest, usefulness and intention-to-use only showed trend-level changes. Conclusions: The findings suggest that a user-centered development process can enhance the perceived usability and user acceptance of AR- based virtual care tools during the prototype stage by providing early-stage empirical evidence linking specific user-centered design interventions to changes in Technology Acceptance Model-related acceptance constructs. Full article

Sleep disorders, such as insomnia, obstructive sleep apnea (OSA), narcolepsy, REM sleep behavior disorder, and circadian rhythm disturbances, represent a rapidly expanding global health burden that is strongly associated with cardiovascular, metabolic, neurological, and psychiatric diseases. Advancements in wearable sensing technologies and Internet of Medical Things (IoMT) infrastructures have expanded the possibilities for continuous, home-based sleep assessment beyond conventional polysomnography laboratories. These Sleep Health Internet of Things (S-HIoT) systems combine multimodal physiological sensing (EEG, ECG, SpO₂, respiratory effort and actigraphy) with wireless communication and cloud-based analytics for automated sleep-stage classification and disorder detection. Nonetheless, the digitization of sleep medicine brings about significant cybersecurity concerns. The constant transmission of sensitive biomedical information makes S-HIoT networks open to anomalous traffic flows, signal manipulation, replay attacks, spoofing, and data integrity violation. Existing studies mostly focus on analyzing physiological signals and network intrusion detection independently, resulting in a systemic vulnerability of cyber–physical sleep monitoring ecosystems. With the aim of addressing this empirical deficiency, this review integrates emerging advances (2022–2026) in the AI-assisted categorization of sleep phases and IoMT anomaly detector designs on the finer analysis of CNN, LSTM/BiLSTM, Transformer-based systems, and a component part of federated schemes and the lightweight, edge-deployable intruder assessor models available. The aim of this study is to uncover a gap in the literature: integrated architectures to trade off audiences of faithfulness of physiological modeling with communication-layer security. To counter it, we present a single framework to include CNN-based spatial feature extraction, Bidirectional Long Short-Term Memory (BiLSTM)-based temporal models and Random Forest-based ensemble classification using a dual task-learning approach. We propose a multi-objective optimization framework to jointly optimize the performance of sleep-stage prediction and that of network anomaly detection. Performance on publicly available datasets (Sleep-EDF and CICIoMT2024) confirms that hybrid integration can be tailored to achieve high accuracy [99.8% sleep staging; 98.6% anomaly detection] whilst being characterized by low inference latency (<45 ms), which is promising for feasibility in real-time deployment in view of targeting edge devices. This work presents a comprehensive framework for developing secure, intelligent, and clinically robust digital sleep health ecosystems by bridging chronobiological signal modeling with cybersecurity mechanisms. Furthermore, it highlights future research directions, including explainable AI, federated secure learning, adversarial robustness, and energy-aware edge optimization. Full article

It is noteworthy that disturbances in circadian rhythms and irregular sleep patterns can exert influence over the onset of Type 2 Diabetes (T2DM). Similarly, they can impact the development of Type 1 Diabetes (T1DM). In recent decades, there has been a notable trend towards both reduced and extended sleep durations, with a concurrent rise in occurrences of compromised sleep quality attributable to sleep fragmentation. These sleep disturbances, along with clinically recognized sleep disorders such as sleep apnea and insomnia, have been increasingly associated with a range of detrimental health outcomes. Of particular concern is the growing evidence linking sleep dysregulation to an augmented risk of metabolic diseases, including diabetes. In addition to sleep duration and quality, emerging research suggests that an individual’s chronotype, reflecting their preferred time for going to sleep, may also exert an influence on disease development, particularly T2DM. The habit of going to bed late when compared to the tendency of going to bed early tends to cause significant disruptions to daily social engagements. Eventually, this misalignment may lead to discrepancies in sleep schedules between weekdays and weekends, commonly referred to as social jetlag. The current review aims to discuss the complex relationship between circadian rhythm misalignment, triggered by improper sleep habits such as short or long sleep duration, disrupted chronotype, social jetlag, and sleep disorders, on the subsequent impact on the development of diabetes. Overall, current evidence suggests that circadian rhythm disruption and sleep disorders contribute significantly to metabolic dysregulation and diabetes risk, highlighting the importance of sleep health in prevention and management of diabetes. Full article

SARS-CoV-2 infection is associated with not only acute respiratory symptoms but is also characterized by strong neurotropism which may contribute to the development of the multisystem post-COVID syndrome (PASC). Patients frequently report chronic neurocognitive disorders such as brain fog, significant attention deficits and increased susceptibility to epileptiform discharges. The aim of this review is to systematize the knowledge regarding deviations in quantitative electroencephalography (QEEG) recordings in convalescents and to evaluate the utility of this method as an objective biomarker. This work constitutes a comprehensive literature review integrating the latest data on neuroinflammation, blood-brain barrier damage and changes in cortical oscillatory dynamics induced by the infection. The literature analysis indicates that the virus may induce a pathological excitation and inhibition imbalance (E/I imbalance) in neuronal networks. In QEEG studies this manifests as excessive activity of slow bands (Theta, Delta), a deficit of rhythms responsible for attention and sensorimotor integration (SMR) and a pathologically elevated Theta to Beta ratio (TBR). In conclusion, QEEG can serve as an objective and highly sensitive tool supporting the diagnosis and stratification of patients with neurocognitive complications of Long COVID. The integration of precise electrophysiological phenotyping with targeted behavioral neuromodulation (e.g., EEG-Biofeedback) fits into the paradigm of personalized medicine and offers a prospective strategy for mitigating long-term neurological burdens. Full article

Background and Objectives: Cardiovascular disorders contribute substantially to medical ineligibility for compulsory military service in Lithuania. This study aimed to describe cardiovascular disease patterns and assess their association with military service eligibility among conscription-age individuals treated at a tertiary care center, considering gender, place of residence, age, and the most common cardiovascular causes of medical ineligibility. Materials and Methods: This retrospective hospital-based study included men and women aged 18–26 years with cardiovascular disease diagnoses defined according to ICD-10 codes specified by the Order of the Minister of National Defense of the Republic of Lithuania. Anonymized medical records from the Hospital of the Lithuanian University of Health Sciences Kaunas Clinics were reviewed. Participants were categorized into four military service eligibility classes based on medical history data and were stratified by gender, age, and place of residence. Results: The study included 521 participants (56.6% male, 43.4% female). Gender and residence showed no significant impact on military service eligibility. Younger individuals, particularly those aged 18–19, were more often deemed eligible, while eligibility declined with age. Males more commonly had essential hypertension and hypertensive heart disease, whereas females more frequently presented with paroxysmal tachycardia and other arrhythmias. Hypertension and other severe cardiovascular conditions most strongly reduced eligibility for compulsory military service, whereas rhythm disorders were more often compatible with service. Conclusions: In this hospital-based cohort of conscription-age individuals with cardiovascular disease, gender and place of residence did not significantly influence eligibility for military service. Eligibility declined with increasing age, and hypertension-related cardiovascular disorders were the leading cause of ineligibility among conscripts. Full article

Melatonin is reported to exert two types of actions: those based on its interaction with cognate receptors (characterized by very high affinities—1 nM and below), and those mediated by unknown targets (characterized by high concentrations—100 µM and above). Whereas receptor-mediated activities are known to regulate circadian rhythm, the high-dose effects are reported to be independent of these receptors and to produce literally dozens of beneficial effects in almost all human diseases, including cancer, neurodegenerative disorders, viral infections, obesity and many others. In the present opinion paper, we discuss this extensive set of claims and place them in perspective with a sum of evidence that collectively challenges the validity of these alleged beneficial effects. Full article

This comparative cross-sectional study simultaneously investigated the dual health burden of body mass index (BMI) and common mental disorders (CMDs) driven by occupational stressors in two stepwise regression models. By classifying stress exposure into three clinically relevant tiers (low, moderate, and severe) in two distinctive populations—a hospital and a manufacturing company—we used the validated SDS-30 and SRQ-20 instruments. The robust multiple regression models uncovered a highly nuanced landscape of employee well-being that highlights the context-dependent nature of psychosocial hazards. The most compelling findings emerged from the interaction analyses, which demonstrated that the physical and mental consequences of severe stress do not impact the workforce uniformly. Regarding mental health, severe occupational stress proved to be a potent catalyst for CMD symptoms, but this psychological toll was significantly magnified within the hospital sector relative to the manufacturing environment. An opposite, yet equally context-dependent, pattern emerged regarding physical health. In the main-effects-adjusted model, the severity of occupational stressors did not demonstrate a statistically significant linear association with an overall increase in BMI. However, the interaction model revealed a hidden vulnerability: employees in operational field roles who report severe stress are highly susceptible to severe BMI increases compared with admin personnel. While administrative staff may face sedentary risks, field workers under severe stress likely endure higher physiological allostatic load, erratic shift patterns that disrupt circadian metabolic rhythms, and potentially poorer dietary coping mechanisms during active labor. This combination of physical exhaustion and severe psychological tension severely disrupts metabolic homeostasis, forcing the redistribution of adipose tissue and driving the observed BMI spike. Full article

(1) Background: Recent studies indicated the prevalence of stress among students. The increased level of stress is concerning due to its association with cardiovascular diseases. This study examined stress within the academic setting and its effects on heart rate patterns, addressing a gap in analysis methods beyond heart rate variability. (2) Methods: The data were collected from 125 students at a large university in Texas who were highly likely to experience stress disorders. Students were asked to wear a smartwatch for the duration of an academic semester to report their stress events. (3) Results: A total of 1513 stress events were reported. The highest frequency of stress events was reported at the beginning of the week, particularly on Tuesdays, and mostly between 10 am and 6 pm. Results also showed significant increases in the number of significant lags, the number of peaks in autocorrelation plots, and the scaling exponent in DFA plots. This indicates persistent correlations in the heart rate data and less regular, less predictable heart rate patterns and rhythms than during non-stress moments. (4) Conclusions: Findings underscore the importance of using time series analysis to understand the complexities in heart rate rhythm associated with stress, with the potential to inform future stress monitoring capabilities. Full article

Sleep is tightly regulated by thermoregulatory processes that include core body temperature (CBT) modulation, the distal–proximal temperature gradient (DPG), and melatonin rhythms. In this review, we examine how these factors intersect with sleep physiology and contribute to the pathophysiology of common sleep disorders such as ADHD, insomnia, narcolepsy, Obstructive Sleep Apnea (OSA), depression, and Restless Legs Syndrome (RLS). We discuss evidence showing that delayed or disrupted CBT minima, impaired DPG, and altered melatonin secretion can prolong sleep latency, fragment rest, and lead to daytime symptoms. In addition, we explore temperature-based interventions, including foot baths, passive body heating, whole-body hyperthermia, and adjustments in room temperature, which have demonstrated potential to mitigate symptoms and enhance sleep quality. Collectively, these findings emphasize the need for personalized interventions to address thermoregulatory disruptions, presenting a noninvasive avenue for more effective sleep disorder management. Full article

Sleep is a cardinal biological process that backstops central nervous system function, which also plays a crucial role in regulating systemic homeostasis, including immune activities. Cytokines, particularly interleukin-1β and tumor necrosis factor-α, act as mediators bridging sleep and inflammation, also influencing both sleep architecture and sleep–wake cycle. Sleep deprivation and sleep disorders such as insomnia, narcolepsy, hypersomnia, or obstructive sleep apnoea may disrupt cytokine production, alter their circadian rhythm of release, and shift secretion peaks from night to day. These changes contribute to daytime fatigue, impaired cognitive and physical performance, increased susceptibility to infections and/or systemic inflammation. Molecular studies indicate that insufficient sleep primes immune cells to enhance pro-inflammatory responses, creating a feedback loop with neuroendocrine pathways that further exacerbates sleep patterns and inflammatory dysregulation. Understanding the bidirectional relationship between sleep and cytokines may highlight the role of sleep as an active component of immunity regulation and underscore the potential usefulness of multilevel interventions that include complementary and integrative health approaches restoring sleep, normalizing cytokine rhythms and mitigating inflammation. Full article

Singing-Oriented Language and Music Education (SOLME) is an accessible, low-resource pedagogical and cognitive framework in which singing serves as the primary interface through which musical activities support both first and foreign language acquisition processes. Early vocalizations in infancy make the overlap between singing and speech highly perceptible, forming a continuum rather than clearly separable domains. Child-directed speech similarly shares key features with singing—such as repetition, emotional engagement, exaggerated pitch variation and rhythm—and both input forms inherently combine musical and linguistic elements. Research has shown that the overlap between singing and language abilities persists throughout the lifespan, positioning singing as a valuable facilitator of language learning processes. Singing, integrated as a musical tool, has proven effective in enhancing key abilities for (foreign) language learning—including phonological awareness, pronunciation, and verbal memory, among others—and in supporting language functioning across diverse communication disorders, from developmental fluency challenges to acquired impairments. This entry outlines the benefits of singing as an integrated means to support musical development as well as first and second language acquisition processes. It outlines functional and structural similarities between singing and language development, from early caregiver–infant interaction to formal foreign-language instruction, and then discusses the many advantages of embedding singing as a musical tool in the (foreign) language learning process. Full article