Search Results (190)

Background: The brain is never truly at rest. Even in the absence of external tasks, it remains active, continuously organizing itself into large-scale resting-state networks involved in shaping our internal thoughts and experiences. Understanding the networks’ structure and dynamics is key to uncovering how the brain functions as a whole. While previous studies have mapped resting-state networks and explored the roles of individual brain regions (network vertices), the relevance of the time-dependent functional interactions (network edges) between them remains largely unexplored. Methods: Here, we assess this relevance by elucidating the time-evolving importance of both brain regions and their interactions, associated with the networks’ constituents, using the fundamental concept of centrality. We investigate long-term electrophysiological recordings of brain dynamics from more than 100 participants and reveal new insights into how resting-state networks are organized over longer times. Results: Our findings reveal that the functional architecture of brain networks in a resting state is critically shaped by the dynamic interplay between brain regions. We identified functional importance backbones–core sets of dynamically central vertices and edges–whose configuration varies significantly between subgroups and further varies with different brain states, including wakefulness and sleep. Notably, regions associated with the default mode network exhibited adaptable patterns of centrality, challenging the notion of static network cores. Conclusions: By considering the temporal evolution of both vertices and edges, we provide a more comprehensive understanding of intrinsic brain activity and its functional relevance. This dynamic perspective reveals how the brain’s intrinsic activity is coordinated across space and time, highlighting the existence of functional importance backbones that adapt to different brain states. Full article

Objectives: We aimed to identify clustering patterns of the device-measured physical activity (PA) levels (i.e., light PA and moderate-to-vigorous PA) and sedentary time (ST), screen time, sleep duration, and breakfast consumption of Spanish adolescents and their associations with the mode of commuting to and from schools (i.e., active and passive). Methods: A total of 151 adolescents aged 14.4 ± 0.6 years (53.64% girls) were included in this study. Participants wore an accelerometer device during seven consecutive days to measure PA levels and ST levels. Screen time, sleep duration, breakfast consumption, and the mode of commuting to and from school were self-reported by the participants. A two-step cluster analysis was performed to examine the different lifestyle behavior patterns (defined as data-driven groupings of daily behaviors identified through cluster analysis). Logistic regression models were used to determine the associations among the lifestyle behavior patterns and the mode of commuting to and from school. Results: The main characteristics of the three identified clusters were as follows: (active) high PA levels and low ST (38.4%); (inactive) high sleep duration and daily breakfast consumption, but low PA levels and high ST and screen time (37.2%); and (unhealthy) low PA levels and sleep duration, high ST and screen time, and usually skip breakfast (24.4%). No associations were found between these clusters and the mode of commuting to and from school (all, p > 0.05). Conclusions: Three different lifestyle behavior patterns were identified among Spanish adolescents, but no associations were found between these patterns and their mode of commuting to and from school. Full article

Background: Snoring and mild to moderate obstructive sleep apnoea (OSA) are common sleep-related breathing disorders with increasing demand for minimally invasive treatment options. This study aimed to systematically evaluate the efficacy and safety of erbium:yttrium–aluminium–garnet (Er:YAG) laser therapy for these conditions. Methods: A systematic review and meta-analysis were conducted in line with PRISMA guidelines. Studies published between 2015 and 2025 were retrieved from major biomedical databases based on predefined inclusion criteria. Data were extracted on treatment outcomes, laser parameters, patient characteristics, and adverse effects. Results: Fifty-six studies were included. Er:YAG laser treatment, particularly in non-ablative SMOOTH and long-pulse modes, significantly reduced snoring intensity and improved subjective sleep quality. High patient satisfaction (65–85%) and a favourable safety profile were observed, with adverse effects generally mild and transient. Therapeutic effects typically lasted 12–24 months, though 25–40% of patients required maintenance sessions. Treatment success was associated with BMI, oropharyngeal anatomy, smoking status, and baseline apnoea-hypopnoea index scores (AHI 5–30 events/hour). Conclusions: Er:YAG laser therapy appears to be a safe and effective short- to medium-term treatment for selected patients with snoring or mild to moderate OSA. Optimising patient selection and treatment protocols may enhance long-term outcomes. Based on moderate-quality evidence for the immediate effects and safety profile, but low to very low quality evidence for long-term outcomes, erbium:yttrium–aluminium–garnet laser treatment appears to be a potentially effective and well-tolerated option for achieving short- to medium-term improvement in carefully selected patients with primary snoring or mild to moderate obstructive sleep apnoea. The practical significance of these findings lies in the refinement of candidate selection criteria, laser parameter settings, and the development of optimal protocols for long-term snoring control. Full article

Background and Objectives: The common cold (acute rhinopharyngitis) and acute rhinosinusitis are highly prevalent conditions that significantly impact quality of life, often leading to nasal congestion, inflammation, and discomfort. Given the growing demand for non-pharmacological treatment options, particularly for vulnerable populations such as children and pregnant women, alternative therapies are increasingly being explored. NESOSPRAY HE-C, a nasal spray formulated with a glycerol-based filmogenic solution, acts by forming a protective osmotic film on the nasal mucosa. This mechanism facilitates mechanical cleansing, enhances decongestion, and reduces inflammation while preserving mucosal integrity. Its purely topical and mechanical mode of action provides a non-systemic alternative for symptom management. Materials and Methods: This randomized, double-blind, parallel-group clinical trial evaluated the efficacy and safety of NESOSPRAY HE-C (n = 29) compared to a placebo nasal spray (n = 26) in patients aged ≥ 3 years diagnosed with the common cold or acute rhinosinusitis. Participants had a baseline Rhinosinusitis Symptom Severity Score (RSSS) of ≥25/50. Treatment consisted of administering 2–3 sprays per nostril, four times daily, every 4 to 6 h, for up to 8 days or until symptom resolution. The primary outcomes included changes in total RSSS, Wisconsin Upper Respiratory Symptom Survey (WURSS) score, and individual symptom scores (rhinorrhea, nasal congestion, cough, poor sleep, facial pain, and fever). Safety assessments included adverse event monitoring and treatment tolerability, with subgroup analyses performed for children and pregnant women. Results: Baseline demographics were comparable between the treatment groups. NESOSPRAY HE-C demonstrated a significantly greater reduction in total RSSS from Day 3 onward (p = 0.0008), with sustained superiority through Day 8 (p < 0.0001). Significant improvements in rhinorrhea and nasal congestion were observed within 2 h of administration (p = 0.0089), while reductions in cough (p = 0.0052), poor sleep (p = 0.0005), and facial pain (p = 0.0111) emerged by Day 3. Fever reduction was most pronounced on Days 6 (p = 0.0001) and 8 (p = 0.0312), indicating a delayed but significant effect. In terms of the WURSS score, NESOSPRAY HE-C showed a significant improvement from Day 1, with a greater reduction in symptom severity compared to placebo. This trend of greater improvement continued through Day 8. The treatment was well tolerated, with no reports of serious adverse events or allergic reactions. Efficacy was consistent across all subgroups, including children, pregnant women, and adults. Conclusions: NESOSPRAY HE-C provides rapid and sustained symptom relief for the common cold and acute rhinosinusitis, serving as a safe and effective non-pharmacological alternative to conventional treatments. By leveraging its osmotic action and barrier-forming properties, it facilitates mechanical cleansing, enhances decongestion, and reduces inflammation while preserving mucosal integrity. Additionally, by forming a protective film on the nasal mucosa, it protects against future irritations, further supporting its role as a valuable therapeutic option, particularly for individuals seeking non-systemic symptom management. Full article

Electroencephalography (EEG) remains an essential method for monitoring brain activity, but the limitations of conventional systems due to the complexity of installation and lack of portability have led to the introduction and development of in-ear EEG technology. In-ear EEG is an emerging method of recording electrical activity in the brain and is an innovative concept that offers multiple advantages both from the point of view of the device itself, which is easily portable, and from the user’s point of view, who is more comfortable with it, even in long-term use. One of the fundamental components of this type of device is the electrodes used to capture the EEG signal. This innovative method allows bioelectrical signals to be captured through electrodes integrated into an earpiece, offering significant advantages in terms of comfort, portability, and accessibility. Recent studies have demonstrated that in-ear EEG can record signals qualitatively comparable to scalp EEG, with an optimized signal-to-noise ratio and improved electrode stability. Furthermore, this review provides a comparative synthesis of performance parameters such as signal-to-noise ratio (SNR), common-mode rejection ratio (CMRR), signal amplitude, and comfort, highlighting the strengths and limitations of in-ear EEG systems relative to conventional scalp EEG. This study also introduces a visual model outlining the stages of technological development for in-ear EEG, from initial research to clinical and commercial deployment. Particular attention is given to current innovations in electrode materials and design strategies aimed at balancing biocompatibility, signal fidelity, and anatomical adaptability. This article analyzes the evolution of EEG in the ear, briefly presents the comparative aspects of EEG—EEG in the ear from the perspective of the electrodes used, highlighting the advantages and challenges of using this new technology. It also discusses aspects related to the electrodes used in EEG in the ear: types of electrodes used in EEG in the ear, improvement of contact impedance, and adaptability to the anatomical variability of the ear canal. A comparative analysis of electrode performance in terms of signal quality, long-term stability, and compatibility with use in daily life was also performed. The integration of intra-auricular EEG in wearable devices opens new perspectives for clinical applications, including sleep monitoring, epilepsy diagnosis, and brain–computer interfaces. This study highlights the challenges and prospects in the development of in-ear EEG electrodes, with a focus on integration into wearable devices and the use of biocompatible materials to improve durability and enhance user comfort. Despite its considerable potential, the widespread deployment of in-ear EEG faces challenges such as anatomical variability of the ear canal, optimization of ergonomics, and reduction in motion artifacts. Future research aims to improve device design for long-term monitoring, integrate advanced signal processing algorithms, and explore applications in neurorehabilitation and early diagnosis of neurodegenerative diseases. Full article

Background: Chronic insomnia (CID) is a highly prevalent sleep disorder, yet the precise mechanisms underlying it remain incompletely understood. The aim of this study is to analyze effective connectivity between key regions of the default mode network (DMN), executive control network (ECN), and salience network (SN) in patients with CID as potential neurologic correlates of the hyperarousal state. Methods: Thirty-one CID patients and 24 healthy controls (HC) were recruited. All the subjects filled out the Insomnia severity index scale (ISI), Beck depression inventory (BDI), and Epworth sleepiness scale (ESS), underwent polysomnography, and were scanned on functional magnetic resonance imaging. Statistical Parametric Mapping 12 was used to analyze the results. Spectral dynamic causal modeling was applied to the chosen regions of interest. Results: There were three significant connections present in the CID group—inhibitory from the dorsolateral prefrontal cortex (DLPFC) to the right hippocampus (Hippocamp R); excitatory from the dorsomedial prefrontal cortex to the ventromedial prefrontal cortex; and excitatory from the common medial prefrontal cortex to the right anterior insula (AIR). Two statistically significant excitatory connections were lacking in the patients’ group—from the posterior cingulate cortex (PCC) to AIR, and from precuneus to PCC. CID patients scored higher on the ISI and BDI. Significant negative correlations between DLPFC-Hippocamp R connectivity and both ISI and BDI scores were identified. Conclusions: Disruptions within the DMN and between the DMN, SN, and ECN reflect an impaired ability to appropriately shift between internally and externally directed cognitive states—an imbalance that potentially underlies the hyperarousal state of CID. Full article

Wireless sensor networks face challenges such as energy consumption, scalability, security vulnerabilities, and communication range limitations, impacting their overall performance and reliability. To resolve these problems, energy-efficient protocols and adaptive sleep modes are implemented in wireless sensor networks (WSNs). Actually, LEACH clustering is widely regarded as one of the primary strategies to extend the lifetime of WSNs. However, clustering does not always guarantee optimal performance. In this paper, we demonstrate that clustering effectiveness is contingent on specific conditions related to several key parameters, including cluster density and the distance of nodes from the base station. Our research presents a mathematically validated analysis, supported by simulation results, that illustrates how clustering can enhance WSN performance, particularly in terms of network lifetime, throughput, and the timing of the first, middle, and last node deaths. Our findings indicate that LEACH is inefficient when nodes are within 80 m of the base station. Furthermore, clusters’ densities are related directly to the distance to the base station. Specifically, for distances less than 80 m, nodes should send their data individually; for distances between 83 and 123 m, a cluster density of two is most effective; and for distances between 123 and 149 m, the optimal density increases to three nodes. Full article

Background: Chinese Americans, the largest Asian American subgroup in the U.S., face linguistic, cultural, and socio-economic barriers to dementia prevention. To promote brain health in this population, a culturally tailored community approach is essential. This study evaluates a culturally tailored community brain health education program to enhance brain health knowledge and motivate lifestyle changes to prevent the risk of dementia among Chinese Americans aged 50 or older. Methods: The program was developed and evaluated in four phases. First, we assessed participants’ interests in brain health topics, availability, and preferred delivery modes. Next, experts on the identified topics developed educational content and outcome assessments. The third phase focused on implementing a six-session program covering general knowledge about Alzheimer’s disease and related dementias, diet, sleep, physical exercise, health checks, and mindfulness. Finally, we evaluated the program’s feasibility and effectiveness using pre–post surveys, feedback questionnaires, and focus groups. Results: Seventy-seven participants registered for the program, and sixty-nine (90%) attended at least four sessions. The quantitative results, based on paired t-tests, showed significant increases in brain health knowledge, sleep quality, and behavioral motivation for lifestyle changes, and a decrease in depressive symptoms, with two-tailed p-values lower than 0.05. The qualitative results further revealed promising feasibility and acceptability, as well as the perceived benefits of the program. Conclusions: The findings highlight the feasibility, acceptability, and potential effectiveness of a culturally tailored community education approach for promoting brain health and lifestyle changes. Sustained community outreach and education efforts among Chinese Americans are needed. Full article

Thermal comfort is not a luxury; rather, a lack of it is a matter of life and death, particularly for vulnerable people, such as older people. This work systematically reviews and analyses the thermal comfort of older people and their health and mortality as it relates to exposure to extreme temperatures, and suggests acceptable thermal conditions and the related energy use of buildings. A total of 69 out of 198 papers were found on older people and these were analysed in detail. This was followed by an analysis of the UN and UK governments’ open access data. This work highlights the disparity regarding the definition of age for older people and encourages the use of the term ”older people”, rather than ”elderly”, which can be an offensive piece of terminology. The UK findings suggest a significant relationship between cold (below 5 °C) outdoor air temperatures and mortality in older people, particularly for those who are over 85 years old. In the UK, thermal conditions can lead to up to 175 deaths per degree temperature change up to two weeks after a cold spell or an overly hot period. The indoor comfort temperature of older people varies between 22.5 and 27 °C in natural ventilation mode. However, some studies found 18 °C to be comfortable in winter time, a finding which could lead to a significant energy saving in relation to space heating. Current gaps in and the recommended future direction of research include topics such as gender differences in terms of thermal comfort and during menopause; thermal comfort conditions, adaptive behaviours and naturally ventilated buildings; thermal conditions when sleeping and energy use as it relates to space heating or cooling for older people. Full article

Background: Optimizing sedative techniques for drug-induced sleep endoscopy (DISE) enhances accuracy and reproducibility in tailoring treatment for obstructive sleep apnea (OSA). The Schnider and Eleveld pharmacokinetic–pharmacodynamic (PK-PD) models, which predict propofol concentration in effect-site compartment based on patient-specific parameters, were utilized to guide intravenous sedation in this study. We compared the effectiveness of propofol sedation guided by the novel general-purpose Eleveld model versus the Schnider model using target-controlled infusion (TCI) systems. Methods: We investigated twenty-five adult OSA patients, randomized into two groups: the Schnider model group (n = 12) and the Eleveld model group (n = 13). DISE was conducted following standardized protocols, targeting effect-site concentration TCI mode. Data concerning sedation levels, effect-site concentration of propofol, procedural timing, propofol dosages, respiratory and cardiovascular parameters, and any procedural incidents were collected. Results: DISE was performed successfully in all enrolled patients from both groups. A significant difference was observed in the effect-site concentration of propofol (CeP) at the moment of endoscopy between the Eleveld and Schnider groups (2.1 ± 0.4 µg/mL vs. 3.3 ± 0.7 µg/mL, respectively; p < 0.001). The E group also demonstrated a shorter time to attain the optimal sedation plane compared to the S group (6.1 ± 1.7 vs. 9.8 ± 2.2 min, respectively; p < 0.001) and a reduced total procedural time (11.2 ± 1.4 vs. 15.0 ± 2.1 min, respectively; p < 0.001). The incidence of adverse events was comparable between groups. Conclusions: The Eleveld model demonstrated a shorter time to achieve the optimal sedation plane, a shorter total procedural time, and a significant difference in effect-site concentration at the time of endoscopy compared to the Schnider model. The incidence of adverse events was comparable between the two groups, suggesting that the Eleveld model may offer improved efficiency without compromising safety during DISE. Full article

Electroencephalogram (EEG) signal analysis is crucial for understanding neural activity and advancing diagnostics in neurology. However, traditional signal decomposition (SD) techniques are hindered by two critical issues, mode mixing and mode aliasing, that compromise the quality of the decomposed signal. These challenges result in poor signal integrity, which significantly affects the accuracy of subsequent EEG interpretations and classifications. As EEG analysis is widely used in diagnosing conditions such as epilepsy, brain injuries, and sleep disorders, the impact of these shortcomings can be far-reaching, leading to misdiagnoses or delayed treatments. Despite extensive research on SD techniques, these issues remain largely unresolved, emphasizing the urgent need for a more reliable and precise approach. This study proposes a novel solution through the frequency-shifting variational mode decomposition (FS-VMD) method, which overcomes the limitations of traditional SD techniques by providing better resolution of intrinsic mode functions (IMFs). The FS-VMD method works by extracting and shifting the fundamental frequency of the EEG signal to a lower frequency range, followed by an iterative decomposition process that enhances signal clarity and reduces mode aliasing. By integrating advanced feature selection techniques and classifiers such as support vector machines (SVM), convolutional neural networks (CNN), and feature-weighted k-nearest neighbors (FWKNN), this approach offers a significant improvement in classification accuracy, with SVM achieving up to 99.99% accuracy in the 18-channel EEG setup with a standard deviation of 0.25. The results demonstrate that FS-VMD can address the critical issues of mode mixing and aliasing, providing a more accurate and efficient solution for EEG signal analysis and diagnostics. Full article

The regularity of sleep–wake cycles is a defining characteristic of normative sleep patterns that are typically associated with proper circadian rhythmicity. The previous literature indicates that consistent patterns of sleep and wake are associated with improved sleep quality and cognitive functioning. Conversely, sleep irregularity has been associated with reduced well-being and inefficiency in resting-state neural networks. This study investigated the relationship between specific sleep regularity measures and outcomes, including emotional affect, sleep quality, and resting-state functional connectivity. We found that variability in wake onset predicted poorer sleep quality and reduced positive affect. Furthermore, sleep regularity measures were associated with altered functional connectivity between the posterior cingulate cortex and regions involved in emotional processing. We propose that alterations in default mode network (DMN) connectivity linked to sleep irregularity reflect disruptions in emotional processing and sleep quality. Full article

The essential amino acid tryptophan yields a plethora of secondary metabolites with key roles in plants and animals. Its fate in different living organisms is crucial for their own health, and metabolic profiling is a valuable tool for investigating it. Among the various metabolites, those retaining the indole structure were examined for qualitative and quantitative profiling. Liquid chromatography coupled with a tandem mass spectrometry detector with an electrospray ionization source (HPLC-ESI-MS/MS), acquiring in multiple reaction monitoring (MRM) mode, was used to develop a selective and sensitive method for the simultaneous analysis of tryptophan and 10 indole structure-retaining metabolites of it. Satisfactory values were obtained for linearity (R² ≥ 0.99 for all compounds except two), sensitivity (LOD, within 6–31 ng/mL, and LOQ, within 17–94 ng/mL, where minimum and maximum values were relative to serotonin and 5-methoxytryptamin, respectively), reproducibility (interday and intraday precision and accuracy), and effect of the matrix (recovery and matrix effect). The method was then successfully applied to the analysis of different types of beverage, such as herbal products, like Eschscholzia californica and a sleep herbal tea marketed with added melatonin (consumed to reduce anxiety and improve sleep quality), and fermented beverages, like beer and kefir. High amounts of tryptophan (from 77 ng/mL in kefir to 26,974 ng/g in the sleep herbal tea) followed by lower contents of serotonin (from 29 ng/mL in kefir to 2207 ng/g in the sleep herbal tea), were found in all samples along with the serotonin pathway-related compounds 5-hydroxytryptophan and tryptamine. Melatonin was detected in the plant matrix Eschscholzia c. for the first time to our knowledge (446 ng/g) and in the fermented beverages (96 ng/mL in beer and 39 ng/mL in kefir), regardless of their vegetable or animal origin, along with the melatonin route metabolites 5-methoxytryptamine and tryptophan ethyl ester. The amount of melatonin in the sleep herbal tea (556,464 ng/g) was in strong agreement with the declared content. Suggested applications include the search for biomarkers in phytochemical characterization, mechanistic studies of tryptophan’s chemistry, valorization of foods, beverages, and tryptophan-rich agro-food by-products and waste for nutraceutical and pharmacological purposes. Full article

This study conducted a within-subject study to assess sleeping environmental comfort, acceptance, and self-reported sleep quality in air-conditioned and mixed-mode ventilated bedrooms in a subtropical region during the summer. A wide thermal comfort temperature range of 22.2 °C to 28.2 °C was observed, with slightly warmer thermal sensation at higher temperatures but no significant differences in sleep quality or environmental comfort acceptance within this range. Subjects adapted to warmer sleeping conditions by choosing lighter clothing and bedding insulation. Energy simulations indicated a reduction in the percentage of nights requiring cooling from 65% to 23% by increasing the set-point temperature from 22 °C to 28 °C, resulting in a potential 95% savings in cooling energy. This study advocates for an economical and energy-efficient approach to enhance sleeping thermal comfort while reducing cooling energy usage. These findings offer valuable insights for improved residential building design and optimized cooling energy management practices, especially in light of intensified climate change and the imperative for behavioral changes to promote building sustainability. Full article

Background: The four subtypes of G protein-coupled receptors (GPCRs) regulated by histamine play critical roles in various physiological and pathological processes, such as allergy, gastric acid secretion, cognitive and sleep disorders, and inflammation. Previous experimental structures of histamine receptors (HRs) with agonists and antagonists exhibited multiple conformations for the ligands and G protein binding. However, the structural basis for HR regulation and signaling remains elusive. Methods: We determined the cryo-electron microscopy (cryo-EM) structure of the H4R-histamine-Gi complex at 2.9 Å resolution, and predicted the models for all four HRs in the ligand-free apo and G protein subtype binding states using AlphaFold3 (AF3). Results: By comparing our H4R structure with the experimental HR structures and the computational AF3 models, we elucidated the distinct histamine binding modes and G protein interfaces, and proposed the essential roles of Y^6.51 and Q^7.42 in receptor activation and the intracellular loop 2 (ICL2) in G protein bias. Conclusions: Our findings deciphered the molecular mechanisms underlying the regulation of different HRs, from the extracellular ligand-binding pockets and transmembrane motifs to the intracellular G protein coupling interfaces. These insights are expected to facilitate selective drug discovery targeting HRs for diverse therapeutic purposes. Full article