BackgroundChronic insomnia is a prevalent and disabling condition associated with impaired daytime functioning, psychiatric comorbidity, and autonomic dysregulation. Although cognitive behavioral therapy for insomnia (CBT-I) is recommended as the first-line treatment, access is limited. Acupuncture has demonstrated therapeutic benefits for insomnia but requires trained practitioners and repeated clinic visits. Low-level laser therapy (LLLT), an acupoint-targeted form of photobiomodulation that is also referred to as laser acupuncture when applied to acupuncture points, offers a non-invasive and standardized modality that may serve as a practical alternative.MethodsThis single-center, parallel-group, assessor-blinded, superiority randomized controlled trial will compare wearable LLLT with manual acupuncture in 106 adults with chronic insomnia. Participants aged 18–65 years who meet DSM-5 criteria for chronic insomnia and have an Insomnia Severity Index (ISI) score between 8 and 21 will be randomly allocated (1:1) to the LLLT group or acupuncture group. Both interventions will target bilateral HT7, PC6 and SP6 (six acupoints in total) for 30 minutes per session, three times per week, over two weeks (six sessions total). In the LLLT group, 650-nm laser irradiation will be delivered simultaneously to all six acupoints. The primary outcome is the change in ISI score from baseline to week 2. Secondary outcomes include sleep quality (Pittsburgh Sleep Quality Index, PSQI), fatigue (Fatigue Severity Scale, FSS), depressive symptoms (Patient Health Questionnaire-9, PHQ-9), anxiety (Generalized Anxiety Disorder-7, GAD-7) and heart rate variability (HRV) indices. The ISI will be assessed at baseline, post-treatment (week 2), and follow-up (week 6). Secondary outcomes, including PSQI, FSS, PHQ-9, GAD-7, and HRV indices, will be assessed at baseline and week 2. Analyses will follow the intention-to-treat principle using analysis of covariance and prespecified longitudinal or repeated-measures models where appropriate.DiscussionThis trial will provide comparative evidence on the short-term efficacy and safety of wearable LLLT versus manual acupuncture for chronic insomnia. By directly comparing an established acupuncture protocol with a non-invasive intervention that has potential for future home-based implementation, the study aims to clarify the clinical value of LLLT as a less invasive alternative within the framework of complementary and integrative sleep medicine.Clinical trial registrationhttps://itmctr.ccebtcm.org.cn/Home/ProjectView?pid=d0e46c39-0647-4cbd-ba40-e2b02830fd28, identifier ITMCTR2025000977.
Identification of Physiological Sleep Indices That Reflect Clinical Improvement and Reduction in Stress Biomarkers After Stellate Ganglion Block in Patients With Posttraumatic Stress Disorder (PTSD)
Conditions: Post Traumatic Stress Disorder
Interventions: Procedure: Stellate ganglion block
Sponsors: sara dichtwald
Not yet recruiting
Interventions: Procedure: Stellate ganglion block
Sponsors: sara dichtwald
Not yet recruiting
<![CDATA[ASPIRE survey reveals fatigue and cognitive impairment reduce work abilities and quality of life in narcolepsy and idiopathic hypersomnia, exposing unmet needs.]]>
Neuronal Protein Tracing Reveals How the Brain Routes Its Waste
The brain is one of the busiest organs in the body, constantly processing and reshaping itself. That activity produces an equally constant stream of molecular byproducts—proteins that need to be moved out before they accumulate. When those clearance routes slow or break down, waste lingers, and the consequences can be profound. In Alzheimer’s disease, for example, toxic proteins build up in vulnerable regions. Yet despite decades of research, scientists have lacked a clear view of how waste normally leaves the brain.
A new study from the Gladstone Institutes offers the clearest picture yet of how the brain normally takes out its trash—and what happens when those routes fail. Published in Cell as “Physiological brain clearance architecture revealed by neuronal protein tracing,” the work introduces a method that traces waste proteins from the moment they are produced inside neurons to the moment they leave the brain.
For decades, researchers have relied on injecting tracers into the cerebrospinal fluid (CSF) to visualize drainage. But this approach, while illuminating, shows all possible routes, instead of pinpointing the most-used exit. “These injected tracers disturb the very system we’re attempting to measure,” said lead author Andrew Yang, PhD, a Gladstone investigator. “We wanted to find a better way.”
Yang’s team engineered neurons in mice to produce a fluorescent protein, ZsGreen, that could be followed as it exited the brain through its natural routes. This allowed the researchers to track waste as it moved into the dura, skull, nasal cavity, and lymph nodes—regions populated by specialized immune cells that interact with brain‑derived proteins.
The resulting map diverged sharply from the field’s long‑held assumptions. Traditional CSF tracers had pointed to the cervical lymph nodes as a major drainage site. But the new method revealed that very little neuronal waste actually reaches those nodes. “We were surprised to find that very little ZsGreen drained to the cervical lymph nodes,” Yang said. “Instead, waste drained through the dura, skull, and nasal cavity. Our findings underscore why tracking waste proteins themselves, rather than movement of the cerebrospinal fluid, provides a more accurate understanding of waste clearance dynamics.”
The team also uncovered a striking organizational principle: where a protein is made determines where it drains. Proteins produced in upper forebrain regions exited through upper routes, while those from deeper structures, such as the striatum, used lower pathways. The researchers call this the brain’s “nearest‑exit” model. “It’s like each brain region has a biological ZIP code system to ensure waste will be sent to the correct drainage site,” said Nalini Rao, PhD, a postdoctoral fellow. She noted that in aging or disease, these ZIP codes may become scrambled, potentially explaining why certain regions are more vulnerable to disorders like Alzheimer’s.
Disease models reinforced the system’s fragility. In mice with acute inflammation, ZsGreen leaked directly into the bloodstream, bypassing normal routes. In an Alzheimer’s model, waste became trapped inside the brain, unable to drain effectively. “Understanding how diseases disrupt brain clearance could help us design therapeutics to target the brain border compartments and enhance waste removal,” Rao said.
With their new tracing method, Yang’s group plans to probe how clearance changes across aging, sleep, and disease—and whether brain tumors exploit these pathways to evade immune detection. The architecture of brain waste disposal, once opaque, is now open for exploration.
The post Neuronal Protein Tracing Reveals How the Brain Routes Its Waste appeared first on GEN – Genetic Engineering and Biotechnology News.
Emotion recognition based on the temporal patterns of electroencephalogram signals and electrodermal response signals using the TRANSFORMER network
IntroductionEmotion recognition using physiological signals plays an important role in affective neuroscience and human-centered artificial intelligence. Current methods still face challenges in long-range temporal dependency modeling and explicit central–autonomic coupling representation, while generalization under subject-independent protocols needs further improvement.MethodsThis study proposes a Transformer-based multimodal framework for four-class discrete emotion recognition (neutral, happiness, sadness, and fear) by jointly modeling EEG and GSR signals. The architecture integrates temporal self-attention and bidirectional cross-modal attention. Experiments were conducted on 42 neurologically healthy adults with a controlled audiovisual emotion elicitation paradigm, evaluated using subject-independent five-fold cross-validation.ResultsThe model achieved a mean classification accuracy of 87.42% ± 2.13%, with precision of 87.6%, recall of 87.4%, and F1-score of 87.5%. It outperformed CNN and Bi-LSTM baselines by 4.91% and 6.38%, respectively. Multimodal fusion significantly boosted high-arousal emotion recognition, with fear accuracy increasing from 82.11% (EEG-only) to 88.63% (p = 0.004).DiscussionThese findings confirm that long-range temporal modeling and explicit cross-modal interaction can substantially improve multimodal physiological emotion recognition. The proposed framework is scalable and interpretable, advances central–autonomic coupling modeling, enhances generalization via strict subject-independent validation, and supports physiological interpretability through attention visualization and modality sensitivity analysis.
Leveraging Synchrosqueezing Transform (SST)-based representations in a dual-stream attention framework to enhance sleep apnea detection and subtyping
IntroductionSleep apnea and hypopnea syndrome (SAHS) is a prevalent disorder with profound adverse effects on health and overall quality of life, thereby necessitating the development of accurate and accessible screening tools. Electrocardiogram (ECG)-based analysis, being non-invasive and readily deployable in low-cost hardware, offers a particularly convenient approach for SAHS screening and preliminary diagnosis. However, conventional time-frequency analysis often fails to capture the subtle yet critical patterns in ECG signals due to the Heisenberg uncertainty principle, leading to limited resolution and information loss.MethodsTo overcome these limitations, this study proposes a Dual Stream Cross Attention Fusion Network (DSCAFNet) based on the uncertainty-mitigated time-frequency representations generated via Synchrosqueezing Transform (SST). The framework uniquely constructs two complementary, high-fidelity SST-based representations, which are strategically designed to provide distinct yet synergistic perspectives on the complex, non-stationary dynamics of SAHS. A dedicated cross-attention fusion module then harnesses these complementary views, enabling the model to discriminatively integrate multi-resolution features for significantly enhanced pattern recognition.ResultsExtensively evaluated on the public Apnea-ECG dataset, DSCAFNet achieves an accuracy of 0.9572, a sensitivity of 0.9575, a specificity of 0.9584, and an F1-score of 0.9557, performing on par with state-of-the-art methods. More importantly, rigorous validation on a private Huashan-apnea dataset yields an accuracy of 0.9003 for binary classification and 0.7564 for four-class subtyping, demonstrating strong effectiveness and generalization.ConclusionThese consistent results across datasets highlight DSCAFNet as a promising framework for intelligent and accessible SAHS screening, with potential for integration into portable data acquisition systems combined with cloud-based analysis.
Sleep-related problems among patients with rheumatoid arthritis in the World Health Organization Eastern Mediterranean region: a systematic review and meta-analysis
BackgroundSleep-related problems are common among patients with rheumatoid arthritis (RA) and contribute substantially to disease burden and reduced quality of life. Evidence from the World Health Organization Eastern Mediterranean Region (WHO EMRO) remains fragmented, with variability in reported prevalence, sleep constructs assessed, and associated risk factors. This study aimed to systematically review and meta-analyze the prevalence and correlates of sleep-related problems among adults with RA in WHO EMRO countries.MethodsA systematic search of PubMed, Scopus, Web of Science, Embase, CINAHL, and Google Scholar was conducted to identify observational studies reporting sleep-related outcomes among adults (≥18 years) with RA in WHO EMRO countries from inception to 27 July 2025. Study screening, data extraction, and quality appraisal using Joanna Briggs Institute (JBI) checklists were conducted primarily by a single author, with methodological oversight and consultation from senior collaborators. Eligible studies reported prevalence or sufficient data to calculate prevalence of specific sleep-related constructs, including subjective sleep quality, insomnia symptoms, daytime sleepiness, or obstructive sleep apnea. Random-effects meta-analysis (DerSimonian-Laird) was used to pool prevalence estimates and odds ratios (ORs) for associated risk factors. Heterogeneity was assessed using the I² statistic and Cochran’s Q test. Subgroup analyses were conducted by sleep construct, assessment method, and country. Publication bias was evaluated using funnel plots, Egger’s test, and Begg’s test, with cautious interpretation due to the small number of studies.ResultsTen studies met inclusion criteria for qualitative synthesis, and six studies (n = 2,315 participants) were included in the quantitative meta-analysis. The pooled prevalence of sleep-related problems was 60.9% (95% CI: 56.5%–65.2%), with substantial heterogeneity (I² = 88%, p < 0.001), reflecting differences in sleep constructs and assessment methods. Subgroup analyses yielded pooled prevalence estimates of 58% for insomnia symptoms, 65% for obstructive sleep apnea-related measures, and 61% for poor subjective sleep quality (PSQI above cut-off), with no statistically significant differences between subgroups. Among associated factors, depression showed the strongest association with sleep-related problems (OR = 2.65; 95% CI: 1.87–3.75), followed by pain (OR = 2.18; 95% CI: 1.68–2.84), fatigue (OR = 1.91; 95% CI: 1.45–2.52), female gender (OR = 1.67; 95% CI: 1.25–2.23), and older age (OR = 1.42; 95% CI: 1.12–1.80). Heterogeneity for risk factor analyses ranged from low to moderate. Publication bias assessments did not indicate statistically significant small-study effects but were underpowered.ConclusionSleep-related problems—assessed using heterogeneous subjective and objective measures—are highly prevalent among patients with RA in WHO EMRO countries with available data. Given substantial clinical and methodological heterogeneity and the limited number of contributing countries, findings should be interpreted as reflecting overall sleep-related burden rather than the prevalence of a single clinical disorder. Routine screening, multidisciplinary management, and culturally adapted interventions are recommended. Future large-scale, longitudinal studies using standardized diagnostic criteria across a broader range of WHO EMRO countries are needed to strengthen the evidence base.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/view/CRD420251109906, identifier CRD420251109906.
<![CDATA[At the 2026 ASCP Annual Meeting, Eric Konofal, MD, PhD, argued that sleep assessment should become a routine part of ADHD evaluation and treatment.]]>
Transient multidomain functional improvement in advanced Alzheimer’s disease following high-dose psilocybin-containing mushroom administration: a case report
BackgroundAdvanced Alzheimer’s disease (AD) is generally regarded as a stage of irreversible functional decline. Psilocybin is known to transiently alter large-scale brain network dynamics and to induce plasticity-related mechanisms in preclinical models, yet clinical data in advanced dementia remain lacking.Case presentationWe report the case of an octogenarian Japanese-American woman with a 10-year history of Alzheimer’s disease, including 5 years of marked hypofunction and predominantly monosyllabic speech. Baseline features included chronic urinary incontinence, executive dysfunction, dysphagia, dependent mobility, flat affect, and severe reduction in spontaneous communication. The patient received 5 g of orally administered psilocybin-containing mushrooms (Enigma strain). The acute phase was marked by autonomic activation, clinically suspected hyperthermia, profuse sweating, and a prolonged deep sleep-like state. Approximately 19 h post-administration, spontaneous autobiographical speech emerged. Over subsequent days and weeks, functional improvements included restoration of urinary continence, improved ambulation, autonomous dressing, increased emotional responsiveness, sustained social interaction, contextual memory retrieval, preserved working memory for social context, and spontaneous conversational engagement.ConclusionThis case documents transient multidomain functional improvement in advanced Alzheimer’s disease following psilocybin administration. The findings do not imply disease reversal but suggest that residual functional capacity may persist in late-stage neurodegeneration and may become transiently accessible under specific neuromodulatory conditions.
Non-invasive electrical stimulation for sleep disturbances in adults: protocol for an evidence−mapping umbrella review of systematic reviews and meta−analyses with subgroup analysis by intervention type and population
BackgroundSleep disturbances affect 10%–30% of adults worldwide. Non−invasive electrical stimulation (e.g., transcranial electrical stimulation) has emerged as a promising non−pharmacological intervention. Although numerous systematic reviews and meta−analyses have been published, they vary considerably in methodological quality, populations, intervention types, and conclusions. No umbrella review has yet synthesised the evidence across different modalities and populations. This evidence mapping umbrella review aims to systematically chart the existing systematic reviews, assess methodological quality, quantify overlap, and describe evidence patterns across diverse modalities and populations.MethodsFollowing JBI guidelines, we will search PubMed, Embase, Cochrane Database of Systematic Reviews, Web of Science, PsycINFO, and Scopus (inception to April 2026), restricted to English. Grey literature will be searched via PROSPERO, ClinicalTrials.gov, Google Scholar (first 200 records), and reference list screening (snowballing). We will include systematic reviews and meta−analyses of randomised controlled trials evaluating any non−invasive electrical stimulation for sleep outcomes. Two reviewers will independently screen, extract data, and assess methodological quality using AMSTAR 2. Primary study overlap will be quantified by the Corrected Covered Area. Where feasible, we will calculate 95% prediction intervals, perform Egger’s regression tests, and conduct excess significance tests using review-level summary estimates. Subgroup analyses will be stratified by intervention and population type. Sensitivity analyses will exclude: (1) reviews with critically low AMSTAR 2 ratings, (2) preprints, (3) reviews at high risk of reporting bias, and (4) studies where sleep is not the primary outcome. The primary outcome is subjective sleep quality; total sleep time is a key secondary outcome. Evidence will be graded using the Fusar−Poli classification, with GRADE for key outcomes.DiscussionThis umbrella review will provide the highest level of evidence synthesis, identifying modalities with more consistent or higher certainty evidence and highlighting areas where evidence remains uncertain. Limitations include restriction to English (which may disproportionately impact modalities such as TEAS), expected heterogeneity, and possible insufficient data for some subgroup analyses. All amendments have been documented in PROSPERO (CRD420261357590).Clinical Trial Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD420261357590.