Search Results (299)

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had major social and economic consequences worldwide. Whole genome sequencing (WGS) is essential for genomic monitoring, enabling tracking of viral evolution, detection of emerging variants, and identification of introductions and transmission chains to inform timely public health responses. Here, we compile and harmonize SARS-CoV-2 genomic data generated by multiple laboratories across Kazakhstan together with publicly available sequences to provide a national overview of genomic dynamics across successive epidemic waves from 2020 to 2022. We analyzed 4462 genomes deposited in GISAID (including 340 generated in this study), of which 3299 passed Nextclade quality filters, and summarized lineage turnover across major phases (pre-VOC, Alpha, Delta, Omicron BA.1/BA.2, Omicron BA.4/BA.5, and a later recombinant-dominant period). Sequencing intensity varied markedly over time (0.60‰ of confirmed cases during Delta vs. 11.57‰ during the Omicron BA.5 wave), suggesting that lineage diversity and persistence may be underestimated. Pre-VOC circulation included ≥12 Pango lineages with evidence of multiple introductions and sustained local transmission, including a Kazakhstan-restricted B.4.1 lineage that emerged in Nur-Sultan/Astana and disappeared after April 2020. The Tengizchevroil oilfield outbreak comprised B.1.1 viruses with phylogenetic support for ≥three independent introductions. Alpha and Omicron waves were characterized by repeated introductions and heterogeneous origins, whereas Delta was dominated by AY.122 with an additional distinct AY.122 cluster; a notable BF.7 local transmission event was observed during BA.5. We also highlight locally enriched non-lineage-defining mutations. Overall, recurrent importations and variable local amplification shaped SARS-CoV-2 dynamics in Kazakhstan, while interpretation is constrained by strongly time-skewed sequencing. Full article

Developmental Language Disorder (DLD) is associated with abnormalities in both intrinsic resting-state brain networks and task-evoked neural responses, yet direct electrophysiological evidence linking these levels remains limited. This study examined multi-level EEG markers in 21 typically developing children and 15 children with DLD across resting-state, a semantic matching task, and an auditory oddball task. Resting-state analyses revealed frequency-specific connectivity imbalances, reduced stability of intrinsic microstate dynamics, and atypical transitions between microstates in the DLD group. During the semantic matching task, DLD children showed weaker occipital P1 and N2 responses (100–300 ms) and lacked the right fronto-central difference wave (500–700 ms) observed in TD children. In the auditory oddball task, DLD children exhibited high-theta/low-alpha event-related desynchronization at left frontal electrodes (400–500 ms), in contrast to TD children. A machine learning framework integrating resting-state and task-based features discriminated DLD from TD children (test-set F1 = 70.3–80.0%) but showed limited generalizability, highlighting the constraints of small clinical samples. These findings support a translational neurophysiological signature for DLD, in which atypical intrinsic network organization constrains emergent neural computations, providing a foundation for future biomarker development and targeted intervention strategies. Full article

COVID-19 has raised significant concern regarding its neurological impact, particularly during the early pandemic waves when severe systemic inflammation and neuroimmune dysregulation were more common. Although SARS-CoV-2 has been extensively studied, the precise mechanisms underlying its neurological effects remain incompletely understood, and much of the available evidence is derived from early variants with higher pathogenicity. Current research indicates that neuroinflammatory processes—driven primarily by systemic cytokine elevation, microglial activation, and blood–brain barrier dysfunction—contribute to a wide range of neurological symptoms. Severe complications such as encephalopathy, stroke, and cognitive impairment were predominantly reported in critically ill patients infected with the Wuhan, Alpha, or Delta variants, while such manifestations are considerably less frequent in the Omicron era. Most proposed mechanisms, including ACE2-mediated viral entry into the central nervous system, are supported mainly by experimental or preclinical studies rather than definitive human evidence. Biomarkers such as IL-6 and TNF-α, along with neuroimaging modalities including MRI and PET, offer useful but indirect indicators of neuroinflammation. Therapeutic approaches continue to focus on controlling systemic inflammation through immunomodulatory agents, complemented by targeted non-pharmacological strategies—such as physical rehabilitation, cognitive support, and psychological interventions—for the minority of patients with persistent neurological deficits. Overall, current evidence supports a variant-dependent neuroinflammatory profile and underscores the need for longitudinal, mechanism-focused studies to better characterize long-term neurological outcomes and refine therapeutic strategies. Full article

Dam break problem-induced floods can trigger hazardous dike overtopping, demanding predictions that are fast, accurate, and interpretable. We pursue two objectives: (i) introducing a new alpha evolution (AE) optimization scheme to improve tree-model predictive accuracy, and (ii) developing a cluster-wise modeling strategy in which regimes are defined by wave characteristics. Using a dataset generated via physical model experiments and smoothed particle hydrodynamics (SPH) numerical simulations, we first group samples via hierarchical clustering (HC) on the Froude number $\left(\mathrm{Fr}\right)$, wave nonlinearity $\left(R\right)$, and relative distance to the dike $\left(D\right)$. We then benchmark CatBoost, XGBoost, and ExtraTrees within each cluster and select the best-performing CatBoost as the baseline, after which we train standard CatBoost and its AE-optimized variant. Under random train–test splits, AE-CatBoost achieves the strongest generalization for predicting relative run-up distance $H_m$ (testing dataset $R^2=0.9803$, $\mathrm{RMSE}=0.0599$), outperforming particle swarm optimization (PSO) and grid search (GS)-tuned CatBoost. We further perform TreeSHAP analyses on AE-CatBoost for global, local, and interaction attributions. SHAP analysis yields physics-consistent explanations: D dominates, followed by H and L, with a weaker positive effect of $\mathrm{Fr}$ and minimal influence of R; $H\times D$ is the strongest interaction pair. Overall, AE optimization combined with HC-based cluster-wise modeling produces accurate, interpretable overtopping predictions and provides a practical route toward field deployment. Full article

Background/Objectives: Recently, the importance of physical activity for health promotion has increased the demand for physical activities performed in natural environments. However, environmental characteristics that enhance the efficiency of physical activities and contribute to health promotion have not yet been established. This study aimed to verify the mental and physical health of walking in different environments by measuring EEG and HR responses among middle-aged women living in urban areas during forest trail (GU) and school ground (NF) walking. Methods: In total, 30 middle-aged women participated in a 1.5 km walking, with HR measured during normal, NF, and GU walking. EEGs were recorded before and after walking 5 waves (Delta, Theta, Alpha, Beta, and Gamma). All data were collected under standardized conditions and analyzed using paired t-tests. Results: Alpha, beta, and gamma waves increased after GU walking (p < 0.001) but decreased after NF walking, suggesting that walking in natural environments promotes emotional stability, attentional recovery, and cognitive activation. Mean HR during GU was higher than during NF (p < 0.001), and NF walking corresponded to moderate-intensity exercise, whereas GU walking represented vigorous-intensity activity, likely influenced by its 5% slope and multi-sensory natural stimuli such as forest, sounds, and air quality. Conclusions: This study is not a clinical trial but a health experiment of physical activity, highlighting how walking in natural environments can contribute to improved health. The walking environment elicits distinct mental and physical responses, and forest walking has proven to be more effective in improving health. This result highlights the value of nature-based exercise spaces accessible in urban environments and can help with design and health policies. Full article

Retinal ischemia is a key factor in the progression of vision-threatening ocular diseases, including central retinal artery/vein occlusion, exudative age-related macular degeneration (eAMD), and proliferative diabetic retinopathy. This study investigates the effects of paeoniflorin along with its related neuroprotective molecular pathways in the treatment of retinal ischemia. Free radical or ischemic-like damage was induced by incubating retinal pigment epithelium (RPE) cells for 24 h with 1 mM hydrogen peroxide (H₂O₂) or by subjecting retinal neuronal cells to 8 h of oxygen–glucose deprivation (OGD). Both treatments caused significant cell loss. Treatment with paeoniflorin significantly increased cell viability at 0.5 mM in both cell types. In a Wistar rat model of retinal ischemia and reperfusion (I/R) elicited by sustained high intraocular pressure (HIOP), pre-treatment with 0.5 mM paeoniflorin mitigated the ischemia-induced decline in ERG b-wave amplitude, reduction in whole and inner retinal thickness, loss of fluorogold-labeled retinal ganglion cells, and formation of apoptotic cells. Meanwhile, paeoniflorin effectively downregulated pro-neovascular mediators β-catenin, hypoxia-inducible factor 1-alpha (HIF-1α), vascular endothelial growth factor (VEGF), and the pro-inflammatory/angiogenic biomarker angiopoietin-2 (Ang-2), producing effects similar to the Wnt/β-catenin inhibitor (dickkopf-related protein 1), anti-angiogenic pigment epithelium-derived factor (PEDF), and anti-VEGF Avastin (bevacizumab). These findings suggest that paeoniflorin may protect against retinal ischemia through its anti-inflammatory, anti-neovascular/angiogenic, antioxidative, and neuroprotective properties. Full article

Background: The Delta variant of SARS-CoV-2 virus, one of the alarming variants of concern (VOC) with a distinct mutation characteristic, was immensely detrimental and a significant cause of the prolonged pandemic waves. This study aimed to analyze the genetic characteristics of the predominant Delta variant in acute febrile illness (AFI) patients in Ethiopia. Method: Nasopharyngeal swab samples were collected from AFI patients in four hospitals from February 2021 to June 2022 and tested for SARS-CoV-2 by using RT-qPCR. Of 101 positive samples, 48 stored specimens were re-tested, and 26 with sufficient RNA quality (Ct < 30) were sequenced using whole-genome sequencing to identify variants of concern, specific virus lineages and mutation features. Result: Delta variants (21J clade) were found predominant among all the sequenced SARS-CoV-2 isolate (80.8%, 21/26). AY.120 (46.2%) and B.1.617.2 (26.9%) were the predominant sub-lineages of the Delta variant. Omicron (21k, Pango BA.1.1/BA.1.17/BA.1) and Alpha (20I, Pango B.1.1.7) variants accounted for 11.5% and 7.7% of the total sequenced samples. Phylogenetic analysis showed evidence of local transmission and possible multiple introductions of SARS-CoV-2 VOCs in Ethiopia. The number of mutations increases dramatically from Alpha (~35 avg) to Delta (~42 avg) to Omicron (~56 avg). The Delta variant revealed a spike mutation on L452R and T478K and P681R, and was characterized by the double deletion E156-F157- in Spike protein. Conclusions: The findings are indicative of a gradual change in the genetic coding of the virus underscoring the importance of ongoing genomic surveillance to track the evolution and spread of SARS-CoV-2 and other emerging virus. Full article

GNAO1 is an alpha subunit of the G-protein complex involved in signal transduction in neurons. The G203R mutation in the GNAO1 gene arises recurrently de novo and causes epileptic encephalopathy and movement disorder. GNAO1 has two main isoforms, GNAO1-A and GNAO1-B, but their functional or expression differences are poorly understood. Molecular functions of GNAO1 are mainly studied in neurons, yet glial cells also express GNAO1 and participate in the pathogenesis of epilepsy. Here, we used human-induced pluripotent stem cell-based models to investigate the localization and expression of GNAO1 isoforms in astrocytes. We showed that in astrocytes, almost 100% of GNAO1 transcripts encoded GNAO1-B with very low GNAO1-A expression. We showed that there were no differences in localization between GNAO1-A and GNAO1-B, both in WT and G203R states. We also showed that GNAO1 localized in astrocytic retraction fibers and migrasomes, structures not previously described in this cell type. We showed that GNAO1-positive retraction fibers of neighboring cells provided cell-to-cell contacts and also provided calcium waves during astrocytic excitation. Overexpression of both GNAO1-A and GNAO1-B tends to lower calcium activity in astrocytes, with GNAO1-A providing the most severe impairment of activity. Our results demonstrate that astrocytes, in addition to neurons, should be used as a model for studying GNAO1-related disorders and that GNAO1 mutations should be evaluated in the context of both the GNAO1-A and GNAO1-B isoforms. Full article

As the influence of indoor environments on human emotional regulation and cognitive function becomes increasingly critical in modern society, there is a growing need for intelligent lighting systems that dynamically respond to users’ emotional states. While previous studies have investigated either illuminance or color in isolation, this study concentrates on quantitatively analyzing the interaction of these two key elements on human emotion and cognitive control capabilities. Utilizing electroencephalography (EEG) and electrocardiography (ECG) signals, we measured participants’ physiological responses and subjective emotional assessments in 18 unique lighting conditions, combining six colors and three levels of illuminance. The results confirmed that the interaction between light color and illuminance significantly affects physiological indicators related to emotion regulation. Notably, low-illuminance purple lighting was found to promote positive emotions and inhibit negative ones by increasing frontal alpha asymmetry (FAA) and gamma wave activity. Conversely, low-illuminance environments generally diminished cognitive reappraisal and negative emotion inhibition capabilities. Furthermore, a random forest model integrating time-series data from EEG and ECG predicted emotional valence and arousal with accuracies of 87% and 79%, respectively, demonstrating the validity of multi-modal physiological signal-based emotion prediction. This study provides empirical data and a theoretical foundation for the development of human-centered, emotion-adaptive lighting systems by presenting a quantitative causal model linking lighting, physiological responses, and emotion. These findings also provide a biomimetic perspective by linking lighting-induced physiological responses with emotion regulation, offering a foundation for the development of adaptive lighting systems that emulate natural light–human interactions. Full article

Background: Obesity remains a major global health challenge, and a significant proportion of bariatric surgery patients continue to experience dysfunctional emotional eating and body image concerns after surgery. Neurofeedback training (NFT) has been investigated as a potential intervention for maladaptive eating behaviours, but evidence in post-bariatric populations is still limited. Methods: Thirty-six patients who underwent sleeve gastrectomy were included, divided into an NFT group (N = 18) and a control group (N = 18). Assessments were performed at baseline and after 10 NFT sessions, using the Eating Disorder Inventory (EDI) and the Body Uneasiness Test (BUT). The intervention aimed to enhance alpha and theta waves with real-time feedback. Results: Compared with the control group, the NFT group showed significant improvements; specifically, reductions were observed in EDI subscales such as Drive for Thinness (p = 0.023, d = 0.51), Bulimia (p = 0.008, d = 0.92), Body Dissatisfaction (p = 0.015, d = 0.52), Ineffectiveness (p = 0.002, d = 0.89), Perfectionism (p = 0.006, d = 0.70), Interpersonal Distrust (p = 0.008, d = 0.82), and Interoceptive Awareness (p = 0.001, d = 0.91). Significant reductions were also found in BUT subscales including Weight Phobia (p = 0.041, d = 0.84), Body Image Concern (p = 0.039, d = 0.90), Avoidance (p = 0.027, d = 0.83), Compulsive Self-Monitoring (p = 0.013, d = 0.83), and Depersonalisation (p = 0.033, d = 0.85). Conclusions: The data indicate that NFT may help reduce emotional eating and related psychological factors in post-bariatric patients in the short term. However, studies with larger samples and longer follow-ups are needed to confirm its effectiveness and assess its clinical applicability. Full article

We investigated the use of gravel packing sand control technology in multi-lateral horizontal wells to support the development of natural gas hydrate reservoirs. An experimental apparatus was developed to investigate the effects of well configurations and operational parameters on ultra-light sand packing behavior and to estimate the field operational parameters through the application of similarity criteria. The results showed that the ultra-light sand packing process includes four stages in a single horizontal main bore, i.e., sand bank formation, alpha-wave, beta-wave, and simultaneous annulus packing, and two stages in lateral wellbores: a sand bank formation and then an alpha-wave pattern or an initial alpha-wave pattern followed by a slope pattern. At comparable injection rates and sand concentrations, the packing sequence is predominantly governed by leakage rates and the quantity of lateral wellbores. When the lateral wellbore is 1 m and the leakage rate exceeds 20%, the lateral packs first. When the lateral wellbore is 2 m and the leakage rate is below 30%, the main bore packs first. For the field prototype (480 m main bore and 200 m lateral wellbore), the deviation angle of lateral wellbores should be controlled within 30°, and it is recommended that the distance between the junction point and the heel of the horizontal main bore be 160 m. When the leakage rates exceed 50%, the recommended injection rates are less than 1.69 m³/min. When the leakage rates range from 10 to 50%, the recommended injection rates range from 1.69 to 3.38 m³/min, with predicted end-of-packing pressures ranging from 6.56 to 19.92 MPa. This study provides valuable insights into the development of gravel packing sand control technologies in a multi-lateral horizontal well for hydrate reservoirs. Full article

The field of human–robot collaboration (HRC) still lacks research studies regarding the evaluation of mental workload (MWL) through objective measurement to assess the mental state of operators in assembly tasks. This research study presents a comparative neuroergonomic analysis to evaluate the mental workload and productivity in three laboratory experimental conditions: in the first, the participant assembles a component without the intervention of the robot (standard scenario); in the second scenario, the participant performs the same activity in collaboration with the robot (collaborative scenario); in the third scenario, the participant is fully guided in the task in collaboration with the robot (collaborative guided scenario) through a system of guiding labels according to Poka-Yoke principles. The assessment of participants’ mental workload is shown through combinative analysis of subjective (NASA TLX) and objective (electroencephalogram—EEG). Objective MWL was assessed as the power waves ratio β/α (Beta—stress indicator, Alpha—relaxation indicator). Furthermore, the research used observational measurements to calculate the productivity index in terms of accurately assembled components across the three scenarios. Through ANOVA RM, mental workload significantly decreased in the activities involving the cobot. Also, an increase in productivity was observed shifting from the manual scenario to the cobot-assisted one (18.4%), and to the collaborative guided scenarios supported by Poka-Yoke principles (33.87%). Full article

Motor impairments significantly affect individuals’ ability to perform activities of daily living, reducing autonomy and quality of life. In response to this, robot-assisted rehabilitation has emerged as an effective and practical solution, enabling controlled limb movements and supporting functional recovery. This study presents the development of an upper-limb exoskeleton designed to assist rehabilitation by integrating neurophysiological signal processing and real-time control strategies. The system incorporates a proportional–derivative (PD) controller to execute cyclic flexion and extension movements based on a sinusoidal reference signal, providing repeatability and precision in motion. The exoskeleton integrates a brain–computer interface (BCI) that utilizes electroencephalographic signals for therapy selection and engagement enabling user-driven interaction. The EEG data extraction was possible by using the UltraCortex Mark IV headset, with electrodes positioned according to the international 10–20 system, targeting alpha-band activity in channels O1, O2, P3, P4, Fp1, and Fp2. These channels correspond to occipital (O1, O2), parietal (P3, P4), and frontal pole (Fp1, Fp2) regions, associated with visual processing, sensorimotor integration, and attention-related activity, respectively. This approach enables a more adaptive and personalized rehabilitation experience by allowing the user to influence therapy mode selection through real-time feedback. Experimental evaluation across five subjects showed an overall mean accuracy of 86.25% in alpha wave detection for EEG-based therapy selection. The PD control strategy achieved smooth trajectory tracking with a mean angular error of approximately 1.70°, confirming both the reliability of intention detection and the mechanical precision of the exoskeleton. Also, our core contributions in this research are compared with similar studies inspired by the rehabilitation needs of stroke patients. In this research, the proposed system demonstrates the potential of integrating robotic systems, control theory, and EEG data processing to improve rehabilitation outcomes for individuals with upper-limb motor deficits, particularly post-stroke patients. By focusing the exoskeleton on a single degree of freedom and employing low-cost manufacturing through 3D printing, the system remains affordable across a wide range of economic contexts. This design choice enables deployment in diverse clinical settings, both public and private. Full article

The neuropeptide oxytocin (OXT) is involved in social bonding, reproduction, and childbirth. Its activity is mediated by the oxytocin receptor (OXTR), also expressed in the skin. OXT alleviates dermal fibroblast senescence, and OXT levels correlate with visible skin aging. OXT inhibits nociceptive signaling and promotes neuronal plasticity. Here, we demonstrate OXT-like benefits of OXTR activation for skin touch sensoriality and nociception, as well as visible skin health and beauty indicators, using an aqueous extract of Hyacinthus orientalis bulbs. OXTR activation was evaluated in a Chinese hamster ovary (CHO) cell model. Nociception and innervation benefits were investigated in keratinocyte/sensory neuron coculture models. A placebo-controlled clinical study evaluated gentle touch receptivity, nociception, skin tone, elasticity, and wrinkling. The extract activated OXTR and enhanced dermal fibroblast proliferation in vitro. In the keratinocyte-neuron coculture, the HO extract lowered nociceptive CGRP release below that of the unstimulated and OXT controls and promoted neuronal survival and dendricity. An organ-on-a-chip coculture showed decreased electrical activity and increased neuronal peripherin. Clinically, we observed selective left-side frontal alpha-wave activation, indicating pleasant sensation, reduced nociception, enhanced skin glow, improved elasticity, and reduced wrinkling. This extract thus shows high value for holistic wellbeing solutions, enhancing the skin’s receptivity to pleasant sensations and promoting well-aging. Full article

Borderline Personality Disorder (BPD) is marked by emotional dysregulation, instability in self-image and relationships, and high impulsivity. While functional magnetic resonance imaging (fMRI) studies have provided valuable insights into the disorder’s neural correlates, electroencephalography (EEG) may capture real-time brain activity changes relevant to BPD’s rapid emotional shifts. This review summarizes findings from studies investigating resting state and task-based EEG in individuals with BPD, highlighting common neurophysiological markers and their clinical implications. A targeted literature search (1980–2025) was conducted across databases, including PubMed, Google Scholar, and Cochrane. The search terms combined “EEG” or “electroencephalography” with “borderline personality disorder” or “BPD”. Clinical trials and case reports published in English were included if they recorded and analyzed EEG activity in BPD. A total of 24 studies met the inclusion criteria. Findings indicate that individuals with BPD often show patterns consistent with chronic hyperarousal (e.g., reduced alpha power and increased slow-wave activity) and difficulties shifting between vigilance states. Studies examining frontal EEG asymmetry reported varying results—some linked left-frontal activity to heightened hostility, while others found correlations between right-frontal shifts and dissociation. Childhood trauma, mentalization deficits, and dissociative symptoms were frequently predicted or correlated with EEG anomalies, underscoring the impact of adverse experiences on neural regulation—however, substantial heterogeneity in methods, small sample sizes, and comorbid conditions limited study comparability. Overall, EEG research supports the notion of altered arousal and emotion regulation circuits in BPD. While no single EEG marker uniformly defines the disorder, patterns such as reduced alpha power, increased theta/delta activity, and shifting frontal asymmetries converge with core BPD features of emotional lability and interpersonal hypersensitivity. More extensive, standardized, and multimodal investigations are needed to establish more reliable EEG biomarkers and elucidate how early trauma and dissociation shape BPD’s neurophysiological profile. Full article