Search Results (373,010)

Accurate and interpretable assessment of cognitive workload from EEG remains a central challenge in neuroergonomics and real-time human–machine interaction. To address the limitations of existing Empirical Mode Decomposition (EMD) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) approaches, particularly their instability, limited neuroscientific grounding, and sensitivity to amplitude fluctuations, this paper introduces Scale-Stabilized Relative Intrinsic Mode Energy (SS-RIME), a theoretically motivated and physiologically informed feature extraction framework. SS-RIME integrates instantaneous frequency stabilization to enforce a consistent oscillatory hierarchy across subjects, delta (1–4 Hz) and theta (4–7.5 Hz) spectral weighting based on established frontal-midline activity, and cross-IMF energy normalization to reduce amplitude-driven variability. Applied to 64-channel EEG recorded during N-back tasks, the proposed framework achieved high performance, outperforming both classical machine-learning baselines and deep learning models such as EEGNet, DeepConvNet, and ShallowConvNet. SS-RIME yielded accuracies of $99.12\pm 0.41\%$ (0 vs. 2-back), $97.84\pm 0.63\%$ (0 vs. 3-back), and $92.31\pm 1.12\%$ (2 vs. 3-back), demonstrating strong cross-subject generalization. Theta-dominant IMFs over frontal midline regions emerged as the most discriminative components, supporting the neuroscientific validity of the stabilized and spectrally weighted Hilbert–Huang representation. With an inference time below 20 ms per epoch, SS-RIME is computationally efficient and suitable for real-time neuroergonomics applications, providing a robust, explainable, and physiologically grounded solution for EEG-based cognitive workload decoding while addressing key methodological gaps in prior EMD/CEEMDAN and deep learning approaches. Full article

The widespread residual ciprofloxacin (CIP) poses severe environmental and health risks, demanding efficient detection methods. Herein, a Zr–Tb bimetallic MOF (ZTM) was green-synthesized via a room-temperature aqueous route with disodium terephthalate as ligand, and developed as a ratiometric fluorescent probe for CIP detection. Structural characterization confirmed Tb³⁺ was successfully incorporated into the Zr-MOF framework, endowing ZTM with high stability and excellent luminescence. The absorption edge of ZTM (320–330 nm) overlapped with CIP’s 330 nm absorption peak, so 327 nm was selected as the excitation wavelength. Under this excitation, ZTM showed a strong Tb³⁺ emission at 657 nm; upon CIP addition, the 657 nm peak was quenched, while the 491 nm emission was enhanced, realizing a distinct ratiometric response. The ratio I₄₉₁/I₆₅₇ was linear with CIP concentration (0.5–25 μM, R² = 0.992), with a limit of detection far below the statutory 30 μM limit (0.16 μM). ZTM also exhibited excellent selectivity, good pH tolerance (5.0–8.0) and rapid response (1 min). Mechanism analysis revealed that the response was mainly due to the inner filter effect (IFE) between ZTM and CIP. This work provides a green-synthesized MOF probe for sensitive and selective CIP detection in environmental samples. Full article

Rural communities face significant healthcare access barriers that contribute to persistent health disparities. Mobile health clinics (MHCs) have emerged as a promising strategy for expanding healthcare access, yet their effectiveness in rural settings remains understudied. The aim of this review was to examine the literature to determine what is known about access, health outcomes, and the cost-effectiveness of rural MHCs, specifically with regard to their impact on patient access and outcomes, return on investment (ROI)/financial, and program sustainability. We conducted a comprehensive search of peer-reviewed and grey literature sources. Systematic screening yielded 34 documents for full analysis. Thematic analysis was conducted across three domains: patient access, patient outcomes, and ROI/sustainability. All 34 documents provided data on patient access, with common themes including expanded service utilization, multi-service integration, overcoming geographic and transportation barriers, and improved healthcare affordability. Thirty-two documents addressed patient outcomes, reporting improvements in preventive care delivery, chronic disease management, and high patient satisfaction. Twenty-eight documents included ROI/sustainability information, with evidence suggesting cost-effectiveness particularly through emergency department visit avoidance and multi-service integration. Across the literature reviewed, the quality of evidence varied considerably, yet we concluded mobile health clinics demonstrate promise for expanding healthcare access and improving outcomes in rural populations. Key success factors include multi-service integration, diverse funding partnerships, technological integration, and strong community engagement. More rigorous research with longitudinal clinical outcome measures and robust economic analyses is needed. Full article

Galectins are a functionally diverse family of β-galactosyl-binding lectins that are ubiquitously present in animal species, with key roles in development and immune regulation. Recently, galectins have been found to recognize microbial glycosylated moieties, but the detailed mechanisms of their innate immune functions in mucosal epithelia have remained elusive. The zebrafish (Danio rerio) represents an ideal genetically tractable model to address these questions, as the skin, gills, and gut display mucosal surfaces exposed to the environment. In this study, we investigated the range of endogenous and microbial glycans that are recognized by zebrafish galectin Drgal1 present in epidermal mucus, which would be consistent with defense functions against a bacterial challenge. Results revealed that zebrafish galectin isoform Drgal1-L2 can recognize selected bacterial glycans, as well as zebrafish mucus glycans and cell-surface receptors for bacterial adhesins such as fibronectin (K_D = 1.593 × 10⁻⁶ M) and CD147 (K_D = 1.115 × 10⁻⁶ M). Furthermore, preliminary experiments revealed that Drgal1-L2 may hinder bacterial adhesion to epidermal mucus in about 50% at 2.5 μg/mL. Our results suggest that Drgal1-L2 present in epidermal mucus can prevent access of pathogenic bacteria to the epithelial cell surface by alternate or synergic binding to bacterial glycans and to zebrafish mucus components and epithelial receptors for bacterial adhesins. Thus, the present study provides key information for the testing of the abovementioned hypothesis by implementing gene-silencing approaches targeting both zebrafish Drgal1-L2 and its ligands. Full article

Background and Objectives: Head and neck cancer (HNC) frequently necessitates reconstructive surgery due to defects following oncologic resection. The influence of age on reconstructive outcomes in head and neck cancer remains controversial. This study aimed to evaluate the impact of age on oncologic characteristics, reconstructive strategies, and functional outcomes following microvascular free flap reconstruction. Materials and Methods: A retrospective review was conducted on 286 patients who underwent free flap reconstruction for head and neck cancer between 2016 and 2020. Patients were stratified into three age groups: <40 years, 40–60 years, and >60 years. Demographic characteristics, tumor features, reconstructive approaches, complications, and functional outcomes—including postoperative dietary tolerance and tube feeding dependency—were analyzed. Results: The oral cavity was the most common tumor site across all age groups. Advanced-stage tumors (T4) were more frequently observed in older patients (>60 years), although the difference was not statistically significant (p = 0.0575). The overall flap survival rate was 98.6%. The mean hospital stay was 24.6 ± 15.86 days and was significantly longer in the >60-years group (p < 0.001). Postoperative dietary tolerance was comparable across age groups, with 56.8% of patients resuming a regular diet. Tube feeding dependency was slightly higher in the >60-years group but did not reach statistical significance (p = 0.1599). Conclusions: Age alone does not significantly affect reconstructive outcomes following microvascular free flap reconstruction for head and neck cancer. Despite a higher prevalence of comorbidities in and longer hospital stays for older patients, flap success rates and functional outcomes were comparable across age groups. Full article

This paper examines the subjective annoyance associated with shared-bike electronic alert sounds (SBeASs), an emerging urban noise source. A study was conducted by employing extensive questionnaire surveys and psychoacoustic experiments. A preliminary survey (N = 1340) indicated that 90.6% of participants reported being impacted by SBeASs, with pronounced effects on nighttime rest and daytime work efficiency. In this study, SBeAS samples were taken from three prominent Chinese bike-sharing brands: Hello Bike, Meituan Bike, and DiDi Bike. Under laboratory conditions, subjective annoyance assessments (N = 28) for SBeASs were conducted at controlled sound pressure levels (SPLs) ranging from 45 to 65 dBA, with occurrence frequencies of 1, 3, and 5 s. Simultaneously, annoyance assessments were also conducted for two reference noise types: traffic noise and street noise. The results indicated a notable increase in annoyance levels related to SBeASs with rising SPL and increased occurrence frequency. Minor variations in annoyance were identified among different bike-sharing brands, which can be attributed to their distinct acoustic features. When the SPL was above 55 dBA, the DiDi Bike SBeASs produced considerably higher annoyance than those of other brands. This can be attributed to its elevated low-frequency energy, loudness, and roughness. Moreover, individuals exhibiting increased sensitivity to noise reported notably higher annoyance ratings on the SBeAS scale (p = 0.019). Under low-SPL conditions (45–55 dBA), the annoyance attributed to frequent SBeASs can exceed that caused by traffic noise and street noise at comparable SPLs, highlighting the distinct disruptive impact of abrupt sound sources. Full article

Circular RNAs (circRNAs) have been reported to be closely associated with tumor progression in multiple malignancies. However, the specific mechanism by which circPRKCA influences tumor progression has not been fully elucidated. CircPRKCA is highly expressed in non-small cell lung cancer (NSCLC) tissues and cells. Knockdown of circPRKCA inhibits the malignant behaviors of NSCLC cells. RNA sequencing results revealed that FRMD6 and SNAI2 mRNAs are positively correlated with circPRKCA. Subsequently, we proved that circPRKCA acts as a molecular sponge for miR-200b-3p. Additionally, miR-200b-3p binds to the 3′ untranslated regions (3′UTRs) of FRMD6 and SNAI2 mRNAs to promote their degradation. Overexpression of circPRKCA thereby suppresses this degradation process and coun-teracts the tumor-suppressive effects induced by miR-200b-3p. CircPRKCA functions as the sponge of miR-200b-3p, suppressing the SNAI2/FRMD6 mRNA degradation driven by miR-200b-3p and accelerating NSCLC progression. Full article

The purpose of this study was to examine the multivariate relationship between college students’ Big Five personality traits and their perceptions of generative artificial intelligence (AI). Guided by sustainable digital education and expectancy-value theory, this study investigated whether personality profiles were associated with students’ knowledge of AI, attainment value, intrinsic value, utility value, perceived cost, and intention to use AI. Using a cross-sectional survey design, data were collected from 375 students enrolled at a Southwestern doctoral-granting public university. Participants completed an adapted measure of generative AI perceptions and the Big Five Inventory, and canonical correlation analysis (CCA) was conducted to examine the multivariate relationship between the two variable sets. The results indicated that the full canonical model was statistically significant and that three interpretable canonical functions were retained. The first and strongest function showed that higher openness, agreeableness, and conscientiousness were associated primarily with greater AI knowledge and, to a lesser extent, with higher perceived cost. The second function indicated that higher neuroticism was associated with greater perceived cost and lower utility and attainment value. The third function showed that lower neuroticism, together with higher openness and conscientiousness, was associated with a stronger attainment value, greater intention to use AI, and lower perceived cost. Our findings suggest that students differ meaningfully in how they understand and value generative AI. These results have important implications for higher education because they highlight the potential value of differentiated, human-centered AI literacy efforts in supporting more equitable and responsible AI integration. Full article

Artificial intelligence (AI) is a new paradigm in software engineering that automates key phases of the development cycle. The methods of creating test cases and designing requirements are still mostly manual and prone to error. Unclear requirements can result in expensive rework and undiscovered defects in the development process. Scalability and dependability are crucial concerns in complex systems. These shortcomings highlight the need for improved methods to enhance accuracy and consistency throughout these critical phases. To generate well-organized system requirements, this article outlines a clear strategy that leverages Extended Finite State Machine models as formal inputs for large language models (LLMs). Five system models are used to assess the suggested framework. The comparison analysis evaluates the accuracy, completeness, test coverage, and runtime efficiency of the artifacts. Along with a comparison with a human-made reference standard, the study evaluates the performance of LLMs such as ChatGPT-5, Claude Sonnet 4.5, and DeepSeek V3.2. The findings demonstrate that AI models can achieve human-comparable accuracy by exceeding 90% with EFSM-based prompting. Claude Sonnet generated the most reliable findings, ChatGPT demonstrated exceptional flexibility, and DeepSeek demonstrated exceptional runtime economy. These findings show that human–AI workflows provide a new paradigm in scalable, traceable, and reproducible system engineering. Full article

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder in women of reproductive age, characterized by hyperandrogenism, insulin resistance, and ovarian dysfunction. Current therapies are often associated with adverse effects, highlighting the need for safer therapeutic alternatives. Peganum harmala (P. harmala), a medicinal plant rich in bioactive metabolites, was investigated through in silico approaches to identify compounds with predicted binding affinity for the androgen receptor (AR), steroid 17α-hydroxylase/17,20-lyase (CYP17A1), and glycogen synthase kinase-3 beta (GSK-3β). GC-MS analysis of P. harmala leaf essential oil collected in Riyadh, Saudi Arabia, identified 109 compounds, with terpenoids as the dominant class (21.89%). The major constituents were cis-chrysanthenyl acetate (3.48%), cis-β-damascenone (3.06%), farnesylacetone (1.44%), β-calacorene (1.36%), dihydroedulan II (1.04%), and trans-calamenene (0.46%). In silico ADMET evaluation indicated that most compounds complied with Lipinski’s rule of five and showed favorable predicted pharmacokinetic properties. Safety profiling suggested an overall acceptable toxicity profile, with minimal predicted CYP450 inhibition, except for L11, which showed broader inhibitory potential. Molecular docking showed that L15 (trans-calamenene), L14 (dihydroedulan II), L6 (β-calacorene), L3 (farnesylacetone), and L8 exhibited higher predicted binding affinity toward the androgen receptor; L3, L10 (cis-β-damascenone), and L16 (cis-chrysanthenyl acetate) interacted with CYP17A1, while L3, L9, and L6 exhibited higher affinity toward GSK-3β. Overall, these findings provide hypothesis-generating in silico predictions of ligand–target binding affinities and drug-likeness profiles. These computational findings highlight the importance of future experimental investigations to substantiate the biological activity, pharmacokinetic behavior, and safety profile of P. harmala constituents. Full article

Acute coronary syndromes (ACS) remain time-critical clinical emergencies in which early diagnosis and accurate risk stratification determine management and outcomes. Although symptoms, electrocardiography, and high-sensitivity cardiac troponin (hs-cTn) provide a reliable framework for detecting myocardial injury, they offer limited insight into plaque instability, thromboinflammatory activity, vascular repair, and post-infarction remodeling. In this narrative review, we examine the biological rationale and current clinical evidence supporting brain-derived neurotrophic factor (BDNF) as a candidate biomarker in ACS, with particular attention to pre-analytical, analytical, and phenotypic sources of heterogeneity. Available studies show that circulating BDNF concentrations vary substantially according to biological matrix, timing of sampling, ACS subtype, and assay methodology, which likely contributes to inconsistent findings across cohorts. Overall, current evidence does not support BDNF as a diagnostic alternative to hs-cTn in rule-in or rule-out pathways. However, BDNF may have value in biological phenotyping and risk stratification by reflecting platelet activation, endothelial dysfunction, inflammatory signaling, and remodeling processes after ACS. Further progress will require standardized pre-analytical procedures, separate assessment of mature BDNF and proBDNF, serial sampling, and validation in large multicenter studies. Full article

Grape (Vitis vinifera L.) is an important fruit crop, but its production is severely threatened by ripe rot, a fungal disease caused by Colletotrichum gloeosporioides. However, V. pseudoreticulata ‘Dongan-1’ has been reported to have significant resistance to ripe rot. To investigate the molecular basis of this resistance, we employed RNA-Seq to profile transcriptome changes in the leaves and berry skins of ‘Dongan-1’ following infection. Gene Ontology (GO) enrichment analysis suggested that differentially expressed genes (DEGs) were mainly linked to stress response, cellular processes, and metabolic processes. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that DEGs in both tissues were predominantly enriched in the plant MAPK signaling pathway, peroxisome pathway, plant–pathogen interaction pathway, and plant hormone signal transduction pathway. Notably, VpCML41 was identified as a highly induced gene. Functional characterization through heterologous overexpression in Arabidopsis thaliana and transient expression in ‘Thompson Seedless’ grape leaves demonstrated that VpCML41 enhances resistance to C. gloeosporioides. This enhanced resistance involves the coordinated regulation of salicylic acid and jasmonic acid signaling cascades. Our findings provide valuable genetic resources for understanding ripe rot resistance and offer a foundation for developing resistant grape varieties. Full article

Novel brominated flame retardants (NBFRs), including 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), are emerging endocrine-disrupting chemicals, though their direct effects on female gamete maturation remain insufficiently characterized. In this study, we used a refined zebrafish oocyte in vitro maturation (IVM) model integrating germinal vesicle breakdown (GVBD) assessment with real-time, image-based oocyte diameter quantification. The workflow incorporated donor-condition optimization and diameter-based quality control during sorting. Oocytes from donors 4 to 5 months post-fertilization (mpf) showed more consistent diameter dynamics at the dish level than those from donors 3 to 4 mpf. Mixed-sex co-housing was associated with higher GVBD and larger Δdiameter than separated housing, although this comparison should be considered preliminary. Under DHP induction, BTBPE (1–1000 nM) consistently suppressed GVBD and attenuated maturation-associated diameter increases, with a non-monotonic-like response pattern. These findings indicate that BTBPE impairs oocyte maturation competence in vitro and supports real-time morphometric tracking as a practical QC component for zebrafish IVM workflows. Full article

Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by persistent mucosal inflammation and dysregulated immune–metabolic responses. Koumiss, a traditional fermented mare’s milk, has long been used in ethnomedicine for gastrointestinal disorders; however, its molecular mechanisms in UC remain unclear. In this study, an integrated multi-omics approach combining network pharmacology, quantitative proteomics, and molecular docking was employed to elucidate the therapeutic mechanism of koumiss powder (KP) in a dextran sulfate sodium (DSS)-induced murine colitis model. Network pharmacology identified twelve bioactive compounds targeting fourteen UC-associated proteins, predominantly enriched in the peroxisome proliferator-activated receptor (PPAR) signaling pathway. In vivo experiments demonstrated that high-dose KP significantly alleviated disease activity, improved colon shortening and histopathological injury, reduced serum TNF-α and IL-6 levels, and restored anti-inflammatory cytokines IL-4 and IL-10. Proteomic analysis further revealed activation of the PPAR signaling pathway, with significant upregulation of Plin4 and Sorbs1. Immunofluorescence staining further confirmed that KP restored the expression of PPARA and increased the levels of Plin4 and Sorbs1 in colonic tissues. Molecular docking confirmed strong binding affinities between key koumiss-derived lipid metabolites, including 13(S)-HOTrE and stearoyl ethanolamide, and PPAR-related target proteins. Collectively, these findings demonstrate that koumiss exerts protective effects against experimental UC primarily through activation of PPAR-mediated lipid metabolic and anti-inflammatory pathways. This study provides mechanistic insight into the biological activity of koumiss and highlights the value of multi-omics integration in natural product research. Full article

To support low-cost, non-destructive crop growth monitoring, this study systematically compared different vegetation indices, voxel sizes, and camera angles using a point cloud voxelization approach combined with a vegetation index weighted canopy volume index (CVM_VI) to assess aboveground biomass (AGB) in winter oilseed rape (Brassica napus L.). Field experiments were conducted from 2021 to 2024 at the Yangma Experimental Base of the Chengdu Academy of Agricultural and Forestry Sciences. Red, green, blue (RGB) imagery of oilseed rape was acquired using an unmanned aerial vehicle (UAV) during the following five key growth stages: seedling, bolting, flowering, podding, and maturity. Collected images were processed to generate point clouds, which were subsequently voxelized at four resolutions (0.03, 0.05, 0.07, and 0.1 m). CVM_VI was constructed by integrating vegetation indices (VIs) derived from the RGB data and the voxelized canopy structural information. Regression models were established between the CVM_VI values and field-measured AGB to estimate biomass. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and relative error (RE). There were strong correlations (r > 0.80) between the estimated and measured AGB across all voxelization treatments throughout the growth period. Among the 20 VIs tested, regression methods based on the blue green ratio index (BGI), color intensity index, blue red ratio index, vegetative index, and green red ratio index consistently showed superior estimation performance across three consecutive years, demonstrating their good applicability for estimating AGB in oilseed rape under varying agronomic conditions (different varieties, densities, and sowing dates). The cubic regression model CVM_BGI performed best under a 45° UAV camera angle, with the highest R² and lowest RMSE and RE (2021–2022: R² = 0.864, RMSE = 2414.18 kg/ha, RE = 14.8%; 2022–2023: R² = 0.754, RMSE = 2550.53 kg/ha, RE = 14.9%; 2023–2024: R² = 0.863, RMSE = 1953.61 kg/ha, RE = 22.9%). Since the estimation performance showed negligible differences among voxel sizes, and the 0.1–m voxel offered the smallest data volume and shortest analysis time, the CVM_BGI model with a 0.1–m voxel was selected as the preferred approach, providing a practical balance between estimation performance and processing demand. These findings highlight the application potential of point cloud voxelization technology for crop biomass estimation. This study proposes a novel, non-destructive, and efficient framework for estimating field crop AGB using low-cost UAV RGB imagery, facilitating the wider adoption of UAV technology in practical agricultural production. Full article