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Fecal Metabolomic Insights into Memory-Associated Pathways Modulated by Bacopa monnieri, Mixed Thai Berry, and Combined Extracts in Rats Under Chronic Unpredictable Mild Stress
No full textChronic stress impairs cognition through gut–brain axis dysregulation and metabolic imbalance. This study applied untargeted fecal metabolomics to investigate the cognitive and metabolic effects of Bacopa monnieri (L.) Wettst (Brahmi), mixed Thai berry, and their combined extracts in rats exposed to chronic unpredictable mild stress. Cognitive performance was evaluated using the novel object recognition test. Fecal metabolites were profiled using LC-ESI-QTOF-MS, followed by data preprocessing and multivariate statistical analysis. Orthogonal partial least squares regression was applied to identify metabolites associated with the recognition index, and pathway enrichment analysis was subsequently performed to interpret biological relevance. All interventions were associated with improved recognition performance and treatment-related metabolic modulation. Biosynthesis of unsaturated fatty acids was consistently enriched across treatment groups, indicating a shared involvement of lipid remodeling. Treatment-specific responses were also observed: Brahmi was associated with linoleic and alpha-linolenic acid metabolism; mixed Thai berry extract demonstrated dose-dependent modulation of lipid metabolism, with low-dose supplementation additionally yielding amino-acid-derived metabolites; and bile acid-related signaling was uniquely detected in the low-dose combined extract group. These findings demonstrate that fecal metabolomics can capture distinct metabolic signatures associated with herbal extract-induced cognitive improvement and highlight lipid remodeling as a shared metabolic feature across interventions under chronic stress
Impact of FilmArray Gastrointestinal Panel Compared to Standard-of-Care Diagnostic Tests in Clinical Practice of Acute Gastroenteritis in an HIV Reference Center with Limited Resources
No full textBackground/Objectives: Gastroenteritis remains a major global health concern, particularly in resource-limited regions, where rapid and accurate diagnosis is crucial for effective patient management. Syndromic multiplex PCR panels, such as the FilmArray gastrointestinal (FAGI) panel, offer the potential to significantly improve diagnostic yield and turnaround time, enabling more targeted treatments and reducing unnecessary antibiotic use. However, real-world data on their performance in low-resource settings remains scarce. This study evaluates the performance, clinical impact, and cost-effectiveness of the FAGI panel compared to standard of care (SOC) diagnostic methods in gastroenteritis cases at São José Hospital for Infectious Diseases in Fortaleza, Brazil, an HIV Reference Center, in a resource-limited region of a middle-income country. Methods: A retrospective observational study was conducted among patients tested with FAGI (n = 161) and a retrospective control group tested only with SOC methods (n = 166). Results: The FAGI panel was associated with a significant reduction in the turnaround time, antimicrobial use, and total treatment costs while increasing the pathogen detection rate. Specifically, the median diagnostic time was reduced by 18%, with an increase in pathogen detection compared to SOC methods (64% positivity compared to 32%). Moreover, the FAGI group experienced a 30% reduction in antibiotic use, with a corresponding 83% reduction in antimicrobial costs. Conclusions: These results suggest that the FilmArray panel may offer substantial benefits in terms of efficiency and cost savings, highlighting its potential for broader implementation in clinical practice, especially in resource-limited settings, to improve patient outcomes in infectious disease management
Efficient Separation of Per- and Polyfluoroalkyl Substances (PFAS) by Organic Framework Membranes: Advances, Mechanisms, and Challenges
No full textPer- and polyfluoroalkyl substances (PFAS) represent a class of highly persistent environmental contaminants with exceptional chemical stability. Efficient removal of PFAS from water poses a significant challenge for the chemical industry and constitutes a critical requirement for sustainable environmental development. Membrane technology has demonstrated considerable potential in water treatment due to its low energy consumption and environmentally friendly characteristics. This review comprehensively summarizes recent advances in emerging metal–organic framework (MOF)-, covalent organic framework (COF)-, and hydrogen-bonded organic framework (HOF)-based membranes for highly efficient separation and catalytic degradation of PFAS. We provide a detailed analysis of design strategies for various organic framework membranes (OFMs) and their synergistic separation mechanisms, including size exclusion, electrostatic interactions, adsorption, as well as catalytic degradation based on advanced oxidation processes. Furthermore, we systematically evaluate the performance and applicability of these membranes in practical aquatic environments. Finally, this review outlines future directions toward developing integrated “separation-degradation” membrane processes for practical applications by discussing current challenges concerning material stability, manufacturing costs, and long-term operational efficiency. This review aims to provide theoretical guidance and technical insights for developing next-generation high-performance membranes for PFAS removal
Novel Biomarkers for Prognostic Assessment of Patients with Acute Exacerbation of COPD in the Emergency Department—Tools to Enhance the Quality of Care in Critical Patient Management
No full textBackground/Objectives: Chronic obstructive pulmonary disease (COPD) remains a major global health problem, affecting over 300 million people worldwide. Its high morbidity and mortality rates impose substantial psychosocial and financial burdens on patients and healthcare systems. In the emergency setting, managing acute exacerbations of COPD (AECOPD) poses a major clinical challenge, as these patients often present with multi-organ dysfunction secondary to hypoxia and hypercapnia. Identifying reliable prognostic biomarkers could improve early risk stratification, guide therapeutic decisions, and enhance patient outcomes. Methods: This multicenter, prospective, observational study aims to evaluate the prognostic significance of several novel biomarkers—resistin, club cell secretory protein 16 (CC16), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), S100β protein—alongside conventional markers such as N-terminal-pro–B-type-Natriuretic-Peptide (NT-proBNP), D-dimer, high-sensitivity troponin I (hs-cTnI), C-reactive protein (CRP), and procalcitonin in patients with AECOPD admitted to the Emergency Department (ED). Blood samples will be collected at admission. The novel biomarkers (resistin, CC16, IL-6, TNF-α, S100β) will be measured using standardized ELISA kits, while conventional biomarkers (NT-proBNP, troponin I, CRP, procalcitonin) will be analyzed using routine automated clinical laboratory methods. Correlations between biomarker levels, clinical and imaging data, severity scores (GCS, SOFA, CFS, Ottawa COPD Risk Scale, DECAF, BAP-65), and short-term outcomes (hospital discharge status and 28-day survival) will be assessed. The study has received approval from the Ethics Committee of the “Iuliu-Hatieganu” University of Medicine and Pharmacy, Cluj-Napoca, and all participating hospitals. Written informed consent will be obtained from all participants or their legal representatives. Results: This study protocol does not report results, as data collection and analysis are ongoing. Conclusions /Expected Impact: By identifying novel biomarkers with prognostic and pathophysiological relevance, this research aims to inform the development of early risk stratification tools and support future evidence-based approaches to the management of critically ill COPD patients in the ED
Leakage Modelling in Water Distribution Networks: A Novel Framework for Embedding FAVAD Formulation into EPANET 2.2
No full textThis paper proposes a novel framework for embedding the Fixed And Variable Area Discharge (FAVAD) equation into the software EPANET 2.2 for the simulation of water distribution networks (WDNs). This framework yields a realistic model of leakage outflows that accounts for the expansion of the leak area as a function of service pressure. Without altering the source code of EPANET, this is accomplished by using node emitters and by iteratively adjusting emitter coefficients in the Matlab® (R2023a) environment to mimic the effects of the FAVAD equation along WDN pipes. An additional benefit consists of preventing backflow occurring under negative pressure conditions in EPANET 2.2. The application to two benchmark WDNs under various leakage configurations demonstrates the robustness and the numerical efficiency of the framework, as well as the impact and benefits of the FAVAD formulation. For instance, for pipes with higher elasticity, omitting the expansion of the leak area leads to an underestimation of the total leakage rate that exceeds 30% for one of the studied cases. Furthermore, the algorithm successfully prevents leakage backflow under both demand-driven and pressure-driven analyses
Nanotube Alignment and Surface Chemistry in Altering Water and Salt Permeabilities for Imogolite-Polyamide Membranes
No full textReducing the specific energy consumption of reverse osmosis (RO) processes motivates the development of new membrane materials that have enhanced water permeability while maintaining low salt permeability (high rejection). Nanocomposite membranes have shown great promise in achieving these goals, particularly those using nanotubes as fillers. Here, we report on the relationships between the orientations and surface functionalities of imogolite nanotubes (INTs) with water and salt permeabilities for polyamide nanocomposite membranes. An external electric field was used to manipulate the INT orientation within the polyamide active layer. The INT interior and exterior chemistries, respectively, were made hydrophobic using methyl triethoxysilane as a precursor during INT synthesis and post-synthesis modification with alkali-phosphate groups. Irrespective of nanotube orientation or surface chemistry, membrane permeance increased from 0.3 to ≥1.0 L m−2 h−1 bar−1. A salt permeability comparable to the conventional polyamide membrane was maintained by making the INT pore throat hydrophobic. These findings indicated that salt rejection could be tailored by manipulating the INT interior surface chemistry without sacrificing water permeability
Navigating the Future of Education: A Review on Telecommunications and AI Technologies, Ethical Implications, and Equity Challenges
No full textThe increasing integration of Artificial Intelligence (AI) in education (AIEd) and its dependence on contemporary communication infrastructures (5G/6G, the Internet of Things (IoT), and Multi-Access Edge Computing (MEC)) has prompted a surge of research into applications, infrastructural dependencies, and deployment constraints. This is giving rise to a new paradigm termed AI-Enabled Telecommunication-Based Education (AITE). This review synthesises the recent literature (2022–2025) to examine how telecommunications and AI technologies converge to enhance educational ecosystems through adaptive learning systems, intelligent tutoring systems, AI-driven assessment, and administration. The findings reveal that low-latency, high-bandwidth connectivity, combined with edge-deployed analytics, enables real-time personalisation, continuous feedback, and scalable learning models that extend beyond traditional classrooms. In addition, persistent critical challenges are also reported, including issues with ethical governance, data privacy, algorithmic fairness, and uneven access to digital infrastructure, all affecting equitable adoption. By linking pedagogical transformation with telecom performance metrics—namely, latency, Quality of Service (QoS), and device interconnectivity—this work outlines a unified cross-layer framework for AITE. This review concludes by identifying future research avenues in ethical AI deployment, resilient architectures, and inclusive policy design to ensure transparent, secure, and human-centred educational transformation
Imaging Approaches for the Diagnosis of Dry Eye: A Review
No full textDry eye disease (DED) is a multifactorial disorder of the ocular surface, characterised by tear film instability, hyperosmolarity, inflammation, and neurosensory abnormalities. Its clinical heterogeneity and the weak correlation between symptoms and signs complicate both diagnosis and management. Conventional assessments, such as patient-reported symptom questionnaires and basic clinical tests like the Schirmer test, are useful; however, their variability and limited sensitivity highlight the need for more reliable and objective diagnostic tools. This narrative review summarises and analyses current imaging approaches used for the diagnosis of DED. A comprehensive literature search was performed in the PubMed and Google Scholar databases to identify relevant studies published up to October 2025. In recent years, imaging technologies have revolutionised the approach to DED. Modalities such as in vivo confocal microscopy (IVCM), meibography, anterior segment optical coherence tomography (AS-OCT), interferometry, thermography, tear fluorescein clearance, impression cytology, and multifunctional imaging systems allow for non-invasive, high-resolution, and reproducible assessment of ocular surface structures and tear film dynamics. The integration of these techniques into clinical practice supports a more personalised management of DED. Future directions include further technological refinements and the application of artificial intelligence (AI) to imaging analysis, with the potential to enhance diagnostic precision and facilitate earlier intervention. While imaging cannot replace a thorough clinical examination, it has become an essential adjunct that significantly enriches the evaluation and management of patients with DED
Electron Beam Irradiation-Assisted Synthesis of MIL-88A(Fe) Toward Efficient Periodate Activation for Tetracycline Degradation
No full textIn this study, MIL-88A(Fe)-X (X = 300, 500, 600) was successfully synthesized via electron beam irradiation and employed to activate periodate (PI) for tetracycline (TC) degradation. Experimental results indicated that the optimal irradiation dosage was 300 kGy for MIL-88A(Fe)-X. And 99.0% of TC could be degraded under the optimum reaction conditions (catalyst dosage of 20 mg, PI concentration of 1.0 mM, initial TC concentration of 10 mg/L, pH = 6.8, and temperature of 25 °C) in MIL-88A(Fe)-300/PI system. Furthermore, quenching experiments were conducted to investigate the degradation mechanism, revealing IO3· and IO4· radicals played predominant roles in MIL-88A(Fe)-300/PI system. The system exhibited excellent stability and recyclability, maintaining a degradation efficiency of over 90% after three consecutive cycles. This study demonstrated that the MIL-88A(Fe)/PI system achieved rapid degradation and high reproducibility for TC removal. The proposed method could effectively reduce antibiotic residues in the environment, offering a promising strategy for addressing antibiotic pollution. Future work can be conducted to assess its practical application performance under various environmental conditions
Somatostatin-Expressing Neurons Regulate Sleep Deprivation and Recovery
No full textBackground/Objectives We re-analyzed publicly available gene expression profiles from the male mouse cortex under conditions of sleep deprivation (SD) using tensor decomposition-based unsupervised feature extraction, originally proposed by one of the authors in 2017. Methods We focused on two distinct expression patterns: genes whose levels were altered in SD and failed to normalize during recovery sleep (RS), and genes that overshot normal levels during RS. This selection excluded the expected “altered in SD and recovered in RS” pattern, which was not significantly observed. These two gene sets showed substantial overlap but were still distinct from each other. Results The analysis revealed that the selected gene sets were enriched in various brain regions as evidenced through clustering in the Allen Brain Atlas. This suggests that the successful selection identified biologically meaningful genes. Furthermore, somatostatin (Sst)-expressing neuronal clusters were among the most highly enriched. Conclusions Given that sst is already implicated in SD and RS, our fully data-driven transcriptomic analysis successfully identified the activity of sst during SD and RS. These findings reveal that Sst-expressing neurons may play a key role in SD. These results were further validated using AlphaGenome by uploading the selected genes to it