Search Results (3,849)

Background/Objectives: Epilepsy is characterized by unpredictable seizures and drug resistance, along with rising antimicrobial resistance (AMR), highlighting the urgent need for innovative dual-action therapies. This study aimed to design, develop, and evaluate novel pyrazolone derivatives for a dual antimicrobial and antiepileptic potential. Methods: Novel pyrazolone derivatives were designed, synthesized (using 2,4-dinitrophenylhydrazine/semicarbazide condensation with ethyl acetoacetate), and evaluated through molecular docking against antimicrobial (4URM, 3FYV, 3FRA) and neuronal targets (4COF, 5TP9, 5L1F). The in vitro antimicrobial activity was assessed against Gram-positive (S. aureus) and in vitro Gram-negative (E. coli, P. aeruginosa) strains via agar cup plate assays, while in vivo antiepileptic efficacy was tested in a PTZ-induced seizure model in Swiss albino mice. Results: Compound IIa showed potent dual activity, inhibiting E. coli (9 mm zone at 80 μg/mL) and S. aureus (9.5 mm at 80 μg/mL), alongside a significantly delayed seizure onset in the PTZ-induced mouse model (100% survival rate, 45 sec delayed seizure onset, p < 0.001). Compounds Ia and Id showed selective activity against E. coli (6 mm at 80 μg/mL) and P. aeruginosa (7 mm at 80 μg/mL), respectively. Docking studies revealed that compound IIa has a superior binding affinity (−7.57 kcal/mol for 3FYV) compared to standards, driven by hydrogen bonds (SER X: 49) and hydrophobic interactions (LEU X: 20). Conclusions: This study presents a novel approach by proposing a rationally designed pyrazolone scaffold exhibiting both antimicrobial and antiepileptic activity, which integrates in silico modeling with experimental validation. Compound IIa emerged with preliminary dual biological activities, exhibiting strong antibacterial activity, a superior binding affinity toward both bacterial and neuronal targets, and notable seizure prevention in vivo. These findings show the potential of multifunctional pyrazolone derivatives as a new treatment strategy for addressing drug-resistant infections linked to epilepsy and support further optimization toward clinical development. Full article

Background/Objectives: Despite the high prevalence (around 4.1–37.2%) and highly debilitating adverse impact, there has been inconclusive evidence regarding the efficacy of treatment for tinnitus management, especially for those patients with tinnitus who do not have a specific or treatable origin. The aim of this updated network meta-analysis (NMA) was to estimate the efficacy and safety of the different non-invasive brain stimulation (NIBS) interventions in tinnitus management in patients with chronic tinnitus without a specific or treatable origin. Methods: This NMA included randomized controlled trials (RCTs) of NIBS interventions in patients with chronic tinnitus. The current NMA was conducted using the frequentist model. The primary outcome was a change in tinnitus severity after the NIBS intervention. Results: We identified 45 eligible RCTs with a total of 2042 participants. The results of the current NMA showed that both excitatory and inhibitory NIBS interventions exerted significant effects on tinnitus severity, quality of life, or response rate. While several protocols showed a signal, the top-ranked intervention was preliminary and derived from a single, small study. All the NIBS interventions had fair acceptability compared to the controls. Conclusions: This NMA highlighted that both excitatory and inhibitory NIBS interventions exerted significant effects on tinnitus severity, quality of life, and/or response rate. Future well-designed RCTs with electroencephalogram applications are needed for replication over the proclamation of efficacy. Full article

Background and hypothesis: Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic chemicals that can accumulate in renal tissue and potentially disrupt kidney function. Most prospective studies on PFAS–renal associations have focused on middle-aged or older adults, leaving uncertainty about whether similar patterns exist in younger populations. Methods: We investigated decade-long trajectories of plasma concentrations of 11 PFAS and their longitudinal associations with estimated glomerular filtration rate (eGFR) among 529 Taiwanese adolescents and young adults (aged 12–30 years) enrolled in the prospective YOung TAiwanese Cohort (YOTA), with measurements obtained in 2006–2008 and 2017–2019. Results: Nearly all plasma PFAS declined significantly over the 10-year period. Despite these reductions, higher baseline levels and greater annualized increases (Δln-PFAS/Δt) in linear perfluorooctanoic acid (PFOA), linear and branched perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) were consistently associated with larger eGFR gains over time (β = 0.33–0.40, q < 0.05). In complementary models using follow-up eGFR as the outcome, both baseline and cumulative PFAS changes (Δln-PFAS) remained positively associated with higher eGFR (β = 1.71–3.84, q < 0.05). Polynomial analyses further indicated mild non-linear exposure–response patterns for several PFAS, suggesting that renal effects may deviate from linearity across exposure ranges. The composite PFAS exposure index (mean of standardized ln-PFAS concentrations) was robustly associated with higher eGFR across sensitivity analyses excluding participants with chronic conditions. These associations were more pronounced among individuals with greater metabolic or physiological vulnerability. Conclusions: Higher PFAS exposure was associated with elevated eGFR in young adults, which may be consistent with early glomerular hyperfiltration or other renal hemodynamic alterations. These findings raise the hypothesis of early renal stress in early life and underscore the need for ongoing biomonitoring and longitudinal follow-up with additional kidney injury markers to clarify long-term renal consequences. Full article

Microglia-derived small extracellular vesicles (MGEVs) are key mediators of neuroimmune communication, yet their cross-species comparability and translational relevance remain poorly defined. Here, we establish a harmonized framework to compare the molecular and biochemical signatures of sEVs derived from immortalized mouse (BV2) and human (HMC3) microglial cells as well as assess their bioactivity on a human Schwann cell (HuSC) line. MGEVs were isolated via MISEV-aligned size-exclusion chromatography (SEC) and characterized by nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), and immunoblotting for canonical EV markers CD9, CD63, CD81, TSG101. Human and mouse MGEVs exhibited similar morphology but displayed distinct membrane tetraspanin protein enrichment patterns. Functionally, mouse and human MGEVs attenuated HuSC migration while enhancing HuSC proliferation and their resistance to H₂O₂-induced oxidative stress, with human MGEVs providing stronger protective effects, suggesting they retain similar core functional properties. Short, non-coding-miRNA sequencing analysis identified 196 shared miRNAs (Spearman ρ = 0.72) with species-specific enrichment: human MGEVs-derived miRNAs favored regenerative and metabolic pathways, whereas mouse MGEVs-derived miRNAs aligned more so with inflammatory signaling. This study delivers the first integrated cross-species blueprint of MGEVs, revealing conserved neuroprotective actions alongside species-biased miRNA cargo that define translational boundaries and highlight human-relevant MGEV signatures for therapeutic innovation, therefore contributing to the importance of considering these differences in translational research. Full article

Chondroitin sulfate is a glycosaminoglycan polysaccharide, playing key roles in a plethora of physiopathological processes typical of higher animals. The position of sulfate groups within CS disaccharide subunits composing the polysaccharide chain is able to encode specific functional information. In order to expand such a “sulfation code”, access to non-natural CS variants and mimics thereof can be pursued. In this context, an interesting topic concerns phosphorylated analogs of CS polysaccharides, as the replacement of sulfate groups with phosphates can lead to unreported activities of phosphorylated CS. In light of this, the phosphorylation reaction of a microbial-sourced, unsulfated chondroitin polysaccharide with phosphoric acid is reported in the present study, testing different microwave irradiation conditions and comparing them with conventional heating procedures. The obtained products were subjected to a detailed characterization, in terms of chemical structure and hydrodynamic properties, by 1D- and 2D-NMR spectroscopy and HP-SEC-TDA analysis, respectively. The characterization study showed how different reaction conditions can not only influence the regioselectivity and degree of phosphorylation but also trigger the formation of phosphate diester functionalities acting as cross-linkers between polysaccharide chains. The results from the screening presented in this work could be interesting for any research devoted to the regioselective phosphorylation of a polysaccharide. Full article

Fault diagnosis in the power systems of Hybrid Electric Vehicles (HEVs) is crucial for ensuring vehicle safety and energy efficiency. This study proposes an innovative CNN-LSTM fusion model for diagnosing common faults in HEV power systems, such as battery degradation, inverter anomalies, and motor failures. The model integrates the feature extraction capabilities of Convolutional Neural Networks (CNN) with the temporal dependency handling of Long Short-Term Memory (LSTM) networks. Through data preprocessing, model training, and validation, the approach achieves high-precision fault identification. Experimental results demonstrate an accuracy rate exceeding 95% on simulated datasets, outperforming traditional machine learning methods. This research provides a practical framework for HEV fault diagnosis and explores its potential in real-world applications. Full article

Ulcerative colitis (UC) is an inflammatory bowel disease associated with oxidative stress. Pogostemon oil (PO) exhibits potent antioxidant and anti-inflammatory activities but is limited by high volatility and poor gastrointestinal stability. In this study, sporopollenin exine capsules (SECs) were engineered as natural micro-carriers for PO, achieving efficient encapsulation (η > 69%) and a high adsorption capacity (27.64 g/g). A pH-sensitive calcium alginate shell was subsequently applied to construct colon-targeted microspheres (Ca-Alg@PO-SECs). The resulting system improved the thermal and photostability of PO. In vitro dissolution assays confirmed the system’s pH-responsiveness, maintaining integrity under simulated gastric conditions while enabling localized release at intestinal pH. In a DSS-induced acute UC mouse model, Ca-Alg@PO-SECs effectively alleviated clinical symptoms, as evidenced by improved body weight, colon length, and disease activity index. At the inflammatory level, the formulation modulated key cytokines (IL-1β, IL-6, and IL-10). Overall, Ca-Alg@PO-SECs provides a biocompatible, colon-targeted delivery strategy that preserves the bioactivity of essential oils and offers a promising preclinical approach for localized UC therapy. Full article

The study establishes a comprehensive mathematical modeling framework for solar-driven hydrogen production by integrating a triple-diode photovoltaic (PV) model, an alkaline electrolyzer, and a hydrogen turbine (H₂T), subsequently using hybrid power utilization to optimize hydrogen output. The Triple-Diode Model (TDM) accurately reproduces the electrical performance of a 144-cell photovoltaic module under standard test conditions (STC), enabling precise calculations of hourly maximum power point outputs based on real-world conditions of global horizontal irradiance and ambient temperature. The photovoltaic system produced 1.07 MWh during the summer months (May to September 2025), which was sent straight to the alkaline electrolyzer. The electrolyzer, using Specific Energy Consumption (SEC)-based formulations and Faraday’s law, produced 22.6 kg of green hydrogen and used around 203 L of water. The generated hydrogen was later utilized to power a hydrogen turbine (H₂T), producing 414.6 kWh, which was then integrated with photovoltaic power to create a hybrid renewable energy source. This hybrid design increased hydrogen production to 31.4 kg, indicating a substantial improvement in renewable hydrogen output. All photovoltaic, electrolyzer, and turbine models were integrated into a cohesive MATLAB R2024b framework, allowing for an exhaustive depiction of system dynamics. The findings validate that the amalgamation of H₂T with photovoltaic-driven electrolysis may significantly improve both renewable energy and hydrogen production. This research aligns with Saudi Vision 2030 and global clean-energy initiatives, including the Paris Agreement, to tackle climate change and its negative impacts. An integrated green hydrogen system, informed by this study’s findings, could significantly improve energy sustainability, strengthen production reliability, and augment hydrogen output, fully aligning with economical, technical, and environmental objectives. Full article

Sulfamethoxazole (SMX), a widely used antibiotic, poses potential threats to ecosystems and human health due to its persistence and residues in aquatic environments. This study developed a novel intelligent water treatment system, namely Intelligent Pulsed Electrochemical Activation of NaClO₂ (IPEA_NaClO2), which integrates a FeCuC-Ti₄O₇ composite electrode with machine learning (ML) to achieve efficient SMX removal and energy consumption optimization. Six key operational parameters—initial SMX concentration, NaClO₂ dosage, reaction temperature, reaction time, pulsed potential, and pulsed frequency—were systematically investigated to evaluate their effects on removal efficiency and electrical specific energy consumption (E-SEC). Under optimized conditions (SMX 10 mg L⁻¹, NaClO₂ 60~90 mM, pulsed frequency 10 Hz, temperature 313 K) for 60 min, the IPEA_NaClO2 system achieved an SMX removal efficiency of 89.9% with a low E-SEC of 0.66 kWh m⁻³. Among the ML models compared (back-propagation neural network, BPNN; gradient boosting decision tree, GBDT; random forest, RF), BPNN exhibited the best predictive performance for both SMX removal efficiency and E-SEC, with a coefficient of determination (R²) approaching 1 on the test set. Practical application tests demonstrated that the system maintained excellent stability across different water matrices, achieved a bacterial inactivation rate of 98.99%, and significantly reduced SMX residues in a simulated agricultural irrigation system. This study provides a novel strategy for the intelligent control and efficient removal of refractory organic pollutants in complex water bodies. Full article

Organic and inorganic peroxides can induce intracellular redox homeostasis. In this study, a γ-cyclodextrin/genistein inclusion complex (γ-CD/GEN) was constructed to systematically elucidate the molecular mechanism by which it catalyzes GPx4-mediated peroxide reduction. The results indicate that the incorporation of γ-CD effectively disrupts the aggregated state of GEN, achieving an encapsulation efficiency (EE) exceeding 40%. Surface-enhanced Raman spectroscopy (SERS) analysis reveals significant differences in the catalytic behavior of γ-CD/GEN toward cumene hydroperoxide (CHP) and hydrogen peroxide (H₂O₂): the reduction efficiency of CHP depends on both the concentration of γ-CD/GEN and GPx4, whereas the reduction of H₂O₂ is primarily regulated by the concentration of γ-CD/GEN. Isotope effect studies demonstrate that the reduction of CHP relies more on radical-initiated reactions, while the reduction of H₂O₂ involves proton transfer, with the differences in reduction rates correlating with their respective redox mechanisms. Molecular docking and molecular dynamics simulations further confirm that γ-CD/GEN can stably bind to the Sec (Cys)-46 site in the active center of GPx4, thereby enhancing its catalytic activity. This study provides a theoretical basis for the development of antioxidant strategies based on the precise regulation of enzyme activity. Full article

With the acceleration of digital transformation, open-source software has become a fundamental component of modern smart grids and other critical infrastructures. However, the complex dependency structures of open-source ecosystems and the continuous emergence of vulnerabilities pose substantial challenges to software supply chain security. In power information networks and cyber–physical control systems, vulnerabilities in open-source components integrated into Supervisory Control and Data Acquisition (SCADA), Energy Management System (EMS), and Distribution Management System (DMS) platforms and distributed energy controllers may propagate along the supply chain, threatening system security and operational stability. In such application scenarios, large language models (LLMs) often suffer from limited semantic accuracy when handling domain-specific security terminology, as well as deployment inefficiencies that hinder their practical adoption in critical infrastructure environments. To address these issues, this paper proposes KD-SecBERT, a domain-specific semantic bidirectional encoder optimized through multi-level knowledge distillation for open-source software supply chain security in smart grid applications. The proposed framework constructs a hierarchical multi-teacher ensemble that integrates general language understanding, cybersecurity-domain knowledge, and code semantic analysis, together with a lightweight student architecture based on depthwise separable convolutions and multi-head self-attention. In addition, a dynamic, multi-dimensional distillation strategy is introduced to jointly perform layer-wise representation alignment, ensemble knowledge fusion, and task-oriented optimization under a progressive curriculum learning scheme. Extensive experiments conducted on a multi-source dataset comprising National Vulnerability Database (NVD) and Common Vulnerabilities and Exposures (CVE) entries, security-related GitHub code, and Open Web Application Security Project (OWASP) test cases show that KD-SecBERT achieves an accuracy of 91.3%, a recall of 90.6%, and an F1-score of 89.2% on vulnerability classification tasks, indicating strong robustness in recognizing both common and low-frequency security semantics. These results demonstrate that KD-SecBERT provides an effective and practical solution for semantic analysis and software supply chain risk assessment in smart grids and other critical-infrastructure environments. Full article

Post-cardiac arrest syndrome (PCAS) remains a major cause of mortality and neurological impairment following successful resuscitation, yet the mechanisms linking global ischemia–reperfusion injury to microvascular and systemic dysfunction are not yet completely understood. While prior work has focused on inflammation, endothelial injury, and circulatory collapse, the central role of platelets in coordinating these pathological processes has not been comprehensively examined. This review provides the first integrated framework positioning platelets as core modulators, rather than secondary participants, in PCAS pathophysiology. We synthesize emerging evidence demonstrating that ischemia and reperfusion transform platelets into potent thromboinflammatory effectors through oxidative stress, DAMP-mediated pattern recognition signaling, and mitochondrial dysfunction. Hyperactivated platelets drive cerebral microthrombus formation, coronary no-reflow, and peripheral organ hypoperfusion, while platelet–leukocyte aggregates, neutrophil extracellular traps, and platelet-derived microparticles amplify systemic inflammation and endothelial injury. We further highlight the clinical significance of dynamic platelet dysfunction in coagulopathy, prognostication, and responses to post-arrest therapies including targeted temperature management and ECMO. Finally, we outline a novel, platelet-centered therapeutic paradigm, emphasizing selective interventions, such as GPVI inhibition, P-selectin blockade, FXI/XIa inhibition, and NETosis modulation, that target pathological platelet activity while preserving essential hemostatic function. In this review, by reframing platelets as the central determinants of PCAS, we report new mechanistic insights and therapeutic opportunities that are complementary to the existing post-arrest strategies and have the potential to improve survival and neurological outcomes after cardiac arrest. Full article

Background: Glypican-3 (GPC3) is frequently overexpressed in hepatocellular carcinoma (HCC) and serves as a circulating biomarker. Limited evidence exists regarding whether plasma or serum constitutes the optimal matrix for GPC3 measurement. This study aimed to investigate this gap. Methods: Between December 2024 and September 2025, 100 participants were prospectively enrolled, including 33 healthy controls, 29 individuals with chronic liver disease, and 38 patients with HCC. Paired serum and plasma samples were analyzed under fresh conditions and after storage for seven days at 4 °C and −70 °C. GPC3 concentrations were compared across groups. Subsequently, correlation and area under the receiver operating characteristic curve (AUROC) analyses were conducted. Results: In fresh samples of the controls, median plasma GPC3 levels were significantly higher than those in serum (82.36 pg/mL, IQR: 67.56–92.42 vs. 30.89 pg/mL, IQR: 20.36–41.12; p < 0.001). After seven days of storage, plasma GPC3 concentrations declined markedly at both 4 °C (41.73 pg/mL, IQR: 32.49–55.37; p < 0.001) and −70 °C (45.53 pg/mL, IQR: 25.30–55.65; p < 0.001), with no significant difference between the two storage conditions (p = 0.610). In contrast, serum GPC3 levels remained relatively stable across fresh, 4 °C (31.10 pg/mL, IQR: 16.84–38.60), and −70 °C (25.31 pg/mL, IQR: 14.36–40.74) conditions (p = 0.645). Both matrices under −70 °C storage effectively discriminated HCC from non-HCC cases, although serum demonstrated a significantly better diagnostic performance (AUROC: 0.836, 95% CI: 0.749–0.902 vs. 0.772, 95% CI: 0.677–0.850; p = 0.013). Conclusions: Although plasma offers operational convenience and higher baseline GPC3 levels, serum provides both greater stability and superior diagnostic accuracy under frozen conditions, thus supporting its use as the preferred specimen matrix in clinical and research applications. Full article

Background/Objectives: Tibial plateau fractures are difficult to detect using X-ray imaging due to limited three-dimensional visibility. This study evaluated the performance of four You Only Look Once (YOLO) deep learning models trained on different radiographic views for fracture detection. Methods: A total of 1489 knee X-rays were collected from a tertiary referral hospital, comprising 727 fracture images and 762 non-fracture images. YOLOv4, YOLOv5, YOLOv8, and YOLOv9 were each trained using anteroposterior (AP), lateral, and combined views. Results: YOLO models trained on AP views consistently outperformed those trained on other views. YOLOv9 trained on AP images achieved the highest accuracy, specificity, precision, F1-score, and area under the curve (AUC) of 0.99, with both sensitivity and negative predictive value (NPV) at 1.00. YOLOv8 trained on AP views reached 0.97 across all metrics with an AUC of 0.98. YOLOv5 trained on AP images achieved an accuracy and F1-score of 0.98, a sensitivity and NPV of 0.97, and an AUC of 1.00. YOLOv4 trained on AP views showed slightly lower performance, with an accuracy and F1-score of 0.96 and an AUC of 1.00. External validation confirmed the strong generalizability of AP-trained models, particularly YOLOv9, which reached an accuracy of 0.87, a sensitivity of 1.00, a specificity of 0.75, a precision of 0.80, an NPV of 1.00, an F1-score of 0.88, and an AUC of 0.93. Artificial intelligence-assisted YOLO models showed strong potential in detecting tibial plateau fractures. Conclusions: Models trained on AP views consistently achieved better diagnostic accuracy than those using other views. Among all, YOLOv9 delivered the best results, highlighting the benefits of newer deep learning architectures. Full article

Hybrid fluorinated copolymers containing POSS moieties along with fluorinated homopolymers were synthesized via organocatalyzed atom transfer radical (co)polymerization (O-ATRP) of fluoroalkyl methacrylate (FMA) and a POSS-based monomer (IBSS) using perylene as a photocatalyst. Linear and four- and eight-armed star-shaped (co)polymers in a wide range of molecular weights with M_n(SEC) up to 53,100 g/mol for poly(FMA), 22,700 g/mol for poly(IBSS) and 87,300 g/mol for poly(FMA-co-IBSS) were successfully prepared. During polymerization, C–F activation was found to induce chain transfer and branching reactions, contributing to structural diversity. A mechanism for chain transfer to the polymer resulting in branching was proposed, applying density functional theory (DFT). Films based on the obtained (co)polymers showed tunable morphology, high thermal stability (up to 306 °C) and hydrophobicity, with water contact angles reaching 98°. Full article