Search Results (1,612)

The present study reports the design and physicochemical characterization of a hybrid nanoparticle system for the potential intranasal delivery of galantamine (GAL), aimed at improving its bioavailability. Carbon dots (CDs) were used to load GAL, enhancing its dissolution and stability, and were subsequently incorporated into a poly(lactic-co-glycolic acid)–curcumin (PLGA–Cur) conjugate matrix. The successful formation of the PLGA-Cur conjugate was verified via ¹H-NMR and FTIR spectroscopy, while the loading of GAL and its physical state in the CDs was assessed via FTIR and pXRD, respectively. The resulting GAL-CD/PLGA–Cur nanoparticles were spherical, with particle sizes varying from 153.7 nm to 256.3 nm, a uniform morphology and a narrow size distribution. In vitro release studies demonstrated a multi-phase sustained release pattern extending up to 12 days. Spectroscopic and thermal analyses confirmed successful conjugation and molecular interactions between GAL and the carrier matrix. This proof-of-concept hybrid system demonstrates promising controlled, multi-phase sustained galantamine release in vitro, highlighting the role of curcumin conjugation in modulating polymer structure and release kinetics and providing a foundation for future biological evaluation. Full article

The anticipated transition from 5G to 6G is driven not by incremental performance demands but by a widening mismatch between emerging application requirements and the capabilities of existing cellular systems. Despite rapid progress across 3GPP Releases 15–20, the current literature lacks a unified analysis that connects these standardization milestones to the concrete technical gaps that 6G must resolve. This study addresses this omission through a cross-release, application-driven review that traces how the evolution from enhanced mobile broadband to intelligent, sensing integrated networks lays the foundation for three core 6G service pillars: immersive communication (IC), everything connected (EC), and high-precision positioning. By examining use cases such as holographic telepresence, cooperative drone swarms, and large-scale Extended Reality (XR) ecosystems, this study exposes the limitations of today’s spectrum strategies, network architectures, and device capabilities and identifies the performance thresholds of Tbps-level throughput, sub-10 cm localization, sub-ms latency, and 10 M/km² device density that next-generation systems must achieve. The novelty of this review lies in its synthesis of 3GPP advancements in XR, the non-terrestrial network (NTN), RedCap, ambient Internet of Things (IoT), and consideration of sustainability into a cohesive key performance indicator (KPI) framework that links future services to the required architectural and protocol innovations, including AI-native design and sub-THz operation. Positioned against global initiatives such as Hexa-X and the Next G Alliance, this paper argues that 6G represents a fundamental redesign of wireless communication advancement in 5G, driven by intelligence, adaptability, and long-term energy efficiency to satisfy diverse uses cases and requirements. Full article

Fine particulate matter (PM2.5)-induced ovarian damage has attracted widespread attention, but differences in cytotoxicity and underlying mechanisms of water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions are unclear. To investigate potential effects of PM2.5 from livestock farming environments on animal ovaries, PM2.5 samples were collected from large-scale cattle barns. There were significant differences between fractions regarding elemental composition, proportion of water-soluble ions, polycyclic aromatic hydrocarbon content, and endotoxin concentrations. Based on transcriptome sequencing results, in a cowshed PM2.5 exposure model (rats), differentially expressed ovarian mRNAs were significantly enriched in signaling pathways such as cytokine interaction and the Hippo pathway, with the expression of thioredoxin-interacting protein (Txnip) significantly increased. In vitro (primary rat ovarian granulosa cells), short-term exposure to WS-PM2.5 (12 h) significantly induced inflammatory factor release, acute oxidative stress, mitochondrial dysfunction, and intracellular Ca²⁺ overload, with characteristics of rapid acute injury. However, extended (24 h) WIS-PM2.5 exposure had greater disruptive effects on estrogen homeostasis, intracellular enzyme release (LDH), and mitochondrial structure (subacute characteristics). Furthermore, downregulating Txnip expression via inhibitors effectively mitigated cowshed PM2.5-induced ovarian granulosa cell toxicity, oxidative stress, and mitochondrial and hormonal dysfunction. In summary, solubility of cowshed PM2.5 components affected cytotoxic characteristics, and Txnip was a key factor linking oxidative stress to granulosa cell damage. The study provided a mechanistic basis and potential targets for preventing and controlling PM2.5-induced ovarian damage in livestock environments. Full article

Automata and artificial intelligence (AI) have long occupied a central place in cultural and artistic imagination, and the recent proliferation of AI-generated artworks has intensified debates about authorship, creativity, and human agency. Empirical studies show that audiences often perceive AI-generated works as less authentic or emotionally resonant than human creations, with authorship attribution strongly shaping esthetic judgments. Yet little attention has been paid to how AI systems themselves evaluate creative authorship. This study investigates how large language models (LLMs) evaluate literary quality under different framings of authorship—Human, AI, or Human+AI collaboration. Using a questionnaire-based experimental design, we prompted four instruction-tuned LLMs (ChatGPT 4, Gemini 2, Gemma 3, and LLaMA 3) to read and assess three short stories in Italian, originally generated by ChatGPT 4 in the narrative style of Roald Dahl. For each story × authorship condition × model combination, we collected 100 questionnaire completions, yielding 3600 responses in total. Across esthetic, literary, and inclusiveness dimensions, the stated authorship systematically conditioned model judgments: identical stories were consistently rated more favorably when framed as human-authored or human–AI co-authored than when labeled as AI-authored, revealing a robust negative bias toward AI authorship. Model-specific analyses further indicate distinctive evaluative profiles and inclusiveness thresholds across proprietary and open-source systems. Our findings extend research on attribution bias into the computational realm, showing that LLM-based evaluations reproduce human-like assumptions about creative agency and literary value. We publicly release all materials to facilitate transparency and future comparative work on AI-mediated literary evaluation. Full article

Silicon oxide/graphite (SiO_x/Gr) anodes are promising candidates for high energy-density lithium-ion batteries. However, their complex multiphysics degradation mechanisms pose challenges for accurately interpreting and predicting capacity fade behavior. In particular, existing multiphysics models typically treat gas generation and solid electrolyte interphase (SEI) growth as independent or unidirectionally coupled processes, neglecting their bidirectional interactions. Here, we develop an electro–thermal–mechanical–gaseous coupled model to capture the dominant degradation processes in SiO_x/Gr anodes, including SEI growth, gas generation, SEI formation on cracks, and particle fracture. Model validation shows that the proposed framework can accurately reproduce voltage responses under various currents and temperatures, as well as capacity fade under different thermal and mechanical conditions. Based on this validated model, a mechanistic analysis reveals two key findings: (1) Gas generation and SEI growth are bidirectionally coupled. SEI growth induces gas release, while accumulated gas in turn regulates subsequent SEI evolution by promoting SEI formation through hindered mass transfer and suppressing it through reduced active surface area. (2) Crack propagation within particles is jointly governed by the magnitude and duration of stress. High-rate discharges produce large but transient stresses that restrict crack growth, while prolonged stresses at low rates promote crack propagation and more severe structural degradation. This study provides new insights into the coupled degradation mechanisms of SiO_x/Gr anodes, offering guidance for performance optimization and structural design to extend battery cycle life. Full article

This study investigates the dispersion and condensation behavior of tritiated water vapor released into the atmosphere using moist air as a carrier, with an emphasis on safety optimization for nuclear power plant effluent discharge. A coupled heat and mass transfer model was developed and implemented in CFD simulations to analyze the evolution of temperature and relative humidity during the mixing of exhaust moist air with ambient air. The effects of key atmospheric and operational parameters—including the ambient wind speed, turbulence intensity, ambient temperature, relative humidity, and exhaust velocity—were systematically examined. The results indicate that the temperature difference between the exhaust gas and ambient air is the primary factor governing condensation risk. Low wind speeds and weak turbulence favor near-field humidity accumulation, while higher wind speeds and turbulence intensities enhance mixing and dilution, thereby reducing local humidity peaks but extending the downwind impact range. Increasing exhaust velocity strengthens plume rise and long-range transport due to enhanced momentum and latent heat release, mitigating accumulation near the chimney outlet. Furthermore, high ambient temperatures significantly increase the air’s moisture-holding capacity, allowing higher exhaust humidity without inducing condensation. Full article

The mammalian lung operates under a biological paradox, requiring architectural fragility for gas exchange while maintaining robust regenerative plasticity to withstand injury. The Hippo signaling pathway has emerged as a central “rheostat” in orchestrating these opposing needs, yet the distinct roles of its downstream effectors remain underappreciated. This review synthesizes recent genetic and mechanobiological advances to propose a “Tale of Two Effectors” model, arguing for the functional non-redundancy of YAP and TAZ. We posit that YAP functions to drive airway progenitor expansion, mechanical force generation, and maladaptive remodeling. Conversely, TAZ—regulated uniquely via transcriptional mechanisms and mechanotransduction—acts as an obligate driver of alveolar differentiation and adaptive repair through an NKX2-1 feed-forward loop. Furthermore, we introduce the “See-Saw” model of tissue fitness, where mesenchymal niche collapse releases the mechanical brake on the epithelium, triggering the bronchiolization characteristic of pulmonary fibrosis. Finally, we extend this framework to malignancy, illustrating how Small Cell Lung Cancer (SCLC) subtypes mirror these developmental and regenerative states. This integrated framework offers new therapeutic distinct targets for modulating tissue fitness and resolving fibrosis. Full article

Metastatic uveal melanoma (MUM) remains largely refractory to immune-checkpoint inhibition, so recent research has turned to bispecific T-cell engagers (BTCEs), adoptive-cell therapies (ACTs), and oncolytic viruses (OVs). To summarize the available clinical evidence, we performed a structured literature search across PubMed, Scopus, and Europe PMC for primary studies published between 1 January 2010 and 31 May 2025 that enrolled at least three adults with MUM, treated with one of these modalities, and that reported efficacy or grade-3+ safety outcomes; two reviewers independently performed screening, data extraction, and risk-of-bias assessment, and because of notable heterogeneity, we synthesized the findings narratively. Twenty-two studies met the criteria—thirteen phase I–III trials, eight observational cohorts, and one case series—covering fifteen BTCE cohorts, four ACT cohorts, and three OV cohorts. Tebentafusp, the dominant BTCE evaluated in roughly 1150 HLA-A*02:01-positive patients, extended median overall survival from 16.0 to 21.7 months (hazard ratio 0.51, with three-year follow-up HR 0.68) in its pivotal phase-III trial despite objective response rates of only 5–12%, with early skin rash and week-12 circulating-tumor-DNA clearance emerging as consistent markers of benefit. Tumor-infiltrating lymphocyte therapy, administered to about thirty patients, produced objective responses in 11–35% and occasional durable complete remissions, although median progression-free survival remained 2–6 months and severe cytopenias were universal. Three early-phase OV studies, totaling twenty-nine patients, yielded no radiographic responses but showed tumor-specific T-cell expansion and transient disease stabilization. Safety profiles reflected the mechanism of action: tebentafusp most often caused rash, pyrexia, and usually manageable cytokine-release syndrome with grade-3+ events in 40–70% yet discontinuation in roughly 2%; TIL therapy toxicity was driven by lymphodepleting chemotherapy and high-dose interleukin-2 with one treatment-related death; and OVs were generally well tolerated with no more than 20% grade-3 events. Full article

Ammonium nitrogen (NH₄⁺-N) removal and recovery from wastewater have been critical issues worldwide and key to achieving a sustainable nitrogen cycle and circular economy. In this study, we designed and constructed a pilot-scale air stripping system integrated with a nutrient-capture unit and evaluated the effective pH, temperature, and airflow conditions for maximising NH₄⁺-N removal and recovery from dairy processing wastewater (DPW). Our results demonstrated that increasing pH and temperature substantially enhances NH₄⁺-N removal via air stripping, with higher airflow rates further improving performance. Under these conditions (pH 11, 32 °C, and 300 L min⁻¹), NH₄⁺-N removal from synthetic wastewater reached ≈40% after 6 h air stripping. In comparison, real DPW exhibited slightly lower removal efficiency under the same conditions, achieving ≈34%, likely due to its more complex matrix. Additionally, incorporating a chemical precipitation step followed by filtration prior to air stripping removed NH₄⁺-N from DPW, achieving ≈43%. However, extending the stripping duration under identical conditions significantly improved removal performance, increasing NH₄⁺-N removal in DPW to ≈70%. The downstream capturing system, consisting of acid bath and granulated activated carbon (GAC), consistently recovered 70–95% of the released ammonia (NH₃) when even upstream NH₄⁺-N removal via air stripping was moderate. The GAC effectively adsorbed the volatilised NH₃, achieving adsorption capacities of up to ≈18 mg/kg. Overall, this integrated system demonstrates strong potential for simultaneous NH₄⁺-N removal and recovery from industrial wastewater streams, offering notable environmental benefits. Full article

Background: Oral insulin improves compliance and convenience in patients with diabetes who require regular needle injections. However, the clinical application of oral insulin preparations has been limited due to instability and inefficient permeation through the gastrointestinal tract. In this study, a novel cationic polysaccharide nanodrug delivery platform was designed for efficient oral insulin delivery. Methods: The innovative thiolated trimethyl chitosan-grafted β-cyclodextrin (NCT) was synthesized by utilizing N-trimethyl chitosan (TMC) as the polymer backbone. This involved modifying TMC with thiol group-containing N-acetylcysteine and carboxymethyl-β-cyclodextrin that possesses hydrophobic cavities via an amide condensation reaction. Subsequently, this polymer was employed to construct the NCT nanoparticle system using an ionic cross-linking method. The physicochemical properties of the NCT nanoparticles were systematically analyzed, and their therapeutic efficacy was comprehensively evaluated in streptozotocin (STZ)-induced animal models. Results: The NCT nanoparticles demonstrated mucus adhesion, permeability, and pH sensitivity, which facilitated a slow and controlled release within the gastrointestinal microenvironment due to both ionic electrostatic interactions and disulfide bonding interactions. The experiments revealed in vivo that insulin/NCT nanoparticles extended the retention time of insulin in the small intestine. Blood glucose levels decreased to approximately 39% of the initial level at 5 h post-administration while exhibiting smooth hypoglycemic efficacy. Simultaneously, insulin bioavailability increased to 12.58%. Conclusions: The NCT nanoparticles effectively protect insulin from degradation in the gastrointestinal microenvironment while overcoming intestinal barriers, thereby providing a promising approach to oral biomolecule delivery. Full article

Leishmaniasis, a widespread, neglected infectious disease with limited effective treatments and increasing drug resistance, demands innovative therapeutic approaches. In this study, we report the fabrication of pentamidine (PTM)-loaded polycaprolactone (PCL) nanofibers using solution blow spinning (SBS) as a potential topical delivery system for cutaneous leishmaniasis (CL). Homogeneous PCL fiber mats were produced using a simple SBS set-up with a commercial airbrush after optimizing several working parameters. Drug release studies demonstrated sustained PTM release profile over time, which was mechanistically modeled by utilizing the complete nanofiber diameter distribution, obtained from SEM analysis of the blow-spun material. FTIR and XRD analyses were performed to investigate the drug–polymer interactions, revealing molecularly dispersed PTM at low-proportion drug/polymers and partial crystallinity at high loadings. The released PTM exhibited significant leishmanicidal activity against Leishmania major promastigotes. Biological investigations showed that SBS-formulated PTM treatment was consistent with the downregulation of parasite genes involved in cell division and DNA replication (cycA, cyc6, pcna, top2, mcm4) and upregulation of the drug response gene (prp1). The controlled delivery of PTM within SBS-fabricated PCL nanofibers provides an effective therapeutic approach to tackle CL and, through the incorporation of additional drugs, could be extended to address a broader range of cutaneous infections. Full article

Controlled-release systems must translate material design choices into predictable pharmacokinetic (PK) profiles, yet purely mechanistic or purely data-driven models often underperform when tuning complex polymer networks. Here, we develop tunable poly(vinyl formal) membranes (PVFMs) for diclofenac delivery and integrate classical kinetic analysis with a Generalized Regression Neural Network (GRNN) to connect formulation variables to release behavior and PK-relevant targets. PVFMs were synthesized across a gradient of crosslink densities by varying HCl content; diclofenac release was quantified under standardized conditions with geometry and dosing rigorously controlled (thickness, effective area, surface-area-to-volume ratio, and areal drug loading are reported to ensure reproducibility). Release profiles were fitted to Korsmeyer–Peppas, zero-order, first-order, Higuchi, and hyperbolic tangent models, while a GRNN was trained on material descriptors and time to predict cumulative release and flux, including out-of-sample conditions. Increasing crosslink density monotonically reduced swelling, areal release rate, and overall release efficiency (strong linear trends; r ≈ 0.99) and shifted transport from anomalous to Super Case II at the highest crosslinking. Classical models captured regime transitions but did not sustain high accuracy across the full design space; in contrast, the GRNN delivered superior predictive performance and generalized to conditions absent from training, enabling accurate interpolation/extrapolation of release trajectories. Beyond prior work, we provide a material-to-PK design map in which crosslinking, porosity/tortuosity, and hydrophobicity act as explicit “knobs” to shape burst, flux, and near-zero-order behavior, and we introduce a hybrid framework where mechanistic models guide interpretation while GRNN supplies robust, data-driven prediction for formulation selection. This integrated PVFM–GRNN approach supports rational design and quality control of controlled-release devices for diclofenac and is extendable to other therapeutics given appropriate descriptors and training data. Full article

Morningglories (Ipomoea lacunosa, I. hederacea, and I. purpurea) are persistent, problematic weeds in summer row crops throughout warm-temperate regions. Their vining growth habit and enduring seedbanks lead to recurring infestations and harvest interferences. This review synthesizes current knowledge on the seed ecology of these species to clarify how dormancy, germination, and emergence processes contribute to their persistence. Published anatomical and ecological studies were examined to summarize dormancy mechanisms, environmental signals regulating dormancy release, germination requirements, and seasonal emergence patterns. Morningglories exhibit a dormancy system dominated by physical dormancy, occasionally combined with a transient physiological component. Dormancy release is promoted by warm and fluctuating temperatures, hydration–dehydration cycles, and long-term seed-coat weathering. Once permeable, seeds germinate across broad temperature ranges, vary in sensitivity to water potential, and show limited dependence on light. Field studies indicate extended emergence windows from late spring through midsummer, especially in no-till systems where surface seeds experience strong thermal and moisture fluctuations. Despite substantial progress, significant gaps remain concerning maternal environmental effects, population-level variation, seedbank persistence under modern management, and the absence of mechanistic emergence models. An improved understanding of these processes will support the development of more predictive and ecologically informed management strategies. Full article

Compared to cameras and LiDAR, radar provides superior robustness under adverse conditions, as well as extended sensing range and inherent velocity measurement, making it critical for surveillance applications. To advance research in deep learning-based radar perception technology, several radar datasets have been publicly released. However, most of these datasets are designed for autonomous driving applications, and existing radar surveillance datasets suffer from limited scene and target diversity. To address this gap, we introduce KuRALS, a range–Doppler (RD)-level radar surveillance dataset designed for learning-based long-range detection of moving targets. The dataset covers aerial (unmanned aerial vehicles), land (pedestrians and cars) and maritime (boats) scenarios. KuRALS is real-measured by two Kurz-under (Ku) band radars and contains two subsets (KuRALS-CW and KuRALS-PD). It consists of RD spectrograms with pixel-wise annotations of categories, velocity and range coordinates, and the azimuth and elevation angles are also provided. To benchmark performance, we develop a lightweight radar semantic segmentation (RSS) baseline model and further investigate various perception modules within this framework. In addition, we propose a novel interference-suppression loss function to enhance robustness against background interference. Extensive experimental results demonstrate that our proposed solution significantly outperforms existing approaches, with improvements of $10.0\%$ in mIoU on the KuRALS-CW dataset and $9.4\%$ on the KuRALS-PD dataset. Full article

This study investigates the impact of the expansion ratio on combustion oscillation phenomena and their driving mechanisms in a solid-fuel ramjet (SFRJ) through experimental and numerical simulations. By analyzing flow characteristics, combustion oscillations at varying expansion ratios, heat release patterns, and species distribution within the engine, the following key conclusions are drawn: Ground tests revealed first-order pressure oscillations with a dominant frequency of approximately 600 Hz, exhibiting a half-wavelength oscillation pattern. As the expansion ratio increased from 1.75 to 2.25, the amplitude of the first-order oscillation increased by 21%, from 1.89 kPa, while the dominant frequency initially rose and then decreased, peaking at an expansion ratio of 2. The shear-induced downstream of the step was identified as a critical factor influencing heat release and acoustic pressure oscillations in the combustion chamber, which led to periodic unstable heat release that amplified combustion oscillation amplitudes. The numerical results show that the periodic motion of vortices induced by flow shear downstream of the sudden expansion step causes oscillations in the temperature distribution on the propellant surface, which is one of the key factors contributing to combustion instability and pressure oscillations. When the expansion ratio is increased to 2.0 and 2.25, the dominant frequency of pressure oscillations increases by 15.2% and 13.2%, respectively, while the amplitude rises by 7.9% and 30%, respectively. The vortice development blurs the oxygen-rich and fuel-rich zones, enhancing the mixing of oxygen and fuel-rich gases and exacerbating the instability of heat release. Larger expansion ratios further extended the axial range of unstable species distribution, increasing nonuniformity within the combustion region. Full article