Search Results (461)

Slag splashing protection is the dominant technology for extending refractory lining service life and enhancing production efficiency in basic oxygen furnace (BOF) steelmaking. However, the intrinsic mechanism of gas-slag-steel multiphase coupled splashing remains poorly understood, and existing numerical methods suffer from prohibitive computational costs and inaccurate characterization of interfacial momentum transfer and multiphase interactions. This study establishes a fully coupled three-dimensional numerical model integrating Volume of Fluid (VOF)–Discrete Particle Method (DPM) bidirectional phase transition, adaptive mesh refinement (AMR), and Eulerian Wall Film Model (EWFM), and the multiphase flow simulation in this study adopts constant thermophysical parameters of molten steel and slag at the industrial splashing temperature of 1650 °C. Taking the Blowing Number (N_B) as the core similarity criterion, a 1:10 scaled geometric model of a 50-ton industrial BOF is employed to systematically investigate the regulatory effects of top-blowing flow rate, lance height, and N_B on droplet splashing behavior and wall liquid film evolution. The model is validated against mercury-glycerol cold model experimental data, with a relative error of less than 3% in total splashing mass prediction. Results demonstrate that increasing N_B significantly enhances splashing intensity. Under optimal conditions (200 mm lance height, 11.76 Nm³/h flow rate, N_B = 9.30), the wall liquid film fully covers the middle-upper furnace wall with a uniform thickness of 0.8–1.2 mm. N_B dominates jet momentum distribution: high N_B forms a deep-penetrating four-lobed impact cavity, remarkably improving droplet axial momentum and residence time. Molten steel droplets concentrate at 3–4 mm, while slag droplets shift to 2–4 mm at high flow rates of 11.76 Nm³/h, with maximum slag droplet production at N_B = 6.99. This work provides reliable theoretical support for industrial BOF slag-splashing process optimization. Full article

Bacterial extracellular vesicles (BEVs) are nano-sized lipid bilayer particles secreted by bacteria, capable of carrying various proteins, lipids, nucleic acids, and pathogen-associated molecular patterns (PAMPs). The biosynthetic pathway of BEVs determines their load components, physicochemical properties, and different biological activities. Increasing evidence indicates that BEVs play an important role in mediating host immune responses and the dynamic regulation of bacterial biofilms. Additionally, BEVs may serve as a molecular bridge between the two. BEVs derived from pathogens can trigger pro-inflammatory cascades, assist bacteria in immune evasion, and further accelerate the maturation of biofilms, forming a vicious cycle of persistent infection and inflammatory damage. In contrast, BEVs derived from probiotics can maintain host immune homeostasis and exert direct anti-biofilm and synergistic antibacterial effects, thereby breaking the pathological cycle. However, significant methodological research bottlenecks have greatly hindered the comparability and clinical translation of BEVs research. This article systematically summarizes the classification of BEVs and their biosynthetic mechanisms, compares the differential effects of BEVs from pathogenic bacteria and probiotic bacteria on immunity, clarifies the dual regulatory role of BEVs throughout the life cycle of biofilms, and highlights the bridging function of BEVs in the immune–biofilm interaction. Additionally, this article also discusses the current development of BEVs in clinical translation applications, such as vaccine development, antibiotic delivery, and mucosal inflammation intervention, and outlines the key industrial and clinical challenges faced in the future development of BEVs-based therapeutic approaches. Full article

Messenger RNA–lipid nanoparticles (mRNA-LNPs) have emerged as a transformative platform for nucleic acid therapeutics, yet their complex four-component lipid architecture comprising ionizable lipids, PEG–lipids, helper phospholipids, and cholesterol presents substantial analytical challenges for quality control and regulatory compliance. This review presents, for the first time, a critical evaluation of liquid chromatography–mass spectrometry (LC-MS) strategies specifically tailored to quantify all four lipid classes and their degradation products within mRNA-LNP formulations. Unlike prior general lipidomics reviews, we provide a comparative assessment of orthogonal LC modalities including reversed-phase ultra-high-performance liquid chromatography, hydrophilic-interaction liquid chromatography, ion-pairing reversed-phase LC, and high-performance liquid chromatography charged aerosol detection with explicit performance metrics (sensitivity, linearity, and run time). We further integrate emerging analytical frontiers—single-particle analysis, degradation product profiling (e.g., oxysterols and reactive electrophiles), and regulatory frameworks (ICH Q2(R1), Analytical Quality by Design)—to offer a practical guide for method selection. This review’s uniqueness lies in its systematic, application-focused comparison of LC-MS workflows addressing lipid-specific vulnerabilities, matrix effects, and stability-indicating parameters, filling a critical gap between analytical chemistry and mRNA-LNP product development. Full article

Nanoplastics (NPs) in drinking water should be interpreted as the downstream analytical endpoint of a broader continuum of aquatic plastic pollution rather than as an isolated problem. Their detection remains analytically immature because environmentally relevant concentrations are low, particle chemistries are heterogeneous, natural colloids and treatment residuals interfere with measurement, and no single method can simultaneously resolve size, morphology, polymer identity, and mass concentration. Unlike occurrence-centered reviews, this PRISMA-guided review treats drinking-water nanoplastics as a metrological and molecular-identification problem in which preprocessing, particle-level confirmation, polymer-specific quantification, and uncertainty reporting must be integrated. A formal search was closed on 11 April 2026 using prespecified query families across publicly accessible scholarly records and backward citation chaining; 33 unique records were screened, 25 full texts were assessed, and 22 studies were included in the qualitative synthesis. Current evidence indicates that conventional FTIR and routine Raman workflows are inadequate for true nanoscale analysis, whereas advanced Raman-based approaches, AFM-IR, optical photothermal infrared spectroscopy, surface-enhanced Raman spectroscopy, and pyrolysis-gas chromatography-mass spectrometry offer complementary strengths but still have major limitations in throughput, particle-level information, or quantification. The main conclusion is that current uncertainty reflects unresolved analytical chemistry and metrological constraints as much as environmental variability. Regulatory progress will depend on orthogonal workflows, contamination-controlled preprocessing, validated reference materials, LOD/LOQ reporting, and interlaboratory harmonization. Full article

Waste-derived fertilising materials, including sewage sludge, compost, digestate, food-waste-derived products and commercial organic or organo-mineral fertilisers, return nutrients to farmland but can also transfer microplastics to agricultural soil. This critical review examines their occurrence across these streams, analytical constraints, fate after application and the EU regulatory framework. Reported abundances span orders of magnitude and cannot be pooled because extraction, polymer identification and reporting are not harmonised, while particle-counting and mass-based methods measure different quantities. Field evidence indicates topsoil retention and accumulation after repeated application, whereas crop transfer and field-scale ecological effects remain poorly quantified. Regulation (EU) 2019/1009 sets no microplastic-specific product limit. For compost qualifying as CMC 3 and digestate other than fresh crop digestate qualifying as CMC 5, it controls plastic impurities above 2 mm by mass, while smaller particles remain outside that criterion. Waste-derived fertilisers can therefore form a recurrent, incompletely regulated pathway for microplastic transfer to soil. Controlled studies demonstrate hazard potential for selected particles and exposure conditions, but the magnitude and likelihood of effects under field conditions remain uncertain. The immediate priority is harmonised monitoring and reporting of the sub-2 mm fraction, including a stated lower size limit, polymer-confirmed particle counts and minimum QA/QC. Full article

Ultrafine particles (UFPs; <100 nm) can penetrate biological barriers and trigger inflammation, oxidative stress, and endothelial dysfunction, yet they remain largely unregulated and understudied relative to PM_2.5. This scoping review, conducted following PRISMA-ScR guidelines, systematically searched PubMed and Scopus for epidemiological studies examining ambient UFP exposure and mortality. Of 704 articles screened, 21 studies published between 2007 and 2025 met inclusion criteria. Fourteen assessed short-term exposure (≤1 month) using time-series or case-crossover designs with central-site particle number concentration monitors, and seven assessed long-term exposure using land-use regression, chemical transport, or machine learning models. A majority of both short-term (10 of 14) and long-term (6 of 7) studies reported positive associations between UFP exposure and mortality, particularly for respiratory outcomes. The strongest associations were observed in studies using higher-resolution or source-specific exposure methods, a pattern consistent with reduced misclassification. However, exposure assessment approaches varied widely in spatial resolution, instrument type, and particle size definitions, introducing substantial heterogeneity that limits comparability across studies. These findings underscore the need for standardized UFP measurement protocols, high-resolution exposure assessment, and further investigation of disparities in exposure and health outcomes to inform regulatory consideration. Full article

Nanoplastics (NPs; <1000 nm) are persistent soil contaminants that suppress extracellular enzyme activity, the biochemical engine of terrestrial nutrient cycling. Despite a rapidly expanding primary literature, no comprehensive meta-analysis has systematically integrated quantitative effect-size synthesis with interpretable machine learning (ML) approaches to identify and rank the physicochemical drivers of NP-induced soil enzymatic toxicity. Following the PRISMA 2020 statement, we systematically searched four databases (Web of Science, Scopus, PubMed, Google Scholar) from database inception through December 2024 and extracted 413 effect sizes from 113 peer-reviewed studies. Hedges’ g was estimated using three-level random-effects models with restricted maximum likelihood (REML) estimation implemented in the metafor package. Three supervised ML algorithms—random forest (RF), gradient boosting machines (GBMs), and support vector regression (SVR)—were trained using 18 study-level predictors derived from the complete meta-analytic dataset, and SHapley Additive exPlanations (SHAP) were applied to quantify and rank the relative importance of individual predictors. The overall meta-analysis demonstrated a significant inhibitory effect of NPs on soil enzyme activity (Hedges’ g = −0.94; 95% CI: −1.14 to −0.73; k = 413; I² = 78.4%; τ² = 0.412). Among the evaluated enzymes, dehydrogenase activity exhibited the greatest inhibition (g = −1.12), whereas polystyrene nanoplastics produced the strongest adverse effects (g = −1.15). Particles smaller than 100 nm caused approximately 2.6-fold greater inhibition than particles larger than 500 nm, and dose–response meta-regression identified a nonlinear increase in toxicity at concentrations exceeding 200 mg kg⁻¹. The RF model demonstrated the highest predictive performance, explaining 73% of the variance in an independent testing dataset (R² = 0.73; test set n = 83). SHAP analysis identified particle diameter as the most influential predictor, revealing an approximate critical threshold of 150 nm, below which inhibitory effects increased markedly. Higher soil organic carbon concentrations partially mitigated enzymatic inhibition, likely through competitive adsorption and reduced nanoplastic bioavailability. Overall, our findings demonstrate that NP-induced inhibition of soil enzymatic activity is widespread and primarily governed by particle size, exposure concentration, and soil properties. The identified 150 nm threshold should be interpreted as a data-driven hypothesis requiring further validation under environmentally realistic exposure scenarios rather than as a universal regulatory limit. Nevertheless, the integration of three-level meta-analysis with interpretable machine learning (SHAP) provides a robust and reproducible framework for identifying key toxicity drivers and supports future ecological risk assessment and evidence-based regulatory decision-making for nanoplastics. Full article

Pharyngeal infection with high-risk human papillomavirus (HPV), particularly HPV16, is biologically distinct from cervical infection because it occurs within the specialized lymphoepithelial environment of Waldeyer’s ring. This review evaluates nanoparticle materials for the prevention, detection, and treatment of pharyngeal HPV, with an emphasis on structure–property–function relationships, mucosal performance, and translational feasibility. Lipid nanoparticle platforms, polymeric nanoparticle platforms, inorganic systems, and hybrid platforms are compared with respect to composition, particle size distribution, surface charge, colloidal stability, biodegradability, payload compatibility, release behavior, and manufacturing complexity. Evidence suggests that lipid and polymeric systems are the most credible near-future candidates for mucosal vaccination and localized nucleic acid delivery because they offer the best balance between controllable fabrication, analytical tractability, and biologically plausible performance in mucus-exposed tissue. By contrast, the development of inorganic theranostics and CRISPR-enabled platforms remains at an earlier stage because repeated mucosal dosing, retention in lymphoid tissue, and combined product regulation impose substantial burdens. A translational roadmap is proposed in which material selection is guided by clinically relevant quality attributes, standardized saliva- and mucus-relevant assays, human tonsil organoid testing, and early attention to manufacturability, safety, and regulatory strategy. The field is promising, but direct pharyngeal HPV data remain limited; accordingly, there is an urgent need for comparative studies that connect nanoparticle architecture to measurable outcomes such as tonsillar deposition, epithelial uptake, immune activation, and local tolerability. Full article

This critical perspective review first classifies glyphosate-sensing platforms and then evaluates their analytical applicability to agricultural runoff. Platforms are divided at the primary level into optical and electrochemical transduction, because these families measure different physical signals and have different sources of matrix interference. They are then grouped by the process that produces selectivity or signal change: direct interaction or metal coordination, affinity recognition by aptamers, antibodies, or molecularly imprinted polymers, catalytic modulation by enzymes or nanozymes, and separation or preconcentration before detection. This hierarchy distinguishes recognition chemistry from transduction method and device configuration. The review next defines four intended analytical applications—trace surveillance, runoff event screening, spill triage, and laboratory-adjacent confirmation—and compares them in terms of matrix, target concentration range, sample preparation, reporting metrics, and quality control requirements. Glyphosate occurs in dissolved and particle-associated forms, degrades mainly to AMPA, and coexists with phosphate, glufosinate, divalent cations, natural organic matter, and suspended sediment. Consequently, the lowest reported LOD is rarely the sole criterion for selecting a method. Matrix-matched calibration, spike recovery, selectivity, response time, storage stability, reader requirements, and invalid result rules determine whether an assay is suitable for a specified analytical application. The most defensible near-term approach combines matrix-specific sample preparation, platform-specific controls, and LC-MS/MS confirmation when results are regulatory, contested, or close to a decision threshold. Full article

Densely distributed small holes significantly affect the mechanical behavior and fracture characteristics of rock masses. In this study, the two-dimensional particle flow code was employed to establish a series of numerical models of dolomitic limestone, with the number of small circular holes increasing according to the sequence (2n − 1)² (n = 1–6). Comparative models with equivalent area and variable spacing were additionally designed to explore their regulatory effects. The strength, crack evolution, and contact force chain distribution of each model were systematically analyzed. The results reveal that the number of small holes exhibits an approximately linear negative correlation with the rock strength. The number of holes dominates the crack initiation location and propagation path. The crack initiation stress gradually decreases with increasing hole number, while the ratio of crack initiation stress to peak stress exhibits a V-shaped trend. As the hole number increases, the distribution of compressive force chains shifts from the sides of holes to the vertical strips between holes, and tensile force chains become significantly enhanced in the areas above and below the holes. Hole spacing and equivalent area exert only local modulating effects; the number and spatial arrangement of holes remain the dominant controls on strength deterioration and fracture evolution. These findings offer a theoretical foundation for stability assessment in rock masses characterized by densely distributed hole defects. Full article

Recent advances in vaccinology have accelerated the shift from conventional live-attenuated and inactivated vaccines toward subunit and nucleic acid-based platforms. Although these next-generation vaccines offer improved safety, rapid adaptability, and manufacturing flexibility, their relatively low intrinsic immunogenicity often requires efficient adjuvants and delivery systems. Nanoparticle-based vaccine platforms have therefore emerged as versatile tools capable of protecting antigens, improving targeted delivery, and modulating both innate and adaptive immune responses. This review summarizes the major classes of nanovaccine platforms, including lipid and polymeric nanoparticles, self-assembling protein nanostructures such as virus-like particles and ferritin nanocages, saponin-based self-assembling complexes, and inorganic nanomaterials. Particular attention is given to how vaccine performance is determined not only by material composition but also by nanoparticle physicochemical properties, biodistribution, cellular uptake, and mechanisms of immune activation. We further discuss the major challenges limiting clinical translation, including scalable manufacturing, safety evaluation, quality control, regulatory requirements, and long-term biocompatibility. Finally, emerging strategies involving hybrid and personalized nanovaccine platforms are highlighted, illustrating how nanotechnology and immunoengineering are transforming vaccine development for both prophylactic and therapeutic applications. Full article

Genome editing is one of the key technologies in contemporary plant biotechnology, which has been revolutionized using CRISPR/Cas systems that offer rapid, flexible, and precise options to improve agricultural characteristics, enhance stress tolerance, and accelerate breeding of crops and trees. Despite the significant benefits of CRISPR/Cas systems, their use is restricted by difficulties in genome-editing materials into plant cells. The conventional approaches include Agrobacterium-mediated transformation, particle bombardment and PEG-mediated transfection; these have contributed significantly to advancements in the field; however, dependent on specific plants and requiring tissue cultures, these methods lead to random transgene insertion and poor transformation efficiency. In addition, nanotechnology represents a novel method of delivering CRISPR cargos into plant cells using minimal invasiveness and potentially without DNA. This review provides a synopsis of the most employed CRISPR/Cas systems within plants, comparing the traditional delivery mechanisms and the various nanotechnological delivery vehicles, such as lipid nanoparticles, carbon nanotubes, DNA nanostructures, mesoporous silica nanoparticles, magnetically responsive nanoparticles and green nanomaterials. This review discusses the present challenges of delivery efficacy, biocompatibility, cargo integrity, and regulatory issues, and provides suggestions for future research directions regarding nanotechnology-assisted genome editing for precision breeding, sustainable agriculture, production of crops tolerant to climate conditions, and forest biotechnology. Full article

Four-wheel-drive electric vehicles equipped with independently controllable driving, braking, and steering actuators provide additional degrees of freedom for reducing electric-machine and tire-loss energy. This paper presents a real-time longitudinal–steering coordinated torque-vectoring framework for a vehicle driven by four in-wheel motors. A model-predictive active-front-steering controller coordinates the front-wheel steering angle and external yaw moment to reduce steering resistance and lateral tire-slip loss. A reduced inter-axle propulsion problem is analyzed using the Karush–Kuhn–Tucker conditions, and its speed-dependent switching threshold is calibrated offline by particle swarm optimization. Regenerative braking is allocated by an Energy-Optimized Distribution curve subject to ideal-distribution and regulatory constraints. For general positive-torque operation, sequential quadratic programming distributes the four wheel torques by considering motor input power, tire-slip energy, total torque, yaw-moment demand, and actuator limits. Hardware-in-the-loop results under the United States high-acceleration driving cycle and a double-lane-change maneuver show that the proposed strategy reduces energy consumption relative to uniform and tire-utilization-based torque-vectoring strategies. Full article

The pathogenesis of cardiovascular diseases (CVDs) is intimately linked to cholesterol dysregulation. While high-density lipoprotein cholesterol (HDL-C) is classically considered cardioprotective, contemporary epidemiological evidence reveals a noncausal, often U-shaped, relationship with CVD risk. Static measurements of HDL-C obscure the structural and functional heterogeneity of circulating HDL particles. Under pathological stress, HDL undergoes extensive structural remodeling into dysfunctional HDL, thereby losing its vasculoprotective properties and instead mediating proatherogenic and proinflammatory responses. This review critically evaluates the biogenesis, maturation, and metabolic trajectory of HDL. By integrating recent advancements in proteomics and lipidomics, we map the intricate compositional shifts within HDL subpopulations and clarify the regulatory roles of HDL-associated microRNAs in intercellular communication. We investigate the specific drivers of HDL dysfunction, which is often exacerbated by comorbidities such as diabetes and chronic kidney disease. Furthermore, we outline the methodological transition from automated homogeneous HDL-C quantification to multidimensional profiling. Shifting the clinical focus from HDL quantity to functional quality resolves the HDL-C paradox, helping to drive the development of precision lipidology and targeted therapies to reverse HDL dysfunction in CVDs. Full article

Safflower (Carthamus tinctorius L.) is a cash crop grown worldwide. Its seeds and flowers are primarily processed for edible oil and medicinal raw materials, while stems and leaves are discarded as agricultural waste. Recently, plant-derived exosome-like nanoparticles (PELNs) have gained growing research interest in food nutrition owing to their exceptional biocompatibility and relatively low cost for large-scale production. This study aimed to explore the potential functional value of safflower leaf agricultural waste by isolating safflower-derived PELNs. Firstly, a protocol was established for the isolation and purification of safflower (Carthamus tinctorius L.)-derived exosome-like nanoparticles (Ct-ELNs) from safflower leaves using sucrose density gradient ultracentrifugation. NTA analysis revealed that the 30–45% sucrose fraction enriched with Ct-ELNs exhibited the most uniform particle size, highest particle concentration, and optimal purity. Transmission electron microscopy confirmed typical PELNs ultrastructure: disc- or cup-shaped vesicles surrounded by bilayer lipid membranes. FM4-64 fluorescence suggests time-dependent association and likely cellular uptake of labeled Ct-ELNs by IPEC-J2 cells. Cellular assays demonstrated that Ct-ELNs elevated IPEC-J2 cell metabolic activity under matched protein-normalized dosing conditions. The 30–45% sucrose fraction showed the most favorable physicochemical profile and preliminary in vitro protective effects, including improved IPEC-J2 cell metabolic activity and modulation of Enterotoxigenic Escherichia coli (ETEC)-induced inflammation-related gene expression. Overall, this study established an optimized isolation protocol for Ct-ELNs derived from safflower leaves. These data indicate that safflower-derived Ct-ELNs confer preliminary cytoprotective transcriptional regulatory effects on intestinal epithelial cells under in vitro culture conditions. Full article