Search Results (3,015)

The massive influx and subsequent anaerobic decomposition of pelagic Sargassum on Caribbean coasts release toxic gases, including hydrogen sulfide (H₂S), and pose a real public health hazard, as evidenced by thousands of reported acute exposure cases in Martinique in 2018. To effectively characterize exposure and identify at-risk areas, we utilized the interactive web-based dispersion modeling system C-PORT, representing Sargassum accumulation zones as area sources derived from recent aerial and in situ monitoring data. Inverse modeling, comparing C-PORT output against Madininair observation data from 2024 to 2025, established emission flux rates ranging from 0.45 to 3.58 mg/m² per second for H₂S, depending on Sargassum density. The resulting modeled concentrations exhibit a low average fractional bias (approx. 0.04) when compared to observations. This study demonstrates that C-PORT can be used to estimate spatially resolved concentrations for H₂S, generate health-risk maps for H₂S, evaluate options to mitigate exposure from varying Sargassum intensity levels, and serve as a crucial tool for public health agencies across vulnerable coastal regions. Full article

The influence of passive and active modified-atmosphere packaging (MAP), antioxidants (citric acid and ascorbic acid) and their combinations with a mild thermal process on the shelf life of cut eggplants was evaluated. Eggplant slices were subjected to different treatments (a—MAP: packaged in air with 35 μm polypropylene; b—MAP1: packaged with 3% O₂ + 15% CO₂; c—MAP2: packaged with 5% O₂ + 15% CO₂; d—citric acid 1% + MAP; e—ascorbic acid (A2) 1% + MAP; f—A2 + MAP1; g—TT (50 °C for 1 min) + A2 + MAP; h—TT + A2 + MAP1; and i—control: no treatment) and stored for 12 days at 5 °C. The evolution of sensory characteristics such as color and the browning index, ascorbic acid (AA), total phenols (TP), antioxidant capacity (AC), microorganism count (mesophilic and psychrophilic aerobes, enterobacteria, molds and yeasts) and polyphenol oxidase PPO activity were periodically evaluated. Treatment h was the most effective in prolonging shelf life, maintaining eggplant’s optimal sensory characteristics for up to 10 days, with greater retention of AA and AC and without significantly varying the initial level of TP. Full article

Background/Objectives: Ephedrine and cafedrine/theodrenaline (C/T) are established treatments for spinal anesthesia-induced hypotension during cesarean section. Both aim to stabilize maternal blood pressure and enhance neonatal oxygenation. We compared their effects on maternal hemodynamics and neonatal acid-base status using population kinetic/pharmacodynamic (K/PD) modeling and multiple regression analysis. Methods: The multicenter, prospective, open-label, two-armed, non-interventional HYPOTENS study included 243 parturients undergoing spinal anesthesia for elective cesarean section in Germany. Hypotension was treated with intravenous boluses of either C/T (10–200 mg, 55.6%) or ephedrine (5–40 mg, 44.4%), with dosing determined by the attending anesthesiologist. Maternal mean arterial pressure (MAP), systolic blood pressure (SBP), and heart rate (HR) were recorded for 30 min after treatment. Neonatal acidosis biomarkers included umbilical arterial pH, base excess (BE), and lactate. Results: A population K/PD model captured an initial increase followed by a plateau in MAP, SBP and HR after treatment. Maximum HR (MAX_HR) was 15% higher after ephedrine than after C/T (p < 0.001). BMI and spinal block height significantly influenced maternal hemodynamics (both p < 0.001). Neonatal biomarkers were associated with the duration of maternal MAP below pre-surgery levels, gestational age, spinal block height, antihypotensive treatment, bupivacaine dose, and MAX_HR (all p < 0.05). Conclusions: Ephedrine was associated with higher maternal MAX_HR. Notably, higher maternal MAX_HR was correlated with lower neonatal BE, suggesting that lower maternal peak HR may benefit. These findings may support the use of substances that are largely inert with respect to maternal HR. Full article

This paper is a focused, standards-aligned survey of where autoregressive (AR) large language models (LLMs) tend to break down when deployed inside industrial informatics workflows that must satisfy long-horizon objectives, hard constraints, traceability, and functional-safety obligations (e.g., IEC 61508/ISO 26262/ISO 21448). Rather than claiming new algorithms or experiments, we synthesize and organize prior work into (i) a control-oriented taxonomy of four AR failure modes that recur in practice (compounding error, myopic objectives, data brittleness/hallucinations, and scaling/latency inefficiencies), (ii) a catalog of standards-compatible deployment patterns that mitigate these issues (human-gated LLM-in-the-loop, retrieval + verification pipelines, planner-of-record architectures, and runtime assurance envelopes), and (iii) an operational decision framework (criteria table with observable proxies, a stepwise decision procedure, and worked examples) for deciding when token-centric mitigations are sufficient versus when state/world-model components become warranted. Joint Embedding Predictive Architectures (JEPA) and Hierarchical JEPA (H-JEPA) JEPA are proposed as representative state-predictive architectures, with discussion explicitly bounded by currently available empirical evidence; we explicitly note that the published evidence base is currently concentrated on vision/multimodal benchmarks and that industrial control validation remains limited. To make evidence boundaries transparent, we introduce (a) a survey method (scope, inclusion/exclusion criteria, and data-extraction fields), (b) a comparison matrix across representative prior systems, and (c) an evidence map that links each deployment pattern to peer-reviewed empirical findings and system reports. Full article

Eight H-bonded salts of arsenic acid and nitrogen bases (2,4,6-trimethylpyridine, pyridine-2,6-diamine, pyridin-4-ol, 4-methoxypyridine, 4-methoxyaniline, 1,3,5-triazine-2,4,6-triamine, diethylamine and N¹,N¹,N²,N²-tetraethylethane-1,2-diamine) were studied in the solid state by single crystal X-ray diffraction technique and DFT calculations. In all cases quite short (≤2.65 Å) OHO bonds were found in the self-assembled supramolecular ribbons or 2D networks of dihydrogen arsenates, constituting a repertoire of five different H-bonding patterns (motifs). The electron localization function maps revealed the spots of the nucleophilic sites on oxygen atoms that determine the preferable directions for H-bonding of H₂AsO₄⁻ anions observed in the crystal packing. Analysis of the electrostatic potential maps for isolated species has demonstrated that upon H-bonding between H₂AsO₄⁻ anions and protonated nitrogen bases, NH⁺⋯⁻OAsO(OH)₂, the redistribution of electron density within the anion provides otherwise virtually non-existent electrophilic sites on hydrogen atoms, which balances the Coulomb repulsion and allows for the anion⋯anion pairing within the crystal. The topological analysis of the calculated crystalline electron density after relaxation of the hydrogen atoms’ positions was used to classify the OHO bonds as moderately strong ones (with an interaction energy up to 65 kJ/mol) and revealed a high degree of ionicity of molecular moieties within ion pairs (with an absolute charge up to 0.87 e). For the strongest OHO and NHO bonds, the noticeable covalent character was shown by using the crystal orbital Hamiltonian population analysis. Full article

Forchlorfenuron is a widely used plant cytokinin in Traditional Chinese Medicine and agricultural cultivation to boost resistance, postpone senescence, and increase productivity. However, the improper use of forchlorfenuron results in excessive residues and contamination, raising health and safety concerns. Our research investigated the toxicity of forchlorfenuron on hepatocytes in vitro. Results showed that forchlorfenuron inhibited HepaRG cell viability in a concentration and time-dependent manner. Forchlorfenuron-induced cellular apoptosis and the increased intracellular reactive oxygen species (ROS) indicated the participation of oxidative stress. Molecular docking and network pharmacology data suggested that the hepatotoxicity of forchlorfenuron might involve the MAPK signaling pathway. After 24 h of forchlorfenuron exposure, the P38-MAP kinase, upstream kinases MKK3, and the transcription factor ATF2 were maximally activated. Apoptosis induced by forchlorfenuron was significantly reduced by pretreatment with the P38 inhibitor SB203580. These findings implicated that HepaRG hepatocyte injuries were generated by forchlorfenuron through the induction of cellular apoptosis via the MKK3/P38/ATF2 pathway. Forchlorfenuron application should be closely managed to prevent potential liver damage. Full article

The escalating global rates of traffic accidents in urban areas and the growing demands of smart cities underscore the urgent need for advanced real-time monitoring solutions. This paper presents an EdgeML-based system for vehicle tracking that performs real-time speed and distance analysis and traffic violation detection. This is achieved by deploying a YOLOv8 object detection model on a Raspberry Pi 5 with a Coral USB Edge TPU accelerator. The system integrates computer vision and IoT technologies to enable real-time processing. It utilizes the Message Queuing Telemetry Transport (MQTT) protocol to allow scalable communication between distributed edge devices and a central MongoDB database, facilitating real-time storage and analysis of traffic data. A synthetic dataset generated via the Blender 3D modeling tool validates the system’s accuracy, demonstrating average speed and distance measurement errors of ±2.11 km/h and ±0.58 m, respectively. These findings are further supported by preliminary practical experiments in a real-world environment, where speed estimation errors remained within 0–2 km/h and distance errors stayed below 0.11 m. Key innovations of this work include license plate recognition, speeding and collision detection, and context analysis using Google’s Gemini-2.5-Flash API. A Streamlit dashboard provides real-time visualization of traffic metrics, violations, and aggregated data. A comparative evaluation of YOLOv5n, YOLOv8n, YOLOv11n, and YOLOv12n identifies YOLOv8n as the most suitable model for embedded deployment, achieving 91.07 ± 0.61% mAP@0.5 without quantization, 88.77 ± 3.31% mAP@0.5 with quantization, while maintaining real-time performance of 30–43 frames per second (FPS) on the Edge TPU. The system’s modular architecture, low latency, and robust performance highlight its suitability for smart city applications, enhancing traffic safety and enabling data-driven urban mobility management. Full article

Background: Di(2-ethylhexyl) phthalate (DEHP) is a high-production-volume plasticizer and ubiquitous environ-mental contaminant with established endocrine-disrupting potential. While zebrafish transcriptomic studies have typically used high concentrations and long exposure windows, less is known about genome-wide responses during late embryogenesis/early larval maturation under environmentally relevant exposures. Here we profiled whole-organism transcriptomic responses to a short DEHP exposure during a developmentally sensitive transition (96–120) hours post-fertilization, hpf) and interpreted responses using differential expression, enrichment analyses, and endocrine-focused protein–protein interaction (PPI) network modeling. Methods: Wild-type AB zebrafish lar-vae (96 hpf) were exposed to DEHP at [10⁻⁹ M] or solvent control for 24 h. Larvae were pooled per replicate (25 lar-vae/pool) and processed for poly(A)-selected RNA-seq. Reads were quality-controlled, aligned to the Danio rerio reference genome, and quantified at gene- level. Differential expression was performed using DESeq2. Functional enrichment used KEGG over-representation analysis (ORA) and gene set enrichment analysis (GSEA). Zebrafish genes were mapped to human orthologs for GO/KEGG and STRING-based endocrine subnetworks, which were visualized and interrogated using STRINGdb and visNetwork. Results: Low-dose, short-term exposure does not produce large gene-level effects but induces coordinated, pathway-level transcriptional remodeling. KEGG ORA showed significant enrichment of MAPK signaling and regulation of actin cytoskeleton with additional enrichment of axon guidance and neuroactive ligand–receptor interaction. GSEA detected coordinated downregulation of KEGG neurodegeneration collections with negative normalized enrichment scores reflecting shared gene sets re-lated to mitochondrial function, proteostasis, cytoskeletal organization, and stress-response pathways. Endo-crine-focused STRING subnetworks indicated consistent downregulation of CYP19A1 within estrogen metabo-lism/biosynthesis modules and downregulation of upstream androgen biosynthetic enzymes HSD3B2 and CYP17A1, alongside upregulation of HSD17B3 and proteostasis-associated factors including DNAJA1. Endocrine network to-pology highlighted regulatory and cofactor nodes affecting receptor-linked transcription, consistent with indirect endocrine modulation rather than large receptor-transcript changes. Conclusions: In summary, this study demon-strates that exposure to low-dose DEHP during a critical period of zebrafish embryonic development is associated with modest but coordinated transcriptomic changes across multiple biological pathways. Pathway enrichment and network-based analyses highlight estrogen- and androgen-associated processes, along with broader signaling, met-abolic, and structural pathways, as transcriptionally responsive during this window. Importantly, these findings reflect molecular-level associations rather than direct evidence of functional or physiological endocrine disruption. Instead, they identify candidate pathways and regulatory networks that may be sensitive to low-level environmen-tal exposure and warrant further investigation. Collectively, this work underscores the value of systems-level tran-scriptomic approaches for detecting subtle, pathway-wide responses to environmentally relevant exposures during development. Full article

Soil pH is a critical soil property governing nutrient availability and ecosystem functioning. Digital mapping of its spatial distribution is essential for precision agriculture and sustainable land management. This study performs a comparative analysis of six tree-based models coupled with residual kriging (RK) for 30 m resolution mapping of soil pH in Shayang County, China. Specifically, random forest (RF), extremely randomized trees (ERT), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and categorical boosting (CatBoost) were used. Based on 1343 soil samples and 32 environmental variables, experimental results demonstrate that the integration of RK enhanced the prediction accuracy of all standalone models by taking the spatial dependence of residuals into account. Among the models, CatBoost-RK achieved the best performance with an R² of 0.7265, RMSE of 0.5072, and RPD of 1.9122, closely followed by ERT-RK and RF-RK. The analysis of variable importance identified soil type (ST) and mean annual precipitation (MAP) as the most critical factors affecting soil pH distribution. The generated 30 m resolution soil pH map reveals distinct patterns across different land use types, with croplands showing lower soil pH and grasslands exhibiting higher pH with greater variability. These findings confirm the effectiveness of the hybrid ML-RK framework and provide valuable insights for selecting optimal modeling strategies in digital soil mapping. Full article

Photoionization detector (PID) sensors are widely used for ambient Volatile organic compound (VOC) monitoring because they are inexpensive, flexible, and fast. However, PID outputs are strongly influenced by environmental conditions (especially temperature and relative humidity) and exhibit substantial inter-sensor variability, limiting their quantitative reliability. Here we present a rapid machine-learning calibration workflow that maps PID signals and meteorological covariates to a photochemically relevant reference metric, PTR-derived VOC OH reactivity (R_OH,PTR, s⁻¹), calculated from online PTR-ToF-MS VOC measurements weighted by OH reaction rate constants. Four MiniPID sensors were co-located with a PTR-ToF-MS and a thermohygrometer, and data were harmonized to 10-s resolution. Multiple regression models were evaluated, with ensemble methods (RF and XGBoost) providing the best overall performance. To ensure realistic generalization under temporal autocorrelation, validation used a time-aware split: models were trained on a contiguous 24-h co-location period and evaluated on subsequent days (out-of-time). In this out-of-time evaluation, XGBoost achieved strong agreement with R_OH,PTR across sensors (Pearson’s r = 0.85, R² = 0.64, RMSE = 1.74 s⁻¹), while substantially improving inter-sensor consistency. This short-duration calibration approach supports practical co-location-based harmonization of PID networks for high-temporal-resolution VOC reactivity monitoring in urban and industrial environments. Full article

Soil heterogeneity and acidity are major constraints to Coffea arabica production in the Amazonian soils of Peru. This study developed a spatial predictive framework that integrates a weighted Soil Quality Index (SQIw) and geostatistical modelling (Regression–Kriging and Ordinary Kriging) to estimate lime requirements (LRs) and delineate management zones. A total of 69 coffee-cultivated soil samples were analysed, and spectral information (NDVI) was incorporated to estimate relative yield (RR). Multivariate analysis defined a Minimum Data Set (MDS) composed of exchangeable Na, available P, pH and silt percentage; the highest weights were assigned to P (Wi = 0.292) and pH (Wi = 0.276). SQIw exhibited wide variability (0.01–0.87; CV = 51.8%) and was grouped into five classes, with low (43.5%)- and very low (21.7%)-quality classes predominating. SQIw showed a strong relationship with RR (r = 0.64). Geostatistical models performed differently between localities: in Nuevo Huancabamba, Regression–Kriging improved prediction accuracy (SQIw: R² = 0.58; LR: R² = 0.396), whereas in San José de Sisa, Ordinary Kriging provided better fits only for LRs (R² = 0.32). Nuevo Huancabamba is dominated by moderate-to-high-quality soils (87.29%; SQIw > 0.6) and low lime requirements (74.94%; <0.84 t ha⁻¹), in contrast with San José de Sisa, where low-quality soils prevail (89.45%; SQIw < 0.4) alongside high LRs (75.26%; 2.54–7.13 t ha⁻¹). The resulting maps enable targeted interventions—precision liming and focused P fertilisation—to correct acidity and phosphorus deficiency, thereby improving input-use efficiency and enhancing the sustainability of Amazonian coffee systems. Full article

Objectives: The epidermal growth factor receptor (EGFR) is a clinically relevant membrane receptor that is frequently overexpressed or dysregulated in multiple types of cancer, making it an important target for antibody-based strategies. Nanobodies, derived from camelid heavy-chain antibodies, possess favorable properties such as small size, high stability, and strong antigen-binding capacity. This study aimed to generate EGFR-specific nanobodies and to systematically characterize their binding properties and initial functional activity. Methodology: Bactrian camels were immunized with a whole-cell antigen prepared from 293F cells transiently transfected to express full-length human EGFR. A high-diversity phage display nanobody library was constructed from peripheral blood lymphocytes. After two rounds of biopanning against EGFR, positive clones were screened and selected. The identified nanobodies were recombinantly expressed in Escherichia coli and purified. Binding specificity, epitope relationships, and kinetic parameters were evaluated using high-performance liquid chromatography (HPLC), bio-layer interferometry (Octet), and flow cytometry. The effect of selected nanobodies on EGF-induced cell proliferation was evaluated using a CCK-8 assay. Results: Two EGFR-specific nanobodies, Nb2H4 and Nb2B6, were successfully isolated. Both nanobodies exhibited specific binding to EGFR and recognized distinct, non-competing epitopes. Kinetic analyses revealed favorable binding affinities, and flow cytometry confirmed their ability to recognize EGFR in its native cellular context. In addition, Nb2H4 significantly suppressed EGF-induced proliferation in an EGFR-overexpression cell model, indicating preliminary functional activity. Conclusions: This study reports on the successful generation and in vitro characterization of EGFR-targeting nanobodies based on the extracellular domain of EGFR. The identified nanobodies provide useful molecular tools for epitope mapping, structural studies, and the further exploration of EGFR-directed antibody engineering strategies. Full article

Background and Objectives: Social Determinants of Health (SDoH) are factors that can contribute to health inequities. Improving the conditions in which people are born, grow, and live requires collaboration between professionals from different health sectors. Given their health and well-being-focused care, nurses are crucial to promoting health equity in the care they provide. Thus, their knowledge, attitudes, and actions—i.e., practice—(KAP) regarding SDoH could serve as a helpful starting point for promoting care that also focuses on non-medical factors. This study aims to map the SDoH assessed in the literature in relation to nurses’ and nursing students’ KAPs, using the Dahlgren–Whitehead Rainbow Model as a logical framework. Methods: Following PRISMA guidelines, a systematic literature review was conducted using PubMed, Scopus, Web of Science, CINAHL, and PsycINFO. Records published until June 2024 were selected from primary studies involving nurses and nursing students, with no time limits. The assessed determinants were adapted and categorised according to the Rainbow Model Levels. Results: 22 results were eligible. The SDoH (in general), poverty, social justice, social gradient, social inclusion and exclusion, discrimination, diversity, equity and inequality, food insecurity and access to nutritious food, employment status, geographical isolation, healthcare services, housing difficulties, transportation, social support, individual lifestyle factors, and health literacy were assessed on KAPs. Conversely, health equity has been assessed just for knowledge and attitudes. Considering the latter level of the Rainbow Model and the relative categorisation of the results, age, sex, and constitutional factors were not examined in the studies included in this review. Conclusions: This review maps the most and least frequently assessed SDoH in relation to KAP. As nurses are essential to providing care that considers SDoH, improving health outcomes, and addressing health inequities, and advocating for community health, it would be valuable to enhance nursing education from baccalaureate through postgraduate courses. Moreover, a strong relationship with different healthcare professionals is needed. Full article

Background/Objectives: While CRISPR/Cas9 technology offers a revolutionary approach for correcting genetic ocular blindness, efficient and safe delivery remains the primary bottleneck. Traditional viral vectors, despite their efficacy, face challenges regarding cargo size limitations and potential genomic integration risks. Non-viral vectors offer distinct comparative advantages, including large cargo capacity for diverse CRISPR tools and transient expression to minimize off-target effects, but must overcome the eye’s formidable static and dynamic barriers, specifically the corneal epithelium, vitreous humor, and the inner limiting membrane. In this review, we present an anatomically guided framework for non-viral CRISPR/Cas9 delivery, mapping engineering strategies to specific ocular tissue targets. We first delineate the mechanisms of key physiological barriers, including the corneal stroma, aqueous humor circulation, and the vitreous–retina interface. Subsequently, we critically evaluate the latest advancements in non-viral platforms, such as pH-responsive lipid nanoparticles and engineered virus-like particles. The core focus of this review is on site-specific breakthrough strategies: from utilizing mucoadhesive polymers to counteract tear clearance in the cornea to exploiting specialized administration routes, such as suprachoroidal space and subretinal injection, to bypass retinal barriers, and deep-penetrating intravitreal carriers for targeting the photoreceptor-RPE complex. By integrating material science with precise administration routes, this review highlights feasible translational pathways for next-generation, carrier-free, or biomimetic ocular gene editing therapies. Full article

Background/Objectives: Antibody-dependent cellular cytotoxicity relies on the interaction between the Fc region of immunoglobulin G1 (IgG1) and the CD16a receptor. While removal of core fucosylation on Fc and introduction of the DFTE mutation set (S239D, H268F, S324T, I332E) are known to enhance CD16a binding, the detailed contributions of these engineered sites in solution remain incompletely defined. Methods: Here, we employed 1 µs molecular dynamics simulations to map, at atomic resolution, the interaction networks stabilizing pre-formed Fc-CD16a complexes, including afucosylated Fc-wild-type, DFTE-engineered, Fc-fucosylated, and asymmetrically engineered Fc variants. Results: Our results show that only S239D, present on both Fc chains, and H268F on chain A consistently contribute to stabilizing the CD16a interface, while I332E does not form persistent interactions. Glycan–protein contacts are primarily intrachain, with transient interchain glycan–glycan interactions not contributing significantly to complex stability. Fucosylation on Fc significantly reduces binding stability by disrupting peripheral interactions and critical glycan-mediated contacts. Notably, the asymmetric Fc variant, in which the two heavy chains carry distinct sets of substitutions, retains high-affinity binding despite lacking S239D and carrying core fucose, through a novel hydrophobic cluster and reinforced peripheral electrostatic interactions. Conclusions: Altogether, these findings provide a quantitative framework for how targeted mutations and fucose modifications remodel Fc-CD16a interactions, offering insights for the rational design of next-generation therapeutic antibodies. Full article