Search Results (66,024)

The biocompatibility of materials used in biomedical applications, especially those in direct contact with human tissue, is crucial to ensuring their safety. Ensuring material biocompatibility requires a wide range of in vitro and in vivo tests, with in vitro tests using cell culture systems being the first step in biomaterial characterization. Among the commonly used methods for assessing cell viability are colorimetric tests, such as MTT and LDH assays. While these assays provide valuable information about cell viability, their results can be affected by biochemical substances. This study focused on evaluating the reliability of MTT and LDH assays in nicotinamide-supplemented medium, which optimized culture conditions for the differentiation of ARPE-19 cells. The results were compared with a live/dead viability test based on fluorescence staining, providing insight into the effectiveness of different cell viability assessment methods in this specific context. This research is important in developing biomaterials for retinal prostheses, where maintaining high biocompatibility is essential for successful implantation. Full article

Rainfall-induced landslide deformation is governed by both intrinsic geological conditions and external dynamic triggers. However, many existing predictive models rely primarily on rainfall inputs, which limits their interpretability and robustness. To address these shortcomings, this study introduces a group-based data augmentation method informed by displacement curve morphology and proposes a multi-slope predictive framework that integrates static geological attributes with dynamic triggering factors. Using monitoring data from 274 sites across China, the framework was implemented with a Temporal Fusion Transformer (TFT) and benchmarked against baseline models, including SVR, XGBoost, and LSTM models. The results demonstrate that group-based augmentation enhances the stability and accuracy of predictions, while the integrated dynamic–static TFT framework delivers superior accuracy and improved interpretability. Statistical significance testing further confirms consistent performance improvements across all groups. Collectively, these findings highlight the framework’s effectiveness for short-term landslide forecasting and underscore its potential to advance early warning systems. Full article

Early and accurate detection of lemon disease is necessary for effective citrus crop management. Traditional approaches often lack refined diagnosis, necessitating more powerful solutions. The article introduces adaptive PSO-LemonNetX, a novel framework integrating a novel deep learning model, adaptive Particle Swarm Optimization (PSO)-based feature selection, and explainable AI (XAI) using LIME. The approach improves the accuracy of classification while also enhancing the explainability of the model. Our end-to-end model obtained 97.01% testing and 98.55% validation accuracy. Performance was enhanced further with adaptive PSO and conventional classifiers—100% validation accuracy using Naive Bayes and 98.8% testing accuracy using Naive Bayes and an SVM. The suggested PSO-based feature selection performed better than ReliefF, Kruskal–Wallis, and Chi-squared approaches. Due to its lightweight design and good performance, this approach can be adapted for edge devices in IoT-enabled smart farms, contributing to sustainable and automated disease detection systems. These results show the potential of integrating deep learning, PSO, grid search, and XAI into smart agriculture workflows for enhancing agricultural disease detection and decision-making. Full article

Cucumber green mottle mosaic virus (CGMMV) represents a serious threat in the production of watermelon. Small RNAs facilitate a mechanism known as RNA interference (RNAi), which regulates gene expression. RNAi technology employs foreign double-stranded RNAs (dsRNAs) to target and reduce the expression levels of specific genes in plants by interfering with their mRNAs. In this study, watermelon plants were treated with dsRNAs of CGMMV MET, IR, and HEL fragments that had been generated in E. coli HT115. We investigated variations in several factors, including viral accumulation, virus-derived small interfering RNAs (vsiRNAs), and symptom severity. MET-dsRNA, IR-dsRNA and HEL-dsRNA dramatically decreased the symptoms of CGMMV in plants in the growth chamber test. Plants treated with viral-derived dsRNA showed a considerable decrease in both virus titers and vsiRNA levels. We also explored the mobility of spray-on dsRNA-derived long dsRNA and discovered that it could be identified in both inoculated leaves and the systemic leaves. IR-dsRNA outperformed MET-dsRNA and HEL-dsRNA in dsRNA therapy. Illumina sequencing of small RNAs from watermelon plants treated with IR-dsRNA and those that were not treated showed that the decreased accumulation of vsiRNAs was consistent with interference with CGMMV infection in systemic leaves. dsRNA-treated plants showed a higher level of 24-nt viral siRNA and lower level of 22-nt viral siRNA accumulation, while 22-nt viral siRNA predominated in untreated plants, indicating that dsRNA treatment improved DCL3 activity. In conclusion, our research provides deeper insights into the mechanism of antiviral RNA interference and confirms the effectiveness of applying dsRNA locally to enhance plant antiviral activity. Full article

Head and neck cancer (HNC) is highly heterogeneous and difficult to treat, underscoring the need for rapid, patient-specific models. Standard three-dimensional (3D) cultures often lose stromal partners that influence therapy response. We developed a patient-derived system maintaining tumor cells, cancer-associated fibroblasts (CAFs), and cells undergoing partial epithelial–mesenchymal transition (pEMT) for drug sensitivity testing. Biopsies from four HNC patients were enzymatically dissociated. CAFs were directly cultured, and their conditioned medium (CAF-CM) was collected. Cryopreserved primary tumor cell suspensions were later revived, screened in five different growth media under 2D conditions, and the most heterogeneous cultures were re-embedded in 3D hydrogels with varied gel mixtures, media, and seeding geometries. Tumoroid morphology was quantified using a perimeter-based complexity index. Viability after treatment with cisplatin or Notch modulators (RIN-1, recombination signal-binding protein for immunoglobulin κ J region (RBPJ) inhibitor; FLI-06, inhibitor) was assessed by live imaging and the water-soluble tetrazolium-8 (WST-8) assay. Endothelial Cell Growth Medium 2 (ECM-2) medium alone produced compact CAF-free spheroids, whereas ECM-2 supplemented with CAF-CM generated invasive aggregates that deposited endogenous matrix. Matrigel with this medium and single-point seeding gave the highest complexity scores. Two of the three patient tumoroids were cisplatin-sensitive, and all showed significant growth inhibition with the FLI-06 Notch inhibitor, while the RBPJ inhibitor RIN-1 induced minimal change. The optimized scaffold retains tumor–stroma crosstalk and provides patient-specific drug response data within days after operation, supporting personalized treatment selection in HNC. Full article

Hydrological simulation of large, transboundary water systems like the Laurentian Great Lakes remains challenging. Although deep learning has advanced hydrologic forecasting, prior efforts are fragmented, lacking a unified basin-wide model for daily streamflow. We address this gap by developing a single Entity-Aware Long Short-Term Memory (EA-LSTM) model, an architecture that distinctly processes static catchment attributes and dynamic meteorological forcings, trained without basin-specific calibration. We compile a cross-border dataset integrating daily meteorological forcings, static catchment attributes, and observed streamflow for 975 sub-basins across the United States and Canada (1980–2023). With a temporal training/testing split, the unified EA-LSTM attains a median Nash–Sutcliffe Efficiency (NSE) of 0.685 and a median Kling–Gupta Efficiency (KGE) of 0.678 in validation, substantially exceeding a standard LSTM (median NSE 0.567, KGE 0.555) and the operational NOAA National Water Model (median NSE 0.209, KGE 0.440). Although skill is reduced in the smallest basins (median NSE 0.554) and during high-flow events (median PBIAS −29.6%), the performance is robust across diverse hydroclimatic settings. These results demonstrate that a single, calibration-free deep learning model can provide accurate, scalable streamflow prediction across an international basin, offering a practical path toward unified forecasting for the Great Lakes and a transferable framework for other large, data-sparse watersheds. Full article

The spatiotemporal regulatory mechanism underlying silicon (Si)-mediated cadmium (Cd) detoxification in rice (Oryza sativa L.) was investigated using non-invasive micro-test technology (NMT), combined with physiological and biochemical analyses. The results revealed the following: (1) Si significantly inhibited Cd²⁺ influx into rice roots, with the most pronounced reductions in ion flux observed under moderate Cd stress (Cd50, 50 μmol·L⁻¹), reaching 35.57% at 7 days and 42.30% at 14 days. Cd accumulation in roots decreased by 34.03%, more substantially than the 28.27% reduction observed in leaves. (2) Si application enhanced photosynthetic performance, as evidenced by a 14.21% increase in net photosynthetic rate (Pn), a 32.14% increase in stomatal conductance (Gs), and a marked restoration of Rubisco activity. (3) Si mitigated oxidative damage, with malondialdehyde (MDA) and hydrogen peroxide (H₂O₂) levels reduced by 11.29–21.88%, through the upregulation of antioxidant enzyme activities (SOD, APX, CAT increased by 15.34–38.33%) and glutathione metabolism (GST activity and GSH content increased by 60.78% and 51.35%, respectively). (4) The mitigation effects of Si were found to be spatiotemporally specific, with stronger responses under Cd50 than Cd100 (100 μmol·L⁻¹), at 7 days (d) compared to 14 d, and in roots relative to leaves. Our study reveals a coordinated mechanism by which Si modulates Cd uptake, enhances photosynthetic capacity, and strengthens antioxidant defenses to alleviate Cd toxicity in rice. These findings provide a scientific basis for the application of Si in mitigating heavy metal stress in agricultural systems. Full article

In low-risk and open environments, such as farms and mining sites, efficient cargo transportation is essential. Despite the suitability of autonomous driving for these environments, its high deployment and maintenance costs limit large-scale adoption. To address this issue, a modular unmanned ground vehicle (UGV) system is proposed, which is adapted from existing platforms and supports both autonomous and manual control modes. The autonomous mode uses environmental perception and trajectory planning algorithms for efficient transport in structured scenarios, while the manual mode allows human oversight and flexible task management. To mitigate the control latency and execution delays caused by platform modifications, an enhanced transformer-based general dynamics model is introduced. Specifically, the model is trained on a custom-built dataset and optimized within a bicycle kinematic framework to improve control accuracy and system stability. In road tests allowing a positional error of up to 0.5 m, the transformer-based trajectory estimation method achieved 94.8% accuracy, significantly outperforming non-transformer baselines (54.6%). Notably, the test vehicle successfully passed all functional validations in autonomous driving trials, demonstrating the system’s reliability and robustness. The above results demonstrate the system’s stability and cost-effectiveness, providing a potential solution for scalable deployment of autonomous transport in low-risk environments. Full article

To address the issue of insufficient contrast in conventional X-ray absorption imaging for biological soft tissues and weakly absorbing materials, this paper proposes a beam tracking X-ray phase-contrast imaging system using a conventional X-ray source. A periodic pinhole array mask is placed between the X-ray source and the sample to spatially modulate the X-ray beam, dividing it into multiple independent sub-beams. Each sub-beam is deflected due to the modulation effect of the sample, resulting in slight positional shifts in the intensity patterns formed on the detector. The experiments employ an X-ray source with a 400 μm focal spot and use a two-dimensional step-scanning approach to acquire image sequences of various samples. The experimental results show that this method can extract the edge profile and structural changes in the samples to some extent, and it demonstrates good contrast and detail recovery under weak absorption conditions. These results suggest that this method has certain application potential in material inspection, non-destructive testing, and related fields. Full article

The growing use of experimental radiopharmaceuticals for targeted radionuclide therapy (TRT) highlights the need for robust “in house” radiolabeling protocols. Among these, PSMA-ALB-56 is a PSMA ligand incorporating an albumin-binding moiety to enhance pharmacokinetics, which showed promise for prostate cancer treatment. This study investigated manual radiolabeling conditions of this vector molecule with lutetium-177 and developed a corresponding automated synthesis protocol. Manual experiments on low activities explored buffer systems and antioxidants, identifying sodium acetate buffer and L-methionine as optimal, achieving radiochemical purities above 97% with excellent stability over 48 h. However, when these conditions were transposed directly to an automated process on a GAIA^® module with activities > 2 GBq, radiochemical purity dropped below 70% due to significant radiolysis. This result emphasized that conditions optimized at low activities are not directly transferable to high-activity automated production, and highlighted the crucial role of antioxidant concentration. An optimized automated method was subsequently developed, integrating a solid-phase extraction purification step, higher antioxidant levels during radiolabeling and formulation, and a larger final product volume. These changes led to radiochemical purities above 98.9% and excellent product stability over 120 h for 3 test batches. The presence of high concentrations of methionine and ascorbic acid was essential to protect against radiolysis. This work underscores the importance of adjusting radiolabeling strategies during process scale-up and confirmed that antioxidant concentration is essential for successful ¹⁷⁷Lu radiolabeling. The optimized automated method developed here for [¹⁷⁷Lu]Lu-PSMA-ALB-56 may also be adapted to other radiopharmaceuticals in development for TRT. Full article

This study focuses on the preparation of poly(HCQM-co-VP) copolymeric nanoparticles (NPs) to enhance the aqueous solubility and bioavailability of the hydrophobic and antitumor molecules HCQ (hydroxychloroquine) and α-TOS (α-tocopheryl succinate). HCQ is covalently incorporated into the polymer backbone, while α-TOS is encapsulated within the nanoparticles by non-covalent interactions. Poly(HCQM-co-VP) was synthesized from a vinyl derivative of HCQ (HCQM) and N-vinylpyrrolidone (VP), with a molar composition of 17% HCQM and 83% VP, providing the optimal hydrophobic/hydrophilic balance for forming, via nanoprecipitation, empty nanoparticles (NPs) with a diameter of 123.6 nm and a zeta potential of −5.8 mV. These nanoparticles effectively encapsulated α-TOS within their hydrophobic core, achieving an encapsulation efficiency (%EE) of 78%. These α-TOS-loaded NPs resulted in smaller diameters and more negative zeta potentials (71 nm, −19.2 mV) compared to the non-loaded NPs. The cytotoxicity of these NPs was evaluated using the AlamarBlue assay on MCF-7 breast cancer cells. The empty NPs showed no toxic effects within the tested concentration range, after 72 h of treatment. In contrast, the α-TOS-loaded NPs, exhibited a pronounced cytotoxic effect on MCF-7 cells with an IC₅₀ value of 100.2 μg·mL⁻¹, thereby demonstrating their potential as controlled drug delivery systems for cancer treatment. These findings contribute to the development of a new HCQ-based polymeric nanocarrier for α-TOS or other hydrophobic drugs for the treatment of cancer and other diseases treatable with these drugs. Full article

Microphysiological systems (MPSs) have emerged as alternatives to animal testing in drug development, following the FDA Modernization Act 2.0. Double-layer channel-type MPS chips with porous membranes are widely used for modeling various organs, including the intestines, blood–brain barrier, renal tubules, and lungs. However, these chips faced challenges owing to optical interference caused by light scattering from the porous membrane, which hinders cell observation. Trans-epithelial electrical resistance (TEER) measurement offers a non-invasive method for assessing barrier integrity in these chips. However, existing electrode-integrated MPS chips for TEER measurement have non-uniform current densities, leading to compromised measurement accuracy. Additionally, chips made from polydimethylsiloxane have been associated with drug absorption issues. This study developed an electrode-integrated MPS chip for TEER measurement with a uniform current distribution and minimal drug absorption. Through a finite element method simulation, electrode patterns were optimized and incorporated into a polyethylene terephthalate (PET)-based chip. The device was fabricated by laminating PET films, porous membranes, and patterned gold electrodes. The chip’s performance was evaluated using a perfused Caco-2 intestinal model. TEER levels increased and peaked on day 5 when cells formed a monolayer, and then they decreased with the development of villi-like structures. Concurrently, capacitance increased, indicating microvilli formation. Exposure to staurosporine resulted in a dose-dependent reduction in TEER, which was validated by immunostaining, indicating a disruption of the tight junction. This study presents a TEER measurement MPS platform with a uniform current density and reduced drug absorption, thereby enhancing TEER measurement reliability. This system effectively monitors barrier integrity and drug responses, demonstrating its potential for non-animal drug-testing applications. Full article

Humor translation remains a significant challenge due to its reliance on wordplay, cultural context, and nuance. This study compares a Neural Machine Translation (NMT) system (hereafter referred to as MT) with a Large Language Model (GPT-based translation using three different prompts) for translating jokes from English to Thai. Results show that GPT-based models significantly outperform MT in humor retention, with the explanation-enhanced prompt (GPT-Ex) achieving the highest joke preservation rate (62.94%) compared to 50.12% in MT. Additionally, humor loss was more frequent in MT, while GPT-based models, particularly GPT-Ex, better retained jokes. A McNemar test confirmed significant differences in annotation distributions across models. Beyond evaluation, we propose using GPT-based models with optimized prompt engineering to enhance humor translation. Our refined prompts improved joke retention by guiding the model’s understanding of humor and cultural nuances. Full article

A novel bio-gelatin fiber-reinforced composite (BFRC) was first developed by incorporating industrial bone glue/gelatin as the matrix, magnesium oxide (MgO) as an additive, and natural or synthetic fibers as reinforcement. Systematic tests evaluated mechanical, impact, and thermal performance, alongside microstructural mechanisms. Results showed that polyethylene (PE) fiber-reinforced composites achieved a tensile strength of 3.40 MPa and tensile strain of 10.77%, with notable improvements in compressive and flexural strength. PE-based composites also showed excellent impact energy absorption, while bamboo fiber-reinforced composites exhibited higher thermal conductivity. Microstructural analysis revealed that coordination between Mg²⁺ ions and amino acids in gelatin formed a stable cross-linked network, densifying the matrix and improving structural integrity. A multi-criteria evaluation using the TOPSIS model identified the BC-PE formulation as the most balanced system, combining strength, toughness, and thermal regulation. These findings demonstrate that ionic coordination and fiber reinforcement can overcome inherent weaknesses of gelatin matrices, offering a sustainable pathway for building insulation and cushioning packaging applications. Full article

Posttraumatic Stress Disorder (PTSD) is characterized by disruptions in central nervous system functioning and existential crises, yet the mechanistic links between neurobiological processes and dimensions of life meaning and identity remain underexplored. The aim of this study was to examine the relationships between stress biomarkers (serotonin, cortisol, noradrenaline, and interleukin-12 [IL-12]) and existential attitudes (measured using the Life Attitude Profile (Revised) [LAP-R]) in mining rescuers, considering PTSD duration and participant age. This cross-sectional study included 92 men aged 18–50 years, divided into three groups: no PTSD (n = 28), PTSD ≤ 5 years (n = 33), and PTSD > 5 years (n = 31). Serum levels of four biomarkers and LAP-R scores across eight domains were evaluated. Statistical analyses employed nonparametric tests, including the Kruskal–Wallis test for overall group differences (with Wilcoxon r effect sizes for pairwise comparisons, Mann–Whitney U tests for post hoc pairwise comparisons, and Spearman’s rank correlations for biomarker–LAP-R associations. Age effects were assessed in two strata: 18–35 years and 36–50 years. Kruskal–Wallis tests revealed significant group differences (p < 0.001) for all biomarkers and most LAP-R domains, with very large effect sizes (r > 0.7) in pairwise comparisons for serotonin (control median: 225.2 ng/mL vs. PTSD ≤ 5y: 109.9 ng/mL, r = 0.86; vs. PTSD > 5y: 148.0 ng/mL, r = 0.86), IL-12 (control: ~8.0 pg/mL vs. PTSD ≤ 5y: 62.4 pg/mL, r = 0.86; vs. PTSD > 5y: ~21.0 pg/mL, r = 0.69), and LAP-R scales such as Life Purpose (control: 54.0 vs. PTSD ≤ 5y: 39.0, r = 0.78; vs. PTSD > 5y: 20.0, r = 0.86) and Coherence (control: 53.0 vs. PTSD ≤ 5y: 34.0, r = 0.85; vs. PTSD > 5y: 23.0, r = 0.86). The PTSD ≤ 5y group exhibited decreased serotonin, cortisol (median: 9.8 µg/dL), and noradrenaline (271.7 pg/mL) with elevated IL-12 (all p < 0.001 vs. control), alongside reduced LAP-R scores. The PTSD > 5y group showed elevated cortisol (median: ~50.0 µg/dL, p < 0.001 vs. control, r = 0.86) and normalized IL-12 but persistent LAP-R deficits. Older participants (36–50 years) in the PTSD ≤ 5y group displayed improved existential attitudes (e.g., Life Purpose: 47.0 vs. 27.5 in 18–35 years, p < 0.001), whereas in PTSD > 5y, age exacerbated biological stress (cortisol: 57.6 µg/dL vs. 36.1 µg/dL, p = 0.003). Spearman correlations revealed stage-specific patterns, such as negative associations between cortisol and Death Acceptance in PTSD > 5y (ρ = −0.49, p = 0.005). PTSD alters biomarker levels and their associations with existential dimensions, with duration and age modulating patient profiles. These findings underscore the necessity for integrated therapies addressing both biological and existential facets of PTSD. Full article