Search Results (11,948)

The U94 protein of Human Herpesvirus 6 exerts antiproliferative effects through downregulation of the Src proto-oncogene. We aimed to define the shortest U94 fragment that preserves antiproliferative activity and to explore its structural properties. U94 was truncated into shorter fragments, which were subjected to computational analyses and proliferation assays on MDA-MB-468, BT-549 breast cancer cells. Src phosphorylation levels were scrutinized by Western blot analysis. Data obtained demonstrated that the U94 antiproliferative activity resides in its N-terminal region. Specifically, MT153 (aa 1–153) and MT117 (aa 1–117) fragments exhibited antiproliferative activity, whereas MV85 (aa 1–85) fragment did not. Computational analyses identified MG112 (aa 1–112) and MI108 (aa 1–108) as biologically active and suggested that the β-sheet of the structure is critical. The shortest KI95 fragment (aa 14–108), maintaining a stable β-sheet, demonstrated antiproliferative effects and Src downregulation. The antiproliferative activity of U94 and its active fragments relies on stable tridimensional conformation rather than on linear peptide sequence. KI95 represents the shortest active U94 fragment that preserves biological function, with critical residues likely located within the β-sheet region. These findings highlight the importance of structural integrity in U94 functionality and suggest KI95 as a potential therapeutic agent for cancer treatment. Full article

In this study, a procedure to build Bayesian optimal designs using utility functions and exploiting existing data is proposed. The procedure is illustrated through a case study in the field of reliability, by applying a hierarchical Bayesian model and performing Markov Chain Monte Carlo simulations. Two innovative contributions are introduced: (i) the definition of specific utility functions that involve several key issues and (ii) the use of observational data. The use of observational data makes it possible to build the optimal design without additional costs for the company, while the definition of the utility functions accounts for the specific characteristics of the reliability study. Features like model residuals, i.e., discrepancies between observed and predicted response values, and the costs of the electronic component are addressed. Costs are also weighted considering the environmental impact. Satisfactory results are obtained and subsequently validated through an in-depth sensitivity analysis. Full article

This study is an economic evaluation of a composting facility in southeastern Spain (applying Life Cycle Costing), a key region in European horticulture with a significant availability of agricultural biomass. Composting helps reduce dependence on inorganic fertilizers, aligning with European policies that promote the transition toward organic fertilization practices. In addition, compost enhances soil health, increases soil organic carbon, and supports climate change mitigation. Despite its agronomic and environmental benefits, and the large availability of biomass in this region, there is a notable lack of literature addressing the economic costs of composting, which is the first step in assessing the sustainability of a production process. The proposed facility (production: 9000 tonnes of compost per year) utilizes pruning residues and manure to produce high-quality organic amendments. The analysis includes infrastructure, equipment, and every operational input. Likewise, the analysis also provides socio-economic indicators such as employment generation and contribution to the regional economy. Three scenarios were evaluated based on the pruning–shredding location: at the plant, at the farm with mobile equipment, and at the farm with conventional machinery. The most cost-effective option was shredding at the farm using mobile equipment, reducing the unit cost to EUR 65.19 per tonne due to the transport of a smaller volume of prunings and, therefore, lower fuel consumption. The plant also demonstrates high productivity per square metre and generates stable employment in rural areas. Overall, the findings highlight composting as a viable and competitive strategy within circular and low-carbon agricultural systems. Full article

The increasing share of heavy and high-sulfur crude oils in refinery feed slates worldwide highlights the need for models of delayed coking units (DCUs) that are both physically meaningful and computationally efficient. In this study, we develop and calibrate a simplified yet dynamic one-dimensional model of an industrial coke drum intended for integration into digital twin frameworks. The model includes a three-phase representation of the drum contents, a temperature-dependent global kinetic scheme for vacuum residue cracking, and lumped descriptions of heat transfer and phase holdups. Only three physically interpretable parameters—the kinetic scaling factors for distillate and coke formation and an effective wall temperature—were calibrated using routinely measured plant data, namely the overhead vapor and drum head temperatures and the final coke bed height. The calibrated model reproduces the temporal evolution of the top head and overhead temperatures and the final bed height with mean relative errors of a few percent, while capturing the more complex bottom-head temperature dynamics qualitatively. Scenario simulations illustrate how the coking severity (represented here by the effective wall temperature) affects the coke yield, bed growth, and cycle duration. Overall, the results indicate that low-order dynamic models can provide a practical balance between physical fidelity and computational speed, making them suitable as mechanistic cores for digital twins and optimization tools in delayed coking operations. Full article

Coal-based humic acid waste residue is a solid waste generated during the production of humic acid products. The extraction of coal-based humin (NHM) from such residues presents an effective approach for solid waste resource recovery. In this study, a novel calcium-based humin (Ca-NHM) was synthesized via a low-temperature-assisted method. The material was characterized and its cadmium passivation mechanism was investigated using scanning electron microscopy (SEM), zeta potential analysis (Zeta), carbon nuclear magnetic resonance (¹³C-CPMAS-NMR), and X-ray photoelectron spectroscopy (XPS). Soil incubation experiments were conducted to determine the actual cadmium adsorption capacity of coal-based humin in soils and to evaluate the stability of cadmium passivation. Plant cultivation experiments were carried out to verify the effects of coal-based humin on migration and transformation in soil, as well as on cadmium bioefficiency. The results showed that Ca-NHM passivated soil cadmium through multiple mechanisms such as ion exchange, electrostatic adsorption, complexation reactions, and physical adsorption. Compared with NHM, Ca-NHM exhibited a 69.71% increase in passivation efficiency, and a 2.44% reduction in cadmium leaching concentration. In Ca-NHM treatments, the above- and below-ground biomass of pakchoi increased by 18.06%, and 80.95%, respectively, relative to the control group. Furthermore, Ca-NHM enhanced the cadmium resistance of pakchoi, reduced the enrichment coefficient, activity coefficient, and activity-to-stability ratio in the above-ground portion of pakchoi, and maintained a transfer coefficient below 1, thereby alleviating cadmium toxicity. In summary, this study provides a theoretical foundation for understanding the mechanisms by which coal-based humin mitigates cadmium toxicity in pakchoi. Full article

In this study, a pectin polysaccharide named DESP was extracted using a deep eutectic solvent (DES) from sweet potato residue (SPR) and the extract was optimized through response surface methodology (RSM). The DESP, based on choline chloride–urea (ChCl-Ur), was characterized for yield, molecular weight (Mw), and monosaccharide composition. Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), ¹H-nuclearmagnetic resonance (¹H-NMR), and scanning electron microscopy (SEM) were used to analyze the structure. Optimal extraction conditions for DESP were ChCl-Ur in a molar ratio of 1:2, water content of 75 wt.%, extraction time of 125.7 min, extraction temperature of 83.2 °C, and a liquid-to-solid ratio of 37.0 mL·g⁻¹. The optimized extraction yield was 5.6% ± 0.09%, which was 2.4 times higher than that of hot-water-extracted sweet potato pectin (HWSP, 2.32%). The monosaccharide analysis revealed that galacturonic acid (GalA) was the most abundant saccharide, followed by glucose (Glc), galactose (Gal), arabinose (Ara), and rhamnose (Rha). The Mw of DESP was 20.90 kDa, which was lower than that of HWSP and HASP. In addition, DESP exhibited certain anti-inflammatory activity. Full article

Accurate prediction of ultimate tensile strength (UTS) is central to the design and optimization of heat-treated steels but is traditionally achieved through costly and iterative experimental trials. This study presents a transparent, physics-aware machine learning (ML) framework for predicting UTS using an open-access steel database. A curated dataset of 1255 steel samples was constructed by combining 18 chemical composition variables with 7 processing descriptors extracted from free-text heat-treatment records and filtering them using physically justified consistency criteria. To avoid information leakage arising from repeated measurements, model development and evaluation were conducted under a group-aware validation framework based on thermomechanical states. A Random Forest (RF) regression model achieved robust, conservative test-set performance (R² ≈ 0.90, MAE ≈ 40 MPa), with unbiased residuals and realistic generalization across diverse composition–processing conditions. Performance robustness was further examined using repeated group-aware resampling and strength-stratified error analysis, highlighting increased uncertainty in sparsely populated high-strength regimes. Model interpretability was assessed using SHAP-based feature importance and partial dependence analysis, revealing that UTS is primarily governed by the overall alloying level, carbon content, and processing parameters controlling transformation kinetics, particularly bar diameter and tempering temperature. The results demonstrate that reliable predictions and physically meaningful insights can be obtained from publicly available data using a conservative, reproducible machine-learning workflow. Full article

Long-distance natural gas pipelines with internal corrosion defects are susceptible to fatigue failure under operational pressure fluctuations, posing significant risks to infrastructure integrity and safety. To address this, the present study employs a finite element methodology, utilizing Ansys Workbench to model pipelines of various specifications with parametrically defined corrosion defects, and nCode DesignLife to predict fatigue life based on Miner’s linear cumulative damage theory. The S-N curve for X70 steel was directly adopted, while a power-function model was fitted for X80 steel based on standards. A cleaned real-world pressure-time history was used as the load spectrum. Parametric analysis reveals that defect depth is the most influential factor, with a depth coefficient increase from 0.05 to 0.25, reducing fatigue life by up to 67.5%, while the influence of defect width is minimal. An empirical formula for fatigue life prediction was subsequently developed via multiple linear regression, demonstrating good agreement with simulation results and providing a practical tool for the residual life assessment and maintenance planning of in-service pipelines. Full article

Background/Objectives: The genus Tristerix comprises at least ten species, found from southern Chile to Colombia in South America. In Chile, several species of these hemiparasitic plants are known as quitral or quintral. Quitral, mainly T. corymbosus (syn. T. tetrandus), is used in alternative medicine for its anti-inflammatory, digestive, hemostatic, hypocholesterolemic, and wound-healing properties. This study investigates the phytochemical composition and antimicrobial properties of T. corymbosus. Methods: A hydroalcoholic extract of T. corymbosus was prepared from leaves and small branches. The addition of methanol, on the extract, produced precipitation allowing us to isolate a methanol-soluble fraction, a brown powder obtained after filtration, and a tar-like residue remaining in the flask. These fractions were resuspended and tested for antimicrobial activity. Results: All fractions showed activity against Streptococcus pyogenes, but not E. coli. The brown powder exhibits the strongest potency against Gram-positive bacteria, some Gram-negative and C. albicans. HPLC-MS analysis revealed presence of lipidic compounds with surfactant properties. Conclusions: The abundant lipidic molecules present in the analyzed fraction likely account for the antimicrobial effects through affecting membrane structure of microorganisms supporting the traditional wound-healing uses of T. corymbosus in ancestral medicine. Full article

Influenza A virus expresses three envelope proteins, hemagglutinin (HA), neuraminidase (NA), and matrix protein 2 (M2). Of these, HA and NA associate with lipid rafts, whereas M2 remains in the peri-raft region. One reason for the lipid raft association of HA and NA is that they possess longer transmembrane domains (TMDs) (27 and 29 amino acids, respectively) than that of M2 (19 amino acids). Moreover, M2 localizes in the peri-raft region, despite the presence of some lipid raft-targeting features. Therefore, we introduced amino acid insertions into the N-terminal region of M2 to increase the TMD length to 22, 25, and 27 residues, and evaluated these M2-TMD mutants for their association with lipid rafts and impact on virus replication. Confocal microscopy, immunoprecipitation, and cell cytotoxicity assays showed that the cell surface expression and cytotoxic potential of M2-TMD mutants were comparable to those of wildtype M2. Based on the Triton X-100 solubility assay and colocalization analysis between lipid rafts and M2-TMD mutants, we found that the mutant proteins largely remained localized in non-raft domains. Importantly, an increase in M2-TMD length negatively influenced viral replication. These findings suggest that M2-TMD length is optimized for its proper function and does not determine its association with lipid raft domains. Full article

This study provides a comprehensive long-term assessment of dithiocarbamate (DTC) fungicide residues in foods consumed in Brazil, analyzing nearly two decades of official monitoring data from the Pesticide Residue Analysis Program (PARA/ANVISA) from 2001 to 2023. By integrating fragmented annual reports into a single temporal framework, this study offers a novel evaluation of detection frequencies, residue levels, and regulatory compliance over time. Of the 21,274 samples analyzed, 23.90% contained residues of these fungicides. Papaya showed the highest detection frequency (92.59%) in 2005, while apple showed the highest average percentage of detections (51.68%). Lettuce showed the highest residual levels (10.05 mg kg⁻¹) in samples from the 2017–2018 cycle, despite the lack of authorization for the use of these products in this crop. Strawberries and carrots showed concentrations above the maximum residue limit (MRL), with excesses. Residues of unauthorized pesticides were also detected in crops such as guava, pineapple, and sweet potato. Temporal correlations between detections and residues indicated significant variations among the foods evaluated, with potatoes, strawberries, and lettuce showing the highest residual levels. An overall declining trend in detections and residue concentrations was observed throughout the analyzed period, potentially reflecting improvements in regulatory oversight, agricultural practices, and analytical sensitivity over time. From a public health perspective, the persistence of elevated residues and unauthorized uses highlights the need for continuous surveillance, strengthened enforcement, and risk communication strategies to ensure food safety and consumer protection. Full article

Enhancing the flame retardancy of polymeric materials by adding only eco-friendly ammonium polyphosphate (APP) while simultaneously maintaining high-temperature resistance has become a challenge. Talcum has been introduced as a cooperative agent into the silicone rubber/APP system to investigate the effect of talcum on flame retardancy, thermal stability, and high-temperature resistance. The machining process induces the orientation of talcum in the system. The ceramifiable silicone rubber blends containing oriented talcum (e.g., sample SA₆T₄) exhibited superb flame retardancy, including an LOI of 29.4%, a UL-94 rating of V-0, and a peak heat release rate (PHRR) of 250.2 kW·m⁻². More importantly, the blends present excellent thermal stability and high-temperature resistance, characterized by outstanding self-supporting properties and dimensional stability. Based on the structural analysis of the blends and their residues, the made of action for the improved flame retardancy may be attributed to the formation of a compact barrier layer. This layer is formed by oriented talcum platelets combined with phosphoric acid, from the thermal decomposition of APP, promoting crosslinking, thereby achieving a good inhibition barrier to inhibit heat feedback from the condensation zone. The excellent thermal stability and high-temperature resistance of the ceramifiable silicone rubber blends may be ascribed to a cooperative effect between APP and talcum at high temperatures, which facilitates the formation of ceramic structures. The novel ceramifiable silicone rubber composite has potential applications as flame-retardant sealing components for rail transit equipment and encapsulation materials for new energy battery modules. Full article

E-scooters have become a widely adopted form of urban mobility, increasing the need to understand how vibration exposure affects comfort and safety. While most studies have examined the effects of speed, pavement roughness, and overall tire stiffness, none have evaluated how differing stiffness curves between the front and rear wheels influence rider comfort. This article uses real stiffness curves for rigid and inflatable tires at various pressures (30 psi, 60 psi, and rigid) to assess how front–rear stiffness asymmetry affects vibration transmission across speeds (10–20–30 km/h) and two roughness levels (low and high). The analysis, following the standard UNE-ISO 2631-1:2008 and supported by a multiple-regression model (adjusted R² = 93.84%, homoscedastic residuals), shows that speed and roughness dominate the comfort response (98.9%), while tire stiffness offers a secondary (1.1%) but useful tuning parameter, inducing comfort index variations exceeding 14% between front–rear pressure combinations under typical urban conditions (~20 km/h, low roughness). In this case, the most favorable configuration corresponds to inflatable tires with slightly higher front pressure (+2.9–4.35 psi), whereas solid tires consistently yield the poorest comfort. These findings underscore the role of front–rear stiffness management in improving ride quality and provide practical guidance for optimal inflation strategies in urban e-scooters. Full article

This study aimed to develop a robust morphometric-based framework for classifying Apis cerana populations using deep learning and machine learning approaches. Previous studies on Apis cerana population differentiation have primarily relied on manual morphometrics or genetic markers, which are labor-intensive and often lack scalability for large image-based datasets. Forewing landmarks were automatically detected through a deep learning model employing a heatmap regression and Hourglass Network architecture. The extracted coordinates were processed by Principal Component Analysis (PCA) for dimensionality reduction, and shape alignment was further refined through Procrustes ANOVA to minimize non-biological variation. Nine machine learning algorithms were trained and compared under identical preprocessing and validation settings. Among them, the Extra Trees classifier achieved the highest accuracy (99.7%) in distinguishing the three populations—A. cerana cerana from China and A. cerana indica from Thailand, the northern and southern populations. After applying error-based data filtering and retraining, classification accuracy improved further, with almost perfect population separation. The Procrustes ANOVA confirmed that individual variation significantly exceeded residual error (Pillai’s trace = 1.13, p < 0.0001), validating the biological basis of shape differences. Mahalanobis distance and permutation tests (10,000 rounds) revealed significant morphological divergence among populations (p < 0.0001). The integration of geometric alignment and ensemble learning demonstrated a highly reliable strategy for population identification, supporting morphometric and evolutionary studies in Apis cerana. Full article

This paper analyzes the influence of moonpools on the hydrodynamic performance of drillships using the Reynolds-averaged Navier–Stokes (RANS) method. A three-dimensional numerical wave tank is established to realize regular waves and to perform prediction and validation of the KCS ship’s performance in calm water and head seas. After selecting optimal moonpool configurations under calm conditions, seakeeping analyses for a rectangular-moonpool drillship in waves and drag-reduction optimization in calm water and head seas are conducted. The comparative analysis shows that in calm-water navigation, different moonpool shapes lead to different added-resistance effects, and the drillship with a rectangular moonpool shows overall better performance in resistance and running attitude; the added resistance due to the moonpool mainly originates from the additional residual resistance. The sustained energy supply to the clockwise vortex within the moonpool is maintained by the continuous mass exchange between the water flow beneath the ship’s bottom and the water inside the moonpool. Under regular waves, the presence of a moonpool leads to an increase in the total resistance experienced by the drillship. A flange device can effectively reduce the mean amplitude of waves inside the moonpool, and when the flange is installed 10 mm above the still water level with a length of 120 mm, its drag-reduction effect is better. The flange structure can effectively improve the hydrodynamic characteristics of the drillship in waves. The numerical conclusions provide a reference value for the engineering application of drillships with moonpool structures. Full article