Search Results (353)

Background/Objective: Sepsis-associated acute kidney injury (SA-AKI) is a substantial contributor to mortality in critically ill patients. This study aimed to investigate the impact of gum acacia (GA) and dexamethasone (DEX) combination on lipopolysaccharide (LPS)-induced SA-AKI in rats. Methods: Thirty-six male Sprague Dawley rats were separated into six groups, including the control, GA group, LPS-induced AKI group, DEX + LPS group, GA + LPS group, and GA + DEX + LPS group. AKI was induced in rats using LPS (10 mg/kg, i.p.). GA was administered orally (7.5 g/kg) for 14 days before LPS injection, and DEX was injected (1mg/kg, i.p.) 2 h after LPS injection. Results: LPS injection significantly (p < 0.05, vs. control group) impaired renal function, as evidenced through increased levels of kidney function biomarkers, decreased creatinine clearance, and histopathological alterations in the kidneys. LPS also significantly (p < 0.05, vs. control group) elevated levels of oxidative stress markers, while it reduced levels of antioxidant enzymes. Furthermore, LPS triggered an inflammatory response, manifested by significant (p < 0.05, vs. control group) upregulation of Toll-like receptor 4, myeloid differentiation primary response 88, interleukin-1β, tumor necrosis factor-α, and nuclear factor-κB, along with increased expression of high-mobility group box 1. Administration of GA significantly ameliorated LPS-induced renal impairment by enhancing antioxidant defenses and suppressing inflammatory pathways (p < 0.05, vs. LPS group). Furthermore, GA-DEX-treated rats showed improved kidney function, reduced oxidative stress, and attenuated inflammatory markers (p < 0.05, vs. LPS group). Conclusions: The GA-DEX combination exhibited potent renoprotective effects against LPS-induced SA-AKI, possibly due to their antioxidant and anti-inflammatory properties. These results suggest that the GA-DEX combination could be a promising and effective therapeutic agent for managing SA-AKI. Full article

Concern over the presence of pharmaceutical waste in the environment has prompted research into the management of emerging organic micropollutants (EOMs). In response, sustainable technologies have been applied as alternatives to reduce the effects of these contaminants. This study investigated the capacity of filamentous fungi isolated from iron mine soil in the Amazon region to biodegrade the drug chloroquine diphosphate. An initial screening assessed the growth of four fungal strains on solid media containing chloroquine diphosphate: Trichoderma pseudoasperelloides CBMAI 2752, Penicillium rolfsii CBMAI 2753, Talaromyces verruculosus CBMAI 2754, and Penicillium sp. cf. guaibinense CBMAI 2758. Among them, Penicillium sp. cf. guaibinense CBMAI 2758 was selected for further testing in liquid media. A Box–Behnken factorial design was applied with three variables, pH (5, 7, and 9), incubation time (5, 10, and 15 days), and chloroquine diphosphate concentration (50, 75, and 100 mg·L⁻¹), totaling 15 experiments. The samples were analyzed by gas chromatography–mass spectrometry (GC-MS). The most effective conditions for chloroquine biodegradation were pH 7, 100 mg·L⁻¹ concentration, and 10 days of incubation. Four metabolites were identified: one resulting from N-deethylation M1 (N4-(7-chloroquinolin-4-yl)-N1-ethylpentane-1,4-diamine), two from carbon–carbon bond cleavage M2 (7-chloro-N-ethylquinolin-4-amine) and M3 (N1,N1-diethylpentane-1,4-diamine), and one from aromatic deamination M4 (N1-ethylbutane-1,4-diamine) by enzymatic reactions. The toxicity analysis showed that the products obtained from the biodegradation of chloroquine were less toxic than the commercial formulation of this compound. These findings highlight the biotechnological potential of Amazonian fungi for drug biodegradation and decontamination. Full article

Pear (Pyrus pyrifolia) is an important deciduous fruit tree that requires a specific period of low-temperature accumulation to trigger spring flowering. The warmer winter caused by global warming has led to insufficient winter chilling, disrupting floral initiation and significantly reducing pear yields in Southern China. In this study, we integrated targeted phytohormone metabolomics, full-length transcriptomics, and proteomics to explore the regulatory mechanisms of dormancy in ‘Mixue’, a pear cultivar with an extremely low chilling requirement. Comparative analyses across the multi-omics datasets revealed 30 differentially abundant phytohormone metabolites (DPMs), 2597 differentially expressed proteins (DEPs), and 7722 differentially expressed genes (DEGs). Integrated proteomic and transcriptomic expression clustering analysis identified five members of the dormancy-associated MADS-box (DAM) gene family among dormancy-specific differentially expressed proteins (DEPs) and differentially expressed genes (DEGs). Phytohormone correlation analysis and cis-regulatory element analysis suggest that DAM genes may mediate dormancy progression by responding to abscisic acid (ABA), gibberellin (GA), and salicylic acid (SA). A dormancy-associated transcriptional regulatory network centered on DAM genes and phytohormone signaling revealed 35 transcription factors (TFs): 19 TFs appear to directly regulate the expression of DAM genes, 18 TFs are transcriptionally regulated by DAM genes, and two TFs exhibit bidirectional regulatory interactions with DAM. Within this regulatory network, we identified a novel pathway involving REVEILLE 6 (RVE6), DAM, and CONSTANS-LIKE 8 (COL8), which might play a critical role in regulating bud dormancy in the ‘Mixue’ low-chilling pear cultivar. Furthermore, lncRNAs ONT.19912.1 and ONT.20662.7 exhibit potential cis-regulatory interactions with DAM1/2/3. This study expands the DAM-mediated transcriptional regulatory network associated with bud dormancy, providing new insights into its molecular regulatory mechanisms in pear and establishing a theoretical framework for future investigations into bud dormancy control. Full article

Gallic acid, a major phenolic compound in wine, significantly influences its sensory profile and health-related properties, making its accurate measurement essential for both enological and nutritional studies. In this context, a derivatization protocol for gallic acid using ethyl chloroformate (ECF) was developed and optimized for GC-MS analysis, with experimental conditions refined through a Box–Behnken Design (BBD). The BBD systematically investigated the effects of three critical reagent volumes: ethyl chloroformate, pyridine, and ethanol. This approach elucidated complex interactions and quadratic effects, leading to a predictive second-order polynomial model and identifying the optimal derivatization conditions for maximum yield (137 µL of ethyl chloroformate, 51 µL of pyridine, and 161 µL of ethanol per 150 µL of wine). The BBD-optimized GC-MS method was validated and successfully applied to quantify gallic acid in diverse commercial wine samples (white, red, conventional, natural). A key finding was the method’s wide dynamic range, enabling accurate quantification from 5 up to over 600 µg/mL without sample dilution. This work represents, to our knowledge, the first application of a BBD for optimizing the ethyl chloroformate derivatization of gallic acid, providing a robust, efficient, and widely applicable analytical tool for routine quality control and enological research. Full article

This paper presents methods for modelling and optimising the industrial limestone grinding process carried out using a real limestone plant. Two key process evaluation indicators were developed: specific electric energy consumption and an extended indicator that also includes gas usage. Using process data collected from the SCADA system and results from industrial factorial experiments, regression artificial neural network models were developed, with controllable process parameters used as inputs. In the next phase, black-box optimisation was performed using Bayesian and genetic algorithms to identify optimal mill operating settings. The results demonstrate significant improvements in energy efficiency, with energy savings reaching up to 48% in selected cases. The proposed methodology can be effectively applied to enhance energy performance in similar industrial grinding processes. Full article

Aluminum alloy, due to its low melting point and high thermal conductivity, deforms and contracts significantly during welding. To mitigate this and achieve full penetration in a single pass, this study uses GTAW (Gas Tungsten Arc Welding) additive manufacturing and optimizes welding groove parameters via the Box-Behnken Response Surface Methodology. The focus is on improving tensile strength and penetration depth by analyzing the effects of groove angle, root face width, and root gap. The results show that groove angle most significantly affects tensile strength and penetration depth. Hardness profiles exhibit a W-shape, with base material hardness decreasing and weld zone hardness increasing as groove angle rises. Root face width reduces hardness fluctuation in the weld zone, and an appropriate root gap compensates for thermal expansion, enhancing joint performance. The interaction between root face width and root gap most impacts tensile strength, while groove angle and root face width interaction most affects penetration depth. The optimal welding parameters for 7xxx aluminum alloy GTAW are a groove angle of 70.8°, root face width of 1.38 mm, and root gap of 0 mm. This results in a tensile strength of 297.95 MPa and penetration depth of 5 mm, a 90.38% increase in tensile strength compared to the RSM experimental worst group. Microstructural analysis reveals the presence of β-Mg₂Si and η-MgZn₂ strengthening phases, which contribute to the material’s enhanced mechanical properties. Fracture surface examination exhibits characteristic ductile fracture features, including dimples and shear lips, confirming the material’s high ductility. The coexistence of these strengthening phases and ductile fracture behavior indicates excellent overall mechanical performance, balancing strength and plasticity. Full article

To address the impact of insulation medium degradation in the arc quenching chambers of ultra-high-voltage SF₆ circuit breakers on phase-controlled switching accuracy caused by multiple operations throughout the service life, this paper proposes an adaptive switching algorithm. First, a modified formula for the breakdown voltage of mixed gases is derived based on the synergistic effect. Considering the influence of contact gap on electric field distortion, an adaptive switching strategy is designed to quantify the dynamic relationship among operation times, insulation strength degradation, and electric field distortion. Then, multi-round switching-on and switching-off tests are carried out under the condition of fixed single-arc ablation amount, and the laws of voltage–current, gas decomposition products, and pre-breakdown time are obtained. The test data are processed by the least squares method, adaptive switching algorithm, and machine learning method. The results show that the coincidence degree of the pre-breakdown time obtained by the adaptive switching algorithm and the test value reaches 90%. Compared with the least squares fitting, this algorithm achieves a reasonable balance between goodness of fit and complexity, with prediction deviations tending to be randomly distributed, no obvious systematic offset, and low dispersion degree. It can also explain the physical mechanism of the decay of insulation degradation rate with the number of operations. Compared with the machine learning method, this algorithm has stronger generalization ability, effectively overcoming the defects of difficult interpretation of physical causes and the poor engineering adaptability of the black box model. Full article

MIKC-type MADS-box transcription factors constitute one of the largest gene families in plants, playing pivotal roles in regulating plant growth and development, hormone signaling transduction, and responses to biotic and abiotic stresses. However, there have been no reports on the systematic identification and characterization of MIKC-type MADS-box proteins in walnuts. In this study, we identified 52 JrMADS genes in the walnut genome and transcriptome, and categorized them into 14 subfamilies through structural domain and phylogenetic tree analysis. It was found that these genes were unevenly distributed across 16 chromosomes. Within the MIKC-type MADS-box gene family, we identified three pairs of tandem-duplicated genes and 40 pairs of segmental duplicated genes, indicating that segmental duplication was the primary mechanism of gene amplification in walnut. Ka/Ks analysis showed that the family genes have undergone purifying selection during evolutionary processes. The promoter was predicted to contain cis-acting elements related to growth, development, plant hormones, and stress response. Expression profile analysis showed that JrMADS genes have different expression patterns in various tissues and developmental stages of male and female flower buds. Notably, an ancient clade of TM8 (JrMADS43) genes was found, which is absent in Arabidopsis but present in other flowering plants. Another gene, TM6 gene (JrMADS4), belongs to the AP3 subfamily and is a clade that has diverged from tomatoes. Through qPCR analysis, we verified the differential expression of JrMADS genes at different developmental stages (MB-1/2/3 and FB-1/2/3), with JrMADS5, JrMADS8, JrMADS14, JrMADS24, JrMADS40, JrMADS46, JrMADS47, JrGA3ox1, and JrGA3ox3 showing significantly higher expression in male than in female flower buds. In summary, our results provide valuable information for further biological functions research on MIKC-type MADS-box genes in walnut, such as flower organ development, and lays a solid foundation for future studies. Full article

Deep tight sandstone reservoirs are characterized by low porosity and permeability, complex pore structure, and strong heterogeneity. Conducting research on the heterogeneity characteristics of reservoirs could lay a foundation for evaluating their effectiveness and accurately identifying advantageous reservoirs, which is of great significance for searching for “sweet spot” oil and gas reservoirs in tight reservoirs. In this study, the deep tight sandstone reservoir in the Dibei area, northern Kuqa depression, Tarim Basin, China, is taken as the research object. Firstly, statistical methods are used to calculate the coefficient of variation (CV) and coefficient of heterogeneity (TK) of core permeability, and the heterogeneity within the reservoir is evaluated by analyzing the variations in the reservoir permeability. Then, based on fractal theory, the fractal and multifractal parameters of the GR and acoustic logs are calculated using the box dimension, correlation dimension, and the wavelet leader methods. The results show that the heterogeneity revealed by the box dimension, correlation dimension, and multifractal singular spectrum calculated based on well logs is consistent and in good agreement with the parameters calculated based on core permeability. The heterogeneity of gas layers is comparatively weaker, while that of dry layers is stronger. In addition, the fractal parameters of GR and the acoustic logs of three wells with the oil test in the study area were analyzed, and the relationship between reservoir heterogeneity and production was determined: As reservoir heterogeneity decreases, production increases. Therefore, reservoir heterogeneity can be used as an indicator of production; specifically, reservoirs with weak heterogeneity have high production. Full article

Based on the medium-pressure natural gas ethane recovery and helium extraction process, this paper proposes three different refrigerant Schemes. Thermodynamic analysis and adaptability evaluation of the three Schemes were conducted using Aspen HYSYS V12 software. The ethylene–propane cascade refrigeration Scheme demonstrated superior energy efficiency in terms of comprehensive energy consumption, heat exchange performance in the cryogenic cold box, and exergy analysis. Adaptability analysis indicated that this Scheme exhibits strong tolerance to variations in feed gas temperature as well as N₂ and CO₂ content. The ethylene–propane cascade refrigeration process demonstrates significant energy-saving advantages and exhibits robust operational performance. Full article

This study investigates hazardous emissions from foundry binder systems, comparing organic resins (phenolic urethane, furan, and alkaline-phenolic) and clay-bonded green sand with inorganic alternatives (sodium silicate and geopolymer). The research was conducted at the Fundaciόn Azterlan pilot plant (Spain), involving controlled chamber tests for the production of 60 kg iron alloy castings in 110 kg sand molds. The molds were evaluated under two configurations: homogeneous systems, where both mold and cores were manufactured using the same binder (five trials), and heterogeneous systems, where different binders were used for mold and cores (four trials). Each mold was placed in a metallic box fitted with a lid and an integrated gas extraction duct. The lid remained open during pouring and was closed immediately afterward to enable efficient evacuation of casting gases through the extraction system. Although the box was not completely airtight, it was designed to direct most exhaust gases through the duct. Along the extraction system line, different sampling instruments were strategically located for the precise measurement of contaminants: volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), phenol, multiple forms of particulate matter (including crystalline silica content), and gases produced during pyrolysis. Across the nine trials, inorganic binders demonstrated significant reductions in gas emissions and priority pollutants, achieving decreases of over 90% in BTEX compounds (benzene, toluene, ethylbenzene, and xylene) and over 94% in PAHs compared to organic systems. Gas emissions were also substantially reduced, with CO emissions lowered by over 30%, NO_x by more than 98%, and SO₂ by over 75%. Conducted under the Greencasting LIFE project (LIFE 21 ENV/FI/101074439), this work provides empirical evidence supporting sodium silicate and geopolymer binders as viable, sustainable solutions for minimizing occupational and ecological risks in metal casting processes. Full article

This study investigates the modeling of surface roughness (Ra) in the laser cutting of EN 10130 steel process by integrating classical statistical and machine learning methods. First, a quadratic model was developed using response surface methodology (RSM) based on a Box–Behnken experimental design with 17 runs, using cutting speed, laser power, and auxiliary gas pressure as input parameters. Although the RSM model achieved an R² value of 0.8227, there were still some nonlinear deviations between the predicted and experimental values. To improve the prediction accuracy, a regression tree algorithm was applied to model the residuals of the RSM output. The resulting hybrid model, which combines RSM predictions with machine learning-based corrections, yielded a higher R² of 0.8889 and a lower RMSE compared to the original RSM model. A leave-one-out cross-validation (LOOCV) was performed to evaluate the generalization, which resulted in an RMSE of 0.3241 and an R² of 0.6039. These findings confirm the effectiveness of the hybrid approach in capturing complex dependencies and improving prediction accuracy, highlighting its potential for advanced process modeling in laser machining. Full article

This study proposes a novel non-destructive methodology for assessing structural integrity in liquefied natural gas (LNG) carrier cargo containment systems (CCSs), addressing limitations of conventional inspection techniques like visual inspection and vacuum box testing. The method leverages strain-induced martensitic transformation (SIMT) in austenitic stainless steel (SUS304L), widely used in CCS membranes, quantifying magnetic permeability increase via a Feritscope to evaluate deformation history and damage. To analyze SUS304L SIMT behavior, uniaxial tensile (UT) and equi-biaxial tensile (EBT) tests were conducted, as these stress states predominate in CCS membranes. Microstructural evolution was examined using X-ray diffraction (XRD) and electron backscatter diffraction (EBSD), allowing a quantitative assessment of the transformed martensite volume fraction versus plastic strain. Subsequently, Feritscope measurements under the same conditions were calibrated against the XRD-measured martensite volume fraction for accuracy. Based on testing, this study introduces three complementary Feritscope approaches for evaluating CCS health: outlier detection, quantitative damaged area analysis, and time-series analysis. The methodology integrates data-driven quantitative assessment with conventional qualitative inspection, enhancing safety and maintenance efficiency. Full article

The implementation of lean drilling and completion design techniques is a pivotal strategy for the petroleum and natural gas industry to achieve green, low-carbon, and intelligent transformation and innovation. These techniques significantly enhance oil and gas recovery rates. In shale gas development, the shale brittleness index plays a crucial role in evaluating fracturing ability during hydraulic fracturing. Indoor experiments on Gulong shale oil were conducted under a confining pressure of 30 MPa. Based on Rickman’s brittleness evaluation method, this study performed numerical simulations of triaxial compression tests on shale using the finite discrete element method. The fractal dimensions of the fractures formed during shale fragmentation were calculated using the box-counting method. Utilizing the obtained data, a multiple linear regression equation was established with elastic modulus and Poisson’s ratio as the primary variables, and the coefficients were normalized to propose a new brittleness evaluation method. The research findings indicate that the finite discrete element method can effectively simulate the rock fragmentation process, and the established multiple linear regression equation demonstrates high reliability. The weights reassigned for brittleness evaluation based on Rickman’s method are as follows: the coefficient for elastic modulus is 0.43, and the coefficient for Poisson’s ratio is 0.57. Furthermore, the new brittleness evaluation method exhibits a stronger correlation with the brittleness mineral index. The fractal characteristics of crack networks and the relationship between symmetry response and mechanical parameters offer a new theoretical foundation for brittle weight distribution. Additionally, the scale symmetry characteristics inherent in fractal dimensions can serve as a significant indicator for assessing complex crack morphology. Full article

Semicrystalline polystyrene spheroidal nanoparticles (50–100 nm) were obtained via microemulsion polymerization. They were evaluated as coal collectors in a low-rank carbonaceous mineral containing 2% organic carbon. The recovery of coal using nanoparticles as collectors was 88.2%, in contrast to 53.2%, 46.4%, and 44.8% achieved using an amine-type compound, kerosene, and diesel, respectively. X-ray photoelectron spectroscopy (XPS) and zeta potential measurements confirmed the polystyrene–mineral surface chemical interaction. A Box–Behnken experimental design for flotation optimization was applied, and the results showed that the coal recovery increased up to 99.5% when the dosage of the collector was increased. A contact angle study and density functional theory calculations, together with XPS results, allowed us to postulate an interaction mechanism in which polystyrene nanoparticles adsorb onto the coal surface through hydrophobic interactions, rendering the oxidized surface hydrophobic and the coal buoyant by adhering to the gas bubbles. Full article