Search Results (3,661)

Background/Objective: In the pursuit of identifying novel therapeutic agents against breast cancer, a major priority is finding agents that effectively and safely inhibit the signaling pathways sustaining cancer cells. To better focus research efforts in validating such candidates, this in silico study assessed the pharmacokinetic profiles, thermodynamics, and binding affinity of chlorogenic acid and cinnamaldehyde with the upstream mediators of the Akt pathway implicated in breast cancer cells. Methods: Various software and online tools were used to conduct molecular docking of the small molecules with the proteins PI3K, Akt, and PDK1, and to examine their absorption, distribution, metabolism, elimination, and toxicity (ADMET) profile. Results: The results show strong binding energy (all within the range of those of FDA-approved drugs) and thermostability between the compounds and the proteins. The phytochemicals were predicted to have moderate oral bioavailability and tissue distribution, and were identified as substrates of drug metabolizing enzymes, but not deactivated. Conclusion: Although these predictive data warrant confirmation in a biological system, they suggest that the compounds have good pharmacokinetics and are strong inhibitors of the Akt pathway, with great potential to shut down breast cancer cell invasion and migration. These data also inform more efficient experimental designs for our planned in vivo studies. Full article

Antibiotic resistance is one of the most significant public health issues today. As a consequence, there is an urgent need for novel classes of antibiotics. This necessitates the development of highly efficient screening methods for the rapid identification of antibiotic-producing bacteria. Here, we describe a new method for high-throughput screening of antimicrobial compounds (AMC) producing halophilic bacteria. Our methodology used a newly designed 3D-printed Petri plate replicator used for drop deposition and colony replication. We employed this device in combination with a modified agar overlay assay to screen more than 7400 bacterial colonies. A total of 54 potential AMC producers were discovered at a success rate of 0.7%. Although 40% of them lost their antibacterial activity during the secondary screening, 22 strains retained inhibitory activity and were able to suppress the growth of one or more safe relatives of the ESKAPE group pathogens. The ethyl acetate extract from the most potent strain, Virgibacillus salarius POTR191, demonstrated moderate antibacterial activity against Enterococcus faecalis, Acinetobacter baumanii, and Staphylococcus epidermidis with minimal inhibitory concentrations of 128 μg/mL, 128 μg/mL, and 512 μg/mL, respectively. We propose that our replica plate assay could be used for target-based antimicrobial screening of various extremophilic bacteria. Full article

In the process of evaluating the quality of a company’s development, the issues related to production capacity and environmental pollution have emerged as significant concerns. Drawing on the methodologies employed in previous related research, this study utilizes the Data Envelopment Analysis with relaxation variables and the Global Malmquist–Luenberger index to measure the green total factor productivity of Chinese heavy-polluting enterprises. The main findings of this study are as follows: (1) It is clearly demonstrated that higher managerial effectiveness has a substantial positive impact on the improvement of a company’s green total factor productivity; (2) the digitalization progress within enterprises serves as a moderating factor in the relationship between managerial effectiveness and green total factor productivity; (3) the extent of financial constraints acts as a mediating variable, intervening in the relationship between managerial efficiency and green total factor productivity; and (4) a threshold effect is detected between managerial effectiveness and the debt repayment pressure faced by enterprises. When the threshold values of managerial effectiveness or the quick ratio are surpassed, the influence of managerial effectiveness on the green total factor productivity of enterprises will undergo a change. Full article

Microgreens, having short growth cycles and efficient nutrient uptake, are ideal candidates for biofortification. This study investigated the effects of selenium (Se) and zinc (Zn) on photosynthetic performance in four hydroponically grown Brassica microgreens (broccoli, pak choi, kohlrabi, and kale), using direct and modulated chlorophyll a fluorescence and chlorophyll-to-carotenoid ratios (Chl/Car). The plants were treated with Na₂SeO₄ at 0 (control), 2, 5, and 10 mg/L or ZnSO₄ × 7H₂O at 0 (control), 5, 10, and 20 mg/L. The results showed species-specific responses with Se or Zn uptake. Selenium enhanced photosynthetic efficiency in a dose-dependent manner for most species (8–26% on average compared to controls). It increased the plant performance index (PI_tot), particularly in pak choi (+62%), by improving both primary photochemistry and inter-photosystem energy transfer. Kale and kohlrabi exhibited high PSII-PSI connectivity for efficient energy distribution, with increased cyclic electron flow around PSI and reduced Chl/Car up to 8.5%, while broccoli was the least responsive. Zinc induced variable responses, reducing PI_tot at lower doses (19–23% average decline), with partial recovery at 20 mg/L (9% average reduction). Broccoli exhibited higher susceptibility, with inhibited Q_A re-oxidation, low electron turnover due to donor-side restrictions, and increased pigment ratio (+3.6%). Kohlrabi and pak choi tolerated moderate Zn levels by redirecting electron flow, but higher Zn levels impaired PSII and PSI function. Kale showed the highest tolerance, maintaining stable photochemical parameters and total electron flow, with increased pigment ratio (+4.5%) indicating better acclimation. These results highlight the beneficial stimulant role of Se and the dual essential/toxic nature of Zn, thus emphasizing genotype and dose-specific optimizations for effective biofortification. Full article

This study investigates strategies for urban-scale renewable energy integration through a photovoltaic-centric approach, with a case study of a district in Barcelona. The methodology integrates spatial and morphological data using a geographic information system (GIS)-based and clustering framework to address challenges of CO₂ emissions, air pollution, and energy inefficiency. Rooftop availability and photovoltaic (PV) design constraints are analysed under current urban regulations. The spatial analysis incorporates building geometry and solar exposure, while an evolutionary optimisation algorithm in Grasshopper refines shading analysis, energy yield, and financial performance. Clustering methods (K-means and 3D proximity) group PV panels by solar irradiance uniformity and spatial coherence to enhance system efficiency. Eight PV deployment scenarios are evaluated, incorporating submodule integrated converter technology under a solar power purchase agreement model. Results show distinct trade-offs among PV scenarios. The standard fixed tilted (31.5° tilt, south-facing) scenario offers a top environmental and performance ratio (PR) = 66.81% but limited financial returns. In contrast, large- and huge-sized modules offer peak financial returns, aligning with private-sector priorities but with moderate energy efficiency. Medium- and large-size scenarios provide balanced outcomes, while a small module and its optimised rotated version scenarios maximise energy output yet suffer from high capital costs. A hybrid strategy combining standard fixed tilted with medium and large modules balances environmental and economic goals. The district’s morphology supports “solar neighbourhoods” and demonstrates how multi-scenario evaluation can guide resilient PV planning in Mediterranean cities. Full article

Accurate regional-scale mapping of soil organic matter (SOM) is crucial for land productivity management and global carbon pool monitoring. Current remote sensing inversion of SOM faces challenges, including the underutilization of temporal information and low feature selection efficiency. To address these limitations, this study developed an integrated framework combining multi-temporal Landsat imagery, field-measured SOM data, intelligent feature optimization, and machine learning. The framework employs two novel image-processing strategies: the Maximum Annual Bare-Soil Composite (MABSC) method to extract background spectral information and the Multi-temporal Feature Optimization Composite (MFOC) method to capture seasonal and environmental dynamics. These features, along with topographic covariates, were processed using an improved Feature-Optimized and Interpretable XGBoost (FOI-XGB) model for key variable selection and spatial mapping. Validation across two subtropical coastal mountainous regions at different scales in southeastern China demonstrated the framework’s effectiveness and robustness. Key findings include the following: (1) Both the MABSC-derived spectral bands and the MFOC-optimized indices significantly outperformed traditional single-season approaches. Their combined use achieved a moderate SOM inversion accuracy (R² = 0.42–0.44). (2) The FOI-XGB model substantially outperformed traditional feature selection methods (Pearson, SHAP, and CorrSHAP), achieving significant regional R² improvements ranging from 9.72% to 88.89%. (3) The optimal model integrating the MABSC-derived features, MFOC-optimized indices, and topographic covariates attained the highest accuracy (R² up to 0.51). This represents major improvements compared with using topographic covariates alone (R² increase of up to 160.11%) or the combined spectral features (MABSC + MFOC) alone (R² increase of up to 15.91%). This study provides a robust, scalable, and practical technical solution for accurate SOM mapping in complex environments, with significant implications for sustainable land management and carbon monitoring. Full article

The treatment of contaminants from road infrastructure poses significant challenges due to their variable composition and the high concentrations of chloride ions, heavy metals, and oil-derived substances. Traditional methods for protecting groundwater environments are often insufficient. A promising alternative is permeable reactive barrier (PRB) technology, which utilizes recycled materials and construction waste as reactive components within the treatment zone of the ground. This paper delves into the potential of employing a composite (MIX) consisting of modified construction aggregate (as recycled material) and activated carbon (example of reactive material) to address environmental contamination from a mixture of heavy metals and chloride. The research involved chemical modifications of the road aggregate, activated carbon, and their composite, followed by laboratory tests in glass reactors and non-flow batch tests to evaluate the kinetics and chemical equilibrium of the reactions. The adsorption process was stable and conformed to the pseudo-second-order kinetics and Langmuir, Toth, and Redlich–Peterson isotherm models. Studies using MIX from a heavy metal model solution showed that monolayer adsorption was a key mechanism for removing heavy metals, with strong fits to the Langmuir (R² > 0.80) and Freundlich models, and optimal efficiencies for Cd and Ni (R² > 0.90). The best fit, at Cd, Cu, Ni = 0.96, however, was with the Redlich–Peterson isotherm, indicating a mix of physical and chemical adsorption on heterogeneous surfaces. The Toth model was significant for all analytes, fitting Cl and Cd well and Pb and Zn moderately. The modifications made to the composite significantly enhanced its effectiveness in removing the contaminant mixture. The test results demonstrated an average reduction of chloride by 85%, along with substantial removals of heavy metals: lead (Pb) by 90%, cadmium (Cd) by 86%, nickel (Ni) by 85%, copper (Cu) by 81%, and zinc (Zn) by 79%. Further research should focus on the removal of other contaminants and the optimization of magnesium oxide (MgO) dosage. Full article

Recent major advancements in cryo-electron microscopy (cryo-EM) have enabled high-resolution structural analysis, accompanied by developments in image processing software packages for single-particle analysis (SPA). SPA facilitates the 3D reconstruction of proteins and macromolecular complexes from numerous individual particles. In this study, we systematically evaluated the impact of symmetry parameters and particle quantity on the 3D reconstruction efficiency using the dihydrolipoyl acetyltransferase (E2) inner core of the pyruvate dehydrogenase complex (PDC). We specifically examined how inappropriate symmetry constraints can introduce structural artifacts and distortions, underscoring the necessity for accurate symmetry determination through rigorous validation methods such as directional Fourier shell correlation (FSC) and local-resolution mapping. Additionally, our analysis demonstrates that efficient reconstructions can be achieved with a moderate particle number, significantly reducing computational costs without compromising structural accuracy. We further contextualize these results by discussing recent developments in SPA workflows and hardware optimization, highlighting their roles in enhancing reconstruction accuracy and computational efficiency. Overall, our comprehensive benchmarking provides strategic insights that will facilitate the optimization of SPA experiments, particularly in resource-limited settings, and offers practical guidelines for accurately determining symmetry and particle quantity during cryo-EM data processing. Full article

Due to the complex mineral composition, low clay content, and strong heterogeneity of the mixed sedimentary shale in the Xinjiang Salt Lake Basin, the wettability characteristics of the reservoir and their influencing factors are not yet clear, which restricts the evaluation of oil-bearing properties and the identification of sweet spots. This paper analyzed mixed sedimentary shale samples from the Lucaogou Formation of the Jimsar Sag and the Fengcheng Formation of the Mahu Sag. Methods such as petrographic thin sections, X-ray diffraction, organic matter content analysis, and argon ion polishing scanning electron microscopy were used to examine the lithological and mineralogical characteristics, geochemical characteristics, and pore space characteristics of the mixed sedimentary shale reservoir. Alternating imbibition and nuclear magnetic resonance were employed to quantitatively characterize the wettability of the reservoir and to discuss the effects of compositional factors, lamina types, and pore structure on wettability. Research findings indicate that the total porosity, measured by the alternate imbibition method, reached 72% of the core porosity volume, confirming the effectiveness of alternate imbibition in filling open pores. The Lucaogou Formation exhibits moderate to strong oil-wet wettability, with oil-wet pores predominating and well-developed storage spaces; the Fengcheng Formation has a wide range of wettability, with a higher proportion of mixed-wet pores, strong heterogeneity, and weaker oil-wet properties compared to the Lucaogou Formation. TOC content has a two-segment relationship with wettability, where oil-wet properties increase with TOC content at low TOC levels, while at high TOC levels, the influence of minerals such as carbonates dominates; carbonate content shows an “L” type response to wettability, enhancing oil-wet properties at low levels (<20%), but reducing it due to the continuous weakening effect of minerals when excessive. Lamina types in the Fengcheng Formation significantly affect wettability differentiation, with carbonate-shale laminae dominating oil pores, siliceous laminae contributing to water pores, and carbonate–feldspathic laminae forming mixed pores; the Lucaogou Formation lacks significant laminae, and wettability is controlled by the synergistic effects of minerals, organic matter, and pore structure. Increased porosity strengthens oil-wet properties, with micropores promoting oil adsorption through their high specific surface area, while macropores dominate in terms of storage capacity. Wettability is the result of the synergistic effects of multiple factors, including TOC, minerals, lamina types, and pore structure. Based on the characteristic that oil-wet pores account for up to 74% in shale reservoirs (mixed-wet 12%, water-wet 14%), a wettability-targeted regulation strategy is implemented during actual shale development. Surfactants are used to modify oil-wet pores, while the natural state of water-wet and mixed-wet pores is maintained to avoid interference and preserve spontaneous imbibition advantages. The soaking period is thus compressed from 30 days to 3–5 days, thereby enhancing matrix displacement efficiency. Full article

Detecting biased language in large-scale corpora, such as the Wiki Neutrality Corpus, is essential for promoting neutrality in digital content. This study systematically evaluates a range of machine learning (ML) and deep learning (DL) models for the detection of biased and pre-conditioned phrases. Conventional classifiers, including Extreme Gradient Boosting (XGBoost), Light Gradient-Boosting Machine (LightGBM), and Categorical Boosting (CatBoost), are compared with advanced neural architectures such as Bidirectional Encoder Representations from Transformers (BERT), Long Short-Term Memory (LSTM) networks, and Generative Adversarial Networks (GANs). A novel hybrid architecture is proposed, integrating DistilBERT, LSTM, and GANs within a unified framework. Extensive experimentation with intermediate variants DistilBERT + LSTM (without GAN) and DistilBERT + GAN (without LSTM) demonstrates that the fully integrated model consistently outperforms all alternatives. The proposed hybrid model achieves a cross-validation accuracy of 99.00%, significantly surpassing traditional baselines such as XGBoost (96.73%) and LightGBM (96.83%). It also exhibits superior stability, statistical significance (paired t-tests), and favorable trade-offs between performance and computational efficiency. The results underscore the potential of hybrid deep learning models for capturing subtle linguistic bias and advancing more objective and reliable automated content moderation systems. Full article

The objective of this study was to evaluate the physiological, biochemical, and productive effects of the foliar application of bioregulators, based on auxin, cytokinin, and gibberellic acid, on yellow melon, cultivar DALI^®, plants subjected to different salinity levels in a protected environment to simulate Brazil’s semi-arid conditions. The experiment was conducted using a completely randomized block design, in a 4 × 3 factorial scheme, with four salinity levels (0, 2, 4, and 6 dS m⁻¹) and three doses of the bioregulator, Stimulate^® (0%, 100%, and 150% of the recommended dose), with six weekly applications. The physiological variables (chlorophyll a fluorescence and gas exchange) and biochemical parameters (antioxidant enzyme activity and lipid peroxidation) were evaluated at 28 and 42 days after transplanting, and the agronomic traits (fresh fruit mass, physical attributes, and post-harvest quality) were evaluated at the end of the experiment. The results indicated that salinity impaired the physiological and productive performance of the plants, especially at higher levels (4 and 6 dS m⁻¹), causing oxidative stress, reduced photosynthesis, and decreased yield. However, the application of the bioregulator at the 100% dose mitigated the effects of salt stress under moderate salinity (2 dS m⁻¹), promoting higher CO₂ assimilation rates of up to 31.5%, better water-use efficiency, and reduced lipid peroxidation. In addition, the fruits showed a greater mass of up to 66%, thicker pulp, and higher soluble solids (> 10 °Brix) content, making them suitable for sale in the market. The 150% dose did not provide additional benefits and, in some cases, resulted in inhibitory effects. It is concluded that the application of Stimulate^® at the recommended dose is effective in mitigating the effects of moderate salinity, up to ~3 dS m⁻¹, in yellow melon crops; however, its effectiveness is limited under high salinity conditions, requiring the use of complementary strategies. Full article

Herein, we report a one-pot palladium- and ligand-free tandem Sonogashira coupling/regioselective 6-endo-dig oxacyclization reaction of 2,4-diiodo-1-methyl-imidazole-5-carboxylic acid with terminal alkynes mediated by Copper(I). This impressive approach offers a straightforward, practical, and efficient tandem procedure for accessing 2-alkynylated pyrano[4,3-d]imidazol-4-one in moderate to good yields with an exclusive 6-endo-dig oxacyclization. Notably, this cost-effective methodology demonstrates broad substrate compatibility with various commercially available aliphatic and (hetero)aromatic terminal alkynes. Furthermore, DFT studies were performed to elucidate the origin of this regioselective 6-endo-dig oxacyclization reaction. Full article

Background/Objectives: Chemotherapy-induced alopecia is a common and distressing side effect of cancer treatment, significantly impacting patients’ psychological well-being. Nanocarriers offer a promising strategy for targeted drug delivery to hair follicles, while chitosan nanoparticles have demonstrated hair-growth-promoting properties. This study explores the potential of chitosan nanoparticles as a topical delivery system for five pharmacological agents—phenobarbital, pioglitazone, rifampicin, N-acetylcysteine, and tacrolimus—to prevent chemotherapy-induced alopecia. Methods: Drug-loaded chitosan nanoparticles were prepared using the ionic gelation technique and characterized by particle size, zeta potential, entrapment efficiency, FT-IR spectroscopy, and TEM imaging. Their efficacy was assessed in a cyclophosphamide-induced alopecia model in C57BL/6 mice through macroscopic observation, histopathological examination, and scanning electron microscopy of regrown hair. Results: The prepared particles were spherical, cationic, and between 205 and 536 nm in size. The entrapment efficiencies ranged from 8% to 63%. All five drugs mitigated follicular dystrophy, shifting the hair follicle response from dystrophic catagen to dystrophic anagen. Phenobarbital demonstrated the most significant hair regrowth and quality improvements, followed by N-acetyl cysteine and pioglitazone. Tacrolimus showed moderate efficacy, while rifampicin was the least effective. Conclusions: These findings suggest that phenobarbital-loaded chitosan nanoparticles represent a promising approach for the prevention and treatment of chemotherapy-induced alopecia, warranting further investigation for clinical applications. Full article

Optimizing the metabolizable protein level in ruminant diets represents a promising strategy to increase nitrogen use efficiency and mitigate environmental pollution. This study explored the impacts of varying metabolizable protein (MP) levels on amino acid (AA) balance, nitrogen (N) utilization, and the ruminal microbiota in Hu lambs. Fifty-four female Hu lambs of 60 d old, with an average body weight (BW) of 18.7 ± 2.37 kg, were randomly allocated to three dietary MP groups: (1) low MP (LMP, 7.38% of DM), (2) moderate MP (MMP, 8.66% of DM), and (3) high MP (HMP, 9.93% of DM). Three lambs with similar BW within each group were housed together in a single pen, serving as one experimental replicate (n = 6). The feeding trial lasted for 60 days with 10 days for adaptation. The final BW of lambs in the MMP and HMP groups increased (p < 0.05) by 5.64% and 5.26%, respectively, compared to the LMP group. Additionally, lambs fed the MMP diet exhibited an 11.6% higher (p < 0.05) average daily gain than those in the LMP group. Increasing dietary MP levels enhanced (p < 0.05) N intake, urinary N, retained N, and percent N retained, but decreased apparent N digestibility (p < 0.05). Urinary uric acid, total purine derivatives, intestinally absorbable dietary protein, microbial crude protein, intestinally absorbable microbial crude protein, and actual MP supply all increased (p < 0.05) with higher MP values in the diet. The plasma concentrations of arginine, lysine, methionine, phenylalanine, threonine, aspartic acid, proline, total essential AAs, and total nonessential AAs were the lowest (p < 0.05) in the LMP group. In the rumen, elevated MP levels led to a significant increase (p < 0.05) in the ammonia N content. The relative abundances of Candidatus_Saccharimonas, Ruminococcus, and Oscillospira were the lowest (p < 0.05), whereas the relative abundances of Terrisporobacter and the Christensenellaceae_R-7_group were the highest (p < 0.05) in the MMP group. In conclusion, the moderate dietary metabolizable protein level could enhance growth performance, balance the plasma amino acid profiles, and increase nitrogen utilization efficiency in Hu lambs, while also altering the rumen bacterial community by increasing beneficial probiotics like the Christensenellaceae_R-7_group. Full article

This study investigates the energy performance of paraffin-based hybrid fuels enhanced with potassium nitrate (KNO₃), ammonium nitrate (NH₄NO₃), aluminum (Al), titanium (Ti), and stearic acid additives. The fuels were evaluated using thermochemical calculations via ProPEP3 Version 1.0.3.0 software, revealing significant improvements in specific impulse (I_sp) and combustion temperature. While formulations with nitrates and aluminum exhibited noticeable increases in combustion efficiency and thermal output, titanium-containing mixtures provided moderate improvements. Stearic acid improved fuel processability and provided a stable burning profile without significant energy penalties. These findings demonstrate that suitable combinations of additives can substantially improve the energy output of paraffin-based hybrid fuels, making them more viable for aerospace propulsion applications. Full article