Search Results (793)

Deep eutectic solvents (DESs) have been studied to obtain extracts from medicinal plants, aiming for a more environmentally friendly process. Aligned with this initiative, the use of predictive thermodynamic models for screening the best solvent represents a theoretical action to reduce experimental time and cost. Therefore, this study aimed to perform and validate a relative solubility screening of 5-methoxy-6,7-methylenedioxycoumarin and prenyletin-methyl-ether at 313 K in choline chloride, menthol, and betaine-based DES, using the COSMO-RS model in COSMOThermX software. The density of DES was also predicted with a maximum error of 7.31% for this property. Ultrasound-assisted extraction (UAE) with DES at 313 K, 30 min, and a solid/liquid ratio of 1:20 (w/w) was performed to confirm the theoretical solubility results experimentally, as the extracts were analyzed through ultrafast liquid chromatography (UFLC) for coumarin content. For the results, the coumarin molecules presented intense peaks in the nonpolar region of their σ-profile, and the relative solubility screening indicated the DES Men/Lau (2:1), known for its hydrophobic nature and low polarity, as the best DES to solubilize these coumarins. Nevertheless, the UFLC results, and the complementary solubility screening of pigments, showed an interaction preference of this DES with chlorophylls instead of coumarins. This result was corroborated by spectrophotometric analysis of the extracts in UV-Vis, demonstrating that experimental validation is still mandatory in extraction processes and that predictive methodologies such as COSMO-RS should be used as guiding tools and analyzed in a greater context, considering the complexity of plant matrices in the beginning of simulations. Full article

Background: Purple loosestrife (Lythrum salicaria L.) is a medicinal plant native to the spontaneous Romanian flora. The aim of this study was to investigate the phenolic profile, total phenolic content (TPC), and antioxidant capacity (AC) of two L. salicaria L. extracts, a hydro-methanolic extract (LSmet-1) and a hydro-ethanolic extract (LSeth-2), and their putative toxicity, as well as the effect on eye pigment content in the case of Drosophila melanogaster of an extract derived from LSmet-1 (LSmet-3). To the best of our knowledge, this is the first study to evaluate the influence of L. salicaria L. extracts on cytotoxicity and the expression of genes as determined by eye pigment levels, using a D. melanogaster-based model system. Methods: High-performance liquid chromatography was carried out to investigate the chemical composition of the extracts. Spectrophotometric methods were used to estimate their TPC and AC. Cytotoxicity was evaluated using an in vivo D. melanogaster diet-dependent viability assay and eye pigments of w^m4h males, suitable for position-effect variegation studies, which were quantified by a spectrophotometric method. Results: The results indicated that the main phenolic compounds were gallic acid, resveratrol, and rutin in LSmet-1, whereas in LSeth-2, gallic acid and quercetin were the most relevant. LSmet-1 had a higher TPC compared to LSeth-2. Both extracts exhibited notable efficacy in the applied in vitro antioxidant tests. The viability of flies on normal media increased in a concentration-dependent manner at lower concentrations, with the extract being toxic at higher concentrations. On a high-sugar diet, even lower concentrations were toxic. All tested concentrations influenced the eye pigment content. Conclusions: Our study brings new findings on L. salicaria L. extracts, suggesting the need for further investigation before introducing them in therapy. Full article

Polymer flooding is an enhanced oil recovery (EOR) technique that improves oil extraction by injecting polymer solutions into reservoirs. However, the disposal and treatment of polymer flooding waste liquids (PFWL) present significant challenges due to their high viscosity, complex molecular structure, and environmental impact. This study investigates the shear-induced degradation of polymer solutions, focusing on rheological properties, particle size distribution, and morphological changes under controlled shear conditions. Experimental results show that shear forces significantly reduce the viscosity of polymer solutions, with shear rates of 4285.36 s⁻¹ in the rotating domain and 3505.21 s⁻¹ in the fixed domain. The particle size analysis reveals a significant reduction in average particle size, indicating polymer aggregate breakup. SEM images confirm these morphological changes. Additionally, numerical simulations using a power-law model highlight the correlation between shear rate, wall shear stress, and polymer degradation efficiency. This study suggests that optimizing rotor–stator configurations with high shear forces is essential for efficient polymer degradation, offering insights for designing more effective polymer waste liquid treatment systems in oilfields. Full article

Background: Perinatal research faces significant challenges in understanding placental biology and maternal–fetal interactions due to limited access to human tissues and the lack of reliable models. Emerging technologies, such as liquid biopsy and single-cell analysis, offer novel, non-invasive approaches to investigate these processes. This scoping review explores the current applications of these technologies in placental development and the diagnosis of pregnancy complications, identifying research gaps and providing recommendations for future studies. Methods: This review adhered to PRISMA-ScR guidelines. Studies were selected based on their focus on liquid biopsy or single-cell analysis in perinatal research, particularly related to placental development and pregnancy complications such as preeclampsia, preterm birth, and fetal growth restriction. A systematic search was conducted in PubMed, Scopus, and Web of Science for studies published in the last ten years. Data extraction and thematic synthesis were performed to identify diagnostic applications, monitoring strategies, and biomarker identification. Results: Twelve studies were included, highlighting the transformative potential of liquid biopsy and single-cell analysis in perinatal research. Liquid biopsy technologies, such as cfDNA and cfRNA analysis, provided non-invasive methods for real-time monitoring of placental function and early identification of complications. Extracellular vesicles (EVs) emerged as biomarkers for conditions like preeclampsia. Single-cell RNA sequencing (scRNA-seq) revealed cellular diversity and pathways critical to placental health, offering insights into processes such as vascular remodeling and trophoblast invasion. While promising, challenges such as high costs, technical complexity, and the need for standardization limit their clinical integration. Conclusion: Liquid biopsy and single-cell analysis are revolutionizing perinatal research, offering non-invasive tools to understand and manage complications like preeclampsia. Overcoming challenges in accessibility and standardization will be key to unlocking their potential for personalized care, enabling better outcomes for mothers and children worldwide. Full article

Due to the nearly identical chemical properties of Lu and Yb, the production of no-carrier-added (NCA) ¹⁷⁷Lu faces significant challenges in their separation. Achieving efficient and streamlined separation of Lu and Yb is crucial for the production of NCA ¹⁷⁷Lu. This study systematically investigated the separation performance of the commercial Rext-P350 extraction resin for Lu and Yb. Static adsorption experiments revealed that, at a solid–liquid ratio of 8 g/L, both Lu³⁺ and Yb³⁺ were nearly completely adsorbed, with saturation adsorption capacities of 25.8 mg/g and 21.5 mg/g, respectively. An increase in the nitric acid concentration in the aqueous phase significantly inhibited adsorption, but the separation factor for Lu³⁺/Yb³⁺ remained above 1.88. The adsorption kinetics followed a pseudo-second-order model (R² > 0.99), with equilibrium reached within 15 min, demonstrating fast adsorption kinetics. Characterization by SEM, FT-IR, and XPS confirmed the chemical coordination between the resin and Lu³⁺/Yb³⁺. Dynamic chromatographic separation experiments showed that the Rext-P350 resin exhibited significantly better separation performance for Lu³⁺/Yb³⁺ compared to 2-ethylhexylphosphoric acid mono-2-ethylhexyl ester (P507) extraction resin. Leveraging the excellent performance of Rext-P350 resin, a two-stage continuous extraction chromatography process was designed, achieving efficient separation of 0.045 mg of Lu³⁺ from 200 mg of Yb³⁺ with a Lu³⁺ purity of 90.9% and a yield of 98.4%. This study provides a feasible separation technique for the purification of NCA ¹⁷⁷Lu. Full article

Leaves of Gentiana lutea L., traditionally used for treating heart disorders, represent a sustainable and underutilized source of bitter secoiridoids and xanthones, also found in Gentianae radix—an official herbal drug derived from the same, protected species. As root harvesting leads to the destruction of the plant, using the more readily available leaves could help reduce the pressure on this endangered natural resource. This study aimed to optimize the ultrasound-assisted extraction of the secoiridoid swertiamarin and the xanthone isogentisin from G. lutea leaves using response surface methodology (RSM). Subsequently, the stability of the bioactive compounds (swertiamarin, gentiopicrin, mangiferin, isoorientin, isovitexin, and isogentisin) in the optimized extract was monitored over a 30-day period under different storage conditions. The influence of extraction time (5–65 min), ethanol concentration (10–90% v/v), liquid-to-solid ratio (10–50 mL/g), and temperature (20–80 °C) was analyzed at five levels according to a central composite design. The calculated optimal extraction conditions for the simultaneous maximization of swertiamarin and isogentisin yields were 50 min extraction time, 30% v/v ethanol concentration, 30 mL/g liquid-to-solid ratio, and 62.7 °C extraction temperature. Under these conditions, the experimentally obtained yields were 3.75 mg/g dry weight for swertiamarin and 1.57 mg/g dry weight for isogentisin, closely matching the RSM model predictions. The stability study revealed that low-temperature storage preserved major bioactive compounds, whereas mangiferin stability was compromised by elevated temperature and light exposure. The established models support the production of standardized G. lutea leaf extracts and may facilitate the efficient separation and purification of their bioactive compounds, thereby contributing to the further valorization of this valuable plant material. Full article

Astringency, a complex oral sensation resulting from interactions between mucin and polyphenols, remains difficult to quantify in portable field settings. Therefore, quantifying the aggregation through interactions can enable the classification of the astringency intensity, and assessing the capillary action driven by the surface tension offers an effective approach for this purpose. This study successfully replicates tannic acid (TA)–mucin aggregation on a paper-based microfluidic chip and utilizes machine learning (ML) to analyze the resulting capillary flow dynamics. Aggregates formed by mixing mucin with TA solutions at three concentrations showed that higher TA levels led to greater aggregation, consequently reducing the capillary flow rates. The flow dynamics were consistently recorded using a smartphone mounted within a custom 3D-printed frame equipped with a motorized sample loading system, ensuring standardized experimental conditions. Among eight trained ML models, the support vector machine (SVM) demonstrated the highest classification accuracy at 95.2% in distinguishing the astringency intensity levels. Furthermore, fitting the flow data to a theoretical capillary flow equation allowed for the extraction of a single coefficient as an input feature, which achieved comparable classification performance, validating the simplified feature extraction strategy. This method was also feasible even with only a portion of the initial data. This approach is simple and cost-effective and can potentially be developed into a portable system, making it useful for field analysis of various liquid samples. Full article

The capability to discriminate among nuclear fuel properties is essential for a successful nuclear safeguard and security program. Accurate nuclear material identification is hindered due to challenges such as differing levels of enrichments, weak radiation signals in the case of fresh nuclear fuel, and complex self-shielding effects. This study explores the application of supervised machine learning algorithms to digitized radiation detector data for classifying signatures of special nuclear materials. Three scintillation detectors, an EJ-309 liquid scintillator, a CLYC crystal scintillator, and an EJ-276 plastic scintillator, were used to measure gamma-ray and neutron data from special nuclear material at the National Criticality Experiments Research Center (NCERC) at the National Nuclear Security Site (NNSS), at Nevada, USA. Radiation detector pulse data was extracted from the collected digitized data and applied to three separate supervised learning models: Random Forest, XGBoost, and a feedforward Deep Neural Network, chosen for their wide-spread use and distinct data ingest and processing analytics. Through model refinement, such as adding an additional parameter feature, an accuracy of greater than 95% was achieved. Analysis on model parameter feature importance revealed Countrate, which is the overall gamma-ray and neutron incidents for each detector, was the most influential parameter and essential to include for improved classification. Initial model versions not including the Countrate parameter feature failed to classify. Supervised learning models allow for measured gamma-ray and neutron pulse data to be used to develop effective identification and discrimination between material compositions of different fuel assemblies. The study demonstrated that traditional pulse shape parameters alone were insufficient for discriminating between special nuclear materials; the addition of Countrate markedly improved model accuracy but all models were heavily dependent on this specific feature, thus illustrating the need for alternative, more distinct parameter features. The machine learning development framework captured in this study will be beneficial for future applications in discriminating between different fuel enrichments and additives such as burnable poisons. Full article

In response to the need for precise blossom identification and optimization of key operational parameters in intelligent cherry spraying pollination, the SMD-YOLO (You Only Look Once with spatial and channel reconstruction convolution, multi-scale channel attention, and dual convolution modules) cherry blossom detection model is proposed, along with a pollination experiment platform for parameter optimization. The SMD-YOLO model, built upon YOLOv11, enhances feature extraction through the ScConvC3k2 (spatial and channel reconstruction convolution C3k2) module, incorporates the MSCA (multi-scale channel attention) attention mechanism, and employs the DualConv module for a lightweight design, ensuring both detection accuracy and operational efficiency. Tested on a self-constructed cherry blossom dataset, the model delivered a precision of 87.6%, a recall rate of 86.1%, and an mAP (mean average precision) reaching 93.1% with a compact size of 4765 KB, 2.28 × 10⁶ parameters, a computational cost of 5.8 G, and a detection speed of 75.76 FPS, demonstrating strong practicality and potential for embedded real-time detection in edge devices, such as cherry pollination robots. To further enhance pollination effectiveness, a dedicated pollination experiment bench was designed, and a second-order orthogonal rotational combination experiment method was employed to systematically optimize three key parameters: spraying distance, spraying time, and liquid flow rate. Experimental results indicate that the optimal pollination effect occurs when the spraying distance is 3.4 cm, spraying time is 1.9 s, and liquid flow rate is 339 mL/min, with a deposition amount of 0.18 g and a coverage rate of 97.25%. This study provides a high-precision image detection algorithm and operational parameter optimization basis for intelligent and precise cherry blossom pollination. Full article

With increasing interest in natural therapeutic strategies for skin aging, plant-derived compounds have gained attention for their potential to protect against oxidative stress and inflammation. In this study, we investigated the anti-aging and anti-inflammatory effects of flavonoids isolated from Cercidiphyllum japonicum using a tumor necrosis factor-alpha (TNF-α)-stimulated normal human dermal fibroblast (NHDF) model. The aerial parts of C. japonicum were extracted and analyzed by high-performance liquid chromatography (HPLC), leading to the identification of four major compounds: maltol, chlorogenic acid, ellagic acid, and quercitrin. Each compound was evaluated for its antioxidant and anti-aging activities in TNF-α-stimulated NHDFs. Among them, ellagic acid exhibited the most potent biological activity and was selected for further mechanistic analysis. Ellagic acid significantly suppressed intracellular reactive oxygen species (ROS) generation and matrix metalloproteinase-1 (MMP-1) secretion (both p < 0.001), while markedly increasing type I procollagen production (p < 0.01). Mechanistic studies demonstrated that ellagic acid inhibited TNF-α-induced phosphorylation of mitogen-activated protein kinases (MAPKs), downregulated cyclooxygenase-2 (COX-2), and upregulated heme oxygenase-1 (HO-1), a key antioxidant enzyme. Additionally, ellagic acid attenuated the mRNA expression of inflammatory cytokines, including interleukin-6 (IL-6) and interleukin-8 (IL-8), indicating its broad modulatory effects on oxidative and inflammatory pathways. Collectively, these findings suggest that ellagic acid is a promising plant-derived bioactive compound with strong antioxidant and anti-inflammatory properties, offering potential as a therapeutic agent for the prevention and treatment of skin aging. Full article

The sustainable recovery of valuable metals such as Cu and Co from ores is a pressing need considering environmental and economic challenges. Therefore, this study evaluates the effectiveness of deep eutectic solvents (DESs) as alternative leaching agents for Cu and Co extraction. Four DESs were prepared using choline chloride (ChCl) as a hydrogen bond acceptor (HBA) and oxalic acid (OA), ethylene glycol (EG), urea (U) and thiourea (TU) as hydrogen bond donors (HBDs). Leaching experiments were conducted with DESs supplemented with 30 wt.% water at varying temperatures, various solid-to-liquid ratios, and time durations. The ChCl:OA DES demonstrated the highest leaching efficiencies among the DESs tested on pure CuO and CoO, achieving 89.2% for Cu and 92.4% for Co (60 °C, 400 rpm, 6 h, −75 + 53 µm particle size, and 1:10 solid-to-liquid ratio). In addition, the dissolution kinetics, analysed using the shrinking core model (SCM), showed that the leaching process was mainly controlled by surface chemical reactions. The activation energy values for Cu and Co leaching were 46.8 kJ mol⁻¹ and 51.4 kJ mol⁻¹, respectively, supporting a surface chemical control mechanism. The results highlight the potential of ChCl:OA as a sustainable alternative for metal recovery. Full article

Multistage centrifugal pumps, owing to their high head characteristics, are commonly applied in domains like subsea resource exploitation and groundwater extraction. However, the wear of flow passage components caused by solid particles in the fluid severely threatens equipment lifespan and system safety. To investigate the influence of solid-liquid two-phase flow on pump performance and wear, this study conducted numerical simulations of the solid-liquid two-phase flow within multistage centrifugal pumps based on the Euler–Lagrange approach and the Tabakoff wear model. The simulation results showed good agreement with experimental data. Under the design operating condition, compared to the clear water condition, the efficiency under the solid-liquid two-phase flow condition decreased by 1.64%, and the head coefficient decreased by 0.13. As the flow rate increases, particle momentum increases, the particle Stokes number increases, inertial forces are enhanced, and the coupling effect with the fluid weakens, leading to an increased impact intensity on flow passage components. This results in a gradual increase in the wear area of the impeller front shroud, back shroud, pressure side, and the peripheral casing. Under the same flow rate condition, when particles enter the pump chamber of a subsequent stage from a preceding stage, the fluid, after being rectified by the return guide vane, exhibits a more uniform flow pattern and reduced turbulence intensity. The particle Stokes number in the subsequent stage is smaller than that in the preceding stage, weakening inertial effects and enhancing the coupling effect with the fluid. This leads to a reduced impact intensity on flow passage components, resulting in a smaller wear area of these components in the subsequent stage compared to the preceding stage. This research offers critical theoretical foundations and practical guidelines for developing wear-resistant multistage centrifugal pumps in solid-liquid two-phase flow applications, with direct implications for extending service life and optimizing hydraulic performance. Full article

Mauritia flexuosa, commonly known as “canangucha,” holds significant nutritional and economic value in the Amazon region. While its pulp is widely utilized in local food products, the seed or kernel is largely underutilized. This study investigated the proximal and phytochemical composition of M. flexuosa, alongside its biological properties, specifically focusing on the hypoglycemic activity of an ethanolic extract from M. flexuosa seeds (MFSs). Proximal analysis revealed that MFSs are a notable source of crude fiber (28.4%) and a moderate source of protein (9.1%). Phytochemical screening indicated a high total polyphenol content (123.4 mg gallic acid equivalents/100 mg dry weight) and substantial antiradical capacity against the ABTS radical (IC₅₀ = 171.86 µg/mL). Notably, MFS ethanolic extracts exhibited significant in vitro antihyperglycemic activity via inhibiting α-amylase and α-glucosidase enzymes, demonstrating comparable inhibition to acarbose at higher concentrations. This hypoglycemic effect was further corroborated in an in vivo rat model with induced diabetes, where the administration of 100 mg/kg of MFS ethanolic extract significantly reduced blood glucose levels compared to the diabetic control group (p < 0.05). A moderate antihypertensive effect was observed at a concentration of 150 mg/kg, correlating with ACE inhibition. High-performance liquid chromatography–mass spectrometry (UHPLC-ESI-HRMS) analysis of the seed extract identified phenolic compounds including ellagic, p-coumaric, and chlorogenic acids, as well as flavonoids such as quercetin, myricetin, and epicatechin. This study provides the first evidence of the hypoglycemic activity of MFSs, offering valuable insights into their phytochemistry and potential therapeutic applications. Full article

Separating azeotropes is an important, difficult, and expensive task, in particular for the 2-propanol–water mixture. The literature on the problem is rich in modeling studies but often lacking even the simplest experimental confirmation. In this paper, extractive distillation, liquid–liquid equilibrium-based extraction, and salting-out were experimentally tested for the desired separation. Among the four tested extractive distillation entrainers, none was able—in the investigated experimental setup—to push the system over the azeotropic composition threshold. Four novel hydrophobic deep eutectic extraction media were tested for the desired separation, and those based on menthol or thymol with decanoic acid were found most promising. Among 16 tested salting-out agents, 5 of them produced two-liquid phases, and only 4 hydrophilic inorganic salts promoted 2-propanol separation, with sodium carbonate being the most promising candidate. The purity of the products was tested with FTIR and ¹H-NMR. The experimental findings were compared with COSMO-RS model predictions, with moderate success. Full article

Pteridium aquilinum (bracken fern) poses a global threat to biodiversity and to the health of both animals and humans due to its toxic metabolites and aggressive ecological expansion. In northern Spain, particularly in regions of intensive livestock farming, these risks may be exacerbated, calling for urgent assessment and monitoring strategies. In this study, we implemented a multidisciplinary approach to evaluate the toxicological and ecological relevance of P. aquilinum through four key actions: (a) quantification of pterosins A and B in young fronds (croziers) using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS); (b) analysis of in vivo genotoxicity of aqueous extracts using Drosophila melanogaster as a model organism; (c) a large-scale survey of local livestock farmers to assess awareness and perceived impact of bracken; and (d) the development and field application of a drone-based mapping tool to assess the spatial distribution of the species at the regional level. Our results confirm the consistent presence of pterosins A and B in croziers, with concentrations ranging from 0.17 to 2.20 mg/g dry weight for PtrB and 13.39 to 257 µg/g for PtrA. Both metabolite concentrations and genotoxicity levels were found to correlate with latitude and, importantly, with each other. All tested samples exhibited genotoxic activity, with notable differences among them. The farmer survey (n = 212) revealed that only 50% of respondents were aware of the toxic risks posed by bracken, indicating a need for targeted outreach. The drone-assisted mapping approach proved to be a promising tool for identifying bracken-dominated areas and provides a scalable foundation for future ecological monitoring and land management strategies. Altogether, our findings emphasize that P. aquilinum is not merely a local concern but a globally relevant toxic species whose monitoring and control demand coordinated scientific and policy-based efforts. Full article