Search Results (571)

Yellow onion (Allium cepa L.) outer skins are a high-volume agricultural waste that can be converted into commercially valuable bioproducts using various extraction techniques. This research focused on optimizing a green ultrasound-assisted extraction (UAE) method which allows for the isolation of several phytochemicals valued for their health benefits, such as polyphenols and flavonoids. HPLC/UV analysis of the extracts showed that the main component was quercetin. A one-factor-at-a-time (OFAT) design was used to identify the extraction parameters needed in order to maximize the amount of extracted target phytochemicals. The polyphenols, flavonoids and quercetin contents, along with the antioxidant activity of the extracts, were optimized by response surface methodology using a Box–Behnken design. Ultrasound amplitude, ethanol concentration, and time were selected as the most appropriate variables. The final results showed that TPC ranged from 78.16 to 97.16 mg GAE/g DM, TFC ranged from 22.77 to 26.46 mg QE/g DM, while CUPRAC values varied between 145.24 and 163.75 mg TE/g DM. The optimal extraction conditions were determined using a Box–Behnken model as 30% ultrasound amplitude, 53% ethanol concentration, and an extraction time of 13 min. The use of these conditions allowed the TPC, TFC and CUPRAC to show predicted values of 97.8 mg GAE/g DM, 27.2 mg QE/g DM, and 159.8 mg TE/g DM, respectively. These findings indicate that onion skin extracts could represent a green and promising source of antioxidant phytochemicals. Full article

Spent coffee grounds (SCGs), a major by-product of coffee consumption, remain an underused source of chlorogenic acid (CGA) and other phenolic constituents. This study investigated an ultrasound-assisted extraction strategy using deep eutectic solvents (DESs) to improve the recovery and phenolic-acid enrichment of SCGs. Among the tested DES formulations, the betaine–acetic acid system gave the best CGA extraction performance and was therefore used for further optimization by response surface methodology. The optimized process, conducted at a liquid-to-solid ratio of 28 mL/g, 75 °C, and 50 min, produced a CGA yield of 15.18 mg CGA/g dried SCG powder, markedly exceeding that achieved with 70% ethanol under comparable conditions. Structural and chemical characterizations helped explain this improvement. Scanning electron microscopy revealed that the DES-based process caused more evident disruption of the SCG matrix, which favored solvent penetration and mass transfer. Fourier-transform infrared spectroscopy confirmed the formation of a hydrogen-bonding network between betaine and acetic acid. Ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry further revealed that the betaine–acetic acid extract was mainly composed of CGA and hydroxycinnamic acid derivatives. The purified extract also displayed strong in vitro antioxidant capacity. Overall, the betaine–acetic acid DES combined with ultrasound provides an effective green approach for recovering CGA-rich phenolic extracts from SCGs. Full article

Benzophenones (BPs) and derivatives are endocrine-disrupting chemicals (EDCs) widely used in personal care products, food packaging, and flavoring ingredients. This systematic review and bibliometric analysis aimed to identify and summarize analytical methods used to determine BPs in human milk and infant formulas. Furthermore, the bibliometric evaluation explored publication trends by journal, citation count, and geographical distribution, providing insight into the global research landscape on this topic. The most employed sample preparation techniques included liquid–liquid extraction, solid-phase extraction, dispersive solid-phase extraction, low-temperature partitioning, QuEChERS, and dispersive liquid–liquid microextraction, frequently combined with enzymatic treatments with β-glucuronidase or arylsulfatase to improve recovery and sensitivity. Gas chromatography (GC) and liquid chromatography (LC) coupled with mass spectrometry (MS) were the predominant analytical platforms, with LC–MS being the most used for its ability to detect BPs without derivatization. Recent studies have shown a trend of replacing conventional organic solvents with greener, sustainable, and environmentally friendly approaches, such as miniaturized methods. This trend aligns with Green Analytical Chemistry principles and highlights the need for ongoing methodological and regulatory advancements to ensure food safety and protect public health. Full article

To promote green chemistry and improve the utilization of plant resources, flavonoids from Dalbergia pinnata (Lour.) Prain were extracted in this study by combining NADES (natural deep eutectic solvents) with UAE (ultrasound-assisted extraction). Among the 13 synthesized NADES, choline chloride (ChCl)–urea (NADES-13) exhibited the highest extraction rate, outperforming traditional organic solvents. The optimal conditions determined by response surface methodology (RSM) were as follows: ChCl–urea molar ratio of 1:3, moisture content of 60%, liquid-to-material ratio of 28.5 mL/g, ultrasonic extraction time of 49 min, and temperature of 62 °C. Under these conditions, the extraction rate reached 117.95 ± 5.97 mg/g, a 73.5% improvement compared with 80% EtOH extraction. The comparison of the two algorithms showed that RSM (R = 0.9981, RMSE = 0.6570) had better fitting accuracy and prediction stability under small sample conditions than MLP (R = 0.9427, RMSE = 5.261) and RF (R = 0.9431, RMSE = 5.2442). DFT (density functional theory) analysis demonstrated that hydrogen bonds, Van der Waals forces, and cation–π interactions mediate the interaction between NADES-13 and flavonoids. Ultrasonic cavitation-induced cell wall damage and the hydrogen-bond network of NADES-13 were confirmed separately by SEM (scanning electron microscopy) and FTIR (Fourier transform infrared spectroscopy). In vitro experiments showed that the extract possessed concentration-dependent antioxidant activity and strong antibacterial activity, with an inhibition rate of 96.87 ± 5.09% against Escherichia coli at a concentration of 0.04 mg/mL. In this study, a “Smart Optimization–Molecular Mechanism–Activity Verification” green extraction system was developed, which offers an efficient and environmentally friendly strategy for extracting plant bioactive components and contributes to the progress of green chemistry. Full article

Habanero pepper leaf, annually discarded as a by-product, is a source of phenolic compounds with functional activity. However, their recovery requires sustainable strategies that overcome the limitations of conventional organic solvents and low extraction yields. In this study, a sustainable and adjustable approach for phenolic compound recovery was developed using natural deep eutectic solvents (NADES) combined with ultrasound-assisted extraction and optimized by response surface methodology. Initially, different hydrogen bond donors (HBDs) like glycerol, glucose, and fructose (Fru), molar ratios (MR) of choline chloride (ChCl):HBD (1:1 mol/mol–1:2 mol/mol), and added water (Aw, 50–70%) were evaluated. The ChCl:Fru system (1:1 mol/mol, 70% Aw) was identified as the most efficient, showing the highest total polyphenol content (TPC) and antioxidant capacity (Ax). Simultaneous optimization yielded 147.30 ± 2.71 mg gallic acid equivalent/100 g dry leaf (DL) and 93.00 ± 0.14% Ax (predictive capacity, error < 5%). UPLC analysis identified protocatechuic acid (1285.98 ± 2.83 mg/100 g DL) and catechin (131.82 ± 0.99 mg/100 g DL) as the major compounds during the optimization process with Fru. These results position NADES as a sustainable tool for habanero pepper leaf valorization and targeted phenolic recovery, while designing greener extraction processes for agro-industrial residues. Full article

Background/Objectives: From a phenomenological perspective, the body is not merely a biological entity but the primary medium through which we experience and interpret the world. This study aimed to understand the lived body experience of advanced physiotherapy students at a university in Cali, Colombia, exploring how significant life events are embodied and expressed. Methods: A qualitative phenomenological design was employed. Twenty physiotherapy students participated in a body mapping exercise within a mental health elective. Participants graphically represented sensations, emotions, and memories on a body silhouette using colors and symbols. Data from the resulting body maps were analyzed using a thematic analysis approach via a data extraction matrix to identify patterns in symbolic, chromatic, and narrative elements. Results: The analysis revealed that students consistently inscribe both traumatic and positive life events onto their body maps, illustrating a narrative of resilience. Specific colors and body parts were symbolically charged: black and red in the heart, head, and shoulders represented pain and emotional burden, while blue and green in areas like the hands and stomach signified stability and achievement. External symbols (e.g., landscapes, bicycles) served as emotional anchors or representations of personal growth. Conclusions: Body mapping proves to be a powerful technique for accessing the embodied, often non-verbal, narratives of students. It underscores that the body functions as a living archive of experience. Integrating such methodologies into physiotherapy education can significantly enrich professional training by fostering sensitivity to corporality as a lived, relational, and cultural phenomenon, thereby strengthening future clinicians’ holistic and humanistic competencies. Full article

The 2024 World Heritage inscription of the Beijing Central Axis shifts the focus of historic district governance to quality-oriented urban regeneration. However, evaluating the precise alignment between infrastructural topology and cultural meaning remains a methodological challenge. To move beyond macro-level assumptions, this study constructs a novel “spatial–semantic coupling” diagnostic framework. Integrating multi-source street-view data, Space Syntax, and the zero-shot semantic extraction capabilities of the CLIP model, we performed high-resolution visual semantic identification across 550 fine-grained sampling points in the 6.6 km² South Central Axis Core Area. Rather than merely observing a general “decoupling,” our diagnostic tool successfully mapped the complex spectrum of spatial alignments. While it accurately diagnosed areas with “idle spatial potential”—where high Global Integration (Mean = 0.924) fails to translate into Visual Attraction (r = −0.03) or Historical Perception (r = 0.01)—it also precisely identified “Synergistic” heritage cores and “hidden gems” within capillary hutongs. Furthermore, the framework diagnosed a severe “green island” effect (Mean = 0.26) and a structural contradiction between Spaciousness and Historical Perception (r = −0.33). By utilizing Bivariate LISA to geographically pinpoint these varying coupling characteristics (e.g., severe “High–Low” spatial frictions at gateway transportation hubs), this study establishes a highly scalable, data-driven analytical paradigm for targeted micro-renewal, ensuring the precise alignment of physical centrality and cultural perception in complex historic districts globally. Full article

Artichoke by-products (ABP) represent valuable sources of bioactive compounds with relevant health benefits. In this study, a green extraction strategy based on pressurized liquid extraction (PLE) was optimized to enhance the recovery of phenolic and flavonoid compounds from ABP using a response surface methodology. Extraction temperature and solvent composition were identified as the key factors driving extraction performance. Optimal conditions using a mixture of ethyl acetate and ethanol (90/10, v/v) at 180 °C significantly enhanced extraction yield, total phenolic and flavonoid content, and antioxidant activities, as measured by ORAC and DPPH assays. Chemical characterization via HPLC-C18-Q-TOF-MS/MS revealed a diverse profile of phenolic and flavonoid compounds, including caffeoylquinic acid derivatives and related transformation products. The neuroprotective potential of the optimized extract was further evaluated through in vitro inhibition assays targeting acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and lipoxygenase (LOX), alongside a permeability assessment using an in vitro blood–brain barrier (BBB) model. Molecular docking simulations were performed to explore the interactions of apigenin—the most representative flavonoid in the optimal extract—with the three target enzymes. Overall, these findings support the valorization of ABP as a source of bioactive compounds and highlight the potential of PLE as an efficient and sustainable extraction approach. Full article

In the context of green energy, the use of lake reeds is becoming an increasingly important factor. Therefore, research into the availability of reeds, determining their area in lakes, predicting the potential biomass volume and calculating the carbon footprint are important. Currently, there have been no significant research results on the availability of reeds and the assessment of the sustainability of reed products in Latvia. However, these aspects are crucial for the development of reed products, as they help to assess their market potential and environmental impact. The main goal of this work is to develop a method for modeling the distribution of lake reeds in order to predict their availability in the future, which would allow assessment of the volume of biomass and its impact on the environment. This research develops an integrated GIS–LCA framework that combines Sentinel-2 satellite data, machine learning-based classification, biomass estimation, and carbon footprint modeling. Using Lake Cirma as a case study, the classification results show that reed stands occupy 2.18–3.51 percent of the lake area in certain years, corresponding to approximately 1158–1861 tons of biomass. The framework enables quantification of harvesting potential while considering ecological constraints that limit annual extraction to approximately 50% of total biomass. The proposed GIS–LCA framework provides a replicable methodology for assessing reed biomass availability and environmental performance across lake ecosystems. It supports evidence-based decision-making for sustainable reed resource management and contributes to the development of low-carbon bioeconomy pathways in line with EU climate and bioeconomy strategies. Full article

Corrosion continues to be a major concern in industrial systems, causing material degradation and raising maintenance costs. In recent years, plant-derived corrosion inhibitors have gained interest as environmentally friendly alternatives to conventional chemical treatments. In this work, ethanolic extracts from the leaves of Citrus limon (L.) Osbeck and Eucalyptus globulus Labill. were evaluated as green corrosion inhibitors for C45 carbon steel in 1 M HCl solution. The extracts were prepared by continuous Soxhlet extraction and characterized through antioxidant activity measurements using the 2,2-diphenyl-1-picrylhydrazyl DPPH radical scavenging method, gravimetric (weight loss) tests, and electrochemical techniques including potentiodynamic polarization. In addition, the extraction parameters were optimized using a face-centered central composite design (CCD) within a response surface methodology (RSM) framework, and the resulting models were analyzed by analysis of variance (ANOVA). The effects of inhibitor concentration and temperature on corrosion inhibition performance were systematically examined. The antioxidant assay indicated that E. globulus extract reached a scavenging activity above 95% at 1000 mg/L, while C. limon extract showed moderate activity around 71%. Gravimetric tests revealed that both extracts reduced the corrosion rate, with optimal inhibition efficiencies of approximately 67% for C. limon (at 0.3 g/100 mL) and 82% for E. globulus (at 1.0 g/100 mL). Beyond these optimal concentrations, a decline in performance was observed, suggesting surface saturation. The statistical optimization showed that the C. limon response model was solvent-driven (R² = 92.05%), whereas the E. globulus model was curvature-driven (R² = 95.45%), with contrasting response surface topographies. Electrochemical measurements confirmed that both extracts acted as mixed-type inhibitors, shifting the corrosion potential toward less negative values and reducing the corrosion current density. Overall, E. globulus extract demonstrated superior performance across all methods, and both extracts represent promising candidates for sustainable corrosion protection in acidic industrial environments. Full article

Astrocaryum murumuru Mart., an Amazonian oilseed widely used for cosmetic oil production, generates large amounts of residual biomass that remains underexplored. In this study, ultrasound-assisted extraction (UAE) with ethanol as a green solvent was optimized using a Central Composite Rotational Design (CCRD) with 2 levels (2³) and 3 independent variables. The optimal condition (60 % ethanol, solid–liquid ratio 2.5 % m/v, 26 min) was determined using response surface methodology (RSM), and yielded 9.92 mg GAE/g of total phenolic content (TPC), with an experimental error of 5.34 % compared to the theoretical model prediction. Under this condition, total flavonoids and tannins were also quantified, reaching 0.38 ± 0.01 mg QE/g and 4.03 ± 0.10 mg TA/g, respectively. LC-MS analysis revealed a complex phenolic profile within the extract, confirming the efficiency of UAE in recovering bioactive molecules. Biological assays revealed significant functional properties. Antioxidant activity, evaluated by ABTS and DPPH methods, indicated that the extracts were effective radical scavengers. Antimicrobial assays showed only growth-selective inhibition against Staphylococcus aureus at concentrations of 2.5–20 mg/mL, while no significant activity was observed against Escherichia coli and Pseudomonas spp. These findings highlight the potential of A. murumuru biomass residues as a sustainable source of bioactive compounds with antioxidant activity and a growth inhibitor of S. aureus, reinforcing their possible application in the development of natural additives for food, while contributing to the sustainable bioeconomy of the Amazon. Full article

This study presents an integrated approach for producing antioxidant-rich polar fractions from Inula salicina L. via pressurised ethanol/water extraction (PLE-EtOH/H₂O), optimised by coupling a central composite design and response surface methodology (CCD-RSM) with Aspen Plus^® simulation. The effects of PLE temperature, extraction time, and EtOH/H₂O ratio for yield, total phenolic (TPC) and flavonoid (TFC) content, and Trolox equivalent antioxidant capacity (TEAC) measured in ABTS^•+-scavenging, cupric ion reducing antioxidant (CUPRAC) and oxygen radical absorbance (ORAC) assays were assessed via a multi-response optimisation approach. Optimal conditions were set at 82 °C, 27 min, and 60% EtOH (v/v), yielding ~29 g extract per 100 g plant material, characterised by high TPC (227 mg GAE/g), TFC (34 mg QE/g), and TEAC values in the CUPRAC (1473 mg TE/g), ABTS (869 mg TE/g), and ORAC assays (1165 mg TE/g). The TPC and TEAC values of the post-extraction residue were >92% lower than those of unextracted I. salicina, confirming efficient recovery of the major portion of antioxidant-active constituents by PLE-EtOH/H₂O. The high in vitro radical scavenging capacity, reducing power, and photoprotective potential (sun protection factor ~50 at 0.5 mg/mL) of the I. salicina extract are consistent with its phenolic-rich composition, with chlorogenic acid (~97 mg/g extract) and its derivatives being the major constituents. The validated Aspen Plus^® model closely aligned with the CCD-RSM predictions, supporting process scale-up and energy feasibility and demonstrating an industry-relevant, green-solvent PLE process for producing higher value-added I. salicina fractions with potential applications in the food, pharmaceutical, nutraceutical, and cosmetic sectors. Full article

Artificial intelligence presents a critical paradox for clean technology: while enabling unprecedented environmental optimization, AI deployment demands massive resource inputs that threaten to offset benefits. As global AI infrastructure investment approaches $500 billion annually, data center electricity consumption is projected to exceed 1000 TWh by 2030. We conducted a systematic literature review of 73 peer-reviewed empirical studies (2021–2025) to develop an Environmental Asset-Cost Framework categorizing AI’s impacts across five asset categories (energy optimization, production enhancement, green innovation, resource conservation, precision applications) and five cost categories (energy consumption, water use, e-waste, infrastructure, supply chain extraction). Our analysis reveals three critical insights: First, AI’s environmental impact follows a synthesized S-curve heuristic—a pattern derived from convergent but methodologically diverse evidence strands—characterized by initial emission reductions (0–2 years), mid-term rebound effects (2–5 years), and conditionally projected long-term optimization (5+ years). Second, geographical context creates 10–60× variation in outcomes; regions with high renewable electricity and water abundance achieve net benefits within 2–3 years, while fossil fuel-heavy, water-stressed regions may never reach net positive outcomes. Third, the rebound effect is predictable and manageable through strategic interventions. Our framework provides actionable deployment guidance, demonstrating that achieving AI’s net environmental benefits requires renewable energy infrastructure development before AI deployment, alternative cooling technologies, and policy frameworks incorporating temporal dynamics. Full article

Natural product research has experienced substantial growth over the past two decades, driven by a renewed appreciation for the structural complexity and biological relevance of compounds derived from nature. Technological advances in separation science, spectroscopic characterization, and high-sensitivity bioassays have collectively restored natural products to a position of prominence in modern drug discovery efforts. Nature remains the most prolific source of bioactive molecular diversity, drawing from microorganisms, plants, and marine life to offer a vast reservoir of structurally novel scaffolds whose pharmacological potential remains largely unexplored. Effective extraction and isolation remain foundational to natural product research, as the quality and purity of isolated compounds directly govern the reliability of downstream biological evaluation. Recent years have witnessed remarkable innovation in this space, spanning green and designer solvent systems, pressurized and ultrasound-assisted extraction platforms, supercritical fluid techniques, and integrated purification workflows that dramatically reduce processing time while improving compound recovery and analytical throughput. Particularly noteworthy is the growing application of artificial intelligence and machine learning tools for solvent selection, extraction optimization, and metabolite dereplication, which in combination with advanced phase-separation strategies and informatic platforms have substantially expanded the scope of detectable and characterizable metabolites within complex biological matrices. This review summarizes recent progress in extraction and isolation methodologies supporting natural product research, with particular emphasis on combinatorial extraction strategies, next-generation solvent systems, and AI-driven applications that have collectively improved operational efficiency, selectivity, and analytical output over the past five years. Full article

Low extraction efficiency limits the availability and application of aescins, which exhibit various pharmacological activities. Here, we optimized parameters for ultrasound-assisted extraction of aescins from Aesculus chinensis seeds using deep eutectic solvent (DES)-water mixtures. Seven DES formulations were screened, and one providing the highest yield was selected for optimizing the molar ratio. The effects of four parameters were investigated using single-factor experiments combined with response surface methodology. The optimal extraction conditions were as follows: DES, a 1:1 mixture of 1,3-butanediol and lactic acid, with 42.5% water, used at a liquid-solid ratio of 25 mL/g; ultrasonic frequency, 40 kHz; extraction temperature, 70 °C; and extraction time, 27.5 min. The extraction yield under these conditions was significantly higher than that obtained via traditional methods. Aescin was purified from the DES extract using macroporous resin. AB-8 resin was most efficient in adsorbing aescin in static adsorption tests. Based on dynamic adsorption experiments, optimal separation, with a 100% recovery rate, was achieved by passing four bed volume (BV) of extract through AB-8 column, removing impurities with two BV of deionized water and four BV of 30% ethanol, and eluting with four BV of 60% ethanol at 5–10 mL/min. This green method should be suitable for large-scale applications. Full article