Search Results (5,924)

Background/Objectives: Sentinel lymph node biopsy (SLNB) is currently the standard approach for axillary staging in breast cancer. Conventional techniques are radioisotope-based (Technetium-99m, Tc99m) and remain widely used, but novel tracers like Indocyanine Green (ICG) fluorescence provide potential advantages regarding feasibility and logistics. Methods: We conducted a prospective, observational study including 476 female patients diagnosed with primary invasive breast cancer who underwent SLNB at the Institute of Oncology “Prof. Dr. I. Chiricuță”, Cluj-Napoca, Romania, between January 2022 and May 2025. Clinical, surgical, and pathological variables were systematically extracted. SLNB was performed using either Tc99m or ICG, according to institutional protocols. Comparative analyses were performed to evaluate sentinel node characteristics, histopathological parameters, and positive surgical margins predictors. Results: The median age was 60 years (IQR: 52–69). Breast-conserving surgery (BCS) was performed in 77.9% of cases, while mastectomy was performed in 22.1%. Sentinel lymph node positivity was reported in 25.6% of cases, with no significant differences in the number of excised or metastatic nodes between Tc99m and ICG (mean nodes: 3.23 vs. 3.20, p = 0.860; mean positive nodes: 0.35 vs. 0.36, p = 0.897). Histologically, invasive carcinoma NST was predominant (90.1%), and surgical margins were negative in 96.8% of patients, with all margin-positive cases occurring following BCS. No pathological markers (grade, Ki67, TILs, DCIS extent) predicted margin status or nodal involvement. Notably, younger age correlated inversely with the extent of ductal carcinoma in situ (r = −0.21, p < 0.00001). Conclusions: Tc99m and ICG provided comparable diagnostic performance in performing SLNB, with equivalent rates of nodal detection and pathological yield. These findings support that ICG is a safe and effective alternative for routine axillary staging in breast cancer. Full article

Artisanal and Small-Scale Gold Mining (ASGM) is a primary source of global mercury pollution, creating an urgent need for sustainable, low-cost alternatives to amalgamation. This study investigates the use of cassava wastewater (manipueira), a cyanogenic agricultural byproduct, as a lixiviant for a gold concentrate (14.30–15.87 ppm Au) from an artisanal mine. Two approaches were evaluated: direct leaching with manipueira in natura (250 ppm CN⁻) in single and double 8 h and 12 h cycles, and leaching with a cyanide solution concentrated from dilute manipueira (100 ppm CN⁻) via a simplified air-stripping system. Results were benchmarked against the mine’s amalgamation (44.7% recovery) and 30-day heap leach (75.8% recovery) processes. The most effective method observed was a two-cycle, 8 h leach with manipueira in natura, which achieved a mean gold recovery of $76.75\pm 4.71\%$. This result is comparable to the efficiency of the site’s lengthy heap leach process and suggests a promising, faster, route to eliminating mercury use. Longer (12 h) leaching cycles yielded lower recoveries, suggesting process limitations such as preg-robbing. The cyanide concentration method proved inefficient, recovering a maximum of 12.40% of the available cyanide and resulting in a weaker lixiviant. The findings demonstrate that while direct leaching is a viable alternative to mercury, the inherent instability of manipueira necessitates a focus on developing efficient, controlled systems to extract and concentrate its cyanide content, thereby creating a standardized “green” reagent from a large-volume agricultural waste stream. Full article

Urban streetscapes are among the most frequently encountered spatial environments in daily life, and their restorative visual features have a significant impact on well-being. Although existing studies have revealed the relationship between streetscape environments and perceived restorativeness, there remains a lack of scalable, data-driven methods for quantifying such perception at the street level. This study proposes an interpretable and replicable framework for predicting streetscape restorativeness by integrating semantic segmentation, perceptual evaluation, and machine learning techniques. Taking Liwan District of Guangzhou as a case study, street-view images (SVIs) were collected and processed using the Mask2Former model to extract the following five key visual metrics: greenness, openness, enclosure, walkability, and imageability. Based on the Perceived Restorativeness Scale (PRS), an online questionnaire was designed from four dimensions (fascination, being away, compatibility, and extent) to score a random sample of images. A random forest model was then trained to predict the perceptual levels of the full dataset, followed by K-means clustering to identify spatial distribution patterns. The results revealed that there were significant differences in visual characteristics among high, medium, and low restorativeness street types. The proposed framework enables scalable, data-driven evaluation of perceived restorativeness across diverse urban streetscapes. By embedding perceptual metrics into large-scale urban analysis, the framework offers a replicable and efficient approach for identifying streets with low restorative potential—thus providing urban planners and policymakers with a novel tool for prioritizing street-level renewal, improving public well-being, and supporting perception-oriented urban design without the need for labor-intensive fieldwork. Full article

Borehole sealing materials have drawn significant research attention for their applications in mine disaster prevention, efficient utilization of coalbed methane resources and green mine construction. However, it is still an enormous challenge to simultaneously achieve sealing materials with lower material consumption, lower expense, and lower labor intensity for high-performance long-term borehole sealing. Meanwhile, drilling cuttings (DC) possess large production amounts, low granularity, a large workload for cleaning out the alley, high labor intensity, and high transportation cost. Herein, a composite with universal applicability to DC has been developed, which can be combined with different DC to produce a low-cost sealing material with adjustable strength, fulfilling the sealing requirements of various boreholes. The properties of the sealing material can be adjusted as required by regulating the water/cement ratio and DC content to meet the sealing requirements of different boreholes. Consequently, the DC-derived materials, featuring adjustable strengths and lower usage, can reduce cement usage, material costs, and labor intensity dramatically, displaying great promise in high-performance borehole sealing, coalbed methane extraction and utilization, timely mining waste reutilization, gas disaster prevention, and green mine construction. Full article

Edible and medicinal plants provide a treasure trove of natural phytochemicals for mining the next generation of green food preservatives. Herein, we evaluated antibacterial activities of 55–95% ethanol extracts from the edible rhizome of Rumex madaio (RmEEs). The 75% ethanol extract displayed the strongest antibacterial activity, and its purified fraction 2 (RmEE-F2) blocked the proliferation of common pathogens Staphylococcus aureus and Vibrio cholerae, with minimum inhibitory concentrations (MICs) of 391 μg/mL. RmEE-F2 (1 × MIC) altered the bacterial cell surface biophysical parameters and impaired cell structure, resulting in intracellular nucleic acid and protein leakage. It manifested bacteriostatic rates of 88.21–91.17% against S. aureus and V. cholerae in spiked fish (Carassius auratus) and shrimp (Penaeus vannamei) during storage at 4 °C for 24 h. Meanwhile, RmEE-F2 effectively rendered the pH rising and reduced lipid oxidation and protein degradation of C. auratus and P. vannamei meat samples at 4 °C for 6 days. Additionally, RmEE-F2 (< 781 µg/mL) showed non-cytotoxicity to human colon Caco-2, liver HepG-2, and lung A549 cell lines, and rescued V. cholerae and S. aureus-infected Caco-2 cellcells with enhanced viability of 14.31–16.60% (1 × MIC). Comparative transcriptomic analysis revealed down-regulated protein synthesis, cell wall and cell membrane synthesis, and or DNA replication and repair in the tested bacteria triggered by RmEE-F2. The major antibacterial compounds in RmEE-F2 included melibiose (9.86%), 3-(N, N-dimethylaminomethyl) indole (7.12%), and citric acid (6.07%). Overall, this study underscores the promising potential of RmEE-F2 for aquatic product green preservation. Full article

This study presents the development of antibacterial electrospun nanofibrous mats composed of keratin and polyethylene oxide, incorporating Echinacea purpurea L. (EchP) and green-synthesized silver nanoparticles (bioAgNPs) produced using EchP extract. The successful synthesis of bioAgNPs was confirmed by colorimetric analysis, FTIR, XRD, and TEM. In vitro assays demonstrated antibacterial activity against both Gram-positive and Gram-negative bacteria at ~0.6 µg/mL. Keratin, extracted from sheep wool, retained partial native structure, supporting biocompatibility and cellular regeneration. Incorporation of EchP or bioAgNPs reduced solution viscosity by 25–45%, significantly affecting mat morphology and shifting fiber diameters toward the 50–100 nm range. Quantitative phytochemical analysis, conducted via UV-Vis spectrophotometry, showed 2–3 times higher release of tannins and phenolic compounds compared to hydroxycinnamic acid derivatives and flavonoids. Keratin electrospun mats with bioAgNPs exhibited about 1.5-fold lower polyphenol release, confirming the dual role of polyphenols as electron donors in Ag⁺ bioreduction and as stabilizers. Full article

Volatile organic compounds (VOCs) are critical indicators of the metabolic status of whole-plant maize silage (WPMS). However, the impact of inoculating various strains of fermentation agents on VOC changes has not been systematically explored. This study aimed to determine how inoculation with Lactiplantibacillus plantarum and Lentilactobacillus buchneri modulates the VOC profile and odor of WPMS after 90 days. VOCs were extracted by headspace solid-phase microextraction and analyzed by gas chromatography-mass spectrometry (HS-SPME-GC-MS). Key VOCs were screened using the variable importance in projection (VIP) and substantiated by relative odor activity values (rOAV) and odor descriptions. A total of 82 compounds were identified, including 22 esters, 19 alcohols, 3 acids, 9 aldehydes, 2 ethers, 6 hydrocarbons, 4 ketones, 10 phenols, and 8 terpenoids. L. plantarum enhanced green/fruity odors while strain L. buchneri significantly reduced undesirable phenolic and aldehydic compounds. Six key VOCs influencing the odor of WPMS were selected: 4-ethyl-2-methoxyphenol and benzaldehyde, which contribute smoky, bacon, and bitter almond aromas, and (E)-3-hexen-1-ol, benzyl alcohol, (E, E)-2,4-heptadienal and methyl salicylate, which impart green, fruity, and nutty aromas. These findings highlight the effects and contributions of various strain additives on VOCs in WPMS, providing new theoretical insights for regulating the flavor profile of WPMS. Full article

This paper presents a novel hybrid and hierarchical architecture of a Convolutional Neural Network (CNN), based on MobileNetV2 and Support Vector Machines (SVM) for the classification of crop diseases (SVMobileNetV2). The system feeds from multispectral images captured by Unmanned Aerial Vehicles (UAVs) alongside data from IoT nodes. The primary objective is to improve classification performance in terms of both accuracy and precision. This is achieved by integrating contemporary Deep Learning techniques, specifically different CNN models, a prevalent type of artificial neural network composed of multiple interconnected layers, tailored for the analysis of agricultural imagery. The initial layers are responsible for identifying basic visual features such as edges and contours, while deeper layers progressively extract more abstract and complex patterns, enabling the recognition of intricate shapes. In this study, different datasets of tropical crop images, in this case banana crops, were constructed to evaluate the performance and accuracy of CNNs in detecting diseases in the crops, supported by transfer learning. For this, multispectral images are used to create false-color images to discriminate disease through spectra related to the blue, green and red colors in addition to red edge and near-infrared. Moreover, we used IoT nodes to include environmental data related to the temperature and humidity of the environment and the soil. Machine Learning models were evaluated and fine-tuned using standard evaluation metrics. For classification, we used fundamental metrics such as accuracy, precision, and the confusion matrix; in this study was obtained a performance of up to 86.5% using current deep learning models and up to 98.5% accuracy using the proposed hybrid and hierarchical architecture (SVMobileNetV2). This represents a new paradigm to significantly improve classification using the proposed hybrid CNN-SVM architecture and UAV-based multispectral images. Full article

The widespread presence of antibiotic residues, particularly norfloxacin (NFX), in food products and the environment has raised concern, underscoring the need for sensitive and selective detection methods. In this study, a novel broccoli-derived nitrogen-doped carbon quantum dots (N-CQDs) was synthesized via a green hydrothermal approach, 4-dimethylaminopyridine (DMAP) as both a nitrogen dopant and a functionalizing agent. The synthesized N-CQDs exhibit an average diameter of approximately ~4.2 nm and emit bright blue fluorescence, with a maximum emission at 445 nm upon excitation at 360 nm. A “Turn-ON” response toward NFX was achieved with a detection limit of 0.30 nM, attributed to hydrogen bonding and π–π stacking interactions that suppressed non-radiative decay. Moreover, the sensor demonstrates high selectivity for NFX, effectively distinguishing it from common interfering substances, including other antibiotics, organic acids, and biomolecules. The N-CQDs also exhibit excellent stability under diverse conditions, such as varying pH levels, high ionic strength, and prolonged irradiation. Finally, the practical applicability of the developed sensor was validated by detecting NFX in spiked broccoli extract and milk samples, with recovery rates ranging from 98.2% to 100.1% and relative standard deviations of less than 2.0%. This work presents a sustainable and efficient N-CQD-based fluorescent sensing platform, offering significant potential for rapid and reliable detection of NFX in food safety and environmental monitoring. Full article

In Northeast Brazil, climatic factors and technology synergistically enhance melon productivity and fruit quality. However, the region requires further research on the efficient use of water resources, particularly in determining the crop coefficient (Kc), which comprises the evaporation coefficient (Ke) and the transpiration coefficient (Kcb). Air temperature affects crop growth and development, altering the spectral response and the Kcb. However, the direct influence of air temperature on Kcb and spectral response remains underemphasized. This study employed unmanned aerial vehicle (UAV) with RGB and Red-Green-NIR sensors imagery to extract biophysical parameters for improved water management in melon cultivation in semiarid northern Bahia. Field experiments were conducted during two distinct periods: warm (October–December 2019) and cool (June–August 2020). The ‘Gladial’ and ‘Cantaloupe’ cultivars exhibited higher Kcb values during the warm season (2.753–3.450 and 3.087–3.856, respectively) and lower during the cool season (0.815–0.993 and 1.118–1.317). NDVI-based estimates of Kcb showed strong correlations with field data (r > 0.80), confirming its predictive potential. The results demonstrate that UAV-derived NDVI enables reliable estimation of melon Kcb across seasons, supporting its application for evapotranspiration modeling and precision irrigation in the Brazilian semiarid context. Full article

The synthesis of silver nanoparticles (AgNPs) using sustainable and non-toxic methods has become an important research focus due to the limitations of conventional chemical approaches, which often involve hazardous reagents and produce unstable products. In particular, the effects of reaction conditions on the quality and stability of AgNPs obtained via green synthesis remain insufficiently understood. This study addresses this gap by examining the influence of pH and temperature on the synthesis of AgNPs using Rosmarinus officinalis extract as both reducing and stabilizing agents. UV-vis spectroscopy and TEM analysis revealed that optimal conditions for producing uniform, stable, and spherical AgNPs were achieved at pH 8, with a narrow size distribution (~17.5 nm). At extreme pH values (≤3 or ≥13), nanoparticle formation was hindered by aggregation or precipitation, while elevated temperatures mainly accelerated reaction without altering particle morphology. HRTEM and SAED confirmed the crystalline face-centered cubic structure, and colloids synthesized at pH 8 showed excellent stability over 30 days. Overall, the results demonstrate that precise pH control is critical for obtaining high-quality AgNPs via a simple, scalable, and environmentally friendly approach. Their stability and homogeneous size highlight potential applications in biomedicine, food packaging, and sensing, where reproducibility and long-term functionality are essential. Full article

Chitin, one of the most abundant natural polysaccharides, has gained increasing attention for its structural diversity and potential in biomedicine, agriculture, food packaging, and advanced materials. Conventional chitin production from crustacean shell waste faces limitations, including seasonal availability, allergenic protein contamination, heavy metal residues, and environmentally harmful demineralization processes. Chitin from fungi and microalgae provides a sustainable and chemically versatile alternative. Fungal chitin, generally present in the α-polymorph, is embedded in a chitin–glucan–protein matrix that ensures high crystallinity, mechanical stability, and compatibility for biomedical applications. Microalgal β-chitin, particularly from diatoms, is secreted as high-aspect-ratio microrods and nanofibrils with parallel chain packing, providing enhanced reactivity and structural integrity that are highly attractive for functional materials. Recent progress in green extraction technologies, including enzymatic treatments, ionic liquids, and deep eutectic solvents, enables the recovery of chitin with reduced environmental burden while preserving its native morphology. By integrating sustainable sources with environmentally friendly processing methods, fungal and microalgal chitin offer unique structural polymorphs and tunable properties, positioning them as a promising alternative to crustacean-derived chitin. Full article

Macroalgal polysaccharides represent a diverse group of structurally complex biopolymers with significant potential in biomedicine and functional food applications. This review provides a comprehensive examination of their structural features, biological activities, and molecular targets, with an emphasis on precision applications. Key polysaccharides such as alginates, carrageenans, fucoidans, ulvans, and laminarans are highlighted, focusing on their unique chemical backbones, degrees of sulfation, and branching patterns that underlie their bioactivity. Special attention is given to their roles in modulating inflammation, oxidative stress, apoptosis, gut microbiota, and metabolic pathways. Comparative assessment of extraction strategies, structure–function relationships, and bioactivity data highlights the importance of tailoring polysaccharide processing methods to preserve bioefficacy. Emerging insights from computational modelling and receptor-binding studies reveal promising interactions with immune and apoptotic signalling cascades, suggesting new therapeutic opportunities. Finally, the review outlines challenges related to standardisation, scalability, and regulatory approval, while proposing avenues for future research toward clinical translation and industrial innovation. By integrating structural biology, pharmacology, and nutraceutical sciences, this work underscores the potential of macroalgal polysaccharides as precision agents in health-promoting formulations and next-generation functional foods. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

Food industry generates substantial waste, raising economic and environmental concerns. Green Chemistry (GC) highlights the extraction of nutritional and bioactive compounds as a key strategy for waste valorization, driving interest in sustainable methods to recover valuable compounds efficiently. This review evaluates the sustainability of widely used emerging extraction technologies—Microwave-, Ultrasound- and Enzyme-Assisted, as well as Supercritical Fluid Extraction—and their alignment with GC principles for agri-food waste valorization. It first outlines the principles, key parameters, and main advantages and limitations of each technique. Subsequently, sustainability is then assessed in selected studies using the Analytical GREEnness Metric Approach (AGREEprep). By calculating the greenness score (GS), this metric quantifies the adherence of extraction processes to sustainability standards. The analysis reveals variations within the same extraction method, influenced by solvent choice and operating conditions, as well as differences across the techniques, highlighting the importance of process design in achieving green and efficient valorization. Full article