Search Results (1,681)

Heavy metal contamination of foods remains a persistent global challenge for food safety and public health, driven by industrialization, mining activities, intensive agriculture, and ongoing environmental degradation. This scoping review synthesizes peer-reviewed literature on the occurrence of priority toxic metals—arsenic, cadmium, lead, mercury, and nickel—in food matrices, with emphasis on contamination pathways, analytical detection strategies, and documented human health effects. The reviewed studies reveal widespread accumulation of heavy metals in staple foods, including cereals, vegetables, seafood, and processed products, with concentrations frequently approaching or exceeding international regulatory limits, particularly in regions exposed to strong anthropogenic pressure. Conventional laboratory-based techniques, such as atomic absorption spectrometry and inductively coupled plasma methods, remain the reference standards for quantitative determination and regulatory compliance; however, their application to large-scale or continuous monitoring is often constrained by cost, infrastructure, and operational complexity. Consequently, increasing attention has been directed toward emerging detection approaches, including portable X-Ray fluorescence, Raman/SERS spectroscopy, electrochemical biosensors, electronic tongues, and in situ magnetic measurements, as complementary tools for rapid screening and field-based surveillance. Among these, environmental magnetism and in situ magnetic techniques stand out as non-destructive, low-cost proxies capable of identifying metal-associated particulate contamination linked to food production systems. Chronic dietary exposure to heavy metals is consistently associated with neurotoxicity, nephrotoxicity, carcinogenicity, and oxidative stress, underscoring the need for integrated, multi-tiered monitoring frameworks to support early detection, risk assessment, and prevention. Full article

The field of nanoparticle-based biotechnology has undergone substantial advancement, characterized by progress in targeted drug delivery systems, the development of innovative diagnostic and imaging platforms, the expanded adoption of environmentally sustainable (“green”) synthesis approaches, and an increasing emphasis on the integration of emerging technologies such as artificial intelligence and nanorobotics. Conventional nanoparticle synthesis often involves toxic reducing agents; however, recent advances promote eco-friendly green synthesis methods utilizing biological systems such as bacteria, fungi, algae, yeast, plants, and actinomycetes. These biological approaches are safe, sustainable, cost-effective, and capable of producing highly stable Nanoparticles (NPs). The interaction of nanomaterials with biological systems is crucial for developing intracellular and subcellular drug delivery technologies with minimal toxicity, governed by nano–bio interface mechanisms such as cellular translocation, surface wrapping, embedding, and internal attachment. Key factors influencing NP behavior include morphology, size, surface area, surface charge, and ligand chemistry. Magnetic nanoparticles, particularly iron-based forms, exhibit unique superparamagnetic properties that are strongly influenced by particle size, as explained by the Néel relaxation mechanism, in which thermal energy induces flipping of magnetic moments. Nanoparticles demonstrate diverse modes of action, including antimicrobial activity, reactive oxygen species (ROS)-induced cytotoxicity, genotoxicity, and plant growth promotion. NP performance and biological effects are strongly dependent on their size, shape, dosage, and concentration. This critical review article aims to elucidate evolution, classification, preparation methods, and multifaceted applications of nanoparticles Full article

Artificial intelligence and machine learning techniques can be used for performing magnetic testing on spacecraft that has historically been difficult and risky to perform. Some of the difficulty arises from the need to take these measurements from within the turbulent near-field area of the spacecraft. Some methods of testing require the spacecraft to be hoisted in the air and swung while the measurements are being taken so that any magnetic signatures in the test area can be removed. These new artificial intelligence and machine learning techniques can be used to determine the magnetic torque of complex magnetic systems. Here we will describe a test method that collects such data and poses much less risk to the spacecraft. We will also show some combinations of hyper-parameters that can be used to increase the speed and accuracy of the models. Some models were able to achieve over 96.6% accuracy of multipole determination on simulated data and over a 99.99% accuracy of dipole moment determination on simulated data. Applications include attitude control systems (ACS), science instrument locations, and data analysis. Full article

The efficient capture of chlorinated volatile organic compounds (Cl-VOCs) represents a significant challenge in environmental protection and sustainable chemical engineering. In this study, a functional deep eutectic solvent (DES) composed of tetrabutylphosphonium bromide ([P₄₄₄₄][Br]) and levulinic acid (LEV) at a 1:2 molar ratio was prepared, and its absorption performance toward two typical Cl-VOCs, namely dichloromethane (DCM) and chloroform (TCM), was evaluated using this DES as a recyclable absorbent. Based on COSMO-SAC model predictions and experimental validation, the [P₄₄₄₄][Br]–LEV (1:2) system was identified as the preferred candidate. Under mild conditions (10 °C, N₂ flow rate of 100 mL/min), the saturated absorption capacities of this DES reached 1521.71 mg/g and 1620.30 mg/g for DCM and TCM, respectively. The absorbent exhibited favorable regeneration stability over five consecutive absorption–desorption cycles, retaining over 90% of its initial absorption efficiency. Mechanistic studies, including proton nuclear magnetic resonance (¹H NMR), Fourier-transform infrared spectroscopy (FT-IR) , DSC (Differential Scanning Calorimetry), TGA (Thermogravimetric Analysis) and quantum chemical calculations , including electrostatic potential (ESP), independent gradient model (IGM), and reduced density gradient (RDG), demonstrated that the absorption process was dominated by physical interactions such as hydrogen bonding and van der Waals forces, with no chemical reactions involved. At the laboratory scale, this DES system showed excellent Cl-VOCs absorption performance, providing a useful reference for the rational design of high-efficiency VOC absorbents. Full article

Atypical Parkinsonisms are a diverse group of diseases associated with multiple pathologies, including synucleinopathies and tauopathies. Atypical Parkinsonisms include progressive supranuclear palsy, corticobasal degeneration, multiple system atrophy, and dementia with Lewy bodies. The examination of these diseases is complicated due to their overlapping clinical manifestations. Hence, tools enabling reliable supplementary assessment of atypical Parkinsonisms are needed. The most common methods involve neuroimaging; however, these evaluations generally involve basic magnetic resonance imaging and indicate possible morphological changes. Less attention is given to disease background assessment. Biochemical assessment enables a more detailed examination of the factors impacting neurodegenerative processes. The features that may impact the pathophysiology of these diseases include metabolic abnormalities, excessive inflammation, and environmental factors. In this context, proteomic evaluation, as analyzed in this article, could partly address the insufficiently described aspects of the unclear pathological mechanisms related to atypical Parkinsonisms. Full article

The environmental challenges posed by heavy metal contamination in sludge leachate are becoming increasingly severe, necessitating the development of highly efficient remediation technologies. Among various treatment approaches, magnetic adsorbents have garnered significant attention as a promising solution due to their outstanding adsorption performance, convenient magnetic separation characteristics, and potential for regeneration. This paper systematically reviews the latest research progress on magnetic adsorbents designed for the complex system of sludge leachate, covering synthesis methods, surface functionalization, adsorption mechanisms, and performance evaluation. Key synthesis strategies are analyzed, including magnetic core preparation, inorganic coating, carbon composites, organic polymer grafting, functional molecule impregnation, and metal–organic framework (MOF) composites. The mechanisms by which these strategies influence material adsorption capacity, selectivity, and stability are elucidated. Despite significant achievements in laboratory studies, practical applications still face challenges such as large-scale synthesis, regeneration efficiency, cyclic stability, and adaptability to complex water bodies. Future research should focus on green synthetic pathways to advance the industrial application of structurally functional magnetic composite materials, providing systematic solutions from material design to process optimization for the sustainable remediation of heavy metal contamination in sludge leachate. Full article

In this study, chicken bone biochar (CBC) was prepared from waste chicken bones via oxygen-limited pyrolysis. A magnetic component (Fe₃O₄) was introduced, and the composite was embedded in a sodium alginate (SA) gel network, successfully constructing magnetic chicken bone biochar/sodium alginate composite gel beads (M-CBC/SA). The experimental results showed that under the conditions of pH = 4.5, 25 °C, and an adsorbent dosage of 0.5 g/L, the removal efficiency of M-CBC/SA toward 50 mg/L U(VI) reached 91.67%, corresponding to an adsorption capacity of 91.67 mg/g. The adsorption process followed the pseudo-second-order kinetic model and the Langmuir isotherm model, with a theoretical maximum adsorption capacity of 322.58 mg/g, indicating that the adsorption was dominated by monolayer chemisorption. The material exhibited excellent magnetic separability and good anti-interference ability against coexisting ions such as K⁺, Na⁺, Cl⁻, and SO₄²⁻, and its adsorption behavior was only weakly affected by ionic strength. Characterization by XRD, FTIR, XPS, SEM-EDS and other techniques revealed that the immobilization mechanism of U(VI) involved the synergistic effects of dissolution–precipitation (the formation of a new autunite phase), surface complexation (involving hydroxyl and phosphate groups), ion exchange (exchange with Ca²⁺), and electrostatic attraction. Using waste chicken bones as the raw material, this composite achieves both efficient uranium immobilization and convenient magnetic separation, fully embodying the environmental concept of “treating waste with waste”, and shows promising application prospects in the treatment of uranium-containing wastewater. Full article

Triaxial induction logging is particularly outstanding in identifying reservoir parameters including anisotropic strata, inclined boreholes and horizontal wells. However, the coplanar systems follow the traditional induction method of using a shielding coil to offset the direct coupling. This method results in severe horns in the coplanar coil response, which makes it more difficult to evaluate the water (oil) saturation of the reservoir. In this study, we used an analytic method to derive the magnetic field in a finite-thickness anisotropic medium by applying tangential continuity of the electric and magnetic field strengths, introducing the magnetic vector potential and Bessel functions. The response model influenced by different parameters was established. Under the same environmental parameters, the measurement range of the vertical and horizontal conductivities was larger than that of the traditional coplanar system. The apparent conductivity of the target layer was closer to the true value of the vertical conductivity in the layered strata, with an accuracy improvement of 78.9%. Furthermore, the improved coplanar system mechanism was revealed by analyzing the spatial distributions of eddy currents and the magnitudes of the magnetic fields generated. Finally, we designed an experimental device for a coplanar sensing system. Under the same parameters, the received signals of the improved coplanar system were greater than those of the traditional coplanar system in the air, which laid a foundation for the quantitative evaluation of stratigraphic anisotropy response characterization and inversion. Full article

Undocumented orphan wells present challenges for subsurface characterization and environmental management due to their unknown locations and varied physical conditions. Magnetic surveys offer a promising pathway for identifying these wells by detecting the magnetic anomalies associated with steel casings. However, magnetometer data are typically high-volume, noisy, and complex, making them difficult to process efficiently with conventional methods. Existing processing methods require heavy preprocessing and achieve unsatisfactory recall scores. In this study, we propose a transformer-based deep learning framework designed to efficiently process hyper-resolute data without extensive downsampling. This is achieved through novel on-the-fly techniques as well as the use of sinusoidal positional encoders to allow the model relative positional awareness. Tests on purely synthetic data show that our model achieves F1-scores of over 90% for line spacings between successive flight paths up to 140 m, enabling surveys to take much sparser flight paths, resulting in more efficient coverage. When applied to real-life data, our model achieves a recall of 70%. This flexible and scalable framework enables the detection of orphan wells from drone data and can be readily adapted to other remote sensing applications. Full article

The European Union is currently focused on reducing non-exhaust emissions (NEE), a growing source of particulate matter (PM) pollution from road transport. This study presents the Life Cycle Assessment (LCA) of an innovative zero-emission magneto-rheological braking system specifically designed to meet new brake emission targets. Prototyped for A-segment passenger cars, the system uses magnetorheological fluids that modify their rheological properties when subjected to an external magnetic field. The environmental impacts of this innovative system are compared with those of a conventional disc brake, considering 16 environmental indicators across all life stages: raw material extraction, manufacturing, use, and end-of-life. In fact, although the system eliminates PM emissions during operation, it is crucial to assess whether it remains advantageous in terms of overall environmental impacts when the full life cycle is considered. As a prototype, this study also aims to inform design improvements that minimize environmental burdens. Results show that the innovative braking system performs better, particularly during the use and maintenance phases. Moreover, several eco-design strategies have been identified to reduce impacts related to materials and production. Overall, the magneto-rheological system demonstrates strong potential to meet future emission standards while improving the sustainability of vehicle braking technology. Full article

Microplastic (MP) contamination has become a widespread environmental concern in coastal and freshwater wetlands, ecosystems that play a crucial role in hydrological regulation, nutrient cycling, and biodiversity conservation. Despite their ecological importance, research on MPs in wetlands remains fragmented and comparatively underexplored. This study presents a comprehensive bibliometric and visualization analysis of global research on MPs in coastal wetlands. A total of 17,523 publications were retrieved from the Web of Science Core Collection (2002–2025) using predefined search strings and screening criteria. Analytical tools, including VOSviewer version 1.6.20, were employed to examine co-authorship networks, country contributions, and keyword co-occurrence patterns. The results indicate a significant increase in MP-related publications after 2016, with China, the United States, and India emerging as leading contributors. However, wetland-specific studies constitute only a small fraction compared to marine-focused MP research, highlighting a substantial research gap. Key research themes identified include MP sources, transport pathways, sediment–water interactions, and ecotoxicological impacts. Additionally, there is growing attention to remediation approaches, particularly those involving TiO₂, ZnO, Fe₃O₄, and graphene derivatives, employing photocatalytic, magnetic, and adsorptive mechanisms. Overall, the findings underscore the limited focus on wetland ecosystems in MP research and emphasize the urgent need for integrated research efforts and management strategies to address MP contamination in these vulnerable ecosystems. Full article

Background/Objectives: Magnetic nanoparticles have emerged as powerful tools for biomedical imaging, targeted drug delivery, and hyperthermia therapy. Magnetic particle imaging (MPI) is among the most promising technologies built around its properties: a radiation-free, quantitative tomographic modality that detects superparamagnetic iron oxide nanoparticles (SPIONs) directly against a biologically silent background. This review synthesizes MPI’s physical principles, nanoparticle design strategies, and preclinical applications within the broader landscape of magnetic material engineering for biomedical use. Methods: A systematic review was conducted covering MPI signal generation and image reconstruction, nanoparticle core synthesis and surface coating approaches, and preclinical applications, spanning cell tracking, oncological imaging, vascular perfusion, neuroimaging, and MPI-guided theranostics. Studies were selected to provide quantitative benchmarks and direct comparisons with competing modalities where available. Results: MPI delivers signal-to-background ratios above 1000:1, iron-mass linearity at R² ≥ 0.99, regardless of tissue depth, and acquisition rates up to 46 volumes per second. Tracer architecture—encompassing single-core particles, multicore nanoflowers, and stimuli-responsive cluster designs—is the primary determinant of sensitivity, environmental robustness, and theranostic capability. Preclinical results include detection of cell populations in the low thousands, earlier ischaemia identification than diffusion-weighted MRI, real-time drug release quantification, and spatially confined tumour hyperthermia. Three translational bottlenecks are identified: the absence of a clinically approved tracer with optimal relaxation dynamics, hardware performance losses when scaling to human-bore systems, and overestimation of passive tumour accumulation in murine models. Conclusions: MPI illustrates how progress in magnetic material design directly expands clinical imaging and theranostic possibilities. Successful translation will require indication-driven, interdisciplinary development that integrates materials science, scanner engineering, and regulatory strategy in parallel. Full article

Two-dimensional (2D) magnetic materials have emerged as a promising platform for next-generation sensing technologies due to their atomic thickness, tunable magnetic properties, and compatibility with van der Waals heterostructures. Rapid progress in material discovery, synthesis, and device integration has expanded opportunities for compact, low-power, and highly sensitive sensor platforms. This review examines selected sensing mechanisms enabled by 2D magnetic materials, highlighting recent experimental advances and emerging device concepts. Current limitations and challenges such as environmental stability, scalability, and room-temperature operation are considered in the context of ongoing research efforts. By examining these approaches, this review aims to provide insight into the current development and potential of 2D magnetic materials for sensing technologies. This review is organized to first introduce the fundamental properties and challenges of 2D magnetic materials, followed by a survey of key sensing mechanisms and representative device implementations, and concludes with an outlook on future research directions. Full article

Environmental temperature-induced metabolic changes in dams can be reflected by alterations in metabolomic and fatty acid profiles in colostrum. The colostrum from 13 Black Bengal (BB) dams was collected on the day of parturition at two consecutive parities during the hot conditions (HCs) of summer or rainy seasons and the cold conditions (CCs) of winter. The metabolomic and fatty acid profiles were analyzed using nuclear magnetic resonance (NMR) and gas chromatography–mass spectrometry, respectively. The results showed significantly higher sarcosine, tyrosine, citrate, succinate, galactose, acetylglucosamine, carnitine, choline, glycerophosphocholine, and trimethylamine N-oxide during CCs than HCs; potential discriminant metabolites according to VIP scores were sarcosine, succinate, and choline. Colostrum from CCs had significantly lower levels of saturated fatty acids (SFAs), including butyric acid (C4:0), myristic acid (C14:0), and pentadecanoic acid (C15:0), but higher omega-9 monounsaturated fatty acids (MUFAs), especially oleic acid (C18:1n9c), elaidic acid (C18:1n9t), and eicosenoic acid (C20:1n9), than in HC. Linoleic acid (C18:2n6c) and the omega 6/omega 3 PUFA ratio were higher during CCs than HCs. It is concluded that a metabolic shift for nutrient utilization occurs, from glucose during HCs toward fat during CCs, which may not be due to the diet but rather neurohumoral alterations occurring during temperature adaptation. Full article

Search coil magnetometers (SCMs) are widely used in space science missions to measure time-varying magnetic fields. However, conventional SCM designs often increase sensor mass and electronic power consumption in order to meet mission-specific sensitivity requirements. This study presents the design and ground-based test results of a space search coil magnetometer (SSCM) concept aimed at reducing sensor mass and electronic power consumption while maintaining practical system operability for platform-constrained missions. Mass reduction was achieved by adopting a rolling-sheet core configuration. In addition, printed circuit board (PCB)-based interconnections between segmented windings were implemented to improve the reproducibility of assembly and mechanical robustness without additional structural complexity. Power reduction was achieved by employing an application-specific integrated circuit (ASIC)-based sensor amplifier and a compact control electronic unit implemented as a modular stack with a 1U CubeSat standard board form factor. Performance tests confirmed the stable operation of the integrated sensor–electronics chain over the target measurement band. The system-level noise-equivalent magnetic induction (NEMI) measured under laboratory conditions was 33 fT/√Hz at 1 kHz. Environmental tests including vibration and thermal cycling were performed to further verify the structural safety and functional stability of the sensor assembly under space-relevant conditions. The proposed SSCM architecture provides a practical approach for implementing low-mass and low-power magnetic field instruments for platform-constrained space missions. Full article