Jul 2026· Current Research in Food Science· Vol 13· 0 citations· 40 references
Medicine
Abstract
Nanoplastics (NPs) are new types of pollutants that have emerged in food which has attracted widespread attention. However, due to the small size and low concentration, and the complexity of food matrices, the selective and sensitive determination of NPs in food is challenging. Herein, we report a dual-probe system for determination of trace-level polystyrene (PS) NPs with high sensitivity and selectivity. The proposed dual-probe system was composed of magnetic Fe3O4 nanoparticles functionalized with PS-specific peptides (Fe3O4@Au-PSBP) and a high-quality Li+-doped ZnGa2O4:Cr3+ persistent luminescence nanoparticles (PLNPs) modified with ethylene glycol chitosan. By integrating peptide-based specific recognition, persistent luminescence signaling, and magnetic separation with pH-switchable charge reversal, the proposed system enables effective capture and sensitive detection of PS NPs in complex matrices. Under the optimized conditions, the method showed a linear range of 50–800 pg mL−1 and a detection limit of 8.11 pg mL−1. The precision for the determination of 50 pg mL−1 PS NPs was 5.24% (RSD, n = 11). The method was successfully applied to the analysis of PS NPs in different matrices, including bottled purified water, saltwater (3.5% salinity), artificial lake water, and tea beverage, with recoveries ranging from 91.25% to 110.53%. More importantly, the proposed system can be readily adapted for the analysis of other targets by replacing the recognition unit, providing a versatile and selective sensing strategy for trace-level hazardous analytes.
Nanoplastics (NPs), defined as plastic particles smaller than 1 μm, pose emerging environmental and health concern due to their ability to penetrate biological membranes and accumulate in living organisms. Conventional analytical methods for NPs sampling and detection, generally restricted to NPs >100 nm, are often limited by complexity, high cost, and lack of suitability for rapid or on-field monitoring. In this study, we developed a novel electrochemical strategy for the in-situ capture and detection of polystyrene nanoplastics (PSNPs) using a gold screen-printed electrode, modified by mesoporous silica thin film, followed by proline functionalization via epoxy-silane. The adsorption of negatively charged PSNPs is electrochemically controlled and enhanced by selective accumulation potentials, resulting in a decreased ferricyanide anodic current. The sensor exhibits good sensitivity and reproducibility, as well as size-dependent detection of PSNPs as small as 34 kDa. Calibration curves, obtained by differential pulse voltammetry, demonstrate linear response across environmentally relevant concentration levels for all investigated PSNPs sizes (34, 564, and 2530 kDa), with increasing sensitivity for decreasing particle diameter - a trend consistent with surface coverage and mass transport considerations. Finally, the sensor's real-world applicability was evaluated by the determination of PSNPs in a spiked commercial brand of drinking water, with resulting recoveries between 86.7% and 102.1%. This straightforward, reagent-free electrochemical platform offers rapid response times, simple operational methodology, and suitability for on-site monitoring of NPs contamination in aquatic environments.
Maksimiljan Dekleva, Ula Putar, G. Kalčíková et al.· Talanta: The International J...· 0 citations
The widespread occurrence of micro- and nanoplastic particles (MNPs) in food systems has raised significant concerns regarding their potential impacts on the environment and human health. However, the reliable detection and quantification of MNPs remain highly challenging because of their small size, heterogeneous chemical composition, and the complexity of food matrices. Existing analytical methods often suffer from labor-intensive sample preparation, dependence on expensive instrumentation, or insufficient sensitivity for nanoscale detection. Therefore, there is a critical need for rapid, sensitive, and cost-effective detection methods that can be applied directly to real-world food systems. This dissertation presents the development of a surface-enhanced Raman spectroscopy (SERS)-based sensing platform integrated with cellulose-based materials for detecting MNPs in food matrices. Initially, a SERS method utilizing gold–silver core–shell nanoparticles (Au@Ag) was developed to detect polystyrene (PS) and polyethylene (PE) in both water and leafy vegetables. The method successfully enabled the simultaneous detection of both polymers, achieving limits of detection ranging from approximately 12–50 mg kg⁻¹ for PS and 173–744 mg kg⁻¹ for PE. These results demonstrated the feasibility of SERS for the rapid detection of mixed MNPs. To further improve sensitivity and reproducibility, bacterial cellulose (BNC) was employed as a functional scaffold for the in-situ synthesis of Au@Ag nanoparticles. The resulting BC-based SERS substrate exhibited more uniform nanoparticle distribution and superior plasmonic performance. This enhanced platform enabled reliable detection of MNPs in kale samples at concentrations as low as 4 mg kg⁻¹, with estimated limits of detection of 1.22 mg kg⁻¹ for PS and 3.95 mg kg⁻¹ for PE, showing a significant improvement compared to conventional nanoparticle-based systems. In addition, an ecosystem-informed strategy was developed to enhance bacterial cellulose production using a multi-kingdom microbial consortium. By integrating acetic acid bacteria, yeasts, and cyanobacteria, the optimized system achieved a maximum cellulose yield of 1.69 g L⁻¹, along with improved material properties, such as uniform thickness (2.56 mm) and reduced water vapor permeability. These advancements support the scalable production of high-quality cellulose substrates for sensing applications. Overall, this work demonstrates that integrating SERS with engineered cellulose-based substrates provides a practical, sensitive, and scalable approach for detecting MNPs in complex food matrices. The findings contribute to the advancement of detection technologies for emerging contaminants and support the development of sustainable strategies for food safety monitoring and environmental analysis.
The release of nanoplastics (NPs) from plastic bottled water containers has emerged as a concealed yet critical threat to water quality and consumer health. Yet, on-site and rapid quantification of NPs, particularly at environmentally relevant trace levels, remains a formidable analytical challenge. Here, we reported an ultrasensitive detection platform that integrates a quartz crystal microbalance (QCM) with a custom-engineered nanoporous sensing chip, enabling real-time, field-deployable quantification of NPs in bottled water with a detection limit of 0.39 μg·L-1. The platform achieves quantitative analysis of multiple NP types, including poly(methyl methacrylate) (PMMA), polyethylene terephthalate (PET), poly(vinyl alcohol) (PVA), polyvinyl chloride (PVC), polystyrene (PS), and carboxylated PS (PS-COOH), with a surface mass sensitivity of 17.7 ng·cm-2·Hz-1. Comprehensive interfacial characterization, supported by molecular simulations, shows that electrostatic attraction facilitates initial NP capture, whereas van der Waals interactions stabilize the adsorbed state, with PET exhibiting particularly favorable adsorption energetics. Leveraging this mechanism, we then conceived a portable device and validated its performance across diverse real-world scenarios involving PET-contaminated bottled water. The system demonstrated robust reliability and analytical fidelity under field conditions. This work establishes a QCM-based analytical paradigm for NP quantification and delivers a deployable technological solution for on-site, rapid, and trustworthy monitoring of NPs in drinking water matrices.
Xueyan Suo, Y. Huo, Yifei Wang et al.· Environmental Science and Te...· 0 citations
Triclocarban (TCC) serves as a highly effective antimicrobial agent with a broad range of applications, often found in daily chemical cleaning and disinfection products. Its accumulation in organisms poses ecological risks and potential health hazards. Therefore, it is essential to detect TCC quickly and with high sensitivity. A multi-taper optical fiber biosensor (OFB) based on local surface plasmon resonance (LSPR) was developed for the immediate and label-free identification of TCC in everyday chemical products. The sensor utilizes multi-mode fiber (MMF) along with a specialized type of nano-doped fiber (NDF). Nano-doped optical fibers feature intensified evanescent field and high sensing sensitivity with favorable environmental stability. Gold nanoparticles (AuNPs) were fixed to the taper section of the sensing fiber probe for generating LSPR. Potassium manganate nanoflowers (KMO-NFs) and nickel oxide nanoparticles (NiO-NPs) were also utilized to alter the fiber probe's surface, enhancing the sensor's specific surface area and accelerating its electronic response, thereby improving its performance. The sensing surface was coated with a TCC antibody in this work. Experimental results show that the biosensor maintained a high degree of linear correlation in the 0-100 μg/L range and a limit of identification is 9.87 μg/L. Examinations confirmed that this biosensor possesses outstanding stability, reproducibility, reusability, selectivity, and adaptability to different pH levels. Real sample tests also yielded satisfactory recoveries, proving the accuracy and reliability of the method, which has good prospects for TCC detection.
Ting Yu, Jia-Qi Gao, Xian-cui Su et al.· IEEE Transactions on Nanobio...· 0 citations
The excessive use of ofloxacin (OFL) has led to its persistent residues in water sources and animal-derived foods, posing a threat to human health. Therefore, it is urgent to develop fluorescent sensing materials capable of detecting ofloxacin in water environments and food matrices. Herein, a novel Eu3+@tetrafluorosuccinic acid-functionalized ratiometric fluorescent material Eu3+@UiO-67-TFSA was prepared by a two-step post-synthetic modification of UiO-67. In the concentration range of 1-15 μM, the Eu3+@UiO-67-TFSA had a limit of detection (LOD) of 0.42 μM for OFL, which was approximately 3.90 times lower than that of the non-fluorinated Eu3+@UiO-67-SA (LOD = 1.64 μM). The improved sensing performance could be attributed to the pre-concentration effect provided by the Eu3+@UiO-67-TFSA. The possible detection mechanism was systematically elucidated through relevant experiments and density functional theory (DFT) calculation. Moreover, the constructed smartphone-assisted visual sensing platform was successfully applied to detect OFL in actual food samples and real water environment samples.
Xueqin Sun, Yan Fan, Jia-cheng Liu· Food Chemistry· 0 citations
Precise quantitative monitoring of 17β-estradiol (E2) is important for reproductive management in precision livestock farming. However, E2 determination in complex biological matrices remains challenging because of matrix-derived background and signal variability. Here, we developed a nanoconfinement-assisted solid-state ratiometric fluorescent aptasensor integrating target-induced strand displacement (TISD), magnetic separation, and anodic aluminum oxide (AAO) nanochannel confinement. The sensing probe consisted of streptavidin-coated magnetic nanoparticles (MNPs) carrying a FAM-labeled cDNA internal reference and a Texas Red-labeled E2 aptamer reporter. E2 binding promoted dissociation of the Texas Red-labeled aptamer from the magnetic probe. Magnetic separation and washing reduced soluble matrix-derived interference, while subsequent deposition of the sensing complexes onto an AAO membrane mitigated coffee-ring-associated nonuniformity and produced a more spatially uniform dual-color fluorescence distribution for ratiometric analysis. Under matrix-matched calibration conditions, linear ranges of 5.0–50.0 pM were obtained in tap water and sow saliva, 5.0–40.0 pM in whole milk, and 5.0–15.0 pM in post-estrus sow urine. The LOD determined in tap water was 3.62 pM. The different calibration slopes obtained among the four matrices indicated that residual matrix-dependent effects remained and that matrix-specific calibration was required for quantitative analysis. Matrix-matched spike recoveries ranged from 86.92% to 119.54% across the investigated matrices. The aptasensor exhibited the strongest response toward 17β-E2 among the tested compounds; however, cross-reactivities of 77.3% for E3 and 47.3% for 17α-E2 indicated preferential rather than exclusive recognition. Molecular docking suggested a putative binding pose but did not experimentally establish the molecular recognition mechanism. Overall, the platform demonstrated laboratory-scale analytical feasibility in pretreated tap water, sow saliva, whole milk, and post-estrus sow urine. Further development of sample preparation, magnetic handling, membrane loading, probe selectivity, and portable fluorescence readout will be required before in situ or on-site application.