Strategies and Challenges of Identifying Nanoplastics in Environment by Surface-Enhanced Raman Spectroscopy

Monitoring Poly(methyl methacrylate) and Polyvinyl Dichloride Micro/Nanoplastics in Water by Direct Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

A simple, sustainable, and sensitive monitoring approach of micro/nanoplastics (MNPs) in aqueous samples is crucial since it helps in assessing the extent of contamination and understanding the potential risks associated with their presence without causing additional stress to the environment. In this study, a novel strategy for qualitative and quantitative determination of MNPs in water by direct solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was proposed for the first time. Spherical poly(methyl methacrylate) (PMMA) and irregularly shaped polyvinyl dichloride (PVDC) were used to evaluate the feasibility and performance of the proposed method. The results demonstrated that both PMMA and PVDC MNPs were efficiently extracted by the homemade SPME coating of nitrogen-doped porous carbons (N-SPCs) and exhibited sufficient thermal decomposition in the GC-MS injection port. Excellent extraction performances of N-SPCs coating for MNPs are attributed to hydrophobic cross-linking, electrostatic forcing, hydrogen bonding, and pore trapping. Methyl methacrylate was identified as the marker for PMMA, while 1,3-dichlorobenzene and 1,3,5-trichlorobenzene were the indicators for PVDC. Under the optimal extraction and decomposition conditions, the proposed method exhibited ultrahigh sensitivity, with a limit of detection of 0.0041 μg/L for PMMA and 0.0054 μg/L for PVDC. Notably, a programmed temperature strategy for the GC-MS injector was developed to discriminate and eliminate the potential interferences of intrinsic indicator compounds. Owing to the integration of sampling, extraction, injection, and decomposition into one step by SPME, the proposed method demonstrates exceptional sensitivity, eliminating the necessity for complex sample pretreatment procedures and the use of organic solvents. Finally, the proposed method was successfully applied in the determination of PMMA and PVDC MNPs in real aqueous samples.

SERS-based microdevices for use as in vitro diagnostic biosensors

Advances in surface-enhanced Raman scattering (SERS) detection have helped to overcome the limitations of traditional in vitro diagnostic methods, such as fluorescence and chemiluminescence, owing to its high sensitivity and multiplex detection capability. However, for the implementation of SERS detection technology in disease diagnosis, a SERS-based assay platform capable of analyzing clinical samples is essential. Moreover, infectious diseases like COVID-19 require the development of point-of-care (POC) diagnostic technologies that can rapidly and accurately determine infection status. As an effective assay platform, SERS-based bioassays utilize SERS nanotags labeled with protein or DNA receptors on Au or Ag nanoparticles, serving as highly sensitive optical probes. Additionally, a microdevice is necessary as an interface between the target biomolecules and SERS nanotags. This review aims to introduce various microdevices developed for SERS detection, available for POC diagnostics, including LFA strips, microfluidic chips, and microarray chips. Furthermore, the article presents research findings reported in the last 20 years for the SERS-based bioassay of various diseases, such as cancer, cardiovascular diseases, and infectious diseases. Finally, the prospects of SERS bioassays are discussed concerning the integration of SERS-based microdevices and portable Raman readers into POC systems, along with the utilization of artificial intelligence technology.

Quantitative detecting low concentration polystyrene nanoplastics in aquatic environments via an Ag/Nb2CTx (MXene) SERS substrate

In this study, the plasmonic Ag nanoparticles (Ag NPs) were uniformly anchored on the high conductivity Nb2CTx (MXene) nanosheets to construct an Ag/Nb2CTx substrate for surface-enhanced Raman spectroscopy (SERS) detection of polystyrene (PS) nanoplastics. The KI addition (0.15 mol/L), the volume ratio between substrate colloid and nanoplastic suspension (2:1), and the mass ratio of Nb2CTx in substrate (14%) on SERS performance were optimized. The EM hot spots of Ag/Nb2CTx are significantly enlarged and enhanced, elucidated by FDFD simulation. Then, the linear relationship between the PS nanoplastics concentration with three different sizes (50, 300, and 500 nm) and the SERS intensity was obtained (R2 > 0.976), wherein, the detection limit was as low as 10-4 mg/mL for PS nanoplastic. Owing to the fingerprint feature, the Ag/Nb2CTx-14% substrate successfully discerns the mixtures from two-component nanoplastics. Meanwhile, it exhibits excellent stability of PS nanoplastics on different detection sites. The recovery rates of PS nanoplastics with different sizes in lake water ranged from 94.74% to 107.29%, with the relative standard deviation (RSD) ranging from 2.88% to 8.30%. Based on this method, the expanded polystyrene (EPS) decomposition behavior was evaluated, and the PS concentrations in four water environments were analyzed. This work will pave the way for the accurate quantitative detection of low concentration of nanoplastics in aquatic environments.

Nanoplastics in Water: Artificial Intelligence-Assisted 4D Physicochemical Characterization and Rapid In Situ Detection

For the first time, we present a much-needed technology for the in situ and real-time detection of nanoplastics in aquatic systems. We show an artificial intelligence-assisted nanodigital in-line holographic microscopy (AI-assisted nano-DIHM) that automatically classifies nano- and microplastics simultaneously from nonplastic particles within milliseconds in stationary and dynamic natural waters, without sample preparation. AI-assisted nano-DIHM identifies 2 and 1% of waterborne particles as nano/microplastics in Lake Ontario and the Saint Lawrence River, respectively. Nano-DIHM provides physicochemical properties of single particles or clusters of nano/microplastics, including size, shape, optical phase, perimeter, surface area, roughness, and edge gradient. It distinguishes nano/microplastics from mixtures of organics, inorganics, biological particles, and coated heterogeneous clusters. This technology allows 4D tracking and 3D structural and spatial study of waterborne nano/microplastics. Independent transmission electron microscopy, mass spectrometry, and nanoparticle tracking analysis validates nano-DIHM data. Complementary modeling demonstrates nano- and microplastics have significantly distinct distribution patterns in water, which affect their transport and fate, rendering nano-DIHM a powerful tool for accurate nano/microplastic life-cycle analysis and hotspot remediation.

Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal-phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50-500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

SERS-Based Microneedle Biosensor for In Situ and Sensitive Detection of Tyrosinase

Tyrosinase (TYR) emerges as a key enzyme that exerts a regulatory influence on the synthesis of melanin, thereby assuming the role of a critical biomarker for the detection of melanoma. Detecting the authentic concentration of TYR in the skin remains a primary challenge. Distinguished from ex vivo detection methods, this study introduces a novel sensor platform that integrates a microneedle (MN) biosensor with surface-enhanced Raman spectroscopy (SERS) technology for the in situ detection of TYR in human skin. The platform utilized dopamine (DA)-functionalized gold nanoparticles (Au NPs) as the capturing substrate and 4-mercaptophenylboronic acid (4-MPBA)-modified silver nanoparticles (Ag NPs) acting as the SERS probe. Here, the Au NPs were functionalized with mercaptosuccinic acid (MSA) for DA capture. In the presence of TYR, DA immobilized on the MN is preferentially oxidized to dopamine quinone (DQ), a process that results in a decreased density of SERS probes on the platform. TYR concentration was detected through variations in the signal intensity emitted by the phenylboronic acid. The detection system was able to evaluate TYR concentrations within a linear range of 0.05 U/mL to 200 U/mL and showed robust anti-interference capabilities. The proposed platform, integrating MN-based in situ sensing, SERS technology, and TYR responsiveness, holds significant importance for diagnosing cutaneous melanoma.

A WOx/MoOx hybrid oxide based SERS FET and investigation on its tunable SERS performance

Active control of the surface-enhanced Raman scattering (SERS) enhancement shows great potential for realizing smart detection of different molecules. However, conventional methods usually involve time-consuming structural design or a sophisticated fabrication process. Herein, we reported an electrically tunable field effect transistor (FET) comprising a WOx/MoOx hybrid as the SERS active layer. In the experiment, WOx/MoOx hybrids were first prepared by mixing different molar ratios of WOx and MoOx oxides. Then, R6G molecules were used as Raman reporters, showing that the intensity of the SERS signal observed on the most optimal hybrids (molar ratio = 1 : 3) could be increased by two times as high as that observed on a single WOx or MoOx based substrate, which was ascribed to enhanced charge transfer efficiency by the constructed nano-heterojunction between the WOx and MoOx oxides. Thereafter, a back-gate FET was fabricated on a SiO2/Si substrate, and the most optimal WOx/MoOx hybrid was deposited as the gate channel and the SERS active layer. After that, a series of gate biases (from -15 V to 15 V) were implemented to actively tune the SERS performance of the FET. It is evident that the SERS EF can be further tuned from 2.39 × 107 (-15 V) to 6.55 × 107 (+10 V), which is ∼7.4/4.1 times higher than that observed on the pure WOx device (8.81 × 106) or pure MoOx (1.61 × 107) device, respectively. Finally, the mechanism behind the electrical tuning strategy was investigated. It is revealed that a positive voltage would bend the conduction band down, which increased the electron density near the Fermi level. Consequently, it triggered the resonance charge transfer and significantly improved the SERS performance. In contrast, a negative gate voltage attracted the holes to the Fermi level, which deferred the charge transfer process, and caused the reduction of the SERS enhancement.

Bridging Smart Nanosystems with Clinically Relevant Models and Advanced Imaging for Precision Drug Delivery

Intracellular delivery of nano-drug-carriers (NDC) to specific cells, diseased regions, or solid tumors has entered the era of precision medicine that requires systematic knowledge of nano-biological interactions from multidisciplinary perspectives. To this end, this review first provides an overview of membrane-disruption methods such as electroporation, sonoporation, photoporation, microfluidic delivery, and microinjection with the merits of high-throughput and enhanced efficiency for in vitro NDC delivery. The impact of NDC characteristics including particle size, shape, charge, hydrophobicity, and elasticity on cellular uptake are elaborated and several types of NDC systems aiming for hierarchical targeting and delivery in vivo are reviewed. Emerging in vitro or ex vivo human/animal-derived pathophysiological models are further explored and highly recommended for use in NDC studies since they might mimic in vivo delivery features and fill the translational gaps from animals to humans. The exploration of modern microscopy techniques for precise nanoparticle (NP) tracking at the cellular, organ, and organismal levels informs the tailored development of NDCs for in vivo application and clinical translation. Overall, the review integrates the latest insights into smart nanosystem engineering, physiological models, imaging-based validation tools, all directed towards enhancing the precise and efficient intracellular delivery of NDCs.

Phase-Tunable Molybdenum Boride Ceramics as an Emerging Sensitive and Reliable SERS Platform in Harsh Environments

Traditional surface-enhanced Raman scattering (SERS) sensors rely heavily on the use of plasmonic noble metals, which have limitations due to their high cost and lack of physical and chemical stability. Hence, it is imperative to explore new materials as SERS platforms that can withstand high temperatures and harsh conditions. In this study, the SERS effect of molybdenum boride ceramic powders is presented with an enhancement factor of 5 orders, which is comparable to conventional noble metal substrates. The molybdenum boride powders synthesized through liquid-phase precursor and carbothermal reduction have β-MoB, MoB2 , and Mo2 B5 phases. Among these phases, β-MoB demonstrates the most significant SERS activity, with a detection limit for rhodamine 6G (R6G) molecules of 10-9  m. The impressive SERS enhancement can be attributed to strong molecule interactions and prominent charge interactions between R6G and the various phases of molybdenum boride, as supported by theoretical calculations. Additionally, Raman measurements show that the SERS activity remains intact after exposure to high temperature, strong acids, and alkalis. This research introduces a novel molybdenum boride all-ceramic SERS platform capable of functioning in harsh conditions, thereby showing the promising of boride ultrahigh-temperature ceramics for detection applications in extreme environments.

Underappreciated microplastic galaxy biases the filter-based quantification

Long-term environmental loading of microplastics (MPs) causes alarming exposure risks for a variety of species worldwide, considered a planetary threat to the well-being of ecosystems. Robust quantitative estimates of MP extents and featured diversity are the basis for comprehending their environmental implications precisely, and of these methods, membrane-based characterizations predominate with respect to MP inspections. However, though crucial to filter-based MP quantification, aggregation statuses of retained MPs on these substrates remain poorly understood, leaving us a "blind box" that exaggerates uncertainty in quantitive strategies of preselected areas without knowing overview loading structure. To clarify this uncertainty and estimate their impacts on MP counting, using MP imaging data assembled from peer-reviewed studies through a systematic review, here we analyze the particle-specific profiles of MPs retained on various substrates according to their centre of mass with a fast-random forests algorithm. We visualize the formation of distinct galaxy-like MP aggregation-similar to the solar system and Milky Way System comprised of countless stars-across the pristine and environmental samples by leveraging two spatial parameters developed in this study. This unique pattern greatly challenges the homogeneously or randomly distributed MP presumption adopted extensively for simplified membrane-based quantification purposes and selective ROI (region of interest) estimates for smaller-sized plastics down to the nano-range, as well as the compatibility theory using pristine MPs as the standard to quantify the presence of environmental MPs. Furthermore, our evaluation with exemplified numeration cases confirms these location-specific and area-dependent biases in many imaging analyses of a selective filter area, ascribed to the minimum possibility of reaching an ideal turnover point for the selective quantitive strategies. Consequently, disproportionate MP schemes on loading substrates yield great uncertainty in their quantification processing, highlighting the prompt need to include pattern-resolved calibration prior to quantification. Our findings substantially advance our understanding of the structure, behavior, and formation of these MP aggregating statuses on filtering substrates, addressing a fundamental question puzzling scientists as to why reproducible MP quantification is barely achievable even for subsamples. This study inspires the following studies to reconsider the impacts of aggregating patterns on the effective counting protocols and target-specific removal of retained MP aggregates through membrane separation techniques.

Rapid detection of nanoplastics down to 20 nm in water by surface-enhanced raman spectroscopy

Plastic pollution represents a pressing global environmental issue, with microplastics (MPs) and nanoplastics (NPs) being ubiquitously found in both food and the environment. However, the investigation of NPs has been hampered by limited detection technologies, necessitating the development of advanced techniques. This study introduces a sol-based surface-enhanced Raman spectroscopy (SERS) approach for the swift detection of MPs and NPs in aqueous environment. By leveraging the aggregation effect between silver nanoparticles (Ag nanoparticles) and plastic particles, the plastic Raman signals is significantly enhanced, effectively lowering the detection limit. Utilizing Ag nanoparticles, plastic particles as small as 20 nm were detected in liquid samples, with a detection limit of 0.0005%. With the developed method, nanoplastic particles in seafood packaging samples were successfully tested, with concentration found to be at μg/L level. This method offers a rapid, economical, and convenient means of detecting and identifying MPs and NPs. The sensitivity of the method allows for capturing plastic signals within 2 min, making it valuable for aquatic environment contamination detection. SERS technology also holds promise for rapid plastic solution detection, potentially becoming a fast detection method for food safety.

Automatic Identification of Individual Nanoplastics by Raman Spectroscopy Based on Machine Learning

The increasing prevalence of nanoplastics in the environment underscores the need for effective detection and monitoring techniques. Current methods mainly focus on microplastics, while accurate identification of nanoplastics is challenging due to their small size and complex composition. In this work, we combined highly reflective substrates and machine learning to accurately identify nanoplastics using Raman spectroscopy. Our approach established Raman spectroscopy data sets of nanoplastics, incorporated peak extraction and retention data processing, and constructed a random forest model that achieved an average accuracy of 98.8% in identifying nanoplastics. We validated our method with tap water spiked samples, achieving over 97% identification accuracy, and demonstrated the applicability of our algorithm to real-world environmental samples through experiments on rainwater, detecting nanoscale polystyrene (PS) and polyvinyl chloride (PVC). Despite the challenges of processing low-quality nanoplastic Raman spectra and complex environmental samples, our study demonstrated the potential of using random forests to identify and distinguish nanoplastics from other environmental particles. Our results suggest that the combination of Raman spectroscopy and machine learning holds promise for developing effective nanoplastic particle detection and monitoring strategies.

Detection of environmental nanoplastics via surface-enhanced Raman spectroscopy using high-density, ring-shaped nanogap arrays

Micro- and nano-plastics (MNPs) are global contaminants of growing concern to the ecosystem and human health. In-the-field detection and identification of environmental micro- and nano-plastics (e-MNPs) is critical for monitoring the spread and effects of e-MNPs but is challenging due to the dearth of suitable analytical techniques, especially in the sub-micron size range. Here we show that thin gold films patterned with a dense, hexagonal array of ring-shaped nanogaps (RSNs) can be used as active substrates for the sensitive detection of micro- and nano-plastics by surface-enhanced Raman spectroscopy (SERS), requiring only small sample volumes and no significant sample preparation. By drop-casting 0.2-μL aqueous test samples onto the SERS substrates, 50-nm polystyrene (PS) nanoparticles could be determined via Raman spectroscopy at concentrations down to 1 μg/mL. The substrates were successfully applied to the detection and identification of ∼100-nm polypropylene e-MNPs in filtered drinking water and ∼100-nm polyethylene terephthalate (PET) e-MNPs in filtered wash-water from a freshly cleaned PET-based infant feeding bottle.

Chemical characterization of microplastic particles formed in airborne waste discharged from sewer pipe repairs

Microplastic particles are of increasing environmental concern due to the widespread uncontrolled degradation of various commercial products made of plastic and their associated waste disposal. Recently, common technology used to repair sewer pipes was reported as one of the emission sources of airborne microplastics in urban areas. This research presents results of the multi-modal comprehensive chemical characterization of the microplastic particles related to waste discharged in the pipe repair process and compares particle composition with the components of uncured resin and cured plastic composite used in the process. Analysis of these materials employs complementary use of surface-enhanced Raman spectroscopy, scanning transmission X-ray spectro-microscopy, single particle mass spectrometry, and direct analysis in real-time high-resolution mass spectrometry. It is shown that the composition of the relatively large (100 μm) microplastic particles resembles components of plastic material used in the process. In contrast, the composition of the smaller (micrometer and sub-micrometer) particles is significantly different, suggesting their formation from unintended polymerization of water-soluble components occurring in drying droplets of the air-discharged waste. In addition, resin material type influences the composition of released microplastic particles. Results are further discussed to guide the detection and advanced characterization of airborne microplastics in future field and laboratory studies pertaining to sewer pipe repair technology.

Liquid Interfacial Coassembly of Plasmonic Arrays and Trace Hydrophobic Nanoplastics in Edible Oils for Robust Identification and Classification by Surface-Enhanced Raman Spectroscopy

The ubiquity of micro-/nanoplastics poses a visible threat to the environment, aquatic organisms, and human beings and has become a global concern. Here, we proposed a liquid interface-based strategy using surface-enhanced Raman spectroscopy to coassemble nanoplastics and gold nanoparticles into a dense and homogeneous plasmonic array, thereby enabling the rapid and sensitive detection of trace nanoplastics. In addition, due to the uniqueness of the oil-water immiscible two-phase interface, we achieved ideal results for the detection of nanoplastics in a complex matrix (e.g., aqueous environment and edible oil) with a detection limit of μg/mL. With the aid of the principal component analysis algorithm, the differentiation and identification of multiple nanoplastic components (e.g., polystyrene, polyethylene, and polyethylene terephthalate) in aqueous environments and common hazards (e.g., Bap and Phe) in edible oil were achieved. Therefore, our self-assembled plasmonic arrays are expected to be used for monitoring environmental pollution and food safety.

Dark background-surface enhanced Raman spectroscopic detection of nanoplastics: Thermofluidic strategy

This study aims to develop a cost-effective and time-efficient method for detecting nanoplastics, which have recently garnered significant attention due to their potential harmful impact on the water environment (XiaoZhi, 2021; Gigault et al., 2021; Mitrano et al., 2021; Ferreira et al., 2019). Although several techniques are available to accumulate data on microplastics, there is currently no universally accepted analytical technique for detecting nanoplastics (Gigault et al., 2021; Mitrano et al., 2021; Mitrano et al., 2019; Cai et al., 2021a; Allen et al., 2022). In this study, we have developed a substrate that exhibits Surface-enhanced Raman scattering (SERS) (Zhou et al., 2021; Lv et al., 2020; Lê et al., 2021; Hu et al., 2022; Chang et al., 2022; Yang et al., 2022; Xu et al., 2020; Jeon et al., 2021; Lee and Fang, 2022; Vélez-Escamilla and Contreras-Torres, 2022; Liu et al., 2022; Xie et al., 2023) activity over a large area and a dark background in optical (darkfield mode) vision, enabling the detection of sparkling nanoplastics on the substrate. This darkfield-based strategy allows for the point-by-point detection of single nanoplastics, offering cost and time-saving advantages over other resource-intensive analytical techniques. Our findings reveal the presence of PP nanoplastics in commonly used laboratory equipment, individual PE nanoplastics from a hot water-contained commercial paper cup, and the first detection of natural nanoplastics in coastal seawater. We believe that this technique will have a universal application in establishing a global map of nanoplastics and advancing our understanding of the environmental life cycle of plastics.

Hydrophobicity-driven self-assembly of nanoplastics and silver nanoparticles for the detection of polystyrene microspheres using surface enhanced Raman spectroscopy

Microplastics (MPs) and Nanoplastics (NPs) accumulated in the environment have been identified as a major global issue due to their potential harm to wildlife. Current research in the detection of MPs is well established. However, the detection of NPs remains challenging. The aim of this paper is to investigate the detection of polystyrene (PS) NPs on a super-hydrophobic substrate using surface-enhanced Raman spectroscopy (SERS) technology after high-speed centrifugation of PS NPs and AgNPs. The hydrophobic substrate reduces the contact area of droplet, concentrating PS NPs and AgNPs on a small spot, which eliminates the random distribution of nano particles. The condensed PS NPs and AgNPs improve the SERS intensity, reproductivity and detection sensitivity. The results show that SERS measurement on a hydrophobic substrate could significantly improve the detection sensitivity of PS NPs, with the detection limits of PS NPs as low as 0.5 mg/L (500 nm PS NPs) and 1 mg/L (100 nm PS NPs). The study provides an effective and rapid method for the detection of NPs at trace concentration, demonstrating more possibility for the future detection of trace NPs in the aquatic environment.

A critical review on nanoplastics and its future perspectives in the marine environment

Nanoplastics (plastic particles smaller than 1 μm) are the least-known type of marine litter. Nanoplastics (NPs) have attracted much interest in recent years because of their prevalence in the environment and the potential harm they can cause to living organisms. This article focuses on understanding NPs and their fate in the marine environment. Sources of NPs have been identified, including accidental release from products or through nano-fragmentation of larger plastic debris. As NPs have a high surface area, they may retain harmful compounds. The presence of harmful additives in NPs poses unique practical challenges for studies on their toxicity. In this review, several methods specifically adapted for the physical and chemical characterization of NPs have been discussed. Furthermore, the review provides an overview of the translocation and absorption of NPs into organisms, along with an evaluation of the release of potential toxins from NPs. Further, we have provided an overview about the existing methods suggested for the possible degradation of these NPs. We conclude that the hazards of NPs are plausible but unknown, necessitating a thorough examination of NPs' sources, fate, and effects to better mitigate and spread awareness about this emerging contaminant.

A microfluidic approach for label-free identification of small-sized microplastics in seawater

Marine microplastics are emerging as a growing environmental concern due to their potential harm to marine biota. The substantial variations in their physical and chemical properties pose a significant challenge when it comes to sampling and characterizing small-sized microplastics. In this study, we introduce a novel microfluidic approach that simplifies the trapping and identification process of microplastics in surface seawater, eliminating the need for labeling. We examine various models, including support vector machine, random forest, convolutional neural network (CNN), and residual neural network (ResNet34), to assess their performance in identifying 11 common plastics. Our findings reveal that the CNN method outperforms the other models, achieving an impressive accuracy of 93% and a mean area under the curve of 98 ± 0.02%. Furthermore, we demonstrate that miniaturized devices can effectively trap and identify microplastics smaller than 50 µm. Overall, this proposed approach facilitates efficient sampling and identification of small-sized microplastics, potentially contributing to crucial long-term monitoring and treatment efforts.

Imaging and identification of single nanoplastic particles and agglomerates

Pollution by nanoplastic is a growing environmental and health concern. Currently the extent of nanoplastic in the environment can only be cumbersomely and indirectly estimated but not measured. To be able to quantify the extent of the problem, detection methods that can identify nanoplastic particles that are smaller than 1 [Formula: see text]m are critically needed. Here, we employ surface-enhanced Raman scattering (SERS) to image and identify single nanoplastic particles down to 100 nm in size. We can differentiate between single particles and agglomerates and our method allows an improvement in detection speed of [Formula: see text] compared to state-of-the art surface-enhanced Raman imaging. Being able to resolve single particles allows to measure the SERS enhancement factor on individual nanoplastic particles instead of averaging over a concentration without spatial information. Our results thus contribute to the better understanding and employment of SERS for nanoplastic detection and present an important step for the development of future sensors.

Identification of Poly(ethylene terephthalate) Nanoplastics in Commercially Bottled Drinking Water Using Surface-Enhanced Raman Spectroscopy

Micro/nanoplastics have emerged as global contaminants of serious concern to human and ecosystem health. However, identification and visualization of microplastics and particularly nanoplastics have remained elusive due to the lack of feasible and reliable analytical approaches, particularly for trace nanoplastics. Here, an efficient surface-enhanced Raman spectroscopy (SERS)-active substrate with triangular cavity arrays is reported. The fabricated substrate exhibited high SERS performance for standard polystyrene (PS) nanoplastic detection with size down to 50 nm and a detection limit of 0.001% (1.5 × 10¹¹ particles/mL). Poly(ethylene terephthalate) (PET) nanoplastics collected from commercially bottled drinking water were detected with an average mean size of ∼88.2 nm. Furthermore, the concentration of the collected sample was estimated to be about 10⁸ particles/mL by nanoparticle tracking analysis (NTA), and the annual nanoplastic consumption of human beings through bottled drinking water was also estimated to be about 10¹⁴ particles, assuming water consumption of 2 L/day for adults. The facile and highly sensitive SERS substrate provides more possibilities for detecting trace nanoplastics in an aquatic environment with high sensitivity and reliability.

SGLT2 inhibition ameliorates nano plastics-induced premature endothelial senescence and dysfunction

Nano plastics (NPs) have been a significant threat to human health and are known to cause premature endothelial senescence. Endothelial senescence is considered one of the primary risk factors contributing to numerous cardiovascular disorders. Recent studies have suggested that inhibition of sodium glucose co-transporter (SGLT2) ameliorates endothelial senescence and dysfunction. Therefore, our study intends to explore the role of SGLT2 in NPs-induced endothelial senescence and dysfunction. Porcine coronary artery and its endothelial cells were treated with NPs in the presence or absence of Enavogliflozin (ENA), a SGLT2 inhibitor and then SGLTs expression, senescence markers and vascular function were evaluated. NPs significantly up-regulated SGLT2 and ENA significantly decreased NPs-induced senescence-associated-β-gal activity, cell-cycle arrest, and senescence markers p53 and p21 suggesting that inhibition of SGLT2 prevents NPs-induced endothelial senescence. In addition, ENA decreased the formation of reactive oxygen species with the downregulation of Nox2, and p22^phox. Furthermore, SGLT2 inhibition also up regulated the endothelial nitric oxide synthase expression along with improving vascular function. In conclusion, premature endothelial senescence by NPs is, at least in part, associated with SGLT2 and it could be a potential therapeutic target for preventing and/or treating environmental pollutants-induced cardiovascular disorders mediated by endothelial senescence and dysfunction.