Detection and Quantification of Single Engineered Nanoparticles in Complex Samples Using Template Matching in Wide-Field Surface Plasmon Microscopy

Surface plasmon coupling between wide-field SPR microscopy and gold nanoparticles

The coupling behavior of the wide field surface plasmon microscopy (WF-SPRM) with single-, two-, and multiple-gold nanoparticles (AuNPs) with different AuNPs sizes is investigated using theoretical, simulation, and experimental approaches. The signal intensity of a single AuNP increases from 208 a.u. to 583 a.u. as particle size increases from 40 to 80 nm, which evidences the signal-building mechanism of Rayleigh scattering theory. A discrete particle model of SPR is used to understand the interaction between an Au-layer and a single AuNP. The calculated intensity profile of the single AuNP from the discrete particle model is accepted with the experimental data. In addition, the superposition between 2-AuNPs surface plasmon waves is studied using the finite element method as well as experimental data from WF-SPRM. The surface plasmon waves around the two particles generate an interference pattern. Finally, it is demonstrated that plasmonic multiple particles scattering can be represented by an effective media, which is described by Maxwell-Garnet equations.

Deep Learning Approach for the Localization and Analysis of Surface Plasmon Scattering

Surface plasmon resonance microscopy (SPRM) combines the principles of traditional microscopy with the versatility of surface plasmons to develop label-free imaging methods. This paper describes a proof-of-principles approach based on deep learning that utilized the Y-Net convolutional neural network model to improve the detection and analysis methodology of SPRM. A machine-learning based image analysis technique was used to provide a method for the one-shot analysis of SPRM images to estimate scattering parameters such as the scatterer location. The method was assessed by applying the approach to SPRM images and reconstructing an image from the network output for comparison with the original image. The results showed that deep learning can localize scatterers and predict other variables of scattering objects with high accuracy in a noisy environment. The results also confirmed that with a larger field of view, deep learning can be used to improve traditional SPRM such that it localizes and produces scatterer characteristics in one shot, considerably increasing the detection capabilities of SPRM.

Switchable Polyacrylic Acid Polyelectrolyte Brushes for Surface Plasmon Resonance Applications

Imaging wide-field surface plasmon resonance (SPR) microscopy sensors based on polyacrylic acid polyelectrolyte brushes (PAA PEBs) were designed to enhance the sensitivity of nano-object detection. The switching behavior of the PAA PEBs against changes in the pH values was investigated by analyzing the chemical, morphological, optical, and electrical properties. At pH ~1, the brushes collapse on the surface with the dominance of carboxylic groups (COOH). Upon the increase in the pH to nine, the switching process completes, and the brushes swell from dissociating most of the COOH groups and converting them into COO- groups. The domination of the negatively charged COO- groups increases the electrostatic repulsion in the polymer chains and stretches the brushes. The sensitivity of the SPR sensing device was investigated using a theoretical approach, as well as experimental measurements. The signal-to-noise ratio for a Au layer increases from six to eighteen after coating with PAA PEBs. In addition, the linewidth of the recorded image decreases from six pixels to five pixels by using the Au-PAA layers, which results from the enhanced spatial resolution of the recorded images. Coating a Au-layer with PAA PEBs enhances the sensitivity of the SPR sensing device, and improves the spatial resolution of the recorded image.

The Employment of the Surface Plasmon Resonance (SPR) Microscopy Sensor for the Detection of Individual Extracellular Vesicles and Non-Biological Nanoparticles

A wide-field surface plasmon resonance (SPR) microscopy sensor employs the surface plasmon resonance phenomenon to detect individual biological and non-biological nanoparticles. This sensor enables the detection, sizing, and quantification of biological nanoparticles (bioNPs), such as extracellular vesicles (EVs), viruses, and virus-like particles. The selectivity of bioNP detection does not require biological particle labeling, and it is achieved via the functionalization of the gold sensor surface by target-bioNP-specific antibodies. In the current work, we demonstrate the ability of SPR microscopy sensors to detect, simultaneously, silica NPs that differ by four times in size. Employed silica particles are close in their refractive index to bioNPs. The literature reports the ability of SPR microscopy sensors to detect the binding of lymphocytes (around 10 μm objects) to the sensor surface. Taken together, our findings and the results reported in the literature indicate the power of SPR microscopy sensors to detect bioNPs that differ by at least two orders in size. Modifications of the optical sensor scheme, such as mounting a concave lens, help to achieve homogeneous illumination of a gold sensor chip surface. In the current work, we also characterize the improved magnification factor of the modified SPR instrument. We evaluate the effectiveness of the modified and the primary version of the SPR microscopy sensors in detecting EVs isolated via different approaches. In addition, we demonstrate the possibility of employing translation and rotation stepper motors for precise adjustments of the positions of sensor optical elements-prism and objective-in the primary version of the SPR microscopy sensor instrument, and we present an algorithm to establish effective sensor-actuator coupling.

Surface Plasmon Resonance Sensitivity Enhancement Based on Protonated Polyaniline Films Doped by Aluminum Nitrate

Complex composite films based on polyaniline (PANI) doped hydrochloric acid (HCl) incorporated with aluminum nitrate (Al(NO₃)₃) on Au-layer were designed and synthesized as a surface plasmon resonance (SPR) sensing device. The physicochemical properties of (PANI-HCl)/Al(NO₃)₃ complex composite films were studied for various Al(NO₃)₃ concentrations (0, 2, 4, 8, 16, and 32 wt.%). The refractive index of the (PANI-HCl)/Al(NO₃)₃ complex composite films increased continuously as Al(NO₃)₃ concentrations increased. The electrical conductivity values increased from 5.10 µS/cm to 10.00 µS/cm as Al(NO₃)₃ concentration increased to 32 wt.%. The sensitivity of the SPR sensing device was investigated using a theoretical approach and experimental measurements. The theoretical system of SPR measurement confirmed that increasing Al(NO₃)₃ in (PANI-HCl)/Al(NO₃)₃ complex composite films enhanced the sensitivity from about 114.5 [Deg/RIU] for Au-layer to 159.0 [Deg/RIU] for Au-((PANI-HCl)/Al(NO₃)₃ (32 wt.%)). In addition, the signal-to-noise ratio for Au-layer was 3.95, which increased after coating by (PANI-HCl)/Al(NO₃)₃ (32 wt.%) complex composite layer to 8.82. Finally, we conclude that coating Au-layer by (PANI-HCl)/Al(NO₃)₃ complex composite films enhances the sensitivity of the SPR sensing device.

Nanoparticle Determination in Water by LED-Excited Surface Plasmon Resonance Imaging

The increasing popularity of nanoparticles in many applications has led to the fact that these persistent materials pollute our environment and threaten our health. An online sensor system for monitoring the presence of nanoparticles in fresh water would be highly desired. We propose a label-free sensor based on SPR imaging. The sensitivity was enhanced by a factor of about 100 by improving the detector by using a high-resolution camera. This revealed that the light source also needed to be improved by using LED excitation instead of a laser light source. As a receptor, different self-assembled monolayers have been screened. It can be seen that the nanoparticle receptor interaction is of a complex nature. The best system when taking sensitivity as well as reversibility into account is given by a dodecanethiol monolayer on the gold sensor surface. Lanthanide-doped nanoparticles, 29 nm in diameter and with a similar refractive index to the most common silica nanoparticles were detected in water down to 1.5 µg mL−1. The sensor can be fully regenerated within one hour without the need for any washing buffer. This sensing concept is expected to be easily adapted for the detection of nanoparticles of different size, shape, and composition, and upon miniaturization, suitable for long-term applications to monitor the quality of water.

Advances in Optical Single-Molecule Detection: En Route to Supersensitive Bioaffinity Assays

The ability to detect low concentrations of analytes and in particular low-abundance biomarkers is of fundamental importance, e.g., for early-stage disease diagnosis. The prospect of reaching the ultimate limit of detection has driven the development of single-molecule bioaffinity assays. While many review articles have highlighted the potentials of single-molecule technologies for analytical and diagnostic applications, these technologies are not as widespread in real-world applications as one should expect. This Review provides a theoretical background on single-molecule-or better digital-assays to critically assess their potential compared to traditional analog assays. Selected examples from the literature include bioaffinity assays for the detection of biomolecules such as proteins, nucleic acids, and viruses. The structure of the Review highlights the versatility of optical single-molecule labeling techniques, including enzymatic amplification, molecular labels, and innovative nanomaterials.

Deep Learning Approach for Enhanced Detection of Surface Plasmon Scattering

A deep learning approach has been taken to improve detection characteristics of surface plasmon microscopy (SPM) of light scattering. Deep learning based on the convolutional neural network algorithm was used to estimate the effect of scattering parameters, mainly the number of scatterers. The improvement was assessed on a quantitative basis by applying the approach to SPM images formed by coherent interference of scatterers. It was found that deep learning significantly improves the accuracy over conventional detection: the enhancement in the accuracy was shown to be significantly higher by almost 6 times and useful for scattering by polydisperse mixtures. This suggests that deep learning can be used to find scattering objects effectively in the noisy environment. Furthermore, deep learning can be extended directly to label-free molecular detection assays and provide considerably improved detection in imaging and microscopy techniques.

NanoTiO2 Sunscreen Does Not Prevent Systemic Oxidative Stress Caused by UV Radiation and a Minor Amount of NanoTiO2 is Absorbed in Humans

The present pilot study tested the efficiency of nanoTiO₂ sunscreen to prevent the oxidative stress/inflammation caused by ultraviolet (UV) radiation using biomarkers in subjects’ blood, urine, and exhaled breath condensate (EBC). In addition, the skin absorption of nanoTiO₂ was studied. Six identical subjects participated in three tests: (A) nanoTiO₂ sunscreen, (B) UV radiation, and (C) sunscreen + UV. The first samples were collected before the test and the second after sunscreen application and/or UV exposure. On day 4, the third samples were collected, and the sunscreen was washed off, and the fourth samples were collected on day 11. The following biomarkers were measured: malondialdehyde, 4-hydroxy-trans-hexenal, 4-hydroxy-trans-nonenal, aldehydes C6-C12, 8-iso-Prostaglandin F2α, o-tyrosine, 3-chlorotyrosine, 3-nitrotyrosine, 8-hydroxy-2-deoxyguanosine, 8-hydroxyguanosine, 5-hydroxymethyl uracil, and leukotrienes, using liquid chromatography-electrospray ionisation-tandem mass spectrometry. Titania was measured using inductively coupled plasma mass spectrometry and TiO₂ nanoparticles by transmission and scanning electron microscopy. Sunscreen alone did not elevate the markers, but UV increased the biomarkers in the plasma, urine, and EBC. The sunscreen prevented skin redness, however it did not inhibit the elevation of oxidative stress/inflammatory markers. Titania and nanoTiO₂ particles were found in the plasma and urine (but not in the EBC) in all sunscreen users, suggesting their skin absorption.

Recent Advances in Surface Plasmon Resonance Imaging Sensors

The surface plasmon resonance (SPR) sensor is an important tool widely used for studying binding kinetics between biomolecular species. The SPR approach offers unique advantages in light of its real-time and label-free sensing capabilities. Until now, nearly all established SPR instrumentation schemes are based on single- or several-channel configurations. With the emergence of drug screening and investigation of biomolecular interactions on a massive scale these days for finding more effective treatments of diseases, there is a growing demand for the development of high-throughput 2-D SPR sensor arrays based on imaging. The so-called SPR imaging (SPRi) approach has been explored intensively in recent years. This review aims to provide an up-to-date and concise summary of recent advances in SPRi. The specific focuses are on practical instrumentation designs and their respective biosensing applications in relation to molecular sensing, healthcare testing, and environmental screening.

Identification of Nanoparticles via Plasmonic Scattering Interferometry

The development of optical imaging techniques has led to significant advancements in single-nanoparticle tracking and analysis, but these techniques are incapable of label-free selective nanoparticle recognition. A label-free plasmonic imaging technology that is able to identify different kinds of nanoparticles in water is now presented. It quantifies the plasmonic interferometric scattering patterns of nanoparticles and establishes relationships among the refractive index, particle size, and pattern both numerically and experimentally. Using this approach, metallic and metallic oxide particles with different radii were distinguished without any calibration. The ability to optically identify and size different kinds of nanoparticles can provide a promising platform for investigating nanoparticles in complex environments to facilitate nanoscience studies, such as single-nanoparticle catalysis and nanoparticle-based drug delivery.

Review of analytical studies on TiO2 nanoparticles and particle aggregation, coagulation, flocculation, sedimentation, stabilization

Titanium dioxide (TiO₂) nanoparticles (NPs) have been widely used in industrial and consumer products. Comprehensive and accurate detection, characterization, and quantification of TiO₂ NPs are important for understanding the specific property, behavior, fate, and potential risk of TiO₂ NPs in natural and engineered environments. This review provides a summary of recent analytical studies of TiO₂ NPs and their aggregation, coagulation, flocculation, sedimentation, stabilization under a wide range of conditions and processes. Much attention is paid on sample preparation prior to an analytical procedure, analysis of particle size, morphology, structure, state, chemical composition, surface properties, etc., via measurements of light scattering and zeta potential, microscopy, spectroscopy, and related techniques. Recently, some advanced techniques have also been explored to characterize TiO₂ NPs and their behaviors in the environment. Many issues must be considered including distinction between engineered TiO₂ NPs and their naturally occurring counterparts, lack of reference materials, interlaboratory comparison, when analyzing low concentrations of TiO₂ NPs and their behaviors in complex matrices. No "ideal" technique has emerged as each technique has its own merits, biases, and limitations. Multi-method approach is highlighted to provide in-depth information. Improvements of analytical method for determination of TiO₂ NPs have been recommended to be together with exposure modelers and ecotoxicologists for maximum individual and mutual benefit. Future work should focus on developing analytical technology with the advantages of being reliable, sensitive, selective, reproducible, and capable of in situ detection in complicated sample system.

Absolute Analysis of Nanoparticle Suspension with Surface Plasmon Microscopy

The recently developed surface plasmon microscopy of single nanoparticles offers a powerful tool for monitoring particle transfer from bulk solution to the adsorbing surface. In the present work, the possibility of absolute analysis of suspension, based on particle transfer observation, was examined. A model based on particle diffusion in a laminar flow, which allows analytical solution of mass transport equation, was considered. It was demonstrated that direct determination of particle concentration, based on counting the particles that bind to the sensor surface, is possible. The model contains only independent, easy to determine parameters: flow cell geometry, flow rate, particle size, and liquid viscosity. For applicability of the model, particles should be irreversibly bound when touching the sensor surface. It was demonstrated that the required "perfect binding" is provided in certain electrolyte concentration range because even particles oppositely charged to the surface do not bind in pure water. If the binding probability is less than 100%, "absoluteness" of the method is not violated. It will require the extension of the transport model with the sticking coefficient, which can be also measured by the surface plasmon microscopy directly. The present work shows the feasibility of the absolute analysis. It demonstrates the great potential of the method toward the comprehensive nanoparticle analytics and investigation of binding processes.

Imaging the chemical activity of single nanoparticles with optical microscopy

Chemical activity of single nanoparticles can be imaged and determined by monitoring the optical signal of each individual during chemical reactions with advanced optical microscopes. It allows for clarifying the functional heterogeneity among individuals, and for uncovering the microscopic reaction mechanisms and kinetics that could otherwise be averaged out in ensemble measurements.

Plasmonic detection and visualization of directed adsorption of charged single nanoparticles to patterned surfaces

It has recently been shown that surface plasmon microscopy (SPM) allows single nanoparticles (NPs) on sensor surfaces to be detected and analyzed. The authors have applied this technique to study the adsorption of single metallic and plastic NPs. Binding of gold NPs (40, 60 and 100 nm in size) and of 100 nm polystyrene NPs to gold surfaces modified by differently ω-functionalized alkyl thiols was studied first. Self-assembled monolayers (SAM) with varying terminal functions including amino, carboxy, oligo(ethylene glycol), methyl, or trimethylammonium groups were deposited on gold films to form surfaces possessing different charge and hydrophobicity. The affinity of NPs to these surfaces depends strongly on the type of coating. SAMs terminated with trimethylammonium groups and carboxy group display highly different affinity and therefore were preferred when creating patterned charged surfaces. Citrate-stabilized gold NPs and sulfate-terminated polystyrene NPs were used as negatively charged NPs, while branched polyethylenimine-coated silver NPs were used as positively charged NPs. It is shown that the charged patterned areas on the gold films are capable of selectively adsorbing oppositely charged NPs that can be detected and analyzed with an ~1 ng⋅mL⁻¹ detection limit.

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