Dark field nanoparticle tracking analysis for size characterization of plasmonic and non-plasmonic particles

Label-Free Light Scattering Imaging with Purified Brownian Motion Differentiates Small Extracellular Vesicles in Cell Microenvironments

Small extracellular vesicles (sEVs) are heterogeneous biological nanoparticles (NPs) with wide biomedicine applications. Tracking individual nanoscale sEVs can reveal information that conventional microscopic methods may lack, especially in cellular microenvironments. This usually requires biolabeling to identify single sEVs. Here, we developed a light scattering imaging method based on dark-field technology for label-free nanoparticle diffusion analysis (NDA). Compared with nanoparticle tracking analysis (NTA), our method was shown to determine the diffusion probabilities of a single NP. It was demonstrated that accurate size determination of NPs of 41 and 120 nm in diameter is achieved by purified Brownian motion (pBM), without or within the cell microenvironments. Our pBM method was also shown to obtain a consistent size estimation of the normal and cancerous plasma-derived sEVs without and within cell microenvironments, while cancerous plasma-derived sEVs are statistically smaller than normal ones. Moreover, we showed that the velocity and diffusion coefficient are key parameters for determining the diffusion types of the NPs and sEVs in a cancerous cell microenvironment. Our light scattering-based NDA and pBM methods can be used for size determination of NPs, even in cell microenvironments, and also provide a tool that may be used to analyze sEVs for many biomedical applications.

On-chip light sheet illumination for nanoparticle tracking in microfluidic channels

A simple and inexpensive method is presented to efficiently integrate light sheet illumination in a microfluidic chip for dark-field microscopic tracking and sizing of nanoparticles. The basic idea is to insert an optical fiber inside a polydimethylsiloxane (PDMS) elastomer microfluidic chip and use it as a cylindrical lens. The optical fiber is in this case no longer seen as only an optical waveguide but as a ready-made micro-optical component that is inexpensive and easy to source. Upon insertion, the optical fiber stretches the PDMS microchannel walls, which has two effects. The first effect is to tone down the intrinsic ripples in the PDMS that would otherwise create inhomogeneities in the light sheet illumination. The second effect is to remove any obliqueness of the channel wall and constrain it to be strictly perpendicular to the propagation of the illumination, avoiding the formation of a prismatic diopter. Through calculations, numerical simulations and measurements, we show that the optimal configuration consists in creating a slowly converging light sheet so that its axial thickness is almost uniform along the tracked area. The corresponding thickness was estimated at 12 μm, or 10 times the depth of field of the optical system. This leads to an at least six-fold increase in the signal-to-noise ratio compared to the case without the cylindrical lens. This original light-sheet configuration is used to track and size spherical gold nanoparticles with diameters of 80 nm and 50 nm.

Detectability of unresolved particles in off-axis digital holographic microscopy

Off-axis digital holographic microscopy (DHM) provides both amplitude and phase images, and so it may be used for label-free 3D tracking of micro- and nano-sized particles of different compositions, including biological cells, strongly absorbing particles, and strongly scattering particles. Contrast is provided by differences in either the real or imaginary parts of the refractive index (phase contrast and absorption) and/or by scattering. While numerous studies have focused on phase contrast and improving resolution in DHM, particularly axial resolution, absent have been studies quantifying the limits of detection for unresolved particles. This limit has important implications for microbial detection, including in life-detection missions for space flight. Here we examine the limits of detection of nanosized particles as a function of particle optical properties, microscope optics (including camera well depth and substrate), and data processing techniques and find that DHM provides contrast in both amplitude and phase for unresolved spheres, in rough agreement with Mie theory scattering cross-sections. Amplitude reconstructions are more useful than phase for low-index spheres and should not be neglected in DHM analysis.

On the thermal response of multiscale nanodomains formed in trans-anethol/ethanol/water surfactant-free microemulsion

HYPOTHESIS

Surfactant-free microemulsion (SFME), an emerging phenomenology that occurs in the monophasic zone of a broad category of ternary mixtures 'hydrophobe/hydrotrope/water', has attracted extensive interests due to their unique physicochemical properties. The potential of this kind of ternary fluid for solubilization and drug delivery make them promising candidates in many industrial scenarios.

EXPERIMENTS

Here the thermodynamic behavior of these multiscale nanodomains formed in the ternary trans-anethol/ethanol/water system over a wide range of temperatures is explored. The macroscopic physical properties of the ternary solutions are characterized, with revealing the temperature dependence of refractive index and dynamic viscosity.

FINDINGS

With increasing temperature, the ternary system shows extended areas in the monophasic zone. We demonstrate that the phase behavior and the multiscale nanodomains formed in the monophasic zone can be precisely and reversibly tuned by altering the temperature. Increasing temperature can destroy the stability of the multiscale nanodomains in equilibrium, with an exponential decay in the scattering light intensity. Nevertheless, molecular-scale aggregates and mesoscopic droplets exhibit significantly different response behaviors to temperature stimuli. The temperature-sensitive nature of the ternary SFME system provides a crucial step forward exploring and industrializing its stability.

Three-dimensional deep regression-based light scattering imaging system for nanoscale exosome analysis

Exosomes are extracellular vesicles that serve as promising intrinsic nanoscale biomarkers for disease diagnosis and treatment. Nanoparticle analysis technology is widely used in the field of exosome study. However, the common particle analysis methods are usually complex, subjective, and not robust. Here, we develop a three-dimensional (3D) deep regression-based light scattering imaging system for nanoscale particle analysis. Our system solves the problem of object focusing in common methods and acquires light scattering images of label-free nanoparticles as small as 41 nm in diameter. We develop a new method for nanoparticle sizing with 3D deep regression, where the 3D time series Brownian motion data of single nanoparticles are input as a whole, and sizes are output automatically for both entangled and untangled nanoparticles. Exosomes from the normal and cancer liver cell lineage cells are observed and automatically differentiated by our system. The 3D deep regression-based light scattering imaging system is expected to be widely used in the field of nanoparticle analysis and nanomedicine.

Dynamic multispectral detection of bacteria with nanoplasmonic markers

Culture-based diagnosis of bacterial diseases is a time-consuming technique that can lead not only to antibiotic resistance or bacterial mutation but also to fast-spreading diseases. Such mutations contribute to the fast deterioration of the patient's health and in some cases the death depending on the complexity of the infection. There is great interest in developing widely available molecular-level diagnostics that provide accurate and rapid diagnosis at the individual level and that do not require sophisticated analysis or expensive equipment. Here, we present a promising analytical approach to detect the presence of pathogenic bacteria based on their dynamic properties enhanced with nanoplasmonic biomarkers. These markers have shown greater photostability and biocompatibility compared to fluorescent markers and quantum dots, and serve as both a selective marker and an amplifying agent in optical biomedical detection. We show that a simple dark-field side- illumination technique can provide sufficiently high-contrast dynamic images of individual plasmonic nanoparticles attached to Escherichia coli (E. coli) for multiplex biodetection. Combined with numerical dynamic filtering, our proposed system shows great potential for the deployment of portable commercial devices for rapid diagnostic tests available to physicians in emergency departments, clinics and public hospitals as point-of-care devices.

Tunable 2D diffusion of DNA nanostructures on lipid membranes

DNA nanotechnology facilitates the synthesis of biomimetic models for studying biological systems. This work uses lipid bilayers as platforms for two-dimensional single-particle tracking of the dynamics of DNA nanostructures. Three different DNA origami structures adhere to the membrane through hybridization with cholesterol-modified strands. Their two-dimensional diffusion coefficient is modulated by changing the concentration of monovalent and divalent salts and the number of anchors. In addition, the diffusion coefficient is tuned by targeting cholesterol-modified anchor strands with strand-displacement reactions. We demonstrate a responsive system with changing diffusivity by selectively displacing membrane-bound anchor strands. We also show the programmed release of origami structures from the lipid membranes.

Coupling Effects of Ionic Surfactants and Electrolytes on the Stability of Bulk Nanobubbles

As interest in the extensive application of bulk nanobubbles increases, it is becoming progressively important to understand the key factors affecting their anomalous stability. The scientific intrigue over nanobubbles originates from the discrepancy between the Epstein-Plesset prediction and experimental observations. Herein, the coupling effects of ionic surfactants and electrolytes on the stability of bulk nanobubbles is studied. Experimental results show that ionic surfactants not only reduce the surface tension but also promote the accumulation of net charges, which facilitate the nucleation and stabilization of bulk nanobubbles. The addition of an electrolyte in a surfactant solution further results in a decrease in the zeta potential and the number concentration of nanobubbles due to the ion shielding effect, essentially colloidal stability. An adsorption model for the coexistence of ionic surfactants and electrolytes in solution, that specifically considers the effect of the adsorption layer thickness within the framework of the modified Poisson-Boltzmann equation, is developed. A quantitative agreement between the predicted and experimental surface tension is found in a wide range of bulk concentrations. The spatial distribution of the surface potential, surfactant ions and counterions in the vicinity of the interface of bulk nanobubbles are described. Our study intrinsically paves a route to investigate the stability of bulk nanobubbles.

MPTHub: An Open-Source Software for Characterizing the Transport of Particles in Biorelevant Media

The study of particle transport in different environments plays an essential role in understanding interactions with humans and other living organisms. Importantly, obtained data can be directly used for multiple applications in fields such as fundamental biology, toxicology, or medicine. Particle movement in biorelevant media can be readily monitored using microscopy and converted into time-resolved trajectories using freely available tracking software. However, translation into tangible and meaningful parameters is time consuming and not always intuitive. We developed new software—MPTHub—as an open-access, standalone, user-friendly tool for the rapid and reliable analysis of particle trajectories extracted from video microscopy. The software was programmed using Python and allowed to import and analyze trajectory data, as well as to export relevant data such as individual and ensemble time-averaged mean square displacements and effective diffusivity, and anomalous transport exponent. Data processing was reliable, fast (total processing time of less than 10 s), and required minimal memory resources (up to a maximum of around 150 MB in random access memory). Demonstration of software applicability was conducted by studying the transport of different polystyrene nanoparticles (100–200 nm) in mucus surrogates. Overall, MPTHub represents a freely available software tool that can be used even by inexperienced users for studying the transport of particles in biorelevant media.

Probing Diffusive Dynamics of Natural Tubule Nanoclays with Machine Learning

Reproducibility of the experimental results and object of study itself is one of the basic principles in science. But what if the object characterized by technologically important properties is natural and cannot be artificially reproduced one-to-one in the laboratory? The situation becomes even more complicated when we are interested in exploring stochastic properties of a natural system and only a limited set of noisy experimental data is available. In this paper we address these problems by exploring diffusive motion of some natural clays, halloysite and sepiolite, in a liquid environment. By using a combination of dark-field microscopy and machine learning algorithms, a quantitative theoretical characterization of the nanotubes' rotational diffusive dynamics is performed. Scanning the experimental video with the gradient boosting tree method, we can trace time dependence of the diffusion coefficient and probe different regimes of nonequilibrium rotational dynamics that are due to contacts with surfaces and other experimental imperfections. The method we propose is of general nature and can be applied to explore diffusive dynamics of various biological systems in real time.

Quantification of Motility in Bacillus subtilis at Temperatures Up to 84°C Using a Submersible Volumetric Microscope and Automated Tracking

We describe a system for high-temperature investigations of bacterial motility using a digital holographic microscope completely submerged in heated water. Temperatures above 90°C could be achieved, with a constant 5°C offset between the sample temperature and the surrounding water bath. Using this system, we observed active motility in Bacillus subtilis up to 66°C. As temperatures rose, most cells became immobilized on the surface, but a fraction of cells remained highly motile at distances of >100 μm above the surface. Suspended non-motile cells showed Brownian motion that scaled consistently with temperature and viscosity. A novel open-source automated tracking package was used to obtain 2D tracks of motile cells and quantify motility parameters, showing that swimming speed increased with temperature until ∼40°C, then plateaued. These findings are consistent with the observed heterogeneity of B. subtilis populations, and represent the highest reported temperature for swimming in this species. This technique is a simple, low-cost method for quantifying motility at high temperatures and could be useful for investigation of many different cell types, including thermophilic archaea.

Characterization of Nanoparticles in Diverse Mixtures Using Localized Surface Plasmon Resonance and Nanoparticle Tracking by Dark-Field Microscopy with Redox Magnetohydrodynamics Microfluidics

Redox magnetohydrodynamics (RMHD) microfluidics is coupled with dark-field microscopy (DFM) to offer high-throughput single-nanoparticle (NP) differentiation in situ and operando in a flowing mixture by localized surface plasmon resonance (LSPR) and tracking of NPs. The color of the scattered light allows visualization of the NPs below the diffraction limit. Their Brownian motion in 1-D superimposed on and perpendicular to the RMHD trajectory yields their diffusion coefficients. LSPR and diffusion coefficients provide two orthogonal modalities for characterization where each depends on a particle’s material composition, shape, size, and interactions with the surrounding medium. RMHD coupled with DFM was demonstrated on a mixture of 82 ± 9 nm silver and 140 ± 10 nm gold-coated silica nanospheres. The two populations of NPs in the mixture were identified by blue/green and orange/red LSPR and their scattering intensity, respectively, and their sizes were further evaluated based on their diffusion coefficients. RMHD microfluidics facilitates high-throughput analysis by moving the sample solution across the wide field of view absent of physical vibrations within the experimental cell. The well-controlled pumping allows for a continuous, reversible, and uniform flow for precise and simultaneous NP tracking of the Brownian motion. Additionally, the amounts of nanomaterials required for the analysis are minimized due to the elimination of an inlet and outlet. Several hundred individual NPs were differentiated from each other in the mixture flowing in forward and reverse directions. The ability to immediately reverse the flow direction also facilitates re-analysis of the NPs, enabling more precise sizing.

Ion adsorption stabilizes bulk nanobubbles

The mechanism leading to the extraordinary stability of bulk nanobubbles in aqueous solutions remains an outstanding problem in soft matter, modern surface science, and physical chemistry science. In this work, the stability of bulk nanobubbles in electrolyte solutions under different pH levels and ionic strengths is studied. Nanobubbles are generated via the technique of ultrasonic cavitation, and characterized for size, number concentration and zeta potential under ambient conditions. Experimental results show that nanobubbles can survive in both acidic and basic solutions with pH values far away from the isoelectric point. We attribute the enhanced stability with increasing acidity or alkalinity of the aqueous solutions to the effective accumulation of net charges, regardless of their sign. The kinetic stability of the nanobubbles in various aqueous solutions is evaluated within the classic DLVO framework. Further, by combining a modified Poisson-Boltzmann equation with a modified Langmuir adsorption model, we describe a simple model that captures the influence of ion species and bulk concentration and reproduce the dependence of the nanobubble's surface potential on pH. We also discuss the apparent contradiction between quantitative calculation by ion stabilization model and experimental results. This essentially requires insight into the structure and dynamics of interfacial water on the atomic-scale.

Laser-induced convection shifts size distributions in nanoparticle tracking analysis

This work discusses the effects of increasing laser power on the size data derived from NTA for particles of known size and scatterers in solutions of flufenamic acid in ethanol. We find that whilst a higher laser power reveals more particles as expected, their residence time changes due to laser-induced convection. This reduced residence time decreases the number of tracks available for individual particle size determination, shifting the size distribution to smaller values. This problem is overcome by using a shutter to inhibit the development of convection currents, increasing particle residence time and reducing the error on the size distribution. The detailed understanding of laser-induced convection permits more robust size characterisation of mesoscopic organic clusters, which play a key role in two-step nucleation theory.

Hyperspectral-enhanced dark field analysis of individual and collective photo-responsive gold-copper sulfide nanoparticles

We used hyperspectral-enhanced dark field microscopy for studying physicochemical changes in biomaterials by tracking their unique spectral signatures along their pathway through different biological environments typically found in any biomedical application. We correlate these spectral signatures with discrete environmental features causing changes in nanoparticles' physicochemical properties. We use this correlation to track the nanoparticles intracellularly and to assess the impact of these changes on their functionality. We focus on one example of a photothermal nanocomposite, i.e., polymer-coated gold/copper sulfide nanoparticles, because their performance depends on their localized surface plasmon peak, which is highly sensitive to environmental changes. We found spectral differences both in the dependence of time and discrete environmental factors, affecting the range of illumination wavelengths that can be used to activate the functionality of these types of nanoparticles. The presence of proteins (protein corona) and the increase in ionic strength induce a spectral broadening towards the NIR region which we associated with nanoparticles' agglomeration. In acidic environments, such as that of the lysosome, a red shift was also observed in addition to a decrease in the scattering intensity probably associated with a destabilization of the proteins and/or the change in the net charge of the polymer around the nanoparticles. We observed a loss of the photo-excitation potential of those nanoparticles exposed to acidic conditions in the <600 nm spectral rage. In a similar manner, ageing induces a transitioning from a broad multipeak spectrum to a distinct shoulder with time (up to 8 months) with the loss of spectral contribution in the 450-600 nm range. Hence, a fresh preparation of nanoparticles before their application would be recommended for an optimal performance. We highlight the impact of ageing and the acidic environment on the responsiveness of this type of plasmonic nanoparticle. Regardless of the spectral differences found, polymer-coated gold/copper sulfide nanoparticles retained their photothermal response as demonstrated in vitro upon two-photon irradiation. This could be ascribed to their robust geometry provided by the polymer coating. These results should be useful to rationally design plasmonic photothermal probes.

Microscopic Object Classification through Passive Motion Observations with Holographic Microscopy

Digital holographic microscopy provides the ability to observe throughout a volume that is large compared to its resolution without the need to actively refocus to capture the entire volume. This enables simultaneous observations of large numbers of small objects within such a volume. We have constructed a microscope that can observe a volume of 0.4 µm × 0.4 µm × 1.0 µm with submicrometer resolution (in xy) and 2 µm resolution (in z) for observation of microorganisms and minerals in liquid environments on Earth and on potential planetary missions. Because environmental samples are likely to contain mixtures of inorganics and microorganisms of comparable sizes near the resolution limit of the instrument, discrimination between living and non-living objects may be difficult. The active motion of motile organisms can be used to readily distinguish them from non-motile objects (live or inorganic), but additional methods are required to distinguish non-motile organisms and inorganic objects that are of comparable size but different composition and structure. We demonstrate the use of passive motion to make this discrimination by evaluating diffusion and buoyancy characteristics of cells, styrene beads, alumina particles, and gas-filled vesicles of micron scale in the field of view.

A review of microplastics aggregation in aquatic environment: Influence factors, analytical methods, and environmental implications

A large amount of plastic waste released into natural waters and their demonstrated toxicity have made the transformation of microplastics (MPs; < 5 mm) and nanoplastics (NPs; < 100 nm) an emerging environmental concern. Aggregation is one of the most important environmental behaviors of MPs, especially in aquatic environments, which determines the mobility, distribution and bioavailability of MPs. In this paper, the sources and inputs of MPs in aquatic environments were first summarized followed by the analytical methods for investigating MP aggregation, including the sampling, visualization, and quantification procedures of MP' particle sizes. We critically evaluated the sampling methods that still remains a methodological gap. Identification and quantification of MPs were mostly carried out by visual, spectroscopic and spectrometric techniques, and modeling analysis. Important factors affecting MP aggregation in natural waters and environmental implications of the aggregation process were also reviewed. Finally, recommendations for future research were discussed, including (1) conducting more field studies; (2) using MPs in laboratory works representing those in the environment; and (3) standardizing methods of identification and quantification. The review gives a comprehensive overview of current knowledge for MP aggregation in natural waters, identifies knowledge gaps, and provides suggestions for future research.

Plasmonic nano-aperture label-free imaging (PANORAMA)

Label-free optical imaging of nanoscale objects faces fundamental challenges. Techniques based on propagating surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR) have shown promises. However, challenges remain to achieve diffraction-limited resolution and better surface localization in SPR imaging. LSPR imaging with dark-field microscopy on metallic nanostructures suffers from low light throughput and insufficient imaging capacity. Here we show ultra-near-field index modulated PlAsmonic NanO-apeRture lAbel-free iMAging (PANORAMA) which uniquely relies on unscattered light to detect sub-100 nm dielectric nanoparticles. PANORAMA provides diffraction-limited resolution, higher surface sensitivity, and wide-field imaging with dense spatial sampling. Its system is identical to a standard bright-field microscope with a lamp and a camera – no laser or interferometry is needed. In a parallel fashion, PANORAMA can detect, count and size individual dielectric nanoparticles beyond 25 nm, and dynamically monitor their distance to the plasmonic surface at millisecond timescale.

Here, the authors report on an imaging method based on localized surface plasmon resonance excitation, employing gold nanodisk arrays as substrates that enable imaging of transparent dielectric particles of several sizes. They demonstrate the ability to detect and image particles smaller than the diffraction limit at 25 nm with standard bright-field imaging.

Lensless, reflection-based dark-field microscopy (RDFM) on a CMOS chip

We present for the first time a lens-free, oblique illumination imaging platform for on-sensor dark- field microscopy and shadow-based 3D object measurements. It consists of an LED point source that illuminates a 5-megapixel, 1.4 µm pixel size, back-illuminated CMOS sensor at angles between 0° and 90°. Analytes (polystyrene beads, microorganisms, and cells) were placed and imaged directly onto the sensor. The spatial resolution of this imaging system is limited by the pixel size (∼1.4 µm) over the whole area of the sensor (3.6×2.73 mm). We demonstrated two imaging modalities: (i) shadow imaging for estimation of 3D object dimensions (on polystyrene beads and microorganisms) when the illumination angle is between 0° and 85°, and (ii) dark-field imaging, at >85° illumination angles. In dark-field mode, a 3-4 times drop in background intensity and contrast reversal similar to traditional dark-field imaging was observed, due to larger reflection intensities at those angles. With this modality, we were able to detect and analyze morphological features of bacteria and single-celled algae clusters.

Single-Particle Tracking with Scanning Non-Linear Microscopy

This study describes the adaptation of non-linear microscopy for single-particle tracking (SPT), a method commonly used in biology with single-photon fluorescence. Imaging moving objects with non-linear microscopy raises difficulties due to the scanning process of the acquisitions. The interest of the study is based on the balance between all the experimental parameters (objective, resolution, frame rate) which need to be optimized to record long trajectories with the best accuracy and frame rate. To evaluate the performance of the setup for SPT, several basic estimation methods are used and adapted to the new detection process. The covariance-based estimator (CVE) seems to be the best way to evaluate the diffusion coefficient from trajectories using the specific factors of motion blur and localization error.

High-Resolution Nanoparticle Sizing with Maximum A Posteriori Nanoparticle Tracking Analysis

The rapid and efficient characterization of polydisperse nanoparticle dispersions remains a challenge within nanotechnology and biopharmaceuticals. Current methods for particle sizing, such as dynamic light scattering, analytical ultracentrifugation, and field-flow fractionation, can suffer from a combination of statistical biases, difficult sample preparation, insufficient sampling, and ill-posed data analysis. As an alternative, we introduce a Bayesian method that we call maximum a posteriori nanoparticle tracking analysis (MApNTA) for estimating the size distributions of nanoparticle samples from high-throughput single-particle tracking experiments. We derive unbiased statistical models for two observable quantities in a typical nanoparticle trajectory-the mean square displacement and the trajectory length-as a function of the particle size and calculate size distributions using maximum a posteriori (MAP) estimation with cross validation to mildly regularize solutions. We show that this approach infers nanoparticle size distributions with high resolution by performing extensive Brownian dynamics simulations and experiments with mono- and polydisperse solutions of gold nanoparticles as well as single-walled carbon nanotubes. We further demonstrate particular utility for characterizing minority components and impurity populations and highlight this ability with the identification of an impurity in a commercially produced gold nanoparticle sample. Modern algorithms such as MApNTA should find widespread use in the routine characterization of complex nanoparticle dispersions, allowing for significant advances in nanoparticle synthesis, separation, and functionalization.

Light-Scattering Sizing of Single Submicron Particles by High-Sensitivity Flow Cytometry

Rapid and reliable size measurement of single submicron particles (100-1000 nm) is important for quality control of particulate matter, biomedical research, environmental study, and drug delivery system development. Though direct measurement of the elastically scattered light from individual submicron particles represents the simplest method for particle size measurement, the inadequate instrument sensitivity and complicated relationship between scattering intensity and particle size render it a great challenge. Combining the superior sensitivity of a laboratory-built high-sensitivity flow cytometer (HSFCM) in the side scattering (SSC) detection of single nanoparticles and the great efforts in synthesizing 38 highly monodisperse silica spheres ranging from 180 to 880 nm with small size intervals, here we report the first comprehensive comparison between the experimentally measured and Mie theory calculated intensities of light scattered by single submicron particles. Good agreements were observed for both the silica spheres and polystyrene beads at both the perpendicular and the parallel polarizations of the incident laser beam. Compared with perpendicular polarization, parallel polarization can resolve differently sized beads better due to the continuously increased scattering intensity with particle size. The predictive capability of the simple numerical model constructed in present work can be exploited to allow us to foresee scattering behavior on flow cytometers. More importantly, the linear correlation between the measured and the calculated scattering intensities enables us to develop a method that can measure the particle size of submicron particles with the precision and accuracy of Mie theory rather than a calibration curve fitted by several sparsely separated size reference standards. Comparable sizing resolution and accuracy to those of electron microscopy were demonstrated for Gram-positive bacteria Staphylococcus aureus. The as-developed method shows great potential in guiding the accurate size measurement of submicron particles.

A platform for assessing outer segment fate in primary human fetal RPE cultures

The daily shedding and renewal of photoreceptor outer segments (OS) is critical for maintaining vision. This process relies on the efficient uptake, degradation, and sorting of shed OS material by the retinal pigment epithelium (RPE). Poor OS degradation has been linked to retinal degenerations such as Stargardt disease and may contribute to macular degeneration. While primary human fetal RPE cultures have emerged as a valuable model of in vivo human RPE function, surprisingly few studies have utilized the model for tracking the degradation and fate of OS components in the RPE. Here, we establish an improved platform for studying this topic by modifying existing protocols and creating new methods. Our human fetal culture model facilitates studies of RPE secretion in response to OS ingestion, preserves RPE differentiation and polarization during live-cell imaging of OS phagocytosis, and minimizes costs. We optimize Mer tyrosine kinase-dependent OS phagocytosis assays specifically in human fetal cultures and provide a simple and accurate method for measuring total OS consumption by the RPE. Finally, we utilize chemical transfection, dextran labeling, and immunocytochemistry to evaluate key players in OS degradation, including lysosomes and autophagy proteins. To facilitate quantification of autophagy vesicles, we develop customized image analysis macros in the Fiji/ImageJ software environment. These protocols will facilitate a broad range of studies in human fetal RPE cultures aimed at determining the ultimate fate of OS components after ingestion, a critical step in understanding the pathogenesis of numerous retinal diseases.

Core-shell assay based aptasensor for sensitive and selective thrombin detection using dark-field microscopy

In this work, we developed a robust and ultrasensitive bio-sensor based on the target-aptamer recognition strategy and microscopic enumeration of gold nanoparticles (AuNPs) using dark field microscopy (DFM). The aptasensor with a core-shell structure consisting of a magnetic bead (MB), aptamer and AuNPs was fabricated by complementary hybridization of the DNA probe on the AuNPs surface to the aptamer coupled to the MB. Upon addition of the target molecule, the strong interaction between the aptamer and the target molecule, thrombin, results in the release of the AuNPs from the MB. The quantities of thrombin is therefore linearly correlated to the number of the released AuNPs, which can be digitally counted using DFM. To demonstrate the feasible use of the aptasensor for target detection, thrombin was evaluated as the model target. The limit of detection was determined to be 2.54 fM with dynamic range of 6 fM-100 fM. When the concentration of thrombin exceeded 100 fM, the counted number of AuNPs didn't correlate linearly to molecules of thrombin anymore, as the nanoparticles aggregated partly due to high concentration. However, the color of the solution changes to purple and the concentration of free AuNPs can be conveniently quantified by UV-Vis spectroscopy for up to 100 nM. It is noteworthy that our aptasensor is very easy to operate and requires neither complex isolation and amplification processes nor expensive instruments and consumables. Furthermore, this strategy can be easily generalized to other targets by replacing the corresponding aptamers and show great potential for the detection of biomarkers in clinical samples.

A low cost mobile phone dark-field microscope for nanoparticle-based quantitative studies

Dark-field microscope (DFM) analysis of nanoparticle binding signal is highly useful for a variety of research and biomedical applications, but current applications for nanoparticle quantification rely on expensive DFM systems. The cost, size, limited robustness of these DFMs limits their utility for non-laboratory settings. Most nanoparticle analyses use high-magnification DFM images, which are labor intensive to acquire and subject to operator bias. Low-magnification DFM image capture is faster, but is subject to background from surface artifacts and debris, although image processing can partially compensate for background signal. We thus mated an LED light source, a dark-field condenser and a 20× objective lens with a mobile phone camera to create an inexpensive, portable and robust DFM system suitable for use in non-laboratory conditions. This proof-of-concept mobile DFM device weighs less than 400g and costs less than $2000, but analysis of images captured with this device reveal similar nanoparticle quantitation results to those acquired with a much larger and more expensive desktop DFMM system. Our results suggest that similar devices may be useful for quantification of stable, nanoparticle-based activity and quantitation assays in resource-limited areas where conventional assay approaches are not practical.

Oxygen Nanobubble Tracking by Light Scattering in Single Cells and Tissues

Oxygen nanobubbles (ONBs) have significant potential in targeted imaging and treatment in cancer diagnosis and therapy. Precise localization and tracking of single ONBs is demonstrated based on hyperspectral dark-field microscope (HSDFM) to image and track single oxygen nanobubbles in single cells. ONBs were proposed as promising contrast-generating imaging agents due to their strong light scattering generated from nonuniformity of refractive index at the interface. With this powerful platform, we have revealed the trajectories and quantities of ONBs in cells, and demonstrated the relation between the size and diffusion coefficient. We have also evaluated the presence of ONBs in the nucleus with respect to an increase in incubation time and have quantified the uptake in single cells in ex vivo tumor tissues. Our results demonstrate that HSDFM can be a versatile platform to detect and measure cellulosic nanoparticles at the single-cell level and to assess the dynamics and trajectories of this delivery system.

Noise Reduction Method for Quantifying Nanoparticle Light Scattering in Low Magnification Dark-Field Microscope Far-Field Images

Nanoparticles have become a powerful tool for cell imaging and biomolecule, cell and protein interaction studies, but are difficult to rapidly and accurately measure in most assays. Dark-field microscope (DFM) image analysis approaches used to quantify nanoparticles require high-magnification near-field (HN) images that are labor intensive due to a requirement for manual image selection and focal adjustments needed when identifying and capturing new regions of interest. Low-magnification far-field (LF) DFM imagery is technically simpler to perform but cannot be used as an alternate to HN-DFM quantification, since it is highly sensitive to surface artifacts and debris that can easily mask nanoparticle signal. We now describe a new noise reduction approach that markedly reduces LF-DFM image artifacts to allow sensitive and accurate nanoparticle signal quantification from LF-DFM images. We have used this approach to develop a "Dark Scatter Master" (DSM) algorithm for the popular NIH image analysis program ImageJ, which can be readily adapted for use with automated high-throughput assay analyses. This method demonstrated robust performance quantifying nanoparticles in different assay formats, including a novel method that quantified extracellular vesicles in patient blood sample to detect pancreatic cancer cases. Based on these results, we believe our LF-DFM quantification method can markedly decrease the analysis time of most nanoparticle-based assays to impact both basic research and clinical analyses.

Enzyme catalysis enhanced dark-field imaging as a novel immunohistochemical method

Conventional immunohistochemistry is limited to subjective judgment based on human experience and thus it is clinically required to develop a quantitative immunohistochemical detection. 3,3'-Diaminobenzidin (DAB) aggregates, a type of staining product formed by conventional immunohistochemistry, were found to have a special optical property of dark-field imaging for the first time, and the mechanism was explored. On this basis, a novel immunohistochemical method based on dark-field imaging for detecting HER2 overexpressed in breast cancer was established, and the quantitative analysis standard and relevant software for measuring the scattering intensity was developed. In order to achieve a more sensitive detection, the HRP (horseradish peroxidase)-labeled secondary antibodies conjugated gold nanoparticles were constructed as nanoprobes to load more HRP enzymes, resulting in an enhanced DAB deposition as a dark-field label. Simultaneously, gold nanoparticles also act as a synergistically enhanced agent due to their mimicry of enzyme catalysis and dark-field scattering properties.