Dual-Angle Interferometric Scattering Microscopy for Optical Multiparametric Particle Characterization.

Traditional single-nanoparticle sizing using optical microscopy techniques assesses size via the diffusion constant, which requires suspended particles to be in a medium of known viscosity. However, these assumptions are typically not fulfilled in complex natural sample environments. Here, we introduce dual-angle interferometric scattering microscopy (DAISY), enabling optical quantification of both size and polarizability of individual nanoparticles (radius <170 nm) without requiring a priori information regarding the surrounding media or super-resolution imaging. DAISY achieves this by combining the information contained in concurrently measured forward and backward scattering images through twilight off-axis holography and interferometric scattering (iSCAT). Going beyond particle size and polarizability, single-particle morphology can be deduced from the fact that the hydrodynamic radius relates to the outer particle radius, while the scattering-based size estimate depends on the internal mass distribution of the particles. We demonstrate this by differentiating biomolecular fractal aggregates from spherical particles in fetal bovine serum at the single-particle level.

Diffusion of Lipid Nanovesicles Bound to a Lipid Membrane Is Associated with the Partial-Slip Boundary Condition.

During diffusion of nanoparticles bound to a cellular membrane by ligand-receptor pairs, the distance to the laterally mobile interface is sufficiently short for their motion to depend not only on the membrane-mediated diffusivity of the tethers but also in a not yet fully understood manner on nanoparticle size and interfacial hydrodynamics. By quantifying diffusivity, velocity, and size of individual membrane-bound liposomes subjected to a hydrodynamic shear flow, we have successfully separated the diffusivity contributions from particle size and number of tethers. The obtained diffusion-size relations for synthetic and extracellular lipid vesicles are not well-described by the conventional no-slip boundary condition, suggesting partial slip as well as a significant diffusivity dependence on the distance to the lipid bilayer. These insights, extending the understanding of diffusion of biological nanoparticles at lipid bilayers, are of relevance for processes such as cellular uptake of viruses and lipid nanoparticles or labeling of cell-membrane-residing molecules.

Characteristic heterotopic ossification of the proximal humerus after total shoulder arthroplasty.

OBJECTIVE: A bony spur in a characteristic location involving the proximal humerus is identified on post-operative radiographs in some patients with history of total shoulder arthroplasty. The spur is theorized to represent heterotopic ossification near the attachment site of the pectoralis major tendon on the proximal humerus which is partially detached and then reattached during total shoulder arthroplasty. In this study, we determine the morphology, incidence, demographic associations, and clinical impact of this finding. MATERIALS AND METHODS: This is a single-center, retrospective study of 500 patients who underwent total shoulder arthroplasty (250 standard and 250 reverse technique) between 2012 and 2017. Pre- and post-operative shoulder radiographs were reviewed to identify and measure the characteristic spur; inter-observer agreement was evaluated between the two reviewers. Incidence, demographic associations, and clinical significance were then determined. RESULTS: The study group included 268 men and 234 women with a mean age of 70 (42-89) years, and clinical follow-up of 25 (1-84) months. Characteristic heterotopic ossification was seen in 88 patients (17.6%) and was first noted radiographically at a mean (interquartile range) of 12.1 (11.5-12.8) months after surgery. Male sex (adjusted odds ratio (95% confidence interval), 3.00 (0.68-5.34), p < 0.001) was independently associated with heterotopic ossification. No significant relationships between heterotopic ossification and adverse clinical outcomes were observed. CONCLUSION: Characteristic heterotopic ossification of the proximal humerus in patients status post total shoulder arthroplasty is a common imaging finding that is not associated with adverse clinical outcomes.

FRET-Based Assay for the Quantification of Extracellular Vesicles and Other Vesicles of Complex Composition.

Research in the field of extracellular vesicles is rapidly expanding and finding footholds in many areas of medical science. However, the availability of methodologies to quantify the concentration of membrane material present in a sample remains limited. Herein, we present a novel approach for the quantification of vesicle material, specifically the quantification of the total lipid membrane surface area, found in a sample using Förster resonance energy transfer (FRET). In this assay, sonication is used to drive the fusion between vesicles in the sample to be quantified and liposomes containing a pair of FRET fluorophores. The change in emission spectrum upon vesicle fusion is directly related to the total membrane surface area of the sample added, and a calibration curve allows for the quantification of a variety of vesicle species, including enveloped viruses, bacterial outer membrane vesicles, and mammalian extracellular vesicles. Without extensive optimization of experimental parameters, we were able to quantify down to ∼109 vesicles/mL, using as little as 60 µL of the sample. The assay precision was comparable to that of a commercial nanoparticle tracking analysis system. While its limit of detection was slightly higher, the FRET assay is superior for the detection of small vesicles, as its performance is vesicle-size-independent. Taken together, the FRET assay is a simple, robust, and versatile method for the quantification of a variety of purified vesicle samples.

Size and Refractive Index Determination of Subwavelength Particles and Air Bubbles by Holographic Nanoparticle Tracking Analysis.

Determination of size and refractive index (RI) of dispersed unlabeled subwavelength particles is of growing interest in several fields, including biotechnology, wastewater monitoring, and nanobubble preparations. Conventionally, the size distribution of such samples is determined via the Brownian motion of the particles, but simultaneous determination of their RI remains challenging. This work demonstrates nanoparticle tracking analysis (NTA) in an off-axis digital holographic microscope (DHM) enabling determination of both particle size and RI of individual subwavelength particles from the combined information about size and optical phase shift. The potential of the method to separate particle populations is demonstrated by analyzing a mixture of three types of dielectric particles within a narrow size range, where conventional NTA methods based on Brownian motion alone would fail. Using this approach, the phase shift allowed individual populations of dielectric beads overlapping in either size or RI to be clearly distinguished and quantified with respect to these properties. The method was furthermore applied for analysis of surfactant-stabilized micro- and nanobubbles, with RI lower than that of water. Since bubbles induce a phase shift of opposite sign to that of solid particles, they were easily distinguished from similarly sized solid particles made up of undissolved surfactant. Surprisingly, the dependence of the phase shift on bubble size indicates that only those with 0.15-0.20 µm radius were individual bubbles, whereas larger bubbles were actually clusters of bubbles. This label-free means to quantify multiple parameters of suspended individual submicrometer particles offers a crucial complement to current characterization strategies, suggesting broad applicability for a wide range of nanoparticle systems.

Visualizing Spatial Variations of Plasmon-Exciton Polaritons at the Nanoscale Using Electron Microscopy.

Polaritons are compositional light-matter quasiparticles that have enabled remarkable breakthroughs in quantum and nonlinear optics, as well as in material science. Recently, plasmon-exciton polaritons (plexcitons) have been realized in hybrid material systems composed of transition metal dichalcogenide (TMDC) materials and metal nanoparticles, expanding polaritonic concepts to room temperature and nanoscale systems that also benefit from the exotic properties of TMDC materials. Despite the enormous progress in understanding TMDC-based plexcitons using optical-based methods, experimental evidence of plexcitons formation has remained indirect and mapping their nanometer-scale characteristics has remained an open challenge. Here, we demonstrate that plexcitons generated by a hybrid system composed of an individual silver nanoparticle and a few-layer WS2 flake can be spectroscopically mapped with nanometer spatial resolution using electron energy loss spectroscopy in a scanning transmission electron microscope. Experimental anticrossing measurements using the absorption-dominated extinction signal provide the ultimate evidence for plexciton hybridization in the strong coupling regime. Spatially resolved EELS maps reveal the existence of unexpected nanoscale variations in the deep-subwavelength nature of plexcitons generated by this system. These findings pioneer new possibilities for in-depth studies of the local atomic structure dependence of polariton-related phenomena in TMDC hybrid material systems with nanometer spatial resolution.

Neutron Drip Line in the Ca Region from Bayesian Model Averaging.

The region of heavy calcium isotopes forms the frontier of experimental and theoretical nuclear structure research where the basic concepts of nuclear physics are put to stringent test. The recent discovery of the extremely neutron-rich nuclei around ^{60}Ca O. B. Tarasov et al. [Phys. Rev. Lett. 121, 022501 (2018)10.1103/PhysRevLett.121.022501] and the experimental determination of masses for ^{55-57}Ca S. Michimasa et al. [Phys. Rev. Lett. 121, 022506 (2018)10.1103/PhysRevLett.121.022506] provide unique information about the binding energy surface in this region. To assess the impact of these experimental discoveries on the nuclear landscape's extent, we use global mass models and statistical machine learning to make predictions, with quantified levels of certainty, for bound nuclides between Si and Ti. Using a Bayesian model averaging analysis based on Gaussian-process-based extrapolations we introduce the posterior probability p_{ex} for each nucleus to be bound to neutron emission. We find that extrapolations for drip-line locations, at which the nuclear binding ends, are consistent across the global mass models used, in spite of significant variations between their raw predictions. In particular, considering the current experimental information and current global mass models, we predict that ^{68}Ca has an average posterior probability p_{ex}≈76% to be bound to two-neutron emission while the nucleus ^{61}Ca is likely to decay by emitting a neutron (p_{ex}≈46%).

The limits of the nuclear landscape.

In 2011, 100 new nuclides were discovered. They joined the approximately 3,000 stable and radioactive nuclides that either occur naturally on Earth or are synthesized in the laboratory. Every atomic nucleus, characterized by a specific number of protons and neutrons, occupies a spot on the chart of nuclides, which is bounded by 'drip lines' indicating the values of neutron and proton number at which nuclear binding ends. The placement of the neutron drip line for the heavier elements is based on theoretical predictions using extreme extrapolations, and so is uncertain. However, it is not known how uncertain it is or how many protons and neutrons can be bound in a nucleus. Here we estimate these limits of the nuclear 'landscape' and provide statistical and systematic uncertainties for our predictions. We use nuclear density functional theory, several Skyrme interactions and high-performance computing, and find that the number of bound nuclides with between 2 and 120 protons is around 7,000. We find that extrapolations for drip-line positions and selected nuclear properties, including neutron separation energies relevant to astrophysical processes, are very consistent between the models used.

Electrophoretic Deposition Interferometric Scattering Mass Photometry.

Interferometric scattering microscopy (iSCAT) has rapidly developed as a quantitative tool for the label-free detection of single macromolecules and nanoparticles. In practice, this measurement records the interferometric scattering signal of individual nanoparticles in solution as they land and stick on a coverslip, exhibiting an intensity that varies linearly with particle volume and an adsorption rate that reflects the solution-phase transport kinetics of the system. Together, such measurements provide a multidimensional gauge of the particle size and concentration in solution over time. However, the landing kinetics of particles in solution also manifest a measurement frequency limitation imposed by the slow long-range mobility of particle diffusion to the measurement interface. Here we introduce an effective means to overcome the inherent diffusion-controlled sampling limitation of spontaneous mass photometry. We term this methodology electrophoretic deposition interferometric scattering microscopy (EPD-iSCAT). This approach uses a coverslip supporting a conductive thin film of indium tin oxide (ITO). Charging this ITO film to a potential of around +1 V electrophoretically draws charged nanoparticles from solution and binds them in the focal plane of the microscope. Regulating this potential offers a direct means of controlling particle deposition. Thus, we find for a 0.1 nM solution of 50 nm polystyrene nanoparticles that the application of +1 V to an EPD-iSCAT coverslip assembly drives an electrophoretic deposition rate constant of 1.7 s-1 µm-2 nM-1. Removal of the potential causes deposition to cease. This user control of EPD-iSCAT affords a means to apply single-molecule mass photometry to monitor long-term changes in solution, owing to slow kinetic processes. In contrast with conventional coverslips chemically derivatized with charged thin films, EPD-iSCAT maintains a deposition rate that varies linearly with the bulk concentration.

Studying the Feasibility and Acceptability of an Interactive Web-based Lethal Means Safety Decision Aid for Hospitalized Adults With Suicide Risk (Lock to Live).

OBJECTIVE: Lock to Live is an interactive web-based lethal means safety decision aid that promotes temporary storage of firearms and medications. It has primarily been provided to suicidal patients in emergency department settings. The goal of this study was to evaluate the feasibility and acceptability of the Lock to Live decision aid with hospitalized adults at increased risk of suicide. METHODS: Subjects provided demographic information and completed the Columbia-Suicide Severity Rating Scale after which they completed the Lock to Live program followed by a survey. RESULTS: Twenty participants were recruited for this study, 5 of whom had access to firearms and 19 of whom had access to medications. Lock to Live was feasible to use as the mean length of time to complete the program was 10.0±5.3 minutes. It was acceptable to most participants as 75% of participants found it to be easy to use, and 65% of participants agreed that Lock to Live was helpful in making a decision about changing access to firearms/medications. CONCLUSION: Lock 2 Live decision aid appears to be a feasible and acceptable tool for hospitalized patients at risk for suicide.

Integrated ocean management as a strategy to meet rapid climate change: the Norwegian case.

The prospects of rapid climate change and the potential existence of tipping points in marine ecosystems where nonlinear change may result from them being overstepped, raises the question of strategies for coping with ecosystem change. There is broad agreement that the combined forces of climate change, pollution and increasing economic activities necessitates more comprehensive approaches to oceans management, centering on the concept of ecosystem-based oceans management. This article addresses the Norwegian experience in introducing integrated, ecosystem-based oceans management, emphasizing how climate change, seen as a major long-term driver of change in ecosystems, is addressed in management plans. Understanding the direct effects of climate variability and change on ecosystems and indirect effects on human activities is essential for adaptive planning to be useful in the long-term management of the marine environment.

Single-shot self-supervised object detection in microscopy.

Object detection is a fundamental task in digital microscopy, where machine learning has made great strides in overcoming the limitations of classical approaches. The training of state-of-the-art machine-learning methods almost universally relies on vast amounts of labeled experimental data or the ability to numerically simulate realistic datasets. However, experimental data are often challenging to label and cannot be easily reproduced numerically. Here, we propose a deep-learning method, named LodeSTAR (Localization and detection from Symmetries, Translations And Rotations), that learns to detect microscopic objects with sub-pixel accuracy from a single unlabeled experimental image by exploiting the inherent roto-translational symmetries of this task. We demonstrate that LodeSTAR outperforms traditional methods in terms of accuracy, also when analyzing challenging experimental data containing densely packed cells or noisy backgrounds. Furthermore, by exploiting additional symmetries we show that LodeSTAR can measure other properties, e.g., vertical position and polarizability in holographic microscopy.

Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography.

Characterization of suspended nanoparticles in their native environment plays a central role in a wide range of fields, from medical diagnostics and nanoparticle-enhanced drug delivery to nanosafety and environmental nanopollution assessment. Standard optical approaches for nanoparticle sizing assess the size via the diffusion constant and, as a consequence, require long trajectories and that the medium has a known and uniform viscosity. However, in most biological applications, only short trajectories are available, while simultaneously, the medium viscosity is unknown and tends to display spatiotemporal variations. In this work, we demonstrate a label-free method to quantify not only size but also refractive index of individual subwavelength particles using 2 orders of magnitude shorter trajectories than required by standard methods and without prior knowledge about the physicochemical properties of the medium. We achieved this by developing a weighted average convolutional neural network to analyze holographic images of single particles, which was successfully applied to distinguish and quantify both size and refractive index of subwavelength silica and polystyrene particles without prior knowledge of solute viscosity or refractive index. We further demonstrate how these features make it possible to temporally resolve aggregation dynamics of 31 nm polystyrene nanoparticles, revealing previously unobserved time-resolved dynamics of the monomer number and fractal dimension of individual subwavelength aggregates.

Constructing a library of metal and metal-oxide nanoparticle heterodimers through colloidal assembly.

Nanoparticle dimers composed of different metals or metal oxides, as well as different shapes and sizes, are of wide interest for applications ranging from nanoplasmonic sensing to nanooptics to biomedical engineering. Shaped nanoparticles, like triangles and nanorods, can be particularly useful in applications due to the strong localized plasmonic hot-spot that forms at the tips or corners. By placing catalytic, but traditionally weakly- or non-plasmonic nanoparticles, such as metal oxides and metals like palladium, in these hot-spots, an enhanced function for sensing, photocatalysis or optical use is predicted. Here, we present an electrostatic colloidal assembly strategy for nanoparticles, incorporating different sizes, shapes and metal or metal oxide compositions into heterodimers with smaller gaps than are achievable using nanofabrication techniques. This versatile method is demonstrated on 14 combinations, including a variety of shaped gold nanoparticles as well as palladium, iron oxide, and titanium oxide nanoparticles. These colloidal nanoparticles are stabilized with traditional surfactants, such as citrate, CTAB, PVP and oleic acid/oleylamines, indicating the wide applicability of our approach. Heterodimers of gold and palladium are further analyzed using cathodoluminescence to demonstrate the tunability of these "plasmonic molecules". Since systematically altering the absorption and emission of the plasmonic nanoparticles dimers is crucial to extending their functionality, and small gap sizes produce the strongest hot-spots, this method indicates that the electrostatic approach to heterodimer assembly can be useful in creating new nanoparticle dimers for many applications.

Label-free spatio-temporal monitoring of cytosolic mass, osmolarity, and volume in living cells.

Microorganisms adapt their biophysical properties in response to changes in their local environment. However, quantifying these changes at the single-cell level has only recently become possible, largely relying on fluorescent labeling strategies. In this work, we utilize yeast (Saccharomyces cerevisiae) to demonstrate label-free quantification of changes in both intracellular osmolarity and macromolecular concentration in response to changes in the local environment. By combining a digital holographic microscope with a millifluidic chip, the temporal response of cellular water flux was successfully isolated from the rate of production of higher molecular weight compounds, in addition to identifying the produced compounds in terms of the product of their refractive index increment [Formula: see text] and molar mass. The ability to identify, quantify and temporally resolve multiple biophysical processes in living cells at the single cell level offers a crucial complement to label-based strategies, suggesting broad applicability in studies of a wide-range of cellular processes.

Depletion of regulator-of-G-protein signaling-10 in mice exaggerates high-fat diet-induced insulin resistance and inflammation, and this effect is mitigated by dietary green tea extract.

The interaction between insulin resistance and inflammation plays a central role in the development of chronic diseases, although the mechanism is not fully understood. We previously demonstrated that regulator of G-protein signaling-10 (RGS10) protein is a negative modulator of the inflammatory response in macrophages and microglia. Because inflammation is a critical component in the development of high fat diet-induced insulin resistance, in this study we investigated whether RGS10 is involved in the diet-dependent regulation of glucose tolerance and insulin sensitivity. We hypothesized that the absence of RGS10 would exaggerate high-fat diet (HFD)-induced insulin resistance and inflammation response. Our results showed that RGS10 knockout (KO) mice fed a HFD gained significantly more weight and developed severe insulin resistance compared to wild-type (WT) mice fed HFD. Furthermore, compared to WT HFD-fed mice, KO mice fed the HFD displayed inflammatory phenotypes such as decreased adipose tissue expression of the anti-inflammatory M2 markers YM1 and Fizz1 and increased expression of the proinflammatory M1 cytokine interleukin 6 in adipose and CD11b, CD68 and interleukin 1ß in liver tissues. The impact of RGS10 deficiency on the exaggeration of HFD-induced insulin resistance and inflammation was ameliorated by oral consumption of green tea extract. Our results demonstrate that RGS10 is an important part of a protective mechanism involved in in regulating metabolic homeostasis by reducing inflammatory responses, which could potentially lead to an innovative new approach targeting inflammation and insulin resistance.

DETECTION OF ROAD HAZARDS BY NOVICE TEEN AND EXPERIENCED ADULT DRIVERS.

Previous laboratory and simulator research has indicated that hazard detection skills and abilities are less developed among novice drivers compared with experienced adult drivers. Novices tend to miss some relevant cues and may be less able to process important elements in the environment while driving. As was found with other research methods, it was hypothesized that novices would have lower hazard detection skills and will react less appropriately to hazards than older and more experienced drivers.Three hazard perception scenarios were simulated on a test track and data were collected on newly licensed teen drivers (within 2 weeks of licensure) and a comparison group of adults. The scenarios included a hidden stop sign, hidden pedestrian, and hidden pedestrian with lane closure (this last included a text-messaging task). Discrete quantitative performance metrics were evaluated for this analysis, including: 1) Did the participant glance at the potential hazard (e.g., stop sign, pedestrian)? 2) Did the participant stop (for the stop sign scenario)? 3) Did the participant show signs of indecision, caution, or awareness (for all hazards)?Significant differences between teen drivers and more experienced adult drivers were found in a combined hazard detection analysis. Results indicate that the adult drivers observed hazards and demonstrated overt recognition of hazards more frequently than the teen drivers. Results indicated that a large portion of teen drivers failed to disengage from peripheral task engagement in the presence of hazards. The results will later be compared to naturalistic data for the same set of drivers to see whether these test track results are predictive of real-world behavior.