In biological fluids, proteins bind to particles, forming so-called protein coronas. Such adsorbed protein layers significantly influence the biological interactions of particles, both in vitro and ...in vivo. The adsorbed protein layer is generally described as a two-component system comprising “hard” and “soft” protein coronas. However, a comprehensive picture regarding the protein corona structure is lacking. Herein, we introduce an experimental approach that allows for in situ monitoring of protein adsorption onto silica microparticles. The technique, which mimics flow in vascularized tumors, combines confocal laser scanning microscopy with microfluidics and allows the study of the time-evolution of protein corona formation. Our results show that protein corona formation is kinetically divided into three different phases: phase 1, proteins irreversibly and directly bound (under physiologically relevant conditions) to the particle surface; phase 2, irreversibly bound proteins interacting with preadsorbed proteins, and phase 3, reversibly bound “soft” protein corona proteins. Additionally, we investigate particle–protein interactions on low-fouling zwitterionic-coated particles where the adsorption of irreversibly bound proteins does not occur, and on such particles, only a “soft” protein corona is formed. The reported approach offers the potential to define new state-of-the art procedures for kinetics and protein fouling experiments.
The formation of a biomolecular corona around engineered particles determines, in large part, their biological behavior in vitro and in vivo. To gain a fundamental understanding of how particle ...design and the biological milieu influence the formation of the “hard” biomolecular corona, we conduct a series of in vitro studies using microfluidics. This setup allows the generation of a dynamic incubation environment with precise control over the applied flow rate, stream orientation, and channel dimensions, thus allowing accurate control of the fluid flow and the shear applied to the proteins and particles. We used mesoporous silica particles, poly(2-methacryloyloxyethylphosphorylcholine) (PMPC)-coated silica hybrid particles, and PMPC replica particles (obtained by removal of the silica particle templates), representing high-, intermediate-, and low-fouling particle systems, respectively. The protein source used in the experiments was either human serum or human full blood. The effects of flow, particle surface properties, incubation medium, and incubation time on the formation of the biomolecular corona formation are examined. Our data show that protein adhesion on particles is enhanced after incubation in human blood compared to human serum and that dynamic incubation leads to a more complex corona. By varying the incubation time from 2 s to 15 min, we demonstrate that the “hard” biomolecular corona is kinetically subdivided into two phases comprising a tightly bound layer of proteins interacting directly with the particle surface and a loosely associated protein layer. Understanding the influence of particle design parameters and biological factors on the corona composition, as well as its dynamic assembly, may facilitate more accurate prediction of corona formation and therefore assist in the design of advanced drug delivery vehicles.
Titanium dioxide is one of the most intensely studied oxides due to its interesting electrochemical and photocatalytic properties and it is widely applied, for example in photocatalysis, ...electrochemical energy storage, in white pigments, as support in catalysis, etc. Common synthesis methods of titanium dioxide typically require a high temperature step to crystallize the amorphous material into one of the polymorphs of titania, e.g. anatase, brookite and rutile, thus resulting in larger particles and mostly non-porous materials. Only recently, low temperature solution-based protocols gave access to crystalline titania with higher degree of control over the formed polymorph and its intra- or interparticle porosity. The present work critically reviews the formation of crystalline nanoscale titania particles via solution-based approaches without thermal treatment, with special focus on the resulting polymorphs, crystal morphology, surface area, and particle dimensions. Special emphasis is given to sol-gel processes via glycolated precursor molecules as well as the miniemulsion technique. The functional properties of these materials and the differences to chemically identical, non-porous materials are illustrated using heterogeneous catalysis and electrochemical energy storage (battery materials) as example.
Upon exposure to human blood, nanoengineered particles interact with a multitude of plasma components, resulting in the formation of a biomolecular corona. This corona modulates downstream biological ...responses, including recognition by and association with human immune cells. Considerable research effort has been directed toward the design of materials that can demonstrate a low affinity for various proteins (low-fouling materials) and materials that can exhibit low association with human immune cells (stealth materials). An implicit assumption common to bio–nano research is that nanoengineered particles that are low-fouling will also exhibit stealth. Herein, we investigated the link between the low-fouling properties of a particle and its propensity for stealth in whole human blood. High-fouling mesoporous silica (MS) particles and low-fouling zwitterionic poly(2-methacryloyloxyethyl phosphorylcholine) (PMPC) particles were synthesized, and their interaction with blood components was assessed before and after precoating with serum albumin, immunoglobulin G, or complement protein C1q. We performed an in-depth proteomics characterization of the biomolecular corona that both identifies specific proteins and measures their relative abundance. This was compared with observations from a whole blood association assay that identified with which cell type each particle system associates. PMPC-based particles displayed reduced association both with cells and with serum proteins compared with MS-based particles. Furthermore, the enrichment of specific proteins within the biomolecular corona was found to correlate with association with specific cell types. This study demonstrates how the low-fouling properties of a material are indicative of its stealth with respect to immune cell association.
The adsorption of biomolecules onto nanomaterials can alter the performance of the nanomaterials in vitro and in vivo. Recent studies have primarily focused on the protein “corona”, formed upon ...adsorption of proteins onto nanoparticles in biological fluids, which can change the biological fate of the nanoparticles. Conversely, interactions between nanomaterials and other classes of biomolecules namely, lipids, nucleic acids, and polysaccharides have received less attention despite their important roles in biology. A possible reason is the challenge associated with investigating biomolecule interactions with nanomaterials using current technologies. Herein, a protocol is developed for studying bio–nano interactions by depositing four classes of biomolecules (proteins, lipids, nucleic acids, and polysaccharides) and complex biological media (blood) onto planar substrates, followed by exposure to metal–phenolic network (MPN) complexes. The MPNs preferentially interact with the biomolecule over the inorganic substrate (glass), highlighting that patterned biomolecules can be used to engineer patterned MPNs. Subsequent formation of silver nanoparticles on the MPN films maintains the patterns and endows the films with unique reflectance and fluorescence properties, enabling visualization of latent fingerprints (i.e., invisible residual biomolecule patterns). This study demonstrates the potential complexity of the biomolecule corona as all classes of biomolecules can adsorb onto MPN‐based nanomaterials.
The interaction of specific biomolecules with nanomaterials is important for various applications but can be challenging to study. Metal–phenolic networks can be selectively grown on four major classes of biomolecules, where subsequent growth of silver nanoparticles allows for enhanced detection and visualization. Using this technique, biomolecule patterns, including latent and blood‐based fingerprints, can be visualized in detail.
By using additive manufacturing techniques like the laser powder bed fusion (LPBF) process, parts can be manufactured with high material efficiency because unfused powder material can be ...reconditioned and reused in consecutive manufacturing jobs. Nevertheless, process by-products like spatters may influence the powder quality and hence alter the mechanical properties/performance of parts. In order to investigate these dependencies, a methodology and a standard build job for the recycling behavior of the lightweight aluminum alloy AlSi10Mg was developed and built with ageing powder in 10 consecutive jobs with no refreshing between the cycles. The powder properties and mechanical performance of parts at static load for two build directions (horizontally and vertically to substrate plate) was evaluated. The influence of build height effects on mechanical performance was investigated as well. The findings may indicate that the coarsening of the powder material during recycling could lead to improved mechanical properties for the AlSi10Mg alloy.
Abstract
Two cases of dryline convection initiation (CI) over north Texas have been simulated (3 April 2012 and 15 May 2013) from a 50-member WRF-DART ensemble adjustment Kalman filter (EAKF) ...ensemble. In this study, ensemble sensitivity analysis (ESA) is applied to a convective forecast metric, maximum composite reflectivity (referred to as the response function), as a simple proxy for CI to analyze dynamic mesoscale sensitivities at the surface and aloft. Analysis reveals positional and magnitude sensitivities related to the strength and placement of important dynamic features. Convection initiation is sensitive to the evolving temperature and dewpoint fields upstream of the forecast response region in the near-CI time frame (0–12 h), prior to initiation. The sensitivity to thermodynamics is also manifest in the magnitude of dewpoint gradients along the dryline that triggers the convection. ESA additionally highlights the importance of antecedent precipitation and cold pool generation that modifies the pre-CI environment. Aloft, sensitivity of CI to a weak short-wave trough and capping inversion-level temperature is coherent, consistent, and traceable through the entire forecast period. Notwithstanding the (often) non-Gaussian distribution of ensemble member forecasts of convection, which violate the underpinnings of ESA theory, ESA is demonstrated to sufficiently identify regions that influence dryline CI. These results indicate an application of ESA for severe storm forecasting at operational centers and forecast offices as well as other mesoscale forecasting applications.
We calculate the target normal single-spin asymmetry caused by two-photon exchange in inclusive electron-nucleon scattering in the resonance region. Our analysis uses the 1/Nc expansion of low-energy ...QCD and combines N and Δ intermediate and final states using the contracted SU(4) spin-flavor symmetry. The normal spin asymmetry obtained in leading-order accuracy in 1/Nc has magnitude ∼10−2 and different sign in ep and en scattering. It can be measured in electron scattering at lab energies ∼0.5–1.5 GeV and provides a clean probe of two-photon exchange dynamics.
To develop and validate a machine-learning algorithm to improve prediction of incident OUD diagnosis among Medicare beneficiaries with greater than or equal to1 opioid prescriptions. This prognostic ...study included 361,527 fee-for-service Medicare beneficiaries, without cancer, filling greater than or equal to1 opioid prescriptions from 2011-2016. We randomly divided beneficiaries into training, testing, and validation samples. We measured 269 potential predictors including socio-demographics, health status, patterns of opioid use, and provider-level and regional-level factors in 3-month periods, starting from three months before initiating opioids until development of OUD, loss of follow-up or end of 2016. The primary outcome was a recorded OUD diagnosis or initiating methadone or buprenorphine for OUD as proxy of incident OUD. We applied elastic net, random forests, gradient boosting machine, and deep neural network to predict OUD in the subsequent three months. We assessed prediction performance using C-statistics and other metrics (e.g., number needed to evaluate to identify an individual with OUD NNE). Beneficiaries were stratified into subgroups by risk-score decile. The training (n = 120,474), testing (n = 120,556), and validation (n = 120,497) samples had similar characteristics (age greater than or equal to65 years = 81.1%; female = 61.3%; white = 83.5%; with disability eligibility = 25.5%; 1.5% had incident OUD). In the validation sample, the four approaches had similar prediction performances (C-statistic ranged from 0.874 to 0.882); elastic net required the fewest predictors (n = 48). Using the elastic net algorithm, individuals in the top decile of risk (15.8% n = 19,047 of validation cohort) had a positive predictive value of 0.96%, negative predictive value of 99.7%, and NNE of 104. Nearly 70% of individuals with incident OUD were in the top two deciles (n = 37,078), having highest incident OUD (36 to 301 per 10,000 beneficiaries). Individuals in the bottom eight deciles (n = 83,419) had minimal incident OUD (3 to 28 per 10,000). Machine-learning algorithms improve risk prediction and risk stratification of incident OUD in Medicare beneficiaries.
Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same ...optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available—expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.
PDF
