Nanoparticle carriers are effective drug delivery vehicles. Along with other design parameters including size, composition, and surface charge, particle shape strongly influences cellular uptake. How nanoparticle geometry affects targeted delivery under physiologically relevant conditions, however, is inconclusive. Here, we demonstrate that nanoconstruct core shape influences the dynamics of targeting ligand–receptor interactions on cancer cell membranes. By single-particle tracking of translational and rotational motion, we compared DNA aptamer AS1411 conjugated gold nanostars (AS1411-AuNS) and 50 nm gold spheres (AS1411-50NPs) on cells with and without targeted nucleolin membrane receptors. On nucleolin-expressing cells, AS1411-AuNS exhibited faster velocities under directed diffusion and translated over larger areas during restricted diffusion compared to AS1411-50NPs, despite their similar protein corona profiles. On nucleolin-inhibited cells, AS1411-AuNS showed faster rotation dynamics over smaller translational areas, while AS1411-50NPs did not display significant changes in translation. These differences in translational and rotational motions indicate that nanoparticle shape affects how targeting nanoconstructs bind to cell-membrane receptors.

This paper describes a reconfigurable metalens system that can image at visible wavelengths based on arrays of coupled plasmonic nanoparticles. These lenses manipulated the wavefront and focused light by exciting surface lattice resonances that were tuned by patterned polymer blocks on single-particle sites. Predictive design of the dielectric nanoblocks was performed using an evolutionary algorithm to create a range of three-dimensional focusing responses. For scalability, we demonstrated a simple technique for erasing and writing the polymer nanostructures on the metal nanoparticle arrays in a single step using solvent-assisted nanoscale embossing. This reconfigurable materials platform enables tunable focusing with diffraction-limited resolution and offers prospects for highly adaptive, compact imaging.

This paper describes how differences in the dynamics of targeting and nontargeting constructs can provide information on nanoparticle (NP)–cell interactions. We probed translational and rotational dynamics of functionalized Au nanostar (AuNS) nanoconstructs interacting with cells in serum-containing medium. We found that AuNS with targeting ligands had a larger dynamical footprint and faster rotational speed on cell membranes expressing human epidermal growth factor receptor 2 (HER-2) receptors compared to that of AuNS with nontargeting ligands. Targeting and nontargeting nanoconstructs displayed distinct membrane dynamics despite their similar protein adsorption profiles, which suggests that targeted interactions are preserved even in the presence of a protein corona. The high sensitivity of single-NP dynamics can be used to compare different nanoconstruct properties (such as NP size, shape, and surface chemistry) to improve their design as delivery vehicles.

This paper describes a computational imaging platform to determine the orientation of anisotropic optical probes under differential interference contrast (DIC) microscopy. We established a deep-learning model based on data sets of DIC images collected from metal nanoparticle optical probes at different orientations. This model predicted the in-plane angle of gold nanorods with an error below 20°, the inherent limit of the DIC method. Using low-symmetry gold nanostars as optical probes, we demonstrated the detection of in-plane particle orientation in the full 0–360° range. We also showed that orientation predictions of the same particle were consistent even with variations in the imaging background. Finally, the deep-learning model was extended to enable simultaneous prediction of in-plane and out-of-plane rotation angles for a multibranched nanostar by concurrent analysis of DIC images measured at multiple wavelengths.