No abstract

Differential dynamic microscopy (DDM) is an emerging technique to measure the ensemble dynamics of colloidal and complex fluid motion using optical microscopy in systems that would otherwise be difficult to measure using other methods. To date, DDM has successfully been applied to linear space invariant imaging modes including bright-field, fluorescence, confocal, polarised, and phase-contrast microscopy to study diverse dynamic phenomena. In this work, we show for the first time how DDM analysis can be extended to dark-field imaging, i.e. a linear space variant (LSV) imaging mode. Specifically, we present a particle-based framework for describing dynamic image correlations in DDM, and use it to derive a correction to the image structure function obtained by DDM that accounts for scatterers with non-homogeneous intensity distributions as they move within the imaging plane. To validate the analysis, we study the Brownian motion of gold nanoparticles, whose plasmonic structure allows for nanometer-scale particles to be imaged under dark-field illumination, in Newtonian liquids. We find that diffusion coefficients of the nanoparticles can be reliably measured by dark-field DDM, even under optically dense concentrations where analysis via multiple-particle tracking microrheology fails. These results demonstrate the potential for DDM analysis to be applied to linear space variant forms of microscopy, providing access to experimental systems unavailable to other imaging modes.

Microfluidic cellular models, commonly referred to as “organs‐on‐chips,” continue to advance the field of bioengineering via the development of accurate and higher throughput models, captivating the essence of living human organs. This class of models can mimic key in vivo features, including shear stresses and cellular architectures, in ways that cannot be realized by traditional two‐dimensional in vitro models. Despite such progress, current organ‐on‐a‐chip models are often overly complex, require highly specialized setups and equipment, and lack the ability to easily ascertain temporal and spatial differences in the transport kinetics of compounds translocating across cellular barriers. To address this challenge, we report the development of a three‐dimensional human blood brain barrier (BBB) microfluidic model (μHuB) using human cerebral microvascular endothelial cells (hCMEC/D3) and primary human astrocytes within a commercially available microfluidic platform. Within μHuB, hCMEC/D3 monolayers withstood physiologically relevant shear stresses (2.73 dyn/cm 2 ) over a period of 24 hr and formed a complete inner lumen, resembling in vivo blood capillaries. Monolayers within μHuB expressed phenotypical tight junction markers (Claudin‐5 and ZO‐1), which increased expression after the presence of hemodynamic‐like shear stress. Negligible cell injury was observed when the monolayers were cultured statically, conditioned to shear stress, and subjected to nonfluorescent dextran (70 kDa) transport studies. μHuB experienced size‐selective permeability of 10 and 70 kDa dextrans similar to other BBB models. However, with the ability to probe temporal and spatial evolution of solute distribution, μHuBs possess the ability to capture the true variability in permeability across a cellular monolayer over time and allow for evaluation of the full breadth of permeabilities that would otherwise be lost using traditional end‐point sampling techniques. Overall, the μHuB platform provides a simplified, easy‐to‐use model to further investigate the complexities of the human BBB in real‐time and can be readily adapted to incorporate additional cell types of the neurovascular unit and beyond.

The delivery of suspended active ingredients to a surface is a central function of numerous commercial cosmetic, drug, and agricultural formulations. Many products use liquid droplets as a delivery vehicle but, because interfacial tension keeps droplets spherical, these materials cannot exploit the benefits of anisotropic shape and shape change offered by solid colloids. In this work, individual droplet manipulation is used to produce viscoelastic droplets that can stably retain non-spherical shapes by balancing the Laplace pressure of the liquid-liquid interface with the elasticity of an internal crystalline network. A stability criterion is developed for idealized spherocylindrical droplets and shown to agree with experimental data for varying droplet size and rheology. Shape change can be induced in the anisotropic droplets by upsetting the balance of droplet interfacial tension and internal rheology. Using dilution to increase the interfacial tension shows that external stimuli can trigger collapse and shape change in these droplets. The droplets wrap around substrates during collapse, improving contact and adhesion. The model is used to develop design criteria for production of droplets with tunable response.

Micron-scale rod-shaped droplets with a range of aspect ratios are produced using extrusion of oil containing a soft wax crystal network to permit shape customization. A physical model of the droplet shape stability is developed based on balancing interfacial stresses with the internal crystal network yield stress. The model predicts the mechanical properties required for particular droplet size stability, in a given physicochemical environment, and is tested by microscopic observations of droplets over a range of relevant applied temperatures. The time-dependent response to temperature of individual rods is monitored and used to identify the collapse temperature based on structural yielding. Precise temperature control allows variation of the droplet endoskeleton yield stress and direct determination of the droplet stability as a function of size, by observing the onset of collapse by interfacial compression, and enables validation of the model predictions. Mapping the regions of droplet stability and instability for various-sized droplets yields a basis for designing droplet shapes for multiple applications using easily measured physical variables. The phenomenon of arrested collapse is also explored as a means of transforming simple rod-shaped starting materials into more complex shapes and enhancing adhesion to targeted solid surfaces, enabling exploitation of the hybrid solid-liquid nature of these droplets.