Fluid dynamics play a fundamental role in the development of diabetic retinopathy, one of the leading causes of blindness in the Western world, affecting over 4 million people in the US alone. The disease is defined by microaneurysms, local expansions of capillaries that disturb the hemodynamic forces experienced by the endothelium leading to dysfunction, leakage and edema. Here we present a method to identify microaneurysms with a high risk of leakage based on a critical ratio of microaneurysm to vessel diameter. We derive this non-dimensional parameter from an analytical solution and generalize it using experimentally validated numerical methods. We show that this non-dimensional parameter defines the shear force experienced by endothelial cells, below which endothelial dysfunction is evident in vivo. Our results demonstrate the involvement of vWF in diabetic retinopathy, and explain a perceived disconnect between microaneurysm size and leakage. This method will allow experts to treat microaneurysms poising a high-risk of leakage, prior to edema, minimizing damage and saving vision.

Microfluidic sorting offers a unique ability to isolate large numbers of cells for bulk proteomic or metabolomics studies but is currently limited by low throughput and persistent clogging at low flow rates. Recently we uncovered the physical principles governing the inertial focusing of particles in high-Reynolds numbers. Here, we superimpose high Reynolds inertial focusing on Dean vortices, to rapidly isolate large quantities of young and adult yeast from mixed populations at a rate of 107 cells/min/channel. Using a new algorithm to rapidly quantify budding scars in isolated yeast populations and system-wide proteomic analysis, we demonstrate that protein quality control and expression of established yeast aging markers such as CalM, RPL5, and SAM1 may change after the very first replication events, rather than later in the aging process as previously thought. Our technique enables the large-scale isolation of microorganisms based on minute differences in size (±1.5 μm), a feat unmatched by other technologies.

Inertial focusing is the migration of particles in fluid toward equilibrium, where current theory predicts that shear-induced and wall-induced lift forces are balanced. First reported in 1961, this Segre-Silberberg effect is particularly useful for microfluidic isolation of cells and particles. Interestingly, recent work demonstrated particle focusing at high Reynolds numbers that cannot be explained by current theory. In this work, we show that non-monotonous velocity profiles, such as those developed in curved channels, create peripheral velocity maxima around which opposing shear-induced forces dominate over wall effects. Similarly, entry effects amplified in high Reynolds flow produce an equivalent trapping mechanism in short, straight channels. This new focusing mechanism in the developing flow regime enables a 10-fold miniaturization of inertial focusing devices, while our model corrects long-standing misconceptions about the nature of mechanical forces governing inertial focusing in curved channels.

Here, we introduce Streamline Image Velocimetry, a method to derive fluid velocity fields in fully developed laminar flow from long-exposure images of streamlines. Streamlines confine streamtubes, in which the volumetric flow is constant for incompressible fluid. Using an explicit analytical solution as a boundary condition, velocity fields and emerging properties such as shear force and pressure can be quantified throughout. Numerical and experimental validations show a high correlation between anticipated and measured results, with R 2 > 0.91. We report spatial resolution of 2 lm in a flow rate of 0.15 m/s, resolution that can only be achieved with 75 kHz frame rate in traditional particle tracking velocimetry. V C 2013 AIP Publishing LLC.

Flow behavior in complex three-dimensional (3D) microscale domains is the key in the development of microcirculatory pathologies and the design of 3D microfluidics. While numerical simulations are common practice for the derivation of velocity fields in such domains, they are limited to known geometries. Current experimental methods such as micron-scale particle tracing comprise of intricate algorithmic approaches for the accurate tracing of numerous particles in a dense moving liquid suspension and are fundamentally limited in resolution to the finite size of the interrogated steps. Here, we introduce 3D streamlines image velocimetry (3D-SIV), a method to derive fluid velocity fields in arbitrary resolution for fully developed laminar flow in 3D geometries. Our approach utilizes 3D geometrical fitting and superimposed Delaunay triangulation to reconstruct streamtubes and to trace their volumetric changes. Our algorithm has applications in out-of-plane velocimetries, which we demonstrate in a 3D dilated curved geometry and in an ascending aorta. The 3D-SIV can be applied for high-resolution derivation of velocity fields in microcirculatory pathologies and to 3D microfluidic circuits, extending the potential of out-of-plane velocimetries to complex geometries and arbitrary resolution.