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Flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) in the brain is important for clearance of metabolic waste. Arterial pulsations are thought to drive flow, but this has never been quantitatively shown. We used particle tracking to quantify CSF flow velocities in PVSs of live mice. CSF flow is pulsatile and driven primarily by the cardiac cycle. The speed of the arterial wall matches that of the CSF, suggesting arterial wall motion is the principal driving mechanism, via a process known as perivascular pumping. Increasing blood pressure leaves the artery diameter unchanged but changes the pulsations of the arterial wall, increasing backflow and thereby reducing net flow in the PVS. Perfusion-fixation alters the normal flow direction and causes a 10-fold reduction in PVS size. We conclude that particle tracking velocimetry enables the study of CSF flow in unprecedented detail and that studying the PVS in vivo avoids fixation artifacts. Arterial pulsations are thought to drive CSF flow through perivascular spaces (PVSs), but this has never been quantitatively shown. Using particle tracking to quantify CSF flow velocities in PVSs of live mice, the authors show that flow speeds match the instantaneous speeds of the pulsing artery walls that form the inner boundaries of the PVSs.

Functional hyperemia, also known as neurovascular coupling, is a phenomenon that occurs when neural activity increases local cerebral blood flow. Because all biological activity produces metabolic waste, we here sought to investigate the relationship between functional hyperemia and waste clearance via the glymphatic system. The analysis showed that whisker stimulation increased both glymphatic influx and clearance in the mouse somatosensory cortex with a 1.6-fold increase in periarterial cerebrospinal fluid (CSF) influx velocity in the activated hemisphere. Particle tracking velocimetry revealed a direct coupling between arterial dilation/constriction and periarterial CSF flow velocity. Optogenetic manipulation of vascular smooth muscle cells enhanced glymphatic influx in the absence of neural activation. We propose that impedance pumping allows arterial pulsatility to drive CSF in the same direction as blood flow, and we present a simulation that supports this idea. Thus, functional hyperemia boosts not only the supply of metabolites but also the removal of metabolic waste. Holstein-Rønsbo et al. show that functional hyperemia increases glymphatic CSF inflow and clearance. Direct stimulation of vascular smooth muscle cells, in the absence of neuronal activation, similarly enhances glymphatic flow.

Single-particle tracking (SPT) is a key tool for quantitative analysis of dynamic biological processes and has provided unprecedented insights into a wide range of systems such as receptor localization, enzyme propulsion, bacteria motility, and drug nanocarrier delivery. The inherently complex diffusion in such biological systems can vary drastically both in time and across systems, consequently imposing considerable analytical challenges, and currently requires an a priori knowledge of the system. Here we introduce a method for SPT data analysis, processing, and classification, which we term “diffusional fingerprinting.” This method allows for dissecting the features that underlie diffusional behavior and establishing molecular identity, regardless of the underlying diffusion type. The method operates by isolating 17 descriptive features for each observed motion trajectory and generating a diffusional map of all features for each type of particle. Precise classification of the diffusing particle identity is then obtained by training a simple logistic regression model. A linear discriminant analysis generates a feature ranking that outputs the main differences among diffusional features, providing key mechanistic insights. Fingerprinting operates by both training on and predicting experimental data, without the need for pretraining on simulated data. We found this approach to work across a wide range of simulated and experimentally diverse systems, such as tracked lipases on fat substrates, transcription factors diffusing in cells, and nanoparticles diffusing in mucus. This flexibility ultimately supports diffusional fingerprinting’s utility as a universal paradigm for SPT diffusional analysis and prediction.

The phoretic mechanisms at stake in the propulsion of asymmetric colloids have been the subject of debates during the past years. In particular, the importance of electrokinetic effects on the motility of Pt-PS Janus sphere was recently discussed. Here, we probe the hydrodynamic flow field around a catalytically active colloid using particle tracking velocimetry both in the freely swimming state and when kept stationary with an external force. Our measurements provide information about the fluid velocity in the vicinity of the surface of the colloid, and confirm a mechanism for propulsion that was proposed recently. In addition to offering a unified understanding of the nonequilibrium interfacial transport processes at stake, our results open the way to a thorough description of the hydrodynamic interactions between such active particles and understanding their collective dynamics. In order to predict the behaviours of self-propelled particles it is important to understand the fluid disturbances they generate. Here the authors measure the flow-fields around active particles and show that they are in agreement with theoretical predictions which take into account electrokinetic effects.

Ocean turbulence, as a critical physical process in marine hydrodynamics, holds significant guiding implications for the development of multiple disciplines and has emerged as a research hotspot in recent years. However, constrained by the limitations of traditional oceanographic instruments that rely solely on single-point measurements, our observations and studies of oceanic turbulence remain considerably inadequate. To extend the scope of oceanic turbulence observations from acquiring single-point information to capturing three-dimensional (3D) field distributions, this study builds upon previous work by introducing Holographic Astigmatic Particle Tracking Velocimetry (HAPTV) and successfully measuring a 3D micro-scale turbulence field generated under laboratory conditions. Analysis of the measured results indicates that this technique has yielded reliable turbulence field parameters, demonstrating its capability to measure 3D turbulence fields and its potential for conducting in-depth research in this area.

We present an experimental study of a turbulent boundary layer (TBL) control on a flat plate using plasma actuators. Three different configurations of the actuators produce spanwise arrays of large-scale streamwise vortices (LSSVs). An ultra-high-resolution floating element (FE) force balance, developed in house and calibrated using μ-particle tracking velocimetry, is employed to measure wall friction. The FE captures a drag reduction (DR) of up to 26 % on the FE area (667 × 1333 wall units), downstream of the actuators. The local DR persists downstream, well after the LSSVs disappear. Both plasma-generated flow and the TBL under control are compared with an uncontrolled TBL. The maximum DR takes place when the LSSVs producing wall jets reach a spanwise velocity of 3.9 in wall units. The flow is altered by up to 29 % of the TBL thickness, with a drop in the new vortices due to the control-induced stabilization of the wall streaks. The local friction is characterized by three distinct spatial regions of drag increase, pronounced DR and drag recovery – all connected to the LSSVs. The LSSVs push the streaks to the middle between two adjacent actuators, suppressing transient growth and near-wall turbulent production. A DR mechanism is proposed.

We propose and validate a novel experimental technique to measure two-point statistics of turbulent flows. It consists of spreading rigid fibers in the flow and tracking their position and orientation in time and is therefore named “fiber tracking velocimetry.” By choosing different fiber lengths, i.e., within the inertial or dissipative range of scales, the statistics of turbulence fluctuations at the selected length scale can be probed accurately by simply measuring the fiber velocity at its two ends and projecting it along the transverse-to-fiber direction. By means of fully resolved direct numerical simulations and experiments, we show that these fiber-based transverse velocity increments are statistically equivalent to the (unperturbed) flow transverse velocity increments. Moreover, we show that the turbulent energy-dissipation rate can be accurately measured exploiting sufficiently short fibers. The technique is tested against standard particle tracking velocimetry (PTV) of flow tracers with excellent agreement. Our technique overcomes the well-known problem of PTV to probe two-point statistics reliably because of the fast relative diffusion in turbulence that prevents the mutual distance between particles to remain constant at the length scale of interest. This problem, making it difficult to obtain converged statistics for a fixed separation distance, is even more dramatic for natural flows in open domains. A prominent example is oceanic currents, where drifters (i.e., the tracer-particle counterpart used in field measurements) disperse quickly, but at the same time their number has to be limited to save costs. Inspired by our laboratory experiments, we propose pairs of connected drifters as a viable option to solve the issue.

SignificanceThe plant plasma membrane acts as the front line for cellular perception of the environment. As such, signaling and transport proteins which perceive or transport environmental signals, developmental cues, and nutrients are located within it. A number of studies have revealed that proteins located within the plasma membrane do not simply freely diffuse within its plane. Rather, proteins are localized in nanodomains. In addition to the plasma membrane, plant cells also have an extracellular matrix, the cell wall. Here we have shown that the cell wall has a role in regulating the dynamics and size of plasma-membrane nanodomains for proteins involved in morphogenesis (PIN3) and pathogen perception (FLS2). Plant plasma-membrane (PM) proteins are involved in several vital processes, such as detection of pathogens, solute transport, and cellular signaling. For these proteins to function effectively there needs to be structure within the PM allowing, for example, proteins in the same signaling cascade to be spatially organized. Here we demonstrate that several proteins with divergent functions are located in clusters of differing size in the membrane using subdiffraction-limited Airyscan confocal microscopy. Single particle tracking reveals that these proteins move at different rates within the membrane. Actin and microtubule cytoskeletons appear to significantly regulate the mobility of one of these proteins (the pathogen receptor FLS2) and we further demonstrate that the cell wall is critical for the regulation of cluster size by quantifying single particle dynamics of proteins with key roles in morphogenesis (PIN3) and pathogen perception (FLS2). We propose a model in which the cell wall and cytoskeleton are pivotal for regulation of protein cluster size and dynamics, thereby contributing to the formation and functionality of membrane nanodomains.

The performance of a transcatheter aortic valve (TAV) can be evaluated by analyzing the flow field downstream of the valve. However, three dimensional flow and pressure fields, and particle residence time, a quantity closely related to thrombosis risk, are challenging to obtain. This experimental study aims to provide a comprehensive 3D measurement of the flow field downstream of an Edwards SAPIEN 3 using time-resolved 3D particle tracking velocimetry (3D PTV) with Shake-the-Box (STB) algorithm. The valve was deployed in an idealized aorta model and tested in a left heart simulator under physiological conditions. Detailed 3D vortical structures, pressure distributions, and particle residence time were obtained by analyzing the 3D particle tracks. Results have shown large-scale retrograde flow entering the sinuses of the TAV at systole, reducing flow stasis there. However, the 3D particle tracks reveal that the retrograde flow has a high residence time and might have already experienced high shear stress near the main jet. Thus by only focusing on the flow in the sinus region is not sufficient to evaluate the leaflet thrombosis risk, and the flow downstream of the valve should be taken into consideration. The unique perspectives offered by 3D PTV are important when evaluating the performance of the TAVs.

We explored the settling dynamics of vertically aligned particles in a quiescent, stratified two-layer fluid using particle tracking velocimetry. Glass spheres of $d=4\\,{\\rm mm}$ diameter were released at frequencies of 4, 6 and 8 Hz near the free surface, traversing through an upper ethanol layer ($H_1$), where H is height or layer thickess, varying from $10d$ to $40d$ and a lower oil layer. Results reveal pronounced lateral particle motion in the ethanol layer, attributed to a higher Galileo number ($Ga = 976$, ratio of buoyancy–gravity to viscous effects), compared with the less active behaviour in the oil layer ($Ga = 16$). The ensemble vertical velocity of particles exhibited a minimum just past the density interface, becoming more pronounced with increasing $H_1$, and suggesting that enhanced entrainment from ethanol to oil resulted in an additional buoyancy force. This produced distinct patterns of particle acceleration near the density interface, which were marked by significant deceleration, indicating substantial resistance to particle motion. An increased drag coefficient occurred for $H_1/d = 40$ compared with a single particle settling in oil; drag reduced as the particle-release frequency ($\\,f_p$) increased, likely due to enhanced particle interactions at closer proximity. Particle pair dispersions, lateral ($R^2_L$) and vertical ($R^2_z$), were modulated by $H_1$, initial separation $r_0$ and $f_p$. The $R^2_L$ dispersion displayed ballistic scaling initially, Taylor scaling for $r_0 < H_1$ and Richardson scaling for $r_0 > H_1$. In contrast, $R^2_z$ followed a $R^2_z \\sim t^{5.5}$ scaling under $r_0 < H_1$. Both $R^2_L$ and $R^2_z$ plateaued at a distance from the interface, depending on $H_1$ and $f_p$.