Figure 1.
Cell tracking and experimental setup.
The top panel shows a sample tracking image. Cells are segmented using morphological criteria and are tracked from frame to frame. The middle panel shows a subset of tracked cells, each with a bounding box. Each cell has a series of small color circles projecting from its centroid showing the subsequent trajectory. The black arrows represent that particular cell's velocity fluctuation relative to the median, with magnitude amplified by 4 for visualization. The bottom panel shows the experimental setup which is described in detail in [14] (see Videos S1, S2, S3, S4, S5, S6, S7, S8 for more detail).
Figure 2.
Snapshots of the segmentation process for a single video frame.
See Methods for more detail. From top to bottom: 1. Raw video frame; 2. Thresholded binary version; 3. Foreground markers; 4. Background markers; 5. Marker-controlled watershed transformation; 6. Segmented objects filtered by size and shape. See Videos S1, S2, S3, S4, S5, S6, S7, S8 for additional detail.
Figure 3.
The top panel (a) shows average fluctuations in squared cellular displacement as a function of time (e.g., 〈Δr2(τ)〉) with x- and y-axes defined in the top panel of Figure 1. The middle panel (b) shows the nature of the collective microscopic dynamics characterized by (see text). The dynamics are diffusive for Vbulk>50 µm/s. Error bars show medians and standard deviations for binned data. The bottom panel (c) compares cellular-scale dynamics to cellular volume fraction and shows that density variation in this range has no effect on the nature of cellular scale dynamics.
Figure 4.
Shear-induced diffusion coefficients.
The top panel (a) shows the hydrodynamic diffusion coefficient D as a function of the bulk flow velocity Vbulk for flows fast enough for the diffusive behavior to be recovered, i.e. Vbulk>∼50 µm/s based on Figure 3. The bottom panel (b) compares this relationship for soft oxygenated sickle cells and stiff deoxygenated sickle cells where we see that Ddeoxygenated<Doxygenated. Error bars show medians and standard error for binned data.
Figure 5.
Cellular velocity fluctuations as an effective temperature.
These two panels compare probability distribution functions for normalized squared velocity fluctuations from two different experiments with chi-squared distributions with 2 degrees of freedom. is normalized with mean 0 and standard deviation 1, and x- and y-axes are defined in the top panel of Figure 1. This comparison shows that blood flow has an effective suspension temperature with longer tails as a result of the non-equilibrium nature of the pressure-driven system.