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Effect of endothelial glycocalyx layer redistribution upon microvessel poroelastohydrodynamics

Published online by Cambridge University Press:  10 June 2016

T. C. Lee
Affiliation:
Department of Engineering Science, University of Auckland, Auckland, 1142, New Zealand
D. S. Long
Affiliation:
Department of Engineering Science, University of Auckland, Auckland, 1142, New ZealandAuckland Bioengineering Institute, University of Auckland, Auckland, 1142, New Zealand
R. J. Clarke*
Affiliation:
Department of Engineering Science, University of Auckland, Auckland, 1142, New Zealand
*
†Email address for correspondence: rj.clarke@auckland.ac.nz

Abstract

The endothelial glycocalyx layer (EGL) is a macromolecular layer that lines the inner surface of blood vessels. It is believed to serve a number of physiological functions in the microvasculature, including protection of the vessel walls from potentially harmful levels of fluid shear, as a molecular sieve that acts to regulate transendothelial mass transport, and as a transducer of mechanical stress from the vessel lumen. To best fulfil some of its roles, it has been suggested that the EGL redistributes, so that it is thickest at the cell–cell junctions. It has also been suggested that the majority of mechanotransduction occurs through the solid phase of the EGL, rather than via its fluid phase. The difficulties associated with measuring the distribution of the EGL in vivo make these hypotheses difficult to confirm experimentally. Consequently, to gauge the impact of EGL redistribution from a theoretical standpoint, we compute the flow through a porous-lined microvessel, the endothelial surface of which has been informed by confocal microscopy images of a postcapillary venule. Following earlier studies, we model the poroelastohydrodynamics of the EGL using biphasic mixture theory, taking advantage of a recently developed boundary integral representation of these equations to solve the coupled poroelastohydrodynamics using the boundary element method. However, the low permeabilities of the EGL mean that viscous effects are confined to thin layers, thereby also enabling an asymptotic treatment of the dynamics in this limit. In this asymptotic regime, we also consider a two-layer Stokes flow model for the lumen flow to approximate the effect of red blood cells within the lumen. We demonstrate that redistribution of the EGL can have a substantial impact upon microvessel haemodynamics. We also confirm that the bulk of the mechanical stress is indeed carried through the solid phase of the EGL.

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Papers
Copyright
© 2016 Cambridge University Press 
Figure 0

Figure 1.Diagrams showing the geometry. We modelled a microvessel as a tube with a non-uniform wall shape, due to the presence of endothelial cells and the EGL. The vessel itself can be divided into two regions, Region I is the free lumen (represented by the volume $V_{l}$). Region II is the porous EGL, which is represented by the volume $V_{e}$. These two regions are separated by the surface $S_{i}$, which forms the interface between the two regions. The apical side of the endothelium is represented by the surface $S_{w}$. We consider two possible EGL distributions. (a) Model A: the EGL has redistributed to the relatively flat regions between cell nuclei. The minimum EGL thickness, $t_{min}$, occurs at the top of the endothelial cells. (b) Model B: the non-redistributed EGL, which has constant thickness $t_{min}$ with respect to the endothelial cells.

Figure 1

Figure 2.(a) AMIRA visualisation of cell–cell junctions in a postcapillary venule taken from mouse cremaster muscle, obtained by Bodkin and Nourshargh using confocal microscopy. (b) The cell–cell junction data (red crosses), as viewed down the longitudinal axis. The microvessel shape can be seen to be well approximated by a fitted elliptical cylinder (black line, with its corresponding major axis shown as a blue line). (c,d) Plots showing the triangularisation used for the microvessel. The colour rendering denotes cell height and the green dashed line denotes the area of the cell that is raised due to cell nuclei. These show an EGL mesh of 250 000 (c) and 1 000 000 (d) elements shown on the same section of vessel. (e) An example synthesised endothelium, with colour renderings indicating heights (dominated by the cell nuclei – see also figure 9 in appendix B).

Figure 2

Figure 3.Median of the integrated per cell longitudinal shear stresses divided by ${\it\lambda}$, as a function of ${\it\lambda}$, for (a, model A) a redistributed EGL and (b, model B) a non-redistributed EGL, when ${\it\alpha}_{0}=1.8$. These are plotted as lines with markers. Also included is the asymptotic shear stress in the limit of large $K_{P}$, (3.15), plotted as dashed lines without markers.

Figure 3

Figure 4.Longitudinal component of (a,b) fluid shear stress, $g_{z}$, and (c,d) elastic shear stress, $h_{z}$, exerted upon the endothelium in the low-permeability limit ($K_{P}=10^{-12}~\text{cm}^{2}$, ${\it\lambda}=10^{3.5}$) when the minimum EGL thickness is $t_{min}=1.5$, ${\it\alpha}_{0}=1.8$. These stresses are computed using the asymptotic expression (3.15) and (3.31)–(3.33) respectively. We consider both a redistributed EGL of varying thickness (model A, a,c), and a non-redistributed EGL (model B, b,d).

Figure 4

Table 1.The maximum magnitude of the longitudinal shear stress for solid and fluid stress, normalised on the solid stress value for a non-redistributed EGL with $t_{min}=1.5$, which has a non-dimensional stress value of 1.708. The values given for the fluid stress are $10^{-3}$ smaller than those for the solid stress. Stress values are given for a non-redistributed EGL and three cases of a redistributed EGL with amplitude factor ${\it\alpha}_{0}=1.8$, 2.2 and 3.4 respectively. The highlighted cells denote cases where the EGL protrudes further into the vessel between the cell nuclei as compared with at the cell nuclei. For the case of a bare vessel (no EGL), the fluid shear stress is $0.80$ of the reference stress.

Figure 5

Figure 5.Longitudinal component of (a,b) fluid shear stress, $g_{z}$, and (c,d) elastic shear stress, $h_{z}$, exerted upon the endothelium in the low-permeability limit ($K_{P}=10^{-12}~\text{cm}^{2}$, ${\it\lambda}=10^{3.5}$) when the minimum EGL thickness is $t_{min}=0.25$, ${\it\alpha}_{0}=1.8$. These stresses are computed using the asymptotic expression (3.15) and (3.31)–(3.33) respectively. We consider both a redistributed EGL of varying thickness (model A, a,c), and a non-redistributed EGL (model B, b,d).

Figure 6

Table 2.The maximum magnitude of the azimuthal shear stress for solid and fluid stress, normalised on the same value as table 1. See the caption of table 1 for further information.

Figure 7

Table 3.The maximum magnitude of the longitudinal elastic shear stress for the two-layer Stokes model, normalised on the solid stress value for a non-redistributed EGL with $t_{min}=1.5$, which has a non-dimensional stress value of 1.563 (note that this differs from tables 1 and 2). Stress values are given for a non-redistributed EGL and a redistributed EGL with amplitude factor ${\it\alpha}_{0}=1.8$, 2.2 and 3.4 respectively. The highlighted cells denote cases where the EGL protrudes further into the vessel between the cell nuclei as compared with at the cell nuclei.

Figure 8

Figure 6.Volume flux through the interface divided by the total inlet volume flux against ${\it\lambda}$ for EGL thicknesses of $t_{min}=0.25$, 0.5,1 and 1.5 for (a) a redistributed EGL and (b) a non-redistributed EGL.

Figure 9

Figure 7.(a) Cell centroids simulated throughout the entire vessel surface, as computed using the R spatstat package (Baddeley & Turner 2005) (black circles), also including the original cell centroids obtained from the biological data (red dots). (b,c) Monte Carlo envelopes for 99 simulations of the fitted model were generated to test the goodness of fit of the point particle model. The shaded regions show (b) the nearest-neighbour distance distribution function and (c) the L-function. In both cases, the simulated centroids (black lines) lie within the envelopes, hence offering statistical support for the appropriateness of the spatial distribution of the simulated centroids. The red lines show the mean value for each envelope.

Figure 10

Figure 8.(a) A bubble-growing algorithm is used to construct cell basal surfaces (red lines) from centroids taken from the biological data. Also overlaid are the cell–cell junctions obtained from the data. (b) The normalised cell height profile (solid line) as a function of an arclength parameter $s$ obtained by fitting a 10th-order polynomial to scaled digitised biological data provided by Barbee et al. (1994) (black dots). When used to create the topology of endothelial cells, ranges of heights and widths are informed by biological data.

Figure 11

Figure 9.(a) Cell height data and (b,c) characteristic shape profiles taken through two orthogonal sections of an unsheared bovine aortic endothelial cell. The heights were measured using atomic force microscopy. Figure reproduced from Barbee et al. (1994) (with permission). The figure illustrates the relatively localised elevated topology about the cell nucleus and also the profile used to create the cell nucleus topology.

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