Distinct molecular composition of blood and lymphatic vascular endothelial cell junctions establishes specific functional barriers within the peripheral lymph node

Lymph nodes are strategically localized at the interfaces between the blood and lymphatic vascular system, delivering immune cells and antigens to the lymph node. As cellular junctions of endothelial cells actively regulate vascular permeability and cell traffic, we have investigated their molecular composition by performing an extensive immunofluorescence study for adherens and tight junction molecules, including vascular endothelium (VE)-cadherin, the vascular claudins 1, 3, 5 and 12, occludin, members of the junctional adhesion molecule family plus endothelial cell-selective adhesion molecule (ESAM)-1, platelet endothelial cell adhesion molecule-1, ZO-1 and ZO-2. We found that junctions of high endothelial venules (HEV), which serve as entry site for naive lymphocytes, are unique due to their lack of the endothelial cell-specific claudin-5. LYVE-1(+) sinus-lining endothelial cells form a diffusion barrier for soluble molecules that arrive at the afferent lymph and use claudin-5 and ESAM-1 to establish characteristic tight junctions. Analysis of the spatial relationship between the different vascular compartments revealed that HEV extend beyond the paracortex into the medullary sinuses, where they are protected from direct contact with the lymph by sinus-lining endothelial cells. The specific molecular architecture of cellular junctions present in blood and lymphatic vessel endothelium in peripheral lymph nodes establishes distinct barriers controlling the distribution of antigens and immune cells within this tissue.

Effect of vascular targeting agent in rat tumor model: dynamic contrast-enhanced versus diffusion-weighted MR imaging

PURPOSE: To compare dynamic contrast material-enhanced magnetic resonance (MR) imaging and diffusion-weighted MR imaging for noninvasive evaluation of early and late effects of a vascular targeting agent in a rat tumor model. MATERIALS AND METHODS: The study protocol was approved by the local ethics committee for animal care and use. Thirteen rats with one rhabdomyosarcoma in each flank (26 tumors) underwent dynamic contrast-enhanced imaging and diffusion-weighted echo-planar imaging in a 1.5-T MR unit before intraperitoneal injection of combretastatin A4 phosphate and at early (1 and 6 hours) and later (2 and 9 days) follow-up examinations after the injection. Histopathologic examination was performed at each time point. The apparent diffusion coefficient (ADC) of each tumor was calculated separately on the basis of diffusion-weighted images obtained with low b gradient values (ADC(low); b = 0, 50, and 100 sec/mm(2)) and high b gradient values (ADC(high); b = 500, 750, and 1000 sec/mm(2)). The difference between ADC(low) and ADC(high) was used as a surrogate measure of tissue perfusion (ADC(low) - ADC(high) = ADC(perf)). From the dynamic contrast-enhanced MR images, the volume transfer constant k and the initial slope of the contrast enhancement-time curve were calculated. For statistical analyses, a paired two-tailed Student t test and linear regression analysis were used. RESULTS: Early after administration of combretastatin, all perfusion-related parameters (k, initial slope, and ADC(perf)) decreased significantly (P < .001); at 9 days after combretastatin administration, they increased significantly (P < .001). Changes in ADC(perf) were correlated with changes in k (R(2) = 0.46, P < .001) and the initial slope (R(2) = 0.67, P < .001). CONCLUSION: Both dynamic contrast-enhanced MR imaging and diffusion-weighted MR imaging allow monitoring of perfusion changes induced by vascular targeting agents in tumors. Diffusion-weighted imaging provides additional information about intratumoral cell viability versus necrosis after administration of combretastatin.

Mixing-cell boundary conditions and apparent mass balance errors for advective-dispersive solute transport

In many field or laboratory situations, well-mixed reservoirs like, for instance, injection or detection wells and gas distribution or sampling chambers define boundaries of transport domains. Exchange of solutes or gases across such boundaries can occur through advective or diffusive processes. First we analyzed situations, where the inlet region consists of a well-mixed reservoir, in a systematic way by interpreting them in terms of injection type. Second, we discussed the mass balance errors that seem to appear in case of resident injections. Mixing cells (MC) can be coupled mathematically in different ways to a domain where advective-dispersive transport occurs: by assuming a continuous solute flux at the interface (flux injection, MC-FI), or by assuming a continuous resident concentration (resident injection). In the latter case, the flux leaving the mixing cell can be defined in two ways: either as the value when the interface is approached from the mixing-cell side (MC-RT -), or as the value when it is approached from the column side (MC-RT +). Solutions of these injection types with constant or-in one case-distance-dependent transport parameters were compared to each other as well as to a solution of a two-layer system, where the first layer was characterized by a large dispersion coefficient. These solutions differ mainly at small Peclet numbers. For most real situations, the model for resident injection MC-RI + is considered to be relevant. This type of injection was modeled with a constant or with an exponentially varying dispersion coefficient within the porous medium. A constant dispersion coefficient will be appropriate for gases because of the Eulerian nature of the usually dominating gaseous diffusion coefficient, whereas the asymptotically growing dispersion coefficient will be more appropriate for solutes due to the Lagrangian nature of mechanical dispersion, which evolves only with the fluid flow. Assuming a continuous resident concentration at the interface between a mixing cell and a column, as in case of the MC-RI + model, entails a flux discontinuity. This flux discontinuity arises inherently from the definition of a mixing cell: the mixing process is included in the balance equation, but does not appear in the description of the flux through the mixing cell. There, only convection appears because of the homogeneous concentration within the mixing cell. Thus, the solute flux through a mixing cell in close contact with a transport domain is generally underestimated. This leads to (apparent) mass balance errors, which are often reported for similar situations and erroneously used to judge the validity of such models. Finally, the mixing cell model MC-RI + defines a universal basis regarding the type of solute injection at a boundary. Depending on the mixing cell parameters, it represents, in its limits, flux as well as resident injections. (C) 1998 Elsevier Science B.V. All rights reserved.

Bifurcation Analysis of Reaction Diffusion Systems on Arbitrary Surfaces

In this article we present a computational framework for isolating spatial patterns arising in the steady states of reaction-diffusion systems. Such systems have been used to model many different phenomena in areas such as developmental and cancer biology, cell motility and material science. Often one is interested in identifying parameters which will lead to a particular pattern. To attempt to answer this, we compute eigenpairs of the Laplacian on a variety of domains and use linear stability analysis to determine parameter values for the system that will lead to spatially inhomogeneous steady states whose patterns correspond to particular eigenfunctions. This method has previously been used on domains and surfaces where the eigenvalues and eigenfunctions are found analytically in closed form. Our contribution to this methodology is that we numerically compute eigenpairs on arbitrary domains and surfaces. Here we present various examples and demonstrate that mode isolation is straightforward especially for low eigenvalues. Additionally we see that if two or more eigenvalues are in a permissible range then the inhomogeneous steady state can be a linear combination of the respective eigenfunctions. Finally we show an example which suggests that pattern formation is robust on similar surfaces in cases that the surface either has or does not have a boundary.