No abstract

At its most fundamental level, cerebral blood flow (CBF) may be modeled as fluid flow driven through a network of resistors by pressure gradients. The composition of the blood as well as the cross-sectional area and length of a vessel are the major determinants of its resistance to flow. Here, we introduce a vascular graph modeling framework based on these principles that can compute blood pressure, flow and scalar transport in realistic vascular networks. By embedding the network in a computational grid representative of brain tissue, the interaction between the two compartments can be captured in a truly three-dimensional manner and may be applied, among others, to simulate oxygen extraction from the vessels. Moreover, we have devised an upscaling algorithm that significantly reduces the computational expense and eliminates the need for detailed knowledge on the topology of the capillary bed. The vascular graph framework has been applied to investigate the effect of local vascular dilation and occlusion on the flow in the surrounding network.

A better knowledge of the flow and pressure distribution in realistic microvascular networks is needed for improving our understanding of neurovascular coupling mechanisms and the related measurement techniques. Here, numerical simulations with discrete tracking of red blood cells (RBCs) are performed in three realistic microvascular networks from the mouse cerebral cortex. Our analysis is based on trajectories of individual RBCs and focuses on layer-specific flow phenomena until a cortical depth of 1 mm. The individual RBC trajectories reveal that in the capillary bed RBCs preferentially move in plane. Hence, the capillary flow field shows laminar patterns and a layer-specific analysis is valid. We demonstrate that for RBCs entering the capillary bed close to the cortical surface (< 400 μm) the largest pressure drop takes place in the capillaries (37%), while for deeper regions arterioles are responsible for 61% of the total pressure drop. Further flow characteristics, such as capillary transit time or RBC velocity, also vary significantly over cortical depth. Comparison of purely topological characteristics with flow-based ones shows that a combined interpretation of topology and flow is indispensable. Our results provide evidence that it is crucial to consider layer-specific differences for all investigations related to the flow and pressure distribution in the cortical vasculature. These findings support the hypothesis that for an efficient oxygen up-regulation at least two regulation mechanisms must be playing hand in hand, namely cerebral blood flow increase and microvascular flow homogenization. However, the contribution of both regulation mechanisms to oxygen up-regulation likely varies over depth.

No abstract

Targeting of permissive entry sites is crucial for bacterial infection. The targeting mechanisms are incompletely understood. We have analyzed target-site selection by S . Typhimurium. This enteropathogenic bacterium employs adhesins (e.g. fim ) and the type III secretion system 1 (TTSS-1) for host cell binding, the triggering of ruffles and invasion. Typically, S . Typhimurium invasion is focused on a subset of cells and multiple bacteria invade via the same ruffle. It has remained unclear how this is achieved. We have studied target-site selection in tissue culture by time lapse microscopy, movement pattern analysis and modeling. Flagellar motility (but not chemotaxis) was required for reaching the host cell surface in vitro. Subsequently, physical forces trapped the pathogen for ∼1.5–3 s in “near surface swimming”. This increased the local pathogen density and facilitated “scanning” of the host surface topology. We observed transient TTSS-1 and fim -independent “stopping” and irreversible TTSS-1-mediated docking, in particular at sites of prominent topology, i.e. the base of rounded-up cells and membrane ruffles. Our data indicate that target site selection and the cooperative infection of membrane ruffles are attributable to near surface swimming. This mechanism might be of general importance for understanding infection by flagellated bacteria.