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Increased incidence of stalled capillary blood flow caused by adhesion of leucocytes to the brain microvascular endothelium leads to a 17% reduction of cerebral blood flow and exacerbates short-term memory loss in multiple mouse models of Alzheimer's disease. Here, we report that vascular endothelial growth factor (VEGF) signalling at the luminal side of the brain microvasculature plays an integral role in the capillary stalling phenomenon of the APP/PS1 mouse model. Administration of the anti-mouse VEGF-A164 antibody, an isoform that inhibits blood-brain barrier hyperpermeability, reduced the number of stalled capillaries within an hour of injection, leading to an immediate increase in average capillary blood flow but not capillary diameter. VEGF-A inhibition also reduced the overall endothelial nitric oxide synthase protein concentrations, increased occludin levels and decreased the penetration of circulating Evans Blue dye across the blood-brain barrier into the brain parenchyma, suggesting increased blood-brain barrier integrity. Capillaries prone to neutrophil adhesion after anti-VEGF-A treatment also had lower occludin concentrations than flowing capillaries. Taken together, our findings demonstrate that VEGF-A signalling in APP/PS1 mice contributes to aberrant endothelial nitric oxide synthase /occludin-associated blood-brain barrier permeability, increases the incidence of capillary stalls, and leads to reductions in cerebral blood flow. Reducing leucocyte adhesion by inhibiting luminal VEGF signalling may provide a novel and well-tolerated strategy for improving brain microvascular blood flow in Alzheimer's disease patients. [ABSTRACT FROM AUTHOR]

Exercise exerts a beneficial effect on the major pathological and clinical symptoms associated with Alzheimer's disease in humans and mouse models of the disease. While numerous mechanisms for such benefits from exercise have been proposed, a clear understanding of the causal links remains elusive. Recent studies also suggest that cerebral blood flow in the brain of both Alzheimer's patients and mouse models of the disease is decreased and that the cognitive symptoms can be improved when blood flow is restored. We therefore hypothesized that the mitigating effect of exercise on the development and progression of Alzheimer's disease may be mediated through an increase in the otherwise reduced brain blood flow. To test this idea, we performed a pilot study to examine the impact of three months of voluntary wheel running in a small cohort of ~1-year-old APP/PS1 mice on short-term memory function, brain inflammation, amyloid deposition, and baseline cerebral blood flow. Our findings that exercise led to a trend toward improved spatial short-term memory, reduced brain inflammation, markedly increased neurogenesis in the dentate gyrus, and a reduction in hippocampal amyloid-beta deposits are consistent with other reports on the impact of exercise on the progression of Alzheimer's related symptoms in mouse models. Notably, we did not observe any impact of wheel running on overall baseline blood flow nor on the incidence of non-flowing capillaries, a mechanism we recently identified as one contributing factor to cerebral blood flow deficits in mouse models of Alzheimer's disease. Overall, our findings add to the emerging picture of differential effects of exercise on cognition and blood flow in Alzheimer's disease pathology by showing that capillary stalling is not decreased following exercise. [ABSTRACT FROM AUTHOR]

Despite the key role of the capillaries in neurovascular function, a thorough characterization of cerebral capillary network properties is currently lacking. Here, we define a range of metrics (geometrical, topological, flow, mass transfer, and robustness) for quantification of structural differences between brain areas, organs, species, or patient populations and, in parallel, digitally generate synthetic networks that replicate the key organizational features of anatomical networks (isotropy, connectedness, space-filling nature, convexity of tissue domains, characteristic size). To reach these objectives, we first construct a database of the defined metrics for healthy capillary networks obtained from imaging of mouse and human brains. Results show that anatomical networks are topologically equivalent between the two species and that geometrical metrics only differ in scaling. Based on these results, we then devise a method which employs constrained Voronoi diagrams to generate 3D model synthetic cerebral capillary networks that are locally randomized but homogeneous at the network-scale. With appropriate choice of scaling, these networks have equivalent properties to the anatomical data, demonstrated by comparison of the defined metrics. The ability to synthetically replicate cerebral capillary networks opens a broad range of applications, ranging from systematic computational studies of structure-function relationships in healthy capillary networks to detailed analysis of pathological structural degeneration, or even to the development of templates for fabrication of 3D biomimetic vascular networks embedded in tissue-engineered constructs. [ABSTRACT FROM AUTHOR]

The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to our understanding of the role of vascular structure in normal physiology and in disease mechanisms. The segmentation of vessels, a core image analysis problem, is a bottleneck that has prevented the systematic comparison of 3D vascular architecture across experimental populations. We explored the use of convolutional neural networks to segment 3D vessels within volumetric in vivo images acquired by multiphoton microscopy. We evaluated different network architectures and machine learning techniques in the context of this segmentation problem. We show that our optimized convolutional neural network architecture with a customized loss function, which we call DeepVess, yielded a segmentation accuracy that was better than state-of-the-art methods, while also being orders of magnitude faster than the manual annotation. To explore the effects of aging and Alzheimer’s disease on capillaries, we applied DeepVess to 3D images of cortical blood vessels in young and old mouse models of Alzheimer’s disease and wild type littermates. We found little difference in the distribution of capillary diameter or tortuosity between these groups, but did note a decrease in the number of longer capillary segments (>75μm) in aged animals as compared to young, in both wild type and Alzheimer’s disease mouse models. [ABSTRACT FROM AUTHOR]

This paper describes the development and validation of a virtual microstructure generator that can be used to fabricate a virtual, two-dimensional (2D) microstructure of particle-reinforced composites in general, and of asphalt concrete and/or cement concrete mixtures in particular. In the generator, some core geometric characteristics such as aggregate gradation, aggregate volume fraction, and angularity were used to transform data from a three-dimensional (3D) mixture into its 2D microstructure. Resulting virtual microstructures were then compared with real cross-sectional microstructure images obtained from actual samples for validation. Comparison aided with statistical analyses presented a good agreement between the virtual and real microstructures, which demonstrates that the 3D-2D transformation algorithms were properly developed and implemented into the virtual microstructure generator. A properly generated virtual microstructure of the composites can be incorporated with computational microstructure modeling which leads to significant time and cost savings from expensive laboratory fabrication and testing of actual specimens. [ABSTRACT FROM AUTHOR]

Background: We recently found that increased obstructions in capillaries caused by adhesion of leucocytes in the cortical microvascular leads to a ∼20% reduction of cerebral blood flow (CBF) in mouse models of Alzheimer's disease. Here, we explore the contribution of peripheral Vascular Endothelial Growth Factor (VEGF) signaling at the luminal side of the brain microvasculature as a driver of capillary stalling and blood‐brain barrier (BBB) integrity in the APP/PS1 mouse model of AD. Method: The number of stalled cortical capillaries and blood flow speeds were measured in cortical capillaries using high resolution in vivo two‐photon imaging, before and after one hour and two weeks of i.p. anti‐VEGF164 antibody injection. Capillary stalls were measured using the citizen science platform Stall Catchers. The blood‐brain barrier integrity was analyzed using immunohistochemistry. Result: We found that inhibition of VEGF signaling in APP/PS1 mice reduces capillary stalling by ∼75% and improves average capillary speed by ∼50%. In contrast, no such effects were seen in wild‐type saline‐injected controls. The anti‐VEGF164 injection also reduced overall eNOS protein concentrations and increased the tight junction protein levels of occludin. Intriguingly, the few APP/PS1 capillaries that were still prone to obstructions after anti‐VEGF treatment had lower occludin concentrations between their endothelial cells than flowing capillaries. We further demonstrate that capillary stalling reductions and capillary speed improvements occur within an hour of intraperitoneal anti‐mouseVEGF164 injection. At the same time scale, anti‐VEGF treatment reduced Evan's blue diffusion across the BBB. Conclusion: This data demonstrates that peripheral inhibition of VEGF‐signaling in APP/PS1 mice restores aberrant eNOS/occludin‐associated BBB permeability, and is associated with decreased capillary stalls and increased CBF. [ABSTRACT FROM AUTHOR]