Reductions of baseline cerebral blood flow (CBF) of ∼10–20% are a common symptom of Alzheimer’s disease (AD) that appear early in disease progression and correlate with the severity of cognitive impairment. These CBF deficits are replicated in mouse models of AD and recent work shows that increasing baseline CBF can rapidly improve the performance of AD mice on short term memory tasks. Despite the potential role these data suggest for CBF reductions in causing cognitive symptoms and contributing to brain pathology in AD, there remains a poor understanding of the molecular and cellular mechanisms causing them. This review compiles data on CBF reductions and on the correlation of AD-related CBF deficits with disease comorbidities (e.g. cardiovascular and genetic risk factors) and outcomes (e.g. cognitive performance and brain pathology) from studies in both patients and mouse models, and discusses several potential mechanisms proposed to contribute to CBF reductions, based primarily on work in AD mouse models. Future research aimed at improving our understanding of the importance of and interplay between different mechanisms for CBF reduction, as well as at determining the role these mechanisms play in AD patients could guide the development of future therapies that target CBF reductions in AD.

Obesity is linked to increased risk for and severity of Alzheimer’s disease (AD). Cerebral blood flow (CBF) reductions are an early feature of AD and are also linked to obesity. We recently showed that non-flowing capillaries, caused by adhered neutrophils, contribute to CBF reduction in mouse models of AD. Because obesity could exacerbate the vascular inflammation likely underlying this neutrophil adhesion, we tested links between obesity and AD by feeding APP/PS1 mice a high fat diet (Hfd) and evaluating behavioral, physiological, and pathological changes. We found trends toward poorer memory performance in APP/PS1 mice fed a Hfd, impaired social interactions with either APP/PS1 genotype or a Hfd, and synergistic impairment of sensory-motor function in APP/PS1 mice fed a Hfd. The Hfd led to increases in amyloid-beta monomers and plaques in APP/PS1 mice, as well as increased brain inflammation. These results agree with previous reports showing obesity exacerbates AD-related pathology and symptoms in mice. We used a crowd-sourced, citizen science approach to analyze imaging data to determine the impact of the APP/PS1 genotype and a Hfd on capillary stalling and CBF. Surprisingly, we did not see an increase in the number of non-flowing capillaries or a worsening of the CBF deficit in APP/PS1 mice fed a Hfd as compared to controls, suggesting that capillary stalling is not a mechanistic link between a Hfd and increased severity of AD in mice. Reducing capillary stalling by blocking neutrophil adhesion improved CBF and short-term memory function in APP/PS1 mice, even when fed a Hfd.

The insensitivity of multiphoton microscopy to optical scattering enables high-resolution, high-contrast imaging deep into tissue, including in live animals. Scattering does, however, severely limit the use of spectral dispersion techniques to improve spectral resolution. In practice, this limited spectral resolution together with the need for multiple excitation wavelengths to excite different fluorophores limits multiphoton microscopy to imaging a few, spectrally distinct fluorescent labels at a time, restricting the complexity of biological processes that can be studied. Here, we demonstrate a hyperspectral multiphoton microscope that utilizes three different wavelength excitation sources together with multiplexed fluorescence emission detection using angle-tuned bandpass filters. This microscope maintains scattering insensitivity, while providing high enough spectral resolution on the emitted fluorescence and capitalizing on the wavelength-dependent nonlinear excitation of fluorescent dyes to enable clean separation of multiple, spectrally overlapping labels, in vivo. We demonstrated the utility of this instrument for spectral separation of closely overlapped fluorophores in samples containing 10 different colors of fluorescent beads, live cells expressing up to seven different fluorescent protein fusion constructs, and in multiple in vivo preparations in mouse cortex and inflamed skin, with up to eight different cell types or tissue structures distinguished.

Microhemorrhages are common in the aging brain and are thought to contribute to cognitive decline and the development of neurodegenerative diseases, such as Alzheimer’s disease. Chronic aspirin therapy is widespread in older individuals and decreases the risk of coronary artery occlusions and stroke. There remains a concern that such aspirin usage may prolong bleeding after a vessel rupture in the brain, leading to larger bleeds that cause more damage to the surrounding tissue. Here, we aimed to understand the influence of aspirin usage on the size of cortical microhemorrhages and explored the impact of age. We used femtosecond laser ablation to rupture arterioles in the cortex of both young (2–5 months old) and aged (18–29 months old) mice dosed on aspirin in their drinking water and measured the extent of penetration of both red blood cells and blood plasma into the surrounding tissue. We found no difference in microhemorrhage size for both young and aged mice dosed on aspirin, as compared to controls (hematoma diameter = 104 +/- 39 (97 +/- 38) μm in controls and 109 +/- 25 (101 +/- 28) μm in aspirin-treated young (aged) mice; mean +/- SD). In contrast, young mice treated with intravenous heparin had an increased hematoma diameter of 136 +/- 44 μm. These data suggest that aspirin does not increase the size of microhemorrhages, supporting the safety of aspirin usage.

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.

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.

Rapid growth and perivascular invasion are hallmarks of glioblastoma (GBM) that have been attributed to the presence of cancer stem-like cells (CSCs) and their association with the perivascular niche. However, the mechanisms by which the perivascular niche regulates GBM invasion and CSCs remain poorly understood due in part to a lack of relevant model systems. To simulate perivascular niche conditions and analyze consequential changes of GBM growth and invasion, patient-derived GBM spheroids were co-cultured with brain endothelial cells (ECs) in microfabricated collagen gels. Integrating these systems with 3D imaging and biochemical assays revealed that ECs increase GBM invasiveness and growth through interleukin-8 (IL-8)-mediated enrichment of CSCs. Blockade of IL-8 inhibited these effects in GBM-EC co-cultures, while IL-8 supplementation increased CSC-mediated growth and invasion in GBM-monocultures. Experiments in mice confirmed that ECs and IL-8 stimulate intracranial tumor growth and invasion in vivo. Collectively, perivascular niche conditions promote GBM growth and invasion by increasing CSC frequency, and IL-8 may be explored clinically to inhibit these interactions.

Cerebral blood flow (CBF) reductions in Alzheimer’s disease patients and related mouse models have been recognized for decades, but the underlying mechanisms and resulting consequences for Alzheimer’s disease pathogenesis remain poorly understood. In APP/PS1 and 5xFAD mice we found that an increased number of cortical capillaries had stalled blood flow as compared to in wild-type animals, largely due to neutrophils that had adhered in capillary segments and blocked blood flow. Administration of antibodies against the neutrophil marker Ly6G reduced the number of stalled capillaries, leading to both an immediate increase in CBF and rapidly improved performance in spatial and working memory tasks. This study identified a previously uncharacterized cellular mechanism that explains the majority of the CBF reduction seen in two mouse models of Alzheimer’s disease and demonstrated that improving CBF rapidly enhanced short-term memory function. Restoring cerebral perfusion by preventing neutrophil adhesion may provide a strategy for improving cognition in Alzheimer’s disease patients

Computations are described which estimate flows in all branches of the cortical surface arteriole network from two-photon excited fluorescence (2PEF) microscopy images which provide the network topology and, in selected branches red blood cell (RBC) speeds and lumen diameters. Validation is done by comparing the flow predicted by the model with experimentally measured flows and by comparing the predicted flow redistribution in the network due to single-vessel strokes with experimental observations. The model predicts that tissue is protected from RBC flow decreases caused by multiple occlusions of surface arterioles but not penetrating arterioles. The model can also be used to study flow rerouting due to vessel dilations and constrictions.

Animals collect sensory information from the world and make adaptive choices about how to respond to it. Here, we reveal a network motif in the brain for one of the most fundamental behavioral choices made by bilaterally symmetric animals: whether to respond to a sensory stimulus by moving to the left or to the right. We define network connectivity in the hindbrain important for the lateralized escape behavior of zebrafish and then test the role of neurons by using laser ablations and behavioral studies. Key inhibitory neurons in the circuit lie in a column of morphologically similar cells that is one of a series of such columns that form a developmental and functional ground plan for building hindbrain networks. Repetition within the columns of the network motif we defined may therefore lie at the foundation of other lateralized behavioral choices.