Cerebral blood flow (CBF) reductions in Alzheimer’s disease (AD) patients and related mouse models have been recognized for decades, but the underlying mechanisms and resulting consequences on AD 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 wildtype animals, largely due to neutrophils that adhered in capillary segments and blocked blood flow. Administration of antibodies against the neutrophil marker Ly6G reduced the number of stalled capillaries, leading to an immediate increase in CBF and to rapidly improved performance in spatial and working memory tasks. This study identified a novel cellular mechanism that explains the majority of the CBF reduction seen in two mouse models of AD and demonstrated that improving CBF rapidly improved short-term memory function. Restoring cerebral perfusion by preventing neutrophil adhesion may provide a novel strategy for improving cognition in AD patients.

The formation of solid thin films from colloidal semiconductor quantum dots (QDs) is often accompanied by red shifts in excitonic transitions, but the mechanisms responsible for the red shifts are under debate. We quantitatively address this issue using optical absorption spectroscopy of two-dimensional (2D) and three-dimensional (3D) arrays of PbSe QDs with controlled inter-QD distance, which was determined by the length of alkanedithiol linking molecules. With decreasing inter-QD distance, the first and second exciton absorption peaks show increasing red shifts. Using thin films consisting of large and isolated QDs embedded in a matrix of small QDs, we determine that a dominant contribution to the observed red shift is due to changes in polarization of the dielectric environment surrounding each QD (∼88%), while electronic or transition dipole coupling plays a lesser role. However, the observed red shifts are more than 1 order of magnitude larger than theoretical predictions based on the dielectric polarization effect for spherical QDs. We attribute this anomalously large polarization effect to deviations of the exciton wave functions from eigenfunctions of the idealized spherical quantum well model.

The problem of the splitting of a suspension in bifurcating channels dividing into two branches of non equal flow rates is addressed. As observed for long, in particular in blood flow studies, the volume fraction of particles generally increases in the high flow rate branch and decreases in the other one. In the literature, this phenomenon is sometimes interpreted as the result of some attraction of the particles towards this high flow rate branch. In this paper, we focus on the existence of such an attraction through microfluidic experiments and two-dimensional simulations and show clearly that such an attraction does not occur but is, on the contrary, directed towards the low flow rate branch. Arguments for this attraction are given and a discussion on the sometimes misleading arguments found in the literature is proposed. Finally, the enrichment in particles in the high flow rate branch is shown to be mainly a consequence of the initial distribution in the inlet branch, which shows necessarily some depletion near the walls.

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. This paper presents an overview of a unified framework for finite element and spectral element methods in 1D, 2D and 3D in C ++ called FEEL++. The article is divided in two parts. The first part provides a digression through the design of the library as well as the main abstractions handled by it, namely, meshes, function spaces, operators, linear and bilinear forms and an embedded variational language. In every case, the closeness between the language developed in FEEL++ and the equivalent mathematical objects is highlighted. In the second part, examples using the mortar, Schwartz (non)overlapping, three fields and two fictitious domain-like methods (the Fat Boundary Method and the Penalty Method) are presented and numerically solved in the scope of the library.

International audienceA new framework for two-fluids flow using a Finite Element/Level Set method is presented and verified through the simulation of the rising of a bubble in a viscous fluid. This model is then enriched to deal with vesicles (which mimic red blood cells mechanical behavior) by introducing a Lagrange multiplier to constrain the inextensibility of the membrane. Moreover, high order polynomial approximation is used to increase the accuracy of the simulations. A validation of this model is finally presented on known behaviors of vesicles under flow such as ''tank treading'' and tumbling motions

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Abstract:The existence of cerebral blood flow (CBF) reductions in Alzheimer's disease (AD) patients and related mouse models has been known for decades, but the underlying mechanisms and the resulting impacts on cognitive function and AD pathogenesis remain poorly understood. In the APP/PS1 mouse model of AD we found that an increased number of cortical capillaries had stalled blood flow as compared to wildtype animals, largely due to leukocytes that adhered in capillary segments and blocked blood flow. These capillary stalls were an early feature of disease development, appearing before amyloid deposits.Administration of antibodies against the neutrophil marker Ly6G reduced the number of stalled capillaries, leading to an immediate increase in CBF and to rapidly improved performance in spatial and working memory tasks. Our work has thus identified a cellular mechanism that explains the majority of the CBF reduction seen in a mouse model of AD and has also demonstrated that improving CBF rapidly improved short-term memory function. Restoring cerebral perfusion by preventing the leukocyte adhesion that plugs capillaries may provide a novel strategy for improving cognition in AD patients.