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      Depth-dependent flow and pressure characteristics in cortical microvascular networks

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          Abstract

          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.

          Author summary

          The brain consumes approximately 20% of the total oxygen used by the human body. An efficient and robust energy supply is essential for the brain’s functioning. The brain is able to up-regulate its oxygen supply in the proximity of neuronal activation. However, the details of the underlying vascular regulation mechanisms remain unknown. To improve the understanding of the blood flow patterns in the cortex we perform numerical simulations in realistic microvascular networks. In contrast to experimental measurements, numerical computations offer the advantage that the whole pressure and flow field is available for analysis. It is well established that the cerebral cortex is organized in laminar fashion and indeed our results reveal that the flow field in the capillary bed shows significant layer-specific differences. Those differences must be taken into account in future numerical and experimental works. Furthermore, it seems likely that multiple regulation mechanisms are playing hand in hand and that their impact differs over depth.

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          Correlations of neuronal and microvascular densities in murine cortex revealed by direct counting and colocalization of nuclei and vessels.

          It is well known that the density of neurons varies within the adult brain. In neocortex, this includes variations in neuronal density between different lamina as well as between different regions. Yet the concomitant variation of the microvessels is largely uncharted. Here, we present automated histological, imaging, and analysis tools to simultaneously map the locations of all neuronal and non-neuronal nuclei and the centerlines and diameters of all blood vessels within thick slabs of neocortex from mice. Based on total inventory measurements of different cortical regions ( approximately 10(7) cells vectorized across brains), these methods revealed: (1) In three dimensions, the mean distance of the center of neuronal somata to the closest microvessel was 15 mum. (2) Volume samples within lamina of a given region show that the density of microvessels does not match the strong laminar variation in neuronal density. This holds for both agranular and granular cortex. (3) Volume samples in successive radii from the midline to the ventral-lateral edge, where each volume summed the number of cells and microvessels from the pia to the white matter, show a significant correlation between neuronal and microvessel densities. These data show that while neuronal and vascular densities do not track each other on the 100 mum scale of cortical lamina, they do track each other on the 1-10 mm scale of the cortical mantle. The absence of a disproportionate density of blood vessels in granular lamina is argued to be consistent with the initial locus of functional brain imaging signals.
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            The roles of cerebral blood flow, capillary transit time heterogeneity, and oxygen tension in brain oxygenation and metabolism

            Normal brain function depends critically on moment-to-moment regulation of oxygen supply by the bloodstream to meet changing metabolic needs. Neurovascular coupling, a range of mechanisms that converge on arterioles to adjust local cerebral blood flow (CBF), represents our current framework for understanding this regulation. We modeled the combined effects of CBF and capillary transit time heterogeneity (CTTH) on the maximum oxygen extraction fraction (OEF max) and metabolic rate of oxygen that can biophysically be supported, for a given tissue oxygen tension. Red blood cell velocity recordings in rat brain support close hemodynamic–metabolic coupling by means of CBF and CTTH across a range of physiological conditions. The CTTH reduction improves tissue oxygenation by counteracting inherent reductions in OEF max as CBF increases, and seemingly secures sufficient oxygenation during episodes of hyperemia resulting from cortical activation or hypoxemia. In hypoperfusion and states of blocked CBF, both lower oxygen tension and CTTH may secure tissue oxygenation. Our model predicts that disturbed capillary flows may cause a condition of malignant CTTH, in which states of higher CBF display lower oxygen availability. We propose that conditions with altered capillary morphology, such as amyloid, diabetic or hypertensive microangiopathy, and ischemia–reperfusion, may disturb CTTH and thereby flow-metabolism coupling and cerebral oxygen metabolism.
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              Blood flow in microvascular networks. Experiments and simulation.

              A theoretical model has been developed to simulate blood flow through large microcirculatory networks. The model takes into account the dependence of apparent viscosity of blood on vessel diameter and hematocrit (the Fahraeus-Lindqvist effect), the reduction of intravascular hematocrit relative to the inflow hematocrit of a vessel (the Fahraeus effect), and the disproportionate distribution of red blood cells and plasma at arteriolar bifurcations (phase separation). The model was used to simulate flow in three microvascular networks in the rat mesentery with 436,583, and 913 vessel segments, respectively, using experimental data (length, diameter, and topological organization) obtained from the same networks. Measurements of hematocrit and flow direction in all vessel segments of these networks tested the validity of model results. These tests demonstrate that the prediction of parameters for individual vessel segments in large networks exhibits a high degree of uncertainty; for example, the squared coefficient of correlation between predicted and measured hematocrit of single vessel segments ranges only between 0.15 and 0.33. In contrast, the simulation of integrated characteristics of the network hemodynamics, such as the mean segment hematocrit or the distribution of blood flow velocities, is very precise. In addition, the following conclusions were derived from the comparison of predicted and measured values: 1) The low capillary hematocrits found in mesenteric microcirculatory networks as well as their heterogeneity can be explained on the basis of the Fahraeus effect and phase-separation phenomena. 2) The apparent viscosity of blood in vessels of the investigated tissue with diameters less than 15 microns is substantially higher than expected compared with measurements in glass tubes with the same diameter.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                February 2017
                14 February 2017
                : 13
                : 2
                : e1005392
                Affiliations
                [1 ]Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
                [2 ]Department of Physics, University of California at San Diego, La Jolla, California, United States of America
                [3 ]Section of Neurobiology, University of California, La Jolla, California, United States of America
                [4 ]Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
                University of Virginia, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                • Conceptualization: BW PJ FS.

                • Data curation: FS.

                • Formal analysis: FS.

                • Funding acquisition: BW PJ.

                • Investigation: FS.

                • Methodology: BW PJ FS.

                • Project administration: BW PJ.

                • Resources: DK PST BW PJ.

                • Software: FS.

                • Supervision: BW PJ.

                • Validation: FS.

                • Visualization: FS.

                • Writing – original draft: FS.

                • Writing – review & editing: DK BW PJ.

                Author information
                http://orcid.org/0000-0001-8018-5276
                Article
                PCOMPBIOL-D-16-01643
                10.1371/journal.pcbi.1005392
                5347440
                28196095
                29ceccc7-26b4-489e-91b6-23e5e52f6189
                © 2017 Schmid et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 October 2016
                : 31 January 2017
                Page count
                Figures: 3, Tables: 5, Pages: 22
                Funding
                Funding for this research was provided by the Swiss National Science Foundation Grant No. 140660. BW is a member of the Clinical Research Priority Program of the University of Zurich on Molecular Imaging. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Capillaries
                Medicine and Health Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Capillaries
                Biology and Life Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arterioles
                Medicine and Health Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Arterioles
                Physical Sciences
                Chemistry
                Chemical Elements
                Oxygen
                Physical Sciences
                Physics
                Classical Mechanics
                Continuum Mechanics
                Fluid Mechanics
                Fluid Dynamics
                Flow Rate
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Blood
                Blood Flow
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Blood
                Blood Flow
                Biology and Life Sciences
                Physiology
                Body Fluids
                Blood
                Blood Flow
                Medicine and Health Sciences
                Physiology
                Body Fluids
                Blood
                Blood Flow
                Medicine and Health Sciences
                Hematology
                Blood
                Blood Flow
                Biology and Life Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Venules
                Medicine and Health Sciences
                Anatomy
                Cardiovascular Anatomy
                Blood Vessels
                Venules
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Physical Sciences
                Physics
                Classical Mechanics
                Continuum Mechanics
                Fluid Mechanics
                Fluid Dynamics
                Flow Field
                Custom metadata
                vor-update-to-uncorrected-proof
                2017-03-01
                All relevant data are within the paper and its Supporting Information file. Additionally the raw data is available at: https://doi.org/10.5281/zenodo.269650.

                Quantitative & Systems biology
                Quantitative & Systems biology

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