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      The mechanisms behind perivascular fluid flow

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          Abstract

          Flow of cerebrospinal fluid (CSF) in perivascular spaces (PVS) is one of the key concepts involved in theories concerning clearance from the brain. Experimental studies have demonstrated both net and oscillatory movement of microspheres in PVS (Mestre et al. (2018), Bedussi et al. (2018)). The oscillatory particle movement has a clear cardiac component, while the mechanisms involved in net movement remain disputed. Using computational fluid dynamics, we computed the CSF velocity and pressure in a PVS surrounding a cerebral artery subject to different forces, representing arterial wall expansion, systemic CSF pressure changes and rigid motions of the artery. The arterial wall expansion generated velocity amplitudes of 60–260 μm/s, which is in the upper range of previously observed values. In the absence of a static pressure gradient, predicted net flow velocities were small (<0.5 μm/s), though reaching up to 7 μm/s for non-physiological PVS lengths. In realistic geometries, a static systemic pressure increase of physiologically plausible magnitude was sufficient to induce net flow velocities of 20–30 μm/s. Moreover, rigid motions of the artery added to the complexity of flow patterns in the PVS. Our study demonstrates that the combination of arterial wall expansion, rigid motions and a static CSF pressure gradient generates net and oscillatory PVS flow, quantitatively comparable with experimental findings. The static CSF pressure gradient required for net flow is small, suggesting that its origin is yet to be determined.

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          Most cited references51

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          A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β.

          Because it lacks a lymphatic circulation, the brain must clear extracellular proteins by an alternative mechanism. The cerebrospinal fluid (CSF) functions as a sink for brain extracellular solutes, but it is not clear how solutes from the brain interstitium move from the parenchyma to the CSF. We demonstrate that a substantial portion of subarachnoid CSF cycles through the brain interstitial space. On the basis of in vivo two-photon imaging of small fluorescent tracers, we showed that CSF enters the parenchyma along paravascular spaces that surround penetrating arteries and that brain interstitial fluid is cleared along paravenous drainage pathways. Animals lacking the water channel aquaporin-4 (AQP4) in astrocytes exhibit slowed CSF influx through this system and a ~70% reduction in interstitial solute clearance, suggesting that the bulk fluid flow between these anatomical influx and efflux routes is supported by astrocytic water transport. Fluorescent-tagged amyloid β, a peptide thought to be pathogenic in Alzheimer's disease, was transported along this route, and deletion of the Aqp4 gene suppressed the clearance of soluble amyloid β, suggesting that this pathway may remove amyloid β from the central nervous system. Clearance through paravenous flow may also regulate extracellular levels of proteins involved with neurodegenerative conditions, its impairment perhaps contributing to the mis-accumulation of soluble proteins.
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            Sleep drives metabolite clearance from the adult brain.

            The conservation of sleep across all animal species suggests that sleep serves a vital function. We here report that sleep has a critical function in ensuring metabolic homeostasis. Using real-time assessments of tetramethylammonium diffusion and two-photon imaging in live mice, we show that natural sleep or anesthesia are associated with a 60% increase in the interstitial space, resulting in a striking increase in convective exchange of cerebrospinal fluid with interstitial fluid. In turn, convective fluxes of interstitial fluid increased the rate of β-amyloid clearance during sleep. Thus, the restorative function of sleep may be a consequence of the enhanced removal of potentially neurotoxic waste products that accumulate in the awake central nervous system.
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              Measuring the thickness of the human cerebral cortex from magnetic resonance images.

              Accurate and automated methods for measuring the thickness of human cerebral cortex could provide powerful tools for diagnosing and studying a variety of neurodegenerative and psychiatric disorders. Manual methods for estimating cortical thickness from neuroimaging data are labor intensive, requiring several days of effort by a trained anatomist. Furthermore, the highly folded nature of the cortex is problematic for manual techniques, frequently resulting in measurement errors in regions in which the cortical surface is not perpendicular to any of the cardinal axes. As a consequence, it has been impractical to obtain accurate thickness estimates for the entire cortex in individual subjects, or group statistics for patient or control populations. Here, we present an automated method for accurately measuring the thickness of the cerebral cortex across the entire brain and for generating cross-subject statistics in a coordinate system based on cortical anatomy. The intersubject standard deviation of the thickness measures is shown to be less than 0.5 mm, implying the ability to detect focal atrophy in small populations or even individual subjects. The reliability and accuracy of this new method are assessed by within-subject test-retest studies, as well as by comparison of cross-subject regional thickness measures with published values.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SoftwareRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2020
                29 December 2020
                : 15
                : 12
                : e0244442
                Affiliations
                [1 ] Simula Research Laboratory, Department of Numerical Analysis and Scientific Computing, Lysaker, Norway
                [2 ] Department of Mathematics, University of Oslo, Oslo, Norway
                University of New South Wales, AUSTRALIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-6872-3710
                Article
                PONE-D-20-26021
                10.1371/journal.pone.0244442
                7771676
                33373419
                54f0c595-07bd-43a8-b26b-f1636aa45311
                © 2020 Daversin-Catty 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
                : 19 August 2020
                : 9 December 2020
                Page count
                Figures: 7, Tables: 1, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100010663, H2020 European Research Council;
                Award ID: 714892
                Award Recipient :
                Funded by: Research Council of Norway
                Award ID: 301013
                Award Recipient :
                CDC and MER are supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement 714892, and by the NOTUR grant NN9316K. KAM is supported by the Research Council of Norway under grant agreement 301013. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Physics
                Classical Mechanics
                Continuum Mechanics
                Fluid Mechanics
                Fluid Dynamics
                Fluid Flow
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Velocity
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Medicine and Health Sciences
                Medical Conditions
                Cardiovascular Diseases
                Coronary Heart Disease
                Medicine and Health Sciences
                Cardiology
                Cardiovascular Medicine
                Cardiovascular Diseases
                Coronary Heart Disease
                Medicine and Health Sciences
                Vascular Medicine
                Coronary Heart Disease
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Cerebrospinal Fluid
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Cerebrospinal Fluid
                Biology and Life Sciences
                Physiology
                Body Fluids
                Cerebrospinal Fluid
                Biology and Life Sciences
                Anatomy
                Nervous System
                Cerebrospinal Fluid
                Medicine and Health Sciences
                Anatomy
                Nervous System
                Cerebrospinal Fluid
                Medicine and Health Sciences
                Cardiology
                Diastole
                Medicine and Health Sciences
                Cardiology
                Systole
                Custom metadata
                All data and source code are available via Zenodo: Daversin-Catty C, Vinje V, Mardal KA, Rognes ME. mechanisms-behind-pvs-flow-v1.0 (source code); 2020. Available from: http://doi.org/10.5281/zenodo.3890133.

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