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Corona virus disease 2019 (COVID‐19) causes symptoms from multiple organs after infection by severe acute respiratory syndrome corona virus 2 (SARS CoV‐2). They range from early, low blood oxygen levels (hypoxemia) without breathlessness (“silent hypoxia”), delirium, rashes, and loss of smell (anosmia), to persisting chest pain, muscle weakness and ‐pain, fatigue, confusion, memory problems and difficulty to concentrate (“brain fog”), mood changes, and unexpected onset of hypertension or diabetes. SARS CoV‐2 affects the microcirculation, causing endothelial cell swelling and damage (endotheliitis), microscopic blood clots (microthrombosis), capillary congestion, and damage to pericytes that are integral to capillary integrity and barrier function, tissue repair (angiogenesis), and scar formation. Similar to other instances of critical illness, COVID‐19 is also associated with elevated cytokine levels in the systemic circulation. This review examines how capillary damage and inflammation may contribute to these acute and persisting COVID‐19 symptoms by interfering with blood and tissue oxygenation and with brain function. Undetectable by current diagnostic methods, capillary flow disturbances limit oxygen diffusion exchange in lungs and tissue and may therefore cause hypoxemia and tissue hypoxia. The review analyzes the combined effects of COVID‐19‐related capillary damage, pre‐existing microvascular changes, and upstream vascular tone on tissue oxygenation in key organs. It identifies a vicious cycle, as infection‐ and hypoxia‐related inflammation cause capillary function to deteriorate, which in turn accelerates hypoxia‐related inflammation and tissue damage. Finally, the review addresses the effects of low oxygen and high cytokine levels in brain tissue on neurotransmitter synthesis and mood. Methods to assess capillary functions in human organs and therapeutic means to protect capillary functions and stimulate capillary bed repair may prove important for the individualized management of COVID‐19 patients and targeted rehabilitation strategies. COVID‐19‐related microvascular damage and inflammation may cause tissue hypoxia via transit‐time effects and disturb neurotransmitter synthesis in the brain. The duration of COVID‐19 symptoms and the long‐term health effects of SARS‐CoV‐2 infection may rely on whether disease‐related capillary damage is reversible.

Characterizing neural tissue microstructure is a critical goal for future neuroimaging. Diffusion MRI (dMRI) provides contrasts that reflect diffusing spins’ interactions with myriad microstructural features of biological systems. However, the specificity of dMRI remains limited due to the ambiguity of its signals vis-à-vis the underlying microstructure. To improve specificity, biophysical models of white matter (WM) typically express dMRI signals according to the Standard Model (SM) and have more recently in gray matter (GM) taken spherical compartments into account (the SANDI model) in attempts to represent cell soma. The validity of the assumptions underlying these models, however, remains largely undetermined, especially in GM. To validate these assumptions experimentally, observing their unique, functional properties, such as the b−1/2 power-law associated with one-dimensional diffusion, has emerged as a fruitful strategy. The absence of this signature in GM, in turn, has been explained by neurite water exchange, non-linear morphology, and/or by obscuring soma signal contributions. Here, we present diffusion simulations in realistic neurons demonstrating that curvature and branching does not destroy the stick power-law behavior in impermeable neurites, but also that their signal is drowned by the soma signal under typical experimental conditions. Nevertheless, by studying the GM dMRI signal's behavior as a function of diffusion weighting as well as time, we identify an attainable experimental regime in which the neurite signal dominates. Furthermore, we find that exchange-driven time dependence produces a signal behavior opposite to that which would be expected from restricted diffusion, thereby providing a functional signature that disambiguates the two effects. We present data from dMRI experiments in ex vivo rat brain at ultrahigh field of 16.4T and observe a time dependence that is consistent with substantial exchange but also with a GM stick power-law. The first finding suggests significant water exchange between neurites and the extracellular space while the second suggests a small sub-population of impermeable neurites. To quantify these observations, we harness the Kärger exchange model and incorporate the corresponding signal time dependence in the SM and SANDI models.

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 (OEFmax) 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 OEFmax 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.

Key Points Peripheral neuropathy is a serious but often neglected complication of diabetes mellitus Schwann cells support the structural and functional integrity of nerves, so their damage as a result of the metabolic consequences of diabetes adversely affects axons High polyol pathway flux, oxidative stress and inflammation are the main pathways activated in Schwann cells during diabetic neuropathy Disruption of Schwann cell metabolism by hyperglycaemia and/or dyslipidaemia results in accumulation of neurotoxic intermediates that confer axonal and vascular vulnerability to injury Microvascular changes within the endoneurium create a hypoxic environment that has the potential to disrupt Schwann cell function, promoting activation of inflammatory cascades that lead to neurodegeneration Research into the mechanisms of diabetic neuropathy have focused on neurons, but evidence is accumulating that Schwann cells have a central role. In this Review, the authors consider how Schwann cell dysfunction and the interactions of these cells with neurons and microvessels contribute to the pathogenesis of neuropathy in diabetes. The prevalence of diabetes worldwide is at pandemic levels, with the number of patients increasing by 5% annually. The most common complication of diabetes is peripheral neuropathy, which has a prevalence as high as 50% and is characterized by damage to neurons, Schwann cells and blood vessels within the nerve. The pathogenic mechanisms of diabetic neuropathy remain poorly understood, impeding the development of targeted therapies to treat nerve degeneration and its most disruptive consequences of sensory loss and neuropathic pain. Involvement of Schwann cells has long been proposed, and new research techniques are beginning to unravel a complex interplay between these cells, axons and microvessels that is compromised during the development of diabetic neuropathy. In this Review, we discuss the evolving concept of Schwannopathy as an integral factor in the pathogenesis of diabetic neuropathy, and how disruption of the interactions between Schwann cells, axons and microvessels contribute to the disease.

We recently extended the classic flow–diffusion equation, which relates blood flow to tissue oxygenation, to take capillary transit time heterogeneity (CTH) into account. Realizing that cerebral oxygen availability depends on both cerebral blood flow (CBF) and capillary flow patterns, we have speculated that CTH may be actively regulated and that changes in the capillary morphology and function, as well as in blood rheology, may be involved in the pathogenesis of conditions such as dementia and ischemia-reperfusion injury. The first extended flow–diffusion equation involved simplifying assumptions which may not hold in tissue. Here, we explicitly incorporate the effects of oxygen metabolism on tissue oxygen tension and extraction efficacy, and assess the extent to which the type of capillary transit time distribution affects the overall effects of CTH on flow–metabolism coupling reported earlier. After incorporating tissue oxygen metabolism, our model predicts changes in oxygen consumption and tissue oxygen tension during functional activation in accordance with literature reports. We find that, for large CTH values, a blood flow increase fails to cause significant improvements in oxygen delivery, and can even decrease it; a condition of malignant CTH. These results are found to be largely insensitive to the choice of the transit time distribution.

Information about tissue on the microscopic and mesoscopic scales can be accessed by modelling diffusion MRI signals, with the aim of extracting microstructure-specific biomarkers. The standard model (SM) of diffusion, currently the most broadly adopted microstructural model, describes diffusion in white matter (WM) tissues by two Gaussian components, one of which has zero radial diffusivity, to represent diffusion in intra- and extra-axonal water, respectively. Here, we reappraise these SM assumptions by collecting comprehensive double diffusion encoded (DDE) MRI data with both linear and planar encodings, which was recently shown to substantially enhance the ability to estimate SM parameters. We find however, that the SM is unable to account for data recorded in fixed rat spinal cord at an ultrahigh field of 16.4 T, suggesting that its underlying assumptions are violated in our experimental data. We offer three model extensions to mitigate this problem: first, we generalize the SM to accommodate finite radii (axons) by releasing the constraint of zero radial diffusivity in the intra-axonal compartment. Second, we include intracompartmental kurtosis to account for non-Gaussian behaviour. Third, we introduce an additional (third) compartment. The ability of these models to account for our experimental data are compared based on parameter feasibility and Bayesian information criterion. Our analysis identifies the three-compartment description as the optimal model. The third compartment exhibits slow diffusion with a minor but non-negligible signal fraction (∼12%). We demonstrate how failure to take the presence of such a compartment into account severely misguides inferences about WM microstructure. Our findings bear significance for microstructural modelling at large and can impact the interpretation of biomarkers extracted from the standard model of diffusion.

The regional availability of oxygen in brain tissue is traditionally inferred from the magnitude of cerebral blood flow (CBF) and the concentration of oxygen in arterial blood. Measurements of CBF are therefore widely used in the localization of neuronal response to stimulation and in the evaluation of patients suspected of acute ischemic stroke or flow-limiting carotid stenosis. It was recently demonstrated that capillary transit time heterogeneity (CTH) limits maximum oxygen extraction fraction (OEFmax) that can be achieved for a given CBF. Here we present a statistical approach for determining CTH, mean transit time (MTT), and CBF using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). Using numerical simulations, we demonstrate that CTH, MTT, and OEFmax can be estimated with low bias and variance across a wide range of microvascular flow patterns, even at modest signal-to-noise ratios. Mean transit time estimated by singular value decomposition (SVD) deconvolution, however, is confounded by CTH. The proposed technique readily identifies malperfused tissue in acute stroke patients and appears to highlight information not detected by the standard SVD technique. We speculate that this technique permits the non-invasive detection of tissue with impaired oxygen delivery in neurologic disorders such as acute ischemic stroke and Alzheimer's disease during routine diagnostic imaging.

BACKGROUND Cerebral amyloid angiopathy (CAA) is a hallmark of Alzheimer's disease (AD), linked to adverse effects of emerging AD treatments. We explored the molecular effects of CAA in mouse brain and evaluated how these could be prevented by two repurposed United States Food and Drug Administration (FDA) approved treatments. METHODS Brain proteomics was performed on the Tg‐SwDI genetic mouse model carrying disease causing mutations and developing AD characteristic cognitive deficits and severe CAA. Cortical and hippocampal tissues from presymptomatic male and female mice were studied. RESULTS We identify a core of dysregulated proteins across studies, including established markers of AD as well as proteins indicative of astrogliosis and negative regulators of synaptic stability and function. Two FDA approved, repurposed carbonic anhydrase inhibitors (CAIs), acetazolamide and methazolamide, were effective in preventing these molecular adaptations. DISCUSSION The two drugs broadly prevent proteome adaptations to the detrimental genotype and retain glutamatergic synapse proteins significantly closer to wild‐type levels. Highlights The brain proteome changes of mice with CAA are mapped. Cortical and hippocampal tissues from presymptomatic male and female mice are studied. Markers of AD, astrogliosis, and synaptic stability are dysregulated. Two CAI are effective in preventing these protein changes.

The locus coeruleus (LC) produces most of the brain’s noradrenaline (NA). Among its many roles, NA is often said to be neuroprotective and important for brain upkeep. For this reason, loss of LC integrity is thought to impact brain volume and microstructure as well as plasticity broadly. LC dysfunction is also a suspected driver in the development of neurodegenerative diseases. Nevertheless, the impact of LC dysfunction on the gross structure and microstructure of normal brains is not well-studied. We employed high-field ex vivo magnetic resonance imaging (MRI) to investigate brain volumetrics and microstructure in control (CON) mice and mice with LC ablation (LCA) at two ages, representing the developing brain and the fully matured brain. These whole-brain methods are known to be capable of detecting subtle morphological changes and brain microstructural remodeling. We found mice behavior consistent with histologically confirmed LC ablation. However, MRI showed no difference between CON and LCA groups with regard to brain size, relative regional volumes, or regional microstructural indices. Our findings suggest that LC-NA is not needed for postnatal brain maturation and growth in mice. Nor is it required for maintenance in the normal adult mouse brain, as no atrophy or microstructural aberration is detected after weeks of LC dysfunction. This adds clarity to the often-encountered notion that LC-NA is important for brain “trophic support” as it shows that such effects are likely most relevant to mechanisms related to brain plasticity and neuroprotection in the (pre)diseased brain.

Muscle tissue utilizes glucose as a fuel during exercise and stores glucose in form of glycogen during rest. The associated glucose transport includes delivery of glucose from blood plasma into the interstitial space and subsequent, GLUT‐4 facilitated diffusion into muscle cells. The extent to which the vascular endothelium acts as a barrier to glucose transport, however, remains debated. While accurate measurements of interstitial glucose concentration (IGC) are key to resolve this debate, these are also challenging as removal of interstitial fluid may perturb glucose transport and therefore bias IGC measurements. We developed a three‐compartment model to infer IGC in skeletal muscle from its local metabolism and blood flow. The model predicts that IGC remains within 5% of that of blood plasma during resting conditions but decreases more as metabolism increases. Next, we determined how microdialysis protocols affect IGC. Our model analysis suggests that microdialysis‐based IGC measurements underestimate true values. Notably, reported increases in muscle capillary permeability surface area product (PS) to glucose under the condition of elevated metabolism may owe in part to such measurements bias. Our study demonstrates that microdialysis may be associated with significant measurement bias in the context of muscle IGC assessment. Reappraising literature data with this bias in mind, we find that muscle capillary endothelium may represent less of a barrier to glucose transport in muscle than previously believed. We discuss the impact of glucose removal on the microdialysis relative recovery and means of correcting microdialysis IGC values. Left panel: We developed a three‐compartment (endothelium, blood plasma, interstitium) model to infer muscle interstitial glucose concentration (IGC) from its local metabolism and blood flow. The diffusion equation is applied in each of the compartments. Right panel: Contrary to most experimental reports, the model predicts that IGC remains within 5% of that of blood plasma during resting conditions (rightmost capillaries in the outcome panel). In parallel, we predict that microdialysis‐related interstitial fluid removal creates a significant glucose concentration gradient around the microdialysis probe (right half of the outcome panel), leading to IGC measurement underestimations.