Ageing is a major risk factor for many neurological pathologies, but its mechanisms remain unclear. Unlike other tissues, the parenchyma of the central nervous system (CNS) lacks lymphatic vasculature and waste products are removed partly through a paravascular route. (Re)discovery and characterization of meningeal lymphatic vessels has prompted an assessment of their role in waste clearance from the CNS. Here we show that meningeal lymphatic vessels drain macromolecules from the CNS (cerebrospinal and interstitial fluids) into the cervical lymph nodes in mice. Impairment of meningeal lymphatic function slows paravascular influx of macromolecules into the brain and efflux of macromolecules from the interstitial fluid, and induces cognitive impairment in mice. Treatment of aged mice with vascular endothelial growth factor C enhances meningeal lymphatic drainage of macromolecules from the cerebrospinal fluid, improving brain perfusion and learning and memory performance. Disruption of meningeal lymphatic vessels in transgenic mouse models of Alzheimer's disease promotes amyloid-β deposition in the meninges, which resembles human meningeal pathology, and aggravates parenchymal amyloid-β accumulation. Meningeal lymphatic dysfunction may be an aggravating factor in Alzheimer's disease pathology and in age-associated cognitive decline. Thus, augmentation of meningeal lymphatic function might be a promising therapeutic target for preventing or delaying age-associated neurological diseases.

SARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.

Glioblastoma (GBM) prognosis remains dismal due in part to the invasiveness of GBM cells. Interstitial fluid flow (IFF) has been shown to increase invasion of glioma cells in vitro through the CXCR4 receptor interacting with autologous, pericellular gradients of CXCL12 (autologous chemotaxis) or through the CD44 receptor interactions with the extracellular matrix (hyaluronan-mediated mechanotransduction). These mechanisms have not been examined together and thus we hypothesized that both mechanisms contribute to invasion in populations of cancer cells. Therefore, we examined IFF-stimulated CXCR4-, CXCL12-, and CD44-dependent invasion in patient-derived glioblastoma stem cells (GSCs). Using our 3D in vitro assay and correlative in vivo studies we demonstrated GSC lines show increased invasion with flow. This flow-stimulated invasion was reduced by blockade of CXCR4, CXCL12, and/or CD44, revealing that GSC invasion may be mediated simultaneously by both mechanisms. Characterization of CXCR4, CXCL12, and CD44 populations in four GSC lines revealed different percentages of protein positive subpopulations for each line. We developed an agent-based model to identify the contributions of each subpopulation to flow-stimulated invasion and validated the model through comparisons with experimental blocking studies. Clinically relevant radiation therapy increased flow-stimulated invasion in one GSC line. Our agent-based model predicted that IFF-stimulated invasion is driven primarily by CXCR4CXCL12 populations, and, indeed our irradiated cells had an increase in this subpopulation. Together, these data indicate that different mechanisms govern the flow response across GSCs, but that within a single patient, there are subpopulations of GSCs that respond to flow via either CD44- or CXCR4-CXCL12 mechanisms.

SARS-CoV2 is a previously uncharacterized coronavirus and causative agent of the COVID-19 pandemic. The host response to SARS-CoV2 has not yet been fully delineated, hampering a precise approach to therapy. To address this, we carried out a comprehensive analysis of gene expression data from the blood, lung, and airway of COVID-19 patients. Our results indicate that COVID-19 pathogenesis is driven by populations of myeloid-lineage cells with highly inflammatory but distinct transcriptional signatures in each compartment. The relative absence of cytotoxic cells in the lung suggests a model in which delayed clearance of the virus may permit exaggerated myeloid cell activation that contributes to disease pathogenesis by the production of inflammatory mediators. The gene expression profiles also identify potential therapeutic targets that could be modified with available drugs. The data suggest that transcriptomic profiling can provide an understanding of the pathogenesis of COVID-19 in individual patients.3 1 Methods Read quality, trimming, mapping and summarizationPublicly available data sets used in this study are listed in Table S1. RNA-seq data were processed using a consistent workflow using FASTQC, Trimmomatic, STAR, Sambamba, and featureCounts. As described below SRA files were downloaded and converted into FASTQ format using SRA toolkit. Read ends and adapters were trimmed with Trimmomatic (v0.38) using a sliding window, ilmnclip, and headcrop filters. Both datasets were head cropped at 6bp and adapters were removed before read alignment.Reads were mapped to the human reference genome hg38 using STAR, and the .sam files were converted to sorted .bam files using Sambamba. Read counts were summarized using the featureCounts function of the Subread package (v1.61.)The RNA-seq tools are all free, open source programs available at the following web addresses SRA toolkit -https

Glioblastoma (GBM), a highly aggressive form of brain tumor, is a disease marked by extensive invasion into the surrounding brain. Interstitial fluid flow (IFF), or the movement of fluid within the spaces between cells, has been linked to increased invasion of GBM cells. Better characterization of IFF could elucidate underlying mechanisms driving this invasion in vivo . Here, we develop a technique to non-invasively measure interstitial flow velocities in the glioma microenvironment of mice using dynamic contrast-enhanced magnetic resonance imaging (MRI), a common clinical technique. Using our in vitro model as a phantom “tumor” system and in silico models of velocity vector fields, we show we can measure average velocities and accurately reconstruct velocity directions. With our combined MR and analysis method, we show that velocity magnitudes are similar across four human GBM cell line xenograft models and the direction of fluid flow is heterogeneous within and around the tumors, and not always in the outward direction. These values were not linked to the tumor size. Finally, we compare our flow velocity magnitudes and the direction of flow to a classical marker of vessel leakage and bulk fluid drainage, Evans blue. With these data, we validate its use as a marker of high and low IFF rates and IFF in the outward direction from the tumor border in implanted glioma models. These methods show, for the first time, the nature of interstitial fluid flow in models of glioma using a technique that is translatable to clinical and preclinical models currently using contrast-enhanced MRI.

The delivery of systemically administered gene therapies to brain tumors is exceptionally difficult because of the blood-brain barrier (BBB) and blood-tumor barrier (BTB). In addition, the adhesive and nanoporous tumor extracellular matrix hinders therapeutic dispersion. We first developed the use of magnetic resonance image (MRI)–guided focused ultrasound (FUS) and microbubbles as a platform approach for transfecting brain tumors by targeting the delivery of systemically administered “brain-penetrating” nanoparticle (BPN) gene vectors across the BTB/BBB. Next, using an MRI-based transport analysis, we determined that after FUS-mediated BTB/BBB opening, mean interstitial flow velocity magnitude doubled, with “per voxel” flow directions changing by an average of ~70° to 80°. Last, we observed that FUS-mediated BTB/BBB opening increased the dispersion of directly injected BPNs through tumor tissue by >100%. We conclude that FUS-mediated BTB/BBB opening yields markedly augmented interstitial tumor flow that, in turn, plays a critical role in enhancing BPN transport through tumor tissue.

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