Objective In the brain, protein waste removal is partly performed by paravascular pathways that facilitate convective exchange of water and soluble contents between cerebrospinal and interstitial fluids. Several lines of evidence suggest that bulk flow drainage via the glymphatic system is driven by cerebrovascular pulsation, and is dependent on astroglial water channels that line paravascular cerebrospinal fluid (CSF) pathways. The Objective of this study was to evaluate whether the efficiency of CSF-ISF exchange and interstitial solute clearance is impaired in the aging brain. Methods CSF-ISF exchange was evaluated by in vivo and ex vivo fluorescence microscopy while interstitial solute clearance was evaluated by radio-tracer clearance assays in young (2–3 month), middle age (10–12 month) and old (18–20 month) wild type mice. The relationship between age-related changes in the expression of the astrocytic water channel aquaporin-4 (AQP4) and changes in glymphatic pathway function were evaluated by immunofluorescence. Results Advancing age was associated with a dramatic decline in the efficiency of exchange between the subarachnoid CSF and the brain parenchyma. Relative to the young, clearance of intraparechamally injected amyloid β was impaired by 40% in the old mice. A 27% reduction in the vessel wall pulsatility of intracortical arterioles and widespread loss of perivascular AQP4 polarization along the penetrating arteries accompanied the decline in CSF-ISF exchange. Interpretation We propose that impaired glymphatic clearance contributes to cognitive decline among the elderly and may represent a novel therapeutic target for the treatment of neurodegenerative diseases associated with accumulation of mis-folded protein aggregates.

Background and Purpose— The management of unruptured brain arteriovenous malformations remains unclear. Using a large cohort to determine risk factors predictive of hemorrhagic presentation of arteriovenous malformations, this study aims to develop a predictive tool that could guide hemorrhage risk stratification. Methods— A database of 789 arteriovenous malformation patients presenting to our institution between 1990 and 2017 was used. A hold-out method of model validation was used, whereby the data was randomly split in half into training and validation data sets. Factors significant at the univariable level in the training data set were used to construct a model based on multivariable logistic regression. Model performance was assessed using receiver operating curves on the training, validation, and complete data sets. The predictors and the complete data set were then used to derive a risk prediction formula and a practical scoring system, where every risk factor was worth 1 point except race, which was worth 2 points (total score varies from 0 to 6). The factors are summarized by R 2 eD arteriovenous malformation (acronym: R 2 eD AVM). Results— In 755 patients with complete data, 272 (36%) presented with hemorrhage. From the training data set, a model was derived containing the following risk factors: nonwhite race (odds ratio [OR]=1.8; P =0.02), small nidus size (OR=1.47; P =0.14), deep location (OR=2.3; P< 0.01), single arterial feeder (OR=2.24; P< 0.01), and exclusive deep venous drainage (OR=2.07; P =0.02). Area under the curve from receiver operating curve analysis was 0.702, 0.698, and 0.685 for the training, validation, and complete data sets, respectively. In the entire study population, the predicted probability of hemorrhagic presentation increased in a stepwise manner from 16% for patients with no risk factors (score of 0) to 78% for patients having all the risk factors (score of 6). Conclusions— The final model derived from this study can be used as a predictive tool that supplements clinical judgment and aids in patient counseling.

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