Glymphatic-assisted perivascular brain delivery of intrathecal small gold nanoparticles

Nanoparticles are ultrafine particulate matter having considerable potential for treatment of central nervous system (CNS) disorders. Despite their tiny size, the blood-brain barrier (BBB) restricts their access to the CNS. Their direct cerebrospinal fluid (CSF) administration bypasses the BBB endothelium, but still fails to give adequate brain uptake. We present a novel approach for efficient CNS delivery of 111In-radiolabelled gold nanoparticles (AuNPs; 10–15 nm) via intra-cisterna magna administration, with tracking by SPECT imaging. To accelerate CSF brain influx, we administered AuNPs intracisternally in conjunction with systemic hypertonic saline, which dramatically increased the parenchymal AuNP uptake, especially in deep brain regions. AuNPs entered the CNS along periarterial spaces as visualized by MRI of gadolinium-labelled AuNPs and were cleared from brain within 24 h and excreted through the kidneys. Thus, the glymphatic-assisted perivascular network augment by systemic hypertonic saline is a pathway for highly efficient brain-wide distribution of small AuNPs.RST/Biomedical Imagin

D-JRA2.3 Smart Grid Simulation Environment

This report summarizes the work conducted within ERIGrid related to an integrated simulation environment for large-scale systems.The main goal of the JRA2 is to develop advanced simulation-based tools and methods to validate Smart Grid scenarios, configurations and applications in con-text of co-simulation. The work done in D-JRA2.1 involved assessment of specialized simulation packages for Smart Grids and to develop tools to couple these simulation packages for co-simulation. New tools and models were also developed as some of the existing tools were not sufficient enough to achieve the appropriate couplings. In D-JRA2.2 co-simulation-based assessment methods were developed to compare the performance between monolithic and co-simulations. In D-JRA2.3 we aim to combine all the work done under WP JRA2 to present an integrated simulation package that can be applied to Large Scale systems. The assessment methods developed in D-JRA2.2 have been tested initially in small systems to measure the performance and identify possible flaws. How-ever, the complexity increases significantly in large scale realistic systems. This report documents the challenges faced when the systems and their models grow larger (i.e., upscaled) and how different large scale specific phenomena and issues were identified. After the identification of the challenges, the assessment methods were modified and packaged into an in-tegrated simulation environment which can be used for scaled out systems. The simulation pack-ages are provided as an addendum along with this report while their details are concisely docu-mented in this report.Intelligent Electrical Power Grid