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Warshanna, A.

Publications and source records attributed to Warshanna, A..

2 recordsLinked to original sources

Drug Metabolism and Transport Capacity of Endothelial Cells, Pericytes, and Astrocytes: Implications for CNS Drug Disposition

Therapeutically targeting the brain requires interactions with endothelial cells, pericytes, and astrocytes at the blood brain barrier (BBB). We evaluated regional and cell-type specific drug metabolism and transport mechanisms using rhesus macaques and in vitro treatment of primary human cells. Here, we report heterogenous distribution of representative drugs, tenofovir (TFV), emtricitabine (FTC), and their active metabolites, which cerebrospinal fluid measures could not reflect. We found that all BBB cell types possessed functional drug metabolizing enzymes and transporters that promoted TFV and FTC uptake and pharmacologic activation. Pericytes and astrocytes emerged as pharmacologically dynamic cells that rivaled hepatocytes and were uniquely susceptible to modulation by disease and treatment. Together, our findings demonstrate the importance of considering the BBB as a unique pharmacologic entity, rather than viewing it as an extension of the liver, as each cell type possesses distinct drug metabolism and transport capacities that contribute to differential brain drug disposition.

pharmacology and toxicology↗

SCP Viz - A universal graphical user interface for single protein analysis in single cell proteomics datasets

Single cell proteomics (SCP) requires the analysis of dozens to thousands of single human cells to draw biological conclusions. However, assessing of the abundance of single proteins in output data presents a considerable challenge, and no simple universal solutions currently exist. To address this, we developed SCP Viz, a statistical package with a graphical user interface that can handle small and large scale SCP output from any instrument or data processing software. In this software, the abundance of individual proteins can be plotted in a variety of ways, using either unadjusted or normalized outputs. These outputs can also be transformed or imputed within the software. SCP Viz offers a variety of plotting options which can help identify significantly altered proteins between groups, both before and after quantitative transformations. Upon the discovery of subpopulations of single cells, users can easily regroup the cells of interest using straightforward text-based filters. When used in this way, SCP Viz allows users to visualize proteomic heterogeneity at the level of individual proteins, cells, or identified subcellular populations. SCP Viz is compatible with output files from MaxQuant, FragPipe, SpectroNaut, and Proteome Discoverer, and should work equally well with other formats. SCP Viz is publicly available at https://github.com/orsburn/SCPViz. For demonstrations, users can download our test data from GitHub and use an online version that accepts user input for analysis at https://orsburnlab.shinyapps.io/SCPViz/. Abstract graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=167 SRC="FIGDIR/small/555397v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1c9d1d5org.highwire.dtl.DTLVardef@eefcfeorg.highwire.dtl.DTLVardef@23c098org.highwire.dtl.DTLVardef@1394161_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗