Quantification of apolipoprotein E receptors in human brain-derived cell lines by real-time polymerase chain reaction

Apolipoprotein (apo) E4 is a risk factor for Alzheimer's disease (AD) and other neurodegenerative diseases, compared to wild-type apoE3. The mechanism(s) is unknown. One possibility, demonstrated in peripheral tissue cell lines, is that apoE stimulates nitric oxide synthase (NOS) via a receptor-dependent signalling pathway and that apoE4 generates inappropriate amounts of nitric oxide (NO) compared to apoE3. Prior to biochemical investigations, we have quantified the expression of several candidate receptor genes, including low-density lipoprotein-receptor (LDL-r) family members and scavenger receptor class B, types I and II (SR-BI/II), as well as the three NOS isoenzymes and protein kinase B (Akt), in 38 human cell lines, of which 12 derive from brain. Expression of apoE receptor 2 (apoER2), a known signalling receptor in brain, was readily detected in SH-SY-5Y and CCF-STTG1 cells, common models of neurons and astrocytes, respectively, and was highest in H4 neuroglioma, NT-2 precursor cells and IMR-32 neuroblastoma cells. Transcripts of the other lipoprotein receptors were widely, but variably, distributed across the different cell types. Of particular note was the predominant expression of SR-BII over SR-BI in many of the brain-derived cells. As the C-terminus of SR-BII, like apoER2, contains potential SH3 signalling motifs, we suggest that in brain SR-BII functions as a signal transducer receptor. (c) 2004 Elsevier Inc. All rights reserved

The role of drug transporters in the kidney: lessons from tenofovir

Tenofovir disoproxil fumarate, the prodrug of nucleotide reverse transcriptase inhibitor tenofovir, shows high efficacy and relatively low toxicity in HIV patients. However, long-term kidney toxicity is now acknowledged as a modest but significant risk for tenofovir-containing regimens, and continuous use of tenofovir in HIV therapy is currently under question by practitioners and researchers. Co-morbidities (hepatitis C, diabetes), low body weight, older age, concomitant administration of potentially nephrotoxic drugs, low CD4 count, and duration of therapy are all risk factors associated with tenofovir-associated tubular dysfunction. Tenofovir is predominantly eliminated via the proximal tubules of the kidney, therefore drug transporters expressed in renal proximal tubule cells are believed to influence tenofovir plasma concentration and toxicity in the kidney. We review here the current evidence that the actions, pharmacogenetics, and drug interactions of drug transporters are relevant factors for tenofovir-associated tubular dysfunction. The use of creatinine and novel biomarkers for kidney damage, and the role that drug transporters play in biomarker disposition, are discussed. The lessons learnt from investigating the role of transporters in tenofovir kidney elimination and toxicity can be utilized for future drug development and clinical management programs

Interactions of antiretroviral drugs with the SLC22A1 (OCT1) drug transporter

The SLC22A1 influx transporter is expressed on the basolateral membrane of hepatocytes and is involved in the excretion of numerous cations. Inhibition of SLC22A1 by several antiretrovirals, such as the protease inhibitor darunavir, has not previously been determined. In order to better understand and predict drug-SLC22A1 interactions, a range of antiretrovirals were screened for SLC22A1-associated inhibition and transport. Stable SLC22A1-expressing KCL22 cells were produced previously by nucleofection. Control KCL22 cells were transfected with the empty vector pcDNA3.1. Accumulation of tetraethylammonium (5.5 μM, 30 min) was determined in SLC22A1-expressing and mock-transfected cells with and without 50 μM of SLC22A1 inhibitor prazosin, or 50 μM of each antiretroviral drug. SLC22A1 IC50 values for efavirenz, darunavir, and prazosin were determined. Cellular accumulation of efavirenz and darunavir was also assessed in SLC22A1-expressing KCL22 cells and reversibility of this accumulation was assessed using prazosin. Tetraethylammonium accumulation was higher in SLC22A1-expressing cells compared to mock-transfected cells (10.6 ± 0.8 μM vs. 0.3 ± 0.004 μM, p = 0.009) and was significantly reduced in SLC22A1-expressing cells when co-incubated with all antiretrovirals tested except atazanavir, lamivudine, tenofovir, zidovudine, and raltegravir. Particularly noticeable was the predominance of SLC22A1 inhibitors in the protease inhibitor and non-nucleoside reverse transcriptase inhibitor classes. Absolute SLC22A1 IC50 values for efavirenz, darunavir, and prazosin were 21.8, 46.2, and 2.8 μM, respectively. Efavirenz accumulation was higher in SLC22A1-expressing cells compared to mock-transfected cells (17% higher, p = 0.009) which was reversed using prazosin, whereas no difference was observed for darunavir (p = 0.86). These data inform the mechanistic basis for disposition, drug-drug interactions and pharmacogenetic candidate gene selection for antiretroviral drugs

Matching Temporal Signatures of Solar Features to Their Corresponding Solar-Wind Outflows

The role of small-scale coronal eruptive phenomena in the generation and heating of the solar wind remains an open question. Here, we investigate the role played by coronal jets in forming the solar wind by testing whether temporal variations associated with jetting in EUV intensity can be identified in the outflowing solar-wind plasma. This type of comparison is challenging due to inherent differences between remote-sensing observations of the source and in-situ observations of the outflowing plasma, as well as travel time and evolution of the solar wind throughout the heliosphere. To overcome these, we propose a novel algorithm combining signal filtering, two-step solar-wind ballistic back-mapping, window shifting, and Empirical Mode Decomposition. We first validate the method using synthetic data, before applying it to measurements from the Solar Dynamics Observatory and Wind spacecraft. The algorithm enables the direct comparison of remote-sensing observations of eruptive phenomena in the corona to in-situ measurements of solar-wind parameters, among other potential uses. After application to these datasets, we find several time windows where signatures of dynamics found in the corona are embedded in the solar-wind stream, at a time significantly earlier than expected from simple ballistic back-mapping, with the best-performing in-situ parameter being the solar-wind mass flux

Active Region Modulation of Coronal Hole Solar Wind

Active regions (ARs) are a candidate source of the slow solar wind (SW), the origins of which are a topic of ongoing research. We present a case study that examines the processes by which SW is modulated in the presence of an AR in the vicinity of the SW source. We compare properties of SW associated with a coronal hole (CH)–quiet Sun boundary to SW associated with the same CH but one Carrington rotation later, when this region bordered the newly emerged NOAA AR 12532. Differences found in a range of in situ parameters are compared between these rotations in the context of source region mapping and remote sensing observations. Marked changes exist in the structure and composition of the SW, which we attribute to the influence of the AR on SW production from the CH boundary. These unique observations suggest that the features that emerge in the AR-associated wind are consistent with an increased occurrence of interchange reconnection during SW production, compared with the initial quiet Sun case

Multi-color Molecular Visualization of Signaling Proteins Reveals How C-Terminal Src Kinase Nanoclusters Regulate T Cell Receptor Activation

Elucidating the mechanisms that controlled T cell activation requires visualization of the spatial organization of multiple proteins on the submicron scale. Here, we use stoichiometrically accurate, multiplexed, singlemolecule super-resolution microscopy (DNA-PAINT) to image the nanoscale spatial architecture of the primary inhibitor of the T cell signaling pathway, Csk, and two binding partners implicated in its membrane association, PAG and TRAF3. Combined with a newly developed co-clustering analysis framework, we find that Csk forms nanoscale clusters proximal to the plasma membrane that are lost post-stimulation and are re-recruited at later time points. Unexpectedly, these clusters do not co-localize with PAG at the membrane but instead provide a ready pool of monomers to downregulate signaling. By generating CRISPR-Cas9 knockout T cells, our data also identify that a major risk factor for autoimmune diseases, the protein tyrosine phosphatase non-receptor type 22 (PTPN22) locus, is essential for Csk nanocluster re-recruitment and for maintenance of the synaptic PAG population

Using Social Media to Promote STEM Education: Matching College Students with Role Models

STEM (Science, Technology, Engineering, and Mathematics) fields have become increasingly central to U.S. economic competitiveness and growth. The shortage in the STEM workforce has brought promoting STEM education upfront. The rapid growth of social media usage provides a unique opportunity to predict users' real-life identities and interests from online texts and photos. In this paper, we propose an innovative approach by leveraging social media to promote STEM education: matching Twitter college student users with diverse LinkedIn STEM professionals using a ranking algorithm based on the similarities of their demographics and interests. We share the belief that increasing STEM presence in the form of introducing career role models who share similar interests and demographics will inspire students to develop interests in STEM related fields and emulate their models. Our evaluation on 2,000 real college students demonstrated the accuracy of our ranking algorithm. We also design a novel implementation that recommends matched role models to the students.Comment: 16 pages, 8 figures, accepted by ECML/PKDD 2016, Industrial Trac