‘We achieve the impossible’: discourses of freedom and escape at music festivals and free parties

In this article, we explore the notion of freedom as a form of governance within contemporary consumer culture in a sphere where ‘freedom’ appears as a key component: outdoor music-based leisure events, notably music festivals and free parties. ‘Freedom’ is commodified as central to the marketing of many music festivals, which now form a highly commercialised sector of the UK leisure industry, subject to various regulatory restrictions. Free parties, in contrast, are unlicensed, mostly illegal and far less commercialised leisure spaces. We present data from two related studies to investigate how participants at three major British outdoor music festivals and a small rural free party scene draw on discourses of freedom, escape and regulation. We argue that major music festivals operate as temporary bounded spheres of ‘licensed transgression’, in which an apparent lack of regulation operates as a form of governance. In contrast, free parties appear to ‘achieve the impossible’ by creating alternative (and illegal) spaces in which both freedom and regulation are constituted in different ways compared to music festival settings

Differential effects of apolipoprotein E isoforms on phosphorylation at specific sites on tau by glycogen synthase kinase-3β identified by nano-electrospray mass spectrometry

AbstractPreviously published data have shown an allele-specific variation in the in vitro binding of apolipoprotein E (apoE) to tau, which prompted the hypothesis that apoE binding may protect tau from phosphorylation, apoE3 being more efficient than apoE4. We have, therefore, investigated the effects of apoE on tau phosphorylation in vitro by the proline-directed kinase, glycogen synthase kinase (GSK)-3β. The phosphopeptide maps of tau alone, of tau with apoE3 and of tau with apoE4 were very similar. When apoE2 was present a further four spots were evident. Additionally, of the 15 peptides phosphorylated in the presence or absence of apoE, subtle differences, some isoform-specific, in the relative amounts of phosphorylation were observed

Rapid tyrosine phosphorylation of neuronal proteins including tau and focal adhesion kinase in response to amyloid-beta peptide exposure: Involvement of src family protein kinases

The increased production of amyloid beta -peptide (A beta) in Alzheimer's disease is acknowledged to be a key pathogenic event. In this study, we examined the response of primary human and rat brain cortical cultures to A beta administration and found a marked increase in the tyrosine phosphorylation content of numerous neuronal proteins, including tau and putative microtubule-associated protein 2c (MAP2c). We also found that paired helical filaments of aggregated and hyperphosphorylated tau are tyrosine phosphorylated, indicating that changes in the phosphotyrosine content of cytoplasmic proteins in response to A beta are potentially an important process. Increased tyrosine phosphorylation of cytoskeletal and other neuronal proteins was specific to fibrillar A beta (25-35) and A beta (1-42). The tyrosine phosphorylation was blocked by addition of the Src family tyrosine kinase inhibitor 4-amino-5-( 4-chlorophenyl)- 7(t-butyl) pyrazol(3,4-D) pyramide (PP2) and the phosphatidylinositol 3-kinase inhibitor LY 294002. Tyrosine phosphorylation of tau and MAP2c was concomitant with an increase in the tyrosine phosphorylation and subsequent putative activation of the non-receptor kinase, focal adhesion kinase (FAK). Immunoprecipitation of Fyn, a member of the Src family, from A beta (25-35)-treated neurons showed an increased association of Fyn with FAK. A beta treatment of cells also stimulated the sustained activation of extracellular regulated kinase-2, which was blocked by addition of PP2 and LY 294002, suggesting that FAK/Fyn/PI3-kinase association is upstream of mitogen-activated protein (MAP) kinase signaling in A beta -treated neurons. This cascade of signaling events contains the earliest biochemical changes in neurons to be described in response to A beta exposure and may be critical for subsequent neurodegenerative changes

Plasma lipid profiles change with increasing numbers of mild traumatic brain injuries in rats

Mild traumatic brain injury (mTBI) causes structural, cellular and biochemical alterations which are difficult to detect in the brain and may persist chronically following single or repeated injury. Lipids are abundant in the brain and readily cross the blood-brain barrier, suggesting that lipidomic analysis of blood samples may provide valuable insight into the neuropathological state. This study used liquid chromatography-mass spectrometry (LC-MS) to examine plasma lipid concentrations at 11 days following sham (no injury), one (1×) or two (2×) mTBI in rats. Eighteen lipid species were identified that distinguished between sham, 1× and 2× mTBI. Three distinct patterns were found: (1) lipids that were altered significantly in concentration after either 1× or 2× F mTBI: cholesterol ester CE (14:0) (increased), phosphoserine PS (14:0/18:2) and hexosylceramide HCER (d18:0/26:0) (decreased), phosphoinositol PI(16:0/18:2) (increased with 1×, decreased with 2× mTBI); (2) lipids that were altered in response to 1× mTBI only: free fatty acid FFA (18:3 and 20:3) (increased); (3) lipids that were altered in response to 2× mTBI only: HCER (22:0), phosphoethanolamine PE (P-18:1/20:4 and P-18:0/20:1) (increased), lysophosphatidylethanolamine LPE (20:1), phosphocholine PC (20:0/22:4), PI (18:1/18:2 and 20:0/18:2) (decreased). These findings suggest that increasing numbers of mTBI induce a range of changes dependent upon the lipid species, which likely reflect a balance of damage and reparative responses

THE ELEVENTH AND TWELFTH DATA RELEASES OF THE SLOAN DIGITAL SKY SURVEY: FINAL DATA FROM SDSS-III

Citation: Alam, S., Albareti, F. D., Prieto, C. A., Anders, F., Anderson, S. F., Anderton, T., . . . Zhu, G. T. (2015). THE ELEVENTH AND TWELFTH DATA RELEASES OF THE SLOAN DIGITAL SKY SURVEY: FINAL DATA FROM SDSS-III. Astrophysical Journal Supplement Series, 219(1), 27. doi:10.1088/0067-0049/219/1/12The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg(2) of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg(2) of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg(2); 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra.Additional Authors: Berlind, A. A.;Beutler, F.;Bhardwaj, V.;Bird, J. C.;Bizyaev, D.;Blake, C. H.;Blanton, M. R.;Blomqvist, M.;Bochanski, J. J.;Bolton, A. S.;Bovy, J.;Bradley, A. S.;Brandt, W. N.;Brauer, D. E.;Brinkmann, J.;Brown, P. J.;Brownstein, J. R.;Burden, A.;Burtin, E.;Busca, N. G.;Cai, Z.;Capozzi, D.;Rosell, A. C.;Carr, M. A.;Carrera, R.;Chambers, K. C.;Chaplin, W. J.;Chen, Y. C.;Chiappini, C.;Chojnowski, S. D.;Chuang, C. H.;Clerc, N.;Comparat, J.;Covey, K.;Croft, R. A. C.;Cuesta, A. J.;Cunha, K.;da Costa, L. N.;Da Rio, N.;Davenport, J. R. A.;Dawson, K. S.;De Lee, N.;Delubac, T.;Deshpande, R.;Dhital, S.;Dutra-Ferreira, L.;Dwelly, T.;Ealet, A.;Ebelke, G. L.;Edmondson, E. M.;Eisenstein, D. J.;Ellsworth, T.;Elsworth, Y.;Epstein, C. R.;Eracleous, M.;Escoffier, S.;Esposito, M.;Evans, M. L.;Fan, X. H.;Fernandez-Alvar, E.;Feuillet, D.;Ak, N. F.;Finley, H.;Finoguenov, A.;Flaherty, K.;Fleming, S. W.;Font-Ribera, A.;Foster, J.;Frinchaboy, P. M.;Galbraith-Frew, J. G.;Garcia, R. A.;Garcia-Hernandez, D. A.;Perez, A. E. G.;Gaulme, P.;Ge, J.;Genova-Santos, R.;Georgakakis, A.;Ghezzi, L.;Gillespie, B. A.;Girardi, L.;Goddard, D.;Gontcho, S. G. A.;Hernandez, J. I. G.;Grebel, E. K.;Green, P. J.;Grieb, J. N.;Grieves, N.;Gunn, J. E.;Guo, H.;Harding, P.;Hasselquist, S.;Hawley, S. L.;Hayden, M.;Hearty, F. R.;Hekker, S.;Ho, S.;Hogg, D. W.;Holley-Bockelmann, K.;Holtzman, J. A.;Honscheid, K.;Huber, D.;Huehnerhoff, J.;Ivans, II;Jiang, L. H.;Johnson, J. A.;Kinemuchi, K.;Kirkby, D.;Kitaura, F.;Klaene, M. A.;Knapp, G. R.;Kneib, J. P.;Koenig, X. P.;Lam, C. R.;Lan, T. W.;Lang, D. T.;Laurent, P.;Le Goff, J. M.;Leauthaud, A.;Lee, K. G.;Lee, Y. S.;Licquia, T. C.;Liu, J.;Long, D. C.;Lopez-Corredoira, M.;Lorenzo-Oliveira, D.;Lucatello, S.;Lundgren, B.;Lupton, R. H.;Mack, C. E.;Mahadevan, S.;Maia, M. A. G.;Majewski, S. R.;Malanushenko, E.;Malanushenko, V.;Manchado, A.;Manera, M.;Mao, Q. Q.;Maraston, C.;Marchwinski, R. C.;Margala, D.;Martell, S. L.;Martig, M.;Masters, K. L.;Mathur, S.;McBride, C. K.;McGehee, P. M.;McGreer, I. D.;McMahon, R. G.;Menard, B.;Menzel, M. L.;Merloni, A.;Meszaros, S.;Miller, A. A.;Miralda-Escude, J.;Miyatake, H.;Montero-Dorta, A. D.;More, S.;Morganson, E.;Morice-Atkinson, X.;Morrison, H. L.;Mosser, B.;Muna, D.;Myers, A. D.;Nandra, K.;Newman, J. A.;Neyrinck, M.;Nguyen, D. C.;Nichol, R. C.;Nidever, D. L.;Noterdaeme, P.;Nuza, S. E.;O'Connell, J. E.;O'Connell, R. W.;O'Connell, R.;Ogando, R. L. C.;Olmstead, M. D.;Oravetz, A. E.;Oravetz, D. J.;Osumi, K.;Owen, R.;Padgett, D. L.;Padmanabhan, N.;Paegert, M.;Palanque-Delabrouille, N.;Pan, K. K.;Parejko, J. K.;Paris, I.;Park, C.;Pattarakijwanich, P.;Pellejero-Ibanez, M.;Pepper, J.;Percival, W. J.;Perez-Fournon, I.;Perez-Rafols, I.;Petitjean, P.;Pieri, M. M.;Pinsonneault, M. H.;de Mello, G. F. P.;Prada, F.;Prakash, A.;Price-Whelan, A. M.;Protopapas, P.;Raddick, M. J.;Rahman, M.;Reid, B. A.;Rich, J.;Rix, H. W.;Robin, A. C.;Rockosi, C. M.;Rodrigues, T. S.;Rodriguez-Torres, S.;Roe, N. A.;Ross, A. J.;Ross, N. P.;Rossi, G.;Ruan, J. J.;Rubino-Martin, J. A.;Rykoff, E. S.;Salazar-Albornoz, S.;Salvato, M.;Samushia, L.;Sanchez, A. G.;Santiago, B.;Sayres, C.;Schiavon, R. P.;Schlegel, D. J.;Schmidt, S. J.;Schneider, D. P.;Schultheis, M.;Schwope, A. D.;Scoccola, C. G.;Scott, C.;Sellgren, K.;Seo, H. J.;Serenelli, A.;Shane, N.;Shen, Y.;Shetrone, M.;Shu, Y. P.;Aguirre, V. S.;Sivarani, T.;Skrutskie, M. F.;Slosar, A.;Smith, V. V.;Sobreira, F.;Souto, D.;Stassun, K. G.;Steinmetz, M.;Stello, D.;Strauss, M. A.;Streblyanska, A.;Suzuki, N.;Swanson, M. E. C.;Tan, J. C.;Tayar, J.;Terrien, R. C.;Thakar, A. R.;Thomas, D.;Thomas, N.;Thompson, B. A.;Tinker, J. L.;Tojeiro, R.;Troup, N. W.;Vargas-Magana, M.;Vazquez, J. A.;Verde, L.;Viel, M.;Vogt, N. P.;Wake, D. A.;Wang, J.;Weaver, B. A.;Weinberg, D. H.;Weiner, B. J.;White, M.;Wilson, J. C.;Wisniewski, J. P.;Wood-Vasey, W. M.;Yeche, C.;York, D. G.;Zakamska, N. L.;Zamora, O.;Zasowski, G.;Zehavi, I.;Zhao, G. B.;Zheng, Z.;Zhou, X.;Zhou, Z. M.;Zou, H.;Zhu, G. T

Tyrosine Phosphorylation of Tau by the Src Family Kinases Lck and Fyn

<p>Abstract</p> <p>Background</p> <p>Tau protein is the principal component of the neurofibrillary tangles found in Alzheimer's disease, where it is hyperphosphorylated on serine and threonine residues, and recently phosphotyrosine has been demonstrated. The Src-family kinase Fyn has been linked circumstantially to the pathology of Alzheimer's disease, and shown to phosphorylate Tyr18. Recently another Src-family kinase, Lck, has been identified as a genetic risk factor for this disease.</p> <p>Results</p> <p>In this study we show that Lck is a tau kinase. <it>In vitro</it>, comparison of Lck and Fyn showed that while both kinases phosphorylated Tyr18 preferentially, Lck phosphorylated other tyrosines somewhat better than Fyn. In co-transfected COS-7 cells, mutating any one of the five tyrosines in tau to phenylalanine reduced the apparent level of tau tyrosine phosphorylation to 25-40% of that given by wild-type tau. Consistent with this, tau mutants with only one remaining tyrosine gave poor phosphorylation; however, Tyr18 was phosphorylated better than the others.</p> <p>Conclusions</p> <p>Fyn and Lck have subtle differences in their properties as tau kinases, and the phosphorylation of tau is one mechanism by which the genetic risk associated with Lck might be expressed pathogenically.</p

Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach

[EN] In this article, a numerical methodology for assessing combustion noise in compression ignition engines is described with the specific purpose of analysing the unsteady pressure field inside the combustion chamber. The numerical results show consistent agreement with experimental measurements in both the time and frequency domains. Nonetheless, an exhaustive analysis of the calculation convergence is needed to guarantee an independent solution. These results contribute to the understanding of in-cylinder unsteady processes, especially of those related to combustion chamber resonances, and their effects on the radiated noise levels. The method was applied to different combustion system configurations by modifying the spray angle of the injector, evidencing that controlling the ignition location through this design parameter, it is possible to decrease the combustion noise by minimizing the resonance contribution. Important efficiency losses were, however, observed due to the injector/bowl matching worsening which compromises the performance and emissions levels.The authors want to express their gratitude to CONVERGENT SCIENCE Inc. and Convergent Science GmbH for their kind support for performing the CFD calculations using CONVERGE software.Torregrosa, AJ.; Broatch, A.; Margot, X.; Gómez-Soriano, J. (2018). Understanding the unsteady pressure field inside combustion chambers of compression-ignited engines using a computational fluid dynamics approach. International Journal of Engine Research. 1-13. https://doi.org/10.1177/1468087418803030S113Benajes, J., Novella, R., De Lima, D., & Tribotté, P. (2014). Analysis of combustion concepts in a newly designed two-stroke high-speed direct injection compression ignition engine. International Journal of Engine Research, 16(1), 52-67. doi:10.1177/1468087414562867Costa, M., Bianchi, G. M., Forte, C., & Cazzoli, G. (2014). A Numerical Methodology for the Multi-objective Optimization of the DI Diesel Engine Combustion. Energy Procedia, 45, 711-720. doi:10.1016/j.egypro.2014.01.076Navid, A., Khalilarya, S., & Taghavifar, H. (2016). Comparing multi-objective non-evolutionary NLPQL and evolutionary genetic algorithm optimization of a DI diesel engine: DoE estimation and creating surrogate model. Energy Conversion and Management, 126, 385-399. doi:10.1016/j.enconman.2016.08.014Benajes, J., García, A., Pastor, J. M., & Monsalve-Serrano, J. (2016). Effects of piston bowl geometry on Reactivity Controlled Compression Ignition heat transfer and combustion losses at different engine loads. Energy, 98, 64-77. doi:10.1016/j.energy.2016.01.014Masterton, B., Heffner, H., & Ravizza, R. (1969). The Evolution of Human Hearing. The Journal of the Acoustical Society of America, 45(4), 966-985. doi:10.1121/1.1911574Strahle, W. C. (1978). Combustion noise. 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Combustion chamber resonances in direct injection automotive diesel engines: A numerical approach. International Journal of Engine Research, 5(1), 83-91. doi:10.1243/146808704772914264Broatch, A., Margot, X., Gil, A., & Christian Donayre, (José). (2007). Computational study of the sensitivity to ignition characteristics of the resonance in DI diesel engine combustion chambers. Engineering Computations, 24(1), 77-96. doi:10.1108/02644400710718583Eriksson, L. J. (1980). Higher order mode effects in circular ducts and expansion chambers. The Journal of the Acoustical Society of America, 68(2), 545-550. doi:10.1121/1.384768Broatch, A., Margot, X., Novella, R., & Gomez-Soriano, J. (2017). Impact of the injector design on the combustion noise of gasoline partially premixed combustion in a 2-stroke engine. Applied Thermal Engineering, 119, 530-540. doi:10.1016/j.applthermaleng.2017.03.081Tutak, W., & Jamrozik, A. (2016). 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Assessment of combustion noise in a premixed swirled combustor via Large-Eddy Simulation. Computers & Fluids, 78, 1-9. doi:10.1016/j.compfluid.2010.09.034Jamrozik, A., Tutak, W., Kociszewski, A., & Sosnowski, M. (2013). Numerical simulation of two-stage combustion in SI engine with prechamber. Applied Mathematical Modelling, 37(5), 2961-2982. doi:10.1016/j.apm.2012.07.040Qin, W., Xie, M., Jia, M., Wang, T., & Liu, D. (2014). Large eddy simulation of in-cylinder turbulent flows in a DISI gasoline engine. Applied Mathematical Modelling, 38(24), 5967-5985. doi:10.1016/j.apm.2014.05.004Broatch, A., Margot, X., Novella, R., & Gomez-Soriano, J. (2016). Combustion noise analysis of partially premixed combustion concept using gasoline fuel in a 2-stroke engine. Energy, 107, 612-624. doi:10.1016/j.energy.2016.04.045Torregrosa, A. J., Broatch, A., Martín, J., & Monelletta, L. (2007). 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Assessment of flamelet versus multi-zone combustion modeling approaches for stratified-charge compression ignition engines. International Journal of Engine Research, 17(3), 280-290. doi:10.1177/1468087415571006Torregrosa, A. J., Broatch, A., Gil, A., & Gomez-Soriano, J. (2018). Numerical approach for assessing combustion noise in compression-ignited Diesel engines. Applied Acoustics, 135, 91-100. doi:10.1016/j.apacoust.2018.02.006Torregrosa, A., Olmeda, P., Degraeuwe, B., & Reyes, M. (2006). A concise wall temperature model for DI Diesel engines. Applied Thermal Engineering, 26(11-12), 1320-1327. doi:10.1016/j.applthermaleng.2005.10.021Broatch, A., Javier Lopez, J., García-Tíscar, J., & Gomez-Soriano, J. (2018). Experimental Analysis of Cyclical Dispersion in Compression-Ignited Versus Spark-Ignited Engines and Its Significance for Combustion Noise Numerical Modeling. Journal of Engineering for Gas Turbines and Power, 140(10). doi:10.1115/1.4040287Molina, S., García, A., Pastor, J. 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Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

Modulation of enhancer looping and differential gene targeting by Epstein-Barr virus transcription factors directs cellular reprogramming

Epstein-Barr virus (EBV) epigenetically reprogrammes B-lymphocytes to drive immortalization and facilitate viral persistence. Host-cell transcription is perturbed principally through the actions of EBV EBNA 2, 3A, 3B and 3C, with cellular genes deregulated by specific combinations of these EBNAs through unknown mechanisms. Comparing human genome binding by these viral transcription factors, we discovered that 25% of binding sites were shared by EBNA 2 and the EBNA 3s and were located predominantly in enhancers. Moreover, 80% of potential EBNA 3A, 3B or 3C target genes were also targeted by EBNA 2, implicating extensive interplay between EBNA 2 and 3 proteins in cellular reprogramming. Investigating shared enhancer sites neighbouring two new targets (WEE1 and CTBP2) we discovered that EBNA 3 proteins repress transcription by modulating enhancer-promoter loop formation to establish repressive chromatin hubs or prevent assembly of active hubs. Re-ChIP analysis revealed that EBNA 2 and 3 proteins do not bind simultaneously at shared sites but compete for binding thereby modulating enhancer-promoter interactions. At an EBNA 3-only intergenic enhancer site between ADAM28 and ADAMDEC1 EBNA 3C was also able to independently direct epigenetic repression of both genes through enhancer-promoter looping. Significantly, studying shared or unique EBNA 3 binding sites at WEE1, CTBP2, ITGAL (LFA-1 alpha chain), BCL2L11 (Bim) and the ADAMs, we also discovered that different sets of EBNA 3 proteins bind regulatory elements in a gene and cell-type specific manner. Binding profiles correlated with the effects of individual EBNA 3 proteins on the expression of these genes, providing a molecular basis for the targeting of different sets of cellular genes by the EBNA 3s. Our results therefore highlight the influence of the genomic and cellular context in determining the specificity of gene deregulation by EBV and provide a paradigm for host-cell reprogramming through modulation of enhancer-promoter interactions by viral transcription factors

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr