99 research outputs found
Suppression of charged particle production at large transverse momentum in central Pb-Pb collisions at TeV
Inclusive transverse momentum spectra of primary charged particles in Pb-Pb
collisions at = 2.76 TeV have been measured by the ALICE
Collaboration at the LHC. The data are presented for central and peripheral
collisions, corresponding to 0-5% and 70-80% of the hadronic Pb-Pb cross
section. The measured charged particle spectra in and GeV/ are compared to the expectation in pp collisions at the same
, scaled by the number of underlying nucleon-nucleon
collisions. The comparison is expressed in terms of the nuclear modification
factor . The result indicates only weak medium effects ( 0.7) in peripheral collisions. In central collisions,
reaches a minimum of about 0.14 at -7GeV/ and increases
significantly at larger . The measured suppression of high- particles is stronger than that observed at lower collision energies,
indicating that a very dense medium is formed in central Pb-Pb collisions at
the LHC.Comment: 15 pages, 5 captioned figures, 3 tables, authors from page 10,
published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/98
Two-pion Bose-Einstein correlations in central Pb-Pb collisions at = 2.76 TeV
The first measurement of two-pion Bose-Einstein correlations in central Pb-Pb
collisions at TeV at the Large Hadron Collider is
presented. We observe a growing trend with energy now not only for the
longitudinal and the outward but also for the sideward pion source radius. The
pion homogeneity volume and the decoupling time are significantly larger than
those measured at RHIC.Comment: 17 pages, 5 captioned figures, 1 table, authors from page 12,
published version, figures at
http://aliceinfo.cern.ch/ArtSubmission/node/388
Elliptic flow of charged particles in Pb-Pb collisions at 2.76 TeV
We report the first measurement of charged particle elliptic flow in Pb-Pb
collisions at 2.76 TeV with the ALICE detector at the CERN Large Hadron
Collider. The measurement is performed in the central pseudorapidity region
(||<0.8) and transverse momentum range 0.2< < 5.0 GeV/. The
elliptic flow signal v, measured using the 4-particle correlation method,
averaged over transverse momentum and pseudorapidity is 0.087 0.002
(stat) 0.004 (syst) in the 40-50% centrality class. The differential
elliptic flow v reaches a maximum of 0.2 near = 3
GeV/. Compared to RHIC Au-Au collisions at 200 GeV, the elliptic flow
increases by about 30%. Some hydrodynamic model predictions which include
viscous corrections are in agreement with the observed increase.Comment: 10 pages, 4 captioned figures, published version, figures at
http://aliceinfo.cern.ch/ArtSubmission/node/389
Integration of P2Y receptor-activated signal transduction pathways in G protein-dependent signalling networks
The role of nucleotides in intracellular energy provision and nucleic acid synthesis has been known for a long time. In the past decade, evidence has been presented that, in addition to these functions, nucleotides are also autocrine and paracrine messenger molecules that initiate and regulate a large number of biological processes. The actions of extracellular nucleotides are mediated by ionotropic P2X and metabotropic P2Y receptors, while hydrolysis by ecto-enzymes modulates the initial signal. An increasing number of studies have been performed to obtain information on the signal transduction pathways activated by nucleotide receptors. The development of specific and stable purinergic receptor agonists and antagonists with therapeutical potential largely contributed to the identification of receptors responsible for nucleotide-activated pathways. This article reviews the signal transduction pathways activated by P2Y receptors, the involved second messenger systems, GTPases and protein kinases, as well as recent findings concerning P2Y receptor signalling in C6 glioma cells. Besides vertical signal transduction, lateral cross-talks with pathways activated by other G protein-coupled receptors and growth factor receptors are discussed
From Computer Metaphor to Computational Modeling: The Evolution of Computationalism
In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory to show how modeling has progressed over the years. The methodological assumptions of new modeling work are best understood in the mechanistic framework, which is evidenced by the way in which models are empirically validated. Moreover, the methodological and theoretical progress in computational neuroscience vindicates the new mechanistic approach to explanation, which, at the same time, justifies the best practices of computational modeling. Overall, computational modeling is deservedly successful in cognitive (neuro)science. Its successes are related to deep conceptual connections between cognition and computation. Computationalism is not only here to stay, it becomes stronger every year
Stroke genetics informs drug discovery and risk prediction across ancestries
Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries
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