91 research outputs found

    Performance of the CMS Cathode Strip Chambers with Cosmic Rays

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    The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

    Regulator of G-Protein Signaling 14 (RGS14) Is a Selective H-Ras Effector

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    Background: Regulator of G-protein signaling (RGS) proteins have been well-described as accelerators of Ga-mediated GTP hydrolysis (‘‘GTPase-accelerating proteins’’ or GAPs). However, RGS proteins with complex domain architectures are now known to regulate much more than Ga GTPase activity. RGS14 contains tandem Ras-binding domains that have been reported to bind to Rap- but not Ras GTPases in vitro, leading to the suggestion that RGS14 is a Rap-specific effector. However, more recent data from mammals and Drosophila imply that, in vivo, RGS14 may instead be an effector of Ras.Methodology/Principal Findings: Full-length and truncated forms of purified RGS14 protein were found to bind indiscriminately in vitro to both Rap- and Ras-family GTPases, consistent with prior literature reports. In stark contrast, however, we found that in a cellular context RGS14 selectively binds to activated H-Ras and not to Rap isoforms. Co- transfection / co-immunoprecipitation experiments demonstrated the ability of full-length RGS14 to assemble a multiprotein complex with components of the ERK MAPK pathway in a manner dependent on activated H-Ras. Small interfering RNA-mediated knockdown of RGS14 inhibited both nerve growth factor- and basic fibrobast growth factor- mediated neuronal differentiation of PC12 cells, a process which is known to be dependent on Ras-ERK signaling.Conclusions/Significance: In cells, RGS14 facilitates the formation of a selective Ras?GTP-Raf-MEK-ERK multiprotein complex to promote sustained ERK activation and regulate H-Ras-dependent neuritogenesis. This cellular function for RGS14 is similar but distinct from that recently described for its closely-related paralogue, RGS12, which shares the tandem Ras- binding domain architecture with RGS14

    Optical coherence tomography—current technology and applications in clinical and biomedical research

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    KrĂźppel-like factor 6 is a transcriptional activator of autophagy in acute liver injury

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    Kruppel-like factor 6 (KLF6) is a transcription factor and tumor suppressor. We previously identified KLF6 as mediator of hepatocyte glucose and lipid homeostasis. The loss or reduction of KLF6 is linked to the progression of hepatocellular carcinoma, but its contribution to liver regeneration and repair in acute liver injury are lacking so far. Here we explore the role of KLF6 in acute liver injury models in mice, and in patients with acute liver failure (ALF). KLF6 was induced in hepatocytes in ALF, and in both acetaminophen (APAP)- and carbon tetrachloride (CCl4)- treated mice. In mice with hepatocytespecific Klf6 knockout (DeltaKlf6), cell proliferation following partial hepatectomy (PHx) was increased compared to controls. Interestingly, key autophagic markers and mediators LC3-II, Atg7 and Beclin1 were reduced in DeltaKlf6 mice livers. Using luciferase assay and ChIP, KLF6 was established as a direct transcriptional activator of ATG7 and BECLIN1, but was dependent on the presence of p53. Here we show, that KLF6 expression is induced in ALF and in the regenerating liver, where it activates autophagy by transcriptional induction of ATG7 and BECLIN1 in a p53-dependent manner. These findings couple the activity of an important growth inhibitor in liver to the induction of autophagy in hepatocytes

    CMS Data Processing Workflows during an Extended Cosmic Ray Run

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    Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

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    Transverse-momentum and pseudorapidity distributions of charged hadrons in pp collisions at √s=7 TeV

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    This is the pre-print version of the Published Article which can be accessed from the link below.Charged-hadron transverse-momentum and pseudorapidity distributions in proton-proton collisions at √s=7  TeV are measured with the inner tracking system of the CMS detector at the LHC. The charged-hadron yield is obtained by counting the number of reconstructed hits, hit pairs, and fully reconstructed charged-particle tracks. The combination of the three methods gives a charged-particle multiplicity per unit of pseudorapidity dNch/dη||η|<0.5=5.78±0.01(stat)±0.23(syst) for non-single-diffractive events, higher than predicted by commonly used models. The relative increase in charged-particle multiplicity from √s=0.9 to 7 TeV is [66.1±1.0(stat)±4.2(syst)]%. The mean transverse momentum is measured to be 0.545±0.005(stat)±0.015(syst)  GeV/c. The results are compared with similar measurements at lower energies

    Commissioning of the CMS high-level trigger with cosmic rays

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    This is the Pre-print version of the Article. The official published version of the paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

    Precise mapping of the magnetic field in the CMS barrel yoke using cosmic rays

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    This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPThe CMS detector is designed around a large 4 T superconducting solenoid, enclosed in a 12 000-tonne steel return yoke. A detailed map of the magnetic field is required for the accurate simulation and reconstruction of physics events in the CMS detector, not only in the inner tracking region inside the solenoid but also in the large and complex structure of the steel yoke, which is instrumented with muon chambers. Using a large sample of cosmic muon events collected by CMS in 2008, the field in the steel of the barrel yoke has been determined with a precision of 3 to 8% depending on the location.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)
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