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We measured the Coulomb dissociation of 16O into 4He and 12C at the R3B setup in a first campaign within FAIR Phase 0 at GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt. The goal was to improve the accuracy of the experimental data for the 12C(α,γ)16O fusion reaction and to reach lower center-ofmass energies than measured so far.
The experiment required beam intensities of 109 16O ions per second at an energy of 500 MeV/nucleon. The rare case of Coulomb breakup into 12C and 4He posed another challenge: The magnetic rigidities of the particles are so close because of the same mass-to-charge-number ratio A/Z = 2 for 16O, 12C and 4He. Hence, radical changes of the R3B setup were necessary. All detectors had slits to allow the passage of the unreacted 16O ions, while 4He and 12C would hit the detectors' active areas depending on the scattering angle and their relative energies. We developed and built detectors based on organic scintillators to track and identify the reaction products with sufficient precision.
NeuLAND (New Large-Area Neutron Detector) is the next-generation neutron detector for the R3B (Reactions with Relativistic Radioactive Beams) experiment at FAIR (Facility for Antiproton and Ion Research). NeuLAND detects neutrons with energies from 100 to 1000 MeV, featuring a high detection efficiency, a high spatial and time resolution, and a large multi-neutron reconstruction efficiency. This is achieved by a highly granular design of organic scintillators: 3000 individual submodules with a size of 5 × 5 × 250 cm3 are arranged in 30 double planes with 100 submodules each, providing an active area of 250 × 250 cm2 and a total depth of 3 m. The spatial resolution due to the granularity together with a time resolution of 150 ps ensures high-resolution capabilities. In conjunction with calorimetric properties, a multi-neutron reconstruction efficiency of 50% to 70% for four-neutron events will be achieved, depending on both the emission scenario and the boundary conditions allowed for the reconstruction method. We present in this paper the final design of the detector as well as results from test measurements and simulations on which this design is based.
Neutron total cross sections are an important source of experimental data in the evaluation of neutron-induced cross sections. The sum of all neutron-induced reaction cross sections can be determined with a precision of a few per cent in a relative measurement. The neutron spectrum of the photoneutron source nELBE extends in the fast region from about 100 keV to 10 MeV and has favourable conditions for transmission measurements due to the low instantaneous flux of neutrons and low gamma-flash background. Several materials of interest (in part included in the CIELO evaluation or on the HPRL of OECD/NEA) have been investigated: 197Au [1, 2], natFe [2], natW [2], 238U, natPt, 4He, natO, natNe, natXe. For gaseous targets high pressure gas cells with flat end-caps have been built that hold up to 200 bar pressure. The experimental setup will be presented including results from several transmission experiments and the data analysis leading to the total cross sections will be discussed.
Background and Aims: The prevalence of hepatitis C virus (HCV) antibodies in Germany has been estimated to be in the range of 0.4–0.63%. Screening for HCV is recommended in patients with elevated ALT levels or significant risk factors for HCV transmission only. However, 15–30% of patients report no risk factors and ALT levels can be normal in up to 20–30% of patients with chronic HCV infection. The aim of this study was to assess the HCV seroprevalence in patients visiting two tertiary care emergency departments in Berlin and Frankfurt, respectively.
Methods: Between May 2008 and March 2010, a total of 28,809 consecutive patients were screened for the presence of anti-HCV antibodies. Anti-HCV positive sera were subsequently tested for HCV-RNA.
Results: The overall HCV seroprevalence was 2.6% (95% CI: 2.4–2.8; 2.4% in Berlin and 3.5% in Frankfurt). HCV-RNA was detectable in 68% of anti-HCV positive cases. Thus, the prevalence of chronic HCV infection in the overall study population was 1.6% (95% CI 1.5–1.8). The most commonly reported risk factor was former/current injection drug use (IDU; 31.2%) and those with IDU as the main risk factor were significantly younger than patients without IDU (p<0.001) and the male-to-female ratio was 72% (121 vs. 46 patients; p<0.001). Finally, 18.8% of contacted HCV-RNA positive patients had not been diagnosed previously.
Conclusions: The HCV seroprevalence was more than four times higher compared to current estimates and almost one fifth of contacted HCV-RNA positive patients had not been diagnosed previously.
As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.