GEM-TPC pre-design technical report

This document contains the pre-design of the beam diagnostics components Tracking Detectors for the Super-FRS. A GEM-TPC detector has been suggested as suitable tracking detector for the ion/fragment beams produced at the in-flight separator Super-FRS under construction at the FAIR facility. The detector concept combines two widely used approaches in gas filled detectors, the Time Projection Chamber (TPC) and the Gas Electron Multiplication (GEM). Three detector generations (prototypes) have been tested in 2011, 2012 and 2014 with relativistic ion beams at GSI. Due to the high-resolution achromatic mode of the Super-FRS, highly homogeneous transmission tracking detectors are crucial to tag the momentum of the ion/fragment beam. They must be able to provide precise information on the (horizontal and vertical) deviation from nominal beam optics, while operated with slow-extracted beam on event-by event basis, in order to provide unambiguous identification of the fragments. The main requirements are a maximum active area horizontally and vertically of (380x80) mm2, a position resolution of < 1 mm, a maximum rate capability of 1 MHz, a dynamic range of about 600 fC. About 32 tracking detectors operating in vacuum are needed along the Super-FRS beam line

Beyond the Neutron Drip-Line: Superheavy Oxygen Isotopes

The neutron-unbound ground states of 25 O and 26 O have been investigated using the LAND-R3B setup at GSI in Darmstadt (Germany)

Impact of Gut Microbiota and Diet on the Development of Atherosclerosis in <i>Apoe^-/-</i> Mice

Objective— To investigate the effect of gut microbiota and diet on atherogenesis. Approach and Results— Here, we investigated the interaction between the gut microbiota and diet on atherosclerosis by feeding germ-free or conventionally raised Apoe −/− mice chow or Western diet alone or supplemented with choline (which is metabolized by the gut microbiota and host enzymes to trimethylamine N-oxide) for 12 weeks. We observed smaller aortic lesions and lower plasma cholesterol levels in conventionally raised mice compared with germ-free mice on a chow diet; these differences were not observed in mice on a Western diet. Choline supplementation increased plasma trimethylamine N-oxide levels in conventionally raised mice but not in germ-free mice. However, this treatment did not affect the size of aortic lesions or plasma cholesterol levels. Gut microbiota composition was analyzed by sequencing of 16S rRNA genes. As expected, the global community structure and relative abundance of many taxa differed between mice fed chow or a Western diet. Choline supplementation had minor effects on the community structure although the relative abundance of some taxa belonging to Clostridiales was altered. Conclusions— In conclusion, the impact of the gut microbiota on atherosclerosis is dietary dependent and is associated with plasma cholesterol levels. Furthermore, the microbiota was required for trimethylamine N-oxide production from dietary choline, but this process could not be linked to increased atherosclerosis in this model. </jats:sec

Coulomb dissociation of <SUP>20,21</SUP>N

Neutron-rich light nuclei and their reactions play an important role in the creation of chemical elements. Here, data from a Coulomb dissociation experiment on N20,21 are reported. Relativistic N20,21 ions impinged on a lead target and the Coulomb dissociation cross section was determined in a kinematically complete experiment. Using the detailed balance theorem, the N19(n,γ)N20 and N20(n,γ)N21 excitation functions and thermonuclear reaction rates have been determined. The N19(n,γ)N20 rate is up to a factor of 5 higher at T<1GK with respect to previous theoretical calculations, leading to a 10% decrease in the predicted fluorine abundance

Twin GEM-TPC prototype (HGB4) beam test at GSI – a tracking detector for the Super-FRS

The GEM-TPC detector will be part of the standard Super-FRS detection system, as tracker detectors at several focal diagnostic stations along the separator and its three branches.Non peer reviewe

Design and evaluation of meningococcal vaccines through structure-based modification of host and pathogen molecules.

Neisseria meningitis remains a leading cause of sepsis and meningitis, and vaccines are required to prevent infections by this important human pathogen. Factor H binding protein (fHbp) is a key antigen that elicits protective immunity against the meningococcus and recruits the host complement regulator, fH. As the high affinity interaction between fHbp and fH could impair immune responses, we sought to identify non-functional fHbps that could act as effective immunogens. This was achieved by alanine substitution of fHbps from all three variant groups (V1, V2 and V3 fHbp) of the protein; while some residues affected fH binding in each variant group, the distribution of key amino underlying the interaction with fH differed between the V1, V2 and V3 proteins. The atomic structure of V3 fHbp in complex with fH and of the C-terminal barrel of V2 fHbp provide explanations to the differences in the precise nature of their interactions with fH, and the instability of the V2 protein. To develop transgenic models to assess the efficacy of non-functional fHbps, we determined the structural basis of the low level of interaction between fHbp and murine fH; in addition to changes in amino acids in the fHbp binding site, murine fH has a distinct conformation compared with the human protein that would sterically inhibit binding to fHbp. Non-functional V1 fHbps were further characterised by binding and structural studies, and shown in non-transgenic and transgenic mice (expressing chimeric fH that binds fHbp and precisely regulates complement system) to retain their immunogenicity. Our findings provide a catalogue of non-functional fHbps from all variant groups that can be included in new generation meningococcal vaccines, and establish proof-in-principle for clinical studies to compare their efficacy with wild-type fHbps

Twin GEM-TPC prototype (HGB4) beam test at GSI and Jyväskylä : a development for the Super-FRS at FAIR

The FAIR facility is an international accelerator centre for research with ion and antiproton beams. It is being built at Darmstadt, Germany as an extension to the current GSI research institute. One major part of the facility will be the Super-FRS[2] separator, which will be include in phase one of the project construction. The NUSTAR experiments will benefit from the Super-FRS, which will deliver an unprecedented range of radioactive ion beams (RIB). These experiments will use beams of different energies and characteristics in three different branches; the high-energy which utilizes the RIB at relativistic energies 300-1500 MeV/u as created in the production process, the low-energy branch aims to use beams in the range of 0-150 MeV/u whereas the ring branch will cool and store beams in the NESR ring. The main tasks for the Super-FRS beam diagnostics chambers will be for the set up and adjustment of the separator as well as to provide tracking and event-by-event particle identification. The Helsinki Institute of Physics, and the Detector Laboratory and Experimental Electronics at GSI are in a joint R&D of a GEM-TPC detector which could satisfy the requirements of such tracking detectors, in terms of tracking efficiency, space resolution, count rate capability and momenta resolution. The current prototype, which is the generation four of this type, is two GEM-TPCs in twin configuration inside the same vessel. This means that one of the GEM-TPC is flipped on the middle plane w.r.t. the other one. This chamber was tested at Jyväskylä accelerator with protons projectiles and at GSI with Uranium, fragments and Carbon beams during this year 2016.Peer reviewe

Coulomb dissociation of O-16 into He-4 and C-12

We measured the Coulomb dissociation of O-16 into He-4 and C-12 within the FAIR Phase-0 program at GSI Helmholtzzentrum fur Schwerionenforschung Darmstadt, Germany. From this we will extract the photon dissociation cross section O-16(alpha,gamma)C-12, which is the time reversed reaction to C-12(alpha,gamma)O-16. With this indirect method, we aim to improve on the accuracy of the experimental data at lower energies than measured so far. The expected low cross section for the Coulomb dissociation reaction and close magnetic rigidity of beam and fragments demand a high precision measurement. Hence, new detector systems were built and radical changes to the (RB)-B-3 setup were necessary to cope with the high-intensity O-16 beam. All tracking detectors were designed to let the unreacted O-16 ions pass, while detecting the C-12 and He-4

Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

\ua9 2015 The Authors. This is an open access article under the CC BY-NC-ND license. Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk