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Complexome profiling is an emerging ‘omics’ approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the “minimum information required for a complexome profiling experiment” (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.
Space charge lenses use a confined electron cloud for the focusing of ion beams. The focusing strength is given by the electron density whereas the density distribution influences the mapping quality of the space charge lens and is related to the confinement. The plasma parameters, loss as well as production mechanisms have a strong impact on plasma beam interactions. A scaled up space charge lens was constructed to investigate the properties of a nonneutral plasmas in detail. New non-interceptive diagnostic has been developed to characterize the collective behaviour of the confined nonneutral plasma in terms of an optimized lens design and parameters. Experimental results will be presented in comparison with numerical simulations.
Chopper systems are used to pulse charged particle beams. In most cases, electric deflection systems are used to generate beam pulses of defined lengths and appropriate repetition rates. At high beam intensities, the field distribution of the chopper system needs to be adapted precisely to the beam dynamics in order to avoid aberrations. An additional challenge is a robust design which guarantees reliable operation. For the Frankfurt Neutron Source FRANZ, an E×B chopper system is being developed which combines static magnetic deflection with a pulsed electric field in a Wien filter configuration. It will generate proton pulses with a flat top of 50 ns at a repetition rate of 250 kHz for 120 keV, 200 mA beams. For the electric deflection, pre-experiments with static and pulsed fields were performed using a helium ion beam. In pulsed mode operation, ion beams of different energies were deflected with voltages of up to ±6 kV and the resulting response was measured using a beam current transformer. A comparison between experiments and theoretical calculations as well as numerical simulations are presented.
Space charge lenses using a stable electron cloud for focusing low energy heavy ion beams are an alternative concept to conventional ion optics. Due to external fields electrons are confined inside the lens’ volume. In case of a homogeneously distributed electron cloud the linear electric space charge field enables beam focusing free of aberration. Since the mapping quality of the lens is related to the confinement, non-destructive diagnostics has been developed to determine the plasma parameters and to characterize the collective behavior of the confined nonneutral plasma. Moreover, a scaled up space charge lens was constructed for a detailed investigation of the nonneutral plasma properties as well as beam interactions with a stable confined electron cloud. Experimental results will be presented in comparison with numerical simulations.
No association between Parkinson disease and autoantibodies against NMDA-type glutamate receptors
(2019)
Background: IgG-class autoantibodies to N-Methyl-D-Aspartate (NMDA)-type glutamate receptors define a novel entity of autoimmune encephalitis. Studies examining the prevalence of NMDA IgA/IgM antibodies in patients with Parkinson disease with/without dementia produced conflicting results. We measured NMDA antibodies in a large, well phenotyped sample of Parkinson patients without and with cognitive impairment (n = 296) and controls (n = 295) free of neuropsychiatric disease. Detailed phenotyping and large numbers allowed statistically meaningful correlation of antibody status with diagnostic subgroups as well as quantitative indicators of disease severity and cognitive impairment.
Methods: NMDA antibodies were analysed in the serum of patients and controls using well established validated assays. We used anti-NMDA antibody positivity as the main independent variable and correlated it with disease status and phenotypic characteristics.
Results: The frequency of NMDA IgA/IgM antibodies was lower in Parkinson patients (13%) than in controls (22%) and higher than in previous studies in both groups. NMDA IgA/IgM antibodies were neither significantly associated with diagnostic subclasses of Parkinson disease according to cognitive impairment, nor with quantitative indicators of disease severity and cognitive impairment. A positive NMDA antibody status was positively correlated with age in controls but not in Parkinson patients.
Conclusion: It is unlikely albeit not impossible that NMDA antibodies play a significant role in the pathogenesis or progression of Parkinson disease e.g. to Parkinson disease with dementia, while NMDA IgG antibodies define a separate disease of its own.
Complexome profiling is an emerging ‘omics approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the “minimum information required for a complexome profiling experiment” (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.