143 research outputs found

    Research on Rare Diseases in Germany – The GAIN Registry: a registry for individuals with congenital multi-organ autoimmune diseases

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    Background: Patient registries are an important tool for networking medical caregivers and research, especially in the field of rare diseases. Individuals afflicted by multi-organ autoimmune diseases typically suffer from inflammation of multiple organs. Project: GAIN (German genetic multi-organ Auto-Immunity Network) is the German network for research and therapy optimisation for individuals with congenital multi-organ autoimmune diseases. As a sub-project of the network, the registry systematically collects data from this patient group and makes it available for research purposes. Results: A data set was developed and made available for the GAIN Registry that can map the complex clinical status of persons with multi-organ autoimmune diseases. Data from 486 individuals have been documented to date. Conclusions: The GAIN register allows for a very comprehensive documentation that clearly goes beyond previous approaches, e.g. by linking it to biosamples collected in the consortium. The planned inclusion of patients in the documentation, e.g. of data on quality of life, opens up a new field

    Forschung zu Seltenen Erkrankungen in Deutschland - Das GAIN-Register: Ein Register für Personen mit angeborenen Multi-Organ-Autoimmunerkrankungen

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    Hintergrund: Patientenregister sind insbesondere im Bereich der seltenen Erkrankungen ein wichtiges Instrument für die Vernetzung der medizinischen Betreuenden und die Forschung. Bei Multi-Organ-Autoimmunerkrankungen leiden Betroffene typischerweise an Entzündungen mehrerer Organe. Projekt: GAIN (German genetic multi-organ Auto-Immunity Network) ist das deutsche Netzwerk für die Erforschung und Therapieoptimierung von Personen mit angeborenen Multi-Organ-Autoimmunerkrankungen. Als ein Teilprojekt des Netzwerks erfasst das Register Daten dieser Patientengruppe systematisch und stellt sie für die Forschung zur Verfügung. Ergebnisse: Für das GAIN-Register wurde ein Datensatz entwickelt und bereitgestellt, der die komplexen Krankheitsbilder von Personen mit Multi-Organ-Autoimmunerkrankungen abbilden kann. Bisher wurden die Daten von 486 Personen dokumentiert. Schlussfolgerungen: Das GAIN-Register erlaubt eine sehr umfassende Dokumentation, die deutlich über bisherige Ansätze hinausgeht, bspw. durch die Verknüpfung mit im Konsortium gesammelten Bioproben. Durch das geplante Einbeziehen der Patientinnen und Patienten in die Dokumentation, z. B. von Daten zur Lebensqualität, wird ein neuer Bereich erschlossen

    Long-term follow-up of IPEX syndrome patients after different therapeutic strategies : an international multicenter retrospective study

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    Background: Immunodysregulation polyendocrinopathy enteropathy x-linked(IPEX) syndrome is a monogenic autoimmune disease caused by FOXP3 mutations. Because it is a rare disease, the natural history and response to treatments, including allogeneic hematopoietic stem cell transplantation (HSCT) and immunosuppression (IS), have not been thoroughly examined. Objective: This analysis sought to evaluate disease onset, progression, and long-term outcome of the 2 main treatments in long-term IPEX survivors. Methods: Clinical histories of 96 patients with a genetically proven IPEX syndrome were collected from 38 institutions worldwide and retrospectively analyzed. To investigate possible factors suitable to predict the outcome, an organ involvement (OI) scoring system was developed. Results: We confirm neonatal onset with enteropathy, type 1 diabetes, and eczema. In addition, we found less common manifestations in delayed onset patients or during disease evolution. There is no correlation between the site of mutation and the disease course or outcome, and the same genotype can present with variable phenotypes. HSCT patients (n = 58) had a median follow-up of 2.7 years (range, 1 week-15 years). Patients receiving chronic IS (n 5 34) had a median follow-up of 4 years (range, 2 months-25 years). The overall survival after HSCT was 73.2% (95% CI, 59.4-83.0) and after IS was 65.1% (95% CI, 62.8-95.8). The pretreatment OI score was the only significant predictor of overall survival after transplant (P = .035) but not under IS. Conclusions: Patients receiving chronic IS were hampered by disease recurrence or complications, impacting long-term.disease-free survival. When performed in patients with a low OI score, HSCT resulted in disease resolution with better quality of life, independent of age, donor source, or conditioning regimen

    A Roadmap for HEP Software and Computing R&D for the 2020s

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    Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.Peer reviewe

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

    Alignment of the CMS tracker with LHC and cosmic ray data

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    © CERN 2014 for the benefit of the CMS collaboration, published under the terms of the Creative Commons Attribution 3.0 License by IOP Publishing Ltd and Sissa Medialab srl. Any further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation and DOI.The central component of the CMS detector is the largest silicon tracker ever built. The precise alignment of this complex device is a formidable challenge, and only achievable with a significant extension of the technologies routinely used for tracking detectors in the past. This article describes the full-scale alignment procedure as it is used during LHC operations. Among the specific features of the method are the simultaneous determination of up to 200 000 alignment parameters with tracks, the measurement of individual sensor curvature parameters, the control of systematic misalignment effects, and the implementation of the whole procedure in a multi-processor environment for high execution speed. Overall, the achieved statistical accuracy on the module alignment is found to be significantly better than 10μm

    Measurement of the W boson polarisation in ttˉt\bar{t} events from pp collisions at s\sqrt{s} = 8 TeV in the lepton + jets channel with ATLAS

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