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- Abelev, B., et al.
(författare)
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Technical Design Report for the Upgrade of the ALICE Inner Tracking System
- 2014
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Ingår i: Journal of Physics G: Nuclear and Particle Physics. - : IOP Publishing. - 0954-3899 .- 1361-6471. ; 41:8
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Tidskriftsartikel (refereegranskat)abstract
- LICE (A Large Ion Collider Experiment) is studying the physics of strongly interacting matter, and in particular the properties of the Quark–Gluon Plasma (QGP), using proton–proton, proton–nucleus and nucleus–nucleus collisions at the CERN LHC (Large Hadron Collider). The ALICE Collaboration is preparing a major upgrade of the experimental apparatus, planned for installation in the second long LHC shutdown in the years 2018–2019. A key element of the ALICE upgrade is the construction of a new, ultra-light, high-resolution Inner Tracking System (ITS) based on monolithic CMOS pixel detectors. The primary focus of the ITS upgrade is on improving the performance for detection of heavy-flavour hadrons, and of thermal photons and low-mass di-electrons emitted by the QGP. With respect to the current detector, the new Inner Tracking System will significantly enhance the determination of the distance of closest approach to the primary vertex, the tracking efficiency at low transverse momenta, and the read-out rate capabilities. This will be obtained by seven concentric detector layers based on a 50 μm thick CMOS pixel sensor with a pixel pitch of about 30×30 μm2. This document, submitted to the LHCC (LHC experiments Committee) in September 2013, presents the design goals, a summary of the R&D activities, with focus on the technical implementation of the main detector components, and the projected detector and physics performance.
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| 2. |
- Schwarz, E, et al.
(författare)
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Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
- 2019
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Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 12-
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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| 3. |
- Bujko, K., et al.
(författare)
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Postoperative chemotherapy in patients with rectal cancer receiving preoperative radio(chemo)therapy : A meta-analysis of randomized trials comparing surgery +/- a fluoropyrimidine and surgery plus a fluoropyrimidine +/- oxaliplatin
- 2015
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Ingår i: European Journal of Surgical Oncology. - : Elsevier BV. - 0748-7983 .- 1532-2157. ; 41:6, s. 713-723
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is no consensus on the role of postoperative chemotherapy in patients with rectal cancer who have received preoperative radio(chemo)therapy. Materials and methods: A systematic review and meta-analysis were performed of trials that used preoperative radio(chemo)therapy and randomized patients either between postoperative chemotherapy and observation or between a fluoropyrimidine only (FU-only) and a fluoropyrimidine with oxaliplatin (FU-OXA) as postoperative chemotherapy. Results: Five randomized studies compared postoperative chemotherapy with observation in a total of 2398 patients. None of these trials demonstrated a statistically significant benefit of chemotherapy for OS and DFS. The pooled differences in OS and DFS did not differ statistically significantly between the chemotherapy group and the observation group. The hazard ratios (HRs) and 95% confidence intervals (CIs) were 0.95 (CI: 0.82-1.10), P = 0.49 and 0.92 (CI: 0.80-1.04), P = 0.19, respectively. In the subgroup of trials in which randomization was performed after surgery (n = 753), a statistically significant positive pooled chemotherapy effect was observed for DFS (HR = 0.79, 95% CI: 0.62-1.00, P = 0.047), but not for OS (P = 0.39). Four randomized trials compared adjuvant FU OXA with adjuvant FU-only in 2710 patients. In two trials, the difference in DFS between groups was statistically significant in favour of FU OXA, and in the other two trials, the difference was not significant. The pooled difference in DFS between the FU OXA group and the FU-only group was not statistically significant: HR = 0.84 (CI: 0.66-1.06), P = 0.15. Conclusion: The use of postoperative chemotherapy in patients with rectal cancer receiving preoperative radio(chemo)therapy is not based on strong scientific evidence. (C) 2015 Elsevier Ltd. All rights reserved.
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