| 1. |
- Aamodt, K., et al.
(författare)
-
The ALICE experiment at the CERN LHC
- 2008
-
Ingår i: Journal of Instrumentation. - 1748-0221. ; 3:S08002
-
Forskningsöversikt (refereegranskat)abstract
- ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries, Its overall dimensions are 16 x 16 x 26 m(3) with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008.
|
|
| 2. |
- Rocha, M., et al.
(författare)
-
Natural computation meta-heuristics for the in silico optimization of microbial strains
- 2008
-
Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 9, s. 499-
-
Tidskriftsartikel (refereegranskat)abstract
- Background: One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/ productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for in silico metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution. Results: This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of in silico metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using S. cerevisiae and E. coli as model organisms. The proposed algorithms are able to reach optimal/ near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs. Conclusion: The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automati c discovery of the approximate number of gene deletions, without compromising the optimality of the solutions. © 2008 Rocha et al; licensee BioMed Central Ltd.
|
|
| 3. |
- Mohty, M., et al.
(författare)
-
Reduced intensity conditioning allogeneic stem cell transplantation for adult patients with acute lymphoblastic leukemia : A retrospective study from the European Group for Blood and Marrow Transplantation
- 2008
-
Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 0390-6078 .- 1592-8721. ; 93:2, s. 303-306
-
Tidskriftsartikel (refereegranskat)abstract
- This retrospective study reported the outcome of 97 adult acute lymphoblastic leukemia patients who received a reduced-intensity conditioning allogeneic stem cell transplantation. With a median follow-up of 2.8 years, two year overall-survival, leukemia-free survival and non-relapse mortality were significantly better in patients transplanted in first complete remission (CR1, 52±9%, 42±10%, and 18±7% respectively) compared with those transplanted in more advanced phase (p=0.003, p=0.002 and p=0.01 respectively). In multivariate analysis, disease status (CR1 vs. advanced, p=0.001) and chronic graft-vs-host disease (p=0.01) were associated with an improved overall-survival, suggesting that reduced-intensity conditioning allogeneic stem cell transplantation is feasible in patients with high risk lymphoblastic leukemia in remission at transplantation. ©2008 Ferrata Storti Foundation.
|
|
