Fire-Related Carbon Emissions from Land Use Transitions in Southern Amazonia

Various land-use transitions in the tropics contribute to atmospheric carbon emissions, including forest conversion for small-scale farming, cattle ranching, and production of commodities such as soya and palm oil. These transitions involve fire as an effective and inexpensive means for clearing. We applied the DECAF (DEforestation CArbon Fluxes) model to Mato Grosso, Brazil to estimate fire emissions from various land-use transitions during 2001-2005. Fires associated with deforestation contributed 67 Tg C/yr (17 and 50 Tg C/yr from conversion to cropland and pasture, respectively), while conversion of savannas and existing cattle pasture to cropland contributed 17 Tg C/yr and pasture maintenance fires 6 Tg C/yr. Large clearings (>100 ha/yr) contributed 67% of emissions but comprised only 10% of deforestation events. From a policy perspective, results imply that intensification of agricultural production on already-cleared land and policies to discourage large clearings would reduce the major sources of emissions from fires in this region. Copyright 2008 by the American Geophysical Union

Management of breakthrough disease in patients with multiple sclerosis: when an increasing of Interferon beta dose should be effective?

<p>Abstract</p> <p>Background</p> <p>In daily clinical setting, some patients affected by relapsing-remitting Multiple Sclerosis (RRMS) are switched from the low-dose to the high-dose Interferon beta (IFNB) in order to achieve a better control of the disease.</p> <p>Purpose</p> <p>In this observational, post-marketing study we reported the 2-year clinical outcomes of patients switched to the high-dose IFNB; we also evaluated whether different criteria adopted to switch patients had an influence on the clinical outcomes.</p> <p>Methods</p> <p>Patients affected by RRMS and switched from the low-dose to the high-dose IFNB due to the occurrence of relapses, or contrast-enhancing lesions (CELs) as detected by yearly scheduled MRI scans, were followed for two years. Expanded Disability Status Scale (EDSS) scores, as well as clinical relapses, were evaluated during the follow-up period.</p> <p>Results</p> <p>We identified 121 patients switched to the high-dose IFNB. One hundred patients increased the IFNB dose because of the occurrence of one or more relapses, and 21 because of the presence of one or more CELs, even in absence of clinical relapses. At the end of the 2-year follow-up, 72 (59.5%) patients had a relapse, and 51 (42.1%) reached a sustained progression on EDSS score. Overall, 85 (70.3%) patients showed some clinical disease activity (i.e. relapses or disability progression) after the switch.</p> <p>Relapse risk after increasing the IFNB dose was greater in patients who switched because of relapses than those switched only for MRI activity (HR: 5.55, p = 0.001). A high EDSS score (HR: 1.77, p < 0.001) and the combination of clinical and MRI activity at switch raised the risk of sustained disability progression after increasing the IFNB dose (HR: 2.14, p = 0.01).</p> <p>Conclusion</p> <p>In the majority of MS patients, switching from the low-dose to the high-dose IFNB did not reduce the risk of further relapses or increased disability in the 2-year follow period.</p> <p>Although we observed that patients who switched only on the basis on MRI activity (even in absence of clinical attacks) had a lower risk of further relapses, larger studies are warranted before to recommend a switch algorithm based on MRI findings.</p

Mutation analysis of the MDM4 gene in German breast cancer patients

<p>Abstract</p> <p>Background</p> <p>MDM4 is a negative regulator of p53 and cooperates with MDM2 in the cellular response to DNA damage. It is unknown, however, whether <it>MDM4 </it>gene alterations play some role in the inherited component of breast cancer susceptibility.</p> <p>Methods</p> <p>We sequenced the whole <it>MDM4 </it>coding region and flanking untranslated regions in genomic DNA samples obtained from 40 German patients with familial breast cancer. Selected variants were subsequently screened by RFLP-based assays in an extended set of breast cancer cases and controls.</p> <p>Results</p> <p>Our resequencing study uncovered two <it>MDM4 </it>coding variants in 4/40 patients. Three patients carried a silent substitution at codon 74 that was linked with another rare variant in the 5'UTR. No association of this allele with breast cancer was found in a subsequent screening of 133 patients with bilateral breast cancer and 136 controls. The fourth patient was heterozygous for the missense substitution D153G which is located in a less conserved region of the MDM4 protein but may affect a predicted phosphorylation site. The D153G substitution only partially segregated with breast cancer in the family and was not identified on additional 680 chromosomes screened.</p> <p>Conclusion</p> <p>This study did not reveal clearly pathogenic mutations although it uncovered two new unclassified variants at a low frequency. We conclude that there is no evidence for a major role of <it>MDM4 </it>coding variants in the inherited susceptibility towards breast cancer in German patients.</p

Perioperative fluid and volume management: physiological basis, tools and strategies

Fluid and volume therapy is an important cornerstone of treating critically ill patients in the intensive care unit and in the operating room. New findings concerning the vascular barrier, its physiological functions, and its role regarding vascular leakage have lead to a new view of fluid and volume administration. Avoiding hypervolemia, as well as hypovolemia, plays a pivotal role when treating patients both perioperatively and in the intensive care unit. The various studies comparing restrictive vs. liberal fluid and volume management are not directly comparable, do not differ (in most instances) between colloid and crystalloid administration, and mostly do not refer to the vascular barrier's physiologic basis. In addition, very few studies have analyzed the use of advanced hemodynamic monitoring for volume management

The ALICE experiment at the CERN LHC

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 161626 m3 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