55 Eplerenone benefit in patients with elevated baseline heart rate in the EPHESUS trial

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106670/1/ehfs80020-7.pd

Cardiovascular magnetic resonance activity in the United Kingdom: a survey on behalf of the british society of cardiovascular magnetic resonance

<p>Background: The indications, complexity and capabilities of cardiovascular magnetic resonance (CMR) have rapidly expanded. Whether actual service provision and training have developed in parallel is unknown.</p> <p>Methods: We undertook a systematic telephone and postal survey of all public hospitals on behalf of the British Society of Cardiovascular Magnetic Resonance to identify all CMR providers within the United Kingdom.</p> <p>Results: Of the 60 CMR centres identified, 88% responded to a detailed questionnaire. Services are led by cardiologists and radiologists in equal proportion, though the majority of current trainees are cardiologists. The mean number of CMR scans performed annually per centre increased by 44% over two years. This trend was consistent across centres of different scanning volumes. The commonest indication for CMR was assessment of heart failure and cardiomyopathy (39%), followed by coronary artery disease and congenital heart disease. There was striking geographical variation in CMR availability, numbers of scans performed, and distribution of trainees. Centres without on site scanning capability refer very few patients for CMR. Just over half of centres had a formal training programme, and few performed regular audit.</p> <p>Conclusion: The number of CMR scans performed in the UK has increased dramatically in just two years. Trainees are mainly located in large volume centres and enrolled in cardiology as opposed to radiology training programmes.</p&gt

<i>Trypanosoma brucei rhodesiense</i> transmitted by a single tsetse fly bite in vervet monkeys as a model of human African trypanosomiasis

Sleeping sickness is caused by a species of trypanosome blood parasite that is transmitted by tsetse flies. To understand better how infection with this parasite leads to disease, we provide here the most detailed description yet of the course of infection and disease onset in vervet monkeys. One infected tsetse fly was allowed to feed on each host individual, and in all cases infections were successful. The characteristics of infection and disease were similar in all hosts, but the rate of progression varied considerably. Parasites were first detected in the blood 4-10 days after infection, showing that migration of parasites from the site of fly bite was very rapid. Anaemia was a key feature of disease, with a reduction in the numbers and average size of red blood cells and associated decline in numbers of platelets and white blood cells. One to six weeks after infection, parasites were observed in the cerebrospinal fluid (CSF), indicating that they had moved from the blood into the brain; this was associated with a white cell infiltration. This study shows that fly-transmitted infection in vervets accurately mimics human disease and provides a robust model to understand better how sleeping sickness develops

Intravenous sodium nitrite in acute ST-elevation myocardial infarction: a randomized controlled trial (NIAMI).

AIM: Despite prompt revascularization of acute myocardial infarction (AMI), substantial myocardial injury may occur, in part a consequence of ischaemia reperfusion injury (IRI). There has been considerable interest in therapies that may reduce IRI. In experimental models of AMI, sodium nitrite substantially reduces IRI. In this double-blind randomized placebo controlled parallel-group trial, we investigated the effects of sodium nitrite administered immediately prior to reperfusion in patients with acute ST-elevation myocardial infarction (STEMI). METHODS AND RESULTS: A total of 229 patients presenting with acute STEMI were randomized to receive either an i.v. infusion of 70 μmol sodium nitrite (n = 118) or matching placebo (n = 111) over 5 min immediately before primary percutaneous intervention (PPCI). Patients underwent cardiac magnetic resonance imaging (CMR) at 6-8 days and at 6 months and serial blood sampling was performed over 72 h for the measurement of plasma creatine kinase (CK) and Troponin I. Myocardial infarct size (extent of late gadolinium enhancement at 6-8 days by CMR-the primary endpoint) did not differ between nitrite and placebo groups after adjustment for area at risk, diabetes status, and centre (effect size -0.7% 95% CI: -2.2%, +0.7%; P = 0.34). There were no significant differences in any of the secondary endpoints, including plasma troponin I and CK area under the curve, left ventricular volumes (LV), and ejection fraction (EF) measured at 6-8 days and at 6 months and final infarct size (FIS) measured at 6 months. CONCLUSIONS: Sodium nitrite administered intravenously immediately prior to reperfusion in patients with acute STEMI does not reduce infarct size

Changes in vegetation and soil characteristics in coastal sand dunes along a gradient of atmospheric nitrogen deposition

A field survey was conducted to detect signals of atmospheric nitrogen (N) in 11 dune systems along a nitrogen deposition gradient in the United Kingdom. In the mobile and semi-fixed dunes, above-ground biomass was positively related to N inputs. This increase was largely due to increased height and cover of Ammophila arenaria. In the long term, this increased biomass may lead to increased organic matter accumulation and consequently accelerated soil development. In the fixed dunes, above ground biomass also showed a positive relationship with N inputs as did soil C : N ratio while soil available N was negatively related to N inputs. Plant species richness was negatively related to N inputs. In the dune slacks, while soil and bulk vegetation parameters showed no relationship with N inputs, cover of Carex arenaria and Hypochaeris radicata increased. Site mean Ellenberg N numbers showed no relationship with N deposition either within habitats or across the whole dataset. Neither abundance-weighting nor inclusion of the Siebel numbers for bryophytes improved the relationship. The survey reveals that the relationships of soil and vegetation with atmospheric N deposition vary between sand dune habitats but, despite this variability, clear correlations with N inputs exist. While this survey cannot establish causality, on the basis of the relationships observed we suggest a critical load range of 10 - 20 kg N ha(-1) yr(-1) for coastal sand dunes in the UK

Tropical Peatland Hydrology Simulated With a Global Land Surface Model

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM(Trop,Nat)) and drained (PEATCLSM(Trop,Drain)) tropical peatlands. Simulations with PEATCLSM(Trop,Nat) were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM(North,Nat)) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM(Trop,Drain) was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM(Trop,Drain) outperformed CLSM, PEATCLSM(North,Nat), and PEATCLSM(Trop,Nat) over drained sites. Despite the overall improvements of PEATCLSM(Trop,Nat) over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.Peer reviewe

The rationale and design of the perindopril genetic association study (PERGENE): A pharmacogenetic analysis of angiotensin-converting enzyme inhibitor therapy in patients with stable coronary artery disease

Background: Angiotensin-converting enzyme (ACE) inhibitors reduce clinical symptoms and improve outcome in patients with hypertension, heart failure, and stable coronary artery disease (CAD) and are among the most frequently used drugs in these patient groups. For hypertension, treatment is guided by the level of blood pressure. In the secondary prevention setting, there are no means of guiding therapy. Prior attempts to target ACE-inhibitors to those patients that are most likely to benefit have not been successful, mainly due to the consistency in the treatment effect in clinical subgroups. Still, for prolonged prophylactic treatment with ACE-inhibitors it would be best to target treatment to only those patients most likely to benefit, which would considerably lower the number needed to treat and increase cost-effectiveness. A new approach for such "tailored-therapy" may be to integrate information on the genetic variation between patients. Until now, pharmacogenetic research of the efficacy of ACE-inhibitor therapy in CAD patients is still in a preliminary stage. Methods: The PERindopril GENEtic association study (PERGENE) is a substudy of the EUROPA trial, a randomized double-blind placebo-controlled multicentre clinical trial which demonstrated a beneficial effect of the ACE-inhibitor perindopril in reducing cardiovascular morbidity and mortality in 12.218 patients with stable coronary artery disease (mean follow-up 4.2 years). Blood tubes were received from patients at the beginning of the EUROPA trial and buffy coats were stored at -40°C at the central core laboratory. Candidate genes were selected in the renin-angiotensin-system and bradykinin pathways. Polymorphisms were selected based on haplotype tagging principles using the HapMap genome project, Seattle and other up-to-date genetic database platforms to comprehensively cover all common genetic variation within the genes. Selection also took into consideration the functionality of SNP's, location within the gene (promoter) and existing relevant literature. The main outcome measure of PERGENE is the effect of genetic factors on the treatment benefit with ACE-inhibitors. The size of this pharmacogenetic substudy allows detection with a statistical power of 98% to detect a difference in hazard ratios (treatment effect) of 20% between genotypes with minor allele frequency of 0.20 (two-sided alpha 0.05). Conclusion: The PERGENE study is a large cardiovascular pharmacogenetic study aimed to assess the feasibility of pharmacogenetic profiling of the treatment effect of ACE-inhibitor use with the perspective to individualize treatment in patients with stable coronary artery disease

Age, extent and carbon storage of the central Congo Basin peatland complex

Peatlands are carbon-rich ecosystems that cover just three per cent of Earth's land surface, but store one-third of soil carbon. Peat soils are formed by the build-up of partially decomposed organic matter under waterlogged anoxic conditions. Most peat is found in cool climatic regions where unimpeded decomposition is slower, but deposits are also found under some tropical swamp forests. Here we present field measurements from one of the world's most extensive regions of swamp forest, the Cuvette Centrale depression in the central Congo Basin. We find extensive peat deposits beneath the swamp forest vegetation (peat defined as material with an organic matter content of at least 65 per cent to a depth of at least 0.3 metres). Radiocarbon dates indicate that peat began accumulating from about 10,600 years ago, coincident with the onset of more humid conditions in central Africa at the beginning of the Holocene. The peatlands occupy large interfluvial basins, and seem to be largely rain-fed and ombrotrophic-like (of low nutrient status) systems. Although the peat layer is relatively shallow (with a maximum depth of 5.9 metres and a median depth of 2.0 metres), by combining in situ and remotely sensed data, we estimate the area of peat to be approximately 145,500 square kilometres (95 per cent confidence interval of 131,900-156,400 square kilometres), making the Cuvette Centrale the most extensive peatland complex in the tropics. This area is more than five times the maximum possible area reported for the Congo Basin in a recent synthesis of pantropical peat extent. We estimate that the peatlands store approximately 30.6 petagrams (30.6 × 10(15) grams) of carbon belowground (95 per cent confidence interval of 6.3-46.8 petagrams of carbon)-a quantity that is similar to the above-ground carbon stocks of the tropical forests of the entire Congo Basin. Our result for the Cuvette Centrale increases the best estimate of global tropical peatland carbon stocks by 36 per cent, to 104.7 petagrams of carbon (minimum estimate of 69.6 petagrams of carbon; maximum estimate of 129.8 petagrams of carbon). This stored carbon is vulnerable to land-use change and any future reduction in precipitation

Energy Prediction for Cloud Workload Patterns

The excessive use of energy consumption in Cloud infrastructures has become one of the major cost factors for Cloud providers to maintain. In order to enhance the energy efficiency of Cloud resources, proactive and reactive management tools are used. However, these tools need to be supported with energy-awareness not only at the physical machine (PM) level but also at virtual machine (VM) level in order to enhance decision-making. This paper introduces an energy-aware profiling model to identify energy consumption for heterogeneous and homogeneous VMs running on the same PM and presents an energy-aware prediction framework to forecast future VMs energy consumption. This framework first predicts the VMs’ workload based on historical workload patterns using Autoregressive Integrated Moving Average (ARIMA) model. The predicted VM workload is then correlated to the physical resources within this framework in order to get the predicted VM energy consumption. Compared with actual results obtained in a real Cloud testbed, the predicted results show that this energy-aware prediction framework can get up to 2.58 Mean Percentage Error (MPE) for the VM workload prediction, and up to −4.47 MPE for the VM energy prediction based on periodic workload pattern