Assessing the apparent imbalance between geochemical and biochemical indicators of meso- and bathypelagic biological activity: What the @$#! is wrong with present calculations of carbon budgets?

Metabolic activity in the water column below the euphotic zone is ultimately fuelled by the vertical flux of organic material from the surface. Over time, the deep ocean is presumably at steady state, with sources and sinks balanced. But recently compiled global budgets and intensive local field studies suggest that estimates of metabolic activity in the dark ocean exceed the influx of organic substrates. This imbalance indicates either the existence of unaccounted sources of organic carbon or that metabolic activity in the dark ocean is being over-estimated. Budgets of organic carbon flux and metabolic activity in the dark ocean have uncertainties associated with environmental variability, measurement capabilities, conversion parameters, and processes that are not well sampled. We present these issues and quantify associated uncertainties where possible, using a Monte Carlo analysis of a published data set to determine the probability that the imbalance can be explained purely by uncertainties in measurements and conversion factors. A sensitivity analysis demonstrates that the bacterial growth efficiencies and assumed cell carbon contents have the greatest effects on the magnitude of the carbon imbalance. Two poorly quantified sources, lateral advection of particles and a population of slowly settling particles, are discussed as providing a means of closing regional carbon budgets. Finally, we make recommendations concerning future research directions to reduce important uncertainties and allow a better determination of the magnitude and causes of the unbalanced carbon budgets. (C) 2010 Elsevier Ltd. All rights reserved

Emerging Solutions to Return Nature to the Urban Ocean

Urban and periurban ocean developments impact 1.5% of the global exclusive economic zones, and the demand for ocean space and resources is increasing. As we strive for a more sustainable future, it is imperative that we better design, manage, and conserve urban ocean spaces for both humans and nature. We identify three key objectives for more sustainable urban oceans: reduction of urban pressures, protection and restoration of ocean ecosystems, and support of critical ecosystem services. We describe an array of emerging evidence-based approaches, including greening grayinfrastructure, restoring habitats, and developing biotechnologies. We then explore new economic instruments and incentives for supporting these new approaches and evaluate their feasibility in delivering these objectives. Several of these tools have the potential to help bring nature back to the urban ocean while also addressing some of the critical needs of urban societies, such as climate adaptation, seafood production, clean water, and recreation, providing both human and environmental benefits in some of our most impacted ocean spaces. </jats:p

Decreased respiratory system compliance on the sixth day of mechanical ventilation is a predictor of death in patients with established acute lung injury

<p>Abstract</p> <p>Background</p> <p>Multiple studies have identified single variables or composite scores that help risk stratify patients at the time of acute lung injury (ALI) diagnosis. However, few studies have addressed the important question of how changes in pulmonary physiologic variables might predict mortality in patients during the subacute or chronic phases of ALI. We studied pulmonary physiologic variables, including respiratory system compliance, P/F ratio and oxygenation index, in a cohort of patients with ALI who survived more than 6 days of mechanical ventilation to see if changes in these variables were predictive of death and whether they are informative about the pathophysiology of subacute ALI.</p> <p>Methods</p> <p>Ninety-three patients with ALI who were mechanically ventilated for more than 6 days were enrolled in this prospective cohort study. Patients were enrolled at two medical centers in the US, a county hospital and a large academic center. Bivariate analyses were used to identify pulmonary physiologic predictors of death during the first 6 days of mechanical ventilation. Predictors on day 1, day 6 and the changes between day 1 and day 6 were compared in a multivariate logistic regression model.</p> <p>Results</p> <p>The overall mortality was 35%. In multivariate analysis, the PaO₂/FiO₂(OR 2.09, p < 0.04) and respiratory system compliance (OR 3.61, p < 0.01) were predictive of death on the 6^thday of acute lung injury. In addition, a decrease in respiratory system compliance between days 1 and days 6 (OR 2.14, p < 0.01) was independently associated with mortality.</p> <p>Conclusions</p> <p>A low respiratory system compliance on day 6 or a decrease in the respiratory system compliance between the 1^stand 6^thday of mechanical ventilation were associated with increased mortality in multivariate analysis of this cohort of patients with ALI. We suggest that decreased respiratory system compliance may identify a subset of patients who have persistent pulmonary edema, atelectasis or the fibroproliferative sequelae of ALI and thus are less likely to survive their hospitalization.</p

Application of Permutation Genetic Algorithm for Sequential Model Building–Model Validation Design of Experiments

YesThe work presented in this paper is motivated by a complex multivariate engineering problem associated with engine mapping experiments, which require efficient Design of Experiment (DoE) strategies to minimise expensive testing. The paper describes the development and evaluation of a Permutation Genetic Algorithm (PermGA) to support an exploration-based sequential DoE strategy for complex real-life engineering problems. A known PermGA was implemented to generate uniform OLH DoEs, and substantially extended to support generation of Model Building–Model Validation (MB-MV) sequences, by generating optimal infill sets of test points as OLH DoEs, that preserve good space filling and projection properties for the merged MB + MV test plan. The algorithm was further extended to address issues with non-orthogonal design spaces, which is a common problem in engineering applications. The effectiveness of the PermGA algorithm for the MB-MV OLH DoE sequence was evaluated through a theoretical benchmark problem based on the Six-Hump-Camel-Back (SHCB) function, as well as the Gasoline Direct Injection (GDI) engine steady state engine mapping problem that motivated this research. The case studies show that the algorithm is effective at delivering quasi-orthogonal space-filling DoEs with good properties even after several MB-MV iterations, while the improvement in model adequacy and accuracy can be monitored by the engineering analyst. The practical importance of this work, demonstrated through the engine case study, also is that significant reduction in the effort and cost of testing can be achieved.The research work presented in this paper was funded by the UK Technology Strategy Board (TSB) through the Carbon Reduction through Engine Optimization (CREO) project

The influence of the accessory genome on bacterial pathogen evolution

Bacterial pathogens exhibit significant variation in their genomic content of virulence factors. This reflects the abundance of strategies pathogens evolved to infect host organisms by suppressing host immunity. Molecular arms-races have been a strong driving force for the evolution of pathogenicity, with pathogens often encoding overlapping or redundant functions, such as type III protein secretion effectors and hosts encoding ever more sophisticated immune systems. The pathogens’ frequent exposure to other microbes, either in their host or in the environment, provides opportunities for the acquisition or interchange of mobile genetic elements. These DNA elements accessorise the core genome and can play major roles in shaping genome structure and altering the complement of virulence factors. Here, we review the different mobile genetic elements focusing on the more recent discoveries and highlighting their role in shaping bacterial pathogen evolution

A pilot study combining individual-based smoking cessation counseling, pharmacotherapy, and dental hygiene intervention

BACKGROUND: Dentists are in a unique position to advise smokers to quit by providing effective counseling on the various aspects of tobacco-induced diseases. The present study assessed the feasibility and acceptability of integrating dentists in a medical smoking cessation intervention. METHODS: Smokers willing to quit underwent an 8-week smoking cessation intervention combining individual-based counseling and nicotine replacement therapy and/or bupropion, provided by a general internist. In addition, a dentist performed a dental exam, followed by an oral hygiene treatment and gave information about chronic effects of smoking on oral health. Outcomes were acceptability, global satisfaction of the dentist's intervention, and smoking abstinence at 6-month. RESULTS: 39 adult smokers were included, and 27 (69%) completed the study. Global acceptability of the dental intervention was very high (94% yes, 6% mostly yes). Annoyances at the dental exam were described as acceptable by participants (61% yes, 23% mostly yes, 6%, mostly no, 10% no). Participants provided very positive qualitative comments about the dentist counseling, the oral exam, and the resulting motivational effect, emphasizing the feeling of oral cleanliness and health that encouraged smoking abstinence. At the end of the intervention (week 8), 17 (44%) participants reported smoking abstinence. After 6 months, 6 (15%, 95% CI 3.5 to 27.2) reported a confirmed continuous smoking abstinence. DISCUSSION: We explored a new multi-disciplinary approach to smoking cessation, which included medical and dental interventions. Despite the small sample size and non-controlled study design, the observed rate was similar to that found in standard medical care. In terms of acceptability and feasibility, our results support further investigations in this field. TRIAL REGISTRATION NUMBER: ISRCTN67470159

On the Treatment of Airline Travelers in Mathematical Models

The global spread of infectious diseases is facilitated by the ability of infected humans to travel thousands of miles in short time spans, rapidly transporting pathogens to distant locations. Mathematical models of the actual and potential spread of specific pathogens can assist public health planning in the case of such an event. Models should generally be parsimonious, but must consider all potentially important components of the system to the greatest extent possible. We demonstrate and discuss important assumptions relative to the parameterization and structural treatment of airline travel in mathematical models. Among other findings, we show that the most common structural treatment of travelers leads to underestimation of the speed of spread and that connecting travel is critical to a realistic spread pattern. Models involving travelers can be improved significantly by relatively simple structural changes but also may require further attention to details of parameterization

Reconciliation of the carbon budget in the ocean’s twilight zone

Photosynthesis in the surface ocean produces approximately 100 gigatonnes of organic carbon per year, of which 5 to 15 per cent is exported to the deep ocean1, 2. The rate at which the sinking carbon is converted into carbon dioxide by heterotrophic organisms at depth is important in controlling oceanic carbon storage3. It remains uncertain, however, to what extent surface ocean carbon supply meets the demand of water-column biota; the discrepancy between known carbon sources and sinks is as much as two orders of magnitude4, 5, 6, 7, 8. Here we present field measurements, respiration rate estimates and a steady-state model that allow us to balance carbon sources and sinks to within observational uncertainties at the Porcupine Abyssal Plain site in the eastern North Atlantic Ocean. We find that prokaryotes are responsible for 70 to 92 per cent of the estimated remineralization in the twilight zone (depths of 50 to 1,000 metres) despite the fact that much of the organic carbon is exported in the form of large, fast-sinking particles accessible to larger zooplankton. We suggest that this occurs because zooplankton fragment and ingest half of the fast-sinking particles, of which more than 30 per cent may be released as suspended and slowly sinking matter, stimulating the deep-ocean microbial loop. The synergy between microbes and zooplankton in the twilight zone is important to our understanding of the processes controlling the oceanic carbon sink

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal