Myocardial infarction, ST-elevation and non-ST-elevation myocardial infarction and modelled daily pollution concentrations; a case-crossover analysis of MINAP data

Objectives: To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI). Methods: Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km x 5 km horizontal resolution, were linked to 202,550 STEMI and 322,198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003-2010. A case-crossover design was used, stratified by year, month, and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0-2 days. Results are presented as percentage change in risk per 10 µg/m3 increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly flu consultation rates, and a sine-cosine annual cycle. Results: There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulphate and elemental carbon). For NSTEMI there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI: 0.01 to 0.54)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. Conclusions: The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required

Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO2, O3, PM10 and PM2.5 for 2001-2010

This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km  ×  5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model–measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2. 5, and PM10 (daily maximum 8 h running mean for O3). The comparison was temporally and spatially comprehensive, covering a 10-year period (2 years for PM2. 5) and all non-roadside measurement data from the UK national reference monitor network, which applies consistent operational and QA/QC procedures for each pollutant (44, 47, 24, and 30 sites for NO2, O3, PM2. 5, and PM10, respectively). Two important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards – correlation and bias – together with root mean square error, were evaluated by site type, year, month, and day-of-week. Model–measurement statistics were generally better than, or comparable to, values that allow for realistic magnitudes of measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2, and PM2. 5 at both rural and urban background sites (median values of r across sites in the range 0.70–0.76 for O3 and NO2, and 0.65–0.69 for PM2. 5), but poorer for PM10 (0.47–0.50). Bias differed between environments, with generally less bias at rural background sites (median normalized mean bias (NMB) values for daily O3 and NO2 of 8 and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB  =  −29 %) and PM2. 5 (−26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km  ×  5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions (e.g. closer to traffic sources) than the grid average. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. some components of wind-blown dust. There were instances of monthly and weekday/weekend variations in the extent of model–measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model–measurement differences (aside from grid versus monitor spatial representivity) was inaccuracy of model emissions – both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals – rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology

The importance of Antarctic krill in biogeochemical cycles

Antarctic krill (Euphausia superba) are swarming, oceanic crustaceans, up to two inches long, and best known as prey for whales and penguins – but they have another important role. With their large size, high biomass and daily vertical migrations they transport and transform essential nutrients, stimulate primary productivity and influence the carbon sink. Antarctic krill are also fished by the Southern Ocean’s largest fishery. Yet how krill fishing impacts nutrient fertilisation and the carbon sink in the Southern Ocean is poorly understood. Our synthesis shows fishery management should consider the influential biogeochemical role of both adult and larval Antarctic krill

Experience developing national evidence-based clinical guidelines for childhood pneumonia in a low-income setting - making the GRADE?

BACKGROUND: The development of evidence-based clinical practice guidelines has gained wide acceptance in high-income countries and reputable international organizations. Whereas this approach may be a desirable standard, challenges remain in low-income settings with limited capacity and resources for evidence synthesis and guideline development. We present our experience using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach for the recent revision of the Kenyan pediatric clinical guidelines focusing on antibiotic treatment of pneumonia. METHODS: A team of health professionals, many with minimal prior experience conducting systematic reviews, carried out evidence synthesis for structured clinical questions. Summaries were compiled and distributed to a panel of clinicians, academicians and policy-makers to generate recommendations based on best available research evidence and locally-relevant contextual factors. RESULTS: We reviewed six eligible articles on non-severe and 13 on severe/very severe pneumonia. Moderate quality evidence suggesting similar clinical outcomes comparing amoxicillin and cotrimoxazole for non-severe pneumonia received a strong recommendation against adopting amoxicillin. The panel voted strongly against amoxicillin for severe pneumonia over benzyl penicillin despite moderate quality evidence suggesting clinical equivalence between the two and additional factors favoring amoxicillin. Very low quality evidence suggesting ceftriaxone was as effective as the standard benzyl penicillin plus gentamicin for very severe pneumonia received a strong recommendation supporting the standard treatment. CONCLUSIONS: Although this exercise may have fallen short of the rigorous requirements recommended by the developers of GRADE, it was arguably an improvement on previous attempts at guideline development in low-income countries and offers valuable lessons for future similar exercises where resources and locally-generated evidence are scarce

Analysing Dynamical Behavior of Cellular Networks via Stochastic Bifurcations

The dynamical structure of genetic networks determines the occurrence of various biological mechanisms, such as cellular differentiation. However, the question of how cellular diversity evolves in relation to the inherent stochasticity and intercellular communication remains still to be understood. Here, we define a concept of stochastic bifurcations suitable to investigate the dynamical structure of genetic networks, and show that under stochastic influence, the expression of given proteins of interest is defined via the probability distribution of the phase variable, representing one of the genes constituting the system. Moreover, we show that under changing stochastic conditions, the probabilities of expressing certain concentration values are different, leading to different functionality of the cells, and thus to differentiation of the cells in the various types

The emergent rhizosphere: imaging the development of the porous architecture at the root-soil interface

The rhizosphere is the zone of soil infuenced by a plant root and is critical for plant health and nutrient acquisition. All below ground resources must pass through this dynamic zone prior to their capture by plant roots. However, researching the undisturbed rhizosphere has proved very challenging. Here we compare the temporal changes to the intact rhizosphere pore structure during the emergence of a developing root system in diferent soils. High resolution X-ray Computed Tomography (CT) was used to quantify the impact of root development on soil structural change, at scales relevant to individual micro-pores and aggregates (µm). A comparison of micro-scale structural evolution in homogenously packed soils highlighted the impacts of a penetrating root system in changing the surrounding porous architecture and morphology. Results indicate the structural zone of infuence of a root can be more localised than previously reported (µm scale rather than mm scale). With time, growing roots signifcantly alter the soil physical environment in their immediate vicinity through reducing root-soil contact and crucially increasing porosity at the root-soil interface and not the converse as has often been postulated. This ‘rhizosphere pore structure’ and its impact on associated dynamics are discussed

Prevalence and risk factors of major depressive disorder in HIV/AIDS as seen in semi-urban Entebbe district, Uganda

BACKGROUND: Not much is known about the risk factors of major depressive disorder (MDD) in HIV/AIDS in the African socio-cultural context. Therefore a study was undertaken to examine the prevalence and risk factors of MDD in HIV/AIDS in semi-urban Uganda. METHODS: A cross-sectional study was undertaken among 618 respondents attending two HIV clinics in Uganda. RESULTS: Prevalence of MDD was 8.1%. Factors associated with MDD at univariate analysis only were female gender, family history of mental illness, negative coping style, alcohol dependency disorder, food insecurity and stress; not associated with MDD were social support, neurocognitive impairment, CD4 counts and BMI. Factors independently associated with MDD were psychosocial impairment, adverse life events, post traumatic stress disorder, generalised anxiety disorder and life-time attempted suicide. CONCLUSION: Psychological and social factors were the main risk factors of MDD among ambulatory HIV positive persons with no evidence for the role of the neurotoxic effects of HIV. Treatment approaches for MDD in this patient group should be modeled on those used among non-HIV groups

An Advanced Method to Assess the Diet of Free-Ranging Large Carnivores Based on Scats

<div><h3>Background</h3><p>The diet of free-ranging carnivores is an important part of their ecology. It is often determined from prey remains in scats. In many cases, scat analyses are the most efficient method but they require correction for potential biases. When the diet is expressed as proportions of consumed mass of each prey species, the consumed prey mass to excrete one scat needs to be determined and corrected for prey body mass because the proportion of digestible to indigestible matter increases with prey body mass. Prey body mass can be corrected for by conducting feeding experiments using prey of various body masses and fitting a regression between consumed prey mass to excrete one scat and prey body mass (correction factor 1). When the diet is expressed as proportions of consumed individuals of each prey species and includes prey animals not completely consumed, the actual mass of each prey consumed by the carnivore needs to be controlled for (correction factor 2). No previous study controlled for this second bias.</p> <h3>Methodology/Principal Findings</h3><p>Here we use an extended series of feeding experiments on a large carnivore, the cheetah (<em>Acinonyx jubatus</em>), to establish both correction factors. In contrast to previous studies which fitted a linear regression for correction factor 1, we fitted a biologically more meaningful exponential regression model where the consumed prey mass to excrete one scat reaches an asymptote at large prey sizes. Using our protocol, we also derive correction factor 1 and 2 for other carnivore species and apply them to published studies. We show that the new method increases the number and proportion of consumed individuals in the diet for large prey animals compared to the conventional method.</p> <h3>Conclusion/Significance</h3><p>Our results have important implications for the interpretation of scat-based studies in feeding ecology and the resolution of human-wildlife conflicts for the conservation of large carnivores.</p> </div

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente