Laboratory and Field Studies on Herpetosoma Trypanosomes From Portugal

Several small mammals were trapped in the Arrabida region (Portugal) and checked for the presence of trypanosomes which were found in 33 of the 197 (11.1 %) Mus spretus and in 9 of the 29 (31 %) Crocidura russula observed. To our knowledge, this was the first time that trypanosomes were isolated from these mammals species. In the liver of one dead C. russula was observed different parasite forms. The studies of infectivity to experimental rodents, analyses of the DNA buoyant density and the isoenzymatic profiles, show that trypanosomes isolates from M. spretus were identical to Trypanosoma musculi isolates from Mus musculus. However the isolates from C. russula, although related to the isolates from murine rodents, were clearly separated from these and close to Trypanosoma microti. These findings may allow further studies on the detection of their vectors and on the study of trypanosome reproduction.publishersversionpublishe

A closer look at chaotic advection in the stratosphere: part II: statistical diagnostics

Statistical diagnostics of mixing and transport are computed for a numerical model of forced shallow-water flow on the sphere and a middle-atmosphere general circulation model. In particular, particle dispersion statistics, transport fluxes, Liapunov exponents (probability density functions and ensemble averages), and tracer concentration statistics are considered. It is shown that the behavior of the diagnostics is in accord with that of kinematic chaotic advection models so long as stochasticity is sufficiently weak. Comparisons with random-strain theory are made

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies

BACKGROUND: An important function of many complex networks is to inhibit or promote the transmission of disease, resources, or information between individuals. However, little is known about how the temporal dynamics of individual-level interactions affect these networks and constrain their function. Ant colonies are a model comparative system for understanding general principles linking individual-level interactions to network-level functions because interactions among individuals enable integration of multiple sources of information to collectively make decisions, and allocate tasks and resources. METHODOLOGY/FINDINGS: Here we show how the temporal and spatial dynamics of such individual interactions provide upper bounds to rates of colony-level information flow in the ant Temnothorax rugatulus. We develop a general framework for analyzing dynamic networks and a mathematical model that predicts how information flow scales with individual mobility and group size. CONCLUSIONS/SIGNIFICANCE: Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted, and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales

Effectiveness of intensive group and individual interventions for smoking cessation in primary health care settings: a randomized trial

<p>Abstract</p> <p>Objectives</p> <p>Primary: To compare the effectiveness of intensive group and individual interventions for smoking cessation in a primary health care setting; secondary: to identify the variables associated with smoking cessation.</p> <p>Methods</p> <p>Three-pronged clinical trial with randomisation at the individual level. We performed the following: an intensive individual intervention (III), an intensive group intervention (IGI) and a minimal intervention (MI). Included in the study were smokers who were prepared to quit smoking. Excluded from the study were individuals aged less than 18 years or with severe mental conditions or terminal illnesses. The outcome measure was continued abstinence at 12 months confirmed through CO-oximetry (CO). The analysis was based on intention to treat.</p> <p>Results</p> <p>In total, 287 smokers were recruited: 81 in the III, 111 in the IGI, and 95 in the MI. Continued abstinence at 12 months confirmed through CO was 7.4% in the III, 5.4% in the IGI, and 1% in the MI. No significant differences were noted between III and MI on the one hand, and between IGI and MI on the other [RR 7.04 (0.9-7.2) and RR 5.1 (0.6-41.9), respectively]. No differences were noted between IGI and III [RR 0.7 (0.2-2.2)]. In multivariate analysis, only overall visit length showed a statistically significant association with smoking cessation.</p> <p>Conclusions</p> <p>The effectiveness of intensive smoking interventions in this study was lower than expected. No statistically significant differences were found between the results of individual and group interventions.</p> <p>Trial registration number</p> <p>ISRCTN32323770</p

Prevalence and correlates of inadequate glycaemic control: results from a nationwide survey in 6,671 adults with diabetes in Brazil

Diabetes is a significant public health burden on the basis of its increased incidence, morbidity, and mortality. This study aimed to estimate the prevalence of inadequate glycaemic control and its correlates in a large multicentre survey of Brazilian patients with diabetes. A cross-sectional study was conducted in a consecutive sample of patients aged 18 years or older with either type 1 or type 2 diabetes, attending health centres located in ten large cities in Brazil (response rate = 84%). Information about diabetes, current medications, complications, diet, and satisfaction with treatment were obtained by trained interviewers, using a standardized questionnaire. Glycated haemoglobin (HbA1c) was measured by high-performance liquid chromatography in a central laboratory. Patients with HbA1c ≥ 7 were considered to have inadequate glycaemic control. Overall 6,701 patients were surveyed, 979 (15%) with type 1 and 5,692 (85%) with type 2 diabetes. The prevalence of inadequate glycaemic control was 76%. Poor glycaemic control was more common in patients with type 1 diabetes (90%) than in those with type 2 (73%), P < 0.001. Characteristics significantly associated with improved glycaemic control included: fewer years of diabetes duration, multi professional care, participation in a diabetes health education program, and satisfaction with current diabetes treatment. Despite increased awareness of the benefits of tight glycaemic control, we found that few diabetic patients in Brazil met recommended glycaemic control targets. This may contribute to increased rates of diabetic complications, which may impact health care costs. Our data support the public health message of implementation of early, aggressive management of diabetes

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

Predicting global invasion risks: a management tool to prevent future introductions

Predicting regions at risk from introductions of non-native species and the subsequent invasions is a fundamental aspect of horizon scanning activities that enable the development of more effective preventative actions and planning of management measures. The Asian cyprinid fish topmouth gudgeon Pseudorasbora parva has proved highly invasive across Europe since its introduction in the 1960s. In addition to direct negative impacts on native fish populations, P. parva has potential for further damage through transmission of an emergent infectious disease, known to cause mortality in other species. To quantify its invasion risk, in regions where it has yet to be introduced, we trained 900 ecological niche models and constructed an Ensemble Model predicting suitability, then integrated a proxy for introduction likelihood. This revealed high potential for P. parva to invade regions well beyond its current invasive range. These included areas in all modelled continents, with several hotspots of climatic suitability and risk of introduction. We believe that these methods are easily adapted for a variety of other invasive species and that such risk maps could be used by policy-makers and managers in hotspots to formulate increased surveillance and early-warning systems that aim to prevent introductions and subsequent invasions

Contribution of spatially explicit models to climate change adaptation and mitigation plans for a priority forest habitat

Climate change will impact forest ecosystems, their biodiversity and the livelihoods they sustain. Several adaptation and mitigation strategies to counteract climate change impacts have been proposed for these ecosystems. However, effective implementation of such strategies requires a clear understanding of how climate change will influence the future distribution of forest ecosystems. This study uses maximum entropy modelling (MaxEnt) to predict environmentally suitable areas for cork oak (Quercus suber) woodlands, a socio-economically important forest ecosystem protected by the European Union Habitats Directive. Specifically, we use two climate change scenarios to predict changes in environmental suitability across the entire geographical range of the cork oak and in areas where stands were recently established. Up to 40 % of current environmentally suitable areas for cork oak may be lost by 2070, mainly in northern Africa and southern Iberian Peninsula. Almost 90 % of new cork oak stands are predicted to lose suitability by the end of the century, but future plantations can take advantage of increasing suitability in northern Iberian Peninsula and France. The predicted impacts cross-country borders, showing that a multinational strategy, will be required for cork oak woodland adaptation to climate change. Such a strategy must be regionally adjusted, featuring the protection of refugia sites in southern areas and stimulating sustainable forest management in areas that will keep long-term suitability. Afforestation efforts should also be promoted but must consider environmental suitability and land competition issues