Ecological niche modelling and differentiation between Rhodnius neglectus Lent, 1954 and Rhodnius nasutus Stål, 1859 (Hemiptera: Reduviidae: Triatominae) in Brazil

Ecological niche modelling was used to predict the potential geographical distribution of Rhodnius nasutus Stål and Rhodnius neglectus Lent, in Brazil and to investigate the niche divergence between these morphologically similar triatomine species. The distribution of R. neglectus covered mainly the cerrado of Central Brazil, but the prediction maps also revealed its occurrence in transitional areas within the caatinga, Pantanal and Amazon biomes. The potential distribution of R. nasutus covered the Northeastern Region of Brazil in the semi-arid caatinga and the Maranhão babaçu forests. Clear ecological niche differences between these species were observed. R. nasutus occurred more in warmer and drier areas than R. neglectus. In the principal component analysis PC1 was correlated with altitude and temperature (mainly temperature in the coldest and driest months) and PC2 with vegetation index and precipitation. The prediction maps support potential areas of co-occurrence for these species in the Maranhão babaçu forests and in caatinga/cerrado transitional areas, mainly in state of Piaui. Entomologists engaged in Chagas disease vector surveillance should be aware that R. neglectus and R. nasutus can occur in the same localities of Northeastern Brazil. Thus, the identification of bugs in these areas should be improved by applying morphometrical and/or molecular methods.

Population pharmacokinetic-pharmacodynamic modelling of angiotensin receptor blockade in healthy volunteers.

OBJECTIVE: To compare the pharmacokinetic and pharmacodynamic characteristics of angiotensin II receptor antagonists as a therapeutic class. DESIGN: Population pharmacokinetic-pharmacodynamic modelling study. METHODS: The data of 14 phase I studies with 10 different drugs were analysed. A common population pharmacokinetic model (two compartments, mixed zero- and first-order absorption, two metabolite compartments) was applied to the 2685 drug and 900 metabolite concentration measurements. A standard nonlinear mixed effect modelling approach was used to estimate the drug-specific parameters and their variabilities. Similarly, a pharmacodynamic model was applied to the 7360 effect measurements, i.e. the decrease of peak blood pressure response to intravenous angiotensin challenge recorded by finger photoplethysmography. The concentration of drug and metabolite in an effect compartment was assumed to translate into receptor blockade [maximum effect (Emax) model with first-order link]. RESULTS: A general pharmacokinetic-pharmacodynamic (PK-PD) model for angiotensin antagonism in healthy individuals was successfully built up for the 10 drugs studied. Representatives of this class share different pharmacokinetic and pharmacodynamic profiles. Their effects on blood pressure are dose-dependent, but the time course of the effect varies between the drugs. CONCLUSIONS: The characterisation of PK-PD relationships for these drugs gives the opportunity to optimise therapeutic regimens and to suggest dosage adjustments in specific conditions. Such a model can be used to further refine the use of this class of drugs.

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Quality of Web-based information on obsessive compulsive disorder.

BACKGROUND: The Internet is increasingly used as a source of information for mental health issues. The burden of obsessive compulsive disorder (OCD) may lead persons with diagnosed or undiagnosed OCD, and their relatives, to search for good quality information on the Web. This study aimed to evaluate the quality of Web-based information on English-language sites dealing with OCD and to compare the quality of websites found through a general and a medically specialized search engine. METHODS: Keywords related to OCD were entered into Google and OmniMedicalSearch. Websites were assessed on the basis of accountability, interactivity, readability, and content quality. The "Health on the Net" (HON) quality label and the Brief DISCERN scale score were used as possible content quality indicators. Of the 235 links identified, 53 websites were analyzed. RESULTS: The content quality of the OCD websites examined was relatively good. The use of a specialized search engine did not offer an advantage in finding websites with better content quality. A score ≥16 on the Brief DISCERN scale is associated with better content quality. CONCLUSION: This study shows the acceptability of the content quality of OCD websites. There is no advantage in searching for information with a specialized search engine rather than a general one. Practical implications: The Internet offers a number of high quality OCD websites. It remains critical, however, to have a provider-patient talk about the information found on the Web.

Modelling short-term ultraviolet exposure as an alternative to individual dosimetry

Background: Excessive exposure to solar Ultra-Violet (UV) light is the main cause of most skin cancers in humans. Factors such as the increase of solar irradiation at ground level (anthropic pollution), the rise in standard of living (vacation in sunny areas), and (mostly) the development of outdoor activities have contributed to increase exposure. Thus, unsurprisingly, incidence of skin cancers has increased over the last decades more than that of any other cancer. Melanoma is the most lethal cutaneous cancer, while cutaneous carcinomas are the most common cancer type worldwide. UV exposure depends on environmental as well as individual factors related to activity. The influence of individual factors on exposure among building workers was investigated in a previous study. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure. A high variance of short-term exposure was observed between different body locations, indicating the occurrence of intense, subacute exposures. It was also found that effective short-term exposure ranged between 0 and 200% of ambient irradiation, suggesting that ambient irradiation is a poor predictor of effective exposure. Various dosimetric techniques enable to assess individual effective exposure, but dosimetric measurements remain tedious and tend to be situation-specific. As a matter of facts, individual factors (exposure time, body posture and orientation in the sun) often limit the extrapolation of exposure results to similar activities conducted in other conditions. Objective: The research presented in this paper aims at developing and validating a predictive tool of effective individual exposure to solar UV. Methods: Existing computer graphic techniques (3D rendering) were adapted to reflect solar exposure conditions and calculate short-term anatomical doses. A numerical model, represented as a 3D triangular mesh, is used to represent the exposed body. The amount of solar energy received by each "triangle is calculated, taking into account irradiation intensity, incidence angle and possible shadowing from other body parts. The model take into account the three components of the solar irradiation (direct, diffuse and albedo) as well as the orientation and posture of the body. Field measurements were carried out using a forensic mannequin at the Payerne MeteoSwiss station. Short-term dosimetric measurements were performed in 7 anatomical locations for 5 body postures. Field results were compared to the model prediction obtained from the numerical model. Results: The best match between prediction and measurements was obtained for upper body parts such as shoulders (Ratio Modelled/Measured; Mean = 1.21, SD = 0.34) and neck (Mean = 0.81, SD = 0.32). Small curved body parts such as forehead (Mean = 6.48, SD = 9.61) exhibited a lower matching. The prediction is less accurate for complex postures such as kneeling (Mean = 4.13, SD = 8.38) compared to standing up (Mean = 0.85, SD = 0.48). The values obtained from the dosimeters and the ones computed from the model are globally consistent. Conclusion: Although further development and validation are required, these results suggest that effective exposure could be predicted for a given activity (work or leisure) in various ambient irradiation conditions. Using a generic modelling approach is of high interest in terms of implementation costs as well as predictive and retrospective capabilities.

Combining palaeodistribution modelling and phylogeographical approaches for identifying glacial refugia in Alpine Primula

Aim We investigated the late Quaternary history of two closely related and partly sympatric species of Primula from the south-western European Alps, P. latifolia Lapeyr. and P. marginata Curtis, by combining phylogeographical and palaeodistribution modelling approaches. In particular, we were interested in whether the two approaches were congruent and identified the same glacial refugia. Location South-western European Alps. Methods For the phylogeographical analysis we included 353 individuals from 28 populations of P. marginata and 172 individuals from 15 populations of P. latifolia and used amplified fragment length polymorphisms (AFLPs). For palaeodistribution modelling, species distribution models (SDMs) were based on extant species occurrences and then projected to climate models (CCSM, MIROC) of the Last Glacial Maximum (LGM), approximately 21 ka. Results The locations of the modelled LGM refugia were confirmed by various indices of genetic variation. The refugia of the two species were largely geographically isolated, overlapping only 6% to 11% of the species' total LGM distribution. This overlap decreased when the position of the glacial ice sheet and the differential elevational and edaphic distributions of the two species were considered. Main conclusions The combination of phylogeography and palaeodistribution modelling proved useful in locating putative glacial refugia of two alpine species of Primula. The phylogeographical data allowed us to identify those parts of the modelled LGM refugial area that were likely source areas for recolonization. The use of SDMs predicted LGM refugial areas substantially larger and geographically more divergent than could have been predicted by phylogeographical data alone

Simulation methods with extended stability for stiff biochemical kinetics

Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.

Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Modelling the effect of minor orthopaedic day surgery on patient mood at the early post-operative period: a prospective population-based cohort study.

OBJECTIVE: The effect of minor orthopaedic day surgery (MiODS) on patient's mood. METHODS: A prospective population-based cohort study of 148 consecutive patients with age above 18 and less than 65, an American Society of Anaesthesiology (ASA) score of 1, and the requirement of general anaesthesia (GA) were included. The Medical Outcomes Study - Short Form 36 (SF-36), Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) were used pre- and post-operatively. RESULTS: The mean physical component score of SF-36 before surgery was 45.3 (SD=+/-10.1) and 8 weeks following surgery was 44.9 (SD=+/-11.04) [n=148, p=0.51, 95% CI=(-1.03 to 1.52)]. For the measurement of the changes in mood using BDI, BAI and SF-36, latent construct modelling was employed to increase validity. The covariance between mood pre- and post-operatively (cov=69.44) corresponded to a correlation coefficient, r=0.88 indicating that patients suffering a greater number of mood symptoms before surgery continue to have a greater number of symptoms following surgery. When the latent mood constructs were permitted to have different means the model fitted well with chi(2) (df=1)=0.86 for which p=0.77, thus the null hypothesis that MiODS has no effect on patient mood was rejected. CONCLUSIONS: MiODS affects patient mood which deteriorates at 8 weeks post-operatively regardless of the pre-operative patient mood state. More importantly patients suffering a greater number of mood symptoms before MiODS continue to have a greater number of symptoms following surgery.

Web semàntica aplicada a la gestió i caracterització de dades, sensors i accés a serveis per a vaixells d'investigació oceanogràfica

Amb el present projecte es proposa fer un estudi de la web semàntica aplicada a la descripció i modelització de la instrumentació marina operada en el context de campanyes d'investigació oceanogràfica.

A limited area model intercomparison on the "Montserrat-2000" flash-flood event using statistical and deterministic methods

In the scope of the European project Hydroptimet, INTERREG IIIB-MEDOCC programme, limited area model (LAM) intercomparison of intense events that produced many damages to people and territory is performed. As the comparison is limited to single case studies, the work is not meant to provide a measure of the different models' skill, but to identify the key model factors useful to give a good forecast on such a kind of meteorological phenomena. This work focuses on the Spanish flash-flood event, also known as "Montserrat-2000" event. The study is performed using forecast data from seven operational LAMs, placed at partners' disposal via the Hydroptimet ftp site, and observed data from Catalonia rain gauge network. To improve the event analysis, satellite rainfall estimates have been also considered. For statistical evaluation of quantitative precipitation forecasts (QPFs), several non-parametric skill scores based on contingency tables have been used. Furthermore, for each model run it has been possible to identify Catalonia regions affected by misses and false alarms using contingency table elements. Moreover, the standard "eyeball" analysis of forecast and observed precipitation fields has been supported by the use of a state-of-the-art diagnostic method, the contiguous rain area (CRA) analysis. This method allows to quantify the spatial shift forecast error and to identify the error sources that affected each model forecasts. High-resolution modelling and domain size seem to have a key role for providing a skillful forecast. Further work is needed to support this statement, including verification using a wider observational data set.

Statistical analysis and modelling of weather radar beam propagation conditions in the Po Valley (Italy)

Ground clutter caused by anomalous propagation (anaprop) can affect seriously radar rain rate estimates, particularly in fully automatic radar processing systems, and, if not filtered, can produce frequent false alarms. A statistical study of anomalous propagation detected from two operational C-band radars in the northern Italian region of Emilia Romagna is discussed, paying particular attention to its diurnal and seasonal variability. The analysis shows a high incidence of anaprop in summer, mainly in the morning and evening, due to the humid and hot summer climate of the Po Valley, particularly in the coastal zone. Thereafter, a comparison between different techniques and datasets to retrieve the vertical profile of the refractive index gradient in the boundary layer is also presented. In particular, their capability to detect anomalous propagation conditions is compared. Furthermore, beam path trajectories are simulated using a multilayer ray-tracing model and the influence of the propagation conditions on the beam trajectory and shape is examined. High resolution radiosounding data are identified as the best available dataset to reproduce accurately the local propagation conditions, while lower resolution standard TEMP data suffers from interpolation degradation and Numerical Weather Prediction model data (Lokal Model) are able to retrieve a tendency to superrefraction but not to detect ducting conditions. Observing the ray tracing of the centre, lower and upper limits of the radar antenna 3-dB half-power main beam lobe it is concluded that ducting layers produce a change in the measured volume and in the power distribution that can lead to an additional error in the reflectivity estimate and, subsequently, in the estimated rainfall rate.

Modelling of weather radar echoes from anomalous propagation using a hybrid parabolic equation method and NWP model data

Contamination of weather radar echoes by anomalous propagation (anaprop) mechanisms remains a serious issue in quality control of radar precipitation estimates. Although significant progress has been made identifying clutter due to anaprop there is no unique method that solves the question of data reliability without removing genuine data. The work described here relates to the development of a software application that uses a numerical weather prediction (NWP) model to obtain the temperature, humidity and pressure fields to calculate the three dimensional structure of the atmospheric refractive index structure, from which a physically based prediction of the incidence of clutter can be made. This technique can be used in conjunction with existing methods for clutter removal by modifying parameters of detectors or filters according to the physical evidence for anomalous propagation conditions. The parabolic equation method (PEM) is a well established technique for solving the equations for beam propagation in a non-uniformly stratified atmosphere, but although intrinsically very efficient, is not sufficiently fast to be practicable for near real-time modelling of clutter over the entire area observed by a typical weather radar. We demonstrate a fast hybrid PEM technique that is capable of providing acceptable results in conjunction with a high-resolution terrain elevation model, using a standard desktop personal computer. We discuss the performance of the method and approaches for the improvement of the model profiles in the lowest levels of the troposphere.