Introduction of an automated system for the diagnosis and quantification of hepatitis B and hepatitis C viruses.

Hepatitis B virus (HBV) and Hepatitis C virus (HCV) infections pose major public health problems because of their prevalence worldwide. Consequently, screening for these infections is an important part of routine laboratory activity. Serological and molecular markers are key elements in diagnosis, prognosis and treatment monitoring for HBV and HCV infections. Today, automated chemiluminescence immunoassay (CLIA) analyzers are widely used for virological diagnosis, particularly in high-volume clinical laboratories. Molecular biology techniques are routinely used to detect and quantify viral genomes as well as to analyze their sequence; in order to determine their genotype and detect resistance to antiviral drugs. Real-time PCR, which provides high sensitivity and a broad dynamic range, has gradually replaced other signal and target amplification technologies for the quantification and detection of nucleic acid. The next-generation DNA sequencing techniques are still restricted to research laboratories.The serological and molecular marker methods available for HBV and HCV are discussed in this article, along with their utility and limitations for use in Chronic Hepatitis B (CHB) diagnosis and monitoring.

Predicting positive food challenges at the introduction of nuts in sensitised children

Rationale: Children with atopic diseases in early life are frequently found with positive IgE tests to nuts, without a history of previous ingestion. We aimed to identify risk factors for reactions to nuts at their first introduction. Methods: A detailed retrospective case note and database analysis was performed. Inclusion criteria were: patients aged 3 to 16 years who had had a standardized food challenge to peanut and/or tree nuts due to primary sensitisation to the nut (positive specific IgE or SPT). A detailed assessment was performed of factors relating to food challenge outcome with univariate and multivariate logistic regression analysis. Results: There were 98 food challenges (48% peanut, 52% tree nut) with 29 positive, 67 negative and 2 inconclusive challenges. A positive maternal history and a specific IgE > 2 kU/l were strongly associated with a significantly increased risk of a positive food challenge (OR 3.54; 95% CI 1.28 to 9.81; and OR 4.82; 95% CI 1.57 to 14.86; respectively). There was no significant association between the type of nut, age, presence of other food allergies, paternal or sibling atopic history, other atopic conditions or severity of previous reaction to other foods. Conclusions: We have demonstrated an association between the presence of a maternal atopic history and a specific IgE > 2 kU/l, and a significant increase in the likelihood of a positive food challenge in children with primary sensitisation to nuts. Although requiring further prospective validation we suggest these easily identifiable components should be considered when deciding the need for a nut challenge.

Community introduction of practice parameters for autistic spectrum disorders: Advancing early recognition.

OBJECTIVES: Within a strong interdisciplinary framework, improvement in the quality of care for children with autistic spectrum disorders through a 2 year implementation program of Practice Parameters, aimed principally at improving early detection and intervention. METHOD: We developed Practice Parameters (PPs) for Pervasive Developmental Disorders and circulated the PPs to all child and adolescent psychiatrists practicing in the region. RESULTS: PP development and parallel information strategies resulted in a significant decrease of 1.5 years in the mean-age-at-diagnosis. However, further analysis indicated that improvement was only transient. CONCLUSION: Despite the encouraging improvement in mean-age-at-diagnosis 2 years after PP implementation, other indicators showed a failure to maintain the improvements. A systematic screening program would be the most reliable method to reinforce the PPs.

Evaluation of Haemophilus influenzaetype b carrier status among children 10 years after the introduction of Hib vaccine in Brazil

The aim of the present study was to assess the prevalence of Haemophilus influenzaetype b (Hib) nasopharyngeal (NP) colonisation among healthy children where Hib vaccination using a 3p+0 dosing schedule has been routinely administered for 10 years with sustained coverage (> 90%). NP swabs were collected from 2,558 children who had received the Hib vaccine, of whom 1,379 were 12-< 24 months (m) old and 1,179 were 48-< 60 m old. Hi strains were identified by molecular methods. Hi carriage prevalence was 45.1% (1,153/2,558) and the prevalence in the 12-< 24 m and 48-< 60 m age groups were 37.5% (517/1,379) and 53.9% (636/1,179), respectively. Hib was identified in 0.6% (16/2,558) of all children in the study, being 0.8% (11/1,379) and 0.4% (5/1,179) among the 12-< 24 m and 48-< 60 m age groups, respectively. The nonencapsulate Hi colonisation was 43% (n = 1,099) and was significantly more frequent at 48-< 60 m of age (51.6%, n = 608) compared with that at 12-< 24 m of age (35.6%, n = 491). The overall resistance rates to ampicillin and chloramphenicol were 16.5% and 3.7%, respectively; the co-resistance was detected in 2.6%. Our findings showed that the Hib carrier rate in healthy children under five years was very low after 10 years of the introduction of the Hib vaccine.

Improved accuracy of co-morbidity coding over time after the introduction of ICD-10 administrative data.

BACKGROUND: Co-morbidity information derived from administrative data needs to be validated to allow its regular use. We assessed evolution in the accuracy of coding for Charlson and Elixhauser co-morbidities at three time points over a 5-year period, following the introduction of the International Classification of Diseases, 10th Revision (ICD-10), coding of hospital discharges.METHODS: Cross-sectional time trend evaluation study of coding accuracy using hospital chart data of 3'499 randomly selected patients who were discharged in 1999, 2001 and 2003, from two teaching and one non-teaching hospital in Switzerland. We measured sensitivity, positive predictive and Kappa values for agreement between administrative data coded with ICD-10 and chart data as the 'reference standard' for recording 36 co-morbidities.RESULTS: For the 17 the Charlson co-morbidities, the sensitivity - median (min-max) - was 36.5% (17.4-64.1) in 1999, 42.5% (22.2-64.6) in 2001 and 42.8% (8.4-75.6) in 2003. For the 29 Elixhauser co-morbidities, the sensitivity was 34.2% (1.9-64.1) in 1999, 38.6% (10.5-66.5) in 2001 and 41.6% (5.1-76.5) in 2003. Between 1999 and 2003, sensitivity estimates increased for 30 co-morbidities and decreased for 6 co-morbidities. The increase in sensitivities was statistically significant for six conditions and the decrease significant for one. Kappa values were increased for 29 co-morbidities and decreased for seven.CONCLUSIONS: Accuracy of administrative data in recording clinical conditions improved slightly between 1999 and 2003. These findings are of relevance to all jurisdictions introducing new coding systems, because they demonstrate a phenomenon of improved administrative data accuracy that may relate to a coding 'learning curve' with the new coding system.

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.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.

BIOMOD - a platform for ensemble forecasting of species distributions

BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species-environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package

First record of species of Liogenys (Coleoptera, Melolonthidae) associated with winter grain crops in Rio Grande do Sul (Brazil)

First record of species of Liogenys (Coleoptera, Melolonthidae) associated with winter crops in Rio Grande do Sul (Brazil). Some species of Liogenys Guerín-Meneville, 1831 are known to cause damage to soybean, corn and other summer crops in the Brazilian "Cerrado" region. This work aimed to identify melolontid larvae associated with winter crops in Rio Grande do Sul state. Larvae and adults of Liogenys species were collected from the municipalities of Ijuí, Cruz Alta, Manoel Viana, São Luiz Gonzaga and São Francisco de Assis. The specimens were identified as L. bidenticeps Moser, 1919; L. fusca Blanchard, 1851, L. obesa Burmeister, 1855, and L. sinuaticeps Moser, 1918. This is the first record of these species associated with winter grain crops, for Rio Grande do Sul State. Biological and behavioral studies are necessary to confirm their association with host plants.

Fauna of Simuliidae (Diptera) from the state of Espírito Santo, Brazil: distribution, new records and list of species

Fauna of Simuliidae (Diptera) from the state of Espírito Santo, Brazil: Distribution, new records and list of species. The fauna of Simuliidae in Brazil is composed of 87 species, 17 of which are recorded from the state of Espírito Santo. Entomological collections were carried out in 2010-2011 with the objective of increasing the knowledge of the species richness of this family in the state. Ninety three rivers and streams were sampled, each collection being carried out in a 50m transect. During the study period 30 species were collected, 13 of which represent new records for the state, 12 of the genus Simulium and one of the genus Lutzsimulium. Among these new state records one, Simulium lobatoi, also represents a new record from southeastern Brazil. The other newly recorded species are: Lutzsimulium hirticosta, Simulium distinctum, Simulium exiguum, Simulium oyapockense, Simulium botulibranchium, Simulium petropoliense, Simulium clavibranchium, Simulium rappae, Simulium minusculum, Simulium dinellii, Simulium ochraceum and Simulium scutistriatum.

Note on predation of the brood of Mischocyttarus injucundus (de Saussure) by another social wasp in Caxiuanã, Pará, Brazil, with new records of species for the Ferreira Penna Research Station (Hymenoptera, Vespidae, Polistinae)

ABSTRACT Predation of the brood of Mischocyttarus injucundus by another polistine social wasp is reported from an Amazonian rainforest locality. This is the first report for the American tropics of naturally occurring predation by one social wasp on the brood of another. Three species are added to the list of the Ferreira Penna Research Station, raising known local richness to 81 species: Mischocyttarus filiformis (de Saussure, 1854), Mischocyttarus vaqueroi Zikán, 1949, and Parachartergus griseus (Fox, 1898).

Unfolding nature "in silico" : overcoming practical and metodological limitations of species distribution models

Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.