Analysis and visualization of H7 influenza using genomic,evolutionary and geographic information in a modular web service

We have reported previously on use of a web‐based application, Supramap ( http://supramap.org ) for the study of biogeographic, genotypic, and phenotypic evolution. Using Supramap we have developed maps of the spread of drug‐resistant influenza and host shifts in H1N1 and H5N1 influenza and coronaviruses such as SARS. Here we report on another zoonotic pathogen, H7 influenza, and provide an update on the implementation of Supramap as a web service. We find that the emergence of pathogenic strains of H7 is labile with many transitions from high to low pathogenicity, and from low to high pathogenicity. We use Supramap to put these events in a temporal and geospatial context. We identify several lineages of H7 influenza with biomarkers of high pathogenicity in regions that have not been reported in the scientific literature. The original implementation of Supramap was built with tightly coupled client and server software. Now we have decoupled the components to provide a modular web service for POY ( http://poyws.org ) that can be consumed by a data provider to create a novel application. To demonstrate the web service, we have produced an application, Geogenes ( http://geogenes.org ). Unlike in Supramap, in which the user is required to create and upload data files, in Geogenes the user works from a graphical interface to query an underlying dataset. Geogenes demonstrates how the web service can provide underlying processing for any sequence and metadata database. © The Willi Hennig Society 2012.     

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.     

Can Newts Cope with the Heat? Disparate Thermoregulatory Strategies of Two Sympatric Species in Water

Many ectotherms effectively reduce their exposure to low or high environmental temperatures using behavioral thermoregulation. In terrestrial ectotherms, thermoregulatory strategies range from accurate thermoregulation to thermoconformity according to the costs and limits of thermoregulation, while in aquatic taxa the quantification of behavioral thermoregulation have received limited attention. We examined thermoregulation in two sympatric newt species, Ichthyosaura alpestris and Lissotriton vulgaris, exposed to elevated water temperatures under semi-natural conditions. According to a recent theory, we predicted that species for which elevated water temperatures pose a lower thermal quality habitat, would thermoregulate more effectively than species in thermally benign conditions. In the laboratory thermal gradient, L. vulgaris maintained higher body temperatures than I. alpestris. Semi-natural thermal conditions provided better thermal quality of habitat for L. vulgaris than for I. alpestris. Thermoregulatory indices indicated that I. alpestris actively thermoregulated its body temperature, whereas L. vulgaris remained passive to the thermal heterogeneity of aquatic environment. In the face of elevated water temperatures, sympatric newt species employed disparate thermoregulatory strategies according to the species-specific quality of the thermal habitat. Both strategies reduced newt exposure to suboptimal water temperatures with the same accuracy but with or without the costs of thermoregulation. The quantification of behavioral thermoregulation proves to be an important conceptual and methodological tool for thermal ecology studies not only in terrestrial but also in aquatic ectotherms.     

Metabolites in Blood for Prediction of Bacteremic Sepsis in the Emergency Room

A metabolomics approach for prediction of bacteremic sepsis in patients in the emergency room (ER) was investigated. In a prospective study, whole blood samples from 65 patients with bacteremic sepsis and 49 ER controls were compared. The blood samples were analyzed using gas chromatography coupled to time-of-flight mass spectrometry. Multivariate and logistic regression modeling using metabolites identified by chromatography or using conventional laboratory parameters and clinical scores of infection were employed. A predictive model of bacteremic sepsis with 107 metabolites was developed and validated. The number of metabolites was reduced stepwise until identifying a set of 6 predictive metabolites. A 6-metabolite predictive logistic regression model showed a sensitivity of 0.91(95% CI 0.69–0.99) and a specificity 0.84 (95% CI 0.58–0.94) with an AUC of 0.93 (95% CI 0.89–1.01). Myristic acid was the single most predictive metabolite, with a sensitivity of 1.00 (95% CI 0.85–1.00) and specificity of 0.95 (95% CI 0.74–0.99), and performed better than various combinations of conventional laboratory and clinical parameters. We found that a metabolomics approach for analysis of acute blood samples was useful for identification of patients with bacteremic sepsis. Metabolomics should be further evaluated as a new tool for infection diagnostics.     

The Macrophage Inhibitor CNI-1493 Blocks Metastasis in a Mouse Model of Ewing Sarcoma through Inhibition of Extravasation

Metastatic Ewing Sarcoma carries a poor prognosis, and novel therapeutics to prevent and treat metastatic disease are greatly needed. Recent evidence demonstrates that tumor-associated macrophages in Ewing Sarcoma are associated with more advanced disease. While some macrophage phenotypes (M1) exhibit anti-tumor activity, distinct phenotypes (M2) may contribute to malignant progression and metastasis. In this study, we show that M2 macrophages promote Ewing Sarcoma invasion and extravasation, pointing to a potential target of anti-metastatic therapy. CNI-1493 is a selective inhibitor of macrophage function and has shown to be safe in clinical trials as an anti-inflammatory agent. In a xenograft mouse model of metastatic Ewing Sarcoma, CNI-1493 treatment dramatically reduces metastatic tumor burden. Furthermore, metastases in treated animals have a less invasive morphology. We show in vitro that CNI-1493 decreases M2-stimulated Ewing Sarcoma tumor cell invasion and extravasation, offering a functional mechanism through which CNI-1493 attenuates metastasis. These data indicate that CNI-1493 may be a safe and effective adjuvant agent for the prevention and treatment of metastatic Ewing Sarcoma.     

Impact of Non-Native Birds on Native Ecosystems: A Global Analysis

Introduction and naturalization of non-native species is one of the most important threats to global biodiversity. Birds have been widely introduced worldwide, but their impacts on populations, communities, and ecosystems have not received as much attention as those of other groups. This work is a global synthesis of the impact of nonnative birds on native ecosystems to determine (1) what groups, impacts, and locations have been best studied; (2) which taxonomic groups and which impacts have greatest effects on ecosystems, (3) how important are bird impacts at the community and ecosystem levels, and (4) what are the known benefits of nonnative birds to natural ecosystems. We conducted an extensive literature search that yielded 148 articles covering 39 species belonging to 18 families -18% of all known naturalized species. Studies were classified according to where they were conducted: Africa, Asia, Australasia, Europe, North America, South America, Islands of the Indian, of the Pacific, and of the Atlantic Ocean. Seven types of impact on native ecosystems were evaluated: competition, disease transmission, chemical, physical, or structural impact on ecosystem, grazing/ herbivory/ browsing, hybridization, predation, and interaction with other non-native species. Hybridization and disease transmission were the most important impacts, affecting the population and community levels. Ecosystem-level impacts, such as structural and chemical impacts were detected. Seven species were found to have positive impacts aside from negative ones. We provide suggestions for future studies focused on mechanisms of impact, regions, and understudied taxonomic groups.