Highly Pathogenic H5N1 Influenza Viruses Carry Virulence Determinants beyond the Polybasic Hemagglutinin Cleavage Site

Highly pathogenic avian influenza viruses (HPAIV) originate from avirulent precursors but differ from all other influenza viruses by the presence of a polybasic cleavage site in their hemagglutinins (HA) of subtype H5 or H7. In this study, we investigated the ability of a low-pathogenic avian H5N1 strain to transform into an HPAIV. Using reverse genetics, we replaced the monobasic HA cleavage site of the low-pathogenic strain A/Teal/Germany/Wv632/2005 (H5N1) (TG05) by a polybasic motif from an HPAIV (TG05poly). To elucidate the virulence potential of all viral genes of HPAIV, we generated two reassortants carrying the HA from the HPAIV A/Swan/Germany/R65/06 (H5N1) (R65) plus the remaining genes from TG05 (TG05-HAR65) or in reversed composition the mutated TG05 HA plus the R65 genes (R65-HATG05poly). In vitro, TG05poly and both reassortants were able to replicate without the addition of trypsin, which is characteristic for HPAIV. Moreover, in contrast to avirulent TG05, the variants TG05poly, TG05-HAR65, and R65-HATG05poly are pathogenic in chicken to an increasing degree. Whereas the HA cleavage site mutant TG05poly led to temporary non-lethal disease in all animals, the reassortant TG05-HAR65 caused death in 3 of 10 animals. Furthermore, the reassortant R65-HATG05poly displayed the highest lethality as 8 of 10 chickens died, resembling “natural” HPAIV strains. Taken together, acquisition of a polybasic HA cleavage site is only one necessary step for evolution of low-pathogenic H5N1 strains into HPAIV. However, these low-pathogenic strains may already have cryptic virulence potential. Moreover, besides the polybasic cleavage site, the additional virulence determinants of H5N1 HPAIV are located within the HA itself and in other viral proteins

Evaluation of species distribution model algorithms for fine-scale container-breeding mosquito risk prediction

The present work evaluates the use of species distribution model (SDM) algorithms to classify high densities of small container-breeding Aedes mosquitoes (Diptera: Culicidae) on a fine scale in the Bermuda Islands. Weekly ovitrap data collected by the Department of Health, Bermuda for the years 2006 and 2007 were used for the models. The models evaluated included the algorithms Bioclim, Domain, GARP (genetic algorithm for rule-set prediction), logistic regression and MaxEnt (maximum entropy). Models were evaluated according to performance and robustness. The area under the receiver operating characteristic curve was used to evaluate each model\u27s performance, and robustness was assessed according to the spatial correlation between classification risks for the two datasets. Relative to the other algorithms, logistic regression was the best and MaxEnt the second best model for classifying high-risk areas. We describe the importance of covariables for these two models and discuss the utility of SDMs in vector control efforts and the potential for the development of scripts that automate the task of creating risk assessment maps. © 2010 The Authors. Medical and Veterinary Entomology © 2010 The Royal Entomological Society

The Impact of Strain-Specific Immunity on Lyme Disease Incidence is Spatially Heterogeneous

Lyme disease, caused by the bacterium Borrelia burgdorferi, is the most common tick-borne infection in the US. Recent studies have demonstrated that the incidence of human Lyme disease would have been even greater were it not for the presence of strain-specific immunity, which protects previously infected patients against subsequent infections by the same B. burgdorferi strain. Here, spatial heterogeneity is incorporated into epidemiological models to accurately estimate the impact of strain-specific immunity on human Lyme disease incidence. The estimated reduction in the number of Lyme disease cases is greater in epidemiologic models that explicitly include the spatial distribution of Lyme disease cases reported at the county level than those that utilize nationwide data. strain-specific immunity has the greatest epidemiologic impact in geographic areas with the highest Lyme disease incidence due to the greater proportion of people that have been previously infected and have developed strain-specific immunity

Public health impact of strain specific immunity to Borrelia burgdorferi

BACKGROUND: Lyme disease, caused by Borrelia burgdorferi, is the most common tick-borne infection in the United States. Although humans can be infected by at least 16 different strains of B. burgdorferi, the overwhelming majority of infections are due to only four strains. It was recently demonstrated that patients who are treated for early Lyme disease develop immunity to the specific strain of B. burgdorferi that caused their infection. The aim of this study is to estimate the reduction in cases of Lyme disease in the United States that may occur as a result of type specific immunity. METHODS: The analysis was performed based on three analytical models that assessed the effects of type specific immunity. Observational data on the frequency with which different B. burgdorferi strains cause human infection in culture-confirmed patients with an initial episode of erythema migrans diagnosed between 1991 and 2005 in the Northeastern United States were used in the analyses. RESULTS: Assuming a reinfection rate of 3 % and a total incidence of Lyme disease per year of 300,000, the estimated number of averted cases of Lyme disease per year ranges from 319 to 2378 depending on the duration of type specific immunity and the model used. CONCLUSION: Given the assumptions of the analyses, this analysis suggests that type specific immunity is likely to have public health significance in the United States. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-015-1190-7) contains supplementary material, which is available to authorized users

Current Concepts in Multi-Modality Imaging of Solid Tumor Angiogenesis

There have been rapid advancements in cancer treatment in recent years, including targeted molecular therapy and the emergence of anti-angiogenic agents, which necessitate the need to quickly and accurately assess treatment response. The ideal tool is robust and non-invasive so that the treatment can be rapidly adjusted or discontinued based on efficacy. Since targeted therapies primarily affect tumor angiogenesis, morphological assessment based on tumor size alone may be insufficient, and other imaging modalities and features may be more helpful in assessing response. This review aims to discuss the biological principles of tumor angiogenesis and the multi-modality imaging evaluation of anti-angiogenic therapeutic responses

Current Concepts in Multi-Modality Imaging of Solid Tumor Angiogenesis

There have been rapid advancements in cancer treatment in recent years, including targeted molecular therapy and the emergence of anti-angiogenic agents, which necessitate the need to quickly and accurately assess treatment response. The ideal tool is robust and non-invasive so that the treatment can be rapidly adjusted or discontinued based on efficacy. Since targeted therapies primarily affect tumor angiogenesis, morphological assessment based on tumor size alone may be insufficient, and other imaging modalities and features may be more helpful in assessing response. This review aims to discuss the biological principles of tumor angiogenesis and the multi-modality imaging evaluation of anti-angiogenic therapeutic responses.</jats:p