Development of a cell line from the American eel brain expressing endothelial cell properties.

A cell line (eelB) was developed from the outgrowth of adherent cells from brain explants of the American eel, Anguilla rostrata (Lesueur). EelB cells have been grown routinely in L-15 with 10% fetal bovine serum (FBS), undergone over 100 passages, and cryopreserved successfully. The cells from late-passage cultures (>45) were polygonal, formed capillary-like structures (CLS) on Matrigel, and stained immunocytochemically for von Willebrand factor (vWF) and for three tight junction proteins, zonula occludens-1 (ZO-1), claudin 3, and claudin 5. These results suggest that eelB is an endothelial cell line, one of the few from fish and the first from the brain. Despite this, eelB did not respond to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) with the induction of CYP1A protein. The cells from early-passage cultures (<20) had more varied shapes and did not form CLS on Matrigel. Only cells from early-passage cultures formed in suspension three-dimensional aggregates that had some cells expressing alkaline phosphatase and nestin. These cells are thought to be neural stem cells and the aggregates neurospheres. The emergence of endothelial-like cells upon the continued subcultivation of cells from early-passage cultures that had neural stem cells has been described previously for mammals, but this is a first for teleosts. Remarkably, cells from all passage levels were stained strongly for senescence-associated ß-galactosidase (SA ß-Gal) activity.

Development and characterization of an endothelial cell line from the bulbus arteriosus of walleye, Sander vitreus.

A cell line has been developed from the bulbus arteriosus (BA) of the walleye (WE), Sander vitreus (Mitchill), and is termed WEBA. WEBA produced collagen I, and when held at confluency for days or weeks, spontaneously formed capillary-like tubes. WEBA cells bound fluorescently-labeled Ulex europaeus lectin agglutinin I (UEA-1), took up acetylated low density lipoprotein (Ac-LDL), were stained for von Willebrand factor (vWF), and produced nitric oxide (NO). The cytoskeleton consisted at least of α- and ß-tubulin, vimentin, and actin, with the actin organized into circumferential bundles. Immunofluorescence staining revealed at least two tight junction proteins, zonula occludens-1 (ZO-1) and claudin 3. Together these results suggest that WEBA is an endothelial cell line. Relatively high doses of 2,3,7,8-tetrachlorodibenzodioxin (TCDD) induced cytochrome P4501A (CYP1A) protein and 7-ethoxyresorufin o-deethylase (EROD) activity in WEBA. As one of the first fish endothelial and BA cell lines, WEBA should be useful in many disciplines in which the teleost cardiovascular system is a focus.

The use of sampling weights in Bayesian hierarchical models for small area estimation.

Hierarchical modeling has been used extensively for small area estimation. However, design weights that are required to reflect complex surveys are rarely considered in these models. We develop computationally efficient, Bayesian spatial smoothing models that acknowledge the design weights. Computation is carried out using the integrated nested Laplace approximation, which is fast. An extensive simulation study is presented that considers the effects of non-response and non-random selection of individuals, allowing examination of the impact of ignoring the design weights and the benefits of spatial smoothing. The results show that, when compared with standard approaches, mean squared error can be greatly reduced with the proposed methods. Bias reduction occurs through the inclusion of the design weights, with variance reduction being achieved through hierarchical smoothing. We analyze data from the Washington State 2006 Behavioral Risk Factor Surveillance System. The models are easily and quickly fitted within the R environment, using existing packages.

Global rise in human infectious disease outbreaks.

To characterize the change in frequency of infectious disease outbreaks over time worldwide, we encoded and analysed a novel 33-year dataset (1980-2013) of 12,102 outbreaks of 215 human infectious diseases, comprising more than 44 million cases occuring in 219 nations. We merged these records with ecological characteristics of the causal pathogens to examine global temporal trends in the total number of outbreaks, disease richness (number of unique diseases), disease diversity (richness and outbreak evenness) and per capita cases. Bacteria, viruses, zoonotic diseases (originating in animals) and those caused by pathogens transmitted by vector hosts were responsible for the majority of outbreaks in our dataset. After controlling for disease surveillance, communications, geography and host availability, we find the total number and diversity of outbreaks, and richness of causal diseases increased significantly since 1980 (p < 0.0001). When we incorporate Internet usage into the model to control for biased reporting of outbreaks (starting 1990), the overall number of outbreaks and disease richness still increase significantly with time (p < 0.0001), but per capita cases decrease significantly ( p = 0.005). Temporal trends in outbreaks differ based on the causal pathogen's taxonomy, host requirements and transmission mode. We discuss our preliminary findings in the context of global disease emergence and surveillance.

A comparison of spatial smoothing methods for small area estimation with sampling weights.

Small area estimation (SAE) is an important endeavor in many fields and is used for resource allocation by both public health and government organizations. Often, complex surveys are carried out within areas, in which case it is common for the data to consist only of the response of interest and an associated sampling weight, reflecting the design. While it is appealing to use spatial smoothing models, and many approaches have been suggested for this endeavor, it is rare for spatial models to incorporate the weighting scheme, leaving the analysis potentially subject to bias. To examine the properties of various approaches to estimation we carry out a simulation study, looking at bias due to both non-response and non-random sampling. We also carry out SAE of smoking prevalence in Washington State, at the zip code level, using data from the 2006 Behavioral Risk Factor Surveillance System. The computation times for the methods we compare are short, and all approaches are implemented in R using currently available packages.