Mammalian deltavirus without hepadnavirus coinfection in the neotropical rodent Proechimys semispinosus.

Hepatitis delta virus (HDV) is a human hepatitis-causing RNA virus, unrelated to any other taxonomic group of RNA viruses. Its occurrence as a satellite virus of hepatitis B virus (HBV) is a singular case in animal virology for which no consensus evolutionary explanation exists. Here we present a mammalian deltavirus that does not occur in humans, identified in the neotropical rodent species Proechimys semispinosus The rodent deltavirus is highly distinct, showing a common ancestor with a recently described deltavirus in snakes. Reverse genetics based on a tandem minus-strand complementary DNA genome copy under the control of a cytomegalovirus (CMV) promoter confirms autonomous genome replication in transfected cells, with initiation of replication from the upstream genome copy. In contrast to HDV, a large delta antigen is not expressed and the farnesylation motif critical for HBV interaction is absent from a genome region that might correspond to a hypothetical rodent large delta antigen. Correspondingly, there is no evidence for coinfection with an HBV-related hepadnavirus based on virus detection and serology in any deltavirus-positive animal. No other coinfecting viruses were detected by RNA sequencing studies of 120 wild-caught animals that could serve as a potential helper virus. The presence of virus in blood and pronounced detection in reproductively active males suggest horizontal transmission linked to competitive behavior. Our study establishes a nonhuman, mammalian deltavirus that occurs as a horizontally transmitted infection, is potentially cleared by immune response, is not focused in the liver, and possibly does not require helper virus coinfection

The index of rural access: an innovative integrated approach for measuring primary care access

<p>Abstract</p> <p>Background</p> <p>The problem of access to health care is of growing concern for rural and remote populations. Many Australian rural health funding programs currently use simplistic rurality or remoteness classifications as proxy measures of access. This paper outlines the development of an alternative method for the measurement of access to primary care, based on combining the three key access elements of spatial accessibility (availability and proximity), population health needs and mobility.</p> <p>Methods</p> <p>The recently developed two-step floating catchment area (2SFCA) method provides a basis for measuring primary care access in rural populations. In this paper, a number of improvements are added to the 2SFCA method in order to overcome limitations associated with its current restriction to a single catchment size and the omission of any distance decay function. Additionally, small-area measures for the two additional elements, health needs and mobility are developed. By utilising this improved 2SFCA method, the three access elements are integrated into a single measure of access. This index has been developed within the state of Victoria, Australia.</p> <p>Results</p> <p>The resultant index, the Index of Rural Access, provides a more sensitive and appropriate measure of access compared to existing classifications which currently underpin policy measures designed to overcome problems of limited access to health services. The most powerful aspect of this new index is its ability to identify access differences within rural populations at a much finer geographical scale. This index highlights that many rural areas of Victoria have been incorrectly classified by existing measures as homogenous in regards to their access.</p> <p>Conclusion</p> <p>The Index of Rural Access provides the first truly integrated index of access to primary care. This new index can be used to better target the distribution of limited government health care funding allocated to address problems of poor access to primary health care services in rural areas.</p

The Role of Visible Wealth for Deprivation

Motivated by the lack of literature linking actual to perceived relative deprivation, this paper assesses the role of visibility in the deprivation of goods and assets vis-à-vis income behind perceptions of relative deprivation. We rely on household survey data that includes unique information on reported perceived deprivation with a pre-specified reference group, namely others in the town or village. Based on a large number of asset and consumption items, we create an index of visible wealth by aggregating visible goods and assets using principal component weights. We find that relative deprivation in visible wealth has a ten percentage point higher explanatory power for reporting a high level of perceived deprivation than that of deprivation in income. The effect is robust under various sensitivity checks and for a number of controls. The finding sheds light on the importance of the visibility of the objects of comparison for an individual's assessment of his relative economic situation and proposes that future research should not solely rely on income-based deprivation measures

The first myriapod genome sequence reveals conservative arthropod gene content and genome organisation in the centipede Strigamia maritima.

Myriapods (e.g., centipedes and millipedes) display a simple homonomous body plan relative to other arthropods. All members of the class are terrestrial, but they attained terrestriality independently of insects. Myriapoda is the only arthropod class not represented by a sequenced genome. We present an analysis of the genome of the centipede Strigamia maritima. It retains a compact genome that has undergone less gene loss and shuffling than previously sequenced arthropods, and many orthologues of genes conserved from the bilaterian ancestor that have been lost in insects. Our analysis locates many genes in conserved macro-synteny contexts, and many small-scale examples of gene clustering. We describe several examples where S. maritima shows different solutions from insects to similar problems. The insect olfactory receptor gene family is absent from S. maritima, and olfaction in air is likely effected by expansion of other receptor gene families. For some genes S. maritima has evolved paralogues to generate coding sequence diversity, where insects use alternate splicing. This is most striking for the Dscam gene, which in Drosophila generates more than 100,000 alternate splice forms, but in S. maritima is encoded by over 100 paralogues. We see an intriguing linkage between the absence of any known photosensory proteins in a blind organism and the additional absence of canonical circadian clock genes. The phylogenetic position of myriapods allows us to identify where in arthropod phylogeny several particular molecular mechanisms and traits emerged. For example, we conclude that juvenile hormone signalling evolved with the emergence of the exoskeleton in the arthropods and that RR-1 containing cuticle proteins evolved in the lineage leading to Mandibulata. We also identify when various gene expansions and losses occurred. The genome of S. maritima offers us a unique glimpse into the ancestral arthropod genome, while also displaying many adaptations to its specific life history.This work was supported by the following grants: NHGRIU54HG003273 to R.A.G; EU Marie Curie ITN #215781 “Evonet” to M.A.; a Wellcome Trust Value in People (VIP) award to C.B. and Wellcome Trust graduate studentship WT089615MA to J.E.G; Marine rhythms of Life” of the University of Vienna, an FWF (http://www.fwf.ac.at/) START award (#AY0041321) and HFSP (http://www.hfsp.org/) research grant (#RGY0082/2010) to KT-­‐R; MFPL Vienna International PostDoctoral Program for Molecular Life Sciences (funded by Austrian Ministry of Science and Research and City of Vienna, Cultural Department -­‐Science and Research to T.K; Direct Grant (4053034) of the Chinese University of Hong Kong to J.H.L.H.; NHGRI HG004164 to G.M.; Danish Research Agency (FNU), Carlsberg Foundation, and Lundbeck Foundation to C.J.P.G.; U.S. National Institutes of Health R01AI55624 to J.H.W.; Royal Society University Research fellowship to F.M.J.; P.D.E. was supported by the BBSRC via the Babraham Institute;This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pbio.100200

Diet-related chronic disease in the northeastern United States: a model-based clustering approach

Background: Obesity and diabetes are global public health concerns. Studies indicate a relationship between socioeconomic, demographic and environmental variables and the spatial patterns of diet-related chronic disease. In this paper, we propose a methodology using model-based clustering and variable selection to predict rates of obesity and diabetes. We test this method through an application in the northeastern United States. Methods: We use model-based clustering, an unsupervised learning approach, to find latent clusters of similar US counties based on a set of socioeconomic, demographic, and environmental variables chosen through the process of variable selection. We then use Analysis of Variance and Post-hoc Tukey comparisons to examine differences in rates of obesity and diabetes for the clusters from the resulting clustering solution. Results: We find access to supermarkets, median household income, population density and socioeconomic status to be important in clustering the counties of two northeastern states. The results of the cluster analysis can be used to identify two sets of counties with significantly lower rates of diet-related chronic disease than those observed in the other identified clusters. These relatively healthy clusters are distinguished by the large central and large fringe metropolitan areas contained in their component counties. However, the relationship of socio-demographic factors and diet-related chronic disease is more complicated than previous research would suggest. Additionally, we find evidence of low food access in two clusters of counties adjacent to large central and fringe metropolitan areas. While food access has previously been seen as a problem of inner-city or remote rural areas, this study offers preliminary evidence of declining food access in suburban areas. Conclusions: Model-based clustering with variable selection offers a new approach to the analysis of socioeconomic, demographic, and environmental data for diet-related chronic disease prediction. In a test application to two northeastern states, this method allows us to identify two sets of metropolitan counties with significantly lower diet-related chronic disease rates than those observed in most rural and suburban areas. Our method could be applied to larger geographic areas or other countries with comparable data sets, offering a promising method for researchers interested in the global increase in diet-related chronic disease