SV40 T antigen and the exocytotic pathway.

A chimeric gene consisting of DNA coding for the 15-amino acid signal peptide of influenza virus hemagglutinin and the C-terminal 694 amino acids of SV40 large T antigen was inserted into a bovine papilloma virus (BPV) expression vector and introduced into NIH-3T3 cells. Cell lines were obtained that express high levels (approximately 5 X 10(6) molecules/cell) of the chimeric protein (HA-T antigen). The biochemical properties and intracellular localization of HA-T antigens were compared with those of wild-type T antigen. Wild-type T antigen. Wild-type T antigen is located chiefly in the cell nucleus, although a small fraction is detected on the cell surface. By contrast, HA-T antigen is found exclusively in the endoplasmic reticulum (ER). During biosynthesis, HA-T antigen is co-translationally translocated across the membrane of the ER, the signal peptide is cleaved and a mannose-rich oligosaccharide is attached to the polypeptide (T antigen contains one potential N-linked glycosylation site at Asn154). HA-T antigen does not become terminally glycosylated or acylated and little or none reaches the cell surface. These results suggest that T antigen is incapable of being transported along the exocytotic pathway. To explain the presence of wild-type T antigen on the surface of SV40-transformed cells, an alternative route is proposed involving transport of T antigen from the nucleus to the cell surface.     

A sticky situation: the unexpected stability of malaria elimination

Malaria eradication involves eliminating malaria from every country where transmission occurs. Current theory suggests that the post-elimination challenges of remaining malaria-free by stopping transmission from imported malaria will have onerous operational and financial requirements. Although resurgent malaria has occurred in a majority of countries that tried but failed to eliminate malaria, a review of resurgence in countries that successfully eliminated finds only four such failures out of 50 successful programmes. Data documenting malaria importation and onwards transmission in these countries suggests malaria transmission potential has declined by more than 50-fold (i.e. more than 98%) since before elimination. These outcomes suggest that elimination is a surprisingly stable state. Elimination''s ‘stickiness’ must be explained either by eliminating countries starting off qualitatively different from non-eliminating countries or becoming different once elimination was achieved. Countries that successfully eliminated were wealthier and had lower baseline endemicity than those that were unsuccessful, but our analysis shows that those same variables were at best incomplete predictors of the patterns of resurgence. Stability is reinforced by the loss of immunity to disease and by the health system''s increasing capacity to control malaria transmission after elimination through routine treatment of cases with antimalarial drugs supplemented by malaria outbreak control. Human travel patterns reinforce these patterns; as malaria recedes, fewer people carry malaria from remote endemic areas to remote areas where transmission potential remains high. Establishment of an international resource with backup capacity to control large outbreaks can make elimination stickier, increase the incentives for countries to eliminate, and ensure steady progress towards global eradication. Although available evidence supports malaria elimination''s stickiness at moderate-to-low transmission in areas with well-developed health systems, it is not yet clear if such patterns will hold in all areas. The sticky endpoint changes the projected costs of maintaining elimination and makes it substantially more attractive for countries acting alone, and it makes spatially progressive elimination a sensible strategy for a malaria eradication endgame.     

Plasmodium falciparum malaria endemicity in Indonesia in 2010

Background

Malaria control programs require a detailed understanding of the contemporary spatial distribution of infection risk to efficiently allocate resources. We used model based geostatistics (MBG) techniques to generate a contemporary map of Plasmodium falciparum malaria risk in Indonesia in 2010.

Methods

Plasmodium falciparum Annual Parasite Incidence (PfAPI) data (2006–2008) were used to map limits of P. falciparum transmission. A total of 2,581 community blood surveys of P. falciparum parasite rate (PfPR) were identified (1985–2009). After quality control, 2,516 were included into a national database of age-standardized 2–10 year old PfPR data (PfPR_2–10) for endemicity mapping. A Bayesian MBG procedure was used to create a predicted surface of PfPR_2–10 endemicity with uncertainty estimates. Population at risk estimates were derived with reference to a 2010 human population count surface.

Results

We estimate 132.8 million people in Indonesia, lived at risk of P. falciparum transmission in 2010. Of these, 70.3% inhabited areas of unstable transmission and 29.7% in stable transmission. Among those exposed to stable risk, the vast majority were at low risk (93.39%) with the reminder at intermediate (6.6%) and high risk (0.01%). More people in western Indonesia lived in unstable rather than stable transmission zones. In contrast, fewer people in eastern Indonesia lived in unstable versus stable transmission areas.

Conclusion

While further feasibility assessments will be required, the immediate prospects for sustained control are good across much of the archipelago and medium term plans to transition to the pre-elimination phase are not unrealistic for P. falciparum. Endemicity in areas of Papua will clearly present the greatest challenge. This P. falciparum endemicity map allows malaria control agencies and their partners to comprehensively assess the region-specific prospects for reaching pre-elimination, monitor and evaluate the effectiveness of future strategies against this 2010 baseline and ultimately improve their evidence-based malaria control strategies.     

Refining the global spatial limits of dengue virus transmission by evidence-based consensus

Background

Dengue is a growing problem both in its geographical spread and in its intensity, and yet current global distribution remains highly uncertain. Challenges in diagnosis and diagnostic methods as well as highly variable national health systems mean no single data source can reliably estimate the distribution of this disease. As such, there is a lack of agreement on national dengue status among international health organisations. Here we bring together all available information on dengue occurrence using a novel approach to produce an evidence consensus map of the disease range that highlights nations with an uncertain dengue status.

Methods/Principal Findings

A baseline methodology was used to assess a range of evidence for each country. In regions where dengue status was uncertain, additional evidence types were included to either clarify dengue status or confirm that it is unknown at this time. An algorithm was developed that assesses evidence quality and consistency, giving each country an evidence consensus score. Using this approach, we were able to generate a contemporary global map of national-level dengue status that assigns a relative measure of certainty and identifies gaps in the available evidence.

Conclusion

The map produced here provides a list of 128 countries for which there is good evidence of dengue occurrence, including 36 countries that have previously been classified as dengue-free by the World Health Organization and/or the US Centers for Disease Control. It also identifies disease surveillance needs, which we list in full. The disease extents and limits determined here using evidence consensus, marks the beginning of a five-year study to advance the mapping of dengue virus transmission and disease risk. Completion of this first step has allowed us to produce a preliminary estimate of population at risk with an upper bound of 3.97 billion people. This figure will be refined in future work.     

Chorismate mutase/prephenate dehydratase from Escherichia coli K12. Effect of phenylalanine, NaCl and pH on the protein conformation.

The effects of phenylalanine, NaCl and pH on the conformation of chorismate mutase/prephenate dehydratase have been investigated, using measurements of far and near-ultraviolet circular dichroic spectra and ultraviolet difference spectra. At pH 8.2 in 20 mM Tris-Cl buffer the enzyme was found to contain 10-20% helix and 40-50% beta-structure. There was little or no change in these values on the addition of 1 mM phenylalanine (the allosteric effector) or 0.4 M NaCl or by decreasing the pH to 7.4. Both phenylalanine and NaCl caused significant changes in the conformation of the enzyme. The most prominent of these was the movement of a tryptophan residue into a more hydrophobic environment. There was also a slight perturbation of this tryptophan when the pH was decreased to 7.4. The conformational changes can explain sigmoidal kinetic behaviour observed previously [Gething et al. (1976) Eur. J. Biochem. 71, 317-325].     

Prioritising Infectious Disease Mapping

BackgroundIncreasing volumes of data and computational capacity afford unprecedented opportunities to scale up infectious disease (ID) mapping for public health uses. Whilst a large number of IDs show global spatial variation, comprehensive knowledge of these geographic patterns is poor. Here we use an objective method to prioritise mapping efforts to begin to address the large deficit in global disease maps currently available.Conclusions/SignificanceA quantitative, easily-updated and flexible framework for prioritising diseases is presented here. The study identifies a possible future strategy for those diseases where significant knowledge gaps remain, as well as recognising those where global mapping programs have already made significant progress. For many conditions, potential shared epidemiological information has yet to be exploited.     

Modeling Within-Host Effects of Drugs on Plasmodium falciparum Transmission and Prospects for Malaria Elimination

Achieving a theoretical foundation for malaria elimination will require a detailed understanding of the quantitative relationships between patient treatment-seeking behavior, treatment coverage, and the effects of curative therapies that also block Plasmodium parasite transmission to mosquito vectors. Here, we report a mechanistic, within-host mathematical model that uses pharmacokinetic (PK) and pharmacodynamic (PD) data to simulate the effects of artemisinin-based combination therapies (ACTs) on Plasmodium falciparum transmission. To contextualize this model, we created a set of global maps of the fold reductions that would be necessary to reduce the malaria R_C (i.e. its basic reproductive number under control) to below 1 and thus interrupt transmission. This modeling was applied to low-transmission settings, defined as having a R₀<10 based on 2010 data. Our modeling predicts that treating 93–98% of symptomatic infections with an ACT within five days of fever onset would interrupt malaria transmission for ∼91% of the at-risk population of Southeast Asia and ∼74% of the global at-risk population, and lead these populations towards malaria elimination. This level of treatment coverage corresponds to an estimated 81–85% of all infected individuals in these settings. At this coverage level with ACTs, the addition of the gametocytocidal agent primaquine affords no major gains in transmission reduction. Indeed, we estimate that it would require switching ∼180 people from ACTs to ACTs plus primaquine to achieve the same transmission reduction as switching a single individual from untreated to treated with ACTs. Our model thus predicts that the addition of gametocytocidal drugs to treatment regimens provides very small population-wide benefits and that the focus of control efforts in Southeast Asia should be on increasing prompt ACT coverage. Prospects for elimination in much of Sub-Saharan Africa appear far less favorable currently, due to high rates of infection and less frequent and less rapid treatment.     

Tree line identification from pollen data: beyond the limit?

Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen–vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line. Location Northern Canada (307 sites) and Alaska (316 sites). Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS‐based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of ‘correct’ versus ‘incorrect’ assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest‐cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed. Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over‐predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization. Main conclusions Corrected biomization should improve broad‐scale reconstructions of spatial patterns in forest/non‐forest vegetation mosaics and across climate‐sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake‐based systems.     

Quantifying Aggregated Uncertainty in Plasmodium falciparum Malaria Prevalence and Populations at Risk via Efficient Space-Time Geostatistical Joint Simulation

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty—the fidelity of predictions at each mapped pixel—but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.     

The expression of influenza virus hemagglutinin in the pancreatic beta cells of transgenic mice results in autoimmune diabetes

Insulin-dependent diabetes mellitus results from the autoimmune destruction of the insulin-producing beta cells of the pancreatic islets. The target antigen(s) involved in this immunopathological process has not been identified. Our strategy was to determine whether expression of a novel surface antigen by murine pancreatic beta cells would result in insulin-dependent diabetes mellitus. We have generated lines of transgenic mice (RIP-HA) that express the hemagglutinin of the A/Japan/305/57 strain of influenza virus on their insulin-producing beta cells. Hyperglycemia developed in mice derived from all three founders at a frequency varying from 13% to 27%, and was associated with lymphocytic infiltration of the islets and a humoral response against beta cell antigens, including hemagglutinin. These results suggest that the RIP-HA mice should provide a useful system in which to study the cellular interactions involved in the induction of self-tolerance and autoimmunity.