Classification of the Universe of Immune Epitope Literature: Representation and Knowledge Gaps

Background

A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continually updated by monitoring PubMed for new, potentially relevant references.

Methodology

Herein we detail the classification of all epitope-specific literature in over 100 different immunological domains representing Infectious Diseases and Microbes, Autoimmunity, Allergy, Transplantation and Cancer. The relative number of references in each category reflects past and present areas of research on immune reactivities. In addition to describing the overall landscape of data distribution, this particular characterization of the epitope reference data also allows for the exploration of possible correlations with global disease morbidity and mortality data.

Conclusions/Significance

While in most cases diseases associated with high morbidity and mortality rates were amongst the most studied, a number of high impact diseases such as dengue, Schistosoma, HSV-2, B. pertussis and Chlamydia trachoma, were found to have very little coverage. The data analyzed in this fashion represents the first estimate of how reported immunological data corresponds to disease-related morbidity and mortality, and confirms significant discrepancies in the overall research foci versus disease burden, thus identifying important gaps to be pursued by future research. These findings may also provide a justification for redirecting a portion of research funds into some of the underfunded, critical disease areas.     

Camel exposure and knowledge about MERS-CoV among Australian Hajj pilgrims in 2014

正Dear Editor,Middle East respiratory syndrome coronavirus(MERS-CoV)affected 1,621 patients worldwide,with a 36%mortality rate by the end of 2015.The highest number of cases was recorded in Saudi Arabia,the location for Hajj     

Partitioning of ecosystem respiration of CO2 released during land‐use transition from temperate agricultural grassland to Miscanthus × giganteus

Conversion of large areas of agricultural grassland is inevitable if European and UK domestic production of biomass is to play a significant role in meeting demand. Understanding the impact of these land‐use changes on soil carbon cycling and stocks depends on accurate predictions from well‐parameterized models. Key considerations are cultivation disturbance and the effect of autotrophic root input stimulation on soil carbon decomposition under novel biomass crops. This study presents partitioned parameters from the conversion of semi‐improved grassland to Miscanthus bioenergy production and compares the contribution of autotrophic and heterotrophic respiration to overall ecosystem respiration of CO₂ in the first and second years of establishment. Repeated measures of respiration from within and without root exclusion collars were used to produce time‐series model integrations separating live root inputs from decomposition of grass residues ploughed in with cultivation of the new crop. These parameters were then compared to total ecosystem respiration derived from eddy covariance sensors. Average soil surface respiration was 13.4% higher in the second growing season, increasing from 2.9 to 3.29 g CO₂‐C m^?2 day^?1. Total ecosystem respiration followed a similar trend, increasing from 4.07 to 5.4 g CO₂‐C m^?2 day^?1. Heterotrophic respiration from the root exclusion collars was 32.2% lower in the second growing season at 1.20 g CO₂‐C m^?2 day^?1 compared to the previous year at 1.77 g CO₂‐C m^?2 day^?1. Of the total respiration flux over the two‐year time period, aboveground autotrophic respiration plus litter decomposition contributed 38.46% to total ecosystem respiration while belowground autotrophic respiration and stimulation by live root inputs contributed 46.44% to soil surface respiration. This figure is notably higher than mean figures for nonforest soils derived from the literature and demonstrates the importance of crop‐specific parameterization of respiration models.     

Using structured decision‐making to set restoration objectives when multiple values and preferences exist

Achieving global targets for restoring native vegetation cover requires restoration projects to identify and work toward common management objectives. This is made challenging by the different values held by concerned stakeholders, which are not often accounted for. Additionally, restoration is time‐dependent and yet there is often little explicit acknowledgment of the time frames required to achieve outcomes. Here, we argue that explicitly incorporating value and time considerations into stated objectives would help to achieve restoration goals. We reviewed the peer‐reviewed literature on restoration of terrestrial vegetation and found that while there is guidance on how to identify and account for stakeholder values and time considerations, there is little evidence these are being incorporated into decision‐making processes. In this article, we explore how a combination of stakeholder surveys and workshops can be used within a structured decision‐making framework to facilitate the integration of diverse stakeholder values and time frame considerations to set restoration objectives. We demonstrate this approach with a case of restoration decision‐making at a regional scale (southeast Queensland, Australia) with a view to this experience supporting similar restoration projects elsewhere.     

Incorporating climate change into ecosystem service assessments and decisions: a review

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.     

Improved Coral Population Estimation Reveals Trends at Multiple Scales on Australia’s Great Barrier Reef

The global erosion of biodiversity presents unique challenges for identifying major changes in population dynamics, establishing their causes, and managing and conserving affected ecosystems at broad spatial scales. Adaptive learning approaches connecting different spatial scales through the transfer of hierarchical information are powerful tools to address such challenges. Here, we use a Semi-Parametric Bayesian Hierarchical (SPa-BaH) model to estimate coral cover trajectories using 16 years of a broad-scale survey on Australia’s Great Barrier Reef (GBR). The spatiotemporal variability of coral populations has been considered by separating three-tiered spatial scales and allowing for alternating phases of increasing and decreasing in the estimation of their trajectories. Model estimates revealed coral cover trajectories that were highly variable according to location but that fairly consistently declined at a regional spatial scale. Notwithstanding this general trend, individual reefs within subregions in the central part of the GBR often displayed different trajectory types between sites separated by only a few hundred meters. These coral dynamics were also associated with reduced recovery rates in the Cairns and Swain subregions. Our study highlights the importance of accounting for local variation in coral cover when estimating the spatiotemporal trends in coral cover trajectories, in this case, at the GBR scale. By retaining information at different hierarchical spatial scales, our SPa-BaH model supports better estimation of large-scale coral cover trajectories. The quantitative approaches developed here can also be applied to other species with complex dynamics thereby enhancing estimations of their trajectories at local- and larger-scales and options for their management.     

CD209 genetic polymorphism and tuberculosis disease

Background

Tuberculosis causes significant morbidity and mortality worldwide, especially in sub-Saharan Africa. DC-SIGN, encoded by CD209, is a receptor capable of binding and internalizing Mycobacterium tuberculosis. Previous studies have reported that the CD209 promoter single nucleotide polymorphism (SNP)-336A/G exerts an effect on CD209 expression and is associated with human susceptibility to dengue, HIV-1 and tuberculosis in humans. The present study investigates the role of the CD209 -336A/G variant in susceptibility to tuberculosis in a large sample of individuals from sub-Saharan Africa.

Methods and Findings

A total of 2,176 individuals enrolled in tuberculosis case-control studies from four sub-Saharan Africa countries were genotyped for the CD209 -336A/G SNP (rs4804803). Significant overall protection against pulmonary tuberculosis was observed with the -336G allele when the study groups were combined (n = 914 controls vs. 1262 cases, Mantel-Haenszel 2x2 χ² = 7.47, P = 0.006, odds ratio = 0.86, 95%CI 0.77–0.96). In addition, the patients with -336GG were associated with a decreased risk of cavitory tuberculosis, a severe form of tuberculosis disease (n = 557, Pearson''s 2×2 χ² = 17.34, P = 0.00003, odds ratio = 0.42, 95%CI 0.27–0.65). This direction of association is opposite to a previously observed result in a smaller study of susceptibility to tuberculosis in a South African Coloured population, but entirely in keeping with the previously observed protective effect of the -336G allele.

Conclusion

This study finds that the CD209 -336G variant allele is associated with significant protection against tuberculosis in individuals from sub-Saharan Africa and, furthermore, cases with -336GG were significantly less likely to develop tuberculosis-induced lung cavitation. Previous in vitro work demonstrated that the promoter variant -336G allele causes down-regulation of CD209 mRNA expression. Our present work suggests that decreased levels of the DC-SIGN receptor may therefore be protective against both clinical tuberculosis in general and cavitory tuberculosis disease in particular. This is consistent with evidence that Mycobacteria can utilize DC-SIGN binding to suppress the protective pro-inflammatory immune response.     

Protecting biodiversity when money matters: maximizing return on investment

Background

Conventional wisdom identifies biodiversity hotspots as priorities for conservation investment because they capture dense concentrations of species. However, density of species does not necessarily imply conservation ‘efficiency’. Here we explicitly consider conservation efficiency in terms of species protected per dollar invested.

Methodology/Principal Findings

We apply a dynamic return on investment approach to a global biome and compare it with three alternate priority setting approaches and a random allocation of funding. After twenty years of acquiring habitat, the return on investment approach protects between 32% and 69% more species compared to the other priority setting approaches. To correct for potential inefficiencies of protecting the same species multiple times we account for the complementarity of species, protecting up to three times more distinct vertebrate species than alternate approaches.

Conclusions/Significance

Incorporating costs in a return on investment framework expands priorities to include areas not traditionally highlighted as priorities based on conventional irreplaceability and vulnerability approaches.     

Optimal Dynamic Allocation of Conservation Funding Among Priority Regions

The optimal allocation of conservation resources between biodiverse conservation regions has generally been calculated using stochastic dynamic programming, or using myopic heuristics. These solutions are hard to interpret and may not be optimal. To overcome these two limitations, this paper approaches the optimal conservation resource allocation problem using optimal control theory. A solution using Pontryagin’s maximum principle provides novel insight into the general properties of efficient conservation resource allocation strategies, and allows more extensive testing of the performance of myopic heuristics. We confirmed that a proposed heuristic (minimize short-term loss) yields near-optimal results in complex allocation situations, and found that a qualitative allocation feature observed in previous analyses (bang-bang allocation) is a general property of the optimal allocation strategy.