Circulating fragments of N-Terminal Pro-B-Type Natriuretic Peptides in plasma of heart failure patients

BACKGROUND: The use of nonstandardized N-terminal pro-B-type natriuretic peptide (NT-proBNP) assays can contribute to the misdiagnosis of heart failure (HF). Moreover, there is yet to be established a common consensus regarding the circulating forms of NT-proBNP being used in current assays. We aimed to characterize and quantify the various forms of NT-proBNP in the circulation of HF patients. METHODS: Plasma samples were collected from HF patients (n = 20) at rest and stored at -80 degrees C. NT-proBNP was enriched from HF patient plasma by use of immunoprecipitation followed by mass spectrometric analysis. Customized homogeneous sandwich AlphaLISA (R) immunoassays were developed and validated to quantify 6 fragments of NT-proBNP. RESULTS: Mass spectrometry identified the presence of several N- and C-terminally processed forms of circulating NT-proBNP, with physiological proteolysis between Pro2-Leu3, Leu3-Gly4, Pro6-Gly7, and Pro75-Arg76. Consistent with this result, AlphaLISA immunoassays demonstrated that antibodies targeting the extreme N or C termini measured a low apparent concentration of circulating NT-proBNP. The apparent circulating NT-proBNP concentration was increased with antibodies targeting nonglycosylated and nonterminal epitopes (P < 0.05). CONCLUSIONS: In plasma collected from HF patients, immunoreactive NT-proBNP was present as multiple N- and C-terminally truncated fragments of the full length NT-proBNP molecule. Immunodetection of NT-proBNP was significantly improved with the use of antibodies that did not target these terminal regions. These findings support the development of a next generation NT-proBNP assay targeting nonterminal epitopes as well as avoiding the central glycosylated region of this molecule. (c) 2013 American Association for Clinical Chemistry

Plant diversity predicts beta but not alpha diversity of soil microbes across grasslands worldwide

Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty-five 1 m2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

A communication model and partitioning algorithm for streaming applications for an embedded MPSoC

Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulated-annealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%.

Global burden of disease attributable to mental and substance use disorders : findings from the Global Burden of Disease Study 2010

Background We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010) to estimate the burden of disease attributable to mental and substance use disorders in terms of disability-adjusted life years (DALYs), years of life lost to premature mortality (YLLs), and years lived with disability (YLDs). Methods For each of the 20 mental and substance use disorders included in GBD 2010, we systematically reviewed epidemiological data and used a Bayesian meta-regression tool, DisMod-MR, to model prevalence by age, sex, country, region, and year. We obtained disability weights from representative community surveys and an internet-based survey to calculate YLDs. We calculated premature mortality as YLLs from cause of death estimates for 1980–2010 for 20 age groups, both sexes, and 187 countries. We derived DALYs from the sum of YLDs and YLLs. We adjusted burden estimates for comorbidity and present them with 95% uncertainty intervals. Findings In 2010, mental and substance use disorders accounted for 183·9 million DALYs (95% UI 153·5 million–216·7 million), or 7·4% (6·2–8·6) of all DALYs worldwide. Such disorders accounted for 8·6 million YLLs (6·5 million–12·1 million; 0·5% [0·4–0·7] of all YLLs) and 175·3 million YLDs (144·5 million–207·8 million; 22·9% [18·6–27·2] of all YLDs). Mental and substance use disorders were the leading cause of YLDs worldwide. Depressive disorders accounted for 40·5% (31·7–49·2) of DALYs caused by mental and substance use disorders, with anxiety disorders accounting for 14·6% (11·2–18·4), illicit drug use disorders for 10·9% (8·9–13·2), alcohol use disorders for 9·6% (7·7–11·8), schizophrenia for 7·4% (5·0–9·8), bipolar disorder for 7·0% (4·4–10·3), pervasive developmental disorders for 4·2% (3·2–5·3), childhood behavioural disorders for 3·4% (2·2–4·7), and eating disorders for 1·2% (0·9–1·5). DALYs varied by age and sex, with the highest proportion of total DALYs occurring in people aged 10–29 years. The burden of mental and substance use disorders increased by 37·6% between 1990 and 2010, which for most disorders was driven by population growth and ageing. Interpretation Despite the apparently small contribution of YLLs—with deaths in people with mental disorders coded to the physical cause of death and suicide coded to the category of injuries under self-harm—our findings show the striking and growing challenge that these disorders pose for health systems in developed and developing regions. In view of the magnitude of their contribution, improvement in population health is only possible if countries make the prevention and treatment of mental and substance use disorders a public health priority.

Towards coordinated multirobot missions for lunar sample collection in an unknown environment

In this paper, the recent results of the space project IMPERA are presented. The goal of IMPERA is the development of a multirobot planning and plan execution architecture with a focus on a lunar sample collection scenario in an unknown environment. We describe the implementation and verification of different modules that are integrated into a distributed system architecture. The modules include a mission planning approach for a multirobot system and modules for task and skill execution within a lunar use-case scenario. The skills needed for the test scenario include cooperative exploration and mapping strategies for an unknown environment, the localization and classification of sample containers using a novel approach of semantic perception, and the skill of transporting sample containers to a collection point using a mobile manipulation robot. Additionally, we present our approach of a reliable communication framework that can deal with communication loss during the mission. Several modules are tested within several experiments in the domain of planning and plan execution, communication, coordinated exploration, perception, and object transportation. An overall system integration is tested on a mission scenario experiment using three robots.

Accounting for management costs in sensitivity analyses of matrix population models

Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.

Cost-effective suppression and eradication of invasive predators

Introduced predators can have pronounced effects on naïve prey species; thus, predator control is often essential for conservation of threatened native species. Complete eradication of the predator, although desirable, may be elusive in budget-limited situations, whereas predator suppression is more feasible and may still achieve conservation goals. We used a stochastic predator-prey model based on a Lotka-Volterra system to investigate the cost-effectiveness of predator control to achieve prey conservation. We compared five control strategies: immediate eradication, removal of a constant number of predators (fixed-number control), removal of a constant proportion of predators (fixed-rate control), removal of predators that exceed a predetermined threshold (upper-trigger harvest), and removal of predators whenever their population falls below a lower predetermined threshold (lower-trigger harvest). We looked at the performance of these strategies when managers could always remove the full number of predators targeted by each strategy, subject to budget availability. Under this assumption immediate eradication reduced the threat to the prey population the most. We then examined the effect of reduced management success in meeting removal targets, assuming removal is more difficult at low predator densities. In this case there was a pronounced reduction in performance of the immediate eradication, fixed-number, and lower-trigger strategies. Although immediate eradication still yielded the highest expected minimum prey population size, upper-trigger harvest yielded the lowest probability of prey extinction and the greatest return on investment (as measured by improvement in expected minimum population size per amount spent). Upper-trigger harvest was relatively successful because it operated when predator density was highest, which is when predator removal targets can be more easily met and the effect of predators on the prey is most damaging. This suggests that controlling predators only when they are most abundant is the "best" strategy when financial resources are limited and eradication is unlikely. © 2008 Society for Conservation Biology.

Making robust decisions for conservation with restricted money and knowledge

1. In conservation decision-making, we operate within the confines of limited funding. Furthermore, we often assume particular relationships between management impact and our investment in management. The structure of these relationships, however, is rarely known with certainty - there is model uncertainty. We investigate how these two fundamentally limiting factors in conservation management, money and knowledge, impact optimal decision-making. 2. We use information-gap decision theory to find strategies for maximizing the number of extant subpopulations of a threatened species that are most immune to failure due to model uncertainty. We thus find a robust framework for exploring optimal decision-making. 3. The performance of every strategy decreases as model uncertainty increases. 4. The strategy most robust to model uncertainty depends not only on what performance is perceived to be acceptable but also on available funding and the time horizon over which extinction is considered. 5. Synthesis and applications. We investigate the impact of model uncertainty on robust decision-making in conservation and how this is affected by available conservation funding. We show that subpopulation triage can be a natural consequence of robust decision-making. We highlight the need for managers to consider triage not as merely giving up, but as a tool for ensuring species persistence in light of the urgency of most conservation requirements, uncertainty and the poor state of conservation funding. We illustrate this theory by a specific application to allocation of funding to reduce poaching impact on the Sumatran tiger Panthera tigris sumatrae in Kerinci Seblat National Park. © 2008 The Authors.

Subpopulation triage: How to allocate conservation effort among populations

Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species. © 2008 Society for Conservation Biology.

Using conservation evidence to guide management

Almost 10 years ago, Pullin and Knight (2001) called for an “effectiveness revolution in conservation” to be enabled by the systematic evaluation of evidence for conservation decision making. Drawing from the model used in clinicalmedicine, they outlined the concept of “evidencebased conservation” in which existing information, or evidence, from relevant and rigorous research is compiled and analyzed in a systematic manner to inform conservation actions (Cochrane 1972). The promise of evidencebased conservation has generated significant interest; 25 systematic reviews have been completed since 2004 and dozens are underway (Collaboration for Environmental Evidence 2010). However we argue that an “effectiveness revolution” (Pullin & Knight 2001) in conservation will not be possible unless mechanisms are devised for incorporating the growing evidence base into decision frameworks. For conservation professionals to accomplish the missions of their organizations they must demonstrate that their actions actually achieve objectives (Pullin & Knight 2009). Systematic evaluation provides a framework for objectively evaluating the effectiveness of actions. To leverage the benefit of these evaluations, we need resource-allocation systems that are responsive to their outcomes. The allocation of conservation resources is often the product of institutional priorities or reliance on intuition (Sutherland et al. 2004; Pullin & Knight 2005; Cook et al. 2010). We highlight the NICE technologyappraisal process because it provides an example of formal integration of systematic-evidence evaluation with provision of guidance for action. The transparent process, which clearly delineates costs and benefits of each alternative action, could also provide the public with new insight into the environmental effects of different decisions. This insight could stimulate a wider discussion about investment in conservation by demonstrating how changes in funding might affect the probability of achieving conservation objectives. ©2010 Society for Conservation Biology

The Why, What, and How of Global Biodiversity Indicators Beyond the 2010 Target

The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well-developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators. ©2010 Society for Conservation Biology.