Plant phenology supports the multi-emergence hypothesis for ebola spillover events

Ebola virus disease outbreaks in animals (including humans and great apes) start with sporadic host switches from unknown reservoir species. The factors leading to such spillover events are little explored. Filoviridae viruses have a wide range of natural hosts and are unstable once outside hosts. Spillover events, which involve the physical transfer of viral particles across species, could therefore be directly promoted by conditions of host ecology and environment. In this report we outline a proof of concept that temporal fluctuations of a set of ecological and environmental variables describing the dynamics of the host ecosystem are able to predict such events of Ebola virus spillover to humans and animals. We compiled a dataset of climate and plant phenology variables and Ebola virus disease spillovers in humans and animals. We identified critical biotic and abiotic conditions for spillovers via multiple regression and neural networks based time series regression. Phenology variables proved to be overall better predictors than climate variables. African phenology variables are not yet available as a comprehensive online resource. Given the likely importance of phenology for forecasting the likelihood of future Ebola spillover events, our results highlight the need for cost-effective transect surveys to supply phenology data for predictive modelling efforts

Hamiltonian Formalism in Quantum Mechanics

Heisenberg motion equations in Quantum mechanics can be put into the Hamilton form. The difference between the commutator and its principal part, the Poisson bracket, can be accounted for exactly. Canonical transformations in Quantum mechanics are not, or at least not what they appear to be; their properties are formulated in a series of Conjectures

Toward a protocol for quantifying the greenhouse gas balance and identifying mitigation options in smallholder farming systems

Globally, agriculture is directly responsible for 14% of annual greenhouse gas (GHG) emissions and induces an additional 17% through land use change, mostly in developing countries (Vermeulen et al 2012). Agricultural intensification and expansion in these regions is expected to catalyze the most significant relative increases in agricultural GHG emissions over the next decade (Smith et al 2008, Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa and Asia are predominately managed by smallholders, with 80% of land holdings smaller than ten hectares (FAO 2012). One can therefore posit that smallholder farming significantly impacts the GHG balance of these regions today and will continue to do so in the near future. However, our understanding of the effect smallholder farming has on the Earth's climate system is remarkably limited. Data quantifying existing and reduced GHG emissions and removals of smallholder production systems are available for only a handful of crops, livestock, and agroecosystems (Herrero et al 2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteen studies of nitrous oxide emissions from soils have taken place in sub-Saharan Africa, leaving the rate of emissions virtually undocumented. Due to a scarcity of data on GHG sources and sinks, most developing countries currently quantify agricultural emissions and reductions using IPCC Tier 1 emissions factors. However, current Tier 1 emissions factors are either calibrated to data primarily derived from developed countries, where agricultural production conditions are dissimilar to that in which the majority of smallholders operate, or from data that are sparse or of mixed quality in developing countries (IPCC 2006). For the most part, there are insufficient emissions data characterizing smallholder agriculture to evaluate the level of accuracy or inaccuracy of current emissions estimates. Consequentially, there is no reliable information on the agricultural GHG budgets for developing economies. This dearth of information constrains the capacity to transition to low-carbon agricultural development, opportunities for smallholders to capitalize on carbon markets, and the negotiating position of developing countries in global climate policy discourse. Concerns over the poor state of information, in terms of data availability and representation, have fueled appeals for new approaches to quantifying GHG emissions and removals from smallholder agriculture, for both existing conditions and mitigation interventions (Berry and Ryan 2013, Olander et al 2013). Considering the dependence of quantification approaches on data and the current data deficit for smallholder systems, it is clear that in situ measurements must be a core part of initial and future strategies to improve GHG inventories and develop mitigation measures for smallholder agriculture. Once more data are available, especially for farming systems of high priority (e.g., those identified through global and regional rankings of emission hotspots or mitigation leverage points), better cumulative estimates and targeted actions will become possible. Greenhouse gas measurements in agriculture are expensive, time consuming, and error prone. These challenges are exacerbated by the heterogeneity of smallholder systems and landscapes and the diversity of methods used. Concerns over methodological rigor, measurement costs, and the diversity of approaches, coupled with the demand for robust information suggest it is germane for the scientific community to establish standards of measurements—'a protocol'—for quantifying GHG emissions from smallholder agriculture. A standard protocol for use by scientists and development organizations will help generate consistent, comparable, and reliable data on emissions baselines and allow rigorous comparisons of mitigation options. Besides enhancing data utility, a protocol serves as a benchmark for non-experts to easily assess data quality. Obviously many such protocols already exist (e.g., GraceNet, Parkin and Venterea 2010). None, however, account for the diversity and complexity of smallholder agriculture, quantify emissions and removals from crops, livestock, and biomass together to calculate the net balance, or are adapted for the research environment of developing countries; conditions that warrant developing specific methods. Here we summarize an approach being developed by the Consultative Group on International Agricultural Research's (CGIAR) Climate Change, Agriculture, and Food Security Program (CCAFS) and partners. The CGIAR-CCAFS smallholder GHG quantification protocol aims to improve quantification of baseline emission levels and support mitigation decisions. The protocol introduces five novel quantification elements relevant for smallholder agriculture (figure 1). First, it stresses the systematic collection of 'activity data' to describe the type, distribution, and extent of land management activities in landscapes cultivated by smallholder. Second, it advocates an informed sampling approach that concentrates measurement activities on emission hotspots and leverage points to capture heterogeneity and account for the diversity and complexity of farming activities. Third, it quantifies emissions at multiple spatial scales, whole-farm and landscape, to provide information targeted to household and communities decisions. Fourth, it encourages GHG research to document farm productivity and economics in addition to emissions, in recognition of the importance of agriculture to livelihoods. Fifth, it develops cost-differentiated measurement solutions that optimize the relationships among scale, cost, and accuracy. Each of the five innovations is further described in the main article

A systematic review of factors influencing treatment adherence in chronic inflammatory skin disease – strategies for optimizing treatment outcome

Adherence describes how a patient follows a medical regime recommended by a healthcare provider. Poor treatment adherence represents a complex and challenging problem of international healthcare systems, as it has a substantial impact on clinical outcomes and patient safety and constitutes an important financial burden. Since it is one of the most common causes of treatment failure, it is extremely important for physicians to reliably distinguish between non‐adherence and non‐response. This systematic review aims to summarize the current literature on treatment adherence in dermatology, focusing on chronic inflammatory skin diseases such as psoriasis, atopic dermatitis and acne. A systematic literature search was performed using the PubMed Database, including articles from 2008 to 2018. Low treatment adherence is a multidimensional phenomenon defined by the interplay of numerous factors and should under no circumstances be considered as the patient's fault alone. Factors influencing treatment adherence in dermatology include patient characteristics and beliefs, treatment efficacy and duration, administration routes, disease chronicity and the disease itself. Moreover, the quality of the physician‐patient relationship including physician‐time available for the patient plays an important role. Understanding patients’ adherence patterns and the main drivers of non‐adherence creates opportunities to improve adherence in the future. Strategies to increase treatment adherence range from reminder programs to simplifying prescriptions or educational interventions. Absolute adherence to treatment may not be realistically achievable, but efforts need to be made to raise awareness in order to maximize adherence as far as possible

Limits of agricultural greenhouse gas calculators to predict soil N2O and CH4 fluxes in tropical agriculture

Acknowledgements This work was undertaken as part of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), which is a strategic partnership of CGIAR and Future Earth. This research was carried out with funding by the European Union (EU) and with technical support from the International Fund for Agricultural Development (IFAD). The UN FAO Mitigation of Climate Change in Agriculture (MICCA) Programme funded data collection in Kenya and Tanzania. The views expressed in the document cannot be taken to reflect the official opinions of CGIAR, Future Earth, or donors. We thank Louis Bockel of the UN FAO Agricultural Development Economics Division (ESA) for his comments on an earlier draft of the manuscript.Peer reviewedPublisher PD

Institutional innovations in African smallholder carbon projects

This paper synthesizes the insights of six African agricultural carbon project case studies and identifies institutional innovations among these projects that are contributing to long-term project success while maximizing benefits and minimizing risk for participating farmers. We review project organization and management, the structure and role of community groups within the projects, costs and benefits for managers and farmers, strategies to manage risks to farmers, and efforts to support women’s participation. Projects have developed organizational systems for financial management, agricultural extension, and carbon monitoring. All of these were managed by project management entities, with farmers implementing practices and supporting monitoring systems. Most projects engaged farmers in small groups and larger clusters of groups, which enabled broad participation, efficient contracting, timely communication, provision of extension services, benefit-sharing, and gender-focused activities. Direct carbon payments to farmers were low. Consequently projects needed to manage expectations around benefits carefully, support more efficient systems of aggregation and ensure non-cash benefits for farmers. Managing power dynamics within and among farmer groups was a significant challenge to ensuring equitable decision-making and participation. Mechanisms for settling conflict over land and benefits were also critical. We present action research questions that emerged from the first phase of this work and discuss the future of the initiative. Case studies about each agriculture carbon project from which our analysis is drawn can be downloaded along with the main report

Polyphyly of non-bioluminescent Vibrio fischeri sharing a lux-locus deletion

available in PMC 2013 May 16This study reports the first description and molecular characterization of naturally occurring, non-bioluminescent strains of Vibrio fischeri. These ‘dark’V. fischeri strains remained non-bioluminescent even after treatment with both autoinducer and aldehyde, substrate additions that typically maximize light production in dim strains of luminous bacteria. Surprisingly, the entire lux locus (eight genes) was absent in over 97% of these dark V. fischeri strains. Although these strains were all collected from a Massachusetts (USA) estuary in 2007, phylogenetic reconstructions allowed us to reject the hypothesis that these newly described non-bioluminescent strains exhibit monophyly within the V. fischeri clade. These dark strains exhibited a competitive disadvantage against native bioluminescent strains when colonizing the light organ of the model V. fischeri host, the Hawaiian bobtail squid Euprymna scolopes. Significantly, we believe that the data collected in this study may suggest the first observation of a functional, parallel locus-deletion event among independent lineages of a non-pathogenic bacterial species.National Institutes of Health (U.S.) (NIH Molecular Biosciences (5T32GM007215-35))National Institutes of Health (U.S.) (NIH Microbes in Health and Disease, training grant (2T32AI055397-07))Gordon and Betty Moore FoundationBroad Institute of MIT and Harvard (SPARC programme)National Science Foundation (U.S.) (NSF IOS 0841507)National Institutes of Health (U.S.) (NIH R01 RR12294)National Science Foundation (U.S.) (NSF Microbial Systems in the Biosphere programme)Woods Hole Center for Oceans & Human Healt

Algebraic Quantum Theory on Manifolds: A Haag-Kastler Setting for Quantum Geometry

Motivated by the invariance of current representations of quantum gravity under diffeomorphisms much more general than isometries, the Haag-Kastler setting is extended to manifolds without metric background structure. First, the causal structure on a differentiable manifold M of arbitrary dimension (d+1>2) can be defined in purely topological terms, via cones (C-causality). Then, the general structure of a net of C*-algebras on a manifold M and its causal properties required for an algebraic quantum field theory can be described as an extension of the Haag-Kastler axiomatic framework. An important application is given with quantum geometry on a spatial slice within the causally exterior region of a topological horizon H, resulting in a net of Weyl algebras for states with an infinite number of intersection points of edges and transversal (d-1)-faces within any neighbourhood of the spatial boundary S^2.Comment: 15 pages, Latex; v2: several corrections, in particular in def. 1 and in sec.