Magneto-optical Kerr Effect Studies of Square Artificial Spin Ice

We report a magneto-optical Kerr effect study of the collective magnetic response of artificial square spin ice, a lithographically-defined array of single-domain ferromagnetic islands. We find that the anisotropic inter-island interactions lead to a non-monotonic angular dependence of the array coercive field. Comparisons with micromagnetic simulations indicate that the two perpendicular sublattices exhibit distinct responses to island edge roughness, which clearly influence the magnetization reversal process. Furthermore, such comparisons demonstrate that disorder associated with roughness in the island edges plays a hitherto unrecognized but essential role in the collective behavior of these systems.Comment: Physical Review B, Rapid Communications (in press

Vacuolar iron stores gated by NRAMP3 and NRAMP4 are the primary source of iron in germinating seeds

During seed germination, iron (Fe) stored in vacuoles is exported by the redundant NRAMP3 and NRAMP4 transporter proteins. A double nramp3 nramp4 mutant is unable to mobilize Fe stores and does not develop in the absence of external Fe. We used RNA sequencing to compare gene expression in nramp3 nramp4 and wild type during germination and early seedling development. Even though sufficient Fe was supplied, the Fe-responsive transcription factors bHLH38, 39, 100, and 101 and their downstream targets FRO2 and IRT1 mediating Fe uptake were strongly upregulated in the nramp3 nramp4 mutant. Activation of the Fe deficiency response was confirmed by increased ferric chelate reductase activity in the mutant. At early stages, genes important for chloroplast redox control (FSD1 and SAPX), Fe homeostasis (FER1 and SUFB), and chlorophyll metabolism (HEMA1 and NYC1) were downregulated, indicating limited Fe availability in plastids. In contrast, expression of FRO3, encoding a ferric reductase involved in Fe import into the mitochondria, was maintained, and Fe-dependent enzymes in the mitochondria were unaffected in nramp3 nramp4. Together, these data show that a failure to mobilize Fe stores during germination triggered Fe deficiency responses and strongly affected plastids, but not mitochondria

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

The use of mobile phone data for the estimation of the travel patterns and imported Plasmodium falciparum rates among Zanzibar residents

Background: malaria endemicity in Zanzibar has reached historically low levels, and the epidemiology of malaria transmission is in transition. To capitalize on these gains, Zanzibar has commissioned a feasibility assessment to help inform on whether to move to an elimination campaign. Declining local transmission has refocused attention on imported malaria. Recent studies have shown that anonimized mobile phone records provide a valuable data source for characterizing human movements without compromising the privacy of phone users. Such movement data in combination with spatial data on P. falciparum endemicity provide a way of characterizing the patterns of parasite carrier movements and the rates of malaria importation, which have been used as part of the malaria elimination feasibility assessment for the islands of Zanzibar. Data and methods: records encompassing three months of complete mobile phone usage for the period October-December 2008 were obtained from the Zanzibar Telecom (Zantel) mobile phone network company, the principal provider on the islands of Zanzibar. The data included the dates of all phone usage by 770,369 individual anonymous users. Each individual call and message was spatially referenced to one of six areas: Zanzibar and five mainland Tanzania regions. Information on the numbers of Zanzibar residents travelling to the mainland, locations visited and lengths of stay were extracted. Spatial and temporal data on P. falciparum transmission intensity and seasonality enabled linkage of this information to endemicity exposure and, motivated by malaria transmission models, estimates of the expected patterns of parasite importation to be made. Results: over the three month period studied, 88% of users made calls that were routed only through masts on Zanzibar, suggesting that no long distance travel was undertaken by this group. Of those who made calls routed through mainland masts the vast majority of trips were estimated to be of less than five days in length, and to the Dar Es Salaam Zantel-defined region. Though this region covered a wide range of transmission intensities, data on total infection numbers in Zanzibar combined with mathematical models enabled informed estimation of transmission exposure and imported infection numbers. These showed that the majority of trips made posed a relatively low risk for parasite importation, but risk groups visiting higher transmission regions for extended periods of time could be identified. Conclusion: anonymous mobile phone records provide valuable information on human movement patterns in areas that are typically data-sparse. Estimates of human movement patterns from Zanzibar to mainland Tanzania suggest that imported malaria risk from this group is heterogeneously distributed; a few people account for most of the risk for imported malaria. In combination with spatial data on malaria endemicity and transmission models, movement patterns derived from phone records can inform on the likely sources and rates of malaria importation. Such information is important for assessing the feasibility of malaria elimination and planning an elimination campaign

The Limits and Intensity of Plasmodium falciparum Transmission: Implications for Malaria Control and Elimination Worldwide

Combining extensive surveillance and climate data, as well as biological characteristics of Anopheles mosquitoes, Robert Snow and colleagues create a global map of risk for P. falciparum malaria

Open Science principles for accelerating trait-based science across the Tree of Life

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

A new world malaria map: Plasmodium falciparum endemicity in 2010

Background: transmission intensity affects almost all aspects of malaria epidemiology and the impact of malaria on human populations. Maps of transmission intensity are necessary to identify populations at different levels of risk and to evaluate objectively options for disease control. To remain relevant operationally, such maps must be updated frequently. Following the first global effort to map Plasmodium falciparum malaria endemicity in 2007, this paper describes the generation of a new world map for the year 2010. This analysis is extended to provide the first global estimates of two other metrics of transmission intensity for P. falciparum that underpin contemporary questions in malaria control: the entomological inoculation rate (PfEIR) and the basic reproductive number (PfR). Methods: annual parasite incidence data for 13,449 administrative units in 43 endemic countries were sourced to define the spatial limits of P. falciparum transmission in 2010 and 22,212 P. falciparum parasite rate (PfPR) surveys were used in a model-based geostatistical (MBG) prediction to create a continuous contemporary surface of malaria endemicity within these limits. A suite of transmission models were developed that link PfPR to PfEIR and PfR and these were fitted to field data. These models were combined with the PfPR map to create new global predictions of PfEIR and PfR. All output maps included measured uncertainty. Results: an estimated 1.13 and 1.44 billion people worldwide were at risk of unstable and stable P. falciparum malaria, respectively. The majority of the endemic world was predicted with a median PfEIR of less than one and a median PfRc of less than two. Values of either metric exceeding 10 were almost exclusive to Africa. The uncertainty described in both PfEIR and PfR was substantial in regions of intense transmission. Conclusions: the year 2010 has a particular significance as an evaluation milestone for malaria global health policy. The maps presented here contribute to a rational basis for control and elimination decisions and can serve as a baseline assessment as the global health community looks ahead to the next series of milestones targeted at 20

The effects of spatial population dataset choice on estimates of population at risk of disease

Background: The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example.Methods: The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets.Results: The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets.Conclusions: Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. © 2011 Tatem et al; licensee BioMed Central Ltd.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

The International Limits and Population at Risk of Plasmodium vivax Transmission in 2009

Growing evidence shows that Plasmodium vivax malaria is clinically less benign than has been commonly believed. In addition, it is the most widely distributed species of human malaria and is likely to cause more illness in certain regions than the more extensively studied P. falciparum malaria. Understanding where P. vivax transmission exists and measuring the number of people who live at risk of infection is a fundamental first step to estimating the global disease toll. The aim of this paper is to generate a reliable map of the worldwide distribution of this parasite and to provide an estimate of how many people are exposed to probable infection. A geographical information system was used to map data on the presence of P. vivax infection and spatial information on climatic conditions that impede transmission (low ambient temperature and extremely arid environments) in order to delineate areas where transmission was unlikely to take place. This map was combined with population distribution data to estimate how many people live in these areas and are, therefore, exposed to risk of infection by P. vivax malaria. The results show that 2.85 billion people were exposed to some level of risk of transmission in 2009

Estimating the Global Clinical Burden of Plasmodium falciparum Malaria in 2007

Simon Hay and colleagues derive contemporary estimates of the global clinical burden of Plasmodium falciparum malaria (the deadliest form of malaria) using cartography-based techniques