Neonatal Sepsis due to Coagulase-Negative Staphylococci

Neonates, especially those born prematurely, are at high risk of morbidity and mortality from sepsis. Multiple factors, including prematurity, invasive life-saving medical interventions, and immaturity of the innate immune system, put these infants at greater risk of developing infection. Although advanced neonatal care enables us to save even the most preterm neonates, the very interventions sustaining those who are hospitalized concurrently expose them to serious infections due to common nosocomial pathogens, particularly coagulase-negative staphylococci bacteria (CoNS). Moreover, the health burden from infection in these infants remains unacceptably high despite continuing efforts. In this paper, we review the epidemiology, immunological risk factors, diagnosis, prevention, treatment, and outcomes of neonatal infection due to the predominant neonatal pathogen CoNS

Whole-farm yield map datasets – data validation for exploring spatiotemporal yield and economic stability

CONTEXT: Statistical methods used for delineation of field management zones and yield stability are frequently only applied to relatively small areas, with few studies performing rotational, whole-farm economic spatiotemporal appraisals. To enable accurate economic analysis, yield map datasets must contain minimal errors while cleaning procedures are often used to remove errors, it is rare that cleaned data is validated before its application. OBJECTIVE: The objective of this study was to process, validate and combine spatial statistical approaches for a rotational yield map dataset from a whole-farm across 7 crops in a winter wheat based rotation. Developing a framework for using validated yield map datasets to support precision agriculture techniques that are applicable for farm-level decision making. METHODS: The rotational completeness of a 10 year combine yield map dataset for a 435 ha farm in Eastern England was assessed. The dataset was cleaned statistically, and its accuracy assessed by comparison with recorded yields from trailer weigh cells. The cleaned, validated, and corrected yield map dataset was used to identify management zones across the whole farm using fuzzy clustering. The temporal stability of management zones and economic performance across the rotation was also assessed. RESULTS AND DISSCUSION: Data cleaning methods removed 16% of data points, improving the degree of spatial correlation within the individual yield maps. Independent validation demonstrated varied accuracy of yield maps from combine harvester data and errors in wheat ranged from 0.53 to 1.53 t/ha RMSE. These errors have implications for researchers using combine yield data to develop and validate precision agriculture technologies. This data set required correction before yield data can be applied with confidence for on-farm decision making. Compared to the zones with the highest margin in each field, 34% of zones had an average annual margin loss of >£100 ha. The temporal stability of the resulting management zones also varied. Areas with the lowest economic performance and greatest yield stability across years will potentially see the greatest economic and environmental benefits from precision agriculture techniques. SIGNIFICANCE: The accuracy of combine yield map data should not be assumed. The application of these datasets, including for the identification of management zones or in developing precision agriculture techniques should attempt to address this through data cleaning and validation procedures. Only then should it be used for on farm decision making, such as identifying areas with the most economic benefit by applying precision agriculture tools such as variable rate nutrient applications.This work was supported by the UK Natural Environment Research Council through the CENTA Doctoral Training Partnership [NERC Ref: NE/L002493/1], together with the AHDB Strategic Cereal Farm East program PR: 2151003

Whole-farm yield map datasets – Data validation for exploring spatiotemporal yield and economic stability

CONTEXT Statistical methods used for delineation of field management zones and yield stability are frequently only applied to relatively small areas, with few studies performing rotational, whole-farm economic spatiotemporal appraisals. To enable accurate economic analysis, yield map datasets must contain minimal errors while cleaning procedures are often used to remove errors, it is rare that cleaned data is validated before its application. OBJECTIVE The objective of this study was to process, validate and combine spatial statistical approaches for a rotational yield map dataset from a whole-farm across 7 crops in a winter wheat based rotation. Developing a framework for using validated yield map datasets to support precision agriculture techniques that are applicable for farm-level decision making. METHODS The rotational completeness of a 10 year combine yield map dataset for a 435 ha farm in Eastern England was assessed. The dataset was cleaned statistically, and its accuracy assessed by comparison with recorded yields from trailer weigh cells. The cleaned, validated, and corrected yield map dataset was used to identify management zones across the whole farm using fuzzy clustering. The temporal stability of management zones and economic performance across the rotation was also assessed. RESULTS AND DISSCUSION Data cleaning methods removed 16% of data points, improving the degree of spatial correlation within the individual yield maps. Independent validation demonstrated varied accuracy of yield maps from combine harvester data and errors in wheat ranged from 0.53 to 1.53 t/ha RMSE. These errors have implications for researchers using combine yield data to develop and validate precision agriculture technologies. This data set required correction before yield data can be applied with confidence for on-farm decision making. Compared to the zones with the highest margin in each field, 34% of zones had an average annual margin loss of >£100 ha. The temporal stability of the resulting management zones also varied. Areas with the lowest economic performance and greatest yield stability across years will potentially see the greatest economic and environmental benefits from precision agriculture techniques. SIGNIFICANCE The accuracy of combine yield map data should not be assumed. The application of these datasets, including for the identification of management zones or in developing precision agriculture techniques should attempt to address this through data cleaning and validation procedures. Only then should it be used for on farm decision making, such as identifying areas with the most economic benefit by applying precision agriculture tools such as variable rate nutrient applications

Cellular metabolism constrains innate immune responses in early human ontogeny

Pathogen immune responses are profoundly attenuated in fetuses and premature infants, yet the mechanisms underlying this developmental immaturity remain unclear. Here we show transcriptomic, metabolic and polysome profiling and find that monocytes isolated from infants born early in gestation display perturbations in PPAR-γ-regulated metabolic pathways, limited glycolytic capacity and reduced ribosomal activity. These metabolic changes are linked to a lack of translation of most cytokines and of MALT1 signalosome genes essential to respond to the neonatal pathogen Candida. In contrast, they have little impact on house-keeping phagocytosis functions. Transcriptome analyses further indicate a role for mTOR and its putative negative regulator DNA Damage Inducible Transcript 4-Like in regulating these metabolic constraints. Our results provide a molecular basis for the broad susceptibility to multiple pathogens in these infants, and suggest that the fetal immune system is metabolically programmed to avoid energetically costly, dispensable and potentially harmful immune responses during ontogeny

Of risks and regulations: how leading U.S. nanoscientists form policy stances about nanotechnology

Even though there is a high degree of scientific uncertainty about the risks of nanotechnology, many scholars have argued that policy-making cannot be placed on hold until risk assessments are complete (Faunce, Med J Aust 186(4):189–191, 2007; Kuzma, J Nanopart Res 9(1):165–182, 2007; O’Brien and Cummins, Hum Ecol Risk Assess 14(3):568–592, 2008; Powell et al., Environ Manag 42(3):426–443, 2008). In the absence of risk assessment data, decision makers often rely on scientists’ input about risks and regulation to make policy decisions. The research we present here goes beyond the earlier descriptive studies about nanotechnology regulation to explore the heuristics that the leading U.S. nanoscientists use when they make policy decisions about regulating nanotechnology. In particular, we explore the relationship between nanoscientists’ risk and benefit perceptions and their support for nanotech regulation. We conclude that nanoscientists are more supportive of regulating nanotechnology when they perceive higher levels of risks; yet, their perceived benefits about nanotechnology do not significantly impact their support for nanotech regulation. We also find some gender and disciplinary differences among the nanoscientists. Males are less supportive of nanotech regulation than their female peers and materials scientists are more supportive of nanotechnology regulation than scientists in other fields. Lastly, our findings illustrate that the leading U.S. nanoscientists see the areas of surveillance/privacy, human enhancement, medicine, and environment as the nanotech application areas that are most in need of new regulations

One Hundred Priority Questions for the Development of Sustainable Food Systems in Sub-Saharan Africa

Sub-Saharan Africa is facing an expected doubling of human population and tripling of food demand over the next quarter century, posing a range of severe environmental, political, and socio-economic challenges. In some cases, key Sustainable Development Goals (SDGs) are in direct conflict, raising difficult policy and funding decisions, particularly in relation to trade-offs between food production, social inequality, and ecosystem health. In this study, we used a horizon-scanning approach to identify 100 practical or research-focused questions that, if answered, would have the greatest positive impact on addressing these trade-offs and ensuring future productivity and resilience of food-production systems across sub-Saharan Africa. Through direct canvassing of opinions, we obtained 1339 questions from 331 experts based in 55 countries. We then used online voting and participatory workshops to produce a final list of 100 questions divided into 12 thematic sections spanning topics from gender inequality to technological adoption and climate change. Using data on the background of respondents, we show that perspectives and priorities can vary, but they are largely consistent across different professional and geographical contexts. We hope these questions provide a template for establishing new research directions and prioritising funding decisions in sub-Saharan Africa

Genetic Architecture of a Reinforced, Postmating, Reproductive Isolation Barrier between Neurospora Species Indicates Evolution via Natural Selection

A role for natural selection in reinforcing premating barriers is recognized, but selection for reinforcement of postmating barriers remains controversial. Organisms lacking evolvable premating barriers can theoretically reinforce postmating isolation, but only under restrictive conditions: parental investment in hybrid progeny must inhibit subsequent reproduction, and selected postmating barriers must restore parents' capacity to reproduce successfully. We show that reinforced postmating isolation markedly increases maternal fitness in the fungus Neurospora crassa, and we detect the evolutionary genetic signature of natural selection by quantitative trait locus (QTL) analysis of the reinforced barrier. Hybrid progeny of N. crassa and N. intermedia are highly inviable. Fertilization by local N. intermedia results in early abortion of hybrid fruitbodies, and we show that abortion is adaptive because only aborted maternal colonies remain fully receptive to future reproduction. In the first QTL analysis of postmating reinforcement in microbial eukaryotes, we identify 11 loci for abortive hybrid fruitbody development, including three major QTLs that together explain 30% of trait variance. One of the major QTLs and six QTLs of lesser effect are found on the mating-type determining chromosome of Neurospora. Several reinforcement QTLs are flanked by genetic markers showing either segregation distortion or non-random associations with alleles at other loci in a cross between N. crassa of different clades, suggesting that the loci also are associated with local effects on same-species reproduction. Statistical analysis of the allelic effects distribution for abortive hybrid fruitbody development indicates its evolution occurred under positive selection. Our results strongly support a role for natural selection in the evolution of reinforced postmating isolation in N. crassa

Mapping past human land use using archaeological data: A new classification for global land use synthesis and data harmonization

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve repre- sentation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evi- dence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both imple- mented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and meth- ods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, link- ing archaeologists with climate modelers, biodiversity conservation workers and initiatives.publishedVersio

Mapping past human land use using archaeological data: A new classification for global land use synthesis and data harmonization.

In the 12,000 years preceding the Industrial Revolution, human activities led to significant changes in land cover, plant and animal distributions, surface hydrology, and biochemical cycles. Earth system models suggest that this anthropogenic land cover change influenced regional and global climate. However, the representation of past land use in earth system models is currently oversimplified. As a result, there are large uncertainties in the current understanding of the past and current state of the earth system. In order to improve representation of the variety and scale of impacts that past land use had on the earth system, a global effort is underway to aggregate and synthesize archaeological and historical evidence of land use systems. Here we present a simple, hierarchical classification of land use systems designed to be used with archaeological and historical data at a global scale and a schema of codes that identify land use practices common to a range of systems, both implemented in a geospatial database. The classification scheme and database resulted from an extensive process of consultation with researchers worldwide. Our scheme is designed to deliver consistent, empirically robust data for the improvement of land use models, while simultaneously allowing for a comparative, detailed mapping of land use relevant to the needs of historical scholars. To illustrate the benefits of the classification scheme and methods for mapping historical land use, we apply it to Mesopotamia and Arabia at 6 kya (c. 4000 BCE). The scheme will be used to describe land use by the Past Global Changes (PAGES) LandCover6k working group, an international project comprised of archaeologists, historians, geographers, paleoecologists, and modelers. Beyond this, the scheme has a wide utility for creating a common language between research and policy communities, linking archaeologists with climate modelers, biodiversity conservation workers and initiatives