Quantum oscillations near the metamagnetic transition in Sr3Ru2O7

This is the final version. Available from American Physical Society via the DOI in this recordWe report a detailed investigation of quantum oscillations in Sr 3 Ru2 O7, observed inductively (the de Haas-van Alphen effect) and thermally (the magnetocaloric effect). Working at fields from 3 to 18 T allowed us to straddle the metamagnetic transition region and probe the low- and high-field Fermi liquids. The observed frequencies are strongly field dependent in the vicinity of the metamagnetic transition, and there is evidence for magnetic breakdown. We also present the results of a comprehensive rotation study. The most surprising result concerns the field dependence of the measured quasiparticle masses. Contrary to conclusions previously drawn by some of us as a result of a study performed with a much poorer signal-to-noise ratio, none of the five Fermi-surface branches for which we have good field-dependent data gives evidence for a strong-field dependence of the mass. The implications of these experimental findings are discussed. © 2010 The American Physical Society.Engineering and Physical Sciences Research Council (EPSRC

Focused Deterrence and the Prevention of Violent Gun Injuries: Practice, Theoretical Principles, and Scientific Evidence

Focused deterrence strategies are a relatively new addition to a growing portfolio of evidence-based violent gun injury prevention practices available to policy makers and practitioners. These strategies seek to change offender behavior by understanding the underlying violence-producing dynamics and conditions that sustain recurring violent gun injury problems and by implementing a blended strategy of law enforcement, community mobilization, and social service actions. Consistent with documented public health practice, the focused deterrence approach identifies underlying risk factors and causes of recurring violent gun injury problems, develops tailored responses to these underlying conditions, and measures the impact of implemented interventions. This article reviews the practice, theoretical principles, and evaluation evidence on focused deterrence strategies. Although more rigorous randomized studies are needed, the available empirical evidence suggests that these strategies generate noteworthy gun violence reduction impacts and should be part of a broader portfolio of violence prevention strategies available to policy makers and practitioners

Increased Avian Diversity Is Associated with Lower Incidence of Human West Nile Infection: Observation of the Dilution Effect

Recent infectious disease models illustrate a suite of mechanisms that can result in lower incidence of disease in areas of higher disease host diversity–the ‘dilution effect’. These models are particularly applicable to human zoonoses, which are infectious diseases of wildlife that spill over into human populations. As many recent emerging infectious diseases are zoonoses, the mechanisms that underlie the ‘dilution effect’ are potentially widely applicable and could contribute greatly to our understanding of a suite of diseases. The dilution effect has largely been observed in the context of Lyme disease and the predictions of the underlying models have rarely been examined for other infectious diseases on a broad geographic scale. Here, we explored whether the dilution effect can be observed in the relationship between the incidence of human West Nile virus (WNV) infection and bird (host) diversity in the eastern US. We constructed a novel geospatial contrasts analysis that compares the small differences in avian diversity of neighboring US counties (where one county reported human cases of WNV and the other reported no cases) with associated between-county differences in human disease. We also controlled for confounding factors of climate, regional variation in mosquito vector type, urbanization, and human socioeconomic factors that are all likely to affect human disease incidence. We found there is lower incidence of human WNV in eastern US counties that have greater avian (viral host) diversity. This pattern exists when examining diversity-disease relationships both before WNV reached the US (in 1998) and once the epidemic was underway (in 2002). The robust disease-diversity relationships confirm that the dilution effect can be observed in another emerging infectious disease and illustrate an important ecosystem service provided by biodiversity, further supporting the growing view that protecting biodiversity should be considered in public health and safety plans

Taguchi Loss Function for Varus/Valgus Alignment in Total Knee Arthroplasty

Methods of designing equipment to improve quality have been developed by Taguchi. A key feature of these methods is the development of loss function, which quantifies the financial cost (loss) resulting from deviations from target dimensions. Total knee arthroplasties can fail due to prosthetic component malalignment. A Taguchi loss function for varus/valgus alignment of the prosthesis and revision rates was developed. Six studies were identified from a comprehensive literature search. Varus and extreme valgus alignments correlated with an increased percentage of prosthetic failure. A loss function of L( y) = $326.80y2 , where y was deviation from ideal varus/valgus angle, was determined. The expected loss function was EL=$326.80y¯2+s2 , where y¯ was the mean deviance from the ideal varus/valgus angle and s2 was the variance in varus/valgus angle. This loss function was used to estimate the cost savings of using computer-assisted surgical navigation in total knee arthroplasty (TKA). The average savings of a navigated TKA versus a conventional TKA, based on the expected loss equation derived from the Taguchi loss function, was $2,304 per knee. The expected loss function derived here can serve as a tool for biomedical engineers seeking to use Taguchi quality engineering methods in designing orthopaedic devices

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy

Wolbachia and DNA barcoding insects: patterns, potential and problems

Wolbachia is a genus of bacterial endosymbionts that impacts the breeding systems of their hosts. Wolbachia can confuse the patterns of mitochondrial variation, including DNA barcodes, because it influences the pathways through which mitochondria are inherited. We examined the extent to which these endosymbionts are detected in routine DNA barcoding, assessed their impact upon the insect sequence divergence and identification accuracy, and considered the variation present in Wolbachia COI. Using both standard PCR assays (Wolbachia surface coding protein – wsp), and bacterial COI fragments we found evidence of Wolbachia in insect total genomic extracts created for DNA barcoding library construction. When >2 million insect COI trace files were examined on the Barcode of Life Datasystem (BOLD) Wolbachia COI was present in 0.16% of the cases. It is possible to generate Wolbachia COI using standard insect primers; however, that amplicon was never confused with the COI of the host. Wolbachia alleles recovered were predominantly Supergroup A and were broadly distributed geographically and phylogenetically. We conclude that the presence of the Wolbachia DNA in total genomic extracts made from insects is unlikely to compromise the accuracy of the DNA barcode library; in fact, the ability to query this DNA library (the database and the extracts) for endosymbionts is one of the ancillary benefits of such a large scale endeavor – for which we provide several examples. It is our conclusion that regular assays for Wolbachia presence and type can, and should, be adopted by large scale insect barcoding initiatives. While COI is one of the five multi-locus sequence typing (MLST) genes used for categorizing Wolbachia, there is limited overlap with the eukaryotic DNA barcode region

The Prehistory of Potyviruses: Their Initial Radiation Was during the Dawn of Agriculture

Background: Potyviruses are found world wide, are spread by probing aphids and cause considerable crop damage. Potyvirus is one of the two largest plant virus genera and contains about 15% of all named plant virus species. When and why did the potyviruses become so numerous? Here we answer the first question and discuss the other. Methods and Findings: We have inferred the phylogenies of the partial coat protein gene sequences of about 50 potyviruses, and studied in detail the phylogenies of some using various methods and evolutionary models. Their phylogenies have been calibrated using historical isolation and outbreak events: the plum pox virus epidemic which swept through Europe in the 20th century, incursions of potyviruses into Australia after agriculture was established by European colonists, the likely transport of cowpea aphid-borne mosaic virus in cowpea seed from Africa to the Americas with the 16th century slave trade and the similar transport of papaya ringspot virus from India to the Americas. Conclusions/Significance: Our studies indicate that the partial coat protein genes of potyviruses have an evolutionary rate of about 1.1561024 nucleotide substitutions/site/year, and the initial radiation of the potyviruses occurred only about 6,600 years ago, and hence coincided with the dawn of agriculture. We discuss the ways in which agriculture may have triggered the prehistoric emergence of potyviruses and fostered their speciation

Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda

<p>Abstract</p> <p>Background</p> <p>Assessing biomass is gaining increasing interest mainly for bioenergy, climate change research and mitigation activities, such as reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+). In response to these needs, a number of biomass/carbon maps have been recently produced using different approaches but the lack of comparable reference data limits their proper validation. The objectives of this study are to compare the available maps for Uganda and to understand the sources of variability in the estimation. Uganda was chosen as a case-study because it presents a reliable national biomass reference dataset.</p> <p>Results</p> <p>The comparison of the biomass/carbon maps show strong disagreement between the products, with estimates of total aboveground biomass of Uganda ranging from 343 to 2201 Tg and different spatial distribution patterns. Compared to the reference map based on country-specific field data and a national Land Cover (LC) dataset (estimating 468 Tg), maps based on biome-average biomass values, such as the Intergovernmental Panel on Climate Change (IPCC) default values, and global LC datasets tend to strongly overestimate biomass availability of Uganda (ranging from 578 to 2201 Tg), while maps based on satellite data and regression models provide conservative estimates (ranging from 343 to 443 Tg). The comparison of the maps predictions with field data, upscaled to map resolution using LC data, is in accordance with the above findings. This study also demonstrates that the biomass estimates are primarily driven by the biomass reference data while the type of spatial maps used for their stratification has a smaller, but not negligible, impact. The differences in format, resolution and biomass definition used by the maps, as well as the fact that some datasets are not independent from the reference data to which they are compared, are considered in the interpretation of the results.</p> <p>Conclusions</p> <p>The strong disagreement between existing products and the large impact of biomass reference data on the estimates indicate that the first, critical step to improve the accuracy of the biomass maps consists of the collection of accurate biomass field data for all relevant vegetation types. However, detailed and accurate spatial datasets are crucial to obtain accurate estimates at specific locations.</p