Mojave Desert - Shaded Relief

Produced for the Mojave Desert Ecosystem Program under the United States Department of Defense Legacy Program in cooperation with the Department of the Interior. Cartography and image processing by: Remote Sensing and Geographic Information Systems Laboratory Department of Geography and Earth Resources College of Natural Resources Utah State University Logan, Utah 84322–5240 Cartographic preparation and printing by U.S. Geological Survey, 1998. Shaded Relief derived from U.S\u3e Geological Survey (USGS) National Elevation Database. Solar elevation 25°, azimuth 315°, exaggeration 5x, ambient light 0.5 Land ownership compiled from 1:100,000-scale Bureau of Land Management Surface Management Status maps. Populated places produced from USGS Geographic Names Information System. Roads and water bodies produced from USGS 1:100,000-scale Digital Line Graph data. Project boundary based on the Mojave Desert Section delineated by Robert G. Bailey, 1995, with a 50 kilometer buffer

Mojave Desert - Satellite Image Map

Produced for the Mojave Desert Ecosystem Program under the United States Department of Defense Legacy Program in cooperation with the Department of the Interior. Cartography and image processing by: Remote Sensing and Geographic Information Systems Laboratory Department of Geography and Earth Resources College of Natural Resources Utah State University Logan, Utah 84322–5240 Cartographic preparation and printing by U.S. Geological Survey, 1998. Image map produced from 15 Landsat Thematic Mapper images recorded from 1991–1993, provided by U.S. Geological Survey (USGS), as part of the Multi–Resolution Land Characteristics Consortium Activities. Bands 7, 4, 2. Simulated natural color composite. Land ownership compiled from 1:100,000-scale Bureau of Land Management Surface Management Status maps. Populated places produced from USGS Geographic Names Information System. Roads produced from USGS 1:100,000-scale Digital Line Graph data. Project boundary based on the Mojave Desert Section delineated by Robert G. Bailey, 1995, with a 50 kilometer buffer

Mojave Desert - Land Ownership and Administration

Produced for the Mojave Desert Ecosystem Program under the United States Department of Defense Legacy Program in cooperation with the Department of the Interior. Cartography and image processing by: Remote Sensing and Geographic Information Systems Laboratory Department of Geography and Earth Resources College of Natural Resources Utah State University Logan, Utah 84322–5240 Cartographic preparation and printing by U.S. Geological Survey, 1998. Land ownership compiled from 1:100,000-scale Bureau of Land Management Surface Management Status maps. Populated places produced from USGS Geographic Names Information System. Roads and water bodies produced from USGS 1:100,000-scale Digital Line Graph data. Project boundary based on the Mojave Desert Section delineated by Robert G. Bailey, 1995, with a 50 kilometer buffe

Rapid determination of antimicrobial susceptibility of Gram-negative bacteria from clinical blood cultures using a scattered light-integrated collection device

Background. A bloodstream infection (BSI) presents a complex and serious health problem, a problem that is being exacerbated by increasing antimicrobial resistance (AMR). Gap Statement. The current turnaround times (TATs) for most antimicrobial susceptibility testing (AST) methods offer results retrospective of treatment decisions, and this limits the impact AST can have on antibiotic prescribing and patient care. Progress must be made towards rapid BSI diagnosis and AST to improve antimicrobial stewardship and reduce preventable deaths from BSIs. To support the successful implementation of rapid AST (rAST) in hospital settings, a rAST method that is affordable, is sustainable and offers comprehensive AMR detection is needed. Aim. To evaluate a scattered light-integrated collection (SLIC) device against standard of care (SOC) to determine whether SLIC could accelerate the current TATs with actionable, accurate rAST results for Gram-negative BSIs. Methods. Positive blood cultures from a tertiary referral hospital were studied prospectively. Flagged positive Gram-negative blood cultures were confirmed by Gram staining and analysed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Vitek 2, disc diffusion (ceftriaxone susceptibility only) and an SLIC device. Susceptibility to a panel of five antibiotics, as defined by European Committee on Antimicrobial Susceptibility Testing breakpoints, was examined using SLIC. Results. A total of 505 bacterial-antimicrobial combinations were analysed. A categorical agreement of 95.5% (482/505) was achieved between SLIC and SOC. The 23 discrepancies that occurred were further investigated by the broth microdilution method, with 10 AST results in agreement with SLIC and 13 in agreement with SOC. The mean time for AST was 10.53±0.46 h and 1.94±0.02 h for Vitek 2 and SLIC, respectively. SLIC saved 23.96±1.47 h from positive blood culture to AST result. Conclusion. SLIC has the capacity to provide accurate AST 1 day earlier from flagged positive blood cultures than SOC. This significant time saving could accelerate time to optimal antimicrobial therapy, improving antimicrobial stewardship and management of BSIs.</p

Analysis of the hydration water around bovine serum albumin using terahertz coherent synchrotron radiation.

Terahertz spectroscopy was used to study the absorption of bovine serum albumin (BSA) in water. The Diamond Light Source operating in a low alpha mode generated coherent synchrotron radiation that covered a useable spectral bandwidth of 0.3-3.3 THz (10-110 cm(-1)). As the BSA concentration was raised, there was a nonlinear change in absorption inconsistent with Beer's law. At low BSA concentrations (0-1 mM), the absorption remained constant or rose slightly. Above a concentration of 1 mM BSA, a steady decrease in absorption was observed, which was followed by a plateau that started at 2.5 mM. Using a overlapping hydration layer model, the hydration layer was estimated to extend 15 Å from the protein. Calculation of the corrected absorption coefficient (αcorr) for the water around BSA by subtracting the excluded volume of the protein provides an alternative approach to studying the hydration layer that provides evidence for complexity in the population of water around BSA.This is the accepted version of an article first published in The Journal of Physical Chemistry A. The version of record is available from ACS Publications at http://pubs.acs.org/doi/abs/10.1021/jp407410

Heritability of Malaria in Africa

BACKGROUND: While many individual genes have been identified that confer protection against malaria, the overall impact of host genetics on malarial risk remains unknown. METHODS AND FINDINGS: We have used pedigree-based genetic variance component analysis to determine the relative contributions of genetic and other factors to the variability in incidence of malaria and other infectious diseases in two cohorts of children living on the coast of Kenya. In the first, we monitored the incidence of mild clinical malaria and other febrile diseases through active surveillance of 640 children 10 y old or younger, living in 77 different households for an average of 2.7 y. In the second, we recorded hospital admissions with malaria and other infectious diseases in a birth cohort of 2,914 children for an average of 4.1 y. Mean annual incidence rates for mild and hospital-admitted malaria were 1.6 and 0.054 episodes per person per year, respectively. Twenty-four percent and 25% of the total variation in these outcomes was explained by additively acting host genes, and household explained a further 29% and 14%, respectively. The haemoglobin S gene explained only 2% of the total variation. For nonmalarial infections, additive genetics explained 39% and 13% of the variability in fevers and hospital-admitted infections, while household explained a further 9% and 30%, respectively. CONCLUSION: Genetic and unidentified household factors each accounted for around one quarter of the total variability in malaria incidence in our study population. The genetic effect was well beyond that explained by the anticipated effects of the haemoglobinopathies alone, suggesting the existence of many protective genes, each individually resulting in small population effects. While studying these genes may well provide insights into pathogenesis and resistance in human malaria, identifying and tackling the household effects must be the more efficient route to reducing the burden of disease in malaria-endemic areas