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"Forrest, Matthew"
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The foundations of operational resilience - assessing the ability to operate in an anti-access/area denial (A2/AD) environment : the analytical framework, lexicon, and characteristics of the Operational Resilience Analysis Model (ORAM)
\"Although much work has been done considering the issue of airbase resilience especially in the Asia-Pacific region these studies have typically focused on a single aspect of the problem (such as hardening or runway repair) but have not considered the issues in total. There is a need to view the issue more holistically, especially given the strategic implications of U.S. power projection in anti-access/area denial (A2/AD) environments. The authors of this report developed a modeling framework and lexicon for conducting a detailed analysis of future Air Force operational resilience in an A2/AD environment; the analysis itself focused on different regions (Pacific, Southwest Asia, etc.) to bound the problem and identify a robust set of strategic assumptions and planning requirements. The study was set within the context of efforts to rebalance the joint force in the Asia-Pacific region. This report describes the Operational Resilience Analysis Model (ORAM) built for this effort, which was used to evaluate the impact of different courses of action from an operational standpoint. The authors explain the ORAM model, discuss the inputs that go into modeling Blue (friendly) and Red (enemy) capabilities, and illustrate the model using a simple notional case. They conclude with some suggestions for follow-on work to improve the functionality of ORAM and to address data uncertainties in the model\"--Publisher's website.
Book
Rapid Detection of Mycobacterium tuberculosis by Recombinase Polymerase Amplification
Improved access to effective tests for diagnosing tuberculosis (TB) has been designated a public health priority by the World Health Organisation. In high burden TB countries nucleic acid based TB tests have been restricted to centralised laboratories and specialised research settings. Requirements such as a constant electrical supply, air conditioning and skilled, computer literate operators prevent implementation of such tests in many settings. Isothermal DNA amplification technologies permit the use of simpler, less energy intensive detection platforms more suited to low resource settings that allow the accurate diagnosis of a disease within a short timeframe. Recombinase Polymerase Amplification (RPA) is a rapid, low temperature isothermal DNA amplification reaction. We report here RPA-based detection of Mycobacterium tuberculosis complex (MTC) DNA in <20 minutes at 39 °C. Assays for two MTC specific targets were investigated, IS6110 and IS1081. When testing purified MTC genomic DNA, limits of detection of 6.25 fg (IS6110) and 20 fg (IS1081)were consistently achieved. When testing a convenience sample of pulmonary specimens from suspected TB patients, RPA demonstrated superior accuracy to indirect fluorescence microscopy. Compared to culture, sensitivities for the IS1081 RPA and microscopy were 91.4% (95%CI: 85, 97.9) and 86.1% (95%CI: 78.1, 94.1) respectively (n = 71). Specificities were 100% and 88.6% (95% CI: 80.8, 96.1) respectively. For the IS6110 RPA and microscopy sensitivities of 87.5% (95%CI: 81.7, 93.2) and 70.8% (95%CI: 62.9, 78.7) were obtained (n = 90). Specificities were 95.4 (95% CI: 92.3,98.1) and 88% (95% CI: 83.6, 92.4) respectively. The superior specificity of RPA for detecting tuberculosis was due to the reduced ability of fluorescence microscopy to distinguish Mtb complex from other acid fast bacteria. The rapid nature of the RPA assay and its low energy requirement compared to other amplification technologies suggest RPA-based TB assays could be of use for integration into a point-of-care test for use in resource constrained settings.
Journal Article
The fire weather in Europe: large-scale trends towards higher danger
The climate over Europe has been recorded to be hotter, drier, and more fire-prone over the last decade than ever before, leading to concerns about how climate change will alter fire weather in the future. A typical measure to estimate fire weather severity based on climate is the Canadian fire weather index (FWI). In this study, we used high-resolution, bias-corrected climate model output (∼9 km) from six CMIP6 climate models and four shared socio-economic pathway projections (SSPs) to calculate consistent and comparable daily FWI datasets for Europe from 1950 to 2080. Our study aims to identify regional and large-scale shifts in fire weather severity and its predictability over time to support adaptive planning. We show that irrespective of the future SSP, fire weather will become more severe, but the increase is much stronger under high greenhouse gas emissions. This leads to new areas being exposed to severe fire weather, such as central Europe and rapidly warming mountainous areas. Already fire-prone regions in southern Europe will experience more extreme conditions. We conclude that only the low-emission SSP1-2.6 pathway can prevent strong increases in fire weather beyond the 2050s. Fire surveillance and management will become more important, even in areas and in seasons where they have not been in the focus so far.
Journal Article
Relative Impact of Nucleotide and Copy Number Variation on Gene Expression Phenotypes
Extensive studies are currently being performed to associate disease susceptibility with one form of genetic variation, namely, single-nucleotide polymorphisms (SNPs). In recent years, another type of common genetic variation has been characterized, namely, structural variation, including copy number variants (CNVs). To determine the overall contribution of CNVs to complex phenotypes, we have performed association analyses of expression levels of 14,925 transcripts with SNPs and CNVs in individuals who are part of the International HapMap project. SNPs and CNVs captured 83.6% and 17.7% of the total detected genetic variation in gene expression, respectively, but the signals from the two types of variation had little overlap. Interrogation of the genome for both types of variants may be an effective way to elucidate the causes of complex phenotypes and disease in humans.
Journal Article
Population genomics of human gene expression
Genetic variation influences gene expression, and this variation in gene expression can be efficiently mapped to specific genomic regions and variants. Here we have used gene expression profiling of Epstein-Barr virus–transformed lymphoblastoid cell lines of all 270 individuals genotyped in the HapMap Consortium to elucidate the detailed features of genetic variation underlying gene expression variation. We find that gene expression is heritable and that differentiation between populations is in agreement with earlier small-scale studies. A detailed association analysis of over 2.2 million common SNPs per population (5% frequency in HapMap) with gene expression identified at least 1,348 genes with association signals in
cis
and at least 180 in
trans
. Replication in at least one independent population was achieved for 37% of
cis
signals and 15% of
trans
signals, respectively. Our results strongly support an abundance of
cis
-regulatory variation in the human genome. Detection of
trans
effects is limited but suggests that regulatory variation may be the key primary effect contributing to phenotypic variation in humans. We also explore several methodologies that improve the current state of analysis of gene expression variation.
Journal Article
Understanding and modelling wildfire regimes: an ecological perspective
Recent extreme wildfire seasons in several regions have been associated with exceptionally hot, dry conditions, made more probable by climate change. Much research has focused on extreme fire weather and its drivers, but natural wildfire regimes—and their interactions with human activities—are far from being comprehensively understood. There is a lack of clarity about the ‘causes’ of wildfire, and about how ecosystems could be managed for the co-existence of wildfire and people. We present evidence supporting an ecosystem-centred framework for improved understanding and modelling of wildfire. Wildfire has a long geological history and is a pervasive natural process in contemporary plant communities. In some biomes, wildfire would be more frequent without human settlement; in others they would be unchanged or less frequent. A world without fire would have greater forest cover, especially in present-day savannas. Many species would be missing, because fire regimes have co-evolved with plant traits that resist, adapt to or promote wildfire. Certain plant traits are favoured by different fire frequencies, and may be missing in ecosystems that are normally fire-free. For example, post-fire resprouting is more common among woody plants in high-frequency fire regimes than where fire is infrequent. The impact of habitat fragmentation on wildfire crucially depends on whether the ecosystem is fire-adapted. In normally fire-free ecosystems, fragmentation facilitates wildfire starts and is detrimental to biodiversity. In fire-adapted ecosystems, fragmentation inhibits fires from spreading and fire suppression is detrimental to biodiversity. This interpretation explains observed, counterintuitive patterns of spatial correlation between wildfire and potential ignition sources. Lightning correlates positively with burnt area only in open ecosystems with frequent fire. Human population correlates positively with burnt area only in densely forested regions. Models for vegetation-fire interactions must be informed by insights from fire ecology to make credible future projections in a changing climate.
Journal Article
Historical (1700–2012) Global Multi-Model Estimates of the Fire Emissions from the Fire Modeling Intercomparison Project (FireMIP)
Fire emissions are critical for carbon and nutrient cycles, climate, and air quality. Dynamic Global Vegetation Models (DGVMs) with interactive fire modeling provide important estimates for long-term and large-scale changes of fire emissions. Here we present the first multi-model estimates of global gridded historical fire emissions for 1700-2012, including carbon and 33 species of trace gases and aerosols. The dataset is based on simulations of nine DGVMs with different state-of-the-art global fire models that participated in the Fire Modeling Intercomparison Project (FireMIP), using the same and standardized protocols and forcing data, and the most up-to-date fire emission factor table from field and laboratory studies over various land cover types. We evaluate the simulations of present-day fire emissions by comparing them with satellite-based products. Evaluation results show that most DGVMs simulate present-day global fire emission totals within the range of satellite-based products, and can capture the high emissions over the tropical savannas, low emissions over the arid and sparsely vegetated regions, and the main features of seasonality. However, most of the models fail to simulate the interannual variability, partly due to a lack of modeling peat fires and tropical deforestation fires. Historically, all models show only a weak trend in global fire emissions before ~1850s, consistent with multi-source merged historical reconstructions. The long-term trends among DGVMs are quite different for the 20th century, with some models showing an increase and others a decrease in fire emissions, mainly as a result of the discrepancy in their simulated responses to human population density change and land-use and land-cover change (LULCC). Our study provides a basic dataset for developing regional and global multi-source merged historical reconstructions and merging methods, and analyzing historical changes of fire emissions and their uncertainties as well as their role in the Earth system. It also highlights the importance of accurately modeling the responses of fire emissions to LULCC and population density change in reducing uncertainties in historical reconstructions of fire emissions and providing more reliable future projections.
Journal Article
Nothing a hot bath won't cure: Infection rates of amphibian chytrid fungus correlate negatively with water temperature under natural field settings
Dramatic declines and extinctions of amphibian populations throughout the world have been associated with chytridiomycosis, an infectious disease caused by the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Previous studies indicated that Bd prevalence correlates with cooler temperatures in the field, and laboratory experiments have demonstrated that Bd ceases growth at temperatures above 28uC. Here we investigate how small-scale variations in water temperature correlate with Bd prevalence in the wild. We sampled 221 amphibians, including 201 lowland leopard frogs (Rana [Lithobates] yavapaiensis), from 12 sites in Arizona, USA, and tested them for Bd. Amphibians were encountered in microhabitats that exhibited a wide range of water temperatures (10–50uC), including several geothermal water sources. There was a strong inverse correlation between the water temperature in which lowland leopard frogs were captured and Bd prevalence, even after taking into account the influence of year, season, and host size. In locations where Bd was known to be present, the prevalence of Bd infections dropped from 75–100% in water ,15uC, to less than 10% in water .30uC. A strong inverse correlation between Bd infection status and water temperature was also observed within sites. Our findings suggest that microhabitats where water temperatures exceed 30uC provide lowland leopard frogs with significant protection from Bd, which could have important implications for disease dynamics, as well as management applications. There must be quite a few things a hot bath won’t cure, but I don’t know many of them - Sylvia Plath, ‘‘The Bell Jar’’ (1963).
Journal Article
Genome-Wide Associations of Gene Expression Variation in Humans
The exploration of quantitative variation in human populations has become one of the major priorities for medical genetics. The successful identification of variants that contribute to complex traits is highly dependent on reliable assays and genetic maps. We have performed a genome-wide quantitative trait analysis of 630 genes in 60 unrelated Utah residents with ancestry from Northern and Western Europe using the publicly available phase I data of the International HapMap project. The genes are located in regions of the human genome with elevated functional annotation and disease interest including the ENCODE regions spanning 1% of the genome, Chromosome 21 and Chromosome 20q12-13.2. We apply three different methods of multiple test correction, including Bonferroni, false discovery rate, and permutations. For the 374 expressed genes, we find many regions with statistically significant association of single nucleotide polymorphisms (SNPs) with expression variation in lymphoblastoid cell lines after correcting for multiple tests. Based on our analyses, the signal proximal (cis-) to the genes of interest is more abundant and more stable than distal and trans across statistical methodologies. Our results suggest that regulatory polymorphism is widespread in the human genome and show that the 5-kb (phase I) HapMap has sufficient density to enable linkage disequilibrium mapping in humans. Such studies will significantly enhance our ability to annotate the non-coding part of the genome and interpret functional variation. In addition, we demonstrate that the HapMap cell lines themselves may serve as a useful resource for quantitative measurements at the cellular level.
Journal Article
Recombinations in Staphylococcal Cassette Chromosome mec Elements Compromise the Molecular Detection of Methicillin Resistance in Staphylococcus aureus
Clinical laboratories are increasingly using molecular tests for methicillin-resistant Staphylococcus aureus (MRSA) screening. However, primers have to be targeted to a variable chromosomal region, the staphylococcal cassette chromosome mec (SCCmec). We initially screened 726 MRSA isolates from a single UK hospital trust by recombinase polymerase amplification (RPA), a novel, isothermal alternative to PCR. Undetected isolates were further characterised using multilocus sequence, spa typing and whole genome sequencing. 96% of our tested phenotypically MRSA isolates contained one of the six orfX-SCCmec junctions our RPA test and commercially available molecular tests target. However 30 isolates could not be detected. Sequencing of 24 of these isolates demonstrated recombinations within the SCCmec element with novel insertions that interfered with the RPA, preventing identification as MRSA. This result suggests that clinical laboratories cannot rely solely upon molecular assays to reliably detect all methicillin-resistance. The presence of significant recombinations in the SCCmec element, where the majority of assays target their primers, suggests that there will continue to be isolates that escape identification. We caution that dependence on amplification-based molecular assays will continue to result in failure to diagnose a small proportion (∼4%) of MRSA isolates, unless the true level of SCCmec natural diversity is determined by whole genome sequencing of a large collection of MRSA isolates.
Journal Article