2,330 research outputs found

    The first maps of κd - the dust mass absorption coefficient - in nearby galaxies, with DustPedia

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    The dust mass absorption coefficient, κd is the conversion function used to infer physical dust masses from observations of dust emission. However, it is notoriously poorly constrained, and it is highly uncertain how it varies, either between or within galaxies. Here we present the results of a proof-of-concept study, using the DustPedia data for two nearby face-on spiral galaxies M 74 (NGC 628) and M 83 (NGC 5236), to create the first ever maps of κd in galaxies. We determine κd using an empirical method that exploits the fact that the dust-to-metals ratio of the interstellar medium is constrained by direct measurements of the depletion of gas-phase metals. We apply this method pixel-by-pixel within M 74 and M 83, to create maps of κd. We also demonstrate a novel method of producing metallicity maps for galaxies with irregularly sampled measurements, using the machine learning technique of Gaussian process regression. We find strong evidence for significant variation in κd. We find values of κd at 500 μm spanning the range 0.11-0.25 m^{2 kg^{-1}} in M 74, and 0.15-0.80 m^{2 kg^{-1}} in M 83. Surprisingly, we find that κd shows a distinct inverse correlation with the local density of the interstellar medium. This inverse correlation is the opposite of what is predicted by standard dust models. However, we find this relationship to be robust against a large range of changes to our method - only the adoption of unphysical or highly unusual assumptions would be able to suppress it

    Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

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    Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

    Comparing Remote Sensing and Field-Based Approaches to Estimate Ladder Fuels and Predict Wildfire Burn Severity

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    While fire is an important ecological process, wildfire size and severity have increased as a result of climate change, historical fire suppression, and lack of adequate fuels management. Ladder fuels, which bridge the gap between the surface and canopy leading to more severe canopy fires, can inform management to reduce wildfire risk. Here, we compared remote sensing and field-based approaches to estimate ladder fuel density. We also determined if densities from different approaches could predict wildfire burn severity (Landsat-based Relativized delta Normalized Burn Ratio; RdNBR). Ladder fuel densities at 1-m strata and 4-m bins (1–4 m and 1–8 m) were collected remotely using a terrestrial laser scanner (TLS), a handheld-mobile laser scanner (HMLS), an unoccupied aerial system (UAS) with a multispectral camera and Structure from Motion (SfM) processing (UAS-SfM), and an airborne laser scanner (ALS) in 35 plots in oak woodlands in Sonoma County, California, United States prior to natural wildfires. Ladder fuels were also measured in the same plots using a photo banner. Linear relationships among ladder fuel densities estimated at broad strata (1–4 m, 1–8 m) were evaluated using Pearson’s correlation (r). From 1 to 4 m, most densities were significantly correlated across approaches. From 1 to 8 m, TLS densities were significantly correlated with HMLS, UAS-SfM and ALS densities and UAS-SfM and HMLS densities were moderately correlated with ALS densities. Including field-measured plot-level canopy base height (CBH) improved most correlations at medium and high CBH, especially those including UAS-SfM data. The most significant generalized linear model to predict RdNBR included interactions between CBH and ladder fuel densities at specific 1-m stratum collected using TLS, ALS, and HMLS approaches (R2 = 0.67, 0.66, and 0.44, respectively). Results imply that remote sensing approaches for ladder fuel density can be used interchangeably in oak woodlands, except UAS-SfM combined with the photo banner. Additionally, TLS, HMLS and ALS approaches can be used with CBH from 1 to 8 m to predict RdNBR. Future work should investigate how ladder fuel densities using our techniques can be validated with destructive sampling and incorporated into predictive models of wildfire severity and fire behavior at varying spatial scales

    Stabilization of α-conotoxin AuIB: Influences of disulfide connectivity and backbone cyclization

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    alpha-Conotoxins are peptides isolated from the venom ducts of cone snails that target nicotinic acetylcholine receptors (nAChRs). They are valuable pharmacological tools and have potential applications for treating a range of conditions in humans, including pain. However, like all peptides, conotoxins are susceptible to degradation, and to enhance their therapeutic potential it is important to elucidate the factors contributing to instability and to develop approaches for improving stability. AuIB is a unique member of the alpha-conotoxin family because the nonnative "ribbon'' disulfide isomer exhibits enhanced activity at the nAChR in rat parasympathetic neurons compared with the native "globular'' isomer. Here we show that the ribbon isomer of AuIB is also more resistant to disulfide scrambling, despite having a nonnative connectivity and flexible structure. This resistance to disulfide scrambling does not correlate with overall stability in serum because the ribbon isomer is degraded in human serum more rapidly than the globular isomer. Cyclization via the joining of the N- and C-termini with peptide linkers of four to seven amino acids prevented degradation of the ribbon isomer in serum and stabilized the globular isomers to disulfide scrambling. The linker length used for cyclization strongly affected the relative proportions of the disulfide isomers produced by oxidative folding. Overall, the results of this study provide important insights into factors influencing the stability and oxidative folding of alpha-conotoxin AuIB and might be valuable in the design of more stable antagonists of nAChRs. Antioxid. Redox Signal. 14, 87-95

    An exploratory cluster randomised controlled trial of knowledge translation strategies to support evidence-informed decision-making in local governments (The KT4LG study)

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    Background: Childhood overweight and obesity is the most prevalent and, arguably, politically complex child health problem internationally. Governments, communities and industry have important roles to play, and are increasingly expected to deliver an evidence-informed system-wide prevention program. However, efforts are impeded by a lack of organisational access to and use of research evidence. This study aims to identify feasible, acceptable and ideally, effective knowledge translation (KT) strategies to increase evidence-informed decision making in local governments, within the context of childhood obesity prevention as a national policy priority.Methods/Design: This paper describes the methods for KT4LG, a cluster randomised controlled trial which is exploratory in nature, given the limited evidence base and methodological advances. KT4LG aims to examine a program of KT strategies to increase the use of research evidence in informing public health decisions in local governments. KT4LG will also assess the feasibility and acceptability of the intervention. The intervention program comprises a facilitated program of evidence awareness, access to tailored research evidence, critical appraisal skills development, networking and evidence summaries and will be compared to provision of evidence summaries alone in the control program. 28 local governments were randomised to intervention or control, using computer generated numbers, stratified by budget tertile (high, medium or low). Questionnaires will be used to measure impact, costs, and outcomes, and key informant interviews will be used to examine processes, feasibility, and experiences. Policy tracer studies will be included to examine impact of intervention on policies within relevant government policy documents.Discussion: Knowledge translation intervention studies with a focus on public health and prevention are very few in number. Thus, this study will provide essential data on the experience of program implementation and evaluation of a system-integrated intervention program employed within the local government public health context. Standardised programs of system, organisational and individual KT strategies have not been described or rigorously evaluated. As such, the findings will make a significant contribution to understanding whether a facilitated program of KT strategies hold promise for facilitating evidence-informed public health decision making within complex multisectoral government organisations.<br /

    Inflammatory cytokines and biofilm production sustain Staphylococcus aureus outgrowth and persistence: A pivotal interplay in the pathogenesis of Atopic Dermatitis

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    Individuals with Atopic dermatitis (AD) are highly susceptible to Staphylococcus aureus colonization. However, the mechanisms driving this process as well as the impact of S. aureus in AD pathogenesis are still incompletely understood. In this study, we analysed the role of biofilm in sustaining S. aureus chronic persistence and its impact on AD severity. Further we explored whether key inflammatory cytokines overexpressed in AD might provide a selective advantage to S. aureus. Results show that the strength of biofilm production by S. aureus correlated with the severity of the skin lesion, being significantly higher (P < 0.01) in patients with a more severe form of the disease as compared to those individuals with mild AD. Additionally, interleukin (IL)-β and interferon γ (IFN-γ), but not interleukin (IL)-6, induced a concentration-dependent increase of S. aureus growth. This effect was not observed with coagulase-negative staphylococci isolated from the skin of AD patients. These findings indicate that inflammatory cytokines such as IL1-β and IFN-γ, can selectively promote S. aureus outgrowth, thus subverting the composition of the healthy skin microbiome. Moreover, biofilm production by S. aureus plays a relevant role in further supporting chronic colonization and disease severity, while providing an increased tolerance to antimicrobials

    Instabilities and robust control in natural resource management

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    Most renewable natural resources exhibit marked demographic and environmental stochasticities, which are exarcebated in management decisions by the uncertainty regarding the choice of an appropriate model to describe system dynamics. Moreover, demand and supply analysis often indicates the presence of instabilities and multiple equilibria, which may lead to management problems that are intensified by uncertainty on the evolution of the resource stock. In this paper the fishery management problem is used as an example to explore the potential of robust optimal control, where the objective is to choose a harvesting rule that will work under a range of admissible specifications for the stock-recruitment equation. The paper derives robust harvesting rules leading to a unique equilibrium, which could be helpful in the design of policy instruments such as robust quota systems.info:eu-repo/semantics/publishedVersio

    Risks and Benefits of Consumption of Great Lakes Fish

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    Background: Beneficial effects of fish consumption on early cognitive development and cardiovascular health have been attributed to the omega-3 fatty acids in fish and fish oils, but toxic chemicals in fish may adversely affect these health outcomes. Risk–benefit assessments of fish consumption have frequently focused on methylmercury and omega-3 fatty acids, not persistent pollutants such as polychlorinated biphenyls, and none have evaluated Great Lakes fish consumption
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