880 resultados para David L. Whitney


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Objective To evaluate the performance of China’s infectious disease automated alert and response system in the detection of outbreaks of hand, foot and mouth (HFM) disease. Methods We estimated size, duration and delay in reporting HFM disease outbreaks from cases notified between 1 May 2008 and 30 April 2010 and between 1 May 2010 and 30 April 2012, before and after automatic alert and response included HFM disease. Sensitivity, specificity and timeliness of detection of aberrations in the incidence of HFM disease outbreaks were estimated by comparing automated detections to observations of public health staff. Findings The alert and response system recorded 106 005 aberrations in the incidence of HFM disease between 1 May 2010 and 30 April 2012 – a mean of 5.6 aberrations per 100 days in each county that reported HFM disease. The response system had a sensitivity of 92.7% and a specificity of 95.0%. The mean delay between the reporting of the first case of an outbreak and detection of that outbreak by the response system was 2.1 days. Between the first and second study periods, the mean size of an HFM disease outbreak decreased from 19.4 to 15.8 cases and the mean interval between the onset and initial reporting of such an outbreak to the public health emergency reporting system decreased from 10.0 to 9.1 days. Conclusion The automated alert and response system shows good sensitivity in the detection of HFM disease outbreaks and appears to be relatively rapid. Continued use of this system should allow more effective prevention and limitation of such outbreaks in China.

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Background Strand specific RNAseq data is now more common in RNAseq projects. Visualizing RNAseq data has become an important matter in Analysis of sequencing data. The most widely used visualization tool is the UCSC genome browser that introduced the custom track concept that enabled researchers to simultaneously visualize gene expression at a particular locus from multiple experiments. Our objective of the software tool is to provide friendly interface for visualization of RNAseq datasets. Results This paper introduces a visualization tool (RNASeqBrowser) that incorporates and extends the functionality of the UCSC genome browser. For example, RNASeqBrowser simultaneously displays read coverage, SNPs, InDels and raw read tracks with other BED and wiggle tracks -- all being dynamically built from the BAM file. Paired reads are also connected in the browser to enable easier identification of novel exon/intron borders and chimaeric transcripts. Strand specific RNAseq data is also supported by RNASeqBrowser that displays reads above (positive strand transcript) or below (negative strand transcripts) a central line. Finally, RNASeqBrowser was designed for ease of use for users with few bioinformatic skills, and incorporates the features of many genome browsers into one platform. Conclusions The features of RNASeqBrowser: (1) RNASeqBrowser integrates UCSC genome browser and NGS visualization tools such as IGV. It extends the functionality of the UCSC genome browser by adding several new types of tracks to show NGS data such as individual raw reads, SNPs and InDels. (2) RNASeqBrowser can dynamically generate RNA secondary structure. It is useful for identifying non-coding RNA such as miRNA. (3) Overlaying NGS wiggle data is helpful in displaying differential expression and is simple to implement in RNASeqBrowser. (4) NGS data accumulates a lot of raw reads. Thus, RNASeqBrowser collapses exact duplicate reads to reduce visualization space. Normal PC’s can show many windows of NGS individual raw reads without much delay. (5) Multiple popup windows of individual raw reads provide users with more viewing space. This avoids existing approaches (such as IGV) which squeeze all raw reads into one window. This will be helpful for visualizing multiple datasets simultaneously. RNASeqBrowser and its manual are freely available at http://www.australianprostatecentre.org/research/software/rnaseqbrowser webcite or http://sourceforge.net/projects/rnaseqbrowser/ webcite

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Background Depression is common after a cardiac event, yet there remain few approaches to management that are both effective and scalable. Purpose We aimed to evaluate the 6-month efficacy and feasibility of a tele-health program (MoodCare) that integrates depression management into a cardiovascular disease risk reduction program for acute coronary syndrome patients with low mood. Methods A two-arm, parallel, randomized design was used comprising 121 patients admitted to one of six hospitals for acute coronary syndrome. Results Significant treatment effects were observed for Patient Health Questionnaire 9 (PHQ9) depression (mean difference [change] = −1.8; p = 0.025; effect size: d = 0.36) for the overall sample, when compared with usual medical care. Results were more pronounced effects for those with a history of depression (mean difference [change] = −2.7; p = 0.043; effect size: d = 0.65). Conclusions MoodCare was effective for improving depression in acute coronary syndrome patients, producing effect sizes exceeding those of some face-to-face psychotherapeutic interventions and pharmacotherapy. (Trial Registration Number: ACTRN1260900038623.)

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Background To date, no genome-wide association study (GWAS) has considered the combined phenotype of asthma with hay fever. Previous analyses of family data from the Tasmanian Longitudinal Health Study provide evidence that this phenotype has a stronger genetic cause than asthma without hay fever. Objective We sought to perform a GWAS of asthma with hay fever to identify variants associated with having both diseases. Methods We performed a meta-analysis of GWASs comparing persons with both physician-diagnosed asthma and hay fever (n = 6,685) with persons with neither disease (n = 14,091). Results At genome-wide significance, we identified 11 independent variants associated with the risk of having asthma with hay fever, including 2 associations reaching this level of significance with allergic disease for the first time: ZBTB10 (rs7009110; odds ratio [OR], 1.14; P = 4 × 10−9) and CLEC16A (rs62026376; OR, 1.17; P = 1 × 10−8). The rs62026376:C allele associated with increased asthma with hay fever risk has been found to be associated also with decreased expression of the nearby DEXI gene in monocytes. The 11 variants were associated with the risk of asthma and hay fever separately, but the estimated associations with the individual phenotypes were weaker than with the combined asthma with hay fever phenotype. A variant near LRRC32 was a stronger risk factor for hay fever than for asthma, whereas the reverse was observed for variants in/near GSDMA and TSLP. Single nucleotide polymorphisms with suggestive evidence for association with asthma with hay fever risk included rs41295115 near IL2RA (OR, 1.28; P = 5 × 10−7) and rs76043829 in TNS1 (OR, 1.23; P = 2 × 10−6). Conclusion By focusing on the combined phenotype of asthma with hay fever, variants associated with the risk of allergic disease can be identified with greater efficiency.

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Genes in the TGF9 signaling pathway play important roles in the regulation of ovarian follicle growth and ovulation rate. Mutations in three genes in this pathway, growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15) and the bone morphogenetic protein receptor B 1 (BMPRB1), influence dizygotic (DZ) twinning rates in sheep. To date, only variants in GDF9 and BMP15, but not their receptors transforming growth factor ss receptor 1 (TGFBR1), bone morphogenetic protein receptor 2 (BMPR2) and BMPR1B, have been investigated with respect to their roles in human DZ twinning. We screened for rare and novel variants in TGFBR1, BMPR2 and BMPR1B in mothers of dizygotic twins (MODZT) from twin-dense families, and assessed association between genotyped and imputed variants and DZ twinning in another large sample of MODZT. Three novel variants were found: a deep intronic variant in BMPR2, and one intronic and one non-synonymous exonic variant in BMPRB1 which would result in the replacement of glutamine by glutamic acid at amino acid position 294 (p.Gln294Glu). None of these variants were predicted to have major impacts on gene function. However, the p.Gln294Glu variant changes the same amino acid as a sheep BMPR1B functional variant and may have functional consequences. Six BMPR1B variants were marginally associated with DZ twinning in the larger case-control sample, but these were no longer significant once multiple testing was taken into account. Our results suggest that variation in the TGF9 signaling pathway type II receptors has limited effects on DZ twinning rates in humans.

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Genome-wide association studies followed by replication provide a powerful approach to map genetic risk factors for asthma. We sought to search for new variants associated with asthma and attempt to replicate the association with four loci reported previously (ORMDL3, PDE4D, DENND1B and IL1RL1). Genome-wide association analyses of individual single nucleotide polymorphisms (SNPs), rare copy number variants (CNVs) and overall CNV burden were carried out in 986 asthma cases and 1846 asthma-free controls from Australia. The most-associated locus in the SNP analysis was ORMDL3 (rs6503525, P = 4.8 x 10(-)(7)). Five other loci were associated with P < 10(-)(5), most notably the chemokine CXC motif ligand 14 (CXCL14) gene (rs31263, P = 7.8 x 10(-)(6)). We found no evidence for association with the specific risk variants reported recently for PDE4D, DENND1B and ILR1L1. However, a variant in IL1RL1 that is in low linkage disequilibrium with that reported previously was associated with asthma risk after accounting for all variants tested (rs10197862, gene wide P = 0.01). This association replicated convincingly in an independent cohort (P = 2.4 x 10(-)(4)). A 300-kb deletion on chromosome 17q21 was associated with asthma risk, but this did not reach experiment-wide significance. Asthma cases and controls had comparable CNV rates, length and number of genes affected by deletions or duplications. In conclusion, we confirm the association between asthma risk and variants in ORMDL3 and identify a novel risk variant in IL1RL1. Follow-up of the 17q21 deletion in larger cohorts is warranted.

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Bactrocera frauenfeldi (Schiner), the ‘mango fruit fly’, is a horticultural pest originating from the Papua New Guinea region. It was first detected in Australia on Cape York Peninsula in north Queensland in 1974 and had spread to Cairns by 1994 and Townsville by 1997. Bactrocera frauenfeldi has not been recorded further south since then despite its invasive potential, an absence of any controls and an abundance of hosts in southern areas. Analysis of cue-lure trapping data from 1997 to 2012 in relation to environmental variables shows that the distribution of B. frauenfeldi in Queensland correlates to locations with a minimum temperature for the coldest month >13.2°C, annual temperature range <19.3°C, mean temperature of the driest quarter >20.2°C, precipitation of the wettest month >268 mm, precipitation of the wettest quarter >697 mm, temperature seasonality <30.9°C (i.e. lower temperature variability) and areas with higher human population per square kilometre. Annual temperature range was the most important variable in predicting this species' distribution. Predictive distribution maps based on an uncorrelated subset of these variables reasonably reflected the current distribution of this species in northern Australia and predicted other areas in the world potentially at risk from invasion by this species. This analysis shows that the distribution of B. frauenfeldi in Australia is correlated to certain environmental variables that have most likely limited this species' spread southward in Queensland. This is of importance to Australian horticulture in demonstrating that B. frauenfeldi is unlikely to establish in horticultural production areas further south than Townsville.

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This study aimed to define the frequency of resistance to critically important antimicrobials (CIAs) [i.e. extended-spectrum cephalosporins (ESCs), fluoroquinolones (FQs) and carbapenems] among Escherichia coli isolates causing clinical disease in Australian food-producing animals. Clinical E. coli isolates (n = 324) from Australian food-producing animals [cattle (n = 169), porcine (n = 114), poultry (n = 32) and sheep (n = 9)] were compiled from all veterinary diagnostic laboratories across Australia over a 1-year period. Isolates underwent antimicrobial susceptibility testing to 18 antimicrobials using the Clinical and Laboratory Standards Institute disc diffusion method. Isolates resistant to CIAs underwent minimum inhibitory concentration determination, multilocus sequence typing (MLST), phylogenetic analysis, plasmid replicon typing, plasmid identification, and virulence and antimicrobial resistance gene typing. The 324 E. coli isolates from different sources exhibited a variable frequency of resistance to tetracycline (29.0–88.6%), ampicillin (9.4–71.1%), trimethoprim/sulfamethoxazole (11.1–67.5%) and streptomycin (21.9–69.3%), whereas none were resistant to imipenem or amikacin. Resistance was detected, albeit at low frequency, to ESCs (bovine isolates, 1%; porcine isolates, 3%) and FQs (porcine isolates, 1%). Most ESC- and FQ-resistant isolates represented globally disseminated E. coli lineages (ST117, ST744, ST10 and ST1). Only a single porcine E. coli isolate (ST100) was identified as a classic porcine enterotoxigenic E. coli strain (non-zoonotic animal pathogen) that exhibited ESC resistance via acquisition of blaCMY-2. This study uniquely establishes the presence of resistance to CIAs among clinical E. coli isolates from Australian food-producing animals, largely attributed to globally disseminated FQ- and ESC-resistant E. coli lineages.

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Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity

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Background The Researching Effective Approaches to Cleaning in Hospitals (REACH) study will generate evidence about the effectiveness and cost-effectiveness of a novel cleaning initiative that aims to improve the environmental cleanliness of hospitals. The initiative is an environmental cleaning bundle, with five interdependent, evidence-based components (training, technique, product, audit and communication) implemented with environmental services staff to enhance hospital cleaning practices. Methods/design The REACH study will use a stepped-wedge randomised controlled design to test the study intervention, an environmental cleaning bundle, in 11 Australian hospitals. All trial hospitals will receive the intervention and act as their own control, with analysis undertaken of the change within each hospital based on data collected in the control and intervention periods. Each site will be randomised to one of the 11 intervention timings with staggered commencement dates in 2016 and an intervention period between 20 and 50 weeks. All sites complete the trial at the same time in 2017. The inclusion criteria allow for a purposive sample of both public and private hospitals that have higher-risk patient populations for healthcare-associated infections (HAIs). The primary outcome (objective one) is the monthly number of Staphylococcus aureus bacteraemias (SABs), Clostridium difficile infections (CDIs) and vancomycin resistant enterococci (VRE) infections, per 10,000 bed days. Secondary outcomes for objective one include the thoroughness of hospital cleaning assessed using fluorescent marker technology, the bio-burden of frequent touch surfaces post cleaning and changes in staff knowledge and attitudes about environmental cleaning. A cost-effectiveness analysis will determine the second key outcome (objective two): the incremental cost-effectiveness ratio from implementation of the cleaning bundle. The study uses the integrated Promoting Action on Research Implementation in Health Services (iPARIHS) framework to support the tailored implementation of the environmental cleaning bundle in each hospital. Discussion Evidence from the REACH trial will contribute to future policy and practice guidelines about hospital environmental cleaning. It will be used by healthcare leaders and clinicians to inform decision-making and implementation of best-practice infection prevention strategies to reduce HAIs in hospitals. Trial registration Australia New Zealand Clinical Trial Registry ACTRN12615000325​505

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Background There is a strong link between antibiotic consumption and the rate of antibiotic resistance. In Australia, the vast majority of antibiotics are prescribed by general practitioners, and the most common indication is for acute respiratory infections. The aim of this study is to assess if implementing a package of integrated, multifaceted interventions reduces antibiotic prescribing for acute respiratory infections in general practice. Methods/design This is a cluster randomised trial comparing two parallel groups of general practitioners in 28 urban general practices in Queensland, Australia: 14 intervention and 14 control practices. The protocol was peer-reviewed by content experts who were nominated by the funding organization. This study evaluates an integrated, multifaceted evidence-based package of interventions implemented over a six month period. The included interventions, which have previously been demonstrated to be effective at reducing antibiotic prescribing for acute respiratory infections, are: delayed prescribing; patient decision aids; communication training; commitment to a practice prescribing policy for antibiotics; patient information leaflet; and near patient testing with C-reactive protein. In addition, two sub-studies are nested in the main study: (1) point prevalence estimation carriage of bacterial upper respiratory pathogens in practice staff and asymptomatic patients; (2) feasibility of direct measures of antibiotic resistance by nose/throat swabbing. The main outcome data are from Australia’s national health insurance scheme, Medicare, which will be accessed after the completion of the intervention phase. They include the number of antibiotic prescriptions and the number of patient visits per general practitioner for periods before and during the intervention. The incidence of antibiotic prescriptions will be modelled using the numbers of patients as the denominator and seasonal and other factors as explanatory variables. Results will compare the change in prescription rates before and during the intervention in the two groups of practices. Semi-structured interviews will be conducted with the general practitioners and practice staff (practice nurse and/or practice manager) from the intervention practices on conclusion of the intervention phase to assess the feasibility and uptake of the interventions. An economic evaluation will be conducted to estimate the costs of implementing the package, and its cost-effectiveness in terms of cost per unit reduction in prescribing. Discussion The results on the effectiveness, cost-effectiveness, acceptability and feasibility of this package of interventions will inform the policy for any national implementation.

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Niche differentiation has been proposed as an explanation for rarity in species assemblages. To test this hypothesis requires quantifying the ecological similarity of species. This similarity can potentially be estimated by using phylogenetic relatedness. In this study, we predicted that if niche differentiation does explain the co-occurrence of rare and common species, then rare species should contribute greatly to the overall community phylogenetic diversity (PD), abundance will have phylogenetic signal, and common and rare species will be phylogenetically dissimilar. We tested these predictions by developing a novel method that integrates species rank abundance distributions with phylogenetic trees and trend analyses, to examine the relative contribution of individual species to the overall community PD. We then supplement this approach with analyses of phylogenetic signal in abundances and measures of phylogenetic similarity within and between rare and common species groups. We applied this analytical approach to 15 long-term temperate and tropical forest dynamics plots from around the world. We show that the niche differentiation hypothesis is supported in six of the nine gap-dominated forests but is rejected in the six disturbance-dominated and three gap-dominated forests. We also show that the three metrics utilized in this study each provide unique but corroborating information regarding the phylogenetic distribution of rarity in communities.

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Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.

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Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25ha), all stems 1cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25 degrees S-61 degrees N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 degrees C), changes in precipitation (up to +/- 30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8g Nm(-2)yr(-1) and 3.1g Sm(-2)yr(-1)), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.