179 research outputs found
Bridging the data gaps in the epidemiology of hepatitis C virus infection in Malaysia using multi-parameter evidence synthesis
BACKGROUND: Collecting adequate information on key epidemiological indicators is a prerequisite to informing a public health response to reduce the impact of hepatitis C virus (HCV) infection in Malaysia. Our goal was to overcome the acute data shortage typical of low/middle income countries using statistical modelling to estimate the national HCV prevalence and the distribution over transmission pathways as of the end of 2009. METHODS: Multi-parameter evidence synthesis methods were applied to combine all available relevant data sources - both direct and indirect - that inform the epidemiological parameters of interest. RESULTS: An estimated 454,000 (95% credible interval [CrI]: 392,000 to 535,000) HCV antibody-positive individuals were living in Malaysia in 2009; this represents 2.5% (95% CrI: 2.2-3.0%) of the population aged 15-64 years. Among males of Malay ethnicity, for 77% (95% CrI: 69-85%) the route of probable transmission was active or a previous history of injecting drugs. The corresponding proportions were smaller for male Chinese and Indian/other ethnic groups (40% and 71%, respectively). The estimated prevalence in females of all ethnicities was 1% (95% CrI: 0.6 to 1.4%); 92% (95% CrI: 88 to 95%) of infections were attributable to non-drug injecting routes of transmission. CONCLUSIONS: The prevalent number of persons living with HCV infection in Malaysia is estimated to be very high. Low/middle income countries often lack a comprehensive evidence base; however, evidence synthesis methods can assist in filling the data gaps required for the development of effective policy to address the future public health and economic burden due to HCV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-014-0564-6) contains supplementary material, which is available to authorized users
Genome of the epsilonproteobacterial chemolithoautotroph Sulfurimonas denitrificans
Author Posting. © American Society for Microbiology, 2008. This article is posted here by permission of American Society for Microbiology for personal use, not for redistribution. The definitive version was published in Applied and Environmental Microbiology 74 (2008): 1145-1156, doi:10.1128/AEM.01844-07.Sulfur-oxidizing epsilonproteobacteria are common in a variety of sulfidogenic environments. These autotrophic and mixotrophic sulfur-oxidizing bacteria are believed to contribute substantially to the oxidative portion of the global sulfur cycle. In order to better understand the ecology and roles of sulfur-oxidizing epsilonproteobacteria, in particular those of the widespread genus Sulfurimonas, in biogeochemical cycles, the genome of Sulfurimonas denitrificans DSM1251 was sequenced. This genome has many features, including a larger size (2.2 Mbp), that suggest a greater degree of metabolic versatility or responsiveness to the environment than seen for most of the other sequenced epsilonproteobacteria. A branched electron transport chain is apparent, with genes encoding complexes for the oxidation of hydrogen, reduced sulfur compounds, and formate and the reduction of nitrate and oxygen. Genes are present for a complete, autotrophic reductive citric acid cycle. Many genes are present that could facilitate growth in the spatially and temporally heterogeneous sediment habitat from where Sulfurimonas denitrificans was originally isolated. Many resistance-nodulation-development family transporter genes (10 total) are present; of these, several are predicted to encode heavy metal efflux transporters. An elaborate arsenal of sensory and regulatory protein-encoding genes is in place, as are genes necessary to prevent and respond to oxidative stress.This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory, University of California, under contract W-7405-ENG-48. Genome closure was funded in part by a USF Innovative Teaching Grant (K.M.S.). S.M.S. received partial support through a fellowship from the Hanse Wissenschaftskolleg in Delmenhorst, Germany (http://www.h-w-k.de), and NSF grant OCE-0452333. K.M.S. is grateful for support from NSF grant MCB-0643713. M.H. was supported by a WHOI postdoctoral scholarship. M.G.K. was supported in part by incentive funds provided by the UofL-EVPR office, the KY Science and Engineering Foundation (KSEF-787-RDE-007), and the National Science Foundation (EF-0412129)
The U.S. Inland Creel and Angler Survey Catalog (CreelCat): Development, Applications, and Opportunities
Inland recreational fishing, defined as primarily leisure-driven fishing in freshwaters, is a popular pastime in the USA. State natural resource agencies endeavor to provide high-quality and sustainable fishing opportunities for anglers. Managers often use creel and other angler survey data to inform state- and waterbody-level management efforts. Despite the broad implementation of angler surveys and their importance to fisheries management at state scales, regional and national coordination among these activities is minimal, limiting data applicability for larger-scale management practices and research. Here, we introduce the U.S. Inland Creel and Angler Survey Catalog (CreelCat), a first-of-its-kind, publicly available national database of angler survey data that establishes a baseline of national inland recreational fishing metrics. We highlight research and management applications to help support sustainable inland recreational fishing practices, consider cautions, and make recommendations for implementation
The RHIC SPIN Program: Achievements and Future Opportunities
Time and again, spin has been a key element in the exploration of fundamental
physics. Spin-dependent observables have often revealed deficits in the assumed
theoretical framework and have led to novel developments and concepts. Spin is
exploited in many parity-violating experiments searching for physics beyond the
Standard Model or studying the nature of nucleon-nucleon forces. The RHIC spin
program plays a special role in this grand scheme: it uses spin to study how a
complex many-body system such as the proton arises from the dynamics of QCD.
Many exciting results from RHIC spin have emerged to date, most of them from
RHIC running after the 2007 Long Range Plan. In this document we present
highlights from the RHIC program to date and lay out the roadmap for the
significant advances that are possible with future RHIC running
What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
From 2017 to 2019 the Text REtrieval Conference (TREC) held a challenge task
on precision medicine using documents from medical publications (PubMed) and
clinical trials. Despite lots of performance measurements carried out in these
evaluation campaigns, the scientific community is still pretty unsure about the
impact individual system features and their weights have on the overall system
performance. In order to overcome this explanatory gap, we first determined
optimal feature configurations using the Sequential Model-based Algorithm
Configuration (SMAC) program and applied its output to a BM25-based search
engine. We then ran an ablation study to systematically assess the individual
contributions of relevant system features: BM25 parameters, query type and
weighting schema, query expansion, stop word filtering, and keyword boosting.
For evaluation, we employed the gold standard data from the three TREC-PM
installments to evaluate the effectiveness of different features using the
commonly shared infNDCG metric.Comment: Accepted for SIGIR2020, 10 page
Multi-drug resistance, inappropriate initial antibiotic therapy and mortality in Gram-negative severe sepsis and septic shock: A retrospective cohort study
INTRODUCTION: The impact of in vitro resistance on initially appropriate antibiotic therapy (IAAT) remains unclear. We elucidated the relationship between non-IAAT and mortality, and between IAAT and multi-drug resistance (MDR) in sepsis due to Gram-negative bacteremia (GNS). METHODS: We conducted a single-center retrospective cohort study of adult intensive care unit patients with bacteremia and severe sepsis/septic shock caused by a gram-negative (GN) organism. We identified the following MDR pathogens: MDR P. aeruginosa, extended spectrum beta-lactamase and carbapenemase-producing organisms. IAAT was defined as exposure within 24 hours of infection onset to antibiotics active against identified pathogens based on in vitro susceptibility testing. We derived logistic regression models to examine a) predictors of hospital mortality and b) impact of MDR on non-IAAT. Proportions are presented for categorical variables, and median values with interquartile ranges (IQR) for continuous. RESULTS: Out of 1,064 patients with GNS, 351 (29.2%) did not survive hospitalization. Non-survivors were older (66.5 (55, 73.5) versus 63 (53, 72) years, P = 0.036), sicker (Acute Physiology and Chronic Health Evaluation II (19 (15, 25) versus 16 (12, 19), P <0.001), and more likely to be on pressors (odds ratio (OR) 2.79, 95% confidence interval (CI) 2.12 to 3.68), mechanically ventilated (OR 3.06, 95% CI 2.29 to 4.10) have MDR (10.0% versus 4.0%, P <0.001) and receive non-IAAT (43.4% versus 14.6%, P <0.001). In a logistic regression model, non-IAAT was an independent predictor of hospital mortality (adjusted OR 3.87, 95% CI 2.77 to 5.41). In a separate model, MDR was strongly associated with the receipt of non-IAAT (adjusted OR 13.05, 95% CI 7.00 to 24.31). CONCLUSIONS: MDR, an important determinant of non-IAAT, is associated with a three-fold increase in the risk of hospital mortality. Given the paucity of therapies to cover GN MDRs, prevention and development of new agents are critical
Predictors of hospital mortality among septic ICU patients with Acinetobacter spp. bacteremia: A cohort study
BACKGROUND: We hypothesized that among septic ICU patients with Acinetobacter spp. bacteremia (Ac-BSI), carbapenem-resistant Acinetobacter spp. (CRAc) increase risk for inappropriate initial antibiotic therapy (non-IAAT), and non-IAAT is a predictor of hospital death. METHODS: We conducted a retrospective cohort study of adult septic ICU patients with Ac-BSI. Non-IAAT was defined as exposure to initially prescribed antibiotics not active against the pathogen based on in vitro susceptibility testing, and having no exposure to appropriate antimicrobial treatment within 24 hours of drawing positive culture. We compared patients who died to those who survived, and derived regression models to identify predictors of hospital mortality and of non-IAAT. RESULTS: Out of 131 patients with Ac-BSI, 65 (49.6%) died (non-survivors, NS). NS were older (63 [51, 76] vs. 56 [45, 66] years, p = 0.014), and sicker than survivors (S): APACHE II (24 [19, 31] vs. 18 [13, 22], p < 0.001) and Charlson (5 [2, 8] vs. 3 [1, 6], p = 0.009) scores. NS were also more likely than S to require pressors (75.4% vs. 42.4%, p < 0.001) and mechanical ventilation (75.4% vs. 53.0%, p = 0.008). Both CRAc (69.2% vs. 47.0%, p = 0.010) and non-IAAT (83.1% vs. 59.1%, p = 0.002) were more frequent among NS than S. In multivariate analyses, non-IAAT emerged as an independent predictor of hospital death (risk ratio [RR] 1.42, 95% confidence interval [CI] 1.10-1.58), while CRAc was the single strongest predictor of non-IAAT (RR 2.66, 95% CI 2.43-2.72). CONCLUSIONS: Among septic ICU patients with Ac-BSI, non-IAAT predicts mortality. Carbapenem resistance appears to mediate the relationship between non-IAAT and mortality
The khmer software package: enabling efficient nucleotide sequence analysis
The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/
The khmer software package: enabling efficient nucleotide sequence analysis [version 1; referees: 2 approved, 1 approved with reservations]
The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/
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