Intensive care doctors and nurses personal preferences for intensive Care, as compared to the general population: a discrete choice experiment

Background To test the hypothesis that Intensive Care Unit (ICU) doctors and nurses differ in their personal preferences for treatment from the general population, and whether doctors and nurses make different choices when thinking about themselves, as compared to when they are treating a patient. Methods Cross sectional, observational study conducted in 13 ICUs in Australia in 2017 using a discrete choice experiment survey. Respondents completed a series of choice sets, based on hypothetical situations which varied in the severity or likelihood of: death, cognitive impairment, need for prolonged treatment, need for assistance with care or requiring residential care. Results A total of 980 ICU staff (233 doctors and 747 nurses) participated in the study. ICU staff place the highest value on avoiding ending up in a dependent state. The ICU staff were more likely to choose to discontinue therapy when the prognosis was worse, compared with the general population. There was consensus between ICU staff personal views and the treatment pathway likely to be followed in 69% of the choices considered by nurses and 70% of those faced by doctors. In 27% (1614/5945 responses) of the nurses and 23% of the doctors (435/1870 responses), they felt that aggressive treatment would be continued for the hypothetical patient but they would not want that for themselves. Conclusion The likelihood of returning to independence (or not requiring care assistance) was reported as the most important factor for ICU staff (and the general population) in deciding whether to receive ongoing treatments. Goals of care discussions should focus on this, over likelihood of survival

Numerical study of duality and universality in a frozen superconductor

The three-dimensional integer-valued lattice gauge theory, which is also known as a "frozen superconductor," can be obtained as a certain limit of the Ginzburg-Landau theory of superconductivity, and is believed to be in the same universality class. It is also exactly dual to the three-dimensional XY model. We use this duality to demonstrate the practicality of recently developed methods for studying topological defects, and investigate the critical behavior of the phase transition using numerical Monte Carlo simulations of both theories. On the gauge theory side, we concentrate on the vortex tension and the penetration depth, which map onto the correlation lengths of the order parameter and the Noether current in the XY model, respectively. We show how these quantities behave near the critical point, and that the penetration depth exhibits critical scaling only very close to the transition point. This may explain the failure of superconductor experiments to see the inverted XY model scaling.Comment: 17 pages, 18 figures. Updated to match the version published in PRB (http://link.aps.org/abstract/PRB/v67/e014525) on 27 Jan 200

A framework for orthology assignment from gene rearrangement data

Abstract. Gene rearrangements have successfully been used in phylogenetic reconstruction and comparative genomics, but usually under the assumption that all genomes have the same gene content and that no gene is duplicated. While these assumptions allow one to work with organellar genomes, they are too restrictive when comparing nuclear genomes. The main challenge is how to deal with gene families, specifically, how to identify orthologs. While searching for orthologies is a common task in computational biology, it is usually done using sequence data. We approach that problem using gene rearrangement data, provide an optimization framework in which to phrase the problem, and present some preliminary theoretical results.

Short-lived Nuclei in the Early Solar System: Possible AGB Sources

(Abridged) We review abundances of short-lived nuclides in the early solar system (ESS) and the methods used to determine them. We compare them to the inventory for a uniform galactic production model. Within a factor of two, observed abundances of several isotopes are compatible with this model. I-129 is an exception, with an ESS inventory much lower than expected. The isotopes Pd-107, Fe-60, Ca-41, Cl-36, Al-26, and Be-10 require late addition to the solar nebula. Be-10 is the product of particle irradiation of the solar system as probably is Cl-36. Late injection by a supernova (SN) cannot be responsible for most short-lived nuclei without excessively producing Mn-53; it can be the source of Mn-53 and maybe Fe-60. If a late SN is responsible for these two nuclei, it still cannot make Pd-107 and other isotopes. We emphasize an AGB star as a source of nuclei, including Fe-60 and explore this possibility with new stellar models. A dilution factor of about 4e-3 gives reasonable amounts of many nuclei. We discuss the role of irradiation for Al-26, Cl-36 and Ca-41. Conflict between scenarios is emphasized as well as the absence of a global interpretation for the existing data. Abundances of actinides indicate a quiescent interval of about 1e8 years for actinide group production in order to explain the data on Pu-244 and new bounds on Cm-247. This interval is not compatible with Hf-182 data, so a separate type of r-process is needed for at least the actinides, distinct from the two types previously identified. The apparent coincidence of the I-129 and trans-actinide time scales suggests that the last actinide contribution was from an r-process that produced actinides without fission recycling so that the yields at Ba and below were governed by fission.Comment: 92 pages, 14 figure files, in press at Nuclear Physics

Grain Surface Models and Data for Astrochemistry

AbstractThe cross-disciplinary field of astrochemistry exists to understand the formation, destruction, and survival of molecules in astrophysical environments. Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. A broad consensus has been reached in the astrochemistry community on how to suitably treat gas-phase processes in models, and also on how to present the necessary reaction data in databases; however, no such consensus has yet been reached for grain-surface processes. A team of ∼25 experts covering observational, laboratory and theoretical (astro)chemistry met in summer of 2014 at the Lorentz Center in Leiden with the aim to provide solutions for this problem and to review the current state-of-the-art of grain surface models, both in terms of technical implementation into models as well as the most up-to-date information available from experiments and chemical computations. This review builds on the results of this workshop and gives an outlook for future directions

ARGONAUT II study of the in vitro activity of plazomicin against carbapenemase-producing klebsiella pneumoniae

Plazomicin was tested against 697 recently acquired carbapenemresistant Klebsiella pneumoniae isolates from the Great Lakes region of the United States. Plazomicin MIC50 and MIC90 values were 0.25 and 1 mg/liter, respectively; 680 isolates (97.6%) were susceptible (MICs of ≤2 mg/liter), 9 (1.3%) intermediate (MICs of 4 mg/liter), and 8 (1.1%) resistant (MICs of>32 mg/liter). Resistance was associated with rmtF-, rmtB-, or armA-encoded 16S rRNA methyltransferases in all except 1 isolate

Identifying the transcriptional response of cancer and inflammation-related genes in lung cells in relation to ambient air chemical mixtures in Houston, Texas

Atmospheric pollution represents a complex mixture of air chemicals that continually interact and transform, making it difficult to accurately evaluate associated toxicity responses representative of real-world exposure. This study leveraged data from a previously published article and reevaluated lung cell transcriptional response induced by outdoor atmospheric pollution mixtures using field-based exposure conditions in the industrialized Houston Ship Channel. The tested hypothesis was that individual and co-occurring chemicals in the atmosphere relate to altered expression of critical genes involved in inflammation and cancer-related processes in lung cells. Human lung cells were exposed at an air−liquid interface to ambient air mixtures for 4 h, with experiments replicated across 5 days. Real-time monitoring of primary and secondary gas-phase pollutants, as well as other atmospheric conditions, was simultaneously conducted. Transcriptional analysis of exposed cells identified critical genes showing differential expression associated with both individual and chemical mixtures. The individual pollutant identified with the largest amount of associated transcriptional response was benzene. Tumor necrosis factor (TNF) and interferon regulatory factor 1 (IRFN1) were identified as key upstream transcription factor regulators of the cellular response to benzene. This study is among the first to measure lung cell transcriptional responses in relation to real-world, gas-phase air mixtures

Limits on anomalous trilinear gauge boson couplings from WW, WZ and Wgamma production in pp-bar collisions at sqrt{s}=1.96 TeV

We present final searches of the anomalous gammaWW and ZWW trilinear gauge boson couplings from WW and WZ production using lepton plus dijet final states and a combination with results from Wgamma, WW, and WZ production with leptonic final states. The analyzed data correspond to up to 8.6/fb of integrated luminosity collected by the D0 detector in pp-bar collisions at sqrt{s}=1.96 TeV. We set the most stringent limits at a hadron collider to date assuming two different relations between the anomalous coupling parameters Delta\kappa_\gamma, lambda, and Delta g_1^Z for a cutoff energy scale Lambda=2 TeV. The combined 68% C.L. limits are -0.057<Delta\kappa_\gamma<0.154, -0.015<lambda<0.028, and -0.008<Delta g_1^Z<0.054 for the LEP parameterization, and -0.007<Delta\kappa<0.081 and -0.017<lambda<0.028 for the equal couplings parameterization. We also present the most stringent limits of the W boson magnetic dipole and electric quadrupole moments.Comment: 10 pages, 5 figures, submitted to PL

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types