Nurse Expertise: A Critical Resource in the COVID-19 Pandemic Response

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TIMEDELN: A programme for the detection and parametrization of overlapping resonances using the time-delay method

TIMEDELn implements the time-delay method of determining resonance parameters from the characteristic Lorentzian form displayed by the largest eigenvalues of the time-delay matrix. TIMEDELn constructs the time-delay matrix from input K-matrices and analyses its eigenvalues. This new version implements multi-resonance fitting and may be run serially or as a high performance parallel code with three levels of parallelism. TIMEDELn takes K-matrices from a scattering calculation, either read from a file or calculated on a dynamically adjusted grid, and calculates the time-delay matrix. This is then diagonalized, with the largest eigenvalue representing the longest time-delay experienced by the scattering particle. A resonance shows up as a characteristic Lorentzian form in the time-delay: the programme searches the time-delay eigenvalues for maxima and traces resonances when they pass through different eigenvalues, separating overlapping resonances. It also performs the fitting of the calculated data to the Lorentzian form and outputs resonance positions and widths. Any remaining overlapping resonances can be fitted jointly. The branching ratios of decay into the open channels can also be found. The programme may be run serially or in parallel with three levels of parallelism. The parallel code modules are abstracted from the main physics code and can be used independently

Phase I study of TP300 in patients with advanced solid tumors with pharmacokinetic, pharmacogenetic and pharmacodynamic analyses

Background: A Phase I dose escalation first in man study assessed maximum tolerated dose (MTD), dose-limiting toxicity (DLT) and recommended Phase II dose of TP300, a water soluble prodrug of the Topo-1 inhibitor TP3076, and active metabolite, TP3011. <p/>Methods: Eligible patients with refractory advanced solid tumors, adequate performance status, haematologic, renal, and hepatic function. TP300 was given as a 1-hour i.v. infusion 3-weekly and pharmacokinetic (PK) profiles of TP300, TP3076 and TP3011 were analysed. Polymorphisms in CYP2D6, AOX1 and UGT1A1 were studied and DNA strand-breaks measured in peripheral blood mononuclear cells (PBMCs). <p/>Results: 32 patients received TP300 at 1, 2, 4, 6, 8, 10, 12 mg/m2. MTD was 10 mg/m2; DLTs at 12 (2/4 patients) and 10 mg/m2 (3/12) included thrombocytopenia and febrile neutropenia; diarrhea was uncommon. Six patients (five had received irinotecan), had stable disease for 1.5-5 months. TP3076 showed dose proportionality in AUC and Cmax from 1--10 mg/m2. Genetic polymorphisms had no apparent influence on exposure. DNA strand-breaks were detected after TP300 infusion. <p/>Conclusions: TP300 had predictable hematologic toxicity, and diarrhea was uncommon. AUC at MTD is substantially greater than for SN38. TP3076 and TP3011 are equi-potent with SN38, suggesting a PK advantage

The Dawn of Open Access to Phylogenetic Data

The scientific enterprise depends critically on the preservation of and open access to published data. This basic tenet applies acutely to phylogenies (estimates of evolutionary relationships among species). Increasingly, phylogenies are estimated from increasingly large, genome-scale datasets using increasingly complex statistical methods that require increasing levels of expertise and computational investment. Moreover, the resulting phylogenetic data provide an explicit historical perspective that critically informs research in a vast and growing number of scientific disciplines. One such use is the study of changes in rates of lineage diversification (speciation - extinction) through time. As part of a meta-analysis in this area, we sought to collect phylogenetic data (comprising nucleotide sequence alignment and tree files) from 217 studies published in 46 journals over a 13-year period. We document our attempts to procure those data (from online archives and by direct request to corresponding authors), and report results of analyses (using Bayesian logistic regression) to assess the impact of various factors on the success of our efforts. Overall, complete phylogenetic data for ~60% of these studies are effectively lost to science. Our study indicates that phylogenetic data are more likely to be deposited in online archives and/or shared upon request when: (1) the publishing journal has a strong data-sharing policy; (2) the publishing journal has a higher impact factor, and; (3) the data are requested from faculty rather than students. Although the situation appears dire, our analyses suggest that it is far from hopeless: recent initiatives by the scientific community -- including policy changes by journals and funding agencies -- are improving the state of affairs

Age-related difference in susceptibility of ApcMin/+ mice towards the chemopreventive efficacy of dietary aspirin and curcumin

The nonsteroidal anti-inflammatory drug aspirin and the spice curcumin retard adenoma formation when administered long-term to ApcMin/+ mice, a model of human familial adenomatous polyposis coli. Both agents interfere with cyclooxygenase activity. When aspirin is administered to ApcMin/+ mice only postweaning, but not before, it is inefficacious, while curcumin given postweaning is active. Here the hypothesis was tested that dietary aspirin (0.05%) or curcumin (0.2%) prevent or delay adenoma formation in offsprings when administered to ApcMin/+ mothers and up to the end of weaning, but not afterwards. Whereas curcumin was without effect when administered in this way, aspirin reduced numbers of intestinal adenomas by 21%. When aspirin given up to the end of weaning was combined with curcumin administered from the end of weaning for the rest of the animals' lifetime, intestinal adenoma numbers were reduced by 38%. The combination was not superior to intervention postweaning with curcumin alone. These results show that aspirin exerts chemopreventive activity in the ApcMin/+ mouse during tumour initiation/early promotion, while curcumin is efficacious when given at a later stage of carcinogenic progression. Thus, the results suggest that in this mouse model aspirin and curcumin act during different ‘windows’ of neoplastic development

Practice priorities for acute care nursing: A Delphi study

Aims and objectives: To describe the risk and frequency of challenges in acute care nursing, and the practice priorities in Australian hospital wards based upon expert consensus. Background: Health care is facing increasing demands that are negatively impacting upon the safety and quality of nursing care. Design: Delphi Method. Method: A three-round electronic Delphi method was used to collect and synthesise expert consensus opinion of 30 participants in Rounds One and Two of the survey, and 12 participants in Round Three. The study was carried out from July to December 2016. This study complied with the STROBE checklist. Results: High patient acuity or complexity, as well as inadequate bed space on wards, are “very high” risks that occur “often” and “very often,” respectively. The pressure to admit patients, delayed medical review and patient boarding are all “high” risks that occur “often.” Though only occurring “sometimes,” inadequate numbers and skill mix of staff, suboptimal communication and early or inappropriate discharge all pose a “very high” risk to patient care. Conclusion: The key practice priorities for nurse managers should include the design, implementation and evaluation of sustainable system-wide frameworks, processes and models of care that address patient boarding, communication and discharge processes, job satisfaction, staffing numbers and expertise. Relevance to clinical practice: This study provides a description of the challenges that face acute care nursing in the provision of safe and high-quality care. © 2020 John Wiley & Sons Lt

Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

Fairy Tales: Attraction and Stereotypes in Same-Gender Relationships

We examine the process of romantic attraction in same-gender relationships using open and closed-ended questionnaire data from a sample of 120 men and women in Northern California. Agreeableness (e.g., kind, supportive) and Extraversion (e.g., fun, sense of humor) are the two most prominent bases of attraction, followed by Physical Attractiveness (e.g., appearance, sexy). The least important attractors represent traits associated with material success (e.g., financially secure, nice house). We also find evidence of seemingly contradictory attraction processes documented previously in heterosexual romantic relationships, in which individuals become disillusioned with the qualities in a partner that were initially appealing. Our findings challenge common stereotypes of same-gender relationships. The results document broad similarities between same-gender and cross-gender couples in attraction

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

<p>Abstract</p> <p>Background</p> <p>The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-<it>t </it>model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-<it>t </it>(BS<it>t</it>) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.</p> <p>Methods</p> <p>In the simulation study, bivariate residuals were generated using Student's-<it>t </it>distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-<it>t </it>or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-<it>t </it>distributions with unknown degrees of freedom.</p> <p>Results</p> <p>Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-<it>t </it>error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-<it>t </it>model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.</p> <p>Conclusions</p> <p>Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.</p> <p>Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.</p