Diet selection in the Coyote Canis latrans

The Coyote (Canis latrans) is one of the most studied species in North America with at least 445 papers on its diet alone. While this research has yielded excellent reviews of what coyotes eat, it has been inadequate to draw deeper conclusions because no synthesis to date has considered prey availability. We accounted for prey availability by investigating the prey selection of coyotes across its distribution using the traditional Jacobs’ index method, as well as the new iterative preference averaging (IPA) method on scats and biomass. We found that coyotes selected for Dall’s Sheep (Ovis dalli), White-tailed Deer (Odocoileus virginianus), Eastern Cottontail Rabbit (Sylvilagus floridanus), and California Vole (Microtus californicus), which yielded a predator-to-preferred prey mass ratio of 1:2. We also found that coyotes avoided preying on other small mammals, including carnivorans and arboreal species. There was strong concordance between the traditional and IPA method on scats, but this pattern was weakened when biomass was considered. General linear models revealed that coyotes preferred to prey upon larger species that were riskier to hunt, reflecting their ability to hunt in groups, and were least likely to hunt solitary species. Coyotes increasingly selected Mule Deer (O. hemionus) and Snowshoe Hare (Lepus americanus) at higher latitudes, whereas Black-tailed Jackrabbit (L. californicus) were increasingly selected toward the tropics. Mule Deer were increasingly selected at higher coyote densities, while Black-tailed Jackrabbit were increasingly avoided at higher coyote densities. Coyote predation could constrain the realized niche of prey species at the distributional limits of the predator through their increased efficiency of predation reflected in increased prey selection values. These results are integral to improved understandings of Coyote ecology and can inform predictive analyses allowing for spatial variation, which ultimately will lead to better understandings about the ecological role of the coyote across different ecosystems

Having a word with yourself:neural correlates of self-criticism and self-reassurance

Self-criticism is strongly correlated with a range of psychopathologies, such as depression, eating disorders and anxiety. In contrast, self-reassurance is inversely associated with such psychopathologies. Despite the importance of self-judgements and evaluations, little is known about the neurophysiology of these internal processes. The current study therefore used a novel fMRI task to investigate the neuronal correlates of self-criticism and self-reassurance. Participants were presented statements describing two types of scenario, with the instruction to either imagine being self-critical or self-reassuring in that situation. One scenario type focused on a personal setback, mistake or failure, which would elicit negative emotions, whilst the second was of a matched neutral event. Self-criticism was associated with activity in lateral prefrontal cortex (PFC) regions and dorsal anterior cingulate (dAC), therefore linking self-critical thinking to error processing and resolution, and also behavioural inhibition. Self-reassurance was associated with left temporal pole and insula activation, suggesting that efforts to be self-reassuring engage similar regions to expressing compassion and empathy towards others. Additionally, we found a dorsal/ventral PFC divide between an individual's tendency to be self-critical or self-reassuring. Using multiple regression analyses, dorsolateral PFC activity was positively correlated with high levels of self-criticism (assessed via self-report measure), suggesting greater error processing and behavioural inhibition in such individuals. Ventrolateral PFC activity was positively correlated with high self-reassurance. Our findings may have implications for the neural basis of a range of mood disorders that are characterised by a preoccupation with personal mistakes and failures, and a self-critical response to such events

Adjunctive rifampicin for Staphylococcus aureus bacteraemia (ARREST): a multicentre, randomised, double-blind, placebo-controlled trial.

BACKGROUND: Staphylococcus aureus bacteraemia is a common cause of severe community-acquired and hospital-acquired infection worldwide. We tested the hypothesis that adjunctive rifampicin would reduce bacteriologically confirmed treatment failure or disease recurrence, or death, by enhancing early S aureus killing, sterilising infected foci and blood faster, and reducing risks of dissemination and metastatic infection. METHODS: In this multicentre, randomised, double-blind, placebo-controlled trial, adults (≥18 years) with S aureus bacteraemia who had received ≤96 h of active antibiotic therapy were recruited from 29 UK hospitals. Patients were randomly assigned (1:1) via a computer-generated sequential randomisation list to receive 2 weeks of adjunctive rifampicin (600 mg or 900 mg per day according to weight, oral or intravenous) versus identical placebo, together with standard antibiotic therapy. Randomisation was stratified by centre. Patients, investigators, and those caring for the patients were masked to group allocation. The primary outcome was time to bacteriologically confirmed treatment failure or disease recurrence, or death (all-cause), from randomisation to 12 weeks, adjudicated by an independent review committee masked to the treatment. Analysis was intention to treat. This trial was registered, number ISRCTN37666216, and is closed to new participants. FINDINGS: Between Dec 10, 2012, and Oct 25, 2016, 758 eligible participants were randomly assigned: 370 to rifampicin and 388 to placebo. 485 (64%) participants had community-acquired S aureus infections, and 132 (17%) had nosocomial S aureus infections. 47 (6%) had meticillin-resistant infections. 301 (40%) participants had an initial deep infection focus. Standard antibiotics were given for 29 (IQR 18-45) days; 619 (82%) participants received flucloxacillin. By week 12, 62 (17%) of participants who received rifampicin versus 71 (18%) who received placebo experienced treatment failure or disease recurrence, or died (absolute risk difference -1·4%, 95% CI -7·0 to 4·3; hazard ratio 0·96, 0·68-1·35, p=0·81). From randomisation to 12 weeks, no evidence of differences in serious (p=0·17) or grade 3-4 (p=0·36) adverse events were observed; however, 63 (17%) participants in the rifampicin group versus 39 (10%) in the placebo group had antibiotic or trial drug-modifying adverse events (p=0·004), and 24 (6%) versus six (2%) had drug interactions (p=0·0005). INTERPRETATION: Adjunctive rifampicin provided no overall benefit over standard antibiotic therapy in adults with S aureus bacteraemia. FUNDING: UK National Institute for Health Research Health Technology Assessment

Application of smooth tests of goodness of fit to generalized linear models

Research Doctorate - Doctor of Philosophy (PhD)Statistical models are an essential part of data analysis across many diverse fields. They are used to test research hypotheses, aid decision making, estimate effect sizes and/or improve understanding of the underlying processes generating the data of interest. However it is essential to critically assess any fitted model, confirming that the model really is compatible with the data, before meaningful conclusions are possible. Generalized linear models (GLMs) provide a flexible modelling framework encompassing many commonly used models including the normal linear model, logistic regression model and Poisson regression model. This thesis explores how the smooth testing concept - originally proposed by Neyman (1937) and further developed by Rayner et al. (2009) among others - can be used to test the distributional assumption in a GLM. However sensible interpretation of this test, or any other test used to assess the fit of a GLM, must recognize that: * the stochastic, deterministic and link components that make up a GLM should all be considered when assessing model validity, * the validity of any one of these three components cannot be sensibly considered in isolation as it is confounded by the validity of the other two. It is therefore important to consider how the smooth test developed in this thesis might be usefully incorporated into an overall model development strategy for GLMs, either replacing or supplementing existing diagnostic tools. Simulation studies demonstrate that the power of the smooth test is competitive with other existing tests. However, it also offers the possibility of improved diagnostic ability through the breakdown of the overall smooth test statistic into a sum of squares of interpretable components. The SmoothGLM package has been developed which implements the smooth test in a form that can be easily applied to models fitted using the standard glm() function within the R statistical computing environment

Generalised score and Wald tests

The generalised score and Wald tests are described and related to their nongeneralised versions. Two interesting applications are discussed. In the first a new test for the Behrens-Fisher problem is derived. The second is testing homogeneity of variances from multiple univariate normal populations

Recent Extensions to the Cochran–Mantel–Haenszel Tests

The Cochran–Mantel–Haenszel (CMH) methodology is a suite of tests applicable to particular tables of count data. The inference is conditional on the treatment and outcome totals on each stratum being known before sighting the data. The CMH tests are important for analysing randomised blocks data when the responses are categorical rather than continuous. This overview of some recent extensions to CMH testing first describes the traditional CMH tests and then explores new alternative presentations of the ordinal CMH tests. Next, the ordinal CMH tests will be extended so they can be used to test for higher moment effects. Finally, unconditional analogues of the extended CMH tests will be developed

Assessing Poisson and logistic regression models using smooth tests

A smooth testing approach has been used to develop a test of the distributional assumption for generalized linear models. Application of this test to help assess Poisson and logistic regression models is discussed in this paper and power is compared to some common tests

Testing the Poisson regression model

A smooth test of the Poisson assumption in the Poisson regression generalised linear model is derived