21-cm signatures of residual HI inside cosmic HII regions during reionization

We investigate the impact of sinks of ionizing radiation on the reionization-era 21-cm signal, focusing on 1-point statistics. We consider sinks in both the intergalactic medium and inside galaxies. At a fixed filling factor of HII regions, sinks will have two main effects on the 21-cm morphology: (i) as inhomogeneous absorbers of ionizing photons they result in smaller and more widespread cosmic HII patches; and (ii) as reservoirs of neutral gas they contribute a non-zero 21-cm signal in otherwise ionized regions. Both effects damp the contrast between neutral and ionized patches during reionization, making detection of the epoch of reionization with 21-cm interferometry more challenging. Here we systematically investigate these effects using the latest semi-numerical simulations. We find that sinks dramatically suppress the peak in the redshift evolution of the variance, corresponding to the midpoint of reionization. As previously predicted, skewness changes sign at midpoint, but the fluctuations in the residual HI suppress a late-time rise. Furthermore, large levels of residual HI dramatically alter the evolution of the variance, skewness and power spectrum from that seen at lower levels. In general, the evolution of the large-scale modes provides a better, cleaner, higher signal-to-noise probe of reionization.Comment: Minor edits to agree with MNRAS published versio

Flexible memory controls sperm competition responses to male Drosophila melanogaster

Males of many species use social cues to predict sperm competition (SC) and tailor their reproductive strategies, such as ejaculate or behavioural investment, accordingly. While these plastic strategies are widespread, the underlying mechanisms remain largely unknown. Plastic behaviour requires individuals to learn and memorize cues associated with environmental change before using this experience to modify behaviour. Drosophila melanogaster respond to an increase in SC threat by extending mating duration after exposure to a rival male. This behaviour shows lag times between environmental change and behavioural response suggestive of acquisition and loss of memory. Considering olfaction is important for a male's ability to assess the SC environment, we hypothesized that an olfactory learning and memory pathway may play a key role in controlling this plastic behaviour. We assessed the role of genes and brain structures known to be involved in learning and memory. We show that SC responses depend on anaesthesia-sensitive memory, specifically the genes rut and amn. We also show that the γ lobes of the mushroom bodies are integral to the control of plastic mating behaviour. These results reveal the genetic and neural properties required for reacting to changes in the SC environment

Health and Medical Researcher Publishing Patterns and How Libraries Support Them

Changing business models in scholarly publishing means that researchers have increased choices as to where to submit their articles. Choices are made on the basis of perceived quality of the journal, the speed of publishing, and how close a match there is between the journal scope and the article topic. Additionally, there is an increasing concern as to whether the journals are predatory. This paper reports on a study which sought to understand how health researchers go about selecting where to publish and the support that they receive in this regard from librarians and related staff. The research confirms that knowledge of a specific journal is still the predominant factor for researchers and that they prefer to rely on their own judgment. Librarians are providing the tools such as databases and whitelists by which better choices can be made whilst exploring new roles in advising and training researchers. Predatory journals are being selected by some, chiefly as a consequence of a lack of awareness amongst researchers and the need for some to publish swiftly and at low cost

When Does Spatial Diversification Usefully Maximize the Durability of Crop Disease Resistance?

Maximizing the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialized. The factors that interact with and determine the magnitude of this spatial suppressive effect are not currently well understood, however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multiseason semidiscrete epidemiological model tracks spatial spread of wild-type and resistance-breaking pathogen strains, and incorporates a localized reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance-breaking trait, the efficacy of host resistance, and the length of the timeframe of interest all influence the strength of the spatial diversification effect. A key result is that spatial diversification has the strongest beneficial effect at intermediate fitness costs of the resistance-breaking trait, an effect driven by a complex set of nonlinear interactions. On the other hand, however, if the resistance-breaking strain is not fit enough to invade the landscape, then a partially effective resistance gene can result in spatial diversification actually worsening the epidemic. These results allow us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modeling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host-pathogen disease systems.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license

Point process models for novelty detection on spatial point patterns and their extremes

Novelty detection is a particular example of pattern recognition identifying patterns that departure from some model of "normal behaviour". The classification of point patterns is considered that are defined as sets of N observations of a multivariate random variable X and where the value N follows a discrete stochastic distribution. The use of point process models is introduced that allow us to describe the length N as well as the geometrical configuration in data space of such patterns. It is shown that such infinite dimensional study can be translated into a one-dimensional study that is analytically tractable for a multivariate Gaussian distribution. Moreover, for other multivariate distributions, an analytic approximation is obtained, by the use of extreme value theory, to model point patterns that occur in low-density regions as defined by X. The proposed models are demonstrated on synthetic and real-world data sets

Modelling physiological deterioration in post-operative patient vital-sign data

Patients who undergo upper-gastrointestinal surgery have a high incidence of post-operative complications, often requiring admission to the intensive care unit several days after surgery. A dataset comprising observational vital-sign data from 171 post-operative patients taking part in a two-phase clinical trial at the Oxford Cancer Centre, was used to explore the trajectory of patients’ vital-sign changes during their stay in the post-operative ward using both univariate and multivariate analyses. A model of normality based vital-sign data from patients who had a “normal” recovery was constructed using a kernel density estimate, and tested with “abnormal” data from patients who deteriorated sufficiently to be re-admitted to the intensive care unit. The vital-sign distributions from “normal” patients were found to vary over time from admission to the post-operative ward to their discharge home, but no significant changes in their distributions were observed from halfway through their stay on the ward to the time of discharge. The model of normality identified patient deterioration when tested with unseen “abnormal” data, suggesting that such techniques may be used to provide early warning of adverse physiological events

Massive pulmonary embolism in patients with extreme bleeding risk: a case series on the successful use of ultrasound-assisted, catheter directed thrombolysis in a district general hospital

This is the final version. Available from the publisher via the DOI in this record.Massive pulmonary embolism (PE), characterised by profound arterial hypotension, is a life-threatening emergency with a 90-day mortality of over 50%. Systemic thrombolysis can signifcantly reduce the risk of death or cardiovascular collapse in these patients, by around 50%, but these benefts are ofset by a fvefold increased risk of intracranial haemorrhage and major bleeding, which may limit its use in patients at high risk of catastrophic haemorrhage. We describe a case series of 3 patients presenting with massive PE, each with extreme risk of bleeding and contra-indication to systemic thrombolysis, treated successfully with ultrasound-assisted, catheter directed thrombolysis (U-ACDT). Our experience of this novel technique using the EkoSonic Endovascular System (Ekos, BTG, London, UK) on carefully selected patients has demonstrated the potential to improve clinical status in shocked patients, with minimal bleed risk. There have been several clinical studies evaluating the Ekos system. Both the ULTIMA and SEATTLE II studies have shown signifcant reductions in RV/LV ratio by CT scanning when compared to standard anticoagulation in patients with intermediate-risk PE, with minimal bleeding complications. However, there is a pressing need for a randomised trial demonstrating improvement in robust clinical outcomes when comparing U-ACDT to simple anticoagulation. We believe that this case series adds new insight and highlights the potential of catheter directed thrombolysis in this high-risk patient cohort and consideration should be made to its use in cases where systemic thrombolysis is felt to be too high ris

Virtual interactive practice™: Utilising healthcare information systems to contexturalise the skills associated with clinical decision making within nurse education

This paper reports on a Virtual Interactive Practice (VIP) project that has the potential to revolutionise the educational delivery and learning of clinical skills complementing "real" practice. The focus is currently on nurse learning but the principles could equally be applied to multi and inter-professional learning and clinical decision-making. This project represents a new model to enhance clinical skill acquisition and clinical reasoning using a structured competency base. Integral to this is a strong partnership between education and practice utilising "real" live and recorded anonymised patient data from a critical care clinical information system (CIS) within a large district general hospital to structure scenarios fostering problem-based learning. This educational practice interface enables the synthesis of clinical data using virtual technology and sophisticated scenario-based simulation within a skills laboratory. The aim is to enhance the more ad hoc system of learning within conventional practice placements. Early findings suggest that VIP enhances practice providing a safe but challenging learning experience with the benefit of instant performance feedback to students

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures