Numerical simulations of bubble-induced star formation in dwarf irregular galaxies with a novel stellar feedback scheme

To study the star formation and feedback mechanism, we simulate the evolution of an isolated dwarf irregular galaxy (dIrr) in a fixed dark matter halo, similar in size to WLM. We use the new version of our original N-body/smoothed particle chemodynamics code, GCD+, which adopts improved hydrodynamics, metal diffusion between the gas particles and new modelling of star formation and stellar wind and supernovae (SNe) feedback. Comparing the simulations with and without stellar feedback effects, we demonstrate that the collisions of bubbles produced by strong feedback can induce star formation in a more widely spread area. We also demonstrate that the metallicity in star forming regions is kept low due to the mixing of the metal-rich bubbles and the metal-poor inter-stellar medium. Our simulations also suggest that the bubble-induced star formation leads to many counter-rotating stars. The bubble-induced star formation could be a dominant mechanism to maintain star formation in dIrrs, which is different from larger spiral galaxies where the non-axisymmetric structures, such as spiral arms, are a main driver of star formation

Treatment-seeking rates in malaria endemic countries

BACKGROUND: The proportion of individuals who seek treatment for fever is an important quantity in understanding access to and use of health systems, as well as for interpreting data on disease incidence from routine surveillance systems. For many malaria endemic countries (MECs), treatment-seeking information is available from national household surveys. The aim of this paper was to assemble sub-national estimates of treatment-seeking behaviours and to predict national treatment-seeking measures for all MECs lacking household survey data. METHODS: Data on treatment seeking for fever were obtained from Demographic and Health Surveys, Malaria Indicator Surveys and Multiple Cluster Indicator Surveys for every MEC and year that data were available. National-level social, economic and health-related variables were gathered from the World Bank as putative covariates of treatment-seeking rates. A generalized additive mixed model (GAMM) was used to estimate treatment-seeking behaviours for countries where survey data were unavailable. Two separate models were developed to predict the proportion of fever cases that would seek treatment at (1) a public health facility or (2) from any kind of treatment provider. RESULTS: Treatment-seeking data were available for 74 MECs and modelled for the remaining 24. GAMMs found that the percentage of pregnant women receiving prenatal care, vaccination rates, education level, government health expenditure, and GDP growth were important predictors for both categories of treatment-seeking outcomes. Treatment-seeking rates, which varied both within and among regions, revealed that public facilities were not always the primary facility type used. CONCLUSIONS: Estimates of treatment-seeking rates show how health services are utilized and help correct reported malaria case numbers to obtain more accurate measures of disease burden. The assembled and modelled data demonstrated that while treatment-seeking rates have overall increased over time, access remains low in some malaria endemic regions and utilization of government services is in some areas limited

A feminist new materialist experiment: exploring what else gets produced through encounters with children’s news media

In this paper we are concerned to grapple with the ways in which real world issues directly impact children’s lives, and ask what else gets produced through encounters with children’s global news media specifically within the contexts of the UK and Norway. Our aim is to experiment with worldling practices as a means to open up generative possibilities to encounter and reconfigure difficult knowledges. We take two contemporary events: the 2017 Grenfell Tower fire tragedy in London, and the 2018 Marjory Stoneman high school shooting massacre in Florida, as a means to attend to ways in which affects are materialised across multiple times and spaces. News reports of these harrowing events, alongside what they produced, in terms of child activism, racism and toxic masculinity, provided a catalyst for a feminist new materialist experiment in generating other knowledges through material-affective-embodied encounters. Newspapers, glue, sticky tape, string, torches, bags and a cartridge for a firearm undertook important work within a speculative workshop, where a small number of early childhood researchers came together to be open to multiple and experimental ways of (k)not-knowing in order to formulate collectively shared problems. Following Manning (2016) we recognise that to avoid getting stuck in familiar ways of thinking and doing we need to undertake research differently. We wondered how might the re-materialisation of these events (through objects, artefacts, sounds and images) shift our thinking about childhood in other directions. We dwell upon the affective work that these high-profile news events perform, and how they might become rearticulated through affective encounters with materiality. Attending to how these events worked on us involves staying with the trouble (Haraway, 2016) as it becomes reignited, mutated and amplified across time and in different contexts. Our goal is to generate other possibilities that seek to reconfigure the ‘image of the child’. By resisting comforts of recognition, reflection and identification we reach beyond what we think we know about how children are in the world, and instead argue for their entanglement with difficult knowledges through, ours and their, world-making practices

Proteomic profile of cystic fibrosis sputum cells in adults chronically infected with Pseudomonas aeruginosa

Lung disease is the main cause of morbidity and mortality in cystic fibrosis (CF), and involves chronic infection and perturbed immune responses. Tissue damage is mediated mostly by extracellular proteases, but other cellular proteins may also contribute to damage through their effect on cell activities and/or release into sputum fluid by means of active secretion or cell death.We employed MudPIT (multidimensional protein identification technology) to identify sputum cellular proteins with consistently altered abundance in adults with CF, chronically infected with Pseudomonas aeruginosa, compared with healthy controls. Ingenuity Pathway Analysis, Gene Ontology, protein abundance and correlation with lung function were used to infer their potential clinical significance.Differentially abundant proteins relate to Rho family small GTPase activity, immune cell movement/activation, generation of reactive oxygen species, and dysregulation of cell death and proliferation. Compositional breakdown identified high abundance of proteins previously associated with neutrophil extracellular traps. Furthermore, negative correlations with lung function were detected for 17 proteins, many of which have previously been associated with lung injury.These findings expand our current understanding of the mechanisms driving CF lung disease and identify sputum cellular proteins with potential for use as indicators of disease status/prognosis, stratification determinants for treatment prescription or therapeutic targets

Needles in the Haystack: Identifying Individuals Present in Pooled Genomic Data

Recent publications have described and applied a novel metric that quantifies the genetic distance of an individual with respect to two population samples, and have suggested that the metric makes it possible to infer the presence of an individual of known genotype in a sample for which only the marginal allele frequencies are known. However, the assumptions, limitations, and utility of this metric remained incompletely characterized. Here we present empirical tests of the method using publicly accessible genotypes, as well as analytical investigations of the method's strengths and limitations. The results reveal that the null distribution is sensitive to the underlying assumptions, making it difficult to accurately calibrate thresholds for classifying an individual as a member of the population samples. As a result, the false-positive rates obtained in practice are considerably higher than previously believed. However, despite the metric's inadequacies for identifying the presence of an individual in a sample, our results suggest potential avenues for future research on tuning this method to problems of ancestry inference or disease prediction. By revealing both the strengths and limitations of the proposed method, we hope to elucidate situations in which this distance metric may be used in an appropriate manner. We also discuss the implications of our findings in forensics applications and in the protection of GWAS participant privacy

Deep residual networks for automatic segmentation of laparoscopic videos of the liver

MOTIVATION: For primary and metastatic liver cancer patients undergoing liver resection, a laparoscopic approach can reduce recovery times and morbidity while offering equivalent curative results; however, only about 10% of tumours reside in anatomical locations that are currently accessible for laparoscopic resection. Augmenting laparoscopic video with registered vascular anatomical models from pre-procedure imaging could support using laparoscopy in a wider population. Segmentation of liver tissue on laparoscopic video supports the robust registration of anatomical liver models by filtering out false anatomical correspondences between pre-procedure and intra-procedure images. In this paper, we present a convolutional neural network (CNN) approach to liver segmentation in laparoscopic liver procedure videos. METHOD: We defined a CNN architecture comprising fully-convolutional deep residual networks with multi-resolution loss functions. The CNN was trained in a leave-one-patient-out cross-validation on 2050 video frames from 6 liver resections and 7 laparoscopic staging procedures, and evaluated using the Dice score. RESULTS: The CNN yielded segmentations with Dice scores ≥0.95 for the majority of images; however, the inter-patient variability in median Dice score was substantial. Four failure modes were identified from low scoring segmentations: minimal visible liver tissue, inter-patient variability in liver appearance, automatic exposure correction, and pathological liver tissue that mimics non-liver tissue appearance. CONCLUSION: CNNs offer a feasible approach for accurately segmenting liver from other anatomy on laparoscopic video, but additional data or computational advances are necessary to address challenges due to the high inter-patient variability in liver appearance

Clinical Applications of Pediatric Pulmonary Function Testing: Lung Function in Recurrent Wheezing and Asthma

Pulmonary function testing remains the gold standard for the diagnosis and management of wheezing disorders in older children and adults. Although wheezing disorders are among the most common clinical problems in pediatrics, most young children and toddlers cannot perform most of the currently clinically available pulmonary function tests. In this article, we review the different types of pulmonary function tests available and discuss the applicability and utility in the different age groups with specific reference to suitability in the diagnosis and management of wheezing disorders.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90475/1/ped-2E2010-2E0060.pd

The Diabetes Manual trial protocol – a cluster randomized controlled trial of a self-management intervention for type 2 diabetes [ISRCTN06315411]

Background The Diabetes Manual is a type 2 diabetes self-management programme based upon the clinically effective 'Heart Manual'. The 12 week programme is a complex intervention theoretically underpinned by self-efficacy theory. It is a one to one intervention meeting United Kingdom requirements for structured diabetes-education and is delivered within routine primary care. Methods/design In a two-group cluster randomized controlled trial, GP practices are allocated by computer minimisation to an intervention group or a six-month deferred intervention group. We aim to recruit 250 participants from 50 practices across central England. Eligibility criteria are adults able to undertake the programme with type 2 diabetes, not taking insulin, with HbA1c over 8% (first 12 months) and following an agreed protocol change over 7% (months 13 to 18). Following randomisation, intervention nurses receive two-day training and delivered the Diabetes Manual programme to participants. Deferred intervention nurses receive the training following six-month follow-up. Primary outcome is HbA1c with total and HDL cholesterol; blood pressure, body mass index; self-efficacy and quality of life as additional outcomes. Primary analysis is between-group HbA1c differences at 6 months powered to give 80% power to detect a difference in HbA1c of 0.6%. A 12 month cohort analysis will assess maintenance of effect and assess relationship between self-efficacy and outcomes, and a qualitative study is running alongside. Discussion This trial incorporates educational and psychological diabetes interventions into a single programme and assesses both clinical and psychosocial outcomes. The trial will increase our understanding of intervention transferability between conditions, those diabetes related health behaviours that are more or less susceptible to change through efficacy enhancing mechanisms and how this impacts on clinical outcomes

What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts

Pathogen circulation among reservoir hosts is a precondition for zoonotic spillover. Unlike the acute, high morbidity infections typical in spillover hosts, infected reservoir hosts often exhibit low morbidity and mortality. Although it has been proposed that reservoir host infections may be persistent with recurrent episodes of shedding, direct evidence is often lacking. We construct a generalized SEIR (susceptible, exposed, infectious, recovered) framework encompassing 46 sub-models representing the full range of possible transitions among those four states of infection and immunity. We then use likelihood-based methods to fit these models to nine years of longitudinal data on henipavirus serology from a captive colony of Eidolon helvum bats in Ghana. We find that reinfection is necessary to explain observed dynamics; that acute infectious periods may be very short (hours to days); that immunity, if present, lasts about 1–2 years; and that recurring latent infection is likely. Although quantitative inference is sensitive to assumptions about serology, qualitative predictions are robust. Our novel approach helps clarify mechanisms of viral persistence and circulation in wild bats, including estimated ranges for key parameters such as the basic reproduction number and the duration of the infectious period. Our results inform how future field-based and experimental work could differentiate the processes of viral recurrence and reinfection in reservoir hosts. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’