INTERSTICE. Training course for Education students

INTERSTICE is an Erasmus+ project developed by universities, artists and cultural settings from Catalonia, United Kingdom, Italy, and Norway to promote spaces of encounter between educators, artists, and children, to improve our learning processes and to build a pedagogy of co-creation through the arts. All University partners of INTERSTICE project designed and developed training experiences for prospective educators, with the active involvement of artists, cultural setting and schools. In this material, the four experiences and summarized, and some reflexions are offered in order to inspire more university professors

International films and international markets: the globalisation of Hollywood entertainment, c.1921-1951

The international appeal of Hollywood films through the twentieth century has been a subject of interest to economic and film historians alike. This paper employs some of the methods of the economic historian to evaluate key arguments within the film history literature explaining the global success of American films. Through careful analysis of both existing and newly constructed data sets, the paper examines the extent to which Hollywood's foreign earnings were affected by: film production costs; the extent of global distribution networks; and also the international orientation of the films themselves. The paper finds that these factors influenced foreign earnings in quite distinct ways, and that their relative importance changed over time. The evidence presented here suggests a degree of interaction between the production and distribution arms of the major US film companies in their pursuit of foreign markets that would benefit from further archival-based investigation

The role of multixenobiotic transporters in predatory marine molluscs as counter-defense mechanisms against dietary allelochemicals

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology 152 (2010): 288-300, doi:10.1016/j.cbpc.2010.05.003.Multixenobiotic transporters have been extensively studied for their ability to modulate the disposition and toxicity of pharmacological agents, yet their influence in regulating the levels of dietary toxins within marine consumers has only recently been explored. This study presents functional and molecular evidence for multixenobiotic transporter-mediated efflux activity and expression in the generalist gastropod Cyphoma gibbosum, and the specialist nudibranch Tritonia hamnerorum, obligate predators of chemically defended gorgonian corals. Immunochemical analysis revealed that proteins with homology to permeability glycoprotein (P-gp) were highly expressed in T. hamnerorum whole animal homogenates and localized to the apical tips of the gut epithelium, a location consistent with a role in protection against ingested prey toxins. In vivo dye assays with specific inhibitors of efflux transporters demonstrated the activity of P-gp and multidrug resistance-associated protein (MRP) families of ABC transporters in T. hamnerorum. In addition, we identified eight partial cDNA sequences encoding two ABCB and two ABCC proteins from each molluscan species. Digestive gland transcripts of C. gibbosum MRP-1, which have homology to vertebrate glutathione-conjugate transporters, were constitutively expressed regardless of gorgonian diet. This constitutive expression may reflect the ubiquitous presence of high affinity substrates for C. gibbosum glutathione transferases in gorgonian tissues likely necessitating export by MRPs. Our results suggest that differences in multixenobiotic transporter expression patterns and activity in molluscan predators may stem from the divergent foraging strategies of each consumer.Financial support was provided by the Ocean Life Institute Tropical Research Initiative Grant (WHOI) to KEW and MEH; the Robert H. Cole Endowed Ocean Ventures Fund (WHOI) to KEW; the National Undersea Research Center – Program Development Proposal (CMRC-03PRMN0103A) to KEW; and the National Science Foundation (Graduate Research Fellowship to KEW and DEB-0919064 to EES)

The higher education impact agenda, scientific realism and policy change: the case of electoral integrity in Britain

Pressures have increasingly been put upon social scientists to prove their economic, cultural and social value through ‘impact agendas’ in higher education. There has been little conceptual and empirical discussion of the challenges involved in achieving impact and the dangers of evaluating it, however. This article argues that a critical realist approach to social science can help to identify some of these key challenges and the institutional incompatibilities between impact regimes and university research in free societies. These incompatibilities are brought out through an autobiographical ‘insider-account’ of trying to achieve impact in the field of electoral integrity in Britain. The article argues that there is a more complex relationship between research and the real world which means that the nature of knowledge might change as it becomes known by reflexive agents. Secondly, the researchers are joined into social relations with a variety of actors, including those who might be the object of study in their research. Researchers are often weakly positioned in these relations. Some forms of impact, such as achieving policy change, are therefore exceptionally difficult as they are dependent on other actors. Strategies for trying to achieve impact are drawn out such as collaborating with civil society groups and parliamentarians to lobby for policy change

Protocol for a randomised controlled trial of treatment of asymptomatic candidiasis for the prevention of preterm birth [ACTRN12610000607077]

<p>Abstract</p> <p>Background</p> <p>Prevention of preterm birth remains one of the most important challenges in maternity care. We propose a randomised trial with: a simple <it>Candida </it>testing protocol that can be easily incorporated into usual antenatal care; a simple, well accepted, treatment intervention; and assessment of outcomes from validated, routinely-collected, computerised databases.</p> <p>Methods/Design</p> <p>Using a prospective, randomised, open-label, blinded-endpoint (PROBE) study design, we aim to evaluate whether treating women with asymptomatic vaginal candidiasis early in pregnancy is effective in preventing spontaneous preterm birth. Pregnant women presenting for antenatal care <20 weeks gestation with singleton pregnancies are eligible for inclusion. The intervention is a 6-day course of clotrimazole vaginal pessaries (100 mg) and the primary outcome is spontaneous preterm birth <37 weeks gestation.</p> <p>The study protocol draws on the usual antenatal care schedule, has been pilot-tested and the intervention involves only a minor modification of current practice. Women who agree to participate will self-collect a vaginal swab and those who are culture positive for Candida will be randomised (central, telephone) to open-label treatment or usual care (screening result is not revealed, no treatment, routine antenatal care). Outcomes will be obtained from population databases.</p> <p>A sample size of 3,208 women with <it>Candida </it>colonisation (1,604 per arm) is required to detect a 40% reduction in the spontaneous preterm birth rate among women with asymptomatic candidiasis from 5.0% in the control group to 3.0% in women treated with clotrimazole (significance 0.05, power 0.8). Analyses will be by intention to treat.</p> <p>Discussion</p> <p>For our hypothesis, a placebo-controlled trial had major disadvantages: a placebo arm would not represent current clinical practice; knowledge of vaginal colonisation with <it>Candida </it>may change participants' behaviour; and a placebo with an alcohol preservative may have an independent affect on vaginal flora. These disadvantages can be overcome by the PROBE study design.</p> <p>This trial will provide definitive evidence on whether screening for and treating asymptomatic candidiasis in pregnancy significantly reduces the rate of spontaneous preterm birth. If it can be demonstrated that treating asymptomatic candidiasis reduces preterm births this will change current practice and would directly impact the management of every pregnant woman.</p> <p>Trial registration</p> <p>Australian New Zealand Clinical Trials Registry <a href="http://www.anzctr.org.au/ACTRN12610000607077.aspx">ACTRN12610000607077</a></p

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions