Participatory politics, environmental journalism and newspaper campaigns

This is an Author's Accepted Manuscript of an article published in Journalism Studies, 13(2), 210 - 225, 2012, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/1461670X.2011.646398.This article explores the extent to which approaches to participatory politics might offer a more useful alternative to understanding the role of environmental journalism in a society where the old certainties have collapsed, only to be replaced by acute uncertainty. This uncertainty not only generates acute public anxiety about risks, it has also undermined confidence in the validity of long-standing premises about the ideal role of the media in society and journalistic professionalism. The consequence, this article argues, is that aspirations of objective reportage are outdated and ill-equipped to deal with many of the new risk stories environmental journalism covers. It is not a redrawing of boundaries that is needed but a wholesale relocation of our frameworks into approaches better suited to the socio-political conditions and uncertainties of late modernity. The exploration of participatory approaches is an attempt to suggest one way this might be done

Human Intelligence and Polymorphisms in the DNA Methyltransferase Genes Involved in Epigenetic Marking

Epigenetic mechanisms have been implicated in syndromes associated with mental impairment but little is known about the role of epigenetics in determining the normal variation in human intelligence. We measured polymorphisms in four DNA methyltransferases (DNMT1, DNMT3A, DNMT3B and DNMT3L) involved in epigenetic marking and related these to childhood and adult general intelligence in a population (n = 1542) consisting of two Scottish cohorts born in 1936 and residing in Lothian (n = 1075) or Aberdeen (n = 467). All subjects had taken the same test of intelligence at age 11yrs. The Lothian cohort took the test again at age 70yrs. The minor T allele of DNMT3L SNP 11330C>T (rs7354779) allele was associated with a higher standardised childhood intelligence score; greatest effect in the dominant analysis but also significant in the additive model (coefficient = 1.40additive; 95%CI 0.22,2.59; p = 0.020 and 1.99dominant; 95%CI 0.55,3.43; p = 0.007). The DNMT3L C allele was associated with an increased risk of being below average intelligence (OR 1.25additive; 95%CI 1.05,1.51; p = 0.011 and OR 1.37dominant; 95%CI 1.11,1.68; p = 0.003), and being in the lowest 40th (padditive = 0.009; pdominant = 0.002) and lowest 30th (padditive = 0.004; pdominant = 0.002) centiles for intelligence. After Bonferroni correction for the number variants tested the link between DNMT3L 11330C>T and childhood intelligence remained significant by linear regression and centile analysis; only the additive regression model was borderline significant. Adult intelligence was similarly linked to the DNMT3L variant but this analysis was limited by the numbers studied and nature of the test and the association was not significant after Bonferroni correction. We believe that the role of epigenetics in the normal variation in human intelligence merits further study and that this novel finding should be tested in other cohorts

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

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

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe

Demographic and angioarchitectural features associated with seizures presentation in patients with brain arteriovenous malformations in Durban, KwaZulu-Natal, South Africa

Background: Brain arteriovenous malformations (AVMs) often present with epileptic seizures which carry standard mortality rate two to three folds higher than in the general population, yet preventative eradication of these lesions remains controversial. The aim of this study was to determine the demographic and angioarchitectural features associated with clinical presentation of seizures in patients with brain AVMs. Methods: We conducted a retrospective chart review of all consecutive patients who presented to three interventional neuroradiology hospitals, with brain AVMs in Kwazulu-Natal, South Africa, over a period of 10years. The demographic and clinical presentations were derived from patient's electronic medical records. Radiological features were determined using axial Computerized Topography (CT) or Magnetic Resonance Imaging (MRI) Scan. Angioarchitectural features were determined from Digital Subtraction Angiography (DSA). Simple and multiple logistic regression models were used to identify factors associated with the risk of seizure as initial presentation in brain AVMs. Results: The analysis identified race/ethnicity, nidus size and location as the predictors of seizure presentation. By multiple logistic regression analysis, African-black race (OR=4.7; 95%CI: 1.15–19.60), brain AVM nidus >3cm in diameter, (OR=4.4; 95%CI: 1.7−11.42) and cortical lobar location (OR=13.6; 95%CI: 2.80−65.14) were found to be significant predictors of brain AVM-associated seizures. Conclusion: Improved knowledge of specific morphological factors associated with brain AVM epilepsy could aid in the formulation of appropriate therapeutic strategies for control and/or cure of these brain AVM-associated seizures. Keywords: Angioarchitecture, Arteriovenous malformations, Brain, Demographics, Seizure

Lesões múltiplas de osteoma cutis na face: terapêutica minimamente invasiva em pacientes com sequela de acne - relato de casos Multiple injuries of osteoma skin in the face: therapeutical least invasive in patients with acne sequela - case report

Osteoma cutis é a formação óssea no interior da pele, podendo ser primária ou secundária. Única ou múltipla, de tamanhos variados e acometendo ambos os sexos, é uma lesão cutânea rara, de etiopatogenia e classificação ainda discutidas. Nosso objetivo foi relatar o diagnóstico e a terapêutica minimamente invasiva de lesões múltiplas de osteoma cutis na face em pacientes com sequelas de acne. Fizemos a retirada dos osteomas com agulhas BD 0,70 x 25 22G1, sem anestésicos tópicos ou injetáveis no local. As pequenas incisões foram deixadas expostas, com pomada cicatrizante. Obteve-se um excelente resultado estético em 15 dias.<br>Osteoma cutis is a bone formation in the dermis can to be primary or secondary forms. Only, multiples, many forms, occurring on either sex, they are a rare cutaneous disease. The pathogenesis and classification remains unclear. Our objective was the diagnostic and small invasive surgery treatment of the osteoma cutis multiple of the face, in patients as a sequel of acne. To remove the osteoma we used needle BD 0,70x25 22G1, without anesthetic topic or inject able site. The small wounds were exposed with scarring balsam. We got an excellent esthetic result after 15 days