Inscribed Greek Thunderstones as House- and Body-Amulets in Roman Imperial Times

La réutilisation des haches néolithiques (également appelées « celts » ou « pierres de foudre ») comme des amulettes à l’époque romaine est aujourd’hui sous-estimée. En conséquence, la date ancienne des deux petits exemples inscrits du British Museum (BM nos 1* et 504) est maintenant remise en doute, en raison d’une évaluation négative qui découle de l’utilisation insuffisante de comparanda. En comparaison avec le corpus croissant de pierres magiques, les médias de ces deux petites haches (jadéite ou serpentine), leur poli et leur forme semblent en effet suspects et difficiles à évaluer comme gemmes en soi, mais quand on les compare à d’autres haches néolithiques inscrites et anépigraphes trouvées dans sites romains et plus tard, il s’avère que les deux pierres à Londres appartiennent à une catégorie bien définie de « pierres de foudre » réutilisées comme amulettes.The re-use of Neolithic axe-heads (also known as “celts” or “thunderstones”) as amulets in Roman times is nowadays underappreciated. As a result, the ancient date of two small inscribed examples in the British Museum (BM nos. 1* and 504) is now in doubt,a negative assessment that arises from the use of insufficient comparanda. When compared with the growing corpus of magical gems, the media of these two small axe-heads (jadeite or serpentine), their high polish and their shape do indeed seem suspicious and difficult to assess as gems per se, but when viewed alongside other thunderstones, inscribed and uninscribed, found in Roman and later sites, we can see that both of the London stones belong to a clearly defined category of thunderstones reused as amulets

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Time courses of improvement and symptom remission in children treated with atomoxetine for attention-deficit/hyperactivity disorder: analysis of Canadian open-label studies

<p>Abstract</p> <p>Background</p> <p>The relatively short durations of the initial pivotal randomized placebo-controlled trials involving atomoxetine HCl for the treatment of attention-deficit/hyperactivity disorder (ADHD) provided limited insight into the time courses of ADHD core symptom responses to this nonstimulant, selective norepinephrine reuptake inhibitor. The aim of this analysis was to evaluate time courses of treatment responses or remission, as assessed by attainment of prespecified scores on the ADHD Rating Scale-IV-Parent Version: Investigator Administered and Scored (ADHDRS-IV-PI) and the Clinical Global Impressions-ADHD-Severity (CGI-ADHD-S) scales, during up to 1 year of atomoxetine treatment in children with ADHD.</p> <p>Methods</p> <p>Using pooled data from three Canadian open-label studies involving 338 children ages 6-11 years with ADHD who were treated with atomoxetine for 3, 6 and 12 months, and survival analysis methods for interval-censored data, we estimated the time to: 1) improvement and robust improvement defined by ≥25% and ≥40% reductions from baseline ADHDRS-IV-PI total scores, respectively; and 2) remission using two definitions: a final score of ADHDRS-IV-PI ≤18 or a final score of CGI-ADHD-S ≤2.</p> <p>Results</p> <p>The median time to improvement was 3.7 weeks (~1 month), but remission of symptoms did not occur until a median of 14.3 weeks (~3.5 months) using the most stringent CGI-ADHD-S threshold. Probabilities of robust improvement were 47% at or before 4 weeks of treatment; 76% at 12 weeks; 85% at 26 weeks; and 96% at 52 weeks. Probabilities of remission at these corresponding time points were 30%, 59%, 77%, and 85% (using the ADHDRS-IV scale) and 8%, 47%, 67%, and 75% (using the CGI-ADHD-S scale). The change from atomoxetine treatment month 5 to month 12 of -1.01 (1.03) was not statistically significant (<it>p </it>= .33).</p> <p>Conclusions</p> <p>Reductions in core ADHD symptoms during atomoxetine treatment are gradual. Although approximately one-half of study participants showed improvement at 1 month of atomoxetine treatment, remission criteria were not met until about 3 months. Understanding the time course of children's responses to atomoxetine treatment may inform clinical decision making and also influence the durations of trials comparing the effects of this medication with other ADHD treatments.</p> <p>Trial Registrations</p> <p>clinicaltrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00191633">NCT00191633</a>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00216918">NCT00216918</a>, <a href="http://www.clinicaltrials.gov/ct2/show/NCT00191880">NCT00191880</a>.</p

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, PPeer reviewe

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

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

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

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