RhoGTPase Regulators Orchestrate Distinct Stages of Synaptic Development

Small RhoGTPases regulate changes in post-synaptic spine morphology and density that support learning and memory. They are also major targets of synaptic disorders, including Autism. Here we sought to determine whether upstream RhoGTPase regulators, including GEFs, GAPs, and GDIs, sculpt specific stages of synaptic development. The majority of examined molecules uniquely regulate either early spine precursor formation or later matura- tion. Specifically, an activator of actin polymerization, the Rac1 GEF β-PIX, drives spine pre- cursor formation, whereas both FRABIN, a Cdc42 GEF, and OLIGOPHRENIN-1, a RhoA GAP, regulate spine precursor elongation. However, in later development, a novel Rac1 GAP, ARHGAP23, and RhoGDIs inactivate actomyosin dynamics to stabilize mature synap- ses. Our observations demonstrate that specific combinations of RhoGTPase regulatory pro- teins temporally balance RhoGTPase activity during post-synaptic spine development

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

Projected resurgence of COVID-19 in the United States in July—December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July–December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July–December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July–December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model

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

Culturally appropriate organization of water and sewerage projects built through public private partnerships.

This paper contributes to the pursuit of socially sustainable water and sanitation infrastructure for all people by discovering statistically robust relationships between Hofstede's dimensions of cross-cultural comparison and the choice of contract award types, project type, and primary revenue sources. This analysis, which represents 973 projects distributed across 24 low- and middle-income nations, uses a World Bank dataset describing high capital cost water and sewerage projects funded through private investment. The results show that cultural dimensions explain variation in the choice of contract award types, project type, and primary revenue sources. These results provide empirical evidence that strategies for water and sewerage project organization are not culturally neutral. The data show, for example, that highly individualistic contexts are more likely to select competitive contract award types and to depend on user fees to provide the primary project revenue stream post-construction. By selecting more locally appropriate ways to organize projects, project stakeholders will be better able to pursue the construction of socially sustainable water and sewerage infrastructure

Cultured Construction: Global Evidence of the Impact of National Values on Piped-to-Premises Water Infrastructure Development

In 2016, the global community undertook the Sustainable Development Goals. One of these goals seeks to achieve universal and equitable access to safe and affordable drinking water for all people by the year 2030. In support of this undertaking, this paper seeks to discover the cultural work done by piped water infrastructure across 33 nations with developed and developing economies that have experienced change in the percentage of population served by piped-to-premises water infrastructure at the national level of analysis. To do so, I regressed the 1990–2012 change in piped-to-premises water infrastructure coverage against Hofstede’s cultural dimensions, controlling for per capita GDP, the 1990 baseline level of coverage, percent urban population, overall 1990–2012 change in improved sanitation (all technologies), and per capita freshwater resources. Separate analyses were carried out for the urban, rural, and aggregate national contexts. Hofstede’s dimensions provide a measure of cross-cultural difference; high or low scores are not in any way intended to represent better or worse but rather serve as a quantitative way to compare aggregate preferences for ways of being and doing. High scores in the cultural dimensions of Power Distance, Individualism–Collectivism, and Uncertainty Avoidance explain increased access to piped-to-premises water infrastructure in the rural context. Higher Power Distance and Uncertainty Avoidance scores are also statistically significant for increased coverage in the urban and national aggregate contexts. These results indicate that, as presently conceived, piped-to-premises water infrastructure fits best with spatial contexts that prefer hierarchy and centralized control. Furthermore, water infrastructure is understood to reduce uncertainty regarding the provision of individually valued benefits. The results of this analysis identify global trends that enable engineers and policy makers to design and manage more culturally appropriate and socially sustainable water infrastructure by better fitting technologies to user preferences

Cultured Construction: Global Evidence of the Impact of National Values on Renewable Electricity Infrastructure Choice

Renewable electricity is an important tool in the fight against climate change, but globally these technologies are still in the early stages of diffusion. To contribute to our understanding of the factors driving this diffusion, I study relationships between national values (measured by Hofstede’s cultural dimensions) and renewable electricity adoption at the national level. Existing data for 66 nations (representing an equal number of developed and developing economies) are used to fuel the analysis. Somewhat dependent on limited available data on controls for grid reliability and the cost of electricity, I discover that three of Hofstede’s dimensions (high uncertainty avoidance, low masculinity-femininity, and high individualism-collectivism) have significant exponential relationships with renewable electricity adoption. The dimension of uncertainty avoidance appears particularly appropriate for practical application. Projects or organizations implementing renewable electricity policy, designs, or construction should particularly attend to this cultural dimension. In particular, as the data imply that renewable technologies are being used to manage risk in electricity supply, geographies with unreliable grids are particularly likely to be open to renewable electricity technologies

Statistically significant results summary.

<p>Statistically significant results summary.</p

Results of Multinomial Logistic Regression, Project Type of Water and Sewerage Projects.

<p>Results of Multinomial Logistic Regression, Project Type of Water and Sewerage Projects.</p