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Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.
Climate science is highly interdisciplinary by nature, so understanding interactions between Earth processes inherently warrants the use of analytical software that can operate across the disciplines of Earth science. Toward this end, we present the Climate Data Toolbox for MATLAB, which contains more than 100 functions that span the major climate-related disciplines of Earth science. The toolbox enables streamlined, entirely scriptable workflows that are intuitive to write and easy to share. Included are functions to evaluate uncertainty, perform matrix operations, calculate climate indices, and generate common data displays. Documentation is presented pedagogically, with thorough explanations of how each function works and tutorials showing how the toolbox can be used to replicate results of published studies. As a well-tested, well-documented platform for interdisciplinary collaborations, the Climate Data Toolbox for MATLAB aims to reduce time spent writing low-level code, let researchers focus on physics rather than coding and encourage more efficacious code sharing. Plain Language Summary This article describes a collection of computer code that has recently been released to help scientists analyze many types of Earth science data. The code in this toolbox makes it easy to investigate things like global warming, El Nino, or other major climate-related processes such as how winds affect ocean circulation. Although the toolbox was designed to be used by expert climate scientists, its instruction manual is well written, and beginners may be able to learn a great deal about coding and Earth science, simply by following along with the provided examples. The toolbox is intended to help scientists save time, help them ensure their analysis is accurate, and make it easy for other scientists to repeat the results of previous studies.
Workplace friendships
(2023)
Workplace friendships, i.e., when work colleagues are also friends, are a widespread phenomenon in organizations which has attracted increasing research interest in recent decades. Numerous studies have investigated consequences of workplace friendships and found positive outcomes, such as increased employee job satisfaction or organizational performance, as well as negative outcomes, such as decreased knowledge-sharing between different friendship cliques. Other studies have examined what shapes workplace friendships, focusing on determinants such as personality or the spatial composition of organizations. Finally, an increasing number of studies focus on multiplex workplace friendships, where employees who are friends are also linked by a specific work-focused relationship. In this chapter, we first take stock of the literature on workplace friendships by providing an overview of their antecedents and consequences at the individual, the group, and the organizational level, and review the smaller body of research on multiplex workplace friendships. Second, we critically discuss practical implications of workplace friendships, focusing on their relevance to three current challenges for employees and organizations: the increase in virtual work, social inequalities in organizations, and the increased overlap of professional and private life. Finally, we provide recommendations for organizations on how to address these challenges and effectively manage workplace friendships.
Bright and eclipsing, the high-mass X-ray binary Vela X-1 offers a unique opportunity to study accretion onto a neutron star from clumpy winds of O/B stars and to disentangle the complex accretion geometry of these systems. In Chandra-HETGS spectroscopy at orbital phase similar to 0.25, when our line of sight towards the source does not pass through the large-scale accretion structure such as the accretion wake, we observe changes in overall spectral shape on timescales of a few kiloseconds. This spectral variability is, at least in part, caused by changes in overall absorption and we show that such strongly variable absorption cannot be caused by unperturbed clumpy winds of O/B stars. We detect line features from high and low ionization species of silicon, magnesium, and neon whose strengths and presence depend on the overall level of absorption. These features imply a co-existence of cool and hot gas phases in the system, which we interpret as a highly variable, structured accretion flow close to the compact object such as has been recently seen in simulations of wind accretion in high-mass X-ray binaries.