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Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Fungi play pivotal roles in ecosystem functioning, but little is known about their global patterns of diversity, endemicity, vulnerability to global change drivers and conservation priority areas. We applied the high-resolution PacBio sequencing technique to identify fungi based on a long DNA marker that revealed a high proportion of hitherto unknown fungal taxa. We used a Global Soil Mycobiome consortium dataset to test relative performance of various sequencing depth standardization methods (calculation of residuals, exclusion of singletons, traditional and SRS rarefaction, use of Shannon index of diversity) to find optimal protocols for statistical analyses. Altogether, we used six global surveys to infer these patterns for soil-inhabiting fungi and their functional groups. We found that residuals of log-transformed richness (including singletons) against log-transformed sequencing depth yields significantly better model estimates compared with most other standardization methods. With respect to global patterns, fungal functional groups differed in the patterns of diversity, endemicity and vulnerability to main global change predictors. Unlike α-diversity, endemicity and global-change vulnerability of fungi and most functional groups were greatest in the tropics. Fungi are vulnerable mostly to drought, heat, and land cover change. Fungal conservation areas of highest priority include wetlands and moist tropical ecosystems.
Humanized mouse models have become increasingly valuable tools to study human hematopoiesis and infectious diseases. However, human T cell differentiation remains inefficient. We generated mice expressing human interleukin (IL-7), a critical growth and survival factor for T cells, under the control of murine IL-7 regulatory elements. After transfer of human cord blood-derived hematopoietic stem and progenitor cells, transgenic mice on the NSGW41 background, termed NSGW41hIL7, showed elevated and prolonged human cellularity in the thymus while maintaining physiological ratios of thymocyte subsets. As a consequence, numbers of functional human T cells in the periphery were increased without evidence for pathological lymphoproliferation or aberrant expansion of effector or memory-like T cells. We conclude that the novel NSGW41hIL7 strain represents an optimized mouse model for humanization to better understand human T cell differentiation in vivo and to generate a human immune system with a better approximation of human lymphocyte ratios.
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
8th International Conference on Nuclear Physics at Storage Rings Stori11, October 9-14, 2011 Laboratori Nazionale di Frascati, Italy.
Storage rings offer the possibility of measuring proton- and alpha-induced reactions in inverse kinematics. The combination of this approachwith a radioactive beamfacility allows, in principle, the determination of the respective cross sections for radioactive isotopes. Such data are highly desired for a better understanding of astrophysical nucleosynthesis processes like the p-process. A pioneering experiment has been performed at the Experimental Storage Ring (ESR) at GSI using a stable 96Ru beam at 9-11 AMeV and a hydrogen target. Monte-Carlo simulations of the experiment were made using the Geant4 code. In these simulations, the experimental setup is described in detail and all reaction channels can be investigated. Based on the Geant4 simulations, a prediction of the shape of different spectral components can be performed. A comparison of simulated predictions with the experimental results shows a good agreement and allows the extraction of the cross section.