Structural Assembly Demonstration Experiment (SADE)

The purpose of the Structural Assembly Demonstration Experiment (SADE) was to create a near-term Shuttle flight experiment focusing on the deployment and erection of structural truss elements. The activities of the MIT Space Systems Laboratory consist of three major areas: preparing and conducting neutral buoyancy simulation test series; producing a formal SADE Experiment plan; and studying the structural dynamics issues of the truss structure. Each of these areas is summarized

Unbiased estimation in seamless phase II/III trials with unequal treatment effect variances and hypothesis-driven selection rules.

Seamless phase II/III clinical trials offer an efficient way to select an experimental treatment and perform confirmatory analysis within a single trial. However, combining the data from both stages in the final analysis can induce bias into the estimates of treatment effects. Methods for bias adjustment developed thus far have made restrictive assumptions about the design and selection rules followed. In order to address these shortcomings, we apply recent methodological advances to derive the uniformly minimum variance conditionally unbiased estimator for two-stage seamless phase II/III trials. Our framework allows for the precision of the treatment arm estimates to take arbitrary values, can be utilised for all treatments that are taken forward to phase III and is applicable when the decision to select or drop treatment arms is driven by a multiplicity-adjusted hypothesis testing procedure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd

Correcting for bias in the selection and validation of informative diagnostic tests.

When developing a new diagnostic test for a disease, there are often multiple candidate classifiers to choose from, and it is unclear if any will offer an improvement in performance compared with current technology. A two-stage design can be used to select a promising classifier (if one exists) in stage one for definitive validation in stage two. However, estimating the true properties of the chosen classifier is complicated by the first stage selection rules. In particular, the usual maximum likelihood estimator (MLE) that combines data from both stages will be biased high. Consequently, confidence intervals and p-values flowing from the MLE will also be incorrect. Building on the results of Pepe et al. (SIM 28:762-779), we derive the most efficient conditionally unbiased estimator and exact confidence intervals for a classifier's sensitivity in a two-stage design with arbitrary selection rules; the condition being that the trial proceeds to the validation stage. We apply our estimation strategy to data from a recent family history screening tool validation study by Walter et al. (BJGP 63:393-400) and are able to identify and successfully adjust for bias in the tool's estimated sensitivity to detect those at higher risk of breast cancer

Accounting for selection and correlation in the analysis of two-stage genome-wide association studies.

The problem of selection bias has long been recognized in the analysis of two-stage trials, where promising candidates are selected in stage 1 for confirmatory analysis in stage 2. To efficiently correct for bias, uniformly minimum variance conditionally unbiased estimators (UMVCUEs) have been proposed for a wide variety of trial settings, but where the population parameter estimates are assumed to be independent. We relax this assumption and derive the UMVCUE in the multivariate normal setting with an arbitrary known covariance structure. One area of application is the estimation of odds ratios (ORs) when combining a genome-wide scan with a replication study. Our framework explicitly accounts for correlated single nucleotide polymorphisms, as might occur due to linkage disequilibrium. We illustrate our approach on the measurement of the association between 11 genetic variants and the risk of Crohn's disease, as reported in Parkes and others (2007. Sequence variants in the autophagy gene IRGM and multiple other replicating loci contribute to Crohn's disease susceptibility. Nat. Gen. 39: (7), 830-832.), and show that the estimated ORs can vary substantially if both selection and correlation are taken into account

Structural Plasticity of the Semliki Forest Virus Glycome upon Interspecies Transmission

Cross-species viral transmission subjects parent and progeny alphaviruses to differential post-translational processing of viral envelope glycoproteins. Alphavirus biogenesis has been extensively studied, and the Semliki Forest virus E1 and E2 glycoproteins have been shown to exhibit differing degrees of processing of N-linked glycans. However the composition of these glycans, including that arising from different host cells, has not been determined. Here we determined the chemical composition of the glycans from the prototypic alphavirus, Semliki Forest virus, propagated in both arthropod and rodent cell lines, by using ion-mobility mass spectrometry and collision-induced dissociation analysis. We observe that both the membrane-proximal E1 fusion glycoprotein and the protruding E2 attachment glycoprotein display heterogeneous glycosylation that contains N-linked glycans exhibiting both limited and extensive processing. However, E1 contained predominantly highly processed glycans dependent on the host cell, with rodent and mosquito-derived E1 exhibiting complex-type and paucimannose-type glycosylation, respectively. In contrast, the protruding E2 attachment glycoprotein primarily contained conserved under-processed oligomannose-type structures when produced in both rodent and mosquito cell lines. It is likely that glycan processing of E2 is structurally restricted by steric-hindrance imposed by local viral protein structure. This contrasts E1, which presents glycans characteristic of the host cell and is accessible to enzymes. We integrated our findings with previous cryo-electron microscopy and crystallographic analyses to produce a detailed model of the glycosylated mature virion surface. Taken together, these data reveal the degree to which virally encoded protein structure and cellular processing enzymes shape the virion glycome during interspecies transmission of Semliki Forest virus

Field validation of habitat suitability models for vulnerable marine ecosystems in the South Pacific Ocean:Implications for the use of broad-scale models in fisheries management

AbstractManagement of human activities which impact the seafloor in the deep ocean is becoming increasingly important as bottom trawling and exploration for minerals, oil, and gas continue to extend into regions where fragile ecosystems containing habitat-forming deep-sea corals and sponges may be found. Spatial management of these vulnerable marine ecosystems requires accurate knowledge of their distribution. Predictive habitat suitability modelling, using species presence data and a suite of environmental predictor variables, has emerged as a useful tool for inferring distributions outside of known areas. However, validation of model predictions is typically performed with non-independent data. In this study, we describe the results of habitat suitability models constructed for four deep-sea reef-forming coral species across a large region of the South Pacific Ocean using MaxEnt and Boosted Regression Tree modelling approaches. In order to validate model predictions we conducted a photographic survey on a set of seamounts in an un-sampled area east of New Zealand. The likelihood of habitat suitable for reef-forming corals on these seamounts was predicted to be variable, but very high in some regions, particularly where levels of aragonite saturation, dissolved oxygen, and particulate organic carbon were optimal. However, the observed frequency of coral occurrence in analyses of survey photographic data was much lower than expected, and patterns of observed versus predicted coral distribution were not highly correlated. The poor performance of these broad-scale models is attributed to lack of recorded species absences to inform the models, low precision of global bathymetry models, and lack of data on the geomorphology and substrate of the seamounts at scales appropriate to the modelled taxa. This demonstrates the need to use caution when interpreting and applying broad-scale, presence-only model results for fisheries management and conservation planning in data poor areas of the deep sea. Future improvements in the predictive performance of broad-scale models will rely on the continued advancement in modelling of environmental predictor variables, refinements in modelling approaches to deal with missing or biased inputs, and incorporation of true absence data

Comparison of Instantaneous and Constant-Rate Stream Tracer Experiments Through Parametric Analysis of Residence Time Distributions

Artificial tracers are frequently employed to characterize solute residence times in stream systems and infer the nature of water retention. When the duration of tracer application is different between experiments, tracer breakthrough curves at downstream locations are difficult to compare directly. We explore methods for deriving stream solute residence time distributions (RTD) from tracer test data, allowing direct, non-parametric comparison of results from experiments of different durations. Paired short- and long-duration field experiments were performed using instantaneous and constant-rate tracer releases, respectively. The experiments were conducted in two study reaches that were morphologically distinct in channel structure and substrate size. Frequency- and time domain deconvolution techniques were used to derive RTDs from the resulting tracer concentrations. Comparisons of results between experiments of different duration demonstrated few differences in hydrologic retention characteristics inferred from short- and long-term tracer tests. Because non-parametric RTD analysis does not presume any shape of the distribution, it is useful for comparisons across tracer experiments with variable inputs and for validations of fundamental transport model assumptions

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line

Low-Temperature Fluorocarbonate Mineralization in Lower Devonian Rhynie Chert, UK

Funding: J.G.T.A was partially funded by the Natural Environment Research Council, grant number NE/T003677/1. Acknowledgments: We are grateful to W. Ritchie, J. Johnston, and J. Bowie for skilled technicalsupport. Samples were archived by N.H. Trewin, C.M. Rice and S. Fayers.Peer reviewedPublisher PD