Survey of College Entrance Exam Preparation Methods

This study surveyed college freshman to determine which types of preparation if any they had before taking either the SAT and/or ACT to decide if a certain type of preparation increased their scores. Students indicated whether they used online resources, self-help resources, school workshops and/or private tutoring before taking either test. The ACT scores were converted to SAT scores so that the data would be uniform. The mean SAT score was computed for those who used preparation and those who did not and comparisons were made. Each individual type of preparation was compared to no preparation. Finally, a correlation was computed between SAT scores and high school grade point averages. The research did not show that students who used preparation performed better than those who did not

Modelling and analysis of biochemical signalling pathway cross-talk

Signalling pathways are abstractions that help life scientists structure the coordination of cellular activity. Cross-talk between pathways accounts for many of the complex behaviours exhibited by signalling pathways and is often critical in producing the correct signal-response relationship. Formal models of signalling pathways and cross-talk in particular can aid understanding and drive experimentation. We define an approach to modelling based on the concept that a pathway is the (synchronising) parallel composition of instances of generic modules (with internal and external labels). Pathways are then composed by (synchronising) parallel composition and renaming; different types of cross-talk result from different combinations of synchronisation and renaming. We define a number of generic modules in PRISM and five types of cross-talk: signal flow, substrate availability, receptor function, gene expression and intracellular communication. We show that Continuous Stochastic Logic properties can both detect and distinguish the types of cross-talk. The approach is illustrated with small examples and an analysis of the cross-talk between the TGF-b/BMP, WNT and MAPK pathways

Modelling and analysis of structure in cellular signalling systems

Cellular signalling is an important area of study in biology. Signalling pathways are well-known abstractions that explain the mechanisms whereby cells respond to signals. Collections of pathways form signalling networks, and interactions between pathways in a network, known as cross-talk, enables further complex signalling behaviours. Increasingly, computational modelling and analysis is required to handle the complexity of such systems. While there are several computational modelling approaches for signalling pathways, none make cross-talk explicit. We present a modular modelling framework for pathways and their cross-talk. Networks are formed by composing pathways: different cross-talks result from different synchronisations of reactions between, and overlaps of, the pathways. We formalise five types of cross-talk and give approaches to reason about possible cross-talks in a network. The complementary problem is how to handle unstructured signalling networks, i.e. networks with no explicit notion of pathways or cross-talk. We present an approach to better understand unstructured signalling networks by modelling them as a set of signal flows through the network. We introduce the Reaction Minimal Paths (RMP) algorithm that computes the set of signal flows in a model. To the best of our knowledge, current algorithms cannot guarantee both correctness and completeness of the set of signal flows in a model. The RMP algorithm is the first. Finally, the RMP algorithm suffers from the well-known state space explosion problem. We use suitable partial order reduction algorithms to improve the efficiency of this algorithm

Modular modelling of signalling pathways and their crosstalk

Signalling pathways are well-known abstractions that explain the mechanisms whereby cells respond to signals. Collections of pathways form networks, and interactions between pathways in a network, known as cross-talk, enables further complex signalling behaviours. While there are several formal modelling approaches for signalling pathways, none make cross-talk explicit; the aim of this paper is to define and categorise cross-talk in a rigorous way. We define a modular approach to pathway and network modelling, based on the module construct in the PRISM modelling language, and a set of generic signalling modules. Five different types of cross-talk are defined according to various biologically meaningful combinations of variable sharing, synchronisation labels and reaction renaming. The approach is illustrated with a case-study analysis of cross-talk between the TGF-β, WNT and MAPK pathways

Parallel Local Approximation MCMC for Expensive Models

Performing Bayesian inference via Markov chain Monte Carlo (MCMC) can be exceedingly expensive when posterior evaluations invoke the evaluation of a computationally expensive model, such as a system of PDEs. In recent work [J. Amer. Statist. Assoc., 111 (2016), pp. 1591-1607] we described a framework for constructing and refining local approximations of such models during an MCMC simulation. These posterior-adapted approximations harness regularity of the model to reduce the computational cost of inference while preserving asymptotic exactness of the Markov chain. Here we describe two extensions of that work. First, we prove that samplers running in parallel can collaboratively construct a shared posterior approximation while ensuring ergodicity of each associated chain, providing a novel opportunity for exploiting parallel computation in MCMC. Second, focusing on the Metropolis-adjusted Langevin algorithm, we describe how a proposal distribution can successfully employ gradients and other relevant information extracted from the approximation. We investigate the practical performance of our approach using two challenging inference problems, the first in subsurface hydrology and the second in glaciology. Using local approximations constructed via parallel chains, we successfully reduce the run time needed to characterize the posterior distributions in these problems from days to hours and from months to days, respectively, dramatically improving the tractability of Bayesian inference.United States. Department of Energy. Office of Science. Scientific Discovery through Advanced Computing (SciDAC) Program (award DE-SC0007099)Natural Sciences and Engineering Research Council of CanadaUnited States. Office of Naval Researc

Equitability revisited: why the “equitable threat score” is not equitable

In the forecasting of binary events, verification measures that are “equitable” were defined by Gandin and Murphy to satisfy two requirements: 1) they award all random forecasting systems, including those that always issue the same forecast, the same expected score (typically zero), and 2) they are expressible as the linear weighted sum of the elements of the contingency table, where the weights are independent of the entries in the table, apart from the base rate. The authors demonstrate that the widely used “equitable threat score” (ETS), as well as numerous others, satisfies neither of these requirements and only satisfies the first requirement in the limit of an infinite sample size. Such measures are referred to as “asymptotically equitable.” In the case of ETS, the expected score of a random forecasting system is always positive and only falls below 0.01 when the number of samples is greater than around 30. Two other asymptotically equitable measures are the odds ratio skill score and the symmetric extreme dependency score, which are more strongly inequitable than ETS, particularly for rare events; for example, when the base rate is 2% and the sample size is 1000, random but unbiased forecasting systems yield an expected score of around −0.5, reducing in magnitude to −0.01 or smaller only for sample sizes exceeding 25 000. This presents a problem since these nonlinear measures have other desirable properties, in particular being reliable indicators of skill for rare events (provided that the sample size is large enough). A potential way to reconcile these properties with equitability is to recognize that Gandin and Murphy’s two requirements are independent, and the second can be safely discarded without losing the key advantages of equitability that are embodied in the first. This enables inequitable and asymptotically equitable measures to be scaled to make them equitable, while retaining their nonlinearity and other properties such as being reliable indicators of skill for rare events. It also opens up the possibility of designing new equitable verification measures

Infant lung function tests as endpoints in the ISIS multicenter clinical trial in cystic fibrosis

BACKGROUND: The Infant Study of Inhaled Saline (ISIS) in CF was the first multicenter clinical trial to utilize infant pulmonary function tests (iPFTs) as an endpoint. METHODS: Secondary analysis of ISIS data was conducted in order to assess feasibility of iPFT measures and their associations with respiratory symptoms. Standard deviations were calculated to aid in power calculations for future clinical trials. RESULTS: Seventy-three participants enrolled, 70 returned for the final visit; 62 (89%) and 45 (64%) had acceptable paired functional residual capacity (FRC) and raised volume measurements, respectively. Mean baseline FEV0.5, FEF75 and FRC z-scores were 0.3 (SD: 1.2), -0.2 (SD: 2.0), and 1.8 (SD: 2.0). CONCLUSIONS: iPFTs are not appropriate primary endpoints for multicenter clinical trials due to challenges of obtaining acceptable data and near-normal average raised volume measurements. Raised volume measures have potential to serve as secondary endpoints in future clinical CF trials

Impact of Engineered Nanomaterials on Health: Considerations for Benefit-Risk Assessment

Nanotechnology encompasses the design, characterisation, production and application of materials and systems by controlling shape and size at the nanoscale (nanometres). Nanomaterials may differ from other materials because of their relatively large specific surface area, such that surface properties become particularly important. There has been rapid growth in investment in nanotechnology by both the public and private sectors worldwide. In the EU, nanotechnology is expected to become an important strategic contributor to achieving economic gain and societal and individual benefits. At the same time there is continuing scientific uncertainty and controversy about the safety of nanomaterials. It is important to ensure that timely policy development takes this into consideration. Uncertainty about safety may lead to polarised public debate and to business unwillingness to invest further. A clear regulatory framework to address potential health and environmental impacts, within the wider context of evaluating and communicating the benefit-risk balance, must be a core part of Europe's integrated efforts for nanotechnology innovation. While a number of studies have been carried out on the effect of environmental nanoparticles, e.g. from combustion processes, on human health, there is yet no generally acceptable paradigm for safety assessment of nanomaterials in consumer and other products. Therefore, a working group was established to consider issues for the possible impact of nanomaterials on human health focussing specifically on engineered nanomaterials. This represents the first joint initiative between EASAC and the Joint Research Centre of the European Commission. The working group was given the remit to describe the state of the art of benefits and potential risks, current methods for safety assessment, and to evaluate their relevance, identify knowledge gaps in studying the safety of current nanomaterials, and recommend on priorities for nanomaterial research and the regulatory framework. This report focuses on key principles and issues, cross-referencing other sources for detailed information, rather than attempting a comprehensive account of the science. The focus is on human health although environmental effects are also discussed when directly relevant to healt

Evaluation of Serologic and Antigenic Relationships Between Middle Eastern Respiratory Syndrome Coronavirus and Other Coronaviruses to Develop Vaccine Platforms for the Rapid Response to Emerging Coronaviruses

Background. Middle East respiratory syndrome coronavirus (MERS-CoV) emerged in 2012, causing severe acute respiratory disease and pneumonia, with 44% mortality among 136 cases to date. Design of vaccines to limit the virus spread or diagnostic tests to track newly emerging strains requires knowledge of antigenic and serologic relationships between MERS-CoV and other CoVs

A Mouse Model for Betacoronavirus Subgroup 2c Using a Bat Coronavirus Strain HKU5 Variant

ABSTRACT Cross-species transmission of zoonotic coronaviruses (CoVs) can result in pandemic disease outbreaks. Middle East respiratory syndrome CoV (MERS-CoV), identified in 2012, has caused 182 cases to date, with ~43% mortality, and no small animal model has been reported. MERS-CoV and Pipistrellus bat coronavirus (BtCoV) strain HKU5 of Betacoronavirus (β-CoV) subgroup 2c share >65% identity at the amino acid level in several regions, including nonstructural protein 5 (nsp5) and the nucleocapsid (N) protein, which are significant drug and vaccine targets. BtCoV HKU5 has been described in silico but has not been shown to replicate in culture, thus hampering drug and vaccine studies against subgroup 2c β-CoVs. We report the synthetic reconstruction and testing of BtCoV HKU5 containing the severe acute respiratory syndrome (SARS)-CoV spike (S) glycoprotein ectodomain (BtCoV HKU5-SE). This virus replicates efficiently in cell culture and in young and aged mice, where the virus targets airway and alveolar epithelial cells. Unlike some subgroup 2b SARS-CoV vaccines that elicit a strong eosinophilia following challenge, we demonstrate that BtCoV HKU5 and MERS-CoV N-expressing Venezuelan equine encephalitis virus replicon particle (VRP) vaccines do not cause extensive eosinophilia following BtCoV HKU5-SE challenge. Passage of BtCoV HKU5-SE in young mice resulted in enhanced virulence, causing 20% weight loss, diffuse alveolar damage, and hyaline membrane formation in aged mice. Passaged virus was characterized by mutations in the nsp13, nsp14, open reading frame 5 (ORF5) and M genes. Finally, we identified an inhibitor active against the nsp5 proteases of subgroup 2c β-CoVs. Synthetic-genome platforms capable of reconstituting emerging zoonotic viral pathogens or their phylogenetic relatives provide new strategies for identifying broad-based therapeutics, evaluating vaccine outcomes, and studying viral pathogenesis.IMPORTANCEThe 2012 outbreak of MERS-CoV raises the specter of another global epidemic, similar to the 2003 SARS-CoV epidemic. MERS-CoV is related to BtCoV HKU5 in target regions that are essential for drug and vaccine testing. Because no small animal model exists to evaluate MERS-CoV pathogenesis or to test vaccines, we constructed a recombinant BtCoV HKU5 that expressed a region of the SARS-CoV spike (S) glycoprotein, thereby allowing the recombinant virus to grow in cell culture and in mice. We show that this recombinant virus targets airway epithelial cells and causes disease in aged mice. We use this platform to (i) identify a broad-spectrum antiviral that can potentially inhibit viruses closely related to MERS-CoV, (ii) demonstrate the absence of increased eosinophilic immune pathology for MERS-CoV N protein-based vaccines, and (iii) mouse adapt this virus to identify viral genetic determinants of cross-species transmission and virulence. This study holds significance as a strategy to control newly emerging viruses