Investigating intra-host and intra-herd sequence diversity of foot-and-mouth disease virus

Due to the poor-fidelity of the enzymes involved in RNA genome replication, foot-and-mouth disease (FMD) virus samples comprise of unique polymorphic populations. In this study, deep sequencing was utilised to characterise the diversity of FMD virus (FMDV) populations in 6 infected cattle present on a single farm during the series of outbreaks in the UK in 2007. A novel RT–PCR method was developed to amplify a 7.6 kb nucleotide fragment encompassing the polyprotein coding region of the FMDV genome. Illumina sequencing of each sample identified the fine polymorphic structures at each nucleotide position, from consensus level changes to variants present at a 0.24% frequency. These data were used to investigate population dynamics of FMDV at both herd and host levels, evaluate the impact of host on the viral swarm structure and to identify transmission links with viruses recovered from other farms in the same series of outbreaks. In 7 samples, from 6 different animals, a total of 5 consensus level variants were identified, in addition to 104 sub-consensus variants of which 22 were shared between 2 or more animals. Further analysis revealed differences in swarm structures from samples derived from the same animal suggesting the presence of distinct viral populations evolving independently at different lesion sites within the same infected animal

Factorial invariance of the Patient Health Questionnaire and Generalized Anxiety Disorder Questionnaire.

The UK's Improving Access to Psychological Therapies (IAPT) programme uses the Patient Health Questionnaire Depression Scale (PHQ-9; Kroenke, Spitzer, & Williams, , J. Gen. Intern. Med., 16, 606) and Generalized Anxiety Disorder Scale (GAD-7; Spitzer et al., , Arch. Intern. Med., 166, 1092) to assess patients' symptoms of depression and anxiety respectively. Data are typically collected via telephone or face-to-face; however, no study has statistically investigated whether the questionnaires' items operate equivalently across these modes of data collection. This study aimed to address this omission

An Evolutionary Framework for Association Testing in Resequencing Studies

Sequencing technologies are becoming cheap enough to apply to large numbers of study participants and promise to provide new insights into human phenotypes by bringing to light rare and previously unknown genetic variants. We develop a new framework for the analysis of sequence data that incorporates all of the major features of previously proposed approaches, including those focused on allele counts and allele burden, but is both more general and more powerful. We harness population genetic theory to provide prior information on effect sizes and to create a pooling strategy for information from rare variants. Our method, EMMPAT (Evolutionary Mixed Model for Pooled Association Testing), generates a single test per gene (substantially reducing multiple testing concerns), facilitates graphical summaries, and improves the interpretation of results by allowing calculation of attributable variance. Simulations show that, relative to previously used approaches, our method increases the power to detect genes that affect phenotype when natural selection has kept alleles with large effect sizes rare. We demonstrate our approach on a population-based re-sequencing study of association between serum triglycerides and variation in ANGPTL4.</p

Ohio 4-H Youth Development Extension Agents\u27 Use of Volunteer Screening Tools

While volunteers are needed for youth development programs, it is imperative that a sound selection process is in place so that the most appropriate individuals are selected to work with young people. The article outlines the results of a research project undertaken to describe the current use of volunteer selection tools with the Ohio 4-H Youth Development program. The authors describe the level of use of specific selection tools and the extent to which specific volunteers are screened prior to placement. The authors offer recommendations and implications applicable to any Extension program using volunteers to deliver programs to vulnerable audiences

A framework for automated anomaly detection in high frequency water-quality data from in situ sensors

River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by technical issues confound these data, while the volume and velocity of data prevent manual detection. We present a framework for automated anomaly detection in high-frequency water-quality data from in situ sensors, using turbidity, conductivity and river level data. After identifying end-user needs and defining anomalies, we ranked their importance and selected suitable detection methods. High priority anomalies included sudden isolated spikes and level shifts, most of which were classified correctly by regression-based methods such as autoregressive integrated moving average models. However, using other water-quality variables as covariates reduced performance due to complex relationships among variables. Classification of drift and periods of anomalously low or high variability improved when we applied replaced anomalous measurements with forecasts, but this inflated false positive rates. Feature-based methods also performed well on high priority anomalies, but were also less proficient at detecting lower priority anomalies, resulting in high false negative rates. Unlike regression-based methods, all feature-based methods produced low false positive rates, but did not and require training or optimization. Rule-based methods successfully detected impossible values and missing observations. Thus, we recommend using a combination of methods to improve anomaly detection performance, whilst minimizing false detection rates. Furthermore, our framework emphasizes the importance of communication between end-users and analysts for optimal outcomes with respect to both detection performance and end-user needs. Our framework is applicable to other types of high frequency time-series data and anomaly detection applications

Polar motion and UT1: Comparison of VLBI, lunar laser, satellite laser, satellite Doppler, and conventional astrometric determinations

Very long baseline interferometry observations made with a 3900 km baseline interferometer (Haystack Observatory in Massachusetts to Owens Valley Observation in California) were used to estimate changes in the X-component of the position of the Earth's pole and in UT1. These estimates are compared with corresponding ones from lunar laser ranging, satellite laser ranging, satellite Doppler, and stellar observations

Transport through an impurity tunnel coupled to a Si/SiGe quantum dot

Achieving controllable coupling of dopants in silicon is crucial for operating donor-based qubit devices, but it is difficult because of the small size of donor-bound electron wavefunctions. Here we report the characterization of a quantum dot coupled to a localized electronic state, and we present evidence of controllable coupling between the quantum dot and the localized state. A set of measurements of transport through this device enable the determination of the most likely location of the localized state, consistent with an electronically active impurity in the quantum well near the edge of the quantum dot. The experiments we report are consistent with a gate-voltage controllable tunnel coupling, which is an important building block for hybrid donor and gate-defined quantum dot devices.Comment: 5 pages, 3 figure

Application of the IDEAS Framework in Adapting a Web-Based Physical Activity Intervention for Young Adult College Students

User-centered developmental processes are critical to ensuring acceptability of e-health behavioral interventions, and yet physical activity research continues to be inundated with top-down developmental approaches. The IDEAS (Integrate, Design, Assess, and Share) framework outlines a user-centered process for development of e-health interventions. The purpose of this manuscript is to describe the application of the IDEAS framework in adapting a web-based physical activity intervention for young adult college students. Steps 1–3 emphasized integrating insights from users and theory and Steps 4–7 focused on iterative and rapid design with user feedback. Data were collected via repeat qualitative interviews with young adult college students (N = 7). Resulting qualitative metathemes were engagement, accountability, and cultural fit. Therefore, intervention modifications focused on strategies to foster ongoing engagement with the program (e.g., increase interactivity), support personal and social accountability (e.g., private social media group), and provide a cultural fit within the college lifestyle (e.g., images relevant to student life). The resulting web-based intervention included eight weekly lessons, an expanded resource library, “how-to” videos, step and goal trackers, and a private social media group to be led by a wellness coach. In conclusion, the IDEAS framework guided an efficient, user-centered adaptation process that integrated empirical evidence and behavior change theory with user preferences and feedback. Furthermore, the process allowed us to address barriers to acceptability during the design and build stages rather than at later stages of pilot and efficacy testing