Variance Analysis of Unevenly Spaced Time Series Data

We have investigated the effect of uneven data spacing on the computation of delta (sub chi)(gamma). Evenly spaced simulated data sets were generated for noise processes ranging from white phase modulation (PM) to random walk frequency modulation (FM). Delta(sub chi)(gamma) was then calculated for each noise type. Data were subsequently removed from each simulated data set using typical two-way satellite time and frequency transfer (TWSTFT) data patterns to create two unevenly spaced sets with average intervals of 2.8 and 3.6 days. Delta(sub chi)(gamma) was then calculated for each sparse data set using two different approaches. First the missing data points were replaced by linear interpolation and delta (sub chi)(gamma) calculated from this now full data set. The second approach ignored the fact that the data were unevenly spaced and calculated delta(sub chi)(gamma) as if the data were equally spaced with average spacing of 2.8 or 3.6 days. Both approaches have advantages and disadvantages, and techniques are presented for correcting errors caused by uneven data spacing in typical TWSTFT data sets

Class Standing Differences in Bystander Intervention Intentions to Prevent Sexual Assault: A Reasoned Action Approach

The purpose of this study was to examine differences in determinants of bystander intervention (BI) participation based on undergraduate students\u27 year in school using the Reasoned Action Approach (RAA). Students (n = 291) were recruited from general education courses at two universities in the United States and completed an online survey evaluating intentions, attitudes, perceived norms, and perceived behavioral control (PBC) associated with engaging in BI. Next, attitudes, perceived norms, and PBC were used to predict intentions using separate linear regression models – one model with upper-level students and another model with first-year students. Both models significantly predicted intentions, with the upper-level student model (adjusted R2 = 0.609) accounting for more variance compared to the first-year student model (adjusted R2 = 0.469). When compared to upper-level students, freshman also had significantly greater knowledge, intentions, and perceived norms, PBC and autonomy to engage in BI (p \u3c .05). These findings provide an in-depth understanding regarding the role of class standing in BI behavior. Results indicate students have different reasons for engaging/not engaging in BI based on year in school and support the need for targeted BI reinforcement sessions throughout the college years

Development and Validation of an Instrument Measuring Determinants of Bystander Intervention to Prevent Sexual Assault: An application of the Reasoned Action Approach

Bystander Intervention (BI) is an evidence-based approach that is considered the gold standard by governmental organizations to reduce sexual assault in college. Few survey instruments are available to measure the predispositions students have towards engaging in BI. Valid and reliable instruments are greatly needed, especially those tailored to BI. The purpose of this study was to develop and validate an instrument based on the reasoned action approach with college students at two U.S. universities. An elicitation of beliefs was accomplished to inform survey items (i.e., behavioral, normative, and control beliefs). Then, an initial draft was developed and sent to an expert panel to establish validity. The final instrument was administered to undergraduate students (n = 291), and further psychometric properties (construct validity and internal consistency reliability) were evaluated. Data were fit into two separate models to evaluate fit. In the first model, a four-factor solution was evaluated (intentions, attitudes, perceived norms, and perceived behavioral control), and while results were modest, the second seven-factor solution model contained a better fit (intentions, instrumental and experiential attitudes, injunctive and descriptive norms, capacity, and autonomy). Researchers and practitioners examining BI in college can use this instrument to measure theory-based determinants of BI to reduce sexual assault

Results of the Calibration of the Delays of Earth Stations for TWSTFT Using the VSL Satellite Simulator Method

Two-way satellite time and frequency transfer (TWSTFT) is the most accurate and precise method of comparing two remote clocks or time scales. The accuracy obtained is dependent on the accuracy of the determination of the non-reciprocal delays of the transmit and the receive paths. When the same transponders in the satellite at the same frequencies are used, then the non-reciprocity in the Earth stations is the limiting factor for absolute time transfer

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data.

Funder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health); doi: https://doi.org/10.13039/100011272; Grant(s): 305444, 305444Funder: Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness); doi: https://doi.org/10.13039/501100003329Funder: Generalitat de Catalunya (Government of Catalonia); doi: https://doi.org/10.13039/501100002809Funder: EC | European Regional Development Fund (Europski Fond za Regionalni Razvoj); doi: https://doi.org/10.13039/501100008530Funder: Instituto Nacional de Bioinformática ELIXIR Implementation Studies Centro de Excelencia Severo OchoaFunder: EC | EC Seventh Framework Programm | FP7 Health (FP7-HEALTH - Specific Programme "Cooperation": Health)Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP's Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient's data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Solving unsolved rare neurological diseases-a Solve-RD viewpoint.

Funder: Durch Princess Beatrix Muscle Fund Durch Speeren voor Spieren Muscle FundFunder: University of Tübingen Medical Faculty PATE programFunder: European Reference Network for Rare Neurological Diseases | 739510Funder: European Joint Program on Rare Diseases (EJP-RD COFUND-EJP) | 44140962

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Comparison of Characteristics of Patients who Received Posaconazole or Voriconazole for the Treatment of Coccidioidomycosis

Class of 2013 AbstractSpecific Aims: To describe the characteristics of patients who were switched to or prescribed posaconazole or voriconazole for the treatment of coccidioidomycosis including duration of previous anti-fungal treatment and rationale for changing from the first-line agents to posaconazole or voriconazole. Methods: This was a retrospective medical chart review of all patients admitted to an academic medical center with a diagnosis of coccidioidomycosis and prescribed posaconazole or voriconazole between January 2008 and December 2011. Subjects for the study were identified by ICD-9 codes for coccidioidomycosis (114.0-114.9) and through the pharmacy system for orders for posaconazole or voriconazole. Data collected included demographic information, antifungal prescription data, and outcome of fungal infection, if available. Main Results: A total of 41 subjects were identified as being prescribed either voriconazole or posaconazole for a diagnosis for coccidioidomycosis. The majority of subjects were prescribed voriconazole (93%) rather than posaconazole. While the majority of subjects were diagnosed with only pulmonary disease, 44% of subjects’ coccidioidomycosis diagnoses were classified as disseminated and 46% were admitted to an intensive care unit. The median (range) duration of first-line antifungal therapy was 3 (2-10) days for the posaconazole group and 3 (0-25) days for the voriconazole group. Overall, the reason(s) for switching antifungal therapy was listed as: failure of first-line therapy (26%), adverse drug event (4.3%), other (35%), and unknown (35%). Conclusion: There was no significant difference in baseline or disease characteristics between patients who were prescribed voriconazole or posaconazole for coccidioidomycosis. The main limitation of this retrospective evaluation is that the reason for use of voriconazole or posaconazole rather than first-line agents was often not easily determined based on the documentation in the medical records.This item is part of the Pharmacy Student Research Projects collection, made available by the College of Pharmacy and the University Libraries at the University of Arizona. For more information about items in this collection, please contact Jennifer Martin, Librarian and Clinical Instructor, Pharmacy Practice and Science, [email protected]