187 resultados para Similarity measure


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We describe methods for obtaining a quantitative description of RNA processing at high resolution in budding yeast. As a model gene expression system, we constructed tetON (for induction studies) and tetOFF (for repression, derepression, and RNA degradation studies) yeast strains with a series of reporter genes integrated in the genome under the control of a tetO7 promoter. Reverse transcription and quantitative real-time-PCR (RT-qPCR) methods were adapted to allow the determination of mRNA abundance as the average number of copies per cell in a population. Fluorescence in situ hybridization (FISH) measurements of transcript numbers in individual cells validated the RT-qPCR approach for the average copy-number determination despite the broad distribution of transcript levels within a population of cells. In addition, RT-qPCR was used to distinguish the products of the different steps in splicing of the reporter transcripts, and methods were developed to map and quantify 3′-end cleavage and polyadenylation. This system permits pre-mRNA production, splicing, 3′-end maturation and degradation to be quantitatively monitored with unprecedented kinetic detail, suitable for mathematical modeling. Using this approach, we demonstrate that reporter transcripts are spliced prior to their 3′-end cleavage and polyadenylation, that is, cotranscriptionally.

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This report summarizes the proceedings of the first Outcome Measures in Rheumatology Clinical Trials (OMERACT) Health Literacy Special Interest Group workshop at the OMERACT 10 conference. Health literacy refers to an individual’s capacity to seek, understand, and use health information. Discussion centered on the relevance of health literacy to the rheumatology field; whether measures of health literacy were important in the context of clinical trials and routine care; and, if so, whether disease-specific measures were required. A nominal group process involving 27 workshop participants, comprising a patient group (n = 12) and a healthcare professional and researcher group (n = 15), confirmed that health literacy encompasses a broad range of concepts and skills that existing scales do not measure. It identified the importance and relevance of patient abilities and characteristics, but also health professional factors and broader contextual factors. Sixteen themes were identified: access to information; cognitive capacity; disease; expression/communication; finances; health professionals; health system; information; literacy/numeracy; management skills; medication; patient approach; dealing with problems; psychological characteristics; social supports; and time. Each of these was divided further into subthemes of one or more of the following: knowledge, attitude, attribute, relationship, skill, action, or context. There were virtually no musculoskeletal-specific statements, suggesting that a generic health literacy tool in rheumatology is justified. The detailed concepts across themes provided new and systematic insight into what needs to be done to improve health literacy and consequently reduce health inequalities. These data will be used to derive a more comprehensive measure of health literacy.

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The workshop Choosing or Developing Instruments held at the Outcome Measures in Rheumatology (OMERACT) 10 meeting was designed to help participants think about the underlying methods of instrument development. Conference pre-reading material and 3 brief introductory presentations elaborated the issues, and participants broke into discussion groups before reconvening to share insights, engage in a more general discussion of the issues, and vote on recommendations. Trade offs between using current imperfect measures and the long and complex process of developing new instruments were considered, together with the need for rigor in patient-reported outcome (PRO) instrument development. The main considerations for PRO instrument development were listed and a research agenda for action produced. As part of the agenda for action, it is recommended that researchers and patient partners work together to tackle these issues, and that OMERACT bring forward proposals for acceptable instrument development protocols that would meet an enhanced “Truth” statement in the OMERACT Filter.

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Centrelink information, as well as postcodes, will determine student SES for the purposes of the new equity loading – but only as an interim measure.

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Any new measure of SES needs to have the confidence of the sector and is fit for purpose, writes Trevor Gale.

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Background: The concept of resilience has captured the imagination of researchers and policy makers over the past two decades. However, despite the ever growing body of resilience research, there is a paucity of relevant, comprehensive measurement tools. In this article, the development of a theoretically based, comprehensive multidimensional measure of resilience in adolescents is described.

Methods: Extensive literature review and focus groups with young people living with chronic illness informed the conceptual development of scales and items. Two sequential rounds of factor and scale analyses were undertaken to revise the conceptually developed scales using data collected from young people living with a chronic illness and a general population sample.

Results: The revised Adolescent Resilience Questionnaire comprises 93 items and 12 scales measuring resilience factors in the domains of self, family, peer, school and community. All scales have acceptable alpha coefficients. Revised scales closely reflect conceptually developed scales.

Conclusions: It is proposed that, with further psychometric testing, this new measure of resilience will provide researchers and clinicians with a comprehensive and developmentally appropriate instrument to measure a young person’s capacity to achieve positive outcomes despite life stressors.

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Static detection of polymorphic malware variants plays an important role to improve system security. Control flow has shown to be an effective characteristic that represents polymorphic malware instances. In our research, we propose a similarity search of malware using novel distance metrics of malware signatures. We describe a malware signature by the set of control flow graphs the malware contains. We propose two approaches and use the first to perform pre-filtering. Firstly, we use a distance metric based on the distance between feature vectors. The feature vector is a decomposition of the set of graphs into either fixed size k-sub graphs, or q-gram strings of the high-level source after decompilation. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flow graphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms.