274 research outputs found

    Computer-interpretable guidelines: electronic tools to enhance the utility of thyroid nodule clinical practice guidelines and risk stratification tools

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    Clinicians seeking guidance for evaluating and managing thyroid nodules currently have several resources. The principal ones are narrative clinical guidelines and clinical risk calculators. This paper will review the strengths and weaknesses of both. The paper will introduce a concept of computer interpretable guideline, a novel way of transforming narrative guidelines in to a clinical decision support tool that can provide patient specific recommendations at the point of care. The paper then describes an experience of developing an interactive web based computer interpretable guideline for thyroid nodule management, called Thyroid Nodule Management App (TNAPP). The advantages of this approach and the potential barriers for widespread adaptation are discussed

    The Role of Quantitative Pharmacology in an Academic Translational Research Environment

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    Translational research is generally described as the application of basic science discoveries to the treatment or prevention of disease or injury. Its value is usually determined based on the likelihood that exploratory or developmental research can yield effective therapies. While the pharmaceutical industry has evolved into a highly specialized sector engaged in translational research, the academic medical research community has similarly embraced this paradigm largely through the motivation of the National Institute of Health (NIH) via its Roadmap initiative. The Clinical and Translational Science Award (CTSA) has created opportunities for institutions which can provide the multidisciplinary environment required to engage such research. A key component of the CTSA and an element of both the NIH Roadmap and the FDA Critical Path is the bridging of bench and bedside science via quantitative pharmacologic relationships. The infrastructure of the University of Pennsylvania/Children’s Hospital of Philadelphia CTSA is highlighted relative to both research and educational objectives reliant upon quantitative pharmacology. A case study, NIH-sponsored research program exploring NK1r antagonism for the treatment NeuroAIDS is used to illustrate the application of quantitative pharmacology in a translational research paradigm

    BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

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    Background: The K3326X variant in BRCA2 (BRCA2*c.9976A>T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

    The Mechanism of Release of P-TEFb and HEXIM1 from the 7SK snRNP by Viral and Cellular Activators Includes a Conformational Change in 7SK

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    The positive transcription elongation factor, P-TEFb, is required for the production of mRNAs, however the majority of the factor is present in the 7SK snRNP where it is inactivated by HEXIM1. Expression of HIV-1 Tat leads to release of P-TEFb and HEXIM1 from the 7SK snRNP in vivo, but the release mechanisms are unclear.We developed an in vitro P-TEFb release assay in which the 7SK snRNP immunoprecipitated from HeLa cell lysates using antibodies to LARP7 was incubated with potential release factors. We found that P-TEFb was directly released from the 7SK snRNP by HIV-1 Tat or the P-TEFb binding region of the cellular activator Brd4. Glycerol gradient sedimentation analysis was used to demonstrate that the same Brd4 protein transfected into HeLa cells caused the release of P-TEFb and HEXIM1 from the 7SK snRNP in vivo. Although HEXIM1 binds tightly to 7SK RNA in vitro, release of P-TEFb from the 7SK snRNP is accompanied by the loss of HEXIM1. Using a chemical modification method, we determined that concomitant with the release of HEXIM1, 7SK underwent a major conformational change that blocks re-association of HEXIM1.Given that promoter proximally paused polymerases are present on most human genes, understanding how activators recruit P-TEFb to those genes is critical. Our findings reveal that the two tested activators can extract P-TEFb from the 7SK snRNP. Importantly, we found that after P-TEFb is extracted a dramatic conformational change occurred in 7SK concomitant with the ejection of HEXIM1. Based on our findings, we hypothesize that reincorporation of HEXIM1 into the 7SK snRNP is likely the regulated step of reassembly of the 7SK snRNP containing P-TEFb

    Evaluation of established breast cancer risk factors as modifiers of BRCA1 or BRCA2: a multi-center case-only analysis

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    The incomplete penetrance of mutations in BRCA1 and BRCA2 suggests that some combination of environmental and genetic factors modifies the risk of breast cancer in mutation carriers. The current study sought to identify possible interactions between established breast cancer risk factors and BRCA1 or BRCA2 mutations using a case-only study design. Breast cancer cases that had been tested for BRCA1 and BRCA2 mutations were identified from 11 collaborating centers. Comparisons of reproductive and lifestyle risk factors were made between women with breast cancer who were positive for BRCA1 mutations (n=283), BRCA2 mutations (n=204) or negative for both BRCA1 and BRCA2 mutations (n=894). Interaction risk ratios (IRRs) were calculated using multinominal logistic regression models. Compared with non-carriers, statistically significant IRRs were observed for later age at menarche among BRCA2 mutation carriers, for a greater number of pregnancies among both BRCA1 and BRCA2 mutation carriers, and for alcohol use among BRCA1 mutation carriers. Our data suggest that the risk for breast cancer among BRCA1 or BRCA2 carriers may be modified by reproductive characteristics and alcohol use. However, our results should be interpreted cautiously given the overall inconsistency in the epidemiologic literature on modifiers of BRCA1 and BRCA2

    A Single-Stranded DNA Aptamer That Selectively Binds to Staphylococcus aureus Enterotoxin B

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    The bacterium Staphylococcus aureus is a common foodborne pathogen capable of secreting a cocktail of small, stable, and strain-specific, staphylococcal enterotoxins (SEs). Staphylococcal food poisoning (SFP) results when improperly handled food contaminated with SEs is consumed. Gastrointestinal symptoms of SFP include emesis, diarrhea and severe abdominal pain, which manifest within hours of ingesting contaminated food. Immuno-affinity based methods directly detect, identify, and quantify several SEs within a food or clinical sample. However, the success of these assays depends upon the availability of a monoclonal antibody, the development of which is non-trivial and costly. The current scope of the available immuno-affinity based methods is limited to the classical SEs and does not encompass all of the known or emergent SEs. In contrast to antibodies, aptamers are short nucleic acids that exhibit high affinity and specificity for their targets without the high-costs and ethical concerns of animal husbandry. Further, researchers may choose to freely distribute aptamers and develop assays without the proprietary issues that increase the per-sample cost of immuno-affinity assays. This study describes a novel aptamer, selected in vitro, with affinity to staphylococcal enterotoxin B (SEB) that may be used in lieu of antibodies in SE detection assays. The aptamer, designated APTSEB1, successfully isolates SEB from a complex mixture of SEs with extremely high discrimination. This work sets the foundation for future aptamer and assay development towards the entire family of SEs. The rapid, robust, and low-cost identification and quantification of all of the SEs in S. aureus contaminated food is essential for food safety and epidemiological efforts. An in vitro generated library of SE aptamers could potentially allow for the comprehensive and cost-effective analysis of food samples that immuno-affinity assays currently cannot provide

    GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

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    GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts
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