402 research outputs found

    Carotid Artery Wall Imaging: Perspective and Guidelines from the ASNR Vessel Wall Imaging Study Group and Expert Consensus Recommendations of the American Society of Neuroradiology

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    SUMMARY: Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis and surface irregularities using in vivo imaging techniques including sonography, CT and MR angiography, and digital subtraction angiography. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. The ability to look beyond the lumen using highly developed vessel wall imaging methods to identify plaque vulnerable to disruption has prompted an active debate as to whether a paradigm shift is needed to move away from relying on measurements of luminal stenosis for gauging the risk of ischemic injury. Further evaluation in randomized clinical trials will help to better define the exact role of plaque imaging in clinical decision-making. However, current carotid vessel wall imaging techniques can be informative. The goal of this article is to present the perspective of the ASNR Vessel Wall Imaging Study Group as it relates to the current status of arterial wall imaging in carotid artery disease

    Adult Drosophila melanogaster evolved for antibacterial defense invest in infection-induced expression of both humoral and cellular immunity genes

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    <p>Abstract</p> <p>Background</p> <p>While the transcription of innate immunity genes in response to bacterial infection has been well-characterised in the Drosophila model, we recently demonstrated the capacity for such transcription to evolve in flies selected for improved antibacterial defense. Here we use this experimental system to examine how insects invest in constitutive versus infection-induced transcription of immunity genes. These two strategies carry with them different consequences with respect to energetic and pleiotropic costs and may be more or less effective in improving defense depending on whether the genes contribute to humoral or cellular aspects of immunity.</p> <p>Findings</p> <p>Contrary to expectation we show that selection preferentially increased the infection-induced expression of both cellular and humoral immunity genes. Given their functional roles, infection induced increases in expression were expected for the humoral genes, while increases in constitutive expression were expected for the cellular genes. We also report a restricted ability to improve transcription of immunity genes that is on the order of 2-3 fold regardless of total transcription level of the gene.</p> <p>Conclusions</p> <p>The evolved increases in infection-induced expression of the cellular genes may result from specific cross talk with humoral pathways or from generalised strategies for enhancing immunity gene transcription. A failure to see improvements in constitutive expression of the cellular genes suggests either that increases might come at too great a cost or that patterns of expression in adults are decoupled from the larval phase where increases would be most effective. The similarity in fold change increase across all immunity genes may suggest a shared mechanism for the evolution of increased transcription in small, discrete units such as duplication of <it>cis</it>-regulatory elements.</p

    Endocrine disruptors and spontaneous premature labor: a case control study

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    <p>Abstract</p> <p>Background</p> <p>Premature labor is a poorly understood condition. Estrogen is thought to play a key role and therefore the labor process may be affected by endocrine disruptors. We sought to determine whether or not an environmental toxicant, DDE, or dietary derived endocrine disruptors, daidzein and genistein, are associated with spontaneous preterm labor.</p> <p>Methods</p> <p>Cases were defined as primiparous patients having a preterm delivery at or before 35 weeks following the spontaneous onset of labor. Controls were defined as primiparous women who delivered on the same day as the cases but at term gestation.</p> <p>Over approximately 1 year, 26 cases and 52 controls were recruited. Subjects agreed to have blood tests on day one postpartum for DDE and for the phytoestrogens genistein and daidzein.</p> <p>Results</p> <p>The mean concentration of DDE was similar in the case and control groups: 4.29 vs 4.32 ng/g lipid p = .85. In the case group, 13/26 had detectable levels of daidzein (range 0.20 – 1.56 ng/ml) compared to 25/52 controls (range 0.21 – 3.26 ng/ml). The mean concentration of daidzein was similar in cases compared to controls: 0.30 vs .34 ng/ml p = 0.91. Of the case group,14/26 had detectable levels of genistein (range 0.20 – 2.19 ng/ml) compared to 32/52 controls (range 0.21 – 2.55 ng/ml). The mean concentration of genistein was similar in cases compared to controls: 0.39 vs 0.31 ng/ml, p = 0.61.</p> <p>Conclusion</p> <p>The serum levels of DDE in this population were found to be low.</p> <p>There appears to be no relationship between serum concentrations of DDE, daidzein, and genistein and spontaneous preterm labor in our population. The inability to identify an effect may be related to the comparatively low concentrations of DDE in our population and the rapid and variable reduction of phytoestrogens from women in labor.</p

    A Visual Data Mining Tool that Facilitates Reconstruction of Transcription Regulatory Networks

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    Background: Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators. One difficulty lies in the interpretation of a list of differentially expressed genes, or in how to plan new experiments given that knowledge. Clustering methods can be used to identify groups of genes with similar expression patterns, and genes with unknown function can be provisionally annotated based on the concept of ‘‘guilt by association’’, where function is tentatively inferred from the known functions of genes with similar expression patterns. These methods frequently suffer from two limitations: (1) visualization usually only gives access to group membership, rather than specific information about nearest neighbors, and (2) the resolution or quality of the relationships are not easily inferred. Methodology/Principal Findings: We have addressed these issues by improving the precision of similarity detection over that of a single experiment and by creating a tool to visualize tractable association networks: we (1) performed metaanalysis computation of correlation coefficients for all gene pairs in a heterogeneous data set collected from 2,145 publicly available micorarray samples in mouse, (2) filtered the resulting distribution of over 130 million correlation coefficients to build new, more tractable distributions from the strongest correlations, and (3) designed and implemented a new Web based tool (StarNet

    Automation of a problem list using natural language processing

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    BACKGROUND: The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However, the current problem list is usually incomplete and inaccurate, and is often totally unused. To alleviate this issue, we are building an environment where the problem list can be easily and effectively maintained. METHODS: For this project, 80 medical problems were selected for their frequency of use in our future clinical field of evaluation (cardiovascular). We have developed an Automated Problem List system composed of two main components: a background and a foreground application. The background application uses Natural Language Processing (NLP) to harvest potential problem list entries from the list of 80 targeted problems detected in the multiple free-text electronic documents available in our electronic medical record. These proposed medical problems drive the foreground application designed for management of the problem list. Within this application, the extracted problems are proposed to the physicians for addition to the official problem list. RESULTS: The set of 80 targeted medical problems selected for this project covered about 5% of all possible diagnoses coded in ICD-9-CM in our study population (cardiovascular adult inpatients), but about 64% of all instances of these coded diagnoses. The system contains algorithms to detect first document sections, then sentences within these sections, and finally potential problems within the sentences. The initial evaluation of the section and sentence detection algorithms demonstrated a sensitivity and positive predictive value of 100% when detecting sections, and a sensitivity of 89% and a positive predictive value of 94% when detecting sentences. CONCLUSION: The global aim of our project is to automate the process of creating and maintaining a problem list for hospitalized patients and thereby help to guarantee the timeliness, accuracy and completeness of this information
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