3,382 research outputs found

    Fluidic temperature control system for liquid- cooled space suits

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    Fluidic temperature control system for liquid cooled space suit

    Platelets are required for enhanced activation of the endothelium and fibrinogen in a mouse thrombosis model of APS

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    Antiphospholipid syndrome (APS) is defined by thrombosis, fetal loss, and the presence of antiphospholipid antibodies, including anti-beta 2-glycoprotein-1 autoantibodies (anti-beta 2GP1) that have a direct role in the pathogenesis of thrombosis in vivo. The cellular targets of the anti-beta 2GP1autoantibody/beta 2GP1complex in vivo were studied using a laser-induced thrombosis model of APS in a live mouse and human anti-beta 2GP1 autoantibodies affinity-purified from APS patients. Cell binding of fluorescently labeled beta 2GP1 and anti-beta 2GP1 autoantibodies revealed their colocalization on the platelet thrombus but not the endothelium. Anti-beta 2GP1 autoantibodies enhanced platelet activation, monitored by calcium mobilization, and endothelial activation, monitored by intercellular adhesion molecule-1 expression. When eptifibatide was infused to block platelet thrombus formation, enhanced fibrin generation and endothelial cell activation were eliminated. Thus, the anti-beta 2GP1 autoantibody/beta 2GP1 complex binds to the thrombus, enhancing platelet activation, and platelet secretion leads to enhanced endothelium activation and fibrin generation. These results lead to a paradigm shift away from the concept that binding of the anti-beta 2GP1 autoantibody/beta 2GP1 complex activates both endothelial cells and platelets toward one in which activation of platelets in response to anti-beta 2GP1 autoantibody/beta 2GP1 complex binding leads to subsequent enhanced endothelium activation and fibrin generation

    <i>‘What retention’ means to me</i>: the position of the adult learner in student retention

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    Studies of student retention and progression overwhelmingly appear adopt definitions that place the institution, rather than the student, at the centre. Retention is most often conceived in terms of linear and continuous progress between institutionally identified start and end points. This paper reports on research that considered data from 38 in-depth interviews conducted with individuals who had characteristics often associated with non-traditional engagement in higher education who between 2006 and 2010 had studied an ‘Introduction to HE’ module at one distance higher education institution, some of whom had progressed to further study at that institution, some of whom had not. The research deployed a life histories approach to seek a finer grained understanding of how individuals conceptualise their own learning journey and experience, in order to reflect on institutional conceptions of student retention. The findings highlight potential anomalies hidden within institutional retention rates – large proportions of the interview participants who were not ‘retained’ by the institution reported successful progression to and in other learning institutions and environments, both formal and informal. Nearly all described positive perspectives on lifelong learning which were either engendered or improved by the learning undertaken. This attests to the complexity of individuals’ lives and provides clear evidence that institution-centric definitions of retention and progression are insufficient to create truly meaningful understanding of successful individual learning journeys and experiences. It is argued that only through careful consideration of the lived experience of students and a re-conception of measures of retention, will we be able to offer real insight into improving student retention

    Studying the Pulsation of Mira Variables in the Ultraviolet

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    We present results from an empirical study of the Mg II h & k emission lines of selected Mira variable stars, using spectra from the International Ultraviolet Explorer (IUE). The stars all exhibit similar Mg II behavior during the course of their pulsation cycles. The Mg II flux always peaks after optical maximum near pulsation phase 0.2-0.5, although the Mg II flux can vary greatly from one cycle to the next. The lines are highly blueshifted, with the magnitude of the blueshift decreasing with phase. The widths of the Mg II lines are also phase-dependent, decreasing from about 70 km/s to 40 km/s between phase 0.2 and 0.6. We also study other UV emission lines apparent in the IUE spectra, most of them Fe II lines. These lines are much narrower and not nearly as blueshifted as the Mg II lines. They exhibit the same phase-dependent flux behavior as Mg II, but they do not show similar velocity or width variations.Comment: 26 pages, 12 figures; AASTEX v5.0 plus EPSF extensions in mkfig.sty; to appear in Ap

    Thrombus Formation: Direct Real‐Time Observation and Digital Analysis of Thrombus Assembly in a Living Mouse by Confocal and Widefield Intravital Microscopy

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    We have developed novel instrumentation using confocal and widefield microscopy to image and analyze thrombus formation in real time in the microcirculation of a living mouse. This system provides high-speed, near-simultaneous acquisition of images of multiple fluorescent probes and a brightfield channel, and supports laser-induced injury through the microscope optics. Although this imaging facility requires interface of multiple hardware components, the primary challenge in vascular imaging is careful experimental design and interpretation. This system has been used to localize tissue factor during thrombus formation, to observe defects in thrombus assembly in genetically altered mice, to study the kinetics of platelet activation and P-selectin expression following vascular injury, to analyze leukocyte rolling on arterial thrombi, to generate three-dimensional models of thrombi, and to analyze the effect of antithrombotic agents in vivo

    Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

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    A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data
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