922 resultados para Rasch measurement model
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Despite the increased use of intracranial neuromonitoring during experimental subarachnoid hemorrhage (SAH), coordinates for probe placement in rabbits are lacking. This study evaluates the safety and reliability of using outer skull landmarks to identify locations for placement of cerebral blood flow (CBF) and intraparenchymal intracranial pressure (ICP) probes. Experimental SAH was performed in 17 rabbits using an extracranial-intracranial shunt model. ICP probes were placed in the frontal lobe and compared to measurements recorded from the olfactory bulb. CBF probes were placed in various locations in the frontal cortex anterior to the coronary suture. Insertion depth, relation to the ventricular system, and ideal placement location were determined by post-mortem examination. ICP recordings at the time of SAH from the frontal lobe did not differ significantly from those obtained from the right olfactory bulb. Ideal coordinates for intraparenchymal CBF probes in the left and right frontal lobe were found to be located 4.6±0.9 and 4.5±1.2 anterior to the bregma, 4.7±0.7mm and 4.7±0.5mm parasagittal, and at depths of 4±0.5mm and 3.9±0.5mm, respectively. The results demonstrate that the presented coordinates based on skull landmarks allow reliable placement of intraparenchymal ICP and CBF probes in rabbit brains without the use of a stereotactic frame.
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Modifications and upgrades to the hydraulic flume facility in the Environmental Fluid Mechanics and Hydraulics Laboratory (EFM&H) at Bucknell University are described. These changes enable small-scale testing of model marine hydrokinetic(MHK) devices. The design of the experimental platform provides a controlled environment for testing of model MHK devices to determine their effect on localsubstrate. Specifically, the effects being studied are scour and erosion around a cylindrical support structure and deposition of sediment downstream from the device.
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This Letter presents a measurement of the W+ W- production cross section in sqrt(s) = 7 TeV pp collisions by the ATLAS experiment, using 34 pb(-1) of integrated luminosity produced by the Large Hadron Collider at CERN. Selecting events with two isolated leptons, each either an electron or a muon, 8 candidate events are observed with an expected background of 1.7 ± 0.6 events. The measured cross section is 41(-16)(+20)(stat) ± 5(syst)±1(lumi) pb, which is consistent with the standard model prediction of 44 ± 3 pb calculated at next-to-leading order in QCD.
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The present study assessed the effects of abrasion, salivary proteins, and measurement angle on the quantification of early dental erosion by the analysis of reflection intensities from enamel. Enamel from 184 caries-free human molars was used for in vitro erosion in citric acid (pH 3.6). Abrasion of the eroded enamel resulted in a 6% to 14% increase in the specular reflection intensity compared to only eroded enamel, and the reflection increase depended on the erosion degree. Nevertheless, monitoring of early erosion by reflection analysis was possible even in the abraded eroded teeth. The presence of the salivary pellicle induced up to 22% higher reflection intensities due to the smoothing of the eroded enamel by the adhered proteins. However, this measurement artifact could be significantly minimized (p<0.05) by removing the pellicle layer with 3% NaOCl solution. Change of the measurement angles from 45 to 60 deg did not improve the sensitivity of the analysis at late erosion stages. The applicability of the method for monitoring the remineralization of eroded enamel remained unclear in a demineralization/remineralization cycling model of early dental erosion in vitro.
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Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th-90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40-111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69-215 Bq/m³) in the medium category, and 219 Bq/m³ (108-427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be robust through validation with an independent dataset. The model is appropriate for predicting radon level exposure of the Swiss population in epidemiological research. Nevertheless, some exposure misclassification and regression to the mean is unavoidable and should be taken into account in future applications of the model.
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Brain functions, such as learning, orchestrating locomotion, memory recall, and processing information, all require glucose as a source of energy. During these functions, the glucose concentration decreases as the glucose is being consumed by brain cells. By measuring this drop in concentration, it is possible to determine which parts of the brain are used during specific functions and consequently, how much energy the brain requires to complete the function. One way to measure in vivo brain glucose levels is with a microdialysis probe. The drawback of this analytical procedure, as with many steadystate fluid flow systems, is that the probe fluid will not reach equilibrium with the brain fluid. Therefore, brain concentration is inferred by taking samples at multiple inlet glucose concentrations and finding a point of convergence. The goal of this thesis is to create a three-dimensional, time-dependent, finite element representation of the brainprobe system in COMSOL 4.2 that describes the diffusion and convection of glucose. Once validated with experimental results, this model can then be used to test parameters that experiments cannot access. When simulations were run using published values for physical constants (i.e. diffusivities, density and viscosity), the resulting glucose model concentrations were within the error of the experimental data. This verifies that the model is an accurate representation of the physical system. In addition to accurately describing the experimental brain-probe system, the model I created is able to show the validity of zero-net-flux for a given experiment. A useful discovery is that the slope of the zero-net-flux line is dependent on perfusate flow rate and diffusion coefficients, but it is independent of brain glucose concentrations. The model was simplified with the realization that the perfusate is at thermal equilibrium with the brain throughout the active region of the probe. This allowed for the assumption that all model parameters are temperature independent. The time to steady-state for the probe is approximately one minute. However, the signal degrades in the exit tubing due to Taylor dispersion, on the order of two minutes for two meters of tubing. Given an analytical instrument requiring a five μL aliquot, the smallest brain process measurable for this system is 13 minutes.
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A new physics-based technique for correcting inhomogeneities present in sub-daily temperature records is proposed. The approach accounts for changes in the sensor-shield characteristics that affect the energy balance dependent on ambient weather conditions (radiation, wind). An empirical model is formulated that reflects the main atmospheric processes and can be used in the correction step of a homogenization procedure. The model accounts for short- and long-wave radiation fluxes (including a snow cover component for albedo calculation) of a measurement system, such as a radiation shield. One part of the flux is further modulated by ventilation. The model requires only cloud cover and wind speed for each day, but detailed site-specific information is necessary. The final model has three free parameters, one of which is a constant offset. The three parameters can be determined, e.g., using the mean offsets for three observation times. The model is developed using the example of the change from the Wild screen to the Stevenson screen in the temperature record of Basel, Switzerland, in 1966. It is evaluated based on parallel measurements of both systems during a sub-period at this location, which were discovered during the writing of this paper. The model can be used in the correction step of homogenization to distribute a known mean step-size to every single measurement, thus providing a reasonable alternative correction procedure for high-resolution historical climate series. It also constitutes an error model, which may be applied, e.g., in data assimilation approaches.
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This paper presents a measurement of the W+W- production cross section in pp collisions at root s = 7 TeV. The leptonic decay channels are analyzed using data corresponding to an integrated luminosity of 4: 6 fb(-1) collected with the ATLAS detector at the Large Hadron Collider. The W+W- production cross section sigma(pp -> W+W- + X) is measured to be 51.9 +/- 2.0(stat) +/- 3.9(syst) +/- 2.0(lumi) pb, compatible with the Standard Model prediction of 44.7(-1.9)(+2.1) pb. A measurement of the normalized fiducial cross section as a function of the leading lepton transverse momentum is also presented. The reconstructed transverse momentum distribution of the leading lepton is used to extract limits on anomalous WWZ and WW gamma couplings.
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Transient inflammation is known to alter visceral sensory function and frequently precede the onset of symptoms in a subgroup of patients with irritable bowel syndrome (IBS). Duration and severity of the initial inflammatory stimulus appear to be risk factors for the manifestation of symptoms. Therefore, we aimed to characterize dose-dependent effects of trinitrobenzenesulfonic acid (TNBS)/ethanol on: (1) colonic mucosa, (2) cytokine release and (3) visceral sensory function in a rat model. Acute inflammation was induced in male Lewis rats by single administration of various doses of TNBS/ethanol (total of 0.8, 0.4 or 0.2 ml) in test animals or saline in controls. Assessment of visceromotor response (VMR) to colorectal distensions, histological evaluation of severity of inflammation, and measurement of pro-inflammatory cytokine levels (IL-2, IL-6) using enzyme-linked immunosorbent assay (ELISA) were performed 2h and 3, 14, 28, 31 and 42 days after induction. Increased serum IL-2 and IL-6 levels were evident prior to mucosal lesions 2h after induction of colitis and persist up to 14 days (p<0.05 vs. saline), although no histological signs of inflammation were detected at 14 days. In the acute phase, VMR was only significantly increased after 0.8 ml and 0.4 ml TNBS/ethanol (p<0.05 vs. saline). After 28 days, distension-evoked responses were persistently elevated (p<0.05 vs. saline) in 0.8 and 0.4 ml TNBS/ethanol-treated rats. In 0.2 ml TNBS/ethanol group, VMR was only enhanced after repeated visceral stimulation. Visceral hyperalgesia occurs after a transient colitis. However, even a mild acute but asymptomatic colitis can induce long-lasting visceral hyperalgesia in the presence of additional stimuli.
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We propose a new method for fitting proportional hazards models with error-prone covariates. Regression coefficients are estimated by solving an estimating equation that is the average of the partial likelihood scores based on imputed true covariates. For the purpose of imputation, a linear spline model is assumed on the baseline hazard. We discuss consistency and asymptotic normality of the resulting estimators, and propose a stochastic approximation scheme to obtain the estimates. The algorithm is easy to implement, and reduces to the ordinary Cox partial likelihood approach when the measurement error has a degenerative distribution. Simulations indicate high efficiency and robustness. We consider the special case where error-prone replicates are available on the unobserved true covariates. As expected, increasing the number of replicate for the unobserved covariates increases efficiency and reduces bias. We illustrate the practical utility of the proposed method with an Eastern Cooperative Oncology Group clinical trial where a genetic marker, c-myc expression level, is subject to measurement error.
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We describe a method for evaluating an ensemble of predictive models given a sample of observations comprising the model predictions and the outcome event measured with error. Our formulation allows us to simultaneously estimate measurement error parameters, true outcome — aka the gold standard — and a relative weighting of the predictive scores. We describe conditions necessary to estimate the gold standard and for these estimates to be calibrated and detail how our approach is related to, but distinct from, standard model combination techniques. We apply our approach to data from a study to evaluate a collection of BRCA1/BRCA2 gene mutation prediction scores. In this example, genotype is measured with error by one or more genetic assays. We estimate true genotype for each individual in the dataset, operating characteristics of the commonly used genotyping procedures and a relative weighting of the scores. Finally, we compare the scores against the gold standard genotype and find that Mendelian scores are, on average, the more refined and better calibrated of those considered and that the comparison is sensitive to measurement error in the gold standard.
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The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.
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Vitamin C (L-ascorbic acid) is an essential micronutrient that serves as an antioxidant and as a cofactor in many enzymatic reactions. Intestinal absorption and renal reabsorption of the vitamin is mediated by the epithelial apical L-ascorbic acid cotransporter SVCT1 (SLC23A1). We explored the molecular mechanisms of SVCT1-mediated L-ascorbic acid transport using radiotracer and voltage-clamp techniques in RNA-injected Xenopus oocytes. L-ascorbic acid transport was saturable (K(0.5) approximately 70 microM), temperature dependent (Q(10) approximately 5), and energized by the Na(+) electrochemical potential gradient. We obtained a Na(+)-L-ascorbic acid coupling ratio of 2:1 from simultaneous measurement of currents and fluxes. L-ascorbic acid and Na(+) saturation kinetics as a function of cosubstrate concentrations revealed a simultaneous transport mechanism in which binding is ordered Na(+), L-ascorbic acid, Na(+). In the absence of L-ascorbic acid, SVCT1 mediated pre-steady-state currents that decayed with time constants 3-15 ms. Transients were described by single Boltzmann distributions. At 100 mM Na(+), maximal charge translocation (Q(max)) was approximately 25 nC, around a midpoint (V(0.5)) at -9 mV, and with apparent valence approximately -1. Q(max) was conserved upon progressive removal of Na(+), whereas V(0.5) shifted to more hyperpolarized potentials. Model simulation predicted that the pre-steady-state current predominantly results from an ion-well effect on binding of the first Na(+) partway within the membrane electric field. We present a transport model for SVCT1 that will provide a framework for investigating the impact of specific mutations and polymorphisms in SLC23A1 and help us better understand the contribution of SVCT1 to vitamin C metabolism in health and disease.
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Skeletal muscle force evaluation is difficult to implement in a clinical setting. Muscle force is typically assessed through either manual muscle testing, isokinetic/isometric dynamometry, or electromyography (EMG). Manual muscle testing is a subjective evaluation of a patient’s ability to move voluntarily against gravity and to resist force applied by an examiner. Muscle testing using dynamometers adds accuracy by quantifying functional mechanical output of a limb. However, like manual muscle testing, dynamometry only provides estimates of the joint moment. EMG quantifies neuromuscular activation signals of individual muscles, and is used to infer muscle function. Despite the abundance of work performed to determine the degree to which EMG signals and muscle forces are related, the basic problem remains that EMG cannot provide a quantitative measurement of muscle force. Intramuscular pressure (IMP), the pressure applied by muscle fibers on interstitial fluid, has been considered as a correlate for muscle force. Numerous studies have shown that an approximately linear relationship exists between IMP and muscle force. A microsensor has recently been developed that is accurate, biocompatible, and appropriately sized for clinical use. While muscle force and pressure have been shown to be correlates, IMP has been shown to be non-uniform within the muscle. As it would not be practicable to experimentally evaluate how IMP is distributed, computational modeling may provide the means to fully evaluate IMP generation in muscles of various shapes and operating conditions. The work presented in this dissertation focuses on the development and validation of computational models of passive skeletal muscle and the evaluation of their performance for prediction of IMP. A transversly isotropic, hyperelastic, and nearly incompressible model will be evaluated along with a poroelastic model.
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BACKGROUND: Patients taking immunosuppressants after transplantation may require intestinal surgery. Mycophenolate mofetil (MMF) has been found to impair the healing of colonic anastomoses in rats. This study examined whether insulin-like growth factor (IGF) I prevents MMF impairment of anastomotic healing. METHODS: Sixty-three rats were divided into three groups (MMF, MMF/IGF and control). Animals underwent a sigmoid colon anastomosis with a 6/0 suture, and were killed on days 2, 4 and 6 after surgery. Investigations included bursting pressure measurement, morphometric analysis, and assessment of mucosal proliferation by 5-bromo-2'-deoxyuridine and Ki67 immunohistochemistry of the anastomoses. RESULTS: The leak rate was three of 21, one of 20 and two of 20 in the MMF, MMF/IGF-I and control groups respectively. Anastomotic bursting pressures were significantly lower in the MMF group than in the control group on days 2 and 4, but there was no significant difference by day 6. Values in the MMF/IGF-I and control groups were similar. Colonic crypt depth was significantly reduced in MMF-treated animals on days 2 and 4, but this impairment was attenuated by IGF-I on day 4. Similarly, IGF-I reduced the negative impact of MMF on mucosal proliferation on days 2 and 6. CONCLUSION: Exogenous IGF-I improves some aspects of MMF-impaired anastomotic healing.