35 resultados para CHD Prediction, Blood Serum Data Chemometrics Methods


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The impact of invasive procedures on preterm neonates has received little systematic attention. We examined facial activity, body movements, and physiological measures in 56 preterm and full-term newborns in response to heel lancing, along with comparison preparatory and recovery intervals. The measures were recorded in special care and full-term nurseries during routine blood sampling. Data analyses indicated that in all measurement categories reactions of greatest magnitude were to the lancing procedure. Neonates with gestational ages as short as 25-27 weeks displayed physiological responsivity to the heel lance, but only in the heart rate measure did this vary with gestational age. Bodily activity was diminished in preterm neonates in general, relative to full-term newborns. Facial activity increased with the gestational age of the infant. Specificity of the response to the heel lance was greatest on the facial activity measure. Identification of pain requires attention to gestational age in the preterm neonate.

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Introduction: Variation across research ethics boards (REBs) in conditions placed on access to medical records for research purposes raises concerns around negative impacts on research quality and on human subject protection, including privacy. Aim: To study variation in REB consent requirements for retrospective chart review and who may have access to the medical record for data abstraction. Methods: Thirty 90-min face-to-face interviews were conducted with REB chairs and administrators affiliated with faculties of medicine in Canadian universities, using structured questions around a case study with open-ended responses. Interviews were recorded, transcribed and coded manually. Results: Fourteen sites (47%) required individual patient consent for the study to proceed as proposed. Three (10%) indicated that their response would depend on how potentially identifying variables would be managed. Eleven sites (38%) did not require consent. Two (7%) suggested a notification and opt-out process. Most stated that consent would be required if identifiable information was being abstracted from the record. Among those not requiring consent, there was substantial variation in recognising that the abstracted information could potentially indirectly re-identify individuals. Concern over access to medical records by an outside individual was also associated with requirement for consent. Eighteen sites (60%) required full committee review. Sixteen (53%) allowed an external research assistant to abstract information from the health record. Conclusions: Large variation was found across sites in the requirement for consent for research involving access to medical records. REBs need training in best practices for protecting privacy and confidentiality in health research. A forum for REB chairs to confidentially share concerns and decisions about specific studies could also reduce variation in decisions.

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Context. Comet 67P/Churyumov-Gerasimenko is the target of the European Space Agency Rosetta spacecraft rendez-vous mission. Detailed physical characteristation of the comet before arrival is important for mission planning as well as providing a test bed for ground-based observing and data-analysis methods. Aims: To conduct a long-term observational programme to characterize the physical properties of the nucleus of the comet, via ground-based optical photometry, and to combine our new data with all available nucleus data from the literature. Methods: We applied aperture photometry techniques on our imaging data and combined the extracted rotational lightcurves with data from the literature. Optical lightcurve inversion techniques were applied to constrain the spin state of the nucleus and its broad shape. We performed a detailed surface thermal analysis with the shape model and optical photometry by incorporating both into the new Advanced Thermophysical Model (ATPM), along with all available Spitzer 8-24 μm thermal-IR flux measurements from the literature. Results: A convex triangular-facet shape model was determined with axial ratios b/a = 1.239 and c/a = 0.819. These values can vary by as much as 7% in each axis and still result in a statistically significant fit to the observational data. Our best spin state solution has Psid = 12.76137 ± 0.00006 h, and a rotational pole orientated at Ecliptic coordinates λ = 78°(±10°), β = + 58°(±10°). The nucleus phase darkening behaviour was measured and best characterized using the IAU HG system. Best fit parameters are: G = 0.11 ± 0.12 and HR(1,1,0) = 15.31 ± 0.07. Our shape model combined with the ATPM can satisfactorily reconcile all optical and thermal-IR data, with the fit to the Spitzer 24 μm data taken in February 2004 being exceptionally good. We derive a range of mutually-consistent physical parameters for each thermal-IR data set, including effective radius, geometric albedo, surface thermal inertia and roughness fraction. Conclusions: The overall nucleus dimensions are well constrained and strongly imply a broad nucleus shape more akin to comet 9P/Tempel 1, rather than the highly elongated or "bi-lobed" nuclei seen for comets 103P/Hartley 2 or 8P/Tuttle. The derived low thermal inertia of

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We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of 'quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

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The mechanisms and kinetics studies of the formation of levoglucosan and formaldehyde from anhydroglucose radical have been carried out theoretically in this paper. The geometries and frequencies of all the stationary points are calculated at the B3LYP/6-31+G(D,P) level based on quantum mechanics, Six elementary reactions are found, and three global reactions are involved. The variational transition-state rate constants for the elementary reactions are calculated within 450-1500 K. The global rate constants for every pathway are evaluated from the sum of the individual elementary reaction rate constants. The first-order Arrhenius expressions for these six elementary reactions and the three pathways are suggested. By comparing with the experimental data, computational methods without tunneling correction give good description for Path1 (the formation of levoglucosan); while methods with tunneling correction (zero-curvature tunneling and small-curvature tunneling correction) give good results for Path2 (the first possibility for the formation of formaldehyde), all the test methods give similar results for Path3 (the second possibility for the formation of formaldehyde), all the modeling results for Path3 are in good agreement with the experimental data, verifying that it is the most possible way for the formation of formaldehyde during cellulose pyrolysis. © 2012 Elsevier Ltd. All rights reserved.

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Complex collaboration in rapidly changing business environments create challenges for management capability in Utility Horizontal Supply Chains (UHSCs) involving the deploying and evolving of performance measures. The aim of the study is twofold. First, there is a need to explore how management capability can be developed and used to deploy and evolve Performance Measurement (PM), both across a UHSC and within its constituent organisations, drawing upon a theoretical nexus of Dynamic Capability (DC) theory and complementary Goal Theory. Second, to make a contribution to knowledge by empirically building theory using these constructs to show the management motivations and behaviours within PM-based DCs. The methodology uses an interpretive theory building, multiple case based approach (n=3) as part of a USHC. The data collection methods include, interviews (n=54), focus groups (n=10), document analysis and participant observation (reflective learning logs) over a five-year period giving longitudinal data. The empirical findings lead to the development of a conceptual framework showing that management capabilities in driving PM deployment and evolution can be represented as multilevel renewal and incremental Dynamic Capabilities, which can be further understood in terms of motivation and behaviour by Goal-Theoretic constructs. In addition three interrelated cross cutting themes of management capabilities in consensus building, goal setting and resource change were identified. These management capabilities require carefully planned development and nurturing within the UHSC. 

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Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

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Standard identification systems usually ensure that biopsy material is correctly associated with a given patient. Sometimes, as when a tumor is unexpectedly found, the provenance (proof of origin) of a tissue sample may be questioned; the tissue may have been mislabelled or contaminated with tissue from another patient. Techniques used to confirm tissue provenance include comparing either tissue markers of gender or ABO blood groups; however, these methods have weak confirmatory power. Recently, the use of DNA-based polymerase chain reaction (PCR) techniques has been reported. Paired, formalin-fixed, paraffin-embedded, 10 microns tissue sections were selected from 17 patients, 8 of whom had carcinoma, either by dividing a biopsy section, using sequential biopsies, or sequential biopsy and autopsy tissue. The resulting 36 samples were coded before analysis. In two additional cases, 1-mm fragments of tumor from one patient were included in the tissue block of benign tissue from another patient, the tumor fragments were identified on hematoxylin-and-eosin-stained sections, separately scraped off the glass slide, and analyzed. Tissue from two clinical cases, one of suspected mislabelling and one with a suspected carry-over of malignant tissue were also investigated. Short tandem repeat sequences (STR) or microsatellites, are 2-5 base pair repeats that vary in their repeat number between individuals. This variation (polymorphism) can be assessed using a PCR. A panel of markers of 3 STRs; ACPP, INT 2, and CYP 19 (on chromosomes 3, 11, and 15, respectively) were used. DNA was isolated from the samples after xylene deparaffinization and proteinase digestion, and was then amplified in a radioactive PCR using primers selected to give a product size ranging from 136-178 bases. Amplified products were electrophoresed on denaturing polyacrylamide gels, dried, and autoradiographed. DNA segments were successfully extracted from all samples but one, which was fixed in Bouin's fluid. By comparing allele sizes from the panel, all tissue pairs (other than the Bouin's pair) were successfully matched, the 1-mm tumor fragments were correctly assigned, and the two clinical problems were solved. STRs are highly informative and robust markers, well suited to PCR of small portions of tissue sections, and are an effective method to confirm the provenance of benign and malignant biopsy and autopsy material.

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Glibenclamide (GLIB), an oral antidiabetic medication of the sulphonylurea drugs family, was stoichiometrically imprinted using tetrabutylammonium methacrylate as the functional monomer, for the first time in molecular imprinting, and utilising the sulphonylurea affinity for carboxylate anions. Solution association between the drug and the novel functional monomer was studied by 1H-NMR titrations, whereby evidence of sulphonylurea deprotonation followed by the formation of “narcissistic” GLIB dimers was found when tested in CDCl3, while an affinity constant in excess of 105 L mol-1 was measured in DMSO-d6. Detailed analysis of GLIB binding on the subsequently prepared imprinted and non-imprinted polymers confirmed deactivation of binding sites by exchange of a proton between GLIB and methacrylate, followed by extraction of the tetrabutylammonium counterion from the polymer matrix, resulting in overall reduced binding capacities and affinities by the imprinted material under equilibrium conditions. An optimised MI-SPE protocol, which included a binding site re-activation step, was developed for the extraction of GLIB from blood serum, whereby recoveries of up to 92.4% were obtained with exceptional sample clean-up.

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One of the challenges the tidal power industry faces, is the requirement of cost effective, reliable but highly accurate acquisition of flow data. Different methods are required , applications range over different spatial and temporal scales. This report assembles in the first sections, theoretical background information on acoustic Doppler Velocimetry and RADAR measurements. The use of existing expertise in field tests of marine vehicles is discussed next, followed by a discussion of issues relating to recreating field conditions in laboratory environments. The last three sections present practical applications of various methods performed in field conditions. While progress has been made over the last years, this overview highlights the challenges in full scale field measurements and knowledge gaps in the industry.

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Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.

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Photometry of moving sources typically suffers from a reduced signal-to-noise ratio (S/N) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue, we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSFs) and trailed PSFs (TSFs) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super-sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with an accuracy of 10 mmag for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve S/Ns of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all S/Ns.

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Background Serum eosinophilic cationic protein (ECP) concentrations may be useful noninvasive markers of airways inflammation in atopic asthma. However, the usefulness of serum ECP measurement for the prediction of airways inflammation in children with a history of wheezing is unknown.

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In contrast to the multitude of studies on fungal PCR assay methods, little work has been reported evaluating Candida PCR performance when using whole blood compared with serum in candidaemic patients. Here, a comparison of the performance of whole-blood and serum specimens using a set of real-time PCR Candida species assays is described. Specimens were collected prospectively from non-neutropenic adults who were recruited to a diagnostic clinical trial, the primary purpose of which was to verify the performance of the assays using serum; in all, 104 participants also had whole-blood specimens submitted for analysis in addition to the serum specimen. Of these participants, 10 had laboratory-confirmed candidaemia and 94 were categorized as being 'unlikely' to have invasive Candida infection. PCR results from the whole-blood specimens are presented here and compared with the results from serum specimens in this subgroup among whom both specimen types were obtained contemporaneously. All participants with candidaemia were PCR-positive from serum samples; however, only seven were PCR-positive from whole blood. All specimens from patients in the 'unlikely' category were PCR-negative in both types of specimen. Moreover, DNA extraction from serum required 1 h; extraction from whole blood required approximately 3 h. These data tentatively suggest that, overall, serum is an appropriate specimen for Candida PCR for detection of candidaemia in non-neutropenic adults.

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Purpose: To evaluate adherence to prescribed antiepileptic drugs (AEDs) in children with epilepsy using a combination of adherence-assessment methods.
Methods: A total of 100 children with epilepsy (=17 years old) were recruited. Medication adherence was determined via parental and child self-reporting (=9 years old), medication refill data from general practitioner (GP) prescribing records, and via AED concentrations in dried blood spot (DBS) samples obtained from children at the clinic and via self- or parental-led sampling in children's own homes. The latter were assessed using population pharmacokinetic modeling. Patients were deemed nonadherent if any of these measures were indicative of nonadherence with the prescribed treatment. In addition, beliefs about medicines, parental confidence in seizure management, and the presence of depressed mood in parents were evaluated to examine their association with nonadherence in the participating children.
Key Findings: The overall rate of nonadherence in children with epilepsy was 33%. Logistic regression analysis indicated that children with generalized epilepsy (vs. focal epilepsy) were more likely (odds ratio [OR] 4.7, 95% confidence interval [CI] 1.37-15.81) to be classified as nonadherent as were children whose parents have depressed mood (OR 3.6, 95% CI 1.16-11.41).
Significance: This is the first study to apply the novel methodology of determining adherence via AED concentrations in clinic and home DBS samples. The present findings show that the latter, with further development, could be a useful approach to adherence assessment when combined with other measures including parent and child self-reporting. Seizure type and parental depressed mood were strongly predictive of nonadherence. © 2013 International League Against Epilepsy.
Key Words: Adherence, Epilepsy, Dried blood spots, MARS, Depressed mood.