938 resultados para Basophil Degranulation Test -- methods


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1. Pearson's correlation coefficient only tests whether the data fit a linear model. With large numbers of observations, quite small values of r become significant and the X variable may only account for a minute proportion of the variance in Y. Hence, the value of r squared should always be calculated and included in a discussion of the significance of r. 2. The use of r assumes that a bivariate normal distribution is present and this assumption should be examined prior to the study. If Pearson's r is not appropriate, then a non-parametric correlation coefficient such as Spearman's rs may be used. 3. A significant correlation should not be interpreted as indicating causation especially in observational studies in which there is a high probability that the two variables are correlated because of their mutual correlations with other variables. 4. In studies of measurement error, there are problems in using r as a test of reliability and the ‘intra-class correlation coefficient’ should be used as an alternative. A correlation test provides only limited information as to the relationship between two variables. Fitting a regression line to the data using the method known as ‘least square’ provides much more information and the methods of regression and their application in optometry will be discussed in the next article.

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1. Fitting a linear regression to data provides much more information about the relationship between two variables than a simple correlation test. A goodness of fit test of the line should always be carried out. Hence, r squared estimates the strength of the relationship between Y and X, ANOVA whether a statistically significant line is present, and the ‘t’ test whether the slope of the line is significantly different from zero. 2. Always check whether the data collected fit the assumptions for regression analysis and, if not, whether a transformation of the Y and/or X variables is necessary. 3. If the regression line is to be used for prediction, it is important to determine whether the prediction involves an individual y value or a mean. Care should be taken if predictions are made close to the extremities of the data and are subject to considerable error if x falls beyond the range of the data. Multiple predictions require correction of the P values. 3. If several individual regression lines have been calculated from a number of similar sets of data, consider whether they should be combined to form a single regression line. 4. If the data exhibit a degree of curvature, then fitting a higher-order polynomial curve may provide a better fit than a straight line. In this case, a test of whether the data depart significantly from a linear regression should be carried out.

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1. The techniques associated with regression, whether linear or non-linear, are some of the most useful statistical procedures that can be applied in clinical studies in optometry. 2. In some cases, there may be no scientific model of the relationship between X and Y that can be specified in advance and the objective may be to provide a ‘curve of best fit’ for predictive purposes. In such cases, the fitting of a general polynomial type curve may be the best approach. 3. An investigator may have a specific model in mind that relates Y to X and the data may provide a test of this hypothesis. Some of these curves can be reduced to a linear regression by transformation, e.g., the exponential and negative exponential decay curves. 4. In some circumstances, e.g., the asymptotic curve or logistic growth law, a more complex process of curve fitting involving non-linear estimation will be required.

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The timeline imposed by recent worldwide chemical legislation is not amenable to conventional in vivo toxicity testing, requiring the development of rapid, economical in vitro screening strategies which have acceptable predictive capacities. When acquiring regulatory neurotoxicity data, distinction on whether a toxic agent affects neurons and/or astrocytes is essential. This study evaluated neurofilament (NF) and glial fibrillary acidic protein (GFAP) directed single-cell (S-C) ELISA and flow cytometry as methods for distinguishing cell-specific cytoskeletal responses, using the established human NT2 neuronal/astrocytic (NT2.N/A) co-culture model and a range of neurotoxic (acrylamide, atropine, caffeine, chloroquine, nicotine) and non-neurotoxic (chloramphenicol, rifampicin, verapamil) test chemicals. NF and GFAP directed flow cytometry was able to identify several of the test chemicals as being specifically neurotoxic (chloroquine, nicotine) or astrocytoxic (atropine, chloramphenicol) via quantification of cell death in the NT2.N/A model at cytotoxic concentrations using the resazurin cytotoxicity assay. Those neurotoxicants with low associated cytotoxicity are the most significant in terms of potential hazard to the human nervous system. The NF and GFAP directed S-C ELISA data predominantly demonstrated the known neurotoxicants only to affect the neuronal and/or astrocytic cytoskeleton in the NT2.N/A cell model at concentrations below those affecting cell viability. This report concluded that NF and GFAP directed S-C ELISA and flow cytometric methods may prove to be valuable additions to an in vitro screening strategy for differentiating cytotoxicity from specific neuronal and/or astrocytic toxicity. Further work using the NT2.N/A model and a broader array of toxicants is appropriate in order to confirm the applicability of these methods.

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A combination of experimental methods was applied at a clogged, horizontal subsurface flow (HSSF) municipal wastewater tertiary treatment wetland (TW) in the UK, to quantify the extent of surface and subsurface clogging which had resulted in undesirable surface flow. The three dimensional hydraulic conductivity profile was determined, using a purpose made device which recreates the constant head permeameter test in-situ. The hydrodynamic pathways were investigated by performing dye tracing tests with Rhodamine WT and a novel multi-channel, data-logging, flow through Fluorimeter which allows synchronous measurements to be taken from a matrix of sampling points. Hydraulic conductivity varied in all planes, with the lowest measurement of 0.1 md1 corresponding to the surface layer at the inlet, and the maximum measurement of 1550 md1 located at a 0.4m depth at the outlet. According to dye tracing results, the region where the overland flow ceased received five times the average flow, which then vertically short-circuited below the rhizosphere. The tracer break-through curve obtained from the outlet showed that this preferential flow-path accounted for approximately 80% of the flow overall and arrived 8 h before a distinctly separate secondary flow-path. The overall volumetric efficiencyof the clogged system was 71% and the hydrology was simulated using a dual-path, dead-zone storage model. It is concluded that uneven inlet distribution, continuous surface loading and high rhizosphere resistance is responsible for the clog formation observed in this system. The average inlet hydraulic conductivity was 2 md1, suggesting that current European design guidelines, which predict that the system will reach an equilibrium hydraulic conductivity of 86 md1, do not adequately describe the hydrology of mature systems.

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Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems.

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Objectives - Powdered and granulated particulate materials make up most of the ingredients of pharmaceuticals and are often at risk of undergoing unwanted agglomeration, or caking, during transport or storage. This is particularly acute when bulk powders are exposed to extreme swings in temperature and relative humidity, which is now common as drugs are produced and administered in increasingly hostile climates and are stored for longer periods of time prior to use. This study explores the possibility of using a uniaxial unconfined compression test to compare the strength of caked agglomerates exposed to different temperatures and relative humidities. This is part of a longer-term study to construct a protocol to predict the caking tendency of a new bulk material from individual particle properties. The main challenge is to develop techniques that provide repeatable results yet are presented simply enough to be useful to a wide range of industries. Methods - Powdered sucrose, a major pharmaceutical ingredient, was poured into a split die and exposed to high and low relative humidity cycles at room temperature. The typical ranges were 20–30% for the lower value and 70–80% for the higher value. The outer die casing was then removed and the resultant agglomerate was subjected to an unconfined compression test using a plunger fitted to a Zwick compression tester. The force against displacement was logged so that the dynamics of failure as well as the failure load of the sample could be recorded. The experimental matrix included varying the number of cycles, the amount between the maximum and minimum relative humidity, the height and diameters of the samples, the number of cycles and the particle size. Results - Trends showed that the tensile strength of the agglomerates increased with the number of cycles and also with the more extreme swings in relative humidity. This agrees with previous work on alternative methods of measuring the tensile strength of sugar agglomerates formed from humidity cycling (Leaper et al 2003). Conclusions - The results show that at the very least the uniaxial tester is a good comparative tester to examine the caking tendency of powdered materials, with a simple arrangement and operation that are compatible with the requirements of industry. However, further work is required to continue to optimize the height/ diameter ratio during tests.

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In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

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A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants. © 2012 Springer Science+Business Media, LLC.

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Background - The PELICAN Multidisciplinary Team Total Mesorectal Excision (MDT-TME) Development Programme aimed to improve clinical outcomes for rectal cancer by educating colorectal cancer teams in precision surgery and related aspects of multidisciplinary care. The Programme reached almost all colorectal cancer teams across England. We took the opportunity to assess the impact of participating in this novel team-based Development Programme on the working lives of colorectal cancer team members. Methods - The impact of participating in the programme on team members' self-reported job stress, job satisfaction and team performance was assessed in a pre-post course study. 333/568 (59%) team members, from the 75 multidisciplinary teams who attended the final year of the Programme, completed questionnaires pre-course, and 6-8 weeks post-course. Results - Across all team members, the main sources of job satisfaction related to working in multidisciplinary teams; whilst feeling overloaded was the main source of job stress. Surgeons and clinical nurse specialists reported higher levels of job satisfaction than team members who do not provide direct patient care, whilst MDT coordinators reported the lowest levels of job satisfaction and job stress. Both job stress and satisfaction decreased after participating in the Programme for all team members. There was a small improvement in team performance. Conclusions - Participation in the Development Programme had a mixed impact on the working lives of team members in the immediate aftermath of attending. The decrease in team members' job stress may reflect the improved knowledge and skills conferred by the Programme. The decrease in job satisfaction may be the consequence of being unable to apply these skills immediately in clinical practice because of a lack of required infrastructure and/or equipment. In addition, whilst the Programme raised awareness of the challenges of teamworking, a greater focus on tackling these issues may have improved working lives further.

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Aim: Contrast sensitivity (CS) provides important information on visual function. This study aimed to assess differences in clinical expediency of the CS increment-matched new back-lit and original paper versions of the Melbourne Edge Test (MET) to determine the CS of the visually impaired. Methods: The back-lit and paper MET were administered to 75 visually impaired subjects (28-97 years). Two versions of the back-lit MET acetates were used to match the CS increments with the paper-based MET. Measures of CS were repeated after 30 min and again in the presence of a focal light source directed onto the MET. Visual acuity was measured with a Bailey-Lovie chart and subjects rated how much difficulty they had with face and vehicle recognition. Results: The back-lit MET gave a significantly higher CS than the paper-based version (14.2 ± 4.1 dB vs 11.3 ± 4.3 dB, p < 0.001). A significantly higher reading resulted with repetition of the paper-based MET (by 1.0 ± 1.7 dB, p < 0.001), but this was not evident with the back-lit MET (by 0.1 ± 1.4 dB, p = 0.53). The MET readings were increased by a focal light source, in both the back-lit (by 0.3 ± 0.81, p < 0.01) and paper-based (1.2 ± 1.7, p < 0.001) versions. CS as measured by the back-lit and paper-based versions of the MET was significantly correlated to patients' perceived ability to recognise faces (r = 0.71, r = 0.85 respectively; p < 0.001) and vehicles (r = 0.67, r = 0.82 respectively; p < 0.001), and with distance visual acuity (both r =-0.64; p < 0.001). Conclusions: The CS increment-matched back-lit MET gives higher CS values than the old paper-based test by approximately 3 dB and is more repeatable and less affected by external light sources. Clinically, the MET score provides information on patient difficulties with visual tasks, such as recognising faces. © 2005 The College of Optometrists.

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Usually, data mining projects that are based on decision trees for classifying test cases will use the probabilities provided by these decision trees for ranking classified test cases. We have a need for a better method for ranking test cases that have already been classified by a binary decision tree because these probabilities are not always accurate and reliable enough. A reason for this is that the probability estimates computed by existing decision tree algorithms are always the same for all the different cases in a particular leaf of the decision tree. This is only one reason why the probability estimates given by decision tree algorithms can not be used as an accurate means of deciding if a test case has been correctly classified. Isabelle Alvarez has proposed a new method that could be used to rank the test cases that were classified by a binary decision tree [Alvarez, 2004]. In this paper we will give the results of a comparison of different ranking methods that are based on the probability estimate, the sensitivity of a particular case or both.

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Aim: To evaluate OneTouch® Verio™ test strip performance at hypoglycaemic blood glucose (BG) levels (<3.9mmol/L [<70mg/dL]) at seven clinical studies. Methods: Trained clinical staff performed duplicate capillary BG monitoring system tests on 700 individuals with type 1 and type 2 diabetes using blood from a single fingerstick lancing. BG reference values were obtained using a YSI 2300 STAT™ Glucose Analyzer. The number and percentage of BG values within ±0.83. mmol/L (±15. mg/dL) and ±0.56. mmol/L (±10. mg/dL) were calculated at BG concentrations of <3.9. mmol/L (<70. mg/dL), <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL). Results: At BG concentrations <3.9. mmol/L (<70. mg/dL), 674/674 (100%) of meter results were within ±0.83. mmol/L (±15. mg/dL) and 666/674 (98.8%) were within ±0.56. mmol/L (±10. mg/dL) of reference values. At BG concentrations <3.3. mmol/L (<60. mg/dL), and <2.8. mmol/L (<50. mg/dL), 358/358 (100%) and 270/270 (100%) were within ±0.56. mmol/L (±10. mg/dL) of reference values, respectively. Conclusion: In this analysis of data from seven independent studies, OneTouch Verio test strips provide highly accurate results at hypoglycaemic BG levels. © 2012 Elsevier Ireland Ltd.

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The paper treats the task for cluster analysis of a given assembly of objects on the basis of the information contained in the description table of these objects. Various methods of cluster analysis are briefly considered. Heuristic method and rules for classification of the given assembly of objects are presented for the cases when their division into classes and the number of classes is not known. The algorithm is checked by a test example and two program products (PP) – learning systems and software for company management. Analysis of the results is presented.

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The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.