913 resultados para tests statistiques


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Given the multiplicity of nanoparticles (NPs), there is a requirement to develop screening strategies to evaluate their toxicity. Within the EU-funded FP7 NanoTEST project, a panel of medically relevant NPs has been used to develop alternative testing strategies of NPs used in medical diagnostics. As conventional toxicity tests cannot necessarily be directly applied to NPs in the same manner as for soluble chemicals and drugs, we determined the extent of interference of NPs with each assay process and components. In this study, we fully characterized the panel of NP suspensions used in this project (poly(lactic-co-glycolic acid)-polyethylene oxide [PLGA-PEO], TiO2, SiO2, and uncoated and oleic-acid coated Fe3O4) and showed that many NP characteristics (composition, size, coatings, and agglomeration) interfere with a range of in vitro cytotoxicity assays (WST-1, MTT, lactate dehydrogenase, neutral red, propidium iodide, (3)H-thymidine incorporation, and cell counting), pro-inflammatory response evaluation (ELISA for GM-CSF, IL-6, and IL-8), and oxidative stress detection (monoBromoBimane, dichlorofluorescein, and NO assays). Interferences were assay specific as well as NP specific. We propose how to integrate and avoid interference with testing systems as a first step of a screening strategy for biomedical NPs.

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This study deals with the statistical properties of a randomization test applied to an ABAB design in cases where the desirable random assignment of the points of change in phase is not possible. In order to obtain information about each possible data division we carried out a conditional Monte Carlo simulation with 100,000 samples for each systematically chosen triplet. Robustness and power are studied under several experimental conditions: different autocorrelation levels and different effect sizes, as well as different phase lengths determined by the points of change. Type I error rates were distorted by the presence of autocorrelation for the majority of data divisions. Satisfactory Type II error rates were obtained only for large treatment effects. The relationship between the lengths of the four phases appeared to be an important factor for the robustness and the power of the randomization test.

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La spectroscopie infrarouge (FTIR) est une technique de choix dans l'analyse des peintures en spray (traces ou bonbonnes de référence), grâce à son fort pouvoir discriminant, sa sensibilité, et ses nombreuses possibilités d'échantillonnage. La comparaison des spectres obtenus est aujourd'hui principalement faite visuellement, mais cette procédure présente des limitations telles que la subjectivité de la prise de décision car celle-ci dépend de l'expérience et de la formation suivie par l'expert. De ce fait, de faibles différences d'intensités relatives entre deux pics peuvent être perçues différemment par des experts, même au sein d'un même laboratoire. Lorsqu'il s'agit de justifier ces différences, certains les expliqueront par la méthode analytique utilisée, alors que d'autres estimeront plutôt qu'il s'agit d'une variabilité intrinsèque à la peinture et/ou à son vécu (par exemple homogénéité, sprayage, ou dégradation). Ce travail propose d'étudier statistiquement les différentes sources de variabilité observables dans les spectres infrarouges, de les identifier, de les comprendre et tenter de les minimiser. Le deuxième objectif principal est de proposer une procédure de comparaison des spectres qui soit davantage transparente et permette d'obtenir des réponses reproductibles indépendamment des experts interrogés. La première partie du travail traite de l'optimisation de la mesure infrarouge et des principaux paramètres analytiques. Les conditions nécessaires afin d'obtenir des spectres reproductibles et minimisant la variation au sein d'un même échantillon (intra-variabilité) sont présentées. Par la suite une procédure de correction des spectres est proposée au moyen de prétraitements et de sélections de variables, afin de minimiser les erreurs systématiques et aléatoires restantes, et de maximiser l'information chimique pertinente. La seconde partie présente une étude de marché effectuée sur 74 bonbonnes de peintures en spray représentatives du marché suisse. Les capacités de discrimination de la méthode FTIR au niveau de la marque et du modèle sont évaluées au moyen d'une procédure visuelle, et comparées à diverses procédures statistiques. Les limites inférieures de discrimination sont testées sur des peintures de marques et modèles identiques mais provenant de différents lots de production. Les résultats ont montré que la composition en pigments était particulièrement discriminante, à cause des étapes de corrections et d'ajustement de la couleur subies lors de la production. Les particularités associées aux peintures en spray présentes sous forme de traces (graffitis, gouttelettes) ont également été testées. Trois éléments sont mis en évidence et leur influence sur le spectre infrarouge résultant testée : 1) le temps minimum de secouage nécessaire afin d'obtenir une homogénéité suffisante de la peinture et, en conséquence, de la surface peinte, 2) la dégradation initiée par le rayonnement ultra- violet en extérieur, et 3) la contamination provenant du support lors du prélèvement. Finalement une étude de population a été réalisée sur 35 graffitis de la région lausannoise et les résultats comparés à l'étude de marché des bonbonnes en spray. La dernière partie de ce travail s'est concentrée sur l'étape de prise de décision lors de la comparaison de spectres deux-à-deux, en essayant premièrement de comprendre la pratique actuelle au sein des laboratoires au moyen d'un questionnaire, puis de proposer une méthode statistique de comparaison permettant d'améliorer l'objectivité et la transparence lors de la prise de décision. Une méthode de comparaison basée sur la corrélation entre les spectres est proposée, et ensuite combinée à une évaluation Bayesienne de l'élément de preuve au niveau de la source et au niveau de l'activité. Finalement des exemples pratiques sont présentés et la méthodologie est discutée afin de définir le rôle précis de l'expert et des statistiques dans la procédure globale d'analyse des peintures. -- Infrared spectroscopy (FTIR) is a technique of choice for analyzing spray paint speciments (i.e. traces) and reference samples (i.e. cans seized from suspects) due to its high discriminating power, sensitivity and sampling possibilities. The comparison of the spectra is currently carried out visually, but this procedure has limitations such as the subjectivity in the decision due to its dependency on the experience and training of the expert. This implies that small differences in the relative intensity of two peaks can be perceived differently by experts, even between analysts working in the same laboratory. When it comes to justifying these differences, some will explain them by the analytical technique, while others will estimate that the observed differences are mostly due to an intrinsic variability from the paint sample and/or its acquired characteristics (for example homogeneity, spraying, or degradation). This work proposes to statistically study the different sources of variability observed in infrared spectra, to identify them, understand them and try to minimize them. The second goal is to propose a procedure for spectra comparison that is more transparent, and allows obtaining reproducible answers being independent from the expert. The first part of the manuscript focuses on the optimization of infrared measurement and on the main analytical parameters. The necessary conditions to obtain reproducible spectra with a minimized variation within a sample (intra-variability) are presented. Following that a procedure of spectral correction is then proposed using pretreatments and variable selection methods, in order to minimize systematic and random errors, and increase simultaneously relevant chemical information. The second part presents a market study of 74 spray paints representative of the Swiss market. The discrimination capabilities of FTIR at the brand and model level are evaluated by means of visual and statistical procedures. The inferior limits of discrimination are tested on paints coming from the same brand and model, but from different production batches. The results showed that the pigment composition was particularly discriminatory, because of the corrections and adjustments made to the paint color during its manufacturing process. The features associated with spray paint traces (graffitis, droplets) were also tested. Three elements were identified and their influence on the resulting infrared spectra were tested: 1) the minimum shaking time necessary to obtain a sufficient homogeneity of the paint and subsequently of the painted surface, 2) the degradation initiated by ultraviolet radiation in an exterior environment, and 3) the contamination from the support when paint is recovered. Finally a population study was performed on 35 graffitis coming from the city of Lausanne and surroundings areas, and the results were compared to the previous market study of spray cans. The last part concentrated on the decision process during the pairwise comparison of spectra. First, an understanding of the actual practice among laboratories was initiated by submitting a questionnaire. Then, a proposition for a statistical method of comparison was advanced to improve the objectivity and transparency during the decision process. A method of comparison based on the correlation between spectra is proposed, followed by the integration into a Bayesian framework at both source and activity levels. Finally, some case examples are presented and the recommended methodology is discussed in order to define the role of the expert as well as the contribution of the tested statistical approach within a global analytical sequence for paint examinations.

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Monte Carlo simulations were used to generate data for ABAB designs of different lengths. The points of change in phase are randomly determined before gathering behaviour measurements, which allows the use of a randomization test as an analytic technique. Data simulation and analysis can be based either on data-division-specific or on common distributions. Following one method or another affects the results obtained after the randomization test has been applied. Therefore, the goal of the study was to examine these effects in more detail. The discrepancies in these approaches are obvious when data with zero treatment effect are considered and such approaches have implications for statistical power studies. Data-division-specific distributions provide more detailed information about the performance of the statistical technique.