821 resultados para node classification


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OBJECTIVE: Prospective analysis of the morbidity and outcome of the sentinel lymph node (SLN) technique in a consecutive series of patients with early-stage melanoma. METHODS: Between 1997 and 1998, 60 patients with stage IB-II malignant melanoma underwent SLN dissection. Preoperative dynamic lymphoscintigraphy with mapping of the lymph vessels and lymph nodes and location of the sentinel node was performed the day before SLN dissection. SLN was identified by use of the blue dye technique. SLN was assessed for histopathological and immunohistochemical examination. Postoperative morbidity and mortality were recorded. Follow-up consisted of repetitive clinical examination with lymph nodes status, laboratory and radiologic findings. RESULTS: Tumor-positive SLN was observed in 18% of the patients and stage II disease was found in 91% of the patients with positive SLN. Breslow thickness was the only significant factor predicting involvement of a SLN (p = 0.02). In 36% of the positive SLN, metastases could be assessed only by immunohistochemical examination. Postoperative complications after SLN dissection were observed in 5% in comparison with 36% after elective lymph node dissection. After a mean follow-up of 32 months, recurrence was observed in 3% with a mean disease-free survival of 8 months. Overall survival was 82% and 90% in patients with positive and negative SLN, respectively. Overall mortality was 15%, due to distant metastases in 78% of the cases. CONCLUSIONS: Staging of early-stage melanoma with the SLN dissection by use of the blue dye technique combined to lymphoscintigraphy and immunohistochemistry is reliable and safe, with less morbidity than elective lymphadenectomy. Long-term follow-up is mandatory to establish the exact reliability of SLN dissection.

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Charcot-Marie-Tooth disease type 4C (CMT4C) is an early-onset, autosomal recessive form of demyelinating neuropathy. The clinical manifestations include progressive scoliosis, delayed age of walking, muscular atrophy, distal weakness, and reduced nerve conduction velocity. The gene mutated in CMT4C disease, SH3TC2/KIAA1985, was recently identified; however, the function of the protein it encodes remains unknown. We have generated knockout mice where the first exon of the Sh3tc2 gene is replaced with an enhanced GFP cassette. The Sh3tc2(DeltaEx1/DeltaEx1) knockout animals develop progressive peripheral neuropathy manifested by decreased motor and sensory nerve conduction velocity and hypomyelination. We show that Sh3tc2 is specifically expressed in Schwann cells and localizes to the plasma membrane and to the perinuclear endocytic recycling compartment, concordant with its possible function in myelination and/or in regions of axoglial interactions. Concomitantly, transcriptional profiling performed on the endoneurial compartment of peripheral nerves isolated from control and Sh3tc2(DeltaEx1/DeltaEx1) animals uncovered changes in transcripts encoding genes involved in myelination and cell adhesion. Finally, detailed analyses of the structures composed of compact and noncompact myelin in the peripheral nerve of Sh3tc2(DeltaEx1/DeltaEx1) animals revealed abnormal organization of the node of Ranvier, a phenotype that we confirmed in CMT4C patient nerve biopsies. The generated Sh3tc2 knockout mice thus present a reliable model of CMT4C neuropathy that was instrumental in establishing a role for Sh3tc2 in myelination and in the integrity of the node of Ranvier, a morphological phenotype that can be used as an additional CMT4C diagnostic marker.

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The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

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This document Classifications and Pay Plans is produced by the State of Iowa Executive Branch, Department of Administrative Services. Informational document about the pay plan codes and classification codes, how to use them.

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An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.

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EMBnet is a consortium of collaborating bioinformatics groups located mainly within Europe (http://www.embnet.org). Each member country is represented by a 'node', a group responsible for the maintenance of local services for their users (e.g. education, training, software, database distribution, technical support, helpdesk). Among these services a web portal with links and access to locally developed and maintained software is essential and different for each node. Our web portal targets biomedical scientists in Switzerland and elsewhere, offering them access to a collection of important sequence analysis tools mirrored from other sites or developed locally. We describe here the Swiss EMBnet node web site (http://www.ch.embnet.org), which presents a number of original services not available anywhere else.

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In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.

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Axée dans un premier temps sur le formalisme et les méthodes, cette thèse est construite sur trois concepts formalisés: une table de contingence, une matrice de dissimilarités euclidiennes et une matrice d'échange. À partir de ces derniers, plusieurs méthodes d'Analyse des données ou d'apprentissage automatique sont exprimées et développées: l'analyse factorielle des correspondances (AFC), vue comme un cas particulier du multidimensional scaling; la classification supervisée, ou non, combinée aux transformations de Schoenberg; et les indices d'autocorrélation et d'autocorrélation croisée, adaptés à des analyses multivariées et permettant de considérer diverses familles de voisinages. Ces méthodes débouchent dans un second temps sur une pratique de l'analyse exploratoire de différentes données textuelles et musicales. Pour les données textuelles, on s'intéresse à la classification automatique en types de discours de propositions énoncées, en se basant sur les catégories morphosyntaxiques (CMS) qu'elles contiennent. Bien que le lien statistique entre les CMS et les types de discours soit confirmé, les résultats de la classification obtenus avec la méthode K- means, combinée à une transformation de Schoenberg, ainsi qu'avec une variante floue de l'algorithme K-means, sont plus difficiles à interpréter. On traite aussi de la classification supervisée multi-étiquette en actes de dialogue de tours de parole, en se basant à nouveau sur les CMS qu'ils contiennent, mais aussi sur les lemmes et le sens des verbes. Les résultats obtenus par l'intermédiaire de l'analyse discriminante combinée à une transformation de Schoenberg sont prometteurs. Finalement, on examine l'autocorrélation textuelle, sous l'angle des similarités entre diverses positions d'un texte, pensé comme une séquence d'unités. En particulier, le phénomène d'alternance de la longueur des mots dans un texte est observé pour des voisinages d'empan variable. On étudie aussi les similarités en fonction de l'apparition, ou non, de certaines parties du discours, ainsi que les similarités sémantiques des diverses positions d'un texte. Concernant les données musicales, on propose une représentation d'une partition musicale sous forme d'une table de contingence. On commence par utiliser l'AFC et l'indice d'autocorrélation pour découvrir les structures existant dans chaque partition. Ensuite, on opère le même type d'approche sur les différentes voix d'une partition, grâce à l'analyse des correspondances multiples, dans une variante floue, et à l'indice d'autocorrélation croisée. Qu'il s'agisse de la partition complète ou des différentes voix qu'elle contient, des structures répétées sont effectivement détectées, à condition qu'elles ne soient pas transposées. Finalement, on propose de classer automatiquement vingt partitions de quatre compositeurs différents, chacune représentée par une table de contingence, par l'intermédiaire d'un indice mesurant la similarité de deux configurations. Les résultats ainsi obtenus permettent de regrouper avec succès la plupart des oeuvres selon leur compositeur.

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In forensic pathology routine, fatal cases of contrast agent exposure can be occasionally encountered. In such situations, beyond the difficulties inherent in establishing the cause of death due to nonspecific or absent autopsy and histology findings as well as limited laboratory investigations, pathologists may face other problems in formulating exhaustive, complete reports, and conclusions that are scientifically accurate. Indeed, terminology concerning adverse drug reactions and allergy nomenclature is confusing. Some terms, still utilized in forensic and radiological reports, are outdated and should be avoided. Additionally, not all forensic pathologists master contrast material classification and pathogenesis of contrast agent reactions. We present a review of the literature covering allergic reactions to contrast material exposure in order to update used terminology, explain the pathophysiology, and list currently available laboratory investigations for diagnosis in the forensic setting.

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Tire traces can be observed on several crime scenes as vehicles are often used by criminals. The tread abrasion on the road, while braking or skidding, leads to the production of small rubber particles which can be collected for comparison purposes. This research focused on the statistical comparison of Py-GC/MS profiles of tire traces and tire treads. The optimisation of the analytical method was carried out using experimental designs. The aim was to determine the best pyrolysis parameters regarding the repeatability of the results. Thus, the pyrolysis factor effect could also be calculated. The pyrolysis temperature was found to be five time more important than time. Finally, a pyrolysis at 650 °C during 15 s was selected. Ten tires of different manufacturers and models were used for this study. Several samples were collected on each tire, and several replicates were carried out to study the variability within each tire (intravariability). More than eighty compounds were integrated for each analysis and the variability study showed that more than 75% presented a relative standard deviation (RSD) below 5% for the ten tires, thus supporting a low intravariability. The variability between the ten tires (intervariability) presented higher values and the ten most variant compounds had a RSD value above 13%, supporting their high potential of discrimination between the tires tested. Principal Component Analysis (PCA) was able to fully discriminate the ten tires with the help of the first three principal components. The ten tires were finally used to perform braking tests on a racetrack with a vehicle equipped with an anti-lock braking system. The resulting tire traces were adequately collected using sheets of white gelatine. As for tires, the intravariability for the traces was found to be lower than the intervariability. Clustering methods were carried out and the Ward's method based on the squared Euclidean distance was able to correctly group all of the tire traces replicates in the same cluster than the replicates of their corresponding tire. Blind tests on traces were performed and were correctly assigned to their tire source. These results support the hypothesis that the tested tires, of different manufacturers and models, can be discriminated by a statistical comparison of their chemical profiles. The traces were found to be not differentiable from their source but differentiable from all the other tires present in the subset. The results are promising and will be extended on a larger sample set.