CD34/QBEND10 immunostaining in bone marrow biopsies: an additional parameter for the diagnosis and classification of myelodysplastic syndromes.

CD34/QBEND10 immunostaining has been assessed in 150 bone marrow biopsies (BMB) including 91 myelodysplastic syndromes (MDS), 16 MDS-related AML, 25 reactive BMB, and 18 cases where RA could neither be established nor ruled out. All cases were reviewed and classified according to the clinical and morphological FAB criteria. The percentage of CD34-positive (CD34 +) hematopoietic cells and the number of clusters of CD34+ cells in 10 HPF were determined. In most cases the CD34+ cell count was similar to the blast percentage determined morphologically. In RA, however, not only typical blasts but also less immature hemopoietic cells lying morphologically between blasts and promyelocytes were stained with CD34. The CD34+ cell count and cluster values were significantly higher in RA than in BMB with reactive changes (p<0.0001 for both), in RAEB than in RA (p=0.0006 and p=0.0189, respectively), in RAEBt than in RAEB (p=0.0001 and p=0.0038), and in MDS-AML than in RAEBt (p<0.0001 and p=0.0007). Presence of CD34+ cell clusters in RA correlated with increased risk of progression of the disease. We conclude that CD34 immunostaining in BMB is a useful tool for distinguishing RA from other anemias, assessing blast percentage in MDS cases, classifying them according to FAB, and following their evolution.

A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature.

BACKGROUND: Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age and Karnofsky Performance Status (KPS), while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK) GBM classification that can easily and non-invasively be determined upon patient admission. METHODS: We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA) corresponding to patients in The Cancer Genome Atlas (TCGA) with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N = 64) from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis. RESULTS: VAK-A and VAK-B classes showed significant median survival differences in discovery (P = 0.007) and validation sets (P = 0.008). VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P = 0.001). A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients. CONCLUSIONS: The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward the refinement of genomics-based personalized therapy for GBM patients.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Genesis and classification of Oxisols in a highland toposequence of the upper Jequitinhonha Valley (MG)

The Brazilian System of Soil Classification (SiBCS) is a taxonomic system, open and in permanent construction, as new knowledge on Brazilian soils is obtained. The objective of this study was to characterize the chemical, physical, morphological, micro-morphological and mineralogical properties of four pedons of Oxisols in a highland toposequence in the upper Jequitinhonha Valley, emphasizing aspects of their genesis, classification and landscape development. The pedons occupy the following slope positions: summit - Red Oxisol (LV), mid slope (upper third) - Yellow-Red Oxisol (LVA), lower slope (middle third)- Yellow Oxisol (LA) and bottom of the valley (lowest third) - "Gray Oxisol" ("LAC"). These pedons were described and sampled for characterization in chemical and physical routine analyses. The total Fe, Al and Mn contents were determined by sulfuric attack and the Fe, Al and Mn oxides in dithionite-citrate-bicarbonate and oxalate extraction. The mineralogy of silicate clays was identified by X ray diffraction and the Fe oxides were detected by differential X ray diffraction. Total Ti, Ga and Zr contents were determined by X ray fluorescence spectrometry. The "LAC" is gray-colored and contains significant fragments of structure units in the form of a dense paste, characteristic of a gleysoil, in the horizons A and BA. All pedons are very clayey, dystrophic and have low contents of available P and a pH of around 5. The soil color was related to the Fe oxide content, which decreased along the slope. The decrease of crystalline and low- crystalline Fe along the slope confirmed the loss of Fe from the "LAC". Total Si increased along the slope and total Al remained constant. The clay fraction in all pedons was dominated by kaolinite and gibbsite. Hematite and goethite were identified in LV, low-intensity hematite and goethite in LVA, goethite in LA. In the "LAC", no hematite peaks and goethite were detected by differential X ray diffraction. The micro-morphology indicated prevalence of granular microstructure and porosity with complex stacking patterns.. The soil properties in the toposequence converged to a single soil class, the Oxisols, derived from the same source material. The landscape evolution and genesis of Oxisols of the highlands in the upper Jequitinhonha Valley are related to the evolution of the drainage system and the activity of excavating fauna.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Soil spectral library and its use in soil classification

Soil science has sought to develop better techniques for the classification of soils, one of which is the use of remote sensing applications. The use of ground sensors to obtain soil spectral data has enabled the characterization of these data and the advancement of techniques for the quantification of soil attributes. In order to do this, the creation of a soil spectral library is necessary. A spectral library should be representative of the variability of the soils in a region. The objective of this study was to create a spectral library of distinct soils from several agricultural regions of Brazil. Spectral data were collected (using a Fieldspec sensor, 350-2,500 nm) for the horizons of 223 soil profiles from the regions of Matão, Paraguaçu Paulista, Andradina, Ipaussu, Mirandópolis, Piracicaba, São Carlos, Araraquara, Guararapes, Valparaíso (SP); Naviraí, Maracajú, Rio Brilhante, Três Lagoas (MS); Goianésia (GO); and Uberaba and Lagoa da Prata (MG). A Principal Component Analysis (PCA) of the data was then performed and a graphic representation of the spectral curve was created for each profile. The reflectance intensity of the curves was principally influenced by the levels of Fe2O3, clay, organic matter and the presence of opaque minerals. There was no change in the spectral curves in the horizons of the Latossolos, Nitossolos, and Neossolos Quartzarênicos. Argissolos had superficial horizon curves with the greatest intensity of reflection above 2,200 nm. Cambissolos and Neossolos Litólicos had curves with greater reflectance intensity in poorly developed horizons. Gleisols showed a convex curve in the region of 350-400 nm. The PCA was able to separate different data collection areas according to the region of source material. Principal component one (PC1) was correlated with the intensity of reflectance samples and PC2 with the slope between the visible and infrared samples. The use of the Spectral Library as an indicator of possible soil classes proved to be an important tool in profile classification.

Side scan sonar image and geologic interpretation of the Ria de Pontevedra seafloor (Galicia, NW Spain).

High-resolution side scan sonar has been used for mapping the seafloor of the Ría de Pontevedra. Four backscatter patterns have been mapped within the Ría: (1) Pattern with isolated reflections, correlated with granite and metamorphic outcrops and located close to the coastal prominence and Ons and Onza Islands. (2) Pattern of strong reflectivity usually located around the basement outcrops and near the coastline and produced by coarse-grained sediment. (3) Pattern of weak backscatter is correlated with fine sand to mud and comprising large areas in the central and deep part of the Ría, where the bottom currents are weak. It is generally featureless, except where pockmarks and anthropogenic features are present. (4) Patches of strong and weak backscatter are located in the boundary between coarse and fine-grained sediments and they are due to the effect of strong bottom currents. The presence of megaripples associated to both patterns of strong reflectivity and sedimentary patches indicate bedload transport of sediment during high energy conditions (storms). Side scan sonar records and supplementary bathymetry, bottom samples and hydrodynamic data reveal that the distribution of seafloor sediment is strongly related to oceanographic processes and the particular morphology and topography of the Ría.

Comment on the plasmon model for image-potential-induced surface states

Calculations of the binding energy of bound positron states in metal surfaces, with explicit inclusion of plasmon dispersion and single-particle effects, are presented. The binding energy is greatly reduced with respect to the undispersed case.

Semiclassical image potential at a solid surface

A surface dielectric function of a semi-infinite plane-bounded metal is defined in the spirit of the plasmon-pole dielectric function of the bulk. It is modeled in such a way that the surface-plasmon dispersion relation is recovered for small momentum transfer. This function is employed to compute the image potential at all distances outside the surface. Interaction with bulk modes is neglected for simplicity and clarity. The interaction of a massive point charge with a metal surface is also considered in the context of a boson model for surface-plasmon excitation. We present a new definition of the image potential for this case.

Voir le monde à travers les lunettes du métacontraste : un modèle mathématique inspiré de la psychologie sociale

Résumé La théorie de l'autocatégorisation est une théorie de psychologie sociale qui porte sur la relation entre l'individu et le groupe. Elle explique le comportement de groupe par la conception de soi et des autres en tant que membres de catégories sociales, et par l'attribution aux individus des caractéristiques prototypiques de ces catégories. Il s'agit donc d'une théorie de l'individu qui est censée expliquer des phénomènes collectifs. Les situations dans lesquelles un grand nombre d'individus interagissent de manière non triviale génèrent typiquement des comportements collectifs complexes qui sont difficiles à prévoir sur la base des comportements individuels. La simulation informatique de tels systèmes est un moyen fiable d'explorer de manière systématique la dynamique du comportement collectif en fonction des spécifications individuelles. Dans cette thèse, nous présentons un modèle formel d'une partie de la théorie de l'autocatégorisation appelée principe du métacontraste. À partir de la distribution d'un ensemble d'individus sur une ou plusieurs dimensions comparatives, le modèle génère les catégories et les prototypes associés. Nous montrons que le modèle se comporte de manière cohérente par rapport à la théorie et est capable de répliquer des données expérimentales concernant divers phénomènes de groupe, dont par exemple la polarisation. De plus, il permet de décrire systématiquement les prédictions de la théorie dont il dérive, notamment dans des situations nouvelles. Au niveau collectif, plusieurs dynamiques peuvent être observées, dont la convergence vers le consensus, vers une fragmentation ou vers l'émergence d'attitudes extrêmes. Nous étudions également l'effet du réseau social sur la dynamique et montrons qu'à l'exception de la vitesse de convergence, qui augmente lorsque les distances moyennes du réseau diminuent, les types de convergences dépendent peu du réseau choisi. Nous constatons d'autre part que les individus qui se situent à la frontière des groupes (dans le réseau social ou spatialement) ont une influence déterminante sur l'issue de la dynamique. Le modèle peut par ailleurs être utilisé comme un algorithme de classification automatique. Il identifie des prototypes autour desquels sont construits des groupes. Les prototypes sont positionnés de sorte à accentuer les caractéristiques typiques des groupes, et ne sont pas forcément centraux. Enfin, si l'on considère l'ensemble des pixels d'une image comme des individus dans un espace de couleur tridimensionnel, le modèle fournit un filtre qui permet d'atténuer du bruit, d'aider à la détection d'objets et de simuler des biais de perception comme l'induction chromatique. Abstract Self-categorization theory is a social psychology theory dealing with the relation between the individual and the group. It explains group behaviour through self- and others' conception as members of social categories, and through the attribution of the proto-typical categories' characteristics to the individuals. Hence, it is a theory of the individual that intends to explain collective phenomena. Situations involving a large number of non-trivially interacting individuals typically generate complex collective behaviours, which are difficult to anticipate on the basis of individual behaviour. Computer simulation of such systems is a reliable way of systematically exploring the dynamics of the collective behaviour depending on individual specifications. In this thesis, we present a formal model of a part of self-categorization theory named metacontrast principle. Given the distribution of a set of individuals on one or several comparison dimensions, the model generates categories and their associated prototypes. We show that the model behaves coherently with respect to the theory and is able to replicate experimental data concerning various group phenomena, for example polarization. Moreover, it allows to systematically describe the predictions of the theory from which it is derived, specially in unencountered situations. At the collective level, several dynamics can be observed, among which convergence towards consensus, towards frag-mentation or towards the emergence of extreme attitudes. We also study the effect of the social network on the dynamics and show that, except for the convergence speed which raises as the mean distances on the network decrease, the observed convergence types do not depend much on the chosen network. We further note that individuals located at the border of the groups (whether in the social network or spatially) have a decisive influence on the dynamics' issue. In addition, the model can be used as an automatic classification algorithm. It identifies prototypes around which groups are built. Prototypes are positioned such as to accentuate groups' typical characteristics and are not necessarily central. Finally, if we consider the set of pixels of an image as individuals in a three-dimensional color space, the model provides a filter that allows to lessen noise, to help detecting objects and to simulate perception biases such as chromatic induction.

Highlands of the upper Jequitinhonha valley, Brazil: I - characterization and classification

In the upper Jequitinhonha valley, state of Minas Gerais, Brazi, there are large plane areas known as "chapadas", which are separated by areas dissected by tributaries of the Jequitinhonha and Araçuaí rivers. These dissected areas have a surface drainage system with tree, shrub, and grass vegetation, more commonly known as "veredas", i.e., palm swamps. The main purpose of this study was to characterize soil physical, chemical and morphological properties of a representative toposequence in the watershed of the Vereda Lagoa do Leandro, a swamp near Minas Novas, MG, on "chapadas", the highlands of the Alto Jequitinhonha region Different soil types are observed in the landscape: at the top - Typic Haplustox (LVA), in the middle slope - Xanthic Haplustox (LA), at the footslope - Xanthic Haplustox, gray color, here called "Gray Haplustox" ("LAC") and, at the bottom of the palm swamp - Typic Albaquult (GXbd). These soils were first morphologically described; samples of disturbed and undisturbed soils were collected from all horizons and subhorizons, to evaluate their essential physical and chemical properties, by means of standard determination of Fe, Al, Mn, Ti and Si oxides after sulfuric extraction. The contents of Fe, Al and Mn, extracted with dithionite-citrate-bicarbonate and oxalate treatments, were also determined. In the well-drained soils of the slope positions, the typical morphological, physical and chemical properties of Oxisols were found. The GXbd sample, from the bottom of the palm swamp, is grayish and has high texture gradient (B/A) and massive structure. The reduction of the proportion of crystalline iron compounds and the low crystallinity along the slope confirmed the loss of iron during pedogenesis, which is reflected in the current soil color. The Si and Al contents were lowest in the "LAC" soil. There was a decrease of the Fe2O3/TiO2 ratio downhill, indicating progressive drainage restriction along the toposequence. The genesis and all physical and chemical properties of the soils at the footslope and the bottom of the palm swamp of the "chapadas" of the Alto Jequitinhonha region are strongly influenced by the occurrence of ground water on the surface or near the surface all year long, at present and/or in the past. Total concentrations of iron oxides, Fe d and Fe o in soils of the toposequence studied are related to the past and/or present soil colors and drainage conditions.

Voir le monde comme une image : le schème de l'image mimétique dans la philosophie de Platon (Cratyle, Sophiste, Timée)

Résumé de la thèse Le travail de thèse «VOIR LE MONDE COMME UNE IMAGE. Le schème de l'image mimétique dans la philosophie de Platon (Cratyle, Sophiste, Timée) » d'Alexandre NEVSKY étudie la conception philosophique de l'image chez Platon. En posant la question : qu'est-ce que l'image pour Platon? l'étude se propose, dans un premier temps, d'analyser la manière précise dont l'idée de l'image fonctionne dans l'articulation logique de l'enquête platonicienne, en se basant avant tout sur trois dialogues majeurs où cette idée est explicitement thématisée par Platon lui-même, à savoir le Cratyle, le Sophiste et le Timée. Par une analyse détaillée de ces textes, Alexandre Nevsky essaie de démontrer que l'idée de l'image fonctionne comme un schème euristique dont la logique interne détermine les moments clés dans le déroulement de chaque dialogue examiné, et constitue ainsi une véritable méthode d'investigation philosophique pour Platon. En suivant cette stratégie platonicienne, l'auteur nous montre quel rôle le schème de l'image joue selon Platon d'abord dans la constitution du langage (le Cratyle), puis, dans celle du discours (le Sophiste) et, enfin, dans celle du monde (le Timée). Une telle approche lui permet de revoir l'interprétation traditionnelle de certains passages clés, célèbres pour leurs difficultés, en mettant en évidence la façon dont la nouvelle perspective platonicienne, introduite grâce au schème de l'image, permet de formuler une solution philosophique originale du problème initial. On y trouve ainsi rediscutés, pour ne citer que quelques exemples, la théorie curieuse de l'imitation phonétique et le problème de la justesse propre du nom-image, la définition philosophique de la notion d'image et la distinction platonicienne entre limage-ressemblance et l'image-apparence, la logique paradoxale de l'introduction d'un troisième genre dans la structure ontologique de l'être et la question du sens exact à donner au «discours vraisemblable » de Platon sur la naissance de l'univers. Dans un deuxième temps, cette étude tente de dégager, derrière la méthode heuristique basée sur le schème de l'image, une véritable conception de l'image mimétique chez Platon. L'une des idées principales de la thèse est ici de montrer que cette conception présente une solution philosophique de Platon au problème de l'apparence archaïque. Car, face à la question sophistique : comment une chose - que ce soit le discours ou le monde - peut-elle être une apparence, quelque chose qui n'existe pas? Platon apporte une réponse tout à fait originale elle le peut en tant qu'image. Or, l'image n'est pas une simple apparence illusoire, elle est le reflet d'une autre réalité, indépendante et véritable, que l'on doit supposer, selon Platon, même quand sa nature exacte nous échappe encore. La conception platonicienne de l'image apparaît ainsi comme un pendant indispensable de la théorie des Formes intelligibles et aussi comme son étape préalable au niveau de laquelle l'âme du philosophe, dans son ascension vers la vérité, se retrouve dans un espace intermédiaire, déjà au-delà des illusions du monde phénoménal, mais encore en-deçà des engagements métaphysiques de la théorie des Formes.