Genetic basis of adaptation in Arabidopsis thaliana: local adaptation at the seed dormancy QTL DOG1.

Local adaptation provides an opportunity to study the genetic basis of adaptation and investigate the allelic architecture of adaptive genes. We study delay of germination 1 (DOG1), a gene controlling natural variation in seed dormancy in Arabidopsis thaliana and investigate evolution of dormancy in 41 populations distributed in four regions separated by natural barriers. Using F(ST) and Q(ST) comparisons, we compare variation at DOG1 with neutral markers and quantitative variation in seed dormancy. Patterns of genetic differentiation among populations suggest that the gene DOG1 contributes to local adaptation. Although Q(ST) for seed dormancy is not different from F(ST) for neutral markers, a correlation with variation in summer precipitation supports that seed dormancy is adaptive. We characterize dormancy variation in several F(2) -populations and show that a series of functionally distinct alleles segregate at the DOG1 locus. Theoretical models have shown that the number and effect of alleles segregatin at quantitative trait loci (QTL) have important consequences for adaptation. Our results provide support to models postulating a large number of alleles at quantitative trait loci involved in adaptation.

Classification of sags according to their origin based on the waveform similarity

A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours

Revised nomenclature and classification of inherited ichthyoses: results of the First Ichthyosis Consensus Conference in Sorèze 2009.

BACKGROUND: Inherited ichthyoses belong to a large, clinically and etiologically heterogeneous group of mendelian disorders of cornification, typically involving the entire integument. Over the recent years, much progress has been made defining their molecular causes. However, there is no internationally accepted classification and terminology. OBJECTIVE: We sought to establish a consensus for the nomenclature and classification of inherited ichthyoses. METHODS: The classification project started at the First World Conference on Ichthyosis in 2007. A large international network of expert clinicians, skin pathologists, and geneticists entertained an interactive dialogue over 2 years, eventually leading to the First Ichthyosis Consensus Conference held in Sorèze, France, on January 23 and 24, 2009, where subcommittees on different issues proposed terminology that was debated until consensus was reached. RESULTS: It was agreed that currently the nosology should remain clinically based. "Syndromic" versus "nonsyndromic" forms provide a useful major subdivision. Several clinical terms and controversial disease names have been redefined: eg, the group caused by keratin mutations is referred to by the umbrella term, "keratinopathic ichthyosis"-under which are included epidermolytic ichthyosis, superficial epidermolytic ichthyosis, and ichthyosis Curth-Macklin. "Autosomal recessive congenital ichthyosis" is proposed as an umbrella term for the harlequin ichthyosis, lamellar ichthyosis, and the congenital ichthyosiform erythroderma group. LIMITATIONS: As more becomes known about these diseases in the future, modifications will be needed. CONCLUSION: We have achieved an international consensus for the classification of inherited ichthyosis that should be useful for all clinicians and can serve as reference point for future research.

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.

New classification of natural breeding habitats for Neotropical anophelines in the Yanomami Indian Reserve, Amazon Region, Brazil and a new larval sampling methodology

Here we present the first in a series of articles about the ecology of immature stages of anophelines in the Brazilian Yanomami area. We propose a new larval habitat classification and a new larval sampling methodology. We also report some preliminary results illustrating the applicability of the methodology based on data collected in the Brazilian Amazon rainforest in a longitudinal study of two remote Yanomami communities, Parafuri and Toototobi. In these areas, we mapped and classified 112 natural breeding habitats located in low-order river systems based on their association with river flood pulses, seasonality and exposure to sun. Our classification rendered seven types of larval habitats: lakes associated with the river, which are subdivided into oxbow lakes and nonoxbow lakes, flooded areas associated with the river, flooded areas not associated with the river, rainfall pools, small forest streams, medium forest streams and rivers. The methodology for larval sampling was based on the accurate quantification of the effective breeding area, taking into account the area of the perimeter and subtypes of microenvironments present per larval habitat type using a laser range finder and a small portable inflatable boat. The new classification and new sampling methodology proposed herein may be useful in vector control programs.

Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach.

Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

Classification and clinical behavior of blastic plasmacytoid dendritic cell neoplasms according to their maturation-associated immunophenotypic profile.

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare subtype of leukemia/lymphoma, whose diagnosis can be difficult to achieve due to its clinical and biological heterogeneity, as well as its overlapping features with other hematologic malignancies. In this study we investigated whether the association between the maturational stage of tumor cells and the clinico-biological and prognostic features of the disease, based on the analysis of 46 BPDCN cases classified into three maturation-associated subgroups on immunophenotypic grounds. Our results show that blasts from cases with an immature plasmacytoid dendritic cell (pDC) phenotype exhibit an uncommon CD56- phenotype, coexisting with CD34+ non-pDC tumor cells, typically in the absence of extramedullary (e.g. skin) disease at presentation. Conversely, patients with a more mature blast cell phenotype more frequently displayed skin/extramedullary involvement and spread into secondary lymphoid tissues. Despite the dismal outcome, acute lymphoblastic leukemia-type therapy (with central nervous system prophylaxis) and/or allogeneic stem cell transplantation appeared to be the only effective therapies. Overall, our findings indicate that the maturational profile of pDC blasts in BPDCN is highly heterogeneous and translates into a wide clinical spectrum -from acute leukemia to mature lymphoma-like behavior-, which may also lead to variable diagnosis and treatment.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.

Coupled reproductive ecologies in a plant-pollinator-seed predator system

Résumé de la thèseBien que le mutualisme puisse être considéré comme une relation harmonieuse entre différentes espèces, son étude révèle plutôt une exploitation réciproque où chaque partenaire tente de maximiser ses bénéfices tout en réduisant ses coûts. Dans ce contexte, l'identification des facteurs qui favorisent ou contrarient, au cours de l'évolution, une issue mutualiste est une étape majeure pour pouvoir reconstruire les étapes clés menant à l'apparition et au maintien des interactions mutualistes. Le but de ce doctorat était l'identification des traits phénotypiques qui permettent à la plante Silene latofolia (Caryophyllacée)et à son pollinisateur - prédateur de graines, la phalène Hadena bicruris (Noctuidé), d'augmenter les bénéfices nets que chacun retire de l'interaction. Ce système d'étude est particulièrement bien approprié à l'étude de ces traits, car on peut assez facilement estimer la qualité et la quantité des descendants (fitness) des deux partenaires. En effet, la femelle papillon pond un oeuf dans la fleur qu'elle pollinise et sa larve se développe dans le fruit, consommant les graines de la plante. Ainsi, sur une même plante, il est possible d'estimer les succès respectifs de la plante et du papillon à obtenir une descendance. De plus, le conflit d'intérêt autour des graines qui sont indispensables, à la fois à la plante et au papillon, peut stimuler l'évolution de traits qui limitent la surexploitation réciproque des partenaires. Dans une première étude, j'ai montré que le papillon mâle était un pollinisateur efficace de S. latifolia et qu'ainsi, il permettait à la plante d'augmenter le nombre de graines produites (i.e.bénéfice) sans pour autant augmenter la quantité de larves sur la plante. Dans ce système, les papillons pondent un seul oeuf par fleur, déposé soit à l'intérieur de la fleur, dans le tube de corolle, soit sur le pétale. Ma seconde étude montre que les plantes répondent différemment à la présence des oeufs suivant leur position. Aussi, quand l'oeuf est placé dans la fleur, la plante a davantage tendance à ne pas développer le fruit de la fleur infesté ou bien à produire des fruits plus petits que lorsque l'oeuf est placé sur le pétale. Enfin, j'ai montré que la femelle du papillon pond plus souvent sur le pétale lorsque elle visite des fleurs dotées d'un long tube de corolle, et que les larves issues de ces oeufs ont moins de chances de réussir à pénétrer dans le fruit que les larves issues des oeufs placés à l'intérieur de la fleur. Aussi, la variation observée du site de ponte pourrait être causé par la morphologie de la fleur qui contraint le papillon à pondre sur le pétale. Vu dans leur ensemble, les résultats obtenus pendant ce doctorat suggèrent que la participation des mâles à la pollination, l'absence de développement des fruits et la profondeur du tube de corolle pourraient réduire les coûts que S. latifolia subit dans son interaction avec H. bicruris. Par ailleurs, je n'ai pas détecté de mécanismes qui permettraient au papillon de réduire les coûts que la plante pourrait lui imposer. La prochaine étape serait de déterminer l'effet des traits identifiés dans ce doctorat sur la fitness globale de la plante et du papillon pour estimer pleinement leur efficacité à réduire les coûts et à favoriser une issue mutualiste. De même, il faudrait évaluer l'effet de ces traits en populations naturelles pour identifier le rôle des facteurs environnementaux sur leur efficacité.AbstractAlthough mutualisms can be regarded as harmonious relationships between the interacting partners, they are best conceptualized as reciprocal exploitations in which each partner attempts to increase its own benefits and decrease its costs. To date, identifying the factors which promote or discourage mutualistic outcomes remains a major goal to reconstruct the ecological conditions leading to mutualisms. The aim of this PhD thesis was to identify phenotypic traits that may increase the net benefits of each partner in the interaction between the plant Silene latifolia (Caryophyllaceae) and its pollinator / seed predator, the moth Hadena bicruris (Noctuidae). This study system is particularly well suited because the fitness of both interacting species can be assessed. The female moth lays its egg in the flower it pollinated, and its offspring grows in the fruit, feeding on the seeds of the plant, which allows for the follow-up of both larva and fruit fates. Furthermore, the inherent conflict of interest over the seeds as plant progeny vs. larval resource may stimulate the evolution of traits that reduce overexploitation in both the moth and plant. In a first study, I show that male moths are efficient pollinators, hence increasing seed production without increasing oviposition. The contribution of male moths to pollination might thus improve the net benefits of the interaction for the host plant. Females of the H. bicruris moth lay a single egg per flower, and place it either inside the corolla tube or on the petal. My second study shows that plants are more likely to abort the infested flower or to produce a smaller fruit when the egg was experimentally placed inside the flower compared to plants that received an egg on the petal. Finally, female moths were found to lay their eggs more frequently on the petal when visiting a flower with a deep corolla tube, and larvae hatching from these eggs less likely to successfully attack the fruit. Variation in egg position on the flower may thus be the result of a constraint imposed by floral morphology. Overall, this PhD work suggests that the pollination by male moths, flower abortion, and deep corolla tube may efficiently reduce the costs experienced by S. latifolia in its interaction with H. bicruris. Interestingly, no apparent mechanism of costs reduction was detected for the moth. Further studies should focus on the effects of these traits (i) in the long term fitness of both the plant and the insect and (ii) their interactions with environmental factors (biotic and abiotic) that may affect their efficiency in natural populations.

Les champignons : essai de classification / par le Dr Paul Vuillemin,...

Collection : Bibliothèque de botanique cryptogamique

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one