Geometric morphometric analyses provide evidence for the adaptive character of the Tanganyikan cichlid fish radiations.

The cichlids of East Africa are renowned as one of the most spectacular examples of adaptive radiation. They provide a unique opportunity to investigate the relationships between ecology, morphological diversity, and phylogeny in producing such remarkable diversity. Nevertheless, the parameters of the adaptive radiations of these fish have not been satisfactorily quantified yet. Lake Tanganyika possesses all of the major lineages of East African cichlid fish, so by using geometric morphometrics and comparative analyses of ecology and morphology, in an explicitly phylogenetic context, we quantify the role of ecology in driving adaptive speciation. We used geometric morphometric methods to describe the body shape of over 1000 specimens of East African cichlid fish, with a focus on the Lake Tanganyika species assemblage, which is composed of more than 200 endemic species. The main differences in shape concern the length of the whole body and the relative sizes of the head and caudal peduncle. We investigated the influence of phylogeny on similarity of shape using both distance-based and variance partitioning methods, finding that phylogenetic inertia exerts little influence on overall body shape. Therefore, we quantified the relative effect of major ecological traits on shape using phylogenetic generalized least squares and disparity analyses. These analyses conclude that body shape is most strongly predicted by feeding preferences (i.e., trophic niches) and the water depths at which species occur. Furthermore, the morphological disparity within tribes indicates that even though the morphological diversification associated with explosive speciation has happened in only a few tribes of the Tanganyikan assemblage, the potential to evolve diverse morphologies exists in all tribes. Quantitative data support the existence of extensive parallelism in several independent adaptive radiations in Lake Tanganyika. Notably, Tanganyikan mouthbrooders belonging to the C-lineage and the substrate spawning Lamprologini have evolved a multitude of different shapes from elongated and Lamprologus-like hypothetical ancestors. Together, these data demonstrate strong support for the adaptive character of East African cichlid radiations.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Adaptive diversity in heterogeneous environments for populations regulated by a mixture of soft and hard selection

The stable co-existence of two haploid genotypes or two species is studied in a spatially heterogeneous environment submitted to a mixture of soft selection (within-patch regulation) and hard selection (outside-patch regulation) and where two kinds of resource are available. This is analysed both at an ecological time-scale (short term) and at an evolutionary time-scale (long term). At an ecological scale, we show that co-existence is very unlikely if the two competitors are symmetrical specialists exploiting different resources. In this case, the most favourable conditions are met when the two resources are equally available, a situation that should favour generalists at an evolutionary scale. Alternatively, low within-patch density dependence (soft selection) enhances the co-existence between two slightly different specialists of the most available resource. This results from the opposing forces that are acting in hard and soft regulation modes. In the case of unbalanced accessibility to the two resources, hard selection favours the most specialized genotype, whereas soft selection strongly favours the less specialized one. Our results suggest that competition for different resources may be difficult to demonstrate in the wild even when it is a key factor in the maintenance of adaptive diversity. At an evolutionary scale, a monomorphic invasive evolutionarily stable strategy (ESS) always exists. When a linear trade-off exists between survival in one habitat versus that in another, this ESS lies between an absolute adjustment of survival to niche size (for mainly soft-regulated populations) and absolute survival (specialization) in a single niche (for mainly hard-regulated populations). This suggests that environments in agreement with the assumptions of such models should lead to an absence of adaptive variation in the long term.

Adaptive colour polymorphism of Acrida ungarica H. (Orthoptera: Acrididae) in a spatially heterogeneous environment

Intra-specific colour polymorphism provides a cryptic camouflage from predators in heterogeneous habitats. The orthoptera species, Acrida ungarica (Herbst, 1786) possess two well-distinguished colour morphs: brown and green and displays several disruptive colouration patterns within each morph to improve the crypsis. This study focused on how the features of the background environment relate to the proportion of the two morphs and to the intensity of disruptive colouration patterns in A. ungarica. As the two sexes are very distinct with respect to mass and length, we also distinctively tested the relationship for each sex. In accordance with the background matching hypothesis, we found that, for both sexes, the brown morph was in higher proportion at sites with a brown-dominant environment, and green morphs were in higher proportion in green-dominant environments. Globally, individuals in drier sites and in the drier year also had more intense disruptive colouration patterns, and brown morphs and females were also more striped. Colour patterns differed largely between populations and were significantly correlated with relevant environmental features. Even if A. ungarica is a polymorphic specialist, disruptive colouration still appears to provide strong benefits, particularly in some habitats. Moreover, because females are larger, they are less able to flee, which might explain the difference between sexes

An adaptive multiscale method for density-driven instabilities

Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

The expansion of amino-acid repeats is not associated to adaptive evolution in mammalian genes.

BACKGROUND: The expansion of amino acid repeats is determined by a high mutation rate and can be increased or limited by selection. It has been suggested that recent expansions could be associated with the potential of adaptation to new environments. In this work, we quantify the strength of this association, as well as the contribution of potential confounding factors. RESULTS: Mammalian positively selected genes have accumulated more recent amino acid repeats than other mammalian genes. However, we found little support for an accelerated evolutionary rate as the main driver for the expansion of amino acid repeats. The most significant predictors of amino acid repeats are gene function and GC content. There is no correlation with expression level. CONCLUSIONS: Our analyses show that amino acid repeat expansions are causally independent from protein adaptive evolution in mammalian genomes. Relaxed purifying selection or positive selection do not associate with more or more recent amino acid repeats. Their occurrence is slightly favoured by the sequence context but mainly determined by the molecular function of the gene.

MDCT arthrography of the hip: value of the adaptive statistical iterative reconstruction technique and potential for radiation dose reduction.

OBJECTIVE: The purpose of this article is to assess the effect of the adaptive statistical iterative reconstruction (ASIR) technique on image quality in hip MDCT arthrography and to evaluate its potential for reducing radiation dose. SUBJECTS AND METHODS: Thirty-seven patients examined with hip MDCT arthrography were prospectively randomized into three different protocols: one with a regular dose (volume CT dose index [CTDIvol], 38.4 mGy) and two with a reduced dose (CTDIvol, 24.6 or 15.4 mGy). Images were reconstructed using filtered back projection (FBP) and four increasing percentages of ASIR (30%, 50%, 70%, and 90%). Image noise and contrast-to-noise ratio (CNR) were measured. Two musculoskeletal radiologists independently evaluated several anatomic structures and image quality parameters using a 4-point scale. They also jointly assessed acetabular labrum tears and articular cartilage lesions. RESULTS: With decreasing radiation dose level, image noise statistically significantly increased (p=0.0009) and CNR statistically significantly decreased (p=0.001). We also found a statistically significant reduction in noise (p=0.0001) and increase in CNR (p≤0.003) with increasing percentage of ASIR; in addition, we noted statistically significant increases in image quality scores for the labrum and cartilage, subchondral bone, overall diagnostic quality (up to 50% ASIR), and subjective noise (p≤0.04), and statistically significant reductions for the trabecular bone and muscles (p≤0.03). Regardless of the radiation dose level, there were no statistically significant differences in the detection and characterization of labral tears (n=24; p=1) and cartilage lesions (n=40; p≥0.89) depending on the ASIR percentage. CONCLUSION: The use of up to 50% ASIR in hip MDCT arthrography helps to reduce radiation dose by approximately 35-60%, while maintaining diagnostic image quality comparable to that of a regular-dose protocol using FBP.

The adaptive function of melanin-based coloration in the tawny owl (Strix aluco) ; the proximate role of the melanocortin system

Colour polymorphism is common in wild population. One of the main questioning of evolutionary biologists is to understand how different colour variants could have evolved and be maintained in fluctuating environments, a selective process that forces individuals to constantly adapt their strategies in order to survive. This issue is particularly true for traits that are genetically inherited. Natural selection erodes genotypes with lowest fitness (less adapted), reducing in turn global genetic variation within population. In this context, the study of the evolution and maintenance of melanin- based coloration is relevant since inter-individual variation in the deposition of these pigments is common in animal and plant kingdoms and is under strong genetic control. In this thesis, I focus on the specific case of the tawny owl (Strix aluco), a species displaying continuous variation in reddish pheomelanin-based coloration. Interestingly, empirical studies highlighted covariations between melanin-based coloration and important behavioural, physiological and life history traits. Recently, a genetic model pointed out the melanocortin system and their pleiotropic effects as a potential regulator of these covariations. Accordingly, this PhD thesis further investigates colour-specific behavioural, physiological, or life history strategies, while examining the proximate mechanisms underlying these reaction norms. We found that differently coloured tawny owls differently resolve fundamental trade-off between offspring number and quality (Chapter 1), light melanic individuals producing many low- quality offspring and dark, melanic ones producing few high-quality offspring. These reproductive strategies are likely to induce alternative physiological constraints. Indeed, we demonstrated that light melanic individuals produced higher levels of reactive oxygen species (ROS, Chapter 2), but also expressed higher levels of antioxidant (GSH, Chapters 2 & 3). Interestingly, we showed that light melanic breeding females could modulate their POMC prohormone levels according to the environmental conditions, while dark reddish ones produced constant levels of this prohormone {Chapter 4). Finally, we highlighted colour-specific patterns of prohormone convertase 1 (PCI) gene expression (Chapter 5), an enzyme responsible for POMC prohormone processing to ACTH and a- MSH, for instance. Altogether, these results provide strong evidence of colour-specific strategies, light and melanic tawny owls better coping with stressful and relaxed environments, respectively. Variation in melanin-based coloration is likely to be maintained by the heterogeneity of our study area and strong environmental stochasticity within and between years, these process favouring differently coloured tawny owls at different periods of time. From a proximate point of view, this PhD thesis supports the hypothesis that covariations between phenotypic traits and melanin-based coloration stems from the melanocortin system, especially the fundamental role of POMC gene expression and its processing to melanocortin peptides. - Le polymorphisme de couleur est une variation phénotypique très fréquente dans la nature. En biologie évolutive, une des problématiques clés est donc de comprendre comment différent morphes de couleur peuvent être apparus et maintenus au cours du temps dans des environnements aussi variables que les nôtres, surtout que ces fluctuations forcent ces morphes à s'adapter constamment pour assurer leur survie. Cette thématique est particulièrement réelle lorsque les variations phénotypiques sont héréditaires et donc sous forte influence génétique. La sélection naturelle a en effet le pouvoir d'éroder rapidement la variation génétique en éliminant les génotypes mal adaptés. Dans ce sens, l'étude de l'évolution, et de la maintenance de la coloration mélanique est donc tout à fait pertinente car la variation de coloration entre individus est très répandue à travers les règnes animal et végétal et sous forte influence génétique. Dans cette thèse, je me suis concentré sur le cas spécifique de la chouette hulotte (Strix aluco), une espèce présentant une variation continue dans la déposition de pigments pheomélaniques roux. De précédentes études ont déjà montré que cette variation de coloration était associée avec des variations de traits comportementaux, physiologiques ou d'histoire de vie. Récemment, une étude a souligné l'importance du système des mélanocortines et de leurs effets pléiotropes dans la régulation de ces covariations. En conséquence, cette thèse de doctoral a pour but d'étudier un peu plus les stratégies comportementales, physiologiques ou d'histoire de vie spécifiques à chaque morphe de couleur, tout en examinant un peu plus les mécanismes proximaux potentiellement à la base de ces normes de réactions. Nous constatons tout d'abord que les morphes de couleurs étaient associés à différentes stratégies dans la résolution de compromis telle que la production de beaucoup de jeunes ou des jeunes de qualité (Chapitre 1). Les morphes gris (dit peu mélaniques) ont tendance à produire beaucoup de jeunes mains de moindre qualité, alors que les morphes roux (dit fortement mélaniques) produisent moins de jeunes mais de meilleure qualité. Ces stratégies sont susceptibles alors d'induire certaines contraintes physiologiques. Par exemple, nous montrons que les morphes gris produisent plus de dérivés réactifs de l'oxygène (ROS, Chapitre 2), mais aussi plus d'antioxydants (GSH, Chapitres 2 & 3). Nous montrons ensuite que les femelles grises ont une plus grande capacité à moduler leur niveau de POMC prohormone dans le sang en fonction des conditions environnementales, alors que les femelles rousses gardent un niveau constant (Chapitre 4). Finalement, nous démontrons que les patterns d'expression du gène codant pour la prohormone convertase 1 varient chez des jeunes issus de parents gris ou roux (Chapitre 5). Ceci est particulièrement intéressant car cette enzyme permet de scinder la POMC prohormone en plusieurs peptides importants tels que l'ACTH ou l'a-MSH. En conclusion, ces résultats démontrent qu'il y a bel et bien des stratégies évolutives différentes entre les morphes de couleurs, les chouettes hulottes grises et rousses étant respectivement plus adaptés à des environnements stressants ou favorables. L'hétérogénéité de notre zone d'étude et la stochasticité environnementale qui caractérise ses habitats pourraient donc agir comme une source de sélection temporelle, laquelle favoriserait les différents morphes de couleurs à diverses périodes. D'un point de vue plus proximale maintenant, cette thèse de doctorat soutient l'hypothèse que les covariations observées entre la coloration mélanique et des traits phénotypiques importants sont modulées par les effets pléiotropes du système des mélanocortines, et met en avant le rôle prépondérant que pourrait jouer l'expression du gène POMC et sa post traduction en mélanocortines.

Angiotensin II-mediated adaptive and maladaptive remodeling of cardiomyocyte excitation-contraction coupling.

Cardiac hypertrophy is associated with alterations in cardiomyocyte excitation-contraction coupling (ECC) and Ca(2+) handling. Chronic elevation of plasma angiotensin II (Ang II) is a major determinant in the pathogenesis of cardiac hypertrophy and congestive heart failure. However, the molecular mechanisms by which the direct actions of Ang II on cardiomyocytes contribute to ECC remodeling are not precisely known. This question was addressed using cardiac myocytes isolated from transgenic (TG1306/1R [TG]) mice exhibiting cardiac specific overexpression of angiotensinogen, which develop Ang II-mediated cardiac hypertrophy in the absence of hemodynamic overload. Electrophysiological techniques, photolysis of caged Ca(2+) and confocal Ca(2+) imaging were used to examine ECC remodeling at early ( approximately 20 weeks of age) and late ( approximately 60 weeks of age) time points during the development of cardiac dysfunction. In young TG mice, increased cardiac Ang II levels induced a hypertrophic response in cardiomyocyte, which was accompanied by an adaptive change of Ca(2+) signaling, specifically an upregulation of the Na(+)/Ca(2+) exchanger-mediated Ca(2+) transport. In contrast, maladaptation was evident in older TG mice, as suggested by reduced sarcoplasmic reticulum Ca(2+) content resulting from a shift in the ratio of plasmalemmal Ca(2+) removal and sarcoplasmic reticulum Ca(2+) uptake. This was associated with a conserved ECC gain, consistent with a state of hypersensitivity in Ca(2+)-induced Ca(2+) release. Together, our data suggest that chronic elevation of cardiac Ang II levels significantly alters cardiomyocyte ECC in the long term, and thereby contractility, independently of hemodynamic overload and arterial hypertension.

Mechanism of HFR1 function in adaptive growth responses in "Arabidopsis thaliana"

AbstractPlants are sessile organisms, which have evolved an astonishing ability to sense changes in their environment. Depending on the surrounding conditions, such as changes in light and temperature, plants modulate the activity of important transcriptional regulators. The shade avoidance syndrome (SAS) is one important mechanism for shade-intolerant plants to adapt their growth in high vegetative density. In shaded conditions plants sense a diminished red/far-red ratio via the phytochrome system and respond with morphological changes such as elongation growth of stems and petioles. The Phytochrome Interacting Factors 4 and 5 (PIF4 and PIF5) are positive regulators of the SAS and required for a full response (Lorrain et al, 2008). They regulate the SAS by inducing the expression of shade avoidance marker genes such as PIL1, ATHB2, XTR7 and HFR1 (Hornitschek et al, 2009; Lorrain et al, 2008).I investigated the molecular mechanism underlying the regulation of the SAS by HFR1 (long Hypocotyl in FR light). Although HFR1 is a PIF-related bHLH transcription factor, we discovered that HFR1 is a non-DNA binding protein. Moreover, we revealed that HFR1 inhibits an exaggerated SAS by forming non-DNA binding heterodimers with PIF4 and PIF5 (Hornitschek et al, 2009). This negative feedback loop is an important mechanism to limit elongation growth also in elevated temperatures. HFR1 accumulation and activity are highly temperature-dependent and the increased activity of HFR1 at warmer temperatures also provides an important restraint on PIF4-driven elongation growth (Foreman et al, 2011).Finally we performed a genome-wide analysis to determine how PIF4 and PIF5 regulate growth in response to shade. We identified potential PIF5- target genes, which represent many well-known shade-responsive genes. Our analysis of gene expression also revealed a role of PIF4 and PIF5 in simulated sun possibly via the regulation of auxin sensitivity.RésuméLes plantes sont des organismes sessiles ayant développé une capacité surprenante à détecter des changements dans leur environnement. En fonction des conditions extérieures, telles que les variations de lumière ou de température, elles adaptent l'activité d'importants régulateurs transcriptionnels. Le syndrome d'évitement de l'ombre (SAS), est un mécanisme important pour les plantes intolérantes à l'ombre leur permettant d'adapter leur croissance lorsqu'elles se développent dans des conditions de végétations très denses. Dans ces conditions, les plantes détectent une réduction de la quantité relative de lumière rouge par rapport à la lumière rouge-lointain (rapport R/FR). Ce changement, perçu via le système des phytochromes, induit des modifications morphologiques telle qu'une élongation des tiges et des pétioles. Les protéines PIF4 et PIF5 (Phytochrome Interacting Factors) sont des régulateurs positifs du SAS et sont nécessaires pour une réponse complète (Lorrain et al, 2008). Ces facteurs de transcription régulent le SAS en induisant l'expression de gènes marqueurs de cette réponse tels que PIL1, ATHB2, XTR7 et HFR1 (Hornitschek et al, 2009; Lorrain et al, 2008).J'ai étudié les mécanismes moléculaires sous-jacents à la régulation du SAS par HFR1 (long Hypocotyl in FR light). HFR1 est un facteur de transcription type bHLH de la famille des PIF, quoique nous ayons découvert que HFR1 est une protéine ne se liant pas à Γ ADN. Nous avons montré que HFR1 inhibe un SAS exagéré en formant des heterodimères avec PIF4 et PIF5 (Hornitschek et al, 2009). Nous avons également montré que cette boucle de régulation négative est également un mécanisme important pour limiter la croissance de l'élongation dans des conditions de fortes températures. De plus l'accumulation et l'activité de HFR1 augmentent avec la température ce qui permet d'inhiber plus fortement l'effet activateur de PIF4 sur la croissance.Enfin, nous avons effectué une analyse génomique à large échelle afin de déterminer comment PIF4 et PIF5 régulent la croissance en réponse à l'ombre. Nous avons identifié les gènes cibles potentiels de PIF5, correspondant en partie à des gènes connus dans la réponse de l'évitement de l'ombre. Notre analyse de l'expression des gènes a également révélé un rôle important de PIF4 et PIF5 dans des conditions de croissance en plein soleil, probablement via la régulation de la sensibilité à l'auxine.

Adaptive statistical iterative reconstruction reduces patient radiation dose in neuroradiology CT studies.

INTRODUCTION: Adaptive statistical iterative reconstruction (ASIR) can decrease image noise, thereby generating CT images of comparable diagnostic quality with less radiation. The purpose of this study is to quantify the effect of systematic use of ASIR versus filtered back projection (FBP) for neuroradiology CT protocols on patients' radiation dose and image quality. METHODS: We evaluated the effect of ASIR on six types of neuroradiologic CT studies: adult and pediatric unenhanced head CT, adult cervical spine CT, adult cervical and intracranial CT angiography, adult soft tissue neck CT with contrast, and adult lumbar spine CT. For each type of CT study, two groups of 100 consecutive studies were retrospectively reviewed: 100 studies performed with FBP and 100 studies performed with ASIR/FBP blending factor of 40 %/60 % with appropriate noise indices. The weighted volume CT dose index (CTDIvol), dose-length product (DLP) and noise were recorded. Each study was also reviewed for image quality by two reviewers. Continuous and categorical variables were compared by t test and free permutation test, respectively. RESULTS: For adult unenhanced brain CT, CT cervical myelography, cervical and intracranial CT angiography and lumbar spine CT both CTDIvol and DLP were lowered by up to 10.9 % (p < 0.001), 17.9 % (p = 0.005), 20.9 % (p < 0.001), and 21.7 % (p = 0.001), respectively, by using ASIR compared with FBP alone. Image quality and noise were similar for both FBP and ASIR. CONCLUSION: We recommend routine use of iterative reconstruction for neuroradiology CT examinations because this approach affords a significant dose reduction while preserving image quality.

Active Contour-Based Segmentation of Head and Neck with Adaptive Atlas Selection

This paper presents automated segmentation of structuresin the Head and Neck (H\&N) region, using an activecontour-based joint registration and segmentation model.A new atlas selection strategy is also used. Segmentationis performed based on the dense deformation fieldcomputed from the registration of selected structures inthe atlas image that have distinct boundaries, onto thepatient's image. This approach results in robustsegmentation of the structures of interest, even in thepresence of tumors, or anatomical differences between theatlas and the patient image. For each patient, an atlasimage is selected from the available atlas-database,based on the similarity metric value, computed afterperforming an affine registration between each image inthe atlas-database and the patient's image. Unlike manyof the previous approaches in the literature, thesimilarity metric is not computed over the entire imageregion; rather, it is computed only in the regions ofsoft tissue structures to be segmented. Qualitative andquantitative evaluation of the results is presented.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.