Notch1 is required for neuronal and glial differentiation in the cerebellum.

The mechanisms that guide progenitor cell fate and differentiation in the vertebrate central nervous system (CNS) are poorly understood. Gain-of-function experiments suggest that Notch signaling is involved in the early stages of mammalian neurogenesis. On the basis of the expression of Notch1 by putative progenitor cells of the vertebrate CNS, we have addressed directly the role of Notch1 in the development of the mammalian brain. Using conditional gene ablation, we show that loss of Notch1 results in premature onset of neurogenesis by neuroepithelial cells of the midbrain-hindbrain region of the neural tube. Notch1-deficient cells do not complete differentiation but are eliminated by apoptosis, resulting in a reduced number of neurons in the adult cerebellum. We have also analyzed the effects of Notch1 ablation on gliogenesis in vivo. Our results show that Notch1 is required for both neuron and glia formation and modulates the onset of neurogenesis within the cerebellar neuroepithelium.

Comparison of the developmental effects of two mercury compounds on glial cells and neurons in aggregate cultures of rat telencephalon.

A three-dimensional cell culture system was used as a model to study the influence of low levels of mercury in the developing brain. Aggregating cell cultures of fetal rat telencephalon were treated for 10 days either during an early developmental period (i.e., between days 5 and 15 in vitro) or during a phase of advanced maturation (i.e., between days 25 and 35) with mercury. An inorganic (HgCl2) and an organic mercury compound (monomethylmercury chloride, MeHgCl) were examined. By monitoring changes in cell type-specific enzymes activities, the concentration-dependent toxicity of the compounds was determined. In immature cultures, a general cytotoxicity was observed at 10(-6) M for both mercury compounds. In these cultures, HgCl2 appeared somewhat more toxic than MeHgCl. However, no appreciable demethylation of MeHgCl could be detected, indicating similar toxic potencies for both mercury compounds. In highly differentiated cultures, by contrast, MeHgCl exhibited a higher toxic potency than HgCl2. In addition, at 10(-6) M, MeHgCl showed pronounced neuron-specific toxicity. Below the cytotoxic concentrations, distinct glia-specific reactions could be observed with both mercury compounds. An increase in the immunoreactivity for glial fibrillary acidic protein, typical for gliosis, could be observed at concentrations between 10(-9) M and 10(-7) M in immature cultures, and between 10(-8) M and 3 x 10(-5) M in highly differentiated cultures. A conspicuous increase in the number and clustering of GSI-B4 lectin-binding cells, indicating a microglial response, was found at concentrations between 10(-10) M and 10(-7) M. These development-dependent and cell type-specific effects may reflect the pathogenic potential of long-term exposure to subclinical doses of mercury.

Storage and uptake of D-serine into astrocytic synaptic-like vesicles specify gliotransmission.

Glial cells are increasingly recognized as active players that profoundly influence neuronal synaptic transmission by specialized signaling pathways. In particular, astrocytes have been shown recently to release small molecules, such as the amino acids l-glutamate and d-serine as "gliotransmitters," which directly control the efficacy of adjacent synapses. However, it is still controversial whether gliotransmitters are released from a cytosolic pool or by Ca(2+)-dependent exocytosis from secretory vesicles, i.e., by a mechanism similar to the release of synaptic vesicles in synapses. Here we report that rat cortical astrocytes contain storage vesicles that display morphological and biochemical features similar to neuronal synaptic vesicles. These vesicles share some, but not all, membrane proteins with synaptic vesicles, including the SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) synaptobrevin 2, and contain both l-glutamate and d-serine. Furthermore, they show uptake of l-glutamate and d-serine that is driven by a proton electrochemical gradient. d-Serine uptake is associated with vesicle acidification and is dependent on chloride. Whereas l-serine is not transported, serine racemase, the synthesizing enzyme for d-serine, is anchored to the membrane of the vesicles, allowing local generation of d-serine. Finally, we reveal a previously unexpected mutual vesicular synergy between d-serine and l-glutamate filling in glia vesicles. We conclude that astrocytes contain vesicles capable of storing and releasing d-serine, l-glutamate, and most likely other neuromodulators in an activity-dependent manner.

FADD adaptor and PEA-15/ERK1/2 partners in major depression and schizophrenia postmortem brains: Basal contents and effects of psychotropic treatments.

Enhanced brain apoptosis (neurons and glia) may be involved in major depression (MD) and schizophrenia (SZ), mainly through the activation of the intrinsic (mitochondrial) apoptotic pathway. In the extrinsic death pathway, pro-apoptotic Fas-associated death domain (FADD) adaptor and its non-apoptotic p-Ser194 FADD form have critical roles interacting with other death regulators such as phosphoprotein enriched in astrocytes of 15kDa (PEA-15) and extracellular signal-regulated kinase (ERK). The basal status of FADD (protein and messenger RNA (mRNA)) and the effects of psychotropic drugs (detected in blood/urine samples) were first assessed in postmortem prefrontal cortex of MD and SZ subjects (including a non-MD/SZ suicide group). In MD, p-FADD, but not total FADD (and mRNA), was increased (26%, n=24; all MD subjects) as well as p-FADD/FADD ratio (a pro-survival marker) in antidepressant-free MD subjects (50%, n=10). In contrast, cortical FADD (and mRNA), p-FADD, and p-FADD/FADD were not altered in SZ brains (n=21) regardless of antipsychotic medications (except enhanced mRNA in treated subjects). Similar negative results were quantified in the non-MD/SZ suicide group. In MD, the regulation of multifunctional PEA-15 (i.e., p-Ser116 PEA-15 blocks pro-apoptotic FADD and PEA-15 prevents pro-survival ERK action) and the modulation of p-ERK1/2 were also investigated. Cortical p-PEA-15 was not changed whereas PEA-15 was increased mainly in antidepressant-treated subjects (16-20%). Interestingly, cortical p-ERK1/2/ERK1/2 ratio was reduced (33%) in antidepressant-free when compared to antidepressant-treated MD subjects. The neurochemical adaptations of brain FADD (increased p-FADD and pro-survival p-FADD/FADD ratio), as well as its interaction with PEA-15, could play a major role to counteract the known activation of the mitochondrial apoptotic pathway in MD.

Visual cortex in Alzheimer's disease: occurrence of neuronal death and glial proliferation, and correlation with pathological hallmarks.

Visual areas 17 and 18 were studied with morphometric methods for numbers of neurons, glia, senile plaques (SP), and neurofibrillary tangles (NFT) in 13 cases of Alzheimer's disease (AD) as compared to 11 controls. In AD cases, the mean neuronal density was significantly decreased by about 30% in both areas 17 and 18, while the glial density was increased significantly only in area 17. The volume of area 17 was unchanged in AD cases but its total number of neurons was decreased by 33% and its total number of glia increased by 45% compared to controls. In AD the number of SP was similar in areas 17 and 18, while that of NFT was significantly higher in area 18. The number of neurons with NFT was only 2% in area 17 and about 10% in area 18. The discrepancy between the loss of neurons and the amount of NFT suggests that neuronal loss can occur without passing through NFT degeneration. The deposition of SP was correlated with glial proliferation, but not with neuronal loss or neurofibrillary degeneration.

Flow-targeted inversion-prepared b-TFE coronary MR angiography: initial results in patients.

PURPOSE: Visualization of coronary blood flow in the right and left coronary system in volunteers and patients by means of a modified inversion-prepared bright-blood coronary magnetic resonance angiography (cMRA) sequence. MATERIALS AND METHODS: cMRA was performed in 14 healthy volunteers and 19 patients on a 1.5 Tesla MR system using a free-breathing 3D balanced turbo field echo (b-TFE) sequence with radial k-space sampling. For magnetization preparation a slab selective and a 2D selective inversion pulse were used for the right and left coronary system, respectively. cMRA images were evaluated in terms of clinically relevant stenoses (< 50 %) and compared to conventional catheter angiography. Signal was measured in the coronary arteries (coro), the aorta (ao) and in the epicardial fat (fat) to determine SNR and CNR. In addition, maximal visible vessel length, and vessel border definition were analyzed. RESULTS: The use of a selective inversion pre-pulse allowed direct visualization of the coronary blood flow in the right and left coronary system. The measured SNR and CNR, vessel length, and vessel sharpness in volunteers (SNR coro: 28.3 +/- 5.0; SNR ao: 37.6 +/- 8.4; CNR coro-fat: 25.3 +/- 4.5; LAD: 128.0 cm +/- 8.8; RCA: 74.6 cm +/- 12.4; Sharpness: 66.6 % +/- 4.8) were slightly increased compared to those in patients (SNR coro: 24.1 +/- 3.8; SNR ao: 33.8 +/- 11.4; CNR coro-fat: 19.9 +/- 3.3; LAD: 112.5 cm +/- 13.8; RCA: 69.6 cm +/- 16.6; Sharpness: 58.9 % +/- 7.9; n.s.). In the patient study the assessment of 42 coronary segments lead to correct identification of 10 clinically relevant stenoses. CONCLUSION: The modification of a previously published inversion-prepared cMRA sequence allowed direct visualization of the coronary blood flow in the right as well as in the left coronary system. In addition, this sequence proved to be highly sensitive regarding the assessment of clinically relevant stenotic lesions.

In situ fluorescence imaging of glutamate-evoked mitochondrial Na+ responses in astrocytes.

Astrocytes can experience large intracellular Na+ changes following the activation of the Na+-coupled glutamate transport. The present study investigated whether cytosolic Na+ changes are transmitted to mitochondria, which could therefore influence their function and contribute to the overall intracellular Na+ regulation. Mitochondrial Na+ (Na+(mit)) changes were monitored using the Na+-sensitive fluorescent probe CoroNa Red (CR) in intact primary cortical astrocytes, as opposed to the classical isolated mitochondria preparation. The mitochondrial localization and Na+ sensitivity of the dye were first verified and indicated that it can be safely used as a selective Na+(mit) indicator. We found by simultaneously monitoring cytosolic and mitochondrial Na+ using sodium-binding benzofuran isophthalate and CR, respectively, that glutamate-evoked cytosolic Na+ elevations are transmitted to mitochondria. The resting Na+(mit) concentration was estimated at 19.0 +/- 0.8 mM, reaching 30.1 +/- 1.2 mM during 200 microM glutamate application. Blockers of conductances potentially mediating Na+ entry (calcium uniporter, monovalent cation conductances, K+(ATP) channels) were not able to prevent the Na+(mit) response to glutamate. However, Ca2+ and its exchange with Na+ appear to play an important role in mediating mitochondrial Na+ entry as chelating intracellular Ca2+ with BAPTA or inhibiting Na+/Ca2+ exchanger with CGP-37157 diminished the Na+(mit) response. Moreover, intracellular Ca2+ increase achieved by photoactivation of caged Ca2+ also induced a Na+(mit) elevation. Inhibition of mitochondrial Na/H antiporter using ethylisopropyl-amiloride caused a steady increase in Na+(mit) without increasing cytosolic Na+, indicating that Na+ extrusion from mitochondria is mediated by these exchangers. Thus, mitochondria in intact astrocytes are equipped to efficiently sense cellular Na+ signals and to dynamically regulate their Na+ content.

Spatial learning by rats across visually disconnected environments

Two spatial tasks were designed to test specific properties of spatial representation in rats. In the first task, rats were trained to locate an escape hole at a fixed position in a visually homogeneous arena. This arena was connected with a periphery where a full view of the room environment existed. Therefore, rats were dependent on their memory trace of the previous position in the periphery to discriminate a position within the central region. Under these experimental conditions, the test animals showed a significant discrimination of the training position without a specific local view. In the second task, rats were trained in a radial maze consisting of tunnels that were transparent at their distal ends only. Because the central part of the maze was non-transparent, rats had to plan and execute appropriate trajectories without specific visual feedback from the environment. This situation was intended to encourage the reliance on prospective memory of the non-visited arms in selecting the following move. Our results show that acquisition performance was only slightly decreased compared to that shown in a completely transparent maze and considerably higher than in a translucent maze or in darkness. These two series of experiments indicate (1) that rats can learn about the relative position of different places with no common visual panorama, and (2) that they are able to plan and execute a sequence of visits to several places without direct visual feed-back about their relative position.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Local re-inversion coronary MR angiography: arterial spin-labeling without the need for subtraction.

PURPOSE: To implement a double-inversion bright-blood coronary MR angiography sequence using a cylindrical re-inversion prepulse for selective visualization of the coronary arteries. MATERIALS AND METHODS: Local re-inversion bright-blood magnetization preparation was implemented using a nonselective inversion followed by a cylindrical aortic re-inversion prepulse. After an inversion delay that allows for in-flow of the labeled blood-pool into the coronary arteries, three-dimensional radial steady-state free-precession (SSFP) imaging (repetition/echo time, 7.2/3.6 ms; flip angle, 120 degrees, 16 profiles per RR interval; field of view, 360 mm; matrix, 512, twelve 3-mm slices) is performed. Coronary MR angiography was performed in three healthy volunteers and in one patient on a commercial 1.5 Tesla whole-body MR System. RESULTS: In all subjects, coronary arteries were selectively visualized with positive contrast. In addition, a middle-grade stenosis of the proximal right coronary artery was seen in one patient. CONCLUSION: A novel T1 contrast-enhancement strategy is presented for selective visualization of the coronary arteries without extrinsic contrast medium application. In comparison to former arterial spin-labeling schemes, the proposed magnetization preparation obviates the need for a second data set and subtraction.

Sh3tc2 deficiency affects neuregulin-1/ErbB signaling.

Mutations in SH3TC2 trigger autosomal recessive demyelinating Charcot-Marie-Tooth type 4C (CMT4C) neuropathy. Sh3tc2 is specifically expressed in Schwann cells and is necessary for proper myelination of peripheral axons. In line with the early onset of neuropathy observed in patients with CMT4C, our analyses of the murine model of CMT4C revealed that the myelinating properties of Sh3tc2-deficient Schwann cells are affected at an early stage. This early phenotype is associated with changes in the canonical Nrg1/ErbB pathway involved in control of myelination. We demonstrated that Sh3tc2 interacts with ErbB2 and plays a role in the regulation of ErbB2 intracellular trafficking from the plasma membrane upon Nrg1 activation. Interestingly, both the loss of Sh3tc2 function in mice and the pathological mutations present in CMT4C patients affect ErbB2 internalization, potentially altering its downstream intracellular signaling pathways. Altogether, our results indicate that the molecular mechanism for the axonal size sensing is disturbed in Sh3tc2-deficient myelinating Schwann cells, thus providing a novel insight into the pathophysiology of CMT4C neuropathy.

Small but thick enough-the Arabidopsis hypocotyl as a model to study secondary growth.

The continuous production of vascular tissues through secondary growth results in radial thickening of plant organs and is pivotal for various aspects of plant growth and physiology, such as water transport capacity or resistance to mechanical stress. It is driven by the vascular cambium, which produces inward secondary xylem and outward secondary phloem. In the herbaceous plant Arabidopsis thaliana (Arabidopsis), secondary growth occurs in stems, in roots and in the hypocotyl. In the latter, radial growth is most prominent and not obscured by parallel ongoing elongation growth. Moreover, its progression is reminiscent of the secondary growth mode of tree trunks. Thus, the Arabidopsis hypocotyl is a very good model to study basic molecular mechanisms of secondary growth. Genetic approaches have succeeded in the identification of various factors, including peptides, receptors, transcription factors and hormones, which appear to participate in a complex network that controls radial growth. Many of these players are conserved between herbaceous and woody plants. In this review, we will focus on what is known about molecular mechanisms and regulators of vascular secondary growth in the Arabidopsis hypocotyl.

Metabolic activation pattern of distinct hippocampal subregions during spatial learning and memory retrieval.

Activation dynamics of hippocampal subregions during spatial learning and their interplay with neocortical regions is an important dimension in the understanding of hippocampal function. Using the (14C)-2-deoxyglucose autoradiographic method, we have characterized the metabolic changes occurring in hippocampal subregions in mice while learning an eight-arm radial maze task. Autoradiogram densitometry revealed a heterogeneous and evolving pattern of enhanced metabolic activity throughout the hippocampus during the training period and on recall. In the early stages of training, activity was enhanced in the CA1 area from the intermediate portion to the posterior end as well as in the CA3 area within the intermediate portion of the hippocampus. At later stages, CA1 and CA3 activations spread over the entire longitudinal axis, while dentate gyrus (DG) activation occurred from the anterior to the intermediate zone. Activation of the retrosplenial cortex but not the amygdala was also observed during the learning process. On recall, only DG activation was observed in the same anterior part of the hippocampus. These results suggest the existence of a functional segmentation of the hippocampus, each subregion being dynamically but also differentially recruited along the acquisition, consolidation, and retrieval process in parallel with some neocortical sites.

Pro-inflammatory cytokines induce the transcription factors C/EBPbeta and C/EBPdelta in astrocytes.

The transcription factors CCAAT/enhancer binding protein (C/EBP)-beta and -delta are key regulators for the expression of the acute phase genes in the liver, such as complement component C3 and antichymotrypsin. In the brain, these acute phase proteins are produced in response to pro-inflammatory cytokines by the reactive astrocytes, in particular those surrounding the amyloid plaques of Alzheimer's disease brains. Here we show that lipopolysaccharides (LPS), IL-1beta, and TNFalpha induce the expression of the c/ebpbeta and -delta genes in mouse primary astrocytes. This induction precedes the expression of the acute phase genes coding for the complement component C3 and the mouse homologue of antichymotrypsin. The induction of these two acute phase genes by LPS is blocked by cycloheximide, whereas this protein synthesis inhibitor does not affect the expression of the c/ebp genes. Altogether, our data support a role as immediate-early genes for c/ebpbeta and -delta, whose expression is induced by pro-inflammatory cytokines in mouse cortical astrocytes. In the liver, these transcription factors are known to play an important role in inflammation and energy metabolism regulation. Therefore, C/EBPbeta and -delta could be pivotal transcription factors involved in brain inflammation, in addition to their previously demonstrated role in brain glycogen metabolism regulation (Cardinaux and Magistretti. J Neurosci 16:919-929, 1996).

Multi-scale systems analysis of plant development : beyond cellular signaling and tissue morphodynamics

Les plantes sont essentielles pour les sociétés humaines. Notre alimentation quotidienne, les matériaux de constructions et les sources énergétiques dérivent de la biomasse végétale. En revanche, la compréhension des multiples aspects développementaux des plantes est encore peu exploitée et représente un sujet de recherche majeur pour la science. L'émergence des technologies à haut débit pour le séquençage de génome à grande échelle ou l'imagerie de haute résolution permet à présent de produire des quantités énormes d'information. L'analyse informatique est une façon d'intégrer ces données et de réduire la complexité apparente vers une échelle d'abstraction appropriée, dont la finalité est de fournir des perspectives de recherches ciblées. Ceci représente la raison première de cette thèse. En d'autres termes, nous appliquons des méthodes descriptives et prédictives combinées à des simulations numériques afin d'apporter des solutions originales à des problèmes relatifs à la morphogénèse à l'échelle de la cellule et de l'organe. Nous nous sommes fixés parmi les objectifs principaux de cette thèse d'élucider de quelle manière l'interaction croisée des phytohormones auxine et brassinosteroïdes (BRs) détermine la croissance de la cellule dans la racine du méristème apical d'Arabidopsis thaliana, l'organisme modèle de référence pour les études moléculaires en plantes. Pour reconstruire le réseau de signalement cellulaire, nous avons extrait de la littérature les informations pertinentes concernant les relations entre les protéines impliquées dans la transduction des signaux hormonaux. Le réseau a ensuite été modélisé en utilisant un formalisme logique et qualitatif pour pallier l'absence de données quantitatives. Tout d'abord, Les résultats ont permis de confirmer que l'auxine et les BRs agissent en synergie pour contrôler la croissance de la cellule, puis, d'expliquer des observations phénotypiques paradoxales et au final, de mettre à jour une interaction clef entre deux protéines dans la maintenance du méristème de la racine. Une étude ultérieure chez la plante modèle Brachypodium dystachion (Brachypo- dium) a révélé l'ajustement du réseau d'interaction croisée entre auxine et éthylène par rapport à Arabidopsis. Chez ce dernier, interférer avec la biosynthèse de l'auxine mène à la formation d'une racine courte. Néanmoins, nous avons isolé chez Brachypodium un mutant hypomorphique dans la biosynthèse de l'auxine qui affiche une racine plus longue. Nous avons alors conduit une analyse morphométrique qui a confirmé que des cellules plus anisotropique (plus fines et longues) sont à l'origine de ce phénotype racinaire. Des analyses plus approfondies ont démontré que la différence phénotypique entre Brachypodium et Arabidopsis s'explique par une inversion de la fonction régulatrice dans la relation entre le réseau de signalisation par l'éthylène et la biosynthèse de l'auxine. L'analyse morphométrique utilisée dans l'étude précédente exploite le pipeline de traitement d'image de notre méthode d'histologie quantitative. Pendant la croissance secondaire, la symétrie bilatérale de l'hypocotyle est remplacée par une symétrie radiale et une organisation concentrique des tissus constitutifs. Ces tissus sont initialement composés d'une douzaine de cellules mais peuvent aisément atteindre des dizaines de milliers dans les derniers stades du développement. Cette échelle dépasse largement le seuil d'investigation par les moyens dits 'traditionnels' comme l'imagerie directe de tissus en profondeur. L'étude de ce système pendant cette phase de développement ne peut se faire qu'en réalisant des coupes fines de l'organe, ce qui empêche une compréhension des phénomènes cellulaires dynamiques sous-jacents. Nous y avons remédié en proposant une stratégie originale nommée, histologie quantitative. De fait, nous avons extrait l'information contenue dans des images de très haute résolution de sections transverses d'hypocotyles en utilisant un pipeline d'analyse et de segmentation d'image à grande échelle. Nous l'avons ensuite combiné avec un algorithme de reconnaissance automatique des cellules. Cet outil nous a permis de réaliser une description quantitative de la progression de la croissance secondaire révélant des schémas développementales non-apparents avec une inspection visuelle classique. La formation de pôle de phloèmes en structure répétée et espacée entre eux d'une longueur constante illustre les bénéfices de notre approche. Par ailleurs, l'exploitation approfondie de ces résultats a montré un changement de croissance anisotropique des cellules du cambium et du phloème qui semble en phase avec l'expansion du xylème. Combinant des outils génétiques et de la modélisation biomécanique, nous avons démontré que seule la croissance plus rapide des tissus internes peut produire une réorientation de l'axe de croissance anisotropique des tissus périphériques. Cette prédiction a été confirmée par le calcul du ratio des taux de croissance du xylème et du phloème au cours de développement secondaire ; des ratios élevés sont effectivement observés et concomitant à l'établissement progressif et tangentiel du cambium. Ces résultats suggèrent un mécanisme d'auto-organisation établi par un gradient de division méristématique qui génèrent une distribution de contraintes mécaniques. Ceci réoriente la croissance anisotropique des tissus périphériques pour supporter la croissance secondaire. - Plants are essential for human society, because our daily food, construction materials and sustainable energy are derived from plant biomass. Yet, despite this importance, the multiple developmental aspects of plants are still poorly understood and represent a major challenge for science. With the emergence of high throughput devices for genome sequencing and high-resolution imaging, data has never been so easy to collect, generating huge amounts of information. Computational analysis is one way to integrate those data and to decrease the apparent complexity towards an appropriate scale of abstraction with the aim to eventually provide new answers and direct further research perspectives. This is the motivation behind this thesis work, i.e. the application of descriptive and predictive analytics combined with computational modeling to answer problems that revolve around morphogenesis at the subcellular and organ scale. One of the goals of this thesis is to elucidate how the auxin-brassinosteroid phytohormone interaction determines the cell growth in the root apical meristem of Arabidopsis thaliana (Arabidopsis), the plant model of reference for molecular studies. The pertinent information about signaling protein relationships was obtained through the literature to reconstruct the entire hormonal crosstalk. Due to a lack of quantitative information, we employed a qualitative modeling formalism. This work permitted to confirm the synergistic effect of the hormonal crosstalk on cell elongation, to explain some of our paradoxical mutant phenotypes and to predict a novel interaction between the BREVIS RADIX (BRX) protein and the transcription factor MONOPTEROS (MP),which turned out to be critical for the maintenance of the root meristem. On the same subcellular scale, another study in the monocot model Brachypodium dystachion (Brachypodium) revealed an alternative wiring of auxin-ethylene crosstalk as compared to Arabidopsis. In the latter, increasing interference with auxin biosynthesis results in progressively shorter roots. By contrast, a hypomorphic Brachypodium mutant isolated in this study in an enzyme of the auxin biosynthesis pathway displayed a dramatically longer seminal root. Our morphometric analysis confirmed that more anisotropic cells (thinner and longer) are principally responsible for the mutant root phenotype. Further characterization pointed towards an inverted regulatory logic in the relation between ethylene signaling and auxin biosynthesis in Brachypodium as compared to Arabidopsis, which explains the phenotypic discrepancy. Finally, the morphometric analysis of hypocotyl secondary growth that we applied in this study was performed with the image-processing pipeline of our quantitative histology method. During its secondary growth, the hypocotyl reorganizes its primary bilateral symmetry to a radial symmetry of highly specialized tissues comprising several thousand cells, starting with a few dozens. However, such a scale only permits observations in thin cross-sections, severely hampering a comprehensive analysis of the morphodynamics involved. Our quantitative histology strategy overcomes this limitation. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with an automated cell type recognition algorithm, it allows precise quantitative characterization of vascular development and reveals developmental patterns that were not evident from visual inspection, for example the steady interspace distance of the phloem poles. Further analyses indicated a change in growth anisotropy of cambial and phloem cells, which appeared in phase with the expansion of xylem. Combining genetic tools and computational modeling, we showed that the reorientation of growth anisotropy axis of peripheral tissue layers only occurs when the growth rate of central tissue is higher than the peripheral one. This was confirmed by the calculation of the ratio of the growth rate xylem to phloem throughout secondary growth. High ratios are indeed observed and concomitant with the homogenization of cambium anisotropy. These results suggest a self-organization mechanism, promoted by a gradient of division in the cambium that generates a pattern of mechanical constraints. This, in turn, reorients the growth anisotropy of peripheral tissues to sustain the secondary growth.