Mapping of Environmental Data Using Kernel-Based Methods

Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

Mult-class differentiation of cannabis seedlings in a forensic context

This article presents an experimental study about the classification ability of several classifiers for multi-classclassification of cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland lawenforcement authorities regularly ask forensic laboratories to determinate the chemotype of a seized cannabisplant and then to conclude if the plantation is legal or not. This classification is mainly performed when theplant is mature as required by the EU official protocol and then the classification of cannabis seedlings is a timeconsuming and costly procedure. A previous study made by the authors has investigated this problematic [1]and showed that it is possible to differentiate between drug type (illegal) and fibre type (legal) cannabis at anearly stage of growth using gas chromatography interfaced with mass spectrometry (GC-MS) based on therelative proportions of eight major leaf compounds. The aims of the present work are on one hand to continueformer work and to optimize the methodology for the discrimination of drug- and fibre type cannabisdeveloped in the previous study and on the other hand to investigate the possibility to predict illegal cannabisvarieties. Seven classifiers for differentiating between cannabis seedlings are evaluated in this paper, namelyLinear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Nearest NeighbourClassification (NNC), Learning Vector Quantization (LVQ), Radial Basis Function Support Vector Machines(RBF SVMs), Random Forest (RF) and Artificial Neural Networks (ANN). The performance of each method wasassessed using the same analytical dataset that consists of 861 samples split into drug- and fibre type cannabiswith drug type cannabis being made up of 12 varieties (i.e. 12 classes). The results show that linear classifiersare not able to manage the distribution of classes in which some overlap areas exist for both classificationproblems. Unlike linear classifiers, NNC and RBF SVMs best differentiate cannabis samples both for 2-class and12-class classifications with average classification results up to 99% and 98%, respectively. Furthermore, RBFSVMs correctly classified into drug type cannabis the independent validation set, which consists of cannabisplants coming from police seizures. In forensic case work this study shows that the discrimination betweencannabis samples at an early stage of growth is possible with fairly high classification performance fordiscriminating between cannabis chemotypes or between drug type cannabis varieties.

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.

Microbial influences on epithelial integrity and immune function as a basis for inflammatory diseases.

Certain autoimmune diseases as well as asthma have increased in recent decades, particularly in developed countries. The hygiene hypothesis has been the prevailing model to account for this increase; however, epidemiology studies also support the contribution of diet and obesity to inflammatory diseases. Diet affects the composition of the gut microbiota, and recent studies have identified various molecules and mechanisms that connect diet, the gut microbiota, and immune responses. Herein, we discuss the effects of microbial metabolites, such as short chain fatty acids, on epithelial integrity as well as immune cell function. We propose that dysbiosis contributes to compromised epithelial integrity and disrupted immune tolerance. In addition, dietary molecules affect the function of immune cells directly, particularly through lipid G-protein coupled receptors such as GPR43.

Immunocytochemical localisation of microtubule-associated proteins 1b and 2 in the developing rat spinal cord.

The straightforward anatomical organisation of the developing and mature rat spinal cord was used to determine and interpret the time of appearance and expression patterns of microtubule-associated proteins (MAP) 1b and 2. Immunoblots revealed the presence of MAP1b and 2 in the early embryonic rat spinal cord and confirmed the specificity of the used anti-MAP mouse monoclonal antibodies. The immunocytochemical data demonstrated a rostral-to-caudal and ventral-to-dorsal gradient in the expression of MAP1b/2 within the developing spinal cord. In the matrix layer, MAP1b was found in a distinct radial pattern distributed between the membrana limitans interna and externa between embryonal day (E)12 and E15. Immunostaining for vimentin revealed that this MAP1b pattern was morphologically and topographically different from the radial glial pattern which was present in the matrix layer between E13 and E19. The ventral-to-dorsal developmental gradient of the MAP1b staining in the spinal cord matrix layer indicates a close involvement of MAP1b either in the organisation of the microtubules in the cytoplasmatic extensions of the proliferating neuroblasts or neuroblast mitosis. MAP2 could not be detected in the developing matrix layer. In the mantle and marginal layer, MAP1b was abundantly present between E12 and postnatal day (P)0. After birth, the staining intensity for MAP1b gradually decreased in both layers towards a faint appearance at maturity. The distribution patterns suggest an involvement of MAP1b in the maturation of the motor neurons, the contralaterally and ipsilaterally projecting axons and the ascending and descending long axons of the rat spinal cord. MAP2 was present in the spinal cord grey matter between E12 and maturity, which reflects a role for MAP2 in the development as well as in the maintenance of microtubules. The present description of the expression patterns of MAP1b and 2 in the developing spinal cord suggests important roles of the two proteins in various morphogenetic events. The findings may serve as the basis for future studies on the function of MAP1b and 2 in the development of the central nervous system.

Neuromodulation by oxytocin and vasopressin in the central nervous system as a basis for their rapid behavioral effects

The last several years have seen an increasing number of studies that describe effects of oxytocin and vasopressin on the behavior of animals or humans. Studies in humans have reported behavioral changes and, through fMRI, effects on brain function. These studies are paralleled by a large number of reports, mostly in rodents, that have also demonstrated neuromodulatory effects by oxytocin and vasopressin at the circuit level in specific brain regions. It is the scope of this review to give a summary of the most recent neuromodulatory findings in rodents with the aim of providing a potential neurophysiological basis for their behavioral effects. At the same time, these findings may point to promising areas for further translational research towards human applications.

Essential role of CD8 palmitoylation in CD8 coreceptor function.

To investigate the molecular basis that makes heterodimeric CD8alphabeta a more efficient coreceptor than homodimeric CD8alphaalpha, we used various CD8 transfectants of T1.4 T cell hybridomas, which are specific for H-2Kd, and a photoreactive derivative of the Plasmodium berghei circumsporozoite peptide PbCS 252-260 (SYIPSAEKI). We demonstrate that CD8 is palmitoylated at the cytoplasmic tail of CD8beta and that this allows partitioning of CD8alphabeta, but not of CD8alphaalpha, in lipid rafts. Localization of CD8 in rafts is crucial for its coreceptor function. First, association of CD8 with the src kinase p56lck takes place nearly exclusively in rafts, mainly due to increased concentration of both components in this compartment. Deletion of the cytoplasmic domain of CD8beta abrogated localization of CD8 in rafts and association with p56lck. Second, CD8-mediated cross-linking of p56lck by multimeric Kd-peptide complexes or by anti-CD8 Ab results in p56lck activation in rafts, from which the abundant phosphatase CD45 is excluded. Third, CD8-associated activated p56lck phosphorylates CD3zeta in rafts and hence induces TCR signaling and T cell activation. This study shows that palmitoylation of CD8beta is required for efficient CD8 coreceptor function, mainly because it dramatically increases CD8 association with p56lck and CD8-mediated activation of p56lck in lipid rafts.

Interim analysis of the Reitan Catheter Pump (RCP) heart failure efficacy study: RCP improves cardiovascular and renal function in acute decompensated heart failure (ADHF)

Background: The RCP is a 14 French collapsable percutaneous cardiovascular support device positioned in the descending part of the thoracic aorta via the femoral artery. A 10 patient first in man study demonstrated device safety and significant improvement in renal function among high risk PCI patients. We now report haemodynamic and renal efficacy in patients with ADHF.Methods: Prospective non randomised study seeking to recruit 20 patients with ADHF with a need for inotropic or mechanical circulatory support with: i) EF < 30% ii)Cardiac index(CI) < 2.2 L / min / m2 Outcome measures included: 1) Cardiac index (CI) 2) Pulmonary Capillary Wedge Pressure (PCWP) 3) Urine output / serum creatinine 4) Vascular / device complications 5) 30 day mortalityResults: INTERIM ANALYSIS (n=12) The mean age of the study group was 64 years, with a mean baseline creatinine of 193 umol/L, eGFR 38 ml/min. The intended RCP treatment period was 24 hours. During RCP treatment there was a significant mean reduction of PCWP at 4 hours of 17% (25 to 21 mmHg p=0.04). Mean CI increased at 12 hours by 11%, though not reaching significance (1.78 to 1.96 L/min/m2 p=0.08). RCP insertion prompted substantial diuresis. Urine output tripled over the first 12 hours compared to baseline (55 ml/hr vs 213 ml/hr p=0.03). This was associated with significantly improved renal function, a 28% reduction in serum creatinine at 12 hours (193 to 151 umol/L p=0.003), and a increase in eGFR from 38 ml/min to 50 ml/min (p=0.0007). 2 patients previously refused cardiac transplantation were reassessed and successfully transplanted within 9 months of RCP treatment on the basis of demonstrable renal reversibility. There were no vascular or device complications. There were 2 deaths at 30 days, one from multi-organ failure and sepsis, and one from intractable heart failure - neither were device related.Conclusion: RCP support in ADHF patients was associated with improved haemodynamics, and an improvement in renal function. The Reitan Catheter Pump may have a role in providing percutaneous cardiovascular and renal support in the acutely decompensated cardiac patient, and may have a role in suggesting renal reversibility in potential cardiac transplant patients. Further data will be reported at recruitment completion.

Circadian regulation of renal function.

Urinary excretion of water and all major electrolytes exhibit robust circadian oscillations. The 24-h periodicity has been well documented for several important determinants of urine formation, including renal blood flow, glomerular filtration, tubular reabsorption, and tubular secretion. Disturbance of the renal circadian rhythms is increasingly recognized as a risk factor for hypertension, polyuria, and other diseases and may contribute to renal fibrosis. The origin of these rhythms has been attributed to the reactive response of the kidney to circadian changes in volume and/or in the composition of extracellular fluids that are entrained by rest/activity and feeding/fasting cycles. However, numerous studies have shown that most of the renal excretory rhythms persist for long periods of time, even in the absence of periodic environmental cues. These observations led to the hypothesis of the existence of a self-sustained mechanism, enabling the kidney to anticipate various predictable circadian challenges to homeostasis. The molecular basis of this mechanism remained unknown until the recent discovery of the mammalian circadian clock made of a system of autoregulatory transcriptional/translational feedback loops, which have been found in all tissues studied, including the kidney. Here, we present a review of the growing evidence showing the involvement of the molecular clock in the generation of renal excretory rhythms.

Distinct profiles of cytotoxic granules in memory CD8 T cells correlate with function, differentiation stage, and antigen exposure.

Cytotoxic CD8 T cells exert their antiviral and antitumor activity primarily through the secretion of cytotoxic granules. Degranulation activity and cytotoxic granules (perforin plus granzymes) generally define CD8 T cells with cytotoxic function. In this study, we have investigated the expression of granzyme K (GrmK) in comparison to that of GrmA, GrmB, and perforin. The expression of the cytotoxic granules was assessed in virus-specific CD8 T cells specific to influenza virus, Epstein-Barr virus (EBV), cytomegalovirus (CMV), or human immunodeficiency virus type 1 (HIV-1). We observed a dichotomy between GrmK and perforin expression in virus-specific CD8 T cells. The profile in influenza virus-specific CD8 T cells was perforin(-) GrmB(-) GrmA(+/-) GrmK(+); in CMV-specific cells, it was perforin(+) GrmB(+) GrmA(+) GrmK(-/+); and in EBV- and HIV-1-specific cells, it was perforin(-/+) GrmB(+) GrmA(+) GrmK(+). On the basis of the delineation of memory and effector CD8 T cells with CD45RA and CD127, the GrmK(+) profile was associated with early-stage memory CD8 T-cell differentiation, the perforin(+) GrmB(+) GrmA(+) profile with advanced-stage differentiation, and the GrmB(+) GrmA(+) Grmk(+) profile with intermediate-stage differentiation. Furthermore, perforin and GrmB but not GrmA and GrmK correlated with cytotoxic activity. Finally, changes in antigen exposure in vitro and in vivo during primary HIV-1 infection and vaccination modulated cytotoxic granule profiles. These results advance our understanding of the relationship between distinct profiles of cytotoxic granules in memory CD8 T cells and function, differentiation stage, and antigen exposure.

Diffusion spectrum imaging shows the structural basis of functional cerebellar circuits in the human cerebellum in vivo.

BACKGROUND: The cerebellum is a complex structure that can be affected by several congenital and acquired diseases leading to alteration of its function and neuronal circuits. Identifying the structural bases of cerebellar neuronal networks in humans in vivo may provide biomarkers for diagnosis and management of cerebellar diseases. OBJECTIVES: To define the anatomy of intrinsic and extrinsic cerebellar circuits using high-angular resolution diffusion spectrum imaging (DSI). METHODS: We acquired high-resolution structural MRI and DSI of the cerebellum in four healthy female subjects at 3T. DSI tractography based on a streamline algorithm was performed to identify the circuits connecting the cerebellar cortex with the deep cerebellar nuclei, selected brainstem nuclei, and the thalamus. RESULTS: Using in-vivo DSI in humans we were able to demonstrate the structure of the following cerebellar neuronal circuits: (1) connections of the inferior olivary nucleus with the cerebellar cortex, and with the deep cerebellar nuclei (2) connections between the cerebellar cortex and the deep cerebellar nuclei, (3) connections of the deep cerebellar nuclei conveyed in the superior (SCP), middle (MCP) and inferior (ICP) cerebellar peduncles, (4) complex intersections of fibers in the SCP, MCP and ICP, and (5) connections between the deep cerebellar nuclei and the red nucleus and the thalamus. CONCLUSION: For the first time, we show that DSI tractography in humans in vivo is capable of revealing the structural bases of complex cerebellar networks. DSI thus appears to be a promising imaging method for characterizing anatomical disruptions that occur in cerebellar diseases, and for monitoring response to therapeutic interventions.

Roles of mGluR5 in synaptic function and plasticity of the mouse thalamocortical pathway.

The group I metabotropic glutamate receptor 5 (mGluR5) has been implicated in the development of cortical sensory maps. However, its precise roles in the synaptic function and plasticity of thalamocortical (TC) connections remain unknown. Here we first show that in mGluR5 knockout (KO) mice bred onto a C57BL6 background cytoarchitectonic differentiation into barrels is missing, but the representations for large whiskers are identifiable as clusters of TC afferents. The altered dendritic morphology of cortical layer IV spiny stellate neurons in mGluR5 KO mice implicates a role for mGluR5 in the dendritic morphogenesis of excitatory neurons. Next, in vivo single-unit recordings of whisker-evoked activity in mGluR5 KO adults demonstrated a preserved topographical organization of the whisker representation, but a significantly diminished temporal discrimination of center to surround whiskers in the responses of individual neurons. To evaluate synaptic function at TC synapses in mGluR5 KO mice, whole-cell voltage-clamp recording was conducted in acute TC brain slices prepared from postnatal day 4-11 mice. At mGluR5 KO TC synapses, N-methyl-D-aspartate (NMDA) currents decayed faster and synaptic strength was more easily reduced, but more difficult to strengthen by Hebbian-type pairing protocols, despite a normal developmental increase in alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated currents and presynaptic function. We have therefore demonstrated that mGluR5 is required for synaptic function/plasticity at TC synapses as barrels are forming, and we propose that these functional alterations at the TC synapse are the basis of the abnormal anatomical and functional development of the somatosensory cortex in the mGluR5 KO mouse.

CD8beta endows CD8 with efficient coreceptor function by coupling T cell receptor/CD3 to raft-associated CD8/p56(lck) complexes.

The extraordinary sensitivity of CD8+ T cells to recognize antigen impinges to a large extent on the coreceptor CD8. While several studies have shown that the CD8beta chain endows CD8 with efficient coreceptor function, the molecular basis for this is enigmatic. Here we report that cell-associated CD8alphabeta, but not CD8alphaalpha or soluble CD8alphabeta, substantially increases the avidity of T cell receptor (TCR)-ligand binding. To elucidate how the cytoplasmic and transmembrane portions of CD8beta endow CD8 with efficient coreceptor function, we examined T1.4 T cell hybridomas transfected with various CD8beta constructs. T1.4 hybridomas recognize a photoreactive Plasmodium berghei circumsporozoite (PbCS) peptide derivative (PbCS (4-azidobezoic acid [ABA])) in the context of H-2K(d), and permit assessment of TCR-ligand binding by TCR photoaffinity labeling. We find that the cytoplasmic portion of CD8beta, mainly due to its palmitoylation, mediates partitioning of CD8 in lipid rafts, where it efficiently associates with p56(lck). In addition, the cytoplasmic portion of CD8beta mediates constitutive association of CD8 with TCR/CD3. The resulting TCR-CD8 adducts exhibit high affinity for major histocompatibility complex (MHC)-peptide. Importantly, because CD8alphabeta partitions in rafts, its interaction with TCR/CD3 promotes raft association of TCR/CD3. Engagement of these TCR/CD3-CD8/lck adducts by multimeric MHC-peptide induces activation of p56(lck) in rafts, which in turn phosphorylates CD3 and initiates T cell activation.

The neurobiological basis of prefrontal cortex impairment in the phencyclidine model of schizophrenia : convergent reduction of synaptic glutamate release, energy metabolism and cognitive performance

RÉSUMÉ : Le traitement répété à la phencyclidine (PCP), un bloqueur du récepteur NMDA (NMDAR), reproduit chez les rongeurs une partie de la symptomatologie typique de la schizophrénie. Le blocage prolongé du NMDAR par la PCP mime une hypofunction du NMDAR, une des principales altérations supposées exister dans les cerveaux des patients schizophréniques. Le but de notre étude était d'examiner les conséquences neurochimiques, métaboliques et fonctionnelles du traitement répété à la phencyclidine in vivo, au niveau du cortex préfrontal (cpf), une région cérébrale qui joue un rôle dans les déficits cognitifs observés chez les patients schizophréniques. Pour répondre à cette question, les rats ou les souris ont reçu chaque jour une injection soit de PCP (5 mg/kg), soit de solution saline, pendant 7 ou 14 jours. Les animaux ont ensuite été sacrifiés au moins 24 heures après le dernier traitement. Des tranches aiguës du cpf ont été préparées rapidement, puis stimulées avec une concentration élevée de KCI, de manière à induire une libération de glutamate à partir des terminaisons synaptiques excitatrices. Les résultats montrent que les tranches du cpf des animaux traités à la PCP ont libéré une quantité de glutamate significativement inférieure par rapport à celles des animaux contrôle. Ce déficit de libération a persisté 72 heures après la fin du traitement, tandis qu'il n'était pas observé dans le cortex visuel primaire, une autre région corticale. En outre, le traitement avec des antipsychotiques, l'halopéridol ou l'olanzapine, a supprimé le déficit induit par la PCP. Le même déficit de libération a été remarqué sur des synaptosomes obtenus à partir du cpf des animaux traités à la phenryclidine. Cette observation indique que la PCP induit une modification plastique adaptative du mécanisme qui contrôle la libération du glutamate dans les terminaisons synaptiques. Nous avons découvert que cette modification implique la sous-régulation d'un NMDAR présynaptique, qui serait doué d'un rôle d'autorécepteur stimulateur de la libération du glutamate. Grâce à des tests comportementaux conduits en parallèle et réalisés pour évaluer la fonctionnalité du cpf, nous avons observé chez les souris traitées à la PCP une flexibilité comportementale réduite lors d'un test de discrimination de stimuli visuels/tactiles. Le déficit cognitif était encore présent 4 jours après la dernière administration de PCP. La technique de l'autoradiographie quantitative du [14C]2-deoxyglucose a permis d'associer ce déficit à une réduction de l'activité métabolique cérébrale pendant le déroulement du test, particulièrement au niveau du cpf. Dans l'ensemble, nos résultats suggèrent que le blocage prolongé du NMDAR lors de l'administration répétée de PCP produit un déficit de libération du glutamate au niveau des terminaisons synaptiques excitatrices du cpf. Un tel déficit pourrait être provoqué par la sousrégulation d'un NMDAR présynaptique, qui aurait une fonction de stimulateur de libération; la transmission excitatrice du cpf s'en trouverait dans ce cas réduite. Ce résultat est en ligne avec l'activité métabolique et fonctionnelle réduite du cpf et l'observation de déficits cognitifs induits lors de l'administration de la PCP. ABSTRACT : Sub-chronic treatment with phencyclidine (PCP), an NMDA receptor (NMDAR) channel blocker, reproduces in rodents part of the symptomatology associated to schizophrenia in humans. Prolonged pharmacological blockade of NMDAR with PCP mimics NMDAR hypofunction, one of the main alterations thought to take place in the brains of schizophrenics. Our study was aimed at investigating the neurochemical, metabolic and behavioral consequences of repeated PCP administration in vivo, focusing on the functioning of the prefrontal cortex (pfc), a brain region highly relevant for the cognitive deficits observed in schizophrenic patients. Rats or mice received a daily administration of either PCP (5 mg/kg) or saline for 7 or 14 days. At least 24 hours after the last treatment the animals were sacrificed. Acute slices of the pfc were quickly prepared and challenged with high KCl to induce synaptic glutamate release. Pfc slices from PCP-treated animals released significantly less glutamate than slices from salinetreated animals. The deficit persisted 72 hours after the end of the treatment, while it was not observed in another cortical region: the primary visual cortex. Interestingly, treatment with antipsychotic drugs, either haloperidol or olanzapine, reverted the glutamate release defect induced by PCP treatment. The same release defect was observed in synaptosomes prepared from the pfc of PCP-treated animals, indicating that PCP induces a plastic adaptive change in the mechanism controlling glutamate release in the glutamatergic terminals. We discovered that such change most likely involves the down-regulation of a newly identified, pre-synaptic NMDAR with stimulatory auto-receptor function on glutamate release. In parallel sets of behavioral experiments challenging pfc function, mice sub-chronically treated with PCP displayed reduced behavioral flexibility (reversal learning) in a visual/tactile-cued discrimination task. The cognitive deficit was still evident 4 days after the last PCP administration and was associated to reduced brain metabolic activity during the performance of the behavioral task, notably in the pfc, as determined by [14C]2-deoxyglucose quantitative autoradiography. Clverall, our findings suggest that prolonged NMDAR blockade by repeated PCP administration results in a defect of glutamate release from excitatory afferents in the pfc, possibly ascribed to down-regulation of apre-synaptic stimulatory NMDAR. Deficient excitatory neurotransmission in the pfc is consistent with the reduced metabolic and functional activation of this area and the observed PCP-induced cognitive deficits.

Control of pancreatic β-cell mass and function by gluco-incretin hormones : identification of novel regulatory mechanisms for the treatment of diabetes

Summary : Control of pancreatic ß-cell mass and function by gluco-incretin hormones: Identification of novel regulatory mechanisms for the treatment of diabetes The ß-cells of islets of Langerhans secrete insulin to reduce hyperglycemia. The number of pancreatic islet ß-cells and their capacity to secrete insulin is modulated in normal physiological conditions to respond to the metabolic demand of the organism. A failure of the endocrine pancreas to maintain an adequate insulin secretory capacity due to a reduced ß-cell number and function underlies the pathogenesis of both type 1 and type 2 diabetes. The molecular mechanisms controlling the glucose competence of mature ß-cells, i.e., the magnitude of their insulin secretion response to glucose, ß-cell replication, their differentiation from precursor cells and protection against apoptosis are poorly understood. To investigate these mechanisms, we studied the effects on ß-cells of the gluco-incretin hormones, glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) which are secreted by intestinal endocrine cells after food intake. Besides acutely potentiating glucose-stimulated insulin secretion, these hormones induce ß-cell differentiation from precursor cells, stimulate mature ß-cell replication, and protect them against apoptosis. Therefore, understanding the molecular basis for gluco-incretin action may lead to the uncovering of novel ß-cell regulatory events with potential application for the treatment or prevention of diabetes. Islets from mice with inactivation of both GIP and GLP-1 receptor genes (dK0) present a defect in glucose-induced insulin secretion and are more sensitive than control islets to cytokine-induced apoptosis. To search for regulatory genes, that may control both glucose competence and protection against apoptosis, we performed comparative transcriptomic analysis of islets from control and dK0 mice. We found a strong down-regulation of the IGF1 Rexpression in dK0 islets. We demonstrated in both a mouse insulin-secreting cell line and primary islets, that GLP-1 stimulated IGF-1R expression and signaling. Importantly, GLP-1induced IGF-1R-dependent Akt phosphorylation required active secretion, indicating the presence of an autocrine activation mechanism. We further showed that activation of IGF-1R signaling was dependent on the secretion of IGF-2 and IGF-2 expression was regulated by nutrients. Finally, we demonstrated that the IGF-Z/IGF-1R autocrine loop was required for GLP-1 i) to protect ß-cells against cytokine-induced apoptosis, ii) to enhance their glucose competence and iii) to increase ß-cell proliferation. Résumé : Contrôle de la masse des cellules ß pancréatiques et de leur fonction par les hormones glucoincrétines: Identification de nouveaux mécanismes régulateurs pour le traitement du diabète Les cellules ß des îlots de Langerhans sécrètent l'insuline pour diminuer l'hyperglycémie. Le nombre de cellules ß et leur capacité à sécréter l'insuline sont modulés dans les conditions physiologiques normales pour répondre à la demande métabolique de l'organisme. Un échec du pancréas endocrine à maintenir sa capacité sécrétoire d'insuline dû à une diminution du nombre et de la fonction des cellules ß conduit au diabète de type 1 et de type 2. Les mécanismes moléculaires contrôlant la compétence au glucose des cellules ß matures, tels que, l'augmentation de la sécrétion d'insuline en réponse au glucose, la réplication des cellules ß, leur différentiation à partir de cellules précurseurs et la protection contre l'apoptose sont encore peu connus. Afin d'examiner ces mécanismes, nous avons étudié les effets sur les cellules ß des hormones gluco-incrétines, glucose-dépendent insulinotropic polypeptide (G1P) et glucagon-like peptide-1 (GLP-1) qui sont sécrétées par les cellules endocrines de l'intestin après la prise alimentaire. En plus de potentialiser la sécrétion d'insuline induite par le glucose, ces hormones induisent la différentiation de cellules ß à partir de cellules précurseurs, stimulent leur prolifération et les protègent contre l'apoptose. Par conséquent, comprendre les mécanismes d'action des gluco-incrétines permettrait de découvrir de nouveaux processus régulant les cellules ß avec d'éventuelles applications dans le traitement ou la prévention du diabète. Les îlots de souris ayant une double inactivation des gènes pour les récepteurs du GIP et du GLP-1 (dK0) présentent un défaut de sécrétion d'insuline stimulée par le glucose et une sensibilité accrue à l'apoptose induite par les cytokines. Afin de déterminer les gènes régulés, qui pourraient contrôler à la fois la compétence au glucose et la protection contre l'apoptose, nous avons effectué une analyse comparative transcriptomique sur des îlots de souris contrôles et dKO. Nous avons constaté une forte diminution de l'expression d'IGF-1R dans les îlots dKO. Nous avons démontré, à la fois dans une lignée cellulaire murine sécrétant l'insuline et dans îlots primaires, que le GLP-1 stimulait l'expression d'IGF-1R et sa voie de signalisation. Par ailleurs, la phosphorylation d'Akt dépendante d'IGF1-R induite parle GLP-1 nécessite une sécrétion active, indiquant la présence d'un mécanisme d'activation autocrine. Nous avons ensuite montré que l'activation de la voie de signalisation d'IGF-1R était dépendante de la sécrétion d'IGF-2, dont l'expression est régulée par les nutriments. Finalement, nous avons démontré que la boucle autocrine IGF-2/IGF-1R est nécessaire pour le GLP-1 i) pour protéger les cellules ß contre l'apoptose induite par les cytokines, ii) pour améliorer la compétence au glucose et iii) pour augmenter la prolifération des cellules ß. Résumé tout public : Contrôle de la masse des cellules ß pancréatiques et de leur fonction par les hormones gluco-incrétines: Identification de nouveaux mécanismes régulateurs pour le traitement du diabète Chez les mammifères, la concentration de glucose sanguine (glycémie) est régulée et maintenue à une valeur relativement constante d'environ 5 mM. Cette régulation est principalement contrôlée par 2 hormones produites par les îlots pancréatiques de Langerhans: l'insuline sécrétée par les cellules ß et le glucagon sécrété par les cellules a. A la suite d'un repas, l'augmentation de la glycémie entraîne la sécrétion d'insuline ce qui permet le stockage du glucose dans le foie, les muscles et le tissu adipeux afin de diminuer le taux de glucose circulant. Lors d'un jeûne, la diminution de la glycémie permet la sécrétion de glucagon favorisant alors la production de glucose par le foie, normalisant ainsi la glycémie. Le nombre de cellules ß et leur capacité sécrétoire s'adaptent aux variations de la demande métabolique pour assurer une normoglycémie. Une destruction complète ou partielle des cellules ß conduit respectivement au diabète de type 1 et de type 2. Bien que l'augmentation de la glycémie soit le facteur stimulant de la sécrétion d'insuline, des hormones gluco-incrétines, principalement le GLP-1 (glucagon-like peptide-1) et le GIP (glucose-dependent insulinotropic polypeptide) sont libérées par l'intestin en réponse aux nutriments (glucose, acides gras) et agissent au niveau des cellules ß, potentialisant la sécrétion d'insuline induite par le glucose, stimulant leur prolifération, induisant la différentiation de cellules précurseurs en cellules ß matures et les protègent contre la mort cellulaire (apoptose). Afin d'étudier plus en détail ces mécanismes, nous avons généré des souris déficientes pour les récepteurs du GIP et du GLP-l. Les îlots pancréatiques de ces souris présentent un défaut de sécrétion d'insuline stimulée par le glucose et une sensibilité accrue à l'apoptose par rapport aux îlots de souris contrôles. Nous avons donc cherché les gènes régulés pas ces hormones contrôlant la sécrétion d'insuline et la protection contre l'apoptose. Nous avons constaté une forte diminution de l'expression du récepteur à l'IGF-1 (IGF-1R) dans les îlots de souris déficientes pour les récepteurs des gluco-incrétines. Nous avons démontré dans un model de cellules ß en culture et d'îlots que le GLP-1 augmentait l'expression d'IGF-1R et la sécrétion de son ligand (IGF-2) permettant l'activation de la voie de signalisation. Finalement, nous avons montré que l'activation de la boucle IGF-2/IGF-1R induite par le GLP-1 était nécessaire pour la protection contre l'apoptose, l'augmentation de la sécrétion et la prolifération des cellules ß.