Der Cortex von Säugetieren ist der Hirnbereich, der fundamental für höhere kognitive Funktionen wie Lernen, Gedächtnis, Aufmerksamkeit und komplexes Denken ist. Die Entwicklung des Cortex wird von neuralen Vorläuferzellen gesteuert, die schnell proliferieren, um ihren Pool zu expandieren, bevor sie zu differenzierenden Zellteilungen wechseln, um alle Neuronen zu generieren, aus denen der reife sechs schichtige Neokortex besteht. Der schrittweise Wechsel von Selbsterneuerung zu Neurogenese ist ein zeitlich regulierter Prozess, dessen Fehler schwere lebenslange kognitive Erkrankungen verursachen können. Aus diesem Grund ist es enorm wichtig zu verstehen, welche Faktoren die Schicksalsentscheidung der neuralen Vorläuferzellen regulieren. In den letzten zwei Jahrzehnten haben mehrere Studien die Wichtigkeit von nicht-kodierenden RNAs, wie lange nicht-kodierende und micro RNAs, für diese zeitliche Regulierung hervorgehoben. Mithilfe der Generierung einer kombinatorischen RFP/GFP Reporter Mauslinie, die die Isolierung von proliferierenden und differenzierenden Vorläuferzellen und neugeborenen Neuronen erlaubt, wurde berichtet, dass die lange nicht-kodierende RNA Miat als ein Regulator des neuralen Vorläuferzellen-Schicksals mittels Spleißen fungiert. Die Arbeit dieser Thesis zeigt, dass die Überexpression von Miat den Wechsel der neuralen Vorläuferzellen von proliferierenden zu neurogenen Zellteilungen verzögert und etabliert eine Strategie, um Miat-gespleißte Ziele auf Einzelpopulationslevel während der Corticogenese zu entdecken. Außerdem wurde die doppelte Reporter Mauslinie genutzt, um einen umfassenden und kompletten Katalog von micro RNAs, die in neuralen Vorläuferzellen und Neuronen exprimiert sind, zu erstellen. Dies führte zur Identifizierung von miR-486-5p als ein neuer Regulator der neuralen Vorläuferzellen-Schicksalsentscheidung.

Spinal muscular atrophy (SMA) is an inherited neuromuscular disorder, which causes dysfunction/loss of lower motor neurons and muscle weakness as well as atrophy. While SMA is primarily considered as a motor neuron disease, recent data suggests that survival motor neuron (SMN) deficiency in muscle causes intrinsic defects. We systematically profiled secreted proteins from control and SMN deficient muscle cells with two combined metabolic labeling methods and mass spectrometry. From the screening, we found lower levels of C1q/TNF-related protein 3 (CTRP3) in the SMA muscle secretome and confirmed that CTRP3 levels are indeed reduced in muscle tissues and serum of an SMA mouse model. We identified that CTRP3 regulates neuronal protein synthesis including SMN via mTOR pathway. Furthermore, CTRP3 enhances axonal outgrowth and protein synthesis rate, which are well-known impaired processes in SMA motor neurons. Our data revealed a new molecular mechanism by which muscles regulate the physiology of motor neurons via secreted molecules. Dysregulation of this mechanism contributes to the pathophysiology of SMA.

La compréhension des mécanismes impliqués dans les cas sains, les maladies neurodégénératives ainsi que le développement de nouvelles approches thérapeutiques repose sur l’utilisation de modèles expérimentaux pertinents et de techniques d’imagerie adaptées. Dans ce contexte, la microscopie virtuelle offre la possibilité unique d’analyser ces modèles à l’échelle cellulaire avec une très grande variété de marquages histologiques. Mon projet de thèse consiste à mettre en place et à appliquer une méthode d’analyse d’images histologiques en couleur permettant de segmenter et de synthétiser l’information relative aux neurones à l’aide de l’anticorps NeuN sur des coupes de cerveau de macaque. Dans ce travail, nous appliquons d’abord la méthode de Random Forest (RF) pour segmenter les neurones ainsi que le tissu et le fond. Ensuite, nous proposons une méthode originale pour séparer les neurones qui sont accolés afin de les individualiser. Cette méthode s’adapte à l’ensemble des neurones présentant une taille variable (diamètre variant entre 5 et 30 μm). Elle est également efficace non seulement pour des régions dites « simples » caractérisées par une faible densité de neurones mais aussi pour des régions dites « complexes » caractérisées par une très forte densité de plusieurs milliers de neurones. Le travail suivant se concentre sur la création de cartes paramétriques synthétisant la morphologie et la distribution des neurones individualisés. Pour cela, un changement d’échelle est mis en œuvre afin de produire des cartographies présentant des résolutions spatiales plus faibles (résolution originale de 0,22 μm et cartographies créées proposant une résolution spatiale adaptative de quelques dizaines à quelques centaines de micromètres). Plusieurs dizaines de paramètres morphologiques (rayon moyen, surface, orientation, etc.) sont d’abord calculés pour chaque neurone ainsi que des paramètres colorimétriques. Ensuite, il est possible de synthétiser ces informations sous la forme de cartes paramétriques à plus basse résolution à l’échelle de régions anatomiques, de coupes voire, à terme, de cerveaux entiers. Cette étape transforme des images microscopiques qualitatives couleur en images mésoscopiques quantitatives, plus informatives et plus simples à analyser. Ce travail permet d’analyser statistiquement de très grands volumes de données, de synthétiser l’information sous la forme de cartographies quantitatives, d’analyser des problèmes extrêmement complexes tels que la mort neuronale et à terme de tester de nouveaux médicaments voire de confronter ces informations acquises post mortem avec des données acquises in vivo. / Understanding the mechanisms involved in healthy cases, neurodegenerative diseases and the development of new therapeutic approaches is based on the use of relevant experimental models and appropriate imaging techniques. In this context, virtual microscopy offers the unique possibility of analyzing these models at a cellular scale with a very wide variety of histological markers. My thesis project consists in carrying out and applying a method of analyzing colored histological images that can segment and synthesize information corresponding to neurons using the NeuN antibody on sections of the macaque brain. In this work, we first apply the Random Forest (RF) method to segment neurons as well as tissue and background. Then, we propose an original method to separate the touching or overlapping neurons in order to individualize them. This method is adapted to process neurons presenting a variable size (diameter varying between 5 and 30 μm). It is also effective not only for so-called "simple" regions characterized by a low density of neurons but also for so-called "complex" regions characterized by a very high density of several thousands of neurons. The next work focuses on the creation of parametric maps synthesizing the morphology and distribution of individualized neurons. For this purpose, a multiscale approach is implemented in order to produce maps with lower spatial resolutions (0.22 μm original resolution and created maps offering adaptive spatial resolution from a few dozens to a few hundred of micrometers). Several dozens of morphological parameters (mean radius, surface, orientation, etc.) are first computed as well as colorimetric parameters. Then, it is possible to synthesize this information in the form of lower-resolution parametric maps at the level of anatomical regions, sections and even, eventually, the entire brains. This step transforms qualitative color microscopic images to quantitative mesoscopic images, more informative and easier to analyze. This work makes it possible to statistically analyze very large volumes of data, to synthesize information in the form of quantitative maps, to analyze extremely complex problems such as neuronal death, to test new drugs and to compare this acquired information post mortem with data acquired in vivo.

No description available.

Intrazelluläre Protein- und RNA-Lokalisation ist ein lebenswichtiger molekularer Mechanismus. Ihm unterliegen sowohl die äußere Gestaltung der Zellform, Zellagilität, zelluläre Differenzierung sowie die intra- sowie interzelluläre Kommunikation. Diverse Krankheiten werden mit Fehlfunktionen des intrazellulären Molekültransportes assoziiert und es existieren unzählige Beispiele für bekannte Wege des intrazellulären Protein- und RNA-Transportes. Allerdings ist die globale Komposition lokaler Protein- und RNA-Reservoirs bisher kaum wissenschaftlich erforscht worden. In dieser Studie beschreibe ich die Protein- sowie RNA-Kompositionen subzellulärer Fraktionen zweier neuronaler Zelltypen. Die Neuriten und Somata von Neuroblastoma-Zellen (N1E-115) und Ascl1 induzierten Neuronen (beides Mauszellen) wurden mechanisch voneinander separiert und mittels RNA-Sequenzierung und Massenspektrometrie auf ihre Bestandteile untersucht. Die Verteilung von mRNAs korreliert signifikant mit der Verteilung der entsprechenden Proteine in Ascl1-iNs während in der Neuroblastoma Zelllinie N1E-115 kein solcher Trend nachgewiesen werden konnte. Der Vergleich zu Datensätzen von anderen Zellsystemen und Methoden zeigt, dass das lokale Proteom sowie das lokale Transkriptome und Translatome stark Zelltyp spezifisch ist. Um den Einfluss lokaler Proteinbiosynthese auf die Komposition subzellulärer Proteinpools zu erheben, habe ich die Lokalisation neu synthetisierter Proteine untersucht. Es scheint, als sei die RNA-Lokalisation und lokale Translation von hoher Relevanz für die Protein-Lokalisation in diesen stark polarisierten Zellsystemen. Des Weiteren stelle ich eine Methode vor, um de novo „zip codes“ in diesen neuronalen Zellsystemen zu identifizieren. Diese könnte ein elementar wichtiger Schritt sein, um Fehlfunktionen im interzellulären Molekültransport zu verstehen. / Intracellular protein and RNA localization is one of the mayor players in the formation of cell shape, enabling cell agility, cellular differentiation and cell signaling. Various diseases are associated with malfunctions of intracellular molecule transport. There are many known pathways of how and why proteins and RNAs are transported within the cell and where they are located, though there is not much known about the global distribution of proteins and RNAs within the cell. In this study I apply a subcellular fractionation method coupled to multiple omics approaches to investigate the global distribution of mRNAs, noncoding RNAs and proteins in neuronal cells. Neurites and soma from mouse neuroblastoma cells (N1E-115) as well as from Ascl1 induced neurons (Ascl1-iNs) were isolated and the composition of the spatial proteome and transcriptome was examined. The localization of mRNAs correlates significantly with the localization of their corresponding protein products in Ascl1-iNs whereas it does not in the mouse neuroblastoma cell line N1E-115. Comparing these datasets with recently published data of other cell lines and methods it is clear, that the local proteome, transcriptome and translatome of neuronal cells is highly cell type specific. To investigate how spatial protein pools are established I analyzed local pools of newly synthesized proteins revealing that many proteins are synthesized on the spot. RNA localization therefore plays a crucial role in generating local protein pools in these highly polarized cell systems. Additionally, I propose a method to identify on a global scale de novo “zip codes” in these cell systems which would be a great step towards understanding malfunctions in molecule transport.

Redes neurais pulsadas - redes que utilizam uma codificação temporal da informação - têm despontado como uma nova e promissora abordagem dentro do paradigma conexionista emergente da ciência cognitiva. Um desses novos modelos é a rede neural pulsada de base radial, capaz de armazenar informação nos tempos de atraso axonais dos neurônios e que comporta algoritmos explícitos de treinamento. A recente proposição de uma sistemática para a codificação temporal dos dados de entrada utilizando campos receptivos gaussianos tem apresentado interessantes resultados na tarefa do agrupamento de dados (clustering). Este trabalho propõe uma função para o aprendizado não supervisionado dessa rede, com o objetivo de simplificar a sistemática de calibração de alguns dos seus parâmetros-chave, aprimorando a convergência da rede neural pulsada no aprendizado baseado em instâncias. O desempenho desse modelo é avaliado na tarefa de classificação de padrões, particularmente na classificação de pixels em imagens coloridas no domínio da visão computacional. / Pulsed neural networks - networks that encode information in the timing of spikes - have been studied as a new and promising approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Recently, a new method for encoding input-data by population code using gaussian receptive fields has showed interesting results in the clustering task. The present work proposes a function for the unsupervised learning task in this network, which goal includes the simplification of the calibration of the network key parameters and the enhancement of the pulsed neural network convergence to instance based learning. The performance of this model is evaluated for pattern classification, particularly for the pixel colors classification task, in the computer vision domain.

Esclerose lateral amiotrófica (ELA) é uma doença neurológica progressiva e fatal, caracterizada por perda dos neurônios motores, levando à fraqueza muscular global. As funções sensitivas e mentais são preservadas durante todo o curso da doença. A esclerose lateral amiotrófica tem uma prevalência de 6 por 100.000 pessoas e o início da doença é geralmente entre os 40 a 60 anos de idade. O prognóstico é reservado e em média os pacientes vivem de 3 a 5 anos após o diagnóstico médico. Com a progressão da doença outros sintomas surgem como fraqueza dos membros, comprometimento da fala, aumento da salivação, dificuldades de deglutição, dificuldades para deambular e fadiga muscular. As alterações dos músculos respiratórios levam à falência respiratória, que é a maior causa de óbito nos pacientes com esclerose lateral amiotrófica. Fadiga é definida como a queda da máxima contração isométrica voluntária e falta de tolerância do músculo sob esforço. A máxima contração isométrica voluntária depende de uma cadeia de eventos que se inicia no córtex motor - condutor excitatório dos neurônios motores superior e inferior, e se continua na transmissão pela junção neuromuscular, no acoplamento excitação-contração e na contração da fibra muscular que depende de um suprimento energético metabólico. A fadiga muscular ocorre em pacientes com esclerose lateral amiotrófica prejudicando a função e a qualidade de vida dos pacientes. O objetivo deste trabalho foi: 1) Quantificar a freqüência da fadiga na esclerose lateral amiotrófica; 2) Analisar a evolução da fadiga nos pacientes; 3) Correlacionar a presença da fadiga com fatores como a funcionalidade, a qualidade de vida, a depressão, a dispnéia, e a sonolência, idade e duração da doença em meses. O grupo controle compôs-se de 60 indivíduos (familiares de funcionários do hospital e da equipe multidisciplinar) que não apresentavam história de doenças pregressas. O grupo teste constitui-se de 60 pacientes com diagnóstico de esclerose lateral amiotrófica. O diagnóstico foi realizado por dois neurologistas independentes e baseou-se na presença de história clínica, exame neurológico e estudos neurofisiológicos compatíveis com esclerose lateral amiotrófica, segundo os critérios de El Escorial da Federação Mundial de Neurologia; além disso, houve a investigação complementar por meio de testes hematológicos, bioquímicos, sorológicos, genéticos e radiológicos para excluir outras patologias. Os pacientes dos grupos controle e teste foram entrevistados pela pesquisadora para aplicação de questionários com escalas para verificação da presença de funcionalidade, de qualidade de vida, de depressão, de dispnéia, de sonolência e de fadiga; e os pacientes do grupo teste foram submetidos à avaliação fisioterapêutica no início do estudo e a cada 3 meses, totalizando 12 meses de coletas. O grupo teste apresentou fadiga significantemente maior em relação ao grupo controle, bem como alterações nos questionários de funcionalidade, de qualidade de vida, de depressão, de dispnéia e de sonolência. Percebeu-se que a fadiga foi evolutiva durante os meses de acompanhamento da pesquisa. A fadiga correlacionou-se com a idade, mostrando que os pacientes mais jovens apresentaram maior grau de fadiga que os pacientes mais idosos. Os resultados desta pesquisa sugerem que a fadiga é um dos problemas que afetam os pacientes com ELA; o fato de não ter correlação com outros problemas estudados sugere que a fadiga deve merecer pesquisa e tratamento individualizados no paciente com ELA, principalmente pelo fato de que os resultados sugeriram piora da fadiga no decorrer da evolução da ELA / Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurological disease, characterized by loss of the motor neurons, taking to the global muscular weakness. The sensitive and mental functions are preserved during whole the course of the disease. The ALS has a prevalence of 6 for 100.000 people and the beginning of the disease is usually among the 40 to 60 years of age. The prognostic is reserved and on average the patients live from 3 to 5 years after the medical diagnosis. With the progression of the disease other symptoms they appear as weakness of the members, compromising of the speech, increase of the salivation, deglutition difficulties, difficulties to stroll and it fatigues muscular. The alterations of the breathing muscles take to the breathing bankruptcy, that is the largest death cause in the patients with ALS. Fatigue is defined as the fall of the maxim voluntary isometric contraction and lack of tolerance of the muscle under effort. The maxim voluntary isometric contraction depends on a chain of events that begins in the motor cortex - driver excitatory of the neurons motor superior and inferior, and it is continued in the transmission by the junction neuromuscular, in the joining excitement-contraction and in the contraction of the muscular fiber that depends on a metabolic energy supply. The muscular fatigue happens in patients with ALS harming the function and the quality of the patients\' life. The objective of this work was: 1) to quantify the frequency of the fatigue in the ALS; 2) to analyze the evolution of the fatigue in the patients; 3) to correlate the presence of the fatigue with factors as the functionality, the life quality, the depression, the dispnéa, and the sleepiness, age and duration of the disease in months. The group control was composed of 60 individuals (family of employees of the hospital and of the team multidisciplinar) that didn\'t present history of past diseases. The group test is constituted of 60 patients with diagnosis of ALS. The diagnosis was accomplished by two independent neurologists and he/she based on the presence of clinical history, neurological exam and studies compatible neurophisiologycs with ALS, according to the criteria of El Escorial of the World Federation of Neurology; besides, there was the complement investigation through tests and exams to exclude other pathologies. The patients of the groups control and test were interviewed by the researcher for application of questionnaires with scales for verification of the functionality presence, of life quality, of depression, of dispnéa, of sleepiness and of fatigue; and the patients of the group test they were submitted to the evaluation physiotherapy in the beginning of the study and every 3 months, totaling 12 months of collections. The group test presented fatigue larger significantly in relation to the group it controls, as well as alterations in the functionality questionnaires, of life quality, of depression, of dispnéa and of sleepiness. It was noticed that the fatigue was evolutionary during the months of accompaniment of the research. The fatigue was correlated with the age, showing that the youngest patients presented larger degree of fatigue than the most senior patients. The results of this research suggest that the fatigue is one of the problems that affect the patients with ALS; the fact of not having correlation with other studied problems suggests that the fatigue should deserve research and treatment individualized in the patient with ALS, mainly for the fact that the results suggested worsening of the fatigue in elapsing of the evolution of the ALS

Neurons can respond to input by firing isolated action potentials or spikes. Sequences of spikes have been linked to the encoding of neuron input. However, many neurons also fire bursts; mechanistically distinct responses consisting of brief high-frequency spike firing. Bursts form separate response symbols but historically have not been thought to encode input. However, recent experimental evidence suggests that bursts can encode input in parallel with tonic spikes. The recognition of bursts as distinct encoding symbols raises important questions; these form the basic aims of this thesis: (1) What inputs do bursts encode? (2) Does burst structure provide extra information about different inputs. (3) Is burst coding robust against the presence of noise; an inherent property of all neural systems? (4) What mechanisms are responsible for burst input encoding? (5) How does burst coding manifest in in-vivo neurons. To answer these questions, bursting is studied using a combination of neuron models and in-vivo hippocampal neuron recordings. Models ranged from neuron-specific cell models to models belonging to three fundamentally different burst dynamic classes (unspecific to any neural region). These classes are defined using concepts from non-linear system theory. Together, analysing these model types with in-vivo recordings provides a specific and general analysis of burst encoding. For neuron-specific and unspecific models, a number of model types expressing different levels of biological realism are analysed. For the study of thalamic encoding, two models containing either a single simplified burst-generating current or multiple currents are used. For models simulating three burst dynamic classes, three further models of different biological complexity are used. The bursts generated by models and real neurons were analysed by assessing the input they encode using methods such as information theory, and reverse correlation. Modelled bursts were also analysed for their resilience to simulated neural noise. In all cases, inputs evoking bursts and tonic spikes were distinct. The structure of burst-evoking input depended on burst dynamic class rather than the biological complexity of models. Different n-spike bursts encoded different inputs that, if read by downstream cells, could discriminate complex input structure. In the thalamus, this n-spike burst code explains informative responses that were not due to tonic spikes. In-vivo hippocampal neurons and a pyramidal cell model both use the n-spike code to mark different LFP features. This n-spike burst may therefore be a general feature of bursting relevant to both model and in-vivo neurons. Bursts can also encode input corrupted by neural noise, often outperforming the encoding of single spikes. Both burst timing and internal structure are informative even when driven by strongly noise-corrupted input. Also, bursts induce input-dependent spike correlations that remain informative despite strong added noise. As a result, bursts endow their constituent spikes with extra information that would be lost if tonic spikes were considered the only informative responses.

Redes neurais pulsadas - redes que utilizam uma codificação temporal da informação - têm despontado como uma nova e promissora abordagem dentro do paradigma conexionista emergente da ciência cognitiva. Um desses novos modelos é a rede neural pulsada de base radial, capaz de armazenar informação nos tempos de atraso axonais dos neurônios e que comporta algoritmos explícitos de treinamento. A recente proposição de uma sistemática para a codificação temporal dos dados de entrada utilizando campos receptivos gaussianos tem apresentado interessantes resultados na tarefa do agrupamento de dados (clustering). Este trabalho propõe uma função para o aprendizado não supervisionado dessa rede, com o objetivo de simplificar a sistemática de calibração de alguns dos seus parâmetros-chave, aprimorando a convergência da rede neural pulsada no aprendizado baseado em instâncias. O desempenho desse modelo é avaliado na tarefa de classificação de padrões, particularmente na classificação de pixels em imagens coloridas no domínio da visão computacional. / Pulsed neural networks - networks that encode information in the timing of spikes - have been studied as a new and promising approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Recently, a new method for encoding input-data by population code using gaussian receptive fields has showed interesting results in the clustering task. The present work proposes a function for the unsupervised learning task in this network, which goal includes the simplification of the calibration of the network key parameters and the enhancement of the pulsed neural network convergence to instance based learning. The performance of this model is evaluated for pattern classification, particularly for the pixel colors classification task, in the computer vision domain.

Cette thèse s'intéresse au développement neuronal in vitro dans le but ultime d'enregistrer l'activité de réseaux de neurones à géométrie et connectivité contrôlées. Le développement neuronal est régi par un ensemble de régulations, intrinsèques mais également sous contrôle de facteurs extérieurs, qui permettent à la cellule d'adhérer à un substrat, de croître, et de se polariser. Une partie de ce travail de thèse explore deux types de contraintes physiques de l'environnement que sont la géométrie d'adhésion et la rugosité de surface. La première révèle l'implication des forces dans les stades précoces de développement neuronal régis par un phénomène de compétition neuritique, et permet in fine de contrôler la direction d'émission de l'axone, notamment par une inhibition de sa différenciation sur lignes ondulées. La seconde montre que la distribution des points d'adhésion peut accélérer la croissance jusqu'à favoriser la polarisation axonale. L'autre partie de ce travail s'attache à résoudre le problème technologique majeur qu'est le remplissage des sites d'adhésion par le biais d'une attraction magnétique, et démontre la possibilité de faire croître des réseaux neuronaux modèles sur nanotransistors. / This thesis focuses on in vitro neuronal development, with the long-term goal of building controlled neuron networks that would allow the recording of their electric activity. A collection of intrinsic regulations are involved in neuronal adhesion, growth and polarization, in such a way that the cell can adapt to changes in its environment. Nevertheless, this environment can affect the behavior of the cell through mechanisms that rely on biophysical signals or even physical properties of this environment. The work presented in this thesis is based on the modification of two main aspects of the physical environment: geometry of adhesion and surface roughness. On the one hand, the geometry is controlled by patterns of adhesions, giving the ability to design bipolar motifs that highligt the importance of mechanical forces in neuronal growth, and also more complex motifs that allow the control of neuronal polarization, in particular by an inhibition of axonal differenciation on curved lines. On the other hand, a roughness below the microscale creates a distribution of adhesion points that results in an increase in neuronal growth rate and even influences axonal polarization. The final part of this thesis focuses on the development of an innovative method for placing cells at precise locations on a substrate, by the help of magnetic traps. This method is the final step required for growing model neuron networks on our nanotransistors.