Oxidative stress is responsible for deficient survival and dendritogenesis in Purkinje neurons from ataxia-telangiectasia mutated mutant mice

Atm gene-disrupted mice recapitulate the majority of characteristics observed in patients with the genetic disorder ataxia-telangiectasia (A-T). However, although they exhibit defects in neuromotor function and a distinct neurological phenotype, they do not show the progressive neurodegeneration seen in human patients, but there is evidence that ataxia-telangiectasia mutated ( Atm)-deficient animals have elevated levels of oxidized macromolecules and some neuropathology. We report here that in vitro survival of cerebellar Purkinje cells from both Atm knock-out and Atm knock-in mice was significantly reduced compared with their wild-type littermates. Although most of the Purkinje neurons from wild-type mice exhibited extensive dendritic elongation and branching under these conditions, most neurons from Atm-deficient mice had dramatically reduced dendritic branching. An antioxidant ( isoindoline nitroxide) prevented Purkinje cell death in Atm-deficient mice and enhanced dendritogenesis to wild-type levels. Furthermore, administration of the antioxidant throughout pregnancy had a small enhancing effect on Purkinje neuron survival in Atm gene-disrupted animals and protected against oxidative stress in older animals. These data provide strong evidence for a defect in the cerebellum of Atm-deficient mice and suggest that oxidative stress contributes to this phenotype.

Genetic disruption of the growth hormone receptor does not influence motoneuron survival in the developing mouse

In the rodent central nervous system (CNS) during the five days prior to birth, both growth hormone (GH) and its receptor (GHR) undergo transient increases in expression to levels considerably higher than those found postnatally. This increase in expression coincides with the period of neuronal programmed cell death (PCD) in the developing CNS. To evaluate the involvement of growth hormone in the process of PCD, we have quantified the number of motoneurons in the spinal cord and brain stem of wild type and littermate GHR-deficient mice at the beginning and end of the neuronal PCD period. We found no change in motoneuron survival in either the brachial or lumbar lateral motor columns of the spinal cord or in the trochlear, trigeminal, facial or hypoglossal nuclei in the brain stem. We also found no significant differences in spinal cord volume, muscle fiber diameter, or body weight of GHR-deficient fetal mice when compared to their littermate controls. Therefore, despite considerable in vitro evidence for GH action on neurons and glia, genetic disruption of GHR signalling has no effect on prenatal motoneuron number in the mouse, under normal physiological conditions. This may be a result of compensation by the signalling of other neurotrophic cytokines.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Identification of neuronal alterations induced by Shank3 mutations using iPS cells from Phelan-McDermid Patients' Fibroblasts

A família de proteínas Shank é o principal conjunto de proteinas de suporte e está localizada na densidade pós-sináptica das sinapses excitatórias. Existem 3 genes na família Shank, Shank1, Shank2 e Shank3 e são caracterizados por múltiplos domínios repetidos de anquirina próximo ao N-terminal seguido pelos domínios Src homologo 3 e PDZ, uma região longa rica em prolina e um domínio de motivo α estéril próximo ao C-terminal. Shank proteínas conectam duas subunidades de receptors glutamatérgicos, recetores NMDA e recetores metabotrópicos de glutamato do tipo-I (mGluRs). O domínio PDZ da Shank conecta-se ao C-terminal do GKAP e este, liga-se, ao complexo recetor PSD-95-NMDA. Por outro lado, a proteína Homer interage com o domínio rico em prolina para confirmar a associação entre a proteína Shank com o mGluR tipo-I. A proteína específica em estudo, Shank3, é haploinsuficiente em pacientes com sindrome Phelan-McDermid devido à deleções no braço comprido do cromossoma 22 levando à danos intelectuais, ausência ou atraso no discurso, comportamentos semelhantes ao autismo, hipotonia e características dismórficas. Neste trabalho, investigamos o papel da Shank3 na função sináptica para compreender a relação entre alterações nesta proteína e as características neurológicas presente em Pacientes com síndrome Phelan-McDermid. Foram utilizados dois modelos diferentes, ratinhos knockout Shank3 e hiPSC de pacientes com PMS. Ratinhos geneticamente modificados são ferramentas uteis no estudo de genes e na compreensão dos mecanismos que experiências in vitro não são capazes de reproduzir, mas de maneira a compreender melhor as patologias humanas, decidimos trabalhar também com células humanas. Os fibroblastos dos pacientes com síndrome Phelan-McDermid fora reprogramados em hiPS cells, diferenciados em neurónios e comparados com os neurónios obtidos a partir de doadores saudavéis e da mesma idade. A reprogramação em iPSC foi realizada por infecção de lentivirus com quatro genes de reprogramação OCT4, c-MYC, SOX2 e KFL4 para posteriormente serem diferenciados em neurónios, com cada passo sendo positivamente confirmado através de marcadores neuronais. Através dos neurónios diferenciados, analisamos a expressão de proteínas sinápticas. Pacientes com haploinsuficiencia na proteína Shank3 apresentam níveis elevados de proteína mGluR5 e decrescidos de proteína Homer sugerindo que a haploinsuficiencia leva a desregulação do complexo mGluR5-Homer-Shank3 conduzindo também, a defeitos na maturação sináptica. Assim, a expressão da proteína mGluR5 está alterada nos pacientes com PMS podendo estar relacionada com defeitos encontrados na diferenciação neuronal e maturação sináptica observados nos neurónios de pacientes. Conclusivamente, iPS cells representam um modelo fundamental no estudo da proteína Shank3 e a sua influência no sindrome de Phelan-McDermid.

Potenciais evocados auditivos de média latência em adultos com epilepsia

Introdução Os potenciais evocados auditivos de média latência (PEAML) reflectem actividade neuronal mesencefáfica, mais precisamente da região tálamo-cortical, dos colículos inferiores e da formação reticular. A epilepsia é caracterizada por variadas manifestações anormais do comportamento cerebral, sendo descrita como uma perturbação da função cerebral, tendo origem numa descarga anómala de um conjunto ou da totalidade dos neurónios do córtice cerebral. Está documentado, que as descargas eléctricas provocadas pelas crises de epilepsia podem levar a perdas neuronais, pelo que poderão existir alterações nos PEAML. Objectivos A escassa existência de literatura sobre o tema e a não investigação na população portuguesa, originou a execução deste estudo, que teve como objectivo investigar e documentar a existência de alterações ou achados nos componentes neuronais de média latência (PEAML), numa amostra de portugueses com epilepsia. Metodologia Foram realizados PEAML a um grupo de controlo (GC) composto por 16 participantes e a um grupo clínico (GCL) de 8 participantes com epilepsia, sendo analisados os componentes Na, Pa e Na-Pa quanto à sua morfologia, latência e amplitude. Resultados A morfologia das ondas e a presença de epilepsia não estão associados, no entanto, contrariamente ao GC que evidenciou latências e amplitudes de Na, Pa e Na-Pa dentro dos padrões de normalidade, a alteração ou ausência de respostas por parte do GCL é significativa na totalidade das medidas investigadas. Conclusão Em epilepsias generalizadas e focais do lobo temporal os PEAML evidenciam alterações, tal achado poderá ser eventualmente justificado pela propagação ascendente e descendente da informação auditiva se encontrar comprometida, devido a sequelas deixadas pelas crises epilépticas nas vias auditivas mesencefálicas. As alterações verificadas foram uma morfologia anómala das ondas ou ausência das mesmas.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Carcinoma neuroendócrino de pequenas células: um estudo de caso em citopatologia ginecológica

O presente estudo reporta o caso de uma mulher de 63 anos da qual a única informação clínica era a suspeita de um sarcoma da cérvix. Simultaneamente à colpocitologia, foram enviadas biópsias do colo e do endométrio para diagnóstico. A visualização da amostra citológica revelou vários agregados de número variável de células monótonas, com tamanho pequeno, formato redondo e citoplasma escasso, num fundo com diátese. Os núcleos apresentavam moldagem, hipercromasia, cromatina “sal-e-pimenta” e ausência de nucléolos. O aspeto microscópico das biópsias foi concordante com os achados citológicos, tendo sido igualmente identificados focos glanduliformes com características atípicas. A neoplasia mostrou expressão imunohistoquímica dos antigénios enolase neurónio-específica (neuron specific enolase, NSE), sinaptofisina e citoqueratina (clones AE1/AE3), e uma elevada atividade proliferativa demonstrada pela imunorreactividade para o marcador nuclear Ki67/Mib1. Os achados citológicos, histológicos e imunohistoquímicos foram consistentes com o diagnóstico de carcinoma neuroendócrino de pequenas células. Dos tumores cervicais, esta neoplasia maligna é das mais raras, mostrando um comportamento muito agressivo, com prognóstico muito pobre, em que as terapêuticas existentes são pouco consensuais quanto à sua eficácia. A sua etiologia ainda é estudada, podendo estar relacionada com a infeção pelo Vírus do Papiloma Humano.

The computational role of short-term plasticity and the balance of excitation and inhibition in neural microcircuits: experimental and theoretical analysis

The computations performed by the brain ultimately rely on the functional connectivity between neurons embedded in complex networks. It is well known that the neuronal connections, the synapses, are plastic, i.e. the contribution of each presynaptic neuron to the firing of a postsynaptic neuron can be independently adjusted. The modulation of effective synaptic strength can occur on time scales that range from tens or hundreds of milliseconds, to tens of minutes or hours, to days, and may involve pre- and/or post-synaptic modifications. The collection of these mechanisms is generally believed to underlie learning and memory and, hence, it is fundamental to understand their consequences in the behavior of neurons.(...)

Atrofia Muscular Espinhal: Análise Descritiva de Uma Série de Casos

Introdução: A Atrofia Muscular Espinhal (AME) é o nome dado a uma doença neuromuscular específica caracterizada pela degeneração dos neurónios motores medulares, condicionando atrofia e fraqueza muscular progressivas. É determinada pela alteração do gene Survival Motor Neuron-1 (SMN1), localizado no braço longo do cromossoma cinco. Uma cópia quase idêntica do gene SMN1, chamada SMN2, modula a gravidade da doença. A AME repercute-se a nível de vários órgãos e sistemas, envolvendo frequentemente os sistemas respiratório, osteoarticular e gastrintestinal. Estão descritos vários subtipos da doença, com base quer na idade do início dos sintomas quer na máxima aquisição motora alcançada. Objectivos: Estudar a população de doentes com o diagnóstico de AME (clínico e/ou genético) seguida na Consulta de Medicina Física e de Reabilitação (CMFR) do Hospital de Dona Estefânia (HDE) em Lisboa, no período de Janeiro de 2007 a Outubro de 2009. Métodos: Estudo retrospectivo com análise de parâmetros sócio-demográficos, clínica, exames complementares de diagnóstico, evolução e complicações da doença. Resultados e Discussão: A casuística é constituída por doze doentes, com idades compreendidas entre os 0 meses e os 21 anos de idade, tendo sete o diagnóstico de AME I, um AME II equatro o diagnóstico de AME tipo III. Verificou-se que a gravidade da doença era inversamente proporcional à idade no início dos sintomas e à função motora máxima atingida pelo indivíduo durante o seu desenvolvimento. Todos os doentes apresentaram infecções respiratórias recorrentes e nos óbitos ocorridos, verificou-se como causa de morte a insuficiência respiratória, complicada de paragem cardio-respiratória. As principais complicações ortopédicas foram o desenvolvimento de contracturas articulares das grandes articulações dos membros inferiores, bem como o desenvolvimento de escoliose. A disfagia foi a principal complicação gastrenterológica. Conclusão: A não aquisição de etapas do desenvolvimento motor está correlacionada com um agravamento do prognóstico funcional e vital.

The role of microRNAs in amyotrophic lateral sclerosis

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

Development of novel human cellular models for neurotoxicity studies

Dissertation to obtain master degree in Genética Molecular e Biomedicina

Cardiac plexus of dogs experimentally infected with Trypanosoma cruzi: inflammatory lesions and quantitative studies

Qualitative and quantitative aspects of the superficial and profound cardiac plexus of dogs experimentally infected with Be-62 and Be-78 strains of Trypanosoma cruzi were studied. Animals were autopsied in the acute phase of infection. The inflammatory process, lesions and number of parasites were more intense and frequent in animals infected with the Be-78 strain than in those infected with Be-62. Despite this, no statistically significant differences could be found between the number of neuron bodies in the ganglia of infected and control dogs.

Coherence and phase locking disruption in electromyograms of patients with amyotrophic lateral sclerosis

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Functional and structural studies of two enzymes: membrane bound kinase and Z-DNA/Z-RNA-binding protein

Dissertação para obtenção do Grau de Doutor em Sistemas de Bioengenharia

Nanostructuring silicon probes via electrodeposition: characterization of electrode coatings for acute in vivo neural recordings

Understanding how the brain works will require tools capable of measuring neuron elec-trical activity at a network scale. However, considerable progress is still necessary to reliably increase the number of neurons that are recorded and identified simultaneously with existing mi-croelectrode arrays. This project aims to evaluate how different materials can modify the effi-ciency of signal transfer from the neural tissue to the electrode. Therefore, various coating materials (gold, PEDOT, tungsten oxide and carbon nano-tubes) are characterized in terms of their underlying electrochemical processes and recording ef-ficacy. Iridium electrodes (177-706 μm2) are coated using galvanostatic deposition under different charge densities. By performing electrochemical impedance spectroscopy in phosphate buffered saline it is determined that the impedance modulus at 1 kHz depends on the coating material and decreased up to a maximum of two orders of magnitude for PEDOT (from 1 MΩ to 25 kΩ). The electrodes are furthermore characterized by cyclic voltammetry showing that charge storage capacity is im-proved by one order of magnitude reaching a maximum of 84.1 mC/cm2 for the PEDOT: gold nanoparticles composite (38 times the capacity of the pristine). Neural recording of spontaneous activity within the cortex was performed in anesthetized rodents to evaluate electrode coating performance.