Bases moléculaires et cellulaires d’un trouble neurodéveloppemental causé par l’haploinsuffisance de SYNGAP1.

La déficience intellectuelle est la cause d’handicap la plus fréquente chez l’enfant. De nombreuses évidences convergent vers l’idée selon laquelle des altérations dans les gènes synaptiques puissent expliquer une fraction significative des affections neurodéveloppementales telles que la déficience intellectuelle ou encore l’autisme. Jusqu’à récemment, la majorité des mutations associées à la déficience intellectuelle a été liée au chromosome X ou à la transmission autosomique récessive. D’un autre côté, plusieurs études récentes suggèrent que des mutations de novo dans des gènes à transmission autosomique dominante, requis dans les processus de la plasticité synaptique peuvent être à la source d’une importante fraction des cas de déficience intellectuelle non syndromique. Par des techniques permettant la capture de l’exome et le séquençage de l’ADN génomique, notre laboratoire a précédemment reporté les premières mutations pathogéniques dans le gène à transmission autosomique dominante SYNGAP1. Ces dernières ont été associées à des troubles comportementaux tels que la déficience intellectuelle, l’inattention, des problèmes d’humeur, d’impulsivité et d’agressions physiques. D’autres patients sont diagnostiqués avec des troubles autistiques et/ou des formes particulières d’épilepsie généralisée. Chez la souris, le knock-out constitutif de Syngap1 (souris Syngap1+/-) résulte en des déficits comme l’hyperactivité locomotrice, une réduction du comportement associée à l’anxiété, une augmentation du réflexe de sursaut, une propension à l’isolation, des problèmes dans le conditionnement à la peur, des troubles dans les mémoires de travail, de référence et social. Ainsi, la souris Syngap1+/- représente un modèle approprié pour l’étude des effets délétères causés par l’haploinsuffisance de SYNGAP1 sur le développement de circuits neuronaux. D’autre part, il est de première importance de statuer si les mutations humaines aboutissent à l’haploinsuffisance de la protéine. SYNGAP1 encode pour une protéine à activité GTPase pour Ras. Son haploinsuffisance entraîne l’augmentation des niveaux d’activité de Ras, de phosphorylation de ERK, cause une morphogenèse anormale des épines dendritiques et un excès dans la concentration des récepteurs AMPA à la membrane postsynaptique des neurones excitateurs. Plusieurs études suggèrent que l’augmentation précoce de l’insertion des récepteurs AMPA au sein des synapses glutamatergiques contribue à certains phénotypes observés chez la souris Syngap1+/-. En revanche, les conséquences de l’haploinsuffisance de SYNGAP1 sur les circuits neuronaux GABAergiques restent inconnues. Les enjeux de mon projet de PhD sont: 1) d’identifier l’impact de mutations humaines dans la fonction de SYNGAP1; 2) de déterminer si SYNGAP1 contribue au développement et à la fonction des circuits GABAergiques; 3) de révéler comment l’haploinsuffisance de Syngap1 restreinte aux circuits GABAergiques affecte le comportement et la cognition. Nous avons publié les premières mutations humaines de type faux-sens dans le gène SYNGAP1 (c.1084T>C [p.W362R]; c.1685C>T [p.P562L]) ainsi que deux nouvelles mutations tronquantes (c.2212_2213del [p.S738X]; c.283dupC [p.H95PfsX5]). Ces dernières sont toutes de novo à l’exception de c.283dupC, héritée d’un père mosaïque pour la même mutation. Dans cette étude, nous avons confirmé que les patients pourvus de mutations dans SYNGAP1 présentent, entre autre, des phénotypes associés à des troubles comportementaux relatifs à la déficience intellectuelle. En culture organotypique, la transfection biolistique de l’ADNc de Syngap1 wild-type dans des cellules pyramidales corticales réduit significativement les niveaux de pERK, en fonction de l’activité neuronale. Au contraire les constructions plasmidiques exprimant les mutations W362R, P562L, ou celle précédemment répertoriée R579X, n’engendre aucun effet significatif sur les niveaux de pERK. Ces résultats suggèrent que ces mutations faux-sens et tronquante résultent en la perte de la fonction de SYNGAP1 ayant fort probablement pour conséquences d’affecter la régulation du développement cérébral. Plusieurs études publiées suggèrent que les déficits cognitifs associés à l’haploinsuffisance de SYNGAP1 peuvent émerger d’altérations dans le développement des neurones excitateurs glutamatergiques. Toutefois, si, et auquel cas, de quelle manière ces mutations affectent le développement des interneurones GABAergiques résultant en un déséquilibre entre l’excitation et l’inhibition et aux déficits cognitifs restent sujet de controverses. Par conséquent, nous avons examiné la contribution de Syngap1 dans le développement des circuits GABAergiques. A cette fin, nous avons généré une souris mutante knockout conditionnelle dans laquelle un allèle de Syngap1 est spécifiquement excisé dans les interneurones GABAergiques issus de l’éminence ganglionnaire médiale (souris Tg(Nkx2.1-Cre);Syngap1flox/+). En culture organotypique, nous avons démontré que la réduction de Syngap1 restreinte aux interneurones inhibiteurs résulte en des altérations au niveau de leur arborisation axonale et dans leur densité synaptique. De plus, réalisés sur des coupes de cerveau de souris Tg(Nkx2.1-Cre);Syngap1flox/+, les enregistrements des courants inhibiteurs postsynaptiques miniatures (mIPSC) ou encore de ceux évoqués au moyen de l’optogénétique (oIPSC) dévoilent une réduction significative de la neurotransmission inhibitrice corticale. Enfin, nous avons comparé les performances de souris jeunes adultes Syngap1+/-, Tg(Nkx2.1-Cre);Syngap1flox/+ à celles de leurs congénères contrôles dans une batterie de tests comportementaux. À l’inverse des souris Syngap1+/-, les souris Tg(Nkx2.1-Cre);Syngap1flox/+ ne présentent pas d’hyperactivité locomotrice, ni de comportement associé à l’anxiété. Cependant, elles démontrent des déficits similaires dans la mémoire de travail et de reconnaissance sociale, suggérant que l’haploinsuffisance de Syngap1 restreinte aux interneurones GABAergiques dérivés de l’éminence ganglionnaire médiale récapitule en partie certains des phénotypes cognitifs observés chez la souris Syngap1+/-. Mes travaux de PhD établissent pour la première fois que les mutations humaines dans le gène SYNGAP1 associés à la déficience intellectuelle causent la perte de fonction de la protéine. Mes études dévoilent, également pour la première fois, l’influence significative de ce gène dans la régulation du développement et de la fonction des interneurones. D’admettre l’atteinte des cellules GABAergiques illustre plus réalistement la complexité de la déficience intellectuelle non syndromique causée par l’haploinsuffisance de SYNGAP1. Ainsi, seule une compréhension raffinée de cette condition neurodéveloppementale pourra mener à une approche thérapeutique adéquate.

Characterization of Probability Distributions by Variance Bounds and its Applications

Department of Statistics, Cochin University of Science and Technology

Queueing Models with Vacations and Working Vacations

The thesis entitled “Queueing Models with Vacations and Working Vacations" consists of seven chapters including the introductory chapter. In chapters 2 to 7 we analyze different queueing models highlighting the role played by vacations and working vacations. The duration of vacation is exponentially distributed in all these models and multiple vacation policy is followed.In chapter 2 we discuss an M/M/2 queueing system with heterogeneous servers, one of which is always available while the other goes on vacation in the absence of customers waiting for service. Conditional stochastic decomposition of queue length is derived. An illustrative example is provided to study the effect of the input parameters on the system performance measures. Chapter 3 considers a similar setup as chapter 2. The model is analyzed in essentially the same way as in chapter 2 and a numerical example is provided to bring out the qualitative nature of the model. The MAP is a tractable class of point process which is in general nonrenewal. In spite of its versatility it is highly tractable as well. Phase type distributions are ideally suited for applying matrix analytic methods. In all the remaining chapters we assume the arrival process to be MAP and service process to be phase type. In chapter 4 we consider a MAP/PH/1 queue with working vacations. At a departure epoch, the server finding the system empty, takes a vacation. A customer arriving during a vacation will be served but at a lower rate.Chapter 5 discusses a MAP/PH/1 retrial queueing system with working vacations.In chapter 6 the setup of the model is similar to that of chapter 5. The signicant dierence in this model is that there is a nite buer for arrivals.Chapter 7 considers an MMAP(2)/PH/1 queueing model with a nite retrial group

Design And Development Of A Named Entity Based Question Answering System For Malayalam Language

This is a Named Entity Based Question Answering System for Malayalam Language. Although a vast amount of information is available today in digital form, no effective information access mechanism exists to provide humans with convenient information access. Information Retrieval and Question Answering systems are the two mechanisms available now for information access. Information systems typically return a long list of documents in response to a user’s query which are to be skimmed by the user to determine whether they contain an answer. But a Question Answering System allows the user to state his/her information need as a natural language question and receives most appropriate answer in a word or a sentence or a paragraph. This system is based on Named Entity Tagging and Question Classification. Document tagging extracts useful information from the documents which will be used in finding the answer to the question. Question Classification extracts useful information from the question to determine the type of the question and the way in which the question is to be answered. Various Machine Learning methods are used to tag the documents. Rule-Based Approach is used for Question Classification. Malayalam belongs to the Dravidian family of languages and is one of the four major languages of this family. It is one of the 22 Scheduled Languages of India with official language status in the state of Kerala. It is spoken by 40 million people. Malayalam is a morphologically rich agglutinative language and relatively of free word order. Also Malayalam has a productive morphology that allows the creation of complex words which are often highly ambiguous. Document tagging tools such as Parts-of-Speech Tagger, Phrase Chunker, Named Entity Tagger, and Compound Word Splitter are developed as a part of this research work. No such tools were available for Malayalam language. Finite State Transducer, High Order Conditional Random Field, Artificial Immunity System Principles, and Support Vector Machines are the techniques used for the design of these document preprocessing tools. This research work describes how the Named Entity is used to represent the documents. Single sentence questions are used to test the system. Overall Precision and Recall obtained are 88.5% and 85.9% respectively. This work can be extended in several directions. The coverage of non-factoid questions can be increased and also it can be extended to include open domain applications. Reference Resolution and Word Sense Disambiguation techniques are suggested as the future enhancements

Queueing Models with Vacations and Working Vacations

The objective of the study of \Queueing models with vacations and working vacations" was two fold; to minimize the server idle time and improve the e ciency of the service system. Keeping this in mind we considered queueing models in di erent set up in this thesis. Chapter 1 introduced the concepts and techniques used in the thesis and also provided a summary of the work done. In chapter 2 we considered an M=M=2 queueing model, where one of the two heterogeneous servers takes multiple vacations. We studied the performance of the system with the help of busy period analysis and computation of mean waiting time of a customer in the stationary regime. Conditional stochastic decomposition of queue length was derived. To improve the e ciency of this system we came up with a modi ed model in chapter 3. In this model the vacationing server attends the customers, during vacation at a slower service rate. Chapter 4 analyzed a working vacation queueing model in a more general set up. The introduction of N policy makes this MAP=PH=1 model di erent from all working vacation models available in the literature. A detailed analysis of performance of the model was provided with the help of computation of measures such as mean waiting time of a customer who gets service in normal mode and vacation mode.

Product autoregressive models for non-negative variables

When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt = Xα t−1Vt , 0 ≤ α < 1, t = 1, 2, . . . may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution

Analysis of Stochastic Volatility Sequences Generated by Product Autoregressive Models

The classical methods of analysing time series by Box-Jenkins approach assume that the observed series uctuates around changing levels with constant variance. That is, the time series is assumed to be of homoscedastic nature. However, the nancial time series exhibits the presence of heteroscedasticity in the sense that, it possesses non-constant conditional variance given the past observations. So, the analysis of nancial time series, requires the modelling of such variances, which may depend on some time dependent factors or its own past values. This lead to introduction of several classes of models to study the behaviour of nancial time series. See Taylor (1986), Tsay (2005), Rachev et al. (2007). The class of models, used to describe the evolution of conditional variances is referred to as stochastic volatility modelsThe stochastic models available to analyse the conditional variances, are based on either normal or log-normal distributions. One of the objectives of the present study is to explore the possibility of employing some non-Gaussian distributions to model the volatility sequences and then study the behaviour of the resulting return series. This lead us to work on the related problem of statistical inference, which is the main contribution of the thesis

A Modeling Analysis of Changing Global Land Use as affected by Changing Demands for Wood Products

The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.

Effects of transformation processes in 'jubraka' agroforestry systems of the Nuba Mountains, Sudan, on nutrient fluxes

Intensification processes in homegardens of the Nuba Mountains, Sudan, raise concerns about strongly positive carbon (C) and nutrient balances which are expected to lead to substantial element losses from these agroecosystems, in particular via soil gaseous emissions. Therefore, this thesis aimed at the quantification of C, nitrogen (N), phosphorus (P) and potassium (K) input and output fluxes with a special focus on soil gaseous losses, and the calculation of respective element balances. A further focus in this thesis was rainfall, a valuable resource for rain-fed agriculture in the Nuba Mountains. To minimize negative consequences of the high variability of rainfall, risk reducing mechanisms were developed by rain-fed farmers that may lose their efficacy in the course of climate change effects predicted for East Africa. Therefore, the second objective of this study was to examine possible changes in rainfall amounts during the last 60 years and to provide reliable risk and probability statements of rainfall-induced events of agricultural importance to rain-fed farmers in the Nuba Mountains. Soil gaseous emissions of C (in form of CO2) and N (in form of NH3 and N2O) of two traditional and two intensified homegardens were determined with a portable dynamic closed chamber system. For C gaseous emission rates reached their peak at the onset of the rainy season (2,325 g CO2-C ha-1 h-1 in an intensified garden type) and for N during the rainy season (16 g NH3-N ha-1 h-1 and 11.3 g N2O-N ha-1 h-1, in a traditional garden type). Data indicated cumulative annual emissions of 5,893 kg CO2-C ha-1, 37 kg NH3-N ha-1, and 16 kg N2O-N ha-1. For the assessment of the long-term productivity of the two types of homegardens and the identification of pathways of substantial element losses, a C and nutrient budget approach was used. In three traditional and three intensified homegardens observation plots were selected. The following variables were quantified on each plot between June and December in 2010: soil amendments, irrigation, biomass removal, symbiotic N2 fixation, C fixation by photosynthesis, atmospheric wet and dry deposition, leaching and soil gaseous emissions. Annual balances for C and nutrients amounted to -21 kg C ha-1, -70 kg N ha-1, 9 kg P ha-1 and -117 kg K ha-1 in intensified homegardens and to -1,722 kg C ha-1, -167 kg N ha-1, -9 kg P ha-1 and -74 kg K ha-1 in traditional homegardens. For the analysis of rainfall data, the INSTAT+ software allowed to aggregate long-term daily rainfall records from the Kadugli and Rashad weather stations into daily, monthly and annual intervals and to calculate rainfall-induced events of agricultural importance. Subsequently, these calculated values and events were checked for possible monotonic trends by Mann-Kendall tests. Over the period from 1970 to 2009, annual rainfall did not change significantly for either station. However, during this period an increase of low rainfall events coinciding with a decline in the number of medium daily rainfall events was observed in Rashad. Furthermore, the availability of daily rainfall data enabled frequency and conditional probability calculations that showed either no statistically significant changes or trends resulting only in minor changes of probabilities.

Maximum Entropy Discrimination

We present a general framework for discriminative estimation based on the maximum entropy principle and its extensions. All calculations involve distributions over structures and/or parameters rather than specific settings and reduce to relative entropy projections. This holds even when the data is not separable within the chosen parametric class, in the context of anomaly detection rather than classification, or when the labels in the training set are uncertain or incomplete. Support vector machines are naturally subsumed under this class and we provide several extensions. We are also able to estimate exactly and efficiently discriminative distributions over tree structures of class-conditional models within this framework. Preliminary experimental results are indicative of the potential in these techniques.

Validating Co-Training Models for Web Image Classification

Co-training is a semi-supervised learning method that is designed to take advantage of the redundancy that is present when the object to be identified has multiple descriptions. Co-training is known to work well when the multiple descriptions are conditional independent given the class of the object. The presence of multiple descriptions of objects in the form of text, images, audio and video in multimedia applications appears to provide redundancy in the form that may be suitable for co-training. In this paper, we investigate the suitability of utilizing text and image data from the Web for co-training. We perform measurements to find indications of conditional independence in the texts and images obtained from the Web. Our measurements suggest that conditional independence is likely to be present in the data. Our experiments, within a relevance feedback framework to test whether a method that exploits the conditional independence outperforms methods that do not, also indicate that better performance can indeed be obtained by designing algorithms that exploit this form of the redundancy when it is present.

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By an essential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur in many compositional situations, such as household budget patterns, time budgets, palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful in such situations. From consideration of such examples it seems sensible to build up a model in two stages, the first determining where the zeros will occur and the second how the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Modelling structural zeros in compositional data

This analysis was stimulated by the real data analysis problem of household expenditure data. The full dataset contains expenditure data for a sample of 1224 households. The expenditure is broken down at 2 hierarchical levels: 9 major levels (e.g. housing, food, utilities etc.) and 92 minor levels. There are also 5 factors and 5 covariates at the household level. Not surprisingly, there are a small number of zeros at the major level, but many zeros at the minor level. The question is how best to model the zeros. Clearly, models that try to add a small amount to the zero terms are not appropriate in general as at least some of the zeros are clearly structural, e.g. alcohol/tobacco for households that are teetotal. The key question then is how to build suitable conditional models. For example, is the sub-composition of spending excluding alcohol/tobacco similar for teetotal and non-teetotal households? In other words, we are looking for sub-compositional independence. Also, what determines whether a household is teetotal? Can we assume that it is independent of the composition? In general, whether teetotal will clearly depend on the household level variables, so we need to be able to model this dependence. The other tricky question is that with zeros on more than one component, we need to be able to model dependence and independence of zeros on the different components. Lastly, while some zeros are structural, others may not be, for example, for expenditure on durables, it may be chance as to whether a particular household spends money on durables within the sample period. This would clearly be distinguishable if we had longitudinal data, but may still be distinguishable by looking at the distribution, on the assumption that random zeros will usually be for situations where any non-zero expenditure is not small. While this analysis is based on around economic data, the ideas carry over to many other situations, including geological data, where minerals may be missing for structural reasons (similar to alcohol), or missing because they occur only in random regions which may be missed in a sample (similar to the durables)