Clonal composition of human adamantinomatous craniopharyngiomas and somatic mutation analyses of the patched (PTCH), Gsα and Gi2α genes

Craniopharyngioma is the most common childhood tumor and thought to arise from embryonic remnants of Rathke's pouch. The paucity of published data on the molecular basis of these tumors prompted us to examine 22 adamantinomatous craniopharyngiomas looking for genetic abnormalities. Using the X-linked polymorphic androgen receptor gene as a tool for X-chromosome inactivating analysis, we found that a subset of craniopharyngiomas are monoclonal and therefore are probably due to acquired somatic genetic defects. Thus, we investigated these tumours for mutations within three candidate genes, Gsα, Gi2α and patched (PTCH). Using single stranded conformational polymorphism (SSCP), denaturing gradient gel electrophoresis and direct sequencing, the presence of somatic mutations in these genes could not be demonstrated in any tumor. Our data indicate that a subset of craniopharyngiomas are monoclonal and the mutations in the PTCH, Gsα, and Gi2α contribute little if any to cranipharyngioma development.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

Formal Definition of Artificial Intelligence

* This publication is partially supported by the KT-DigiCult-Bg project.

Neanderthal admixture in current human populations

In the present body of work two primary subjects have been addressed, both individually and in their correspondence, namely (1) the potential for Neanderthals to have contributed to the Modern Human population, and (2) the genetic diversity of one of the most prehistorically impactful human popuations, the Armenians. The first subject is addressed by assessing 1000 mutations in 384 current humans, particularly for those mutations which appear to derive from the Neanderthal lineage. Additionally, the validity of the Neanderthal sequences themselves is evaluated through alignment analysis of fragementary DNA derived from the Vindija Cave sample. Armenian genetic diversity is analyzed through the autosomal short tandem repeats, y-chromsome single nucleotide polymorphisms, and y-chromosome short tandem repeats. The diversity found indicates that Armenians are a diverse group which has been genetically influenced by the various migrations and invasions which have entered their historic lands. Further, we find evidence that Armenians may be closely associated with the peopling of Europe.

Mutation at the Human D1S80 Minisatellite Locus

Little is known about the general biology of minisatellites. The purpose of this study is to examine repeat mutations from the D1S80 minisatellite locus by sequence analysis to elucidate the mutational process at this locus. This is a highly polymorphic minisatellite locus, located in the subtelomeric region of chromosome 1. We have analyzed 90,000 human germline transmission events and found seven (7) mutations at this locus. The D1S80 alleles of the parentage trio, the child, mother, and the alleged father were sequenced and the origin of the mutation was determined. Using American Association of Blood Banks (AABB) guidelines, we found a male mutation rate of 1 . 0 4 × 1 0− 4 and a female mutation rate of 5 . 1 8 × 1 0− 5 with an overall mutation rate of approximately 7 . 7 7 × 1 0− 5. Also, in this study, we found that the identified mutations are in close proximity to the center of the repeat array rather than at the ends of the repeat array. Several studies have examined the mutational mechanisms of the minisatellites according to infinite allele model (IAM) and the one-step stepwise mutation model (SMM). In this study, we found that this locus fits into the one-step mutation model (SMM) mechanism in six out of seven instances similar to STR loci.

A multimodal and adaptive real-time human -computer interface for peoples with severe motor disability

This dissertation introduces the design of a multimodal, adaptive real-time assistive system as an alternate human computer interface that can be used by individuals with severe motor disabilities. The proposed design is based on the integration of a remote eye-gaze tracking system, voice recognition software, and a virtual keyboard. The methodology relies on a user profile that customizes eye gaze tracking using neural networks. The user profiling feature facilitates the notion of universal access to computing resources for a wide range of applications such as web browsing, email, word processing and editing. ^ The study is significant in terms of the integration of key algorithms to yield an adaptable and multimodal interface. The contributions of this dissertation stem from the following accomplishments: (a) establishment of the data transport mechanism between the eye-gaze system and the host computer yielding to a significantly low failure rate of 0.9%; (b) accurate translation of eye data into cursor movement through congregate steps which conclude with calibrated cursor coordinates using an improved conversion function; resulting in an average reduction of 70% of the disparity between the point of gaze and the actual position of the mouse cursor, compared with initial findings; (c) use of both a moving average and a trained neural network in order to minimize the jitter of the mouse cursor, which yield an average jittering reduction of 35%; (d) introduction of a new mathematical methodology to measure the degree of jittering of the mouse trajectory; (e) embedding an onscreen keyboard to facilitate text entry, and a graphical interface that is used to generate user profiles for system adaptability. ^ The adaptability nature of the interface is achieved through the establishment of user profiles, which may contain the jittering and voice characteristics of a particular user as well as a customized list of the most commonly used words ordered according to the user's preferences: in alphabetical or statistical order. This allows the system to successfully provide the capability of interacting with a computer. Every time any of the sub-system is retrained, the accuracy of the interface response improves even more. ^

Flexible pavement layer moduli determination : an adaptive artificial neural network approach

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.

Glia-augmented artificial neural networks: foundations and applications

Information processing in the human brain has always been considered as a source of inspiration in Artificial Intelligence; in particular, it has led researchers to develop different tools such as artificial neural networks. Recent findings in Neurophysiology provide evidence that not only neurons but also isolated and networks of astrocytes are responsible for processing information in the human brain. Artificial neural net- works (ANNs) model neuron-neuron communications. Artificial neuron-glia networks (ANGN), in addition to neuron-neuron communications, model neuron-astrocyte con- nections. In continuation of the research on ANGNs, first we propose, and evaluate a model of adaptive neuro fuzzy inference systems augmented with artificial astrocytes. Then, we propose a model of ANGNs that captures the communications of astrocytes in the brain; in this model, a network of artificial astrocytes are implemented on top of a typical neural network. The results of the implementation of both networks show that on certain combinations of parameter values specifying astrocytes and their con- nections, the new networks outperform typical neural networks. This research opens a range of possibilities for future work on designing more powerful architectures of artificial neural networks that are based on more realistic models of the human brain.

Genetic-epidemiologic analysis of X-inactivation skewing in human females : suggestive evidence for two distinct traits

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Genetic-epidemiologic analysis of X-inactivation skewing in human females : suggestive evidence for two distinct traits

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Building autonomous sensitive artificial listeners (Extended abstract)

This paper describes a substantial effort to build a real-time interactive multimodal dialogue system with a focus on emotional and non-verbal interaction capabilities. The work is motivated by the aim to provide technology with competences in perceiving and producing the emotional and non-verbal behaviours required to sustain a conversational dialogue. We present the Sensitive Artificial Listener (SAL) scenario as a setting which seems particularly suited for the study of emotional and non-verbal behaviour, since it requires only very limited verbal understanding on the part of the machine. This scenario allows us to concentrate on non-verbal capabilities without having to address at the same time the challenges of spoken language understanding, task modeling etc. We first summarise three prototype versions of the SAL scenario, in which the behaviour of the Sensitive Artificial Listener characters was determined by a human operator. These prototypes served the purpose of verifying the effectiveness of the SAL scenario and allowed us to collect data required for building system components for analysing and synthesising the respective behaviours. We then describe the fully autonomous integrated real-time system we created, which combines incremental analysis of user behaviour, dialogue management, and synthesis of speaker and listener behaviour of a SAL character displayed as a virtual agent. We discuss principles that should underlie the evaluation of SAL-type systems. Since the system is designed for modularity and reuse, and since it is publicly available, the SAL system has potential as a joint research tool in the affective computing research community.

Integrase mutants defective for interaction with LEDGF/p75 are impaired in chromosome tethering and HIV-1 replication

The insertion of a DNA copy of its RNA genome into a chromosome of the host cell is mediated by the viral integrase with the help of mostly uncharacterized cellular cofactors. We have recently described that the transcriptional co-activator LEDGF/p75 strongly interacts with HIV-1 integrase. Here we show that interaction of HIV-1 integrase with LEDGF/p75 is important for viral replication. Using multiple approaches including two-hybrid interaction studies, random and directed mutagenesis, we could demonstrate that HIV-1 virus harboring a single mutation that disrupts integrase-LEDGF/p75 interaction, resulted in defective HIV-1 replication. Furthermore, we found that LEDGF/p75 tethers HIV-1 integrase to chromosomes and that this interaction may be important for the integration process and the replication of HIV-1.

Combining human perception and geometric restrictions for automatic pedestrian detection

[EN]Automatic detection systems do not perform as well as human observers, even on simple detection tasks. A potential solution to this problem is training vision systems on appropriate regions of interests (ROIs), in contrast to training on predefined and arbitrarily selected regions. Here we focus on detecting pedestrians in static scenes. Our aim is to answer the following question: Can automatic vision systems for pedestrian detection be improved by training them on perceptually-defined ROIs?

CASIMIRO: a robot head for human-computer interaction

The physical appearance and behavior of a robot is an important asset in terms of Human-Computer Interaction. Multimodality is also fundamental, as we humans usually expect to interact in a natural way with voice, gestures, etc. People approach complex interaction devices with stances similar to those used in their interaction with other people. In this paper we describe a robot head, currently under development, that aims to be a multimodal (vision, voice, gestures,...) perceptual user interface.