Prevalence, prenatal diagnosis and clinical features of oculo-auriculo-vertebral spectrum: a registry-based study in Europe.

Oculo-auriculo-vertebral spectrum is a complex developmental disorder characterised mainly by anomalies of the ear, hemifacial microsomia, epibulbar dermoids and vertebral anomalies. The aetiology is largely unknown, and the epidemiological data are limited and inconsistent. We present the largest population-based epidemiological study to date, using data provided by the large network of congenital anomalies registries in Europe. The study population included infants diagnosed with oculo-auriculo-vertebral spectrum during the 1990-2009 period from 34 registries active in 16 European countries. Of the 355 infants diagnosed with oculo-auriculo-vertebral spectrum, there were 95.8% (340/355) live born, 0.8% (3/355) fetal deaths, 3.4% (12/355) terminations of pregnancy for fetal anomaly and 1.5% (5/340) neonatal deaths. In 18.9%, there was prenatal detection of anomaly/anomalies associated with oculo-auriculo-vertebral spectrum, 69.7% were diagnosed at birth, 3.9% in the first week of life and 6.1% within 1 year of life. Microtia (88.8%), hemifacial microsomia (49.0%) and ear tags (44.4%) were the most frequent anomalies, followed by atresia/stenosis of external auditory canal (25.1%), diverse vertebral (24.3%) and eye (24.3%) anomalies. There was a high rate (69.5%) of associated anomalies of other organs/systems. The most common were congenital heart defects present in 27.8% of patients. The prevalence of oculo-auriculo-vertebral spectrum, defined as microtia/ear anomalies and at least one major characteristic anomaly, was 3.8 per 100,000 births. Twinning, assisted reproductive techniques and maternal pre-pregnancy diabetes were confirmed as risk factors. The high rate of different associated anomalies points to the need of performing an early ultrasound screening in all infants born with this disorder.

A Semantic wiki for quality management in software development projects

Quality management has become a strategic issue for organisations and is very valuable to produce quality software. However, quality management systems (QMS) are not easy to implement and maintain. The authors' experience shows the benefits of developing a QMS by first formalising it using semantic web ontologies and then putting them into practice through a semantic wiki. The QMS ontology that has been developed captures the core concepts of a traditional QMS and combines them with concepts coming from the MPIu'a development process model, which is geared towards obtaining usable and accessible software products. Then, the ontology semantics is directly put into play by a semantics-aware tool, the Semantic MediaWiki. The developed QMS tool is being used for 2 years by the GRIHO research group, where it has manages almost 50 software development projects taking into account the quality management issues. It has also been externally audited by a quality certification organisation. Its users are very satisfied with their daily work with the tool, which manages all the documents created during project development and also allows them to collaborate, thanks to the wiki features.

Contact Center Functionality - Collecting and Prioritizing Features of Modern Contact Center.

Tässä diplomityössä pohditaan call centereiden asemaa tämän päivän palveluympäristössä ja myöskin call centereiden tulevaisuutta contact centereinä. Tämä työ tutkii kuinka asiakastarpeita ja uusia toiminnallisuuksia voidaan etsiä olemassaolevaan, mutta vielä keskeneräiseen call center tuotteeseen. Tutkimus on tehty lukemalla artikkeleita ja kirjoja tulevaisuuden contact centereistä, haastattelemalla asiakkaita ja järjestämällä ideointisessio yrityksen asiantuntijoille. Näin saadut tulokset priorisoitiin tätä tarkoitusta varten kehitellyllä matriisilla. Lopullisena tuloksena on lista toiminnallisuuksista tärkeysjärjestyksessä ja tuote roadmap kaikkein tärkeimmistä toiminnallisuuksista. Tämä roadmap antaa tuotekehitykselle ehdotuksen mitä tulisi implementoida nykyiseen tuotteeseen ja mitkä ovat prioriteetit. Tässä työssä pohdiskellaan myös tuotteen modulaarista rakennetta.

Mutations in LONP1, a mitochondrial matrix protease, cause CODAS syndrome.

Cerebral, ocular, dental, auricular, skeletal anomalies (CODAS) syndrome (MIM 600373) was first described and named by Shehib et al, in 1991 in a single patient. The anomalies referred to in the acronym are as follows: cerebral-developmental delay, ocular-cataracts, dental-aberrant cusp morphology and delayed eruption, auricular-malformations of the external ear, and skeletal-spondyloepiphyseal dysplasia. This distinctive constellation of anatomical findings should allow easy recognition but despite this only four apparently sporadic patients have been reported in the last 20 years indicating that the full phenotype is indeed very rare with perhaps milder or a typical presentations that are allelic but without sufficient phenotypic resemblance to permit clinical diagnosis. We performed exome sequencing in three patients (an isolated case and a brother and sister sib pair) with classical features of CODAS. Sanger sequencing was used to confirm results as well as for mutation discovery in a further four unrelated patients ascertained via their skeletal features. Compound heterozygous or homozygous mutations in LONP1 were found in all (8 separate mutations; 6 missense, 1 nonsense, 1 small in-frame deletion) thus establishing the genetic basis of CODAS and the pattern of inheritance (autosomal recessive). LONP1 encodes an enzyme of bacterial ancestry that participates in protein turnover within the mitochondrial matrix. The mutations cluster at the ATP-binding and proteolytic domains of the enzyme. Biallelic inheritance and clustering of mutations confirm dysfunction of LONP1 activity as the molecular basis of CODAS but the pathogenesis remains to be explored.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise.

Specific structural features of syndecans and heparan sulfate chains are needed for cell signaling

The syndecans, heparan sulfate proteoglycans, are abundant molecules associated with the cell surface and extracellular matrix and consist of a protein core to which heparan sulfate chains are covalently attached. Each of the syndecan core proteins has a short cytoplasmic domain that binds cytosolic regulatory factors. The syndecans also contain highly conserved transmembrane domains and extracellular domains for which important activities are becoming known. These protein domains locate the syndecan on cell surface sites during development and tumor formation where they interact with other receptors to regulate signaling and cytoskeletal organization. The functions of cell surface heparan sulfate proteoglycan have been centered on the role of heparan sulfate chains, located on the outer side of the cell surface, in the binding of a wide array of ligands, including extracellular matrix proteins and soluble growth factors. More recently, the core proteins of the syndecan family transmembrane proteoglycans have also been shown to be involved in cell signaling through interaction with integrins and tyrosine kinase receptors.

Prevalence of vascular-endothelial growth factor, matrix metalloproteinases and tissue inhibitors of metalloproteinases in primary breast cancer

Our objective was to determine the presence of vascular endothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2) and MMP-9 and specific tissue inhibitors of matrix metalloproteinase (TIMP-1 and TIMP-2) in tumor samples obtained from patients with primary breast cancer. We attempted to correlate these findings with the status of the sentinel lymph node (SLN) and clinical-pathological characteristics such as age, tumor size, histological type, histological grade, and vascular invasion. Tumor samples from 88 patients with primary breast cancer were analyzed. The immunoreactivity of VEGF, MMP-2, MMP-9, TIMP-1, and TIMP-2 in tumors was correlated with clinical and pathological features, as well as SLN status. Nonparametric, Mann-Whittney, Kruskal-Wallis, and Spearmann tests were used. Categorical variables were analyzed by the Pearson test. No statistically significant correlation was found between the amount of VEGF, MMP-2, MMP-9, TIMP-1, and TIMP-2 and the presence of tumor cells in the SLN. However, larger tumor diameter (P < 0.01) and the presence of vascular invasion (P < 0.01) were correlated positively with a positive SLN. A significant correlation of higher VEGF levels (P = 0.04) and lower TIMP-1 levels (P = 0.04) with ductal histology was also observed. Furthermore, lower TIMP-2 levels showed a statistically significant correlation with younger age (<50 years) and larger tumor diameter (2.0-5.0 cm). A positive SLN correlated significantly with a larger tumor diameter and the presence of vascular invasion. Higher VEGF and lower TIMP-1 levels were observed in patients with ductal tumors, while higher TIMP-1 levels were observed in lobular tumors.

Role of the extracellular matrix in variations of invasive pathways in lung cancers

Among the most common features of highly invasive tumors, such as lung adenocarcinomas (AD) and squamous cell carcinomas (SqCC), is the massive degradation of the extracellular matrix. The remarkable qualitative and quantitative modifications of hyaluronidases (HAases), hyaluronan synthases (HAS), E-cadherin adhesion molecules, and the transforming growth factor β (TGF-β) may favor invasion, cellular motility, and proliferation. We examined HAase proteins (Hyal), HAS, E-cadherin, and TGF-β profiles in lung AD subtypes and SqCC obtained from smokers and non-smokers. Fifty-six patients, median age 64 years, who underwent lobectomy for AD (N = 31) and SqCC (N = 25) were included in the study. HAS-1, -2 and -3, and Hyal-1 and -3 were significantly more expressed by tumor cells than normal and stroma cells (P < 0.01). When stratified according to histologic types, HAS-3 and Hyal-1 immunoreactivity was significantly increased in tumor cells of AD (P = 0.01) and stroma of SqCC (P = 0.002), respectively. Tobacco history in patients with AD was significantly associated with increased HAS-3 immunoreactivity in tumor cells (P < 0.01). Stroma cells of SqCC from non-smokers presented a significant association with HAS-3 (P < 0.01). Hyal, HAS, E-cadherin, and TGF-β modulate a different tumor-induced invasive pathway in lung AD subgroups and SqCC. HAases in resected AD and SqCC were strongly related to the prognosis. Therefore, our findings suggest that strategies aimed at preventing high HAS-3 and Hyal-1 synthesis, or local responses to low TGF-β and E-cadherin, may have a greater impact in lung cancer prognosis.

Filopodia and stromal extracellular matrix as regulators of cancer cell invasion and growth

Bidirectional exchange of information between the cancer cells and their environment is essential for cancer to evolve. Cancer cells lose the ability to regulate their growth, gain the ability to detach from neighboring cells and finally some of the cells disseminate from the primary tumor and invade to the adjacent tissue. During cancer progression, cells acquire features that promote cancer motility and proliferation one of them being increased filopodia number. Filopodia are dynamic actin-rich structures extending from the leading edge of migrating cells and the main function of these structures is to serve as environmental sensors. It is nowadays widely appreciated, that not only the cancer cells, but also the surrounding of the tumor – the tumor microenvironment- contribute to cancer cell dissemination and tumor growth. Activated stromal fibroblasts, also known as cancer-associated fibroblasts (CAFs) actively participate on tumor progression. CAFs are the most abundant cell type surrounding the cancer cells and they are the main cell type producing the extracellular matrix (ECM) within tumor stroma. CAFs secrete growth factors to promote tumor growth, direct cancer cell invasion as well as modify the stromal ECM architecture. The aim of this thesis was to investigate the function of filopodia, particularly the role of filopodia-inducing protein Myosin-X (Myo10), in breast cancer cell invasion and metastasis. We found that Myo10 is an important regulator of basal type breast cancer spreading downstream of mutant p53. In addition, I investigated the role of CAFs and their secreted matrix on tumor growth. According to the results, CAF-derived matrix has altered organization and stiffness which induces the carcinoma cell proliferation via epigenetic mechanisms. I identified histone demethylase enzyme JMJD1a to be regulated by the stiffness and to participate in stiffness induced growth control.

The Role of HR Management in the Corporate Matrix System

The successful performance of company in the market relates to the quality management of human capital aiming to improve the company's internal performance and external implementation of the core business strategy. Companies with matrix structure focusing on realization and development of innovation and technologies for the uncertain market need to select thoroughly the approach to HR management system. Human resource management has a significant impact on the organization and use a variety of instruments such as corporate information systems to fulfill their functions and objectives. There are three approaches to strategic control management depending on major impact on the major interference in employee decision-making, development of skills and his integration into the business strategy. The mainstream research has focus only on the framework of strategic planning of HR and general productivity of firm, but not on features of organizational structure and corporate software capabilities for human capital. This study tackles the before mentioned challenges, typical for matrix organization, by using the HR control management tools and corporate information system. The detailed analysis of industry producing and selling electromotor and heating equipment in this master thesis provides the opportunity to improve system for HR control and displays its application in the ERP software. The results emphasize the sustainable role of matrix HR input control for creating of independent project teams for matrix structure who are able to respond to various uncertainties of the market and use their skills for improving performance. Corporate information systems can be integrated into input control system by means of output monitoring to regulate and evaluate the processes of teams, using key performance indicators and reporting systems.

A lexical semantic study of Dene Suliné, an Athabaskan language

Cette thèse constitue une étude systématique du lexique du déné sųłiné, une langue athabaskane du nord-ouest canadien. Elle présente les définitions et les patrons de combinatoire syntaxique et lexicale de plus de 200 unités lexicales, lexèmes et phrasèmes, qui représentent une partie importante du vocabulaire déné sųłiné dans sept domaines: les émotions, le caractère humain, la description physique des entités, le mouvement des êtres vivants, la position des entités, les conditions atmospheriques et les formations topologiques, en les comparant avec le vocubulaire équivalent de l'anglais. L’approche théorique choisie est la Théorie Sens-Texte (TST), une approche formelle qui met l’accent sur la description sémantique et lexicographique empiriques. La présente recherche relève d'importantes différences entre le lexique du déné sųłiné et celui de l'anglais à tous les niveaux: dans la correspondence entre la représentation conceptuelle, considérée (quasi-)extralinguistique, et la structure sémantique; dans les patrons de lexicalisation des unités lexicales, et dans les patrons de combinatoire syntaxique et lexicale, qui montrent parfois des traits propres au déné sųłiné intéressants.

Incorporating complex cells into neural networks for pattern classification

Dans le domaine des neurosciences computationnelles, l'hypothèse a été émise que le système visuel, depuis la rétine et jusqu'au cortex visuel primaire au moins, ajuste continuellement un modèle probabiliste avec des variables latentes, à son flux de perceptions. Ni le modèle exact, ni la méthode exacte utilisée pour l'ajustement ne sont connus, mais les algorithmes existants qui permettent l'ajustement de tels modèles ont besoin de faire une estimation conditionnelle des variables latentes. Cela nous peut nous aider à comprendre pourquoi le système visuel pourrait ajuster un tel modèle; si le modèle est approprié, ces estimé conditionnels peuvent aussi former une excellente représentation, qui permettent d'analyser le contenu sémantique des images perçues. Le travail présenté ici utilise la performance en classification d'images (discrimination entre des types d'objets communs) comme base pour comparer des modèles du système visuel, et des algorithmes pour ajuster ces modèles (vus comme des densités de probabilité) à des images. Cette thèse (a) montre que des modèles basés sur les cellules complexes de l'aire visuelle V1 généralisent mieux à partir d'exemples d'entraînement étiquetés que les réseaux de neurones conventionnels, dont les unités cachées sont plus semblables aux cellules simples de V1; (b) présente une nouvelle interprétation des modèles du système visuels basés sur des cellules complexes, comme distributions de probabilités, ainsi que de nouveaux algorithmes pour les ajuster à des données; et (c) montre que ces modèles forment des représentations qui sont meilleures pour la classification d'images, après avoir été entraînés comme des modèles de probabilités. Deux innovations techniques additionnelles, qui ont rendu ce travail possible, sont également décrites : un algorithme de recherche aléatoire pour sélectionner des hyper-paramètres, et un compilateur pour des expressions mathématiques matricielles, qui peut optimiser ces expressions pour processeur central (CPU) et graphique (GPU).

Urban Detection From Hyperspectral Images Using Dimension-Reduction Model and Fusion of Multiple Segmentations Based on Stuctural and Textural Features

Ce mémoire de maîtrise présente une nouvelle approche non supervisée pour détecter et segmenter les régions urbaines dans les images hyperspectrales. La méthode proposée n ́ecessite trois étapes. Tout d’abord, afin de réduire le coût calculatoire de notre algorithme, une image couleur du contenu spectral est estimée. A cette fin, une étape de réduction de dimensionalité non-linéaire, basée sur deux critères complémentaires mais contradictoires de bonne visualisation; à savoir la précision et le contraste, est réalisée pour l’affichage couleur de chaque image hyperspectrale. Ensuite, pour discriminer les régions urbaines des régions non urbaines, la seconde étape consiste à extraire quelques caractéristiques discriminantes (et complémentaires) sur cette image hyperspectrale couleur. A cette fin, nous avons extrait une série de paramètres discriminants pour décrire les caractéristiques d’une zone urbaine, principalement composée d’objets manufacturés de formes simples g ́eométriques et régulières. Nous avons utilisé des caractéristiques texturales basées sur les niveaux de gris, la magnitude du gradient ou des paramètres issus de la matrice de co-occurrence combinés avec des caractéristiques structurelles basées sur l’orientation locale du gradient de l’image et la détection locale de segments de droites. Afin de réduire encore la complexité de calcul de notre approche et éviter le problème de la ”malédiction de la dimensionnalité” quand on décide de regrouper des données de dimensions élevées, nous avons décidé de classifier individuellement, dans la dernière étape, chaque caractéristique texturale ou structurelle avec une simple procédure de K-moyennes et ensuite de combiner ces segmentations grossières, obtenues à faible coût, avec un modèle efficace de fusion de cartes de segmentations. Les expérimentations données dans ce rapport montrent que cette stratégie est efficace visuellement et se compare favorablement aux autres méthodes de détection et segmentation de zones urbaines à partir d’images hyperspectrales.

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

Comparison of Statistical and Semantic Similarity Techniques for Paraphrase Identification

This paper compares statistical technique of paraphrase identification to semantic technique of paraphrase identification. The statistical techniques used for comparison are word set and word-order based methods where as the semantic technique used is the WordNet similarity matrix method described by Stevenson and Fernando in [3].