989 resultados para Pattern oriented modelling
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Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately
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We present a new approach for analyzing the turnover rates of Cretaceous radiolarians recorded in pelagic sequences of western Tethys, The analysis of major extinction-radiation events and the fluctuation of diversity are compared with major paleoceanographic events and variation of diversity in dinoflagellates, calcareous nannoplankton and ammonites. There is an extraordinary correlation between biotic changes and sea level changes, temperatures, O, C and Sr isotopes, phosphorus accumulation rates and anoxic episodes. This reveals a predominantly abiotic control on the evolution of radiolarians. The rate of turnover and the diversity through time of two major orders of radiolarians (nassellarians and spumellarians) exhibits (1) the quasi-parallelism of their diversity curves, excluding a direct competition between them, (2) greater resistance of spumellarians to extinction during the early stage of extinction intervals and (3) a stronger post-extinction recovery of nassellarians. Evolutionary rates of radiolarians can be a good means of monitoring global environmental changes and allowing us to understand more clearly the relationship between plankton evolution, climate and pale oceanographic processes.
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Abstract Borderline Personality Disorder (BPD) is characterized by both maladaptive thinking and problematic schemas. Kramer and colleagues (2011) showed that using the motive-oriented therapeutic relationship (MOTR), based on the individualized understanding of the patient according to Plan Analysis (Caspar, 2007), can improve treatment outcomes for BPD. The present process-outcome pilot study aimed to examine the effects of the motive-oriented therapeutic relationship on the cognitive biases of patients with BPD. Change in biased cognitions in N=10 patients who were subject to MOTR was compared to that of N=10 patients who received psychiatric-psychodynamic treatment (Gunderson & Links, 2008). Results show a greater decrease in over-generalizations in patients who received MOTR, compared to the patients who received the psychiatric-psychodynamic treatment. These changes were related to outcome in various ways. These findings underline the importance of an individualized case formulation method in bringing about therapeutic change.
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Projecte de recerca elaborat a partir d’una estada a la University of British Columbia, Canadà, entre 2010 i 2012 La malaltia d'Alzheimer (MA) representa avui la forma més comuna de demència en la població envellida. Malgrat fa 100 anys que va ser descoberta, encara avui no existeix cap tractament preventiu i/o curatiu ni cap agent de diagnòstic que permeti valorar quantitativament l'evolució d'aquesta malaltia. L'objectiu en el que s'emmarca aquest treball és contribuir a aportar solucions al problema de la manca d'agents terapèutics i de diagnosi, unívocs i rigorosos, per a la MA. Des del camp de la química bioinorgànica és fàcil fixar-se en l'excessiva concentració d'ions Zn(II) i Cu(II) en els cervells de malalts de MA, plantejar-se la seva utilització com a dianes terapèutica i, en conseqüència, cercar agents quelants que evitin la formació de plaques senils o contribueixin a la seva dissolució. Si bé aquest va ser el punt de partida d’aquest projecte, els múltiples factors implicats en la patogènesi de la MA fan que el clàssic paradigma d’ ¨una molècula, una diana¨ limiti la capacitat de la molècula de combatre aquesta malaltia tan complexa. Per tant, un esforç considerable s’ha dedicat al disseny d’agentsmultifuncionals que combatin els múltiples factors que caracteritzen el desenvolupament de la MA. En el present treball s’han dissenyat agents multifuncionals inspirats en dos esquelets moleculars ben establers i coneguts en el camp de la química medicinal: la tioflavina-T (ThT) i la deferiprona (DFP). La utilització de tècniques in silico que inclouen càlculs farmacocinètics i modelatge molecular ha estat un procés cabdal per a l’avaluació dels millors candidats en base als següents requeriments: (a) compliment de determinades propietats farmacocinètiques que estableixin el seu possible ús com a fàrmac (b) hidrofobicitat adequada per travessar la BBB i (c) interacció amb el pèptid Aen solució.
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We diagnosed a non-small cell lung carcinoma in a 49-year-old female patient with the histopathological diagnosis of stage IIIB mixed bronchioloalveolar and papillary adenocarcinoma with extensive micropapillary feature, which was not visualized on the preoperative multimodality imaging with positron emission tomography (PET) and computed tomography (CT). The micropapillary component characterized by a unique growth pattern with particular morphological features can be observed in all subtypes of lung adenocarcinoma. Micropapillary component is increasingly recognized as a distinct entity associated with higher aggressiveness. Even the most modern multimodality PET/CT imaging technology may fail to adequately visualize this important component with highly relevant prognostic implications. Thus, the pathologist needs to consciously look for a micropapillary component in the surgical specimen or in preoperative biopsies or cytology. This may have potential future treatment implications, as adjuvant or neoadjuvant chemotherapy may be of relevance, even in the early stages of the disease.
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Aim We investigated the late Quaternary history of two closely related and partly sympatric species of Primula from the south-western European Alps, P. latifolia Lapeyr. and P. marginata Curtis, by combining phylogeographical and palaeodistribution modelling approaches. In particular, we were interested in whether the two approaches were congruent and identified the same glacial refugia. Location South-western European Alps. Methods For the phylogeographical analysis we included 353 individuals from 28 populations of P. marginata and 172 individuals from 15 populations of P. latifolia and used amplified fragment length polymorphisms (AFLPs). For palaeodistribution modelling, species distribution models (SDMs) were based on extant species occurrences and then projected to climate models (CCSM, MIROC) of the Last Glacial Maximum (LGM), approximately 21 ka. Results The locations of the modelled LGM refugia were confirmed by various indices of genetic variation. The refugia of the two species were largely geographically isolated, overlapping only 6% to 11% of the species' total LGM distribution. This overlap decreased when the position of the glacial ice sheet and the differential elevational and edaphic distributions of the two species were considered. Main conclusions The combination of phylogeography and palaeodistribution modelling proved useful in locating putative glacial refugia of two alpine species of Primula. The phylogeographical data allowed us to identify those parts of the modelled LGM refugial area that were likely source areas for recolonization. The use of SDMs predicted LGM refugial areas substantially larger and geographically more divergent than could have been predicted by phylogeographical data alone
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A fundamental question in developmental biology is how tissues are patterned to give rise to differentiated body structures with distinct morphologies. The Drosophila wing disc offers an accessible model to understand epithelial spatial patterning. It has been studied extensively using genetic and molecular approaches. Bristle patterns on the thorax, which arise from the medial part of the wing disc, are a classical model of pattern formation, dependent on a pre-pattern of trans-activators and –repressors. Despite of decades of molecular studies, we still only know a subset of the factors that determine the pre-pattern. We are applying a novel and interdisciplinary approach to predict regulatory interactions in this system. It is based on the description of expression patterns by simple logical relations (addition, subtraction, intersection and union) between simple shapes (graphical primitives). Similarities and relations between primitives have been shown to be predictive of regulatory relationships between the corresponding regulatory factors in other Systems, such as the Drosophila egg. Furthermore, they provide the basis for dynamical models of the bristle-patterning network, which enable us to make even more detailed predictions on gene regulation and expression dynamics. We have obtained a data-set of wing disc expression patterns which we are now processing to obtain average expression patterns for each gene. Through triangulation of the images we can transform the expression patterns into vectors which can easily be analysed by Standard clustering methods. These analyses will allow us to identify primitives and regulatory interactions. We expect to identify new regulatory interactions and to understand the basic Dynamics of the regulatory network responsible for thorax patterning. These results will provide us with a better understanding of the rules governing gene regulatory networks in general, and provide the basis for future studies of the evolution of the thorax-patterning network in particular.
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Résumé Le cancer du sein est le cancer le plus commun chez les femmes et est responsable de presque 30% de tous les nouveaux cas de cancer en Europe. On estime le nombre de décès liés au cancer du sein en Europe est à plus de 130.000 par an. Ces chiffres expliquent l'impact social considérable de cette maladie. Les objectifs de cette thèse étaient: (1) d'identifier les prédispositions et les mécanismes biologiques responsables de l'établissement des sous-types spécifiques de cancer du sein; (2) les valider dans un modèle ín vivo "humain-dans-souris"; et (3) de développer des traitements spécifiques à chaque sous-type de cancer du sein identifiés. Le premier objectif a été atteint par l'intermédiaire de l'analyse des données d'expression de gènes des tumeurs, produite dans notre laboratoire. Les données obtenues par puces à ADN ont été produites à partir de 49 biopsies des tumeurs du sein provenant des patientes participant dans l'essai clinique EORTC 10994/BIG00-01. Les données étaient très riches en information et m'ont permis de valider des données précédentes des autres études d'expression des gènes dans des tumeurs du sein. De plus, cette analyse m'a permis d'identifier un nouveau sous-type biologique de cancer du sein. Dans la première partie de la thèse, je décris I identification des tumeurs apocrines du sein par l'analyse des puces à ADN et les implications potentielles de cette découverte pour les applications cliniques. Le deuxième objectif a été atteint par l'établissement d'un modèle de cancer du sein humain, basé sur des cellules épithéliales mammaires humaines primaires (HMECs) dérivées de réductions mammaires. J'ai choisi d'adapter un système de culture des cellules en suspension basé sur des mammosphères précédemment décrit et pat décidé d'exprimer des gènes en utilisant des lentivirus. Dans la deuxième partie de ma thèse je décris l'établissement d'un système de culture cellulaire qui permet la transformation quantitative des HMECs. Par la suite, j'ai établi un modèle de xénogreffe dans les souris immunodéficientes NOD/SCID, qui permet de modéliser la maladie humaine chez la souris. Dans la troisième partie de ma thèse je décris et je discute les résultats que j'ai obtenus en établissant un modèle estrogène-dépendant de cancer du sein par transformation quantitative des HMECs avec des gènes définis, identifiés par analyse de données d'expression des gènes dans le cancer du sein. Les cellules transformées dans notre modèle étaient estrogène-dépendantes pour la croissance, diploïdes et génétiquement normales même après la culture cellulaire in vitro prolongée. Les cellules formaient des tumeurs dans notre modèle de xénogreffe et constituaient des métastases péritonéales disséminées et du foie. Afin d'atteindre le troisième objectif de ma thèse, j'ai défini et examiné des stratégies de traitement qui permettent réduire les tumeurs et les métastases. J'ai produit un modèle de cancer du sein génétiquement défini et positif pour le récepteur de l'estrogène qui permet de modéliser le cancer du sein estrogène-dépendant humain chez la souris. Ce modèle permet l'étude des mécanismes impliqués dans la formation des tumeurs et des métastases. Abstract Breast cancer is the most common cancer in women and accounts for nearly 30% of all new cancer cases in Europe. The number of deaths from breast cancer in Europe is estimated to be over 130,000 each year, implying the social impact of the disease. The goals of this thesis were first, to identify biological features and mechanisms --responsible for the establishment of specific breast cancer subtypes, second to validate them in a human-in-mouse in vivo model and third to develop specific treatments for identified breast cancer subtypes. The first objective was achieved via the analysis of tumour gene expression data produced in our lab. The microarray data were generated from 49 breast tumour biopsies that were collected from patients enrolled in the clinical trial EORTC 10994/BIG00-01. The data set was very rich in information and allowed me to validate data of previous breast cancer gene expression studies and to identify biological features of a novel breast cancer subtype. In the first part of the thesis I focus on the identification of molecular apacrine breast tumours by microarray analysis and the potential imptìcation of this finding for the clinics. The second objective was attained by the production of a human breast cancer model system based on primary human mammary epithelial cells {HMECs) derived from reduction mammoplasties. I have chosen to adopt a previously described suspension culture system based on mammospheres and expressed selected target genes using lentiviral expression constructs. In the second part of my thesis I mainly focus on the establishment of a cell culture system allowing for quantitative transformation of HMECs. I then established a xenograft model in immunodeficient NOD/SCID mice, allowing to model human disease in a mouse. In the third part of my thesis I describe and discuss the results that I obtained while establishing an oestrogen-dependent model of breast cancer by quantitative transformation of HMECs with defined genes identified after breast cancer gene expression data analysis. The transformed cells in our model are oestrogen-dependent for growth; remain diploid and genetically normal even after prolonged cell culture in vitro. The cells farm tumours and form disseminated peritoneal and liver metastases in our xenograft model. Along the lines of the third objective of my thesis I defined and tested treatment schemes allowing reducing tumours and metastases. I have generated a genetically defined model of oestrogen receptor alpha positive human breast cancer that allows to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.
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Background: To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results: To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions: We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.
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AIMS: This study aimed to estimate the prevalence of life-time abstainers, former drinkers and current drinkers, adult per-capita consumption of alcohol and pattern of drinking scores, by country and Global Burden of Disease region for 2005, and to forecast these indicators for 2010. DESIGN: Statistical modelling based on survey data and routine statistics. SETTING AND PARTICIPANTS: A total of 241 countries and territories. MEASUREMENTS: Per-capita consumption data were obtained with the help of the World Health Organization's Global Information System on Alcohol and Health. Drinking status data were obtained from Gender, Alcohol and Culture: An International Study, the STEPwise approach to Surveillance study, the World Health Survey/Multi-Country Study and other surveys. Consumption and drinking status data were triangulated to estimate alcohol consumption across multiple categories. FINDINGS: In 2005 adult per-capita annual consumption of alcohol was 6.1 litres, with 1.7 litres stemming from unrecorded consumption; 17.1 litres of alcohol were consumed per drinker, 45.8% of all adults were life-time abstainers, 13.6% were former drinkers and 40.6% were current drinkers. Life-time abstention was most prevalent in North Africa/Middle East and South Asia. Eastern Europe and Southern sub-Saharan Africa had the most detrimental pattern of drinking scores, while drinkers in Europe (Eastern and Central) and sub-Saharan Africa (Southern and West) consumed the most alcohol. CONCLUSIONS: Just over 40% of the world's adult population consumes alcohol and the average consumption per drinker is 17.1 litres per year. However, the prevalence of abstention, level of alcohol consumption and patterns of drinking vary widely across regions of the world.
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Collage is a pattern-based visual design authoring tool for the creation of collaborative learning scripts computationally modelled with IMS Learning Design (LD). The pattern-based visual approach aims to provide teachers with design ideas that are based on broadly accepted practices. Besides, it seeks hiding the LD notation so that teachers can easily create their own designs. The use of visual representations supports both the understanding of the design ideas and the usability of the authoring tool. This paper presents a multicase study comprising three different cases that evaluate the approach from different perspectives. The first case includes workshops where teachers use Collage. A second case implies the design of a scenario proposed by a third-party using related approaches. The third case analyzes a situation where students follow a design created with Collage. The cross-case analysis provides a global understanding of the possibilities and limitations of the pattern-based visual design approach.
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Designs of CSCL (Computer Supported Collaborative Learning)activities should be flexible, effective and customizable toparticular learning situations. On the other hand, structureddesigns aim to create favourable conditions for learning. Thus,this paper proposes the collection of representative and broadlyaccepted (best practices) structuring techniques in collaborative learning. With the aim of establishing a conceptual common ground among collaborative learning practitioners and softwaredevelopers, and reusing the expertise that best practicesrepresent, the paper also proposes the formulation of these techniques as patterns: the so-called CLFPs (CollaborativeLearning Flow Patterns). To formalize these patterns, we havechosen the educational modelling language IMS Learning Design (IMS-LD). IMS-LD has the capability to specify many of the collaborative characteristics of the CLFPs. Nevertheless, the language bears limited capability for describing the services that mediate interactions within a learning activity and the specification of temporal or rotated roles. This analysis isdiscussed in the paper, as well as our approaches towards thedevelopment of a system capable of integrating tools using IMSLDscripts and a CLFP-based Learning Design authoring tool.
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Collaborative activities, in which students actively interact with each other, have proved to provide significant learning benefits. In Computer-Supported Collaborative Learning (CSCL), these collaborative activities are assisted by technologies. However, the use of computers does not guarantee collaboration, as free collaboration does not necessary lead to fruitful learning. Therefore, practitioners need to design CSCL scripts that structure the collaborative settings so that they promote learning. However, not all teachers have the technical and pedagogical background needed to design such scripts. With the aim of assisting teachers in designing effective CSCL scripts, we propose a model to support the selection of reusable good practices (formulated as patterns) so that they can be used as a starting point for their own designs. This model is based on a pattern ontology that computationally represents the knowledge captured on a pattern language for the design of CSCL scripts. A preliminary evaluation of the proposed approach is provided with two examples based on a set of meaningful interrelated patters computationally represented with the pattern ontology, and a paper prototyping experience carried out with two teaches. The results offer interesting insights towards the implementation of the pattern ontology in software tools.