Development and application of NMR techniques to study water-in-CO2 microemulsions

Self-assembly is a phenomenon that occurs frequently throughout the universe. In this work, two self-assembling systems were studied: the formation of reverse micelles in isooctane and in supercritical CO2 (scCO2), and the formation of gels in organic solvents. The goal was the physicochemical study of these systems and the development of an NMR methodology to study them. In this work, AOT was used as a model molecule both to comprehensively study a widely researched system water/AOT/isooctane at different water concentrations and to assess its aggregation in supercritical carbon dioxide at different pressures. In order to do so an NMR methodology was devised, in which it was possible to accurately determine hydrodynamic radius of the micelle (in agreement with DLS measurements) using diffusion ordered spectroscopy (DOSY), the micellar stability and its dynamics. This was mostly assessed by 1H NMR relaxation studies, which allowed to determine correlation times and size of correlating water molecules, which are in agreement with the size of the shell that interacts with the micellar layer. The encapsulation of differently-sized carbohydrates was also studied and allowed to understand the dynamics and stability of the aggregates in such conditions. A W/CO2 microemulsion was prepared using AOT and water in scCO2, with ethanol as cosurfactant. The behaviour of the components of the system at different pressures was assessed and it is likely that above 130 bar reverse microemulsions were achieved. The homogeneity of the system was also determined by NMR. The formation of the gel network by two small molecular organogelators in toluene-d8 was studied by DOSY. A methodology using One-shot DOSY to perform the spectra was designed and applied with success. This yielded an understanding about the role of the solvent and gelator in the aggregation process, as an estimation of the time of gelation.

Geografia eleitoral : análise espacial de vinte anos de resultados eleitorais

A Geografia Eleitoral definida como a análise da interação entre o espaço, o lugar e os processos eleitorais, compreende fundamentalmente três domínios: padrões de voto, influências geográficas nas eleições e a geografia da representação. A Geografia Eleitoral conta uma longa história, ao ponto de já ter tido um status próprio no âmbito da disciplina. Depois ter aparecido nos anos 70 e 80 com algum vigor no contexto português, esta abordagem dos fenómenos eleitorais tem sido relativamente negligenciada nos anos. Neste trabalho, conjugando as metodologias espaciais-analíticas mais tradicionais com um conjunto de novas tecnologias - como os Sistemas de Informação Geográfica (SIG) e os Self- Organizing Maps (SOM) -, pretendemos dar uma nova ênfase à Geografia Eleitoral nacional, realçando o seu caráter explicativo e abrindo portas a abordagens multidisciplinares dos dados eleitorais. Com base nos resultados das eleições legislativas portuguesas realizadas no período compreendido entre 1991 e 2011, analisamos neste trabalho os seguintes tópicos: a distribuição espacial dos resultados, em conjunto e individualmente, dos cinco partidos com representação parlamentar; a distribuição dos resultados deste conjunto de partidos por região, considerando uma das propostas de divisão administrativa referendada em 1998 e analisando a região da Estremadura e Ribatejo como um estudo de caso; os padrões gerados pela distribuição do bloco constituído pelos dois principais partidos (PS e PPD/PSD); o comportamento espacial dos blocos Direita/Centro-Direita e Esquerda/Centro- Esquerda; a abstenção eleitoral, confrontando os valores registados em cada freguesia com o resultado nacional; a comparação entre diferentes tipos de eleições; a distribuição dos resultados por partido nos dois principais distritos (Lisboa e Porto) que em conjunto representam mais de 40% da população portuguesa; o comportamento do Bloco de Esquerda, o mais jovem dos partidos considerados; e os mapeamentos das freguesias “sociais-democratas” e “socialistas”. Os resultados deste trabalho comprovam de forma geral, de que a georreferenciação dos dados eleitorais nacionais geram uma cartografia que permite confirmar aquilo que outras análises têm vindo a mostrar sobre o comportamento eleitoral dos portugueses. No entanto, existem aspectos específicos da distribuição espacial deste mesmo comportamento eleitoral que permitem aprofundar o conhecimento sobre a interacção entre o espaço e os processos eleitorais.

Contributions towards smart cities : exploring block level census data for the characterization of change in Lisbon

The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.

Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

Notch signaling in hematopoiesis and lymphopoiesis: lessons from Drosophila.

The evolutionarily conserved Notch signaling pathway regulates a broad spectrum of cell fate decisions and differentiation processes during fetal and postnatal life. It is involved in embryonic organogenesis as well as in the maintenance of homeostasis of self-renewing systems. In this article, we review the role of Notch signaling in the hematopoietic system with particular emphasis on lymphocyte development and highlight the similarities in Notch function between Drosophila and mammalian differentiation processes. Recent studies indicating that aberrant NOTCH signaling is frequently linked to the induction of T leukemia in humans will also be discussed.

Obtenció de jerarquies d'estats cel·lulars via web

Hi ha diversos mètodes d'anàlisi que duen a terme una agrupació global de la sèries de mostres de microarrays, com SelfOrganizing Maps, o que realitzen agrupaments locals tenint en compte només un subconjunt de gens coexpressats, com Biclustering, entre d'altres. En aquest projecte s'ha desenvolupat una aplicació web: el PCOPSamplecl, és una eina que pertany als mètodes d'agrupació (clustering) local, que no busca subconjunts de gens coexpresats (anàlisi de relacions linials), si no parelles de gens que davant canvis fenotípics, la seva relació d'expressió pateix fluctuacions. El resultats del PCOPSamplecl seràn les diferents distribucions finals de clusters i les parelles de gens involucrades en aquests canvis fenotípics. Aquestes parelles de gens podràn ser estudiades per trobar la causa i efecte del canvi fenotípic. A més, l'eina facilita l'estudi de les dependències entre les diferents distribucions de clusters que proporciona l'aplicació per poder estudiar la intersecció entre clusters o l'aparició de subclusters (2 clusters d'una mateixa agrupació de clusters poden ser subclusters d'altres clusters de diferents distribucions de clusters). L'eina és disponible al servidor: http://revolutionresearch.uab.es/

Myosin Vs organize actin cables in fission yeast.

Myosin V motors are believed to contribute to cell polarization by carrying cargoes along actin tracks. In Schizosaccharomyces pombe, Myosin Vs transport secretory vesicles along actin cables, which are dynamic actin bundles assembled by the formin For3 at cell poles. How these flexible structures are able to extend longitudinally in the cell through the dense cytoplasm is unknown. Here we show that in myosin V (myo52 myo51) null cells, actin cables are curled, bundled, and fail to extend into the cell interior. They also exhibit reduced retrograde flow, suggesting that formin-mediated actin assembly is impaired. Myo52 may contribute to actin cable organization by delivering actin regulators to cell poles, as myoV defects are partially suppressed by diverting cargoes toward cell tips onto microtubules with a kinesin 7-Myo52 tail chimera. In addition, Myo52 motor activity may pull on cables to provide the tension necessary for their extension and efficient assembly, as artificially tethering actin cables to the nuclear envelope via a Myo52 motor domain restores actin cable extension and retrograde flow in myoV mutants. Together these in vivo data reveal elements of a self-organizing system in which the motors shape their own tracks by transporting cargoes and exerting physical pulling forces.

A mi què m'expliques?

Els alumnes i les alumnes de primer cicle d'ESO s'enfronten amb les dificultats de la nova etapa i la necessitat de demostrar les seves competències lingüístiques, quant al redactat i la correcció en l'elaboració de textos diversos. Les noves tecnologies de la informació i la comunicació poden ajudar (i han de propiciar-ho) a desenvolupar aquestes capacitats, i han de ser un element motivador perquè els nois i les noies sentin la necessitat de crear produccions escrites pròpies, adequades lingüísticament, coherents i amb les idees ben organitzades.És necessari, a més, que l'avaluació d'aquestes tasques els serveixi per millorar l'expressió en llengua catalana, gramaticalment i ortogràficament, tot ajudant-los a establir sistemes d'autocorrecció i rectificació d'errors.L'exposició pública (en un mitjà com el d'internet) de les seves obres hauria de reblar l'aspecte de la motivació en la creació d'escrits, de manera que els aporti noves expectatives de comunicació i els animi a participar de l'espai virtual que els ofereix aquesta finestra oberta al món. El meu treball té la intenció de ser un projecte educatiu per aconseguir una millora en l'expressió escrita dels alumnes del primer curs d'ESO amb l'ajuda de les eines de les Tecnologies de la Informació i la Comunicació.

Clinical performance of cervical restorations: a meta-analysis.

OBJECTIVES: To carry out a meta-analysis in order to assess the influencing factors on retention loss and marginal discoloration of cervical restorations made of composites and glass ionomer (derivates). METHODS: The literature was searched for prospective clinical studies on cervical restorations with an observation period of at least 18 months. RESULTS: Fifty clinical studies involving 40 adhesive systems matched the inclusion criteria. On average, 10% of the cervical fillings were lost and 24% exhibited marginal discoloration after 3 years. The variability ranged from 0% to 50% for retention loss and from 0% to 74% for marginal discoloration. Hardly any secondary caries was detected. When linear mixed models with a study and experiment effect were used, the analysis revealed that the adhesive/restorative class had the most significant influence, with 2-step self-etching adhesive systems performing best and 1-step self-etching adhesive systems performing worst; 3-step etch-and-rinse systems, glass ionomers/resin-modified glass ionomers, 2-step etch-and-rinse systems and polyacid-modified resin composites were ranked in between. Restorations placed in teeth whose dentin/enamel had been prepared/roughened showed a statistically significant higher retention rate than those placed in teeth with unprepared dentin (p<0.05). Beveling of the enamel and the type of isolation used (rubberdam/cotton rolls) had no significant influence. SIGNIFICANCE: The clinical performance of cervical restorations is significantly influenced by the type of adhesive system used and/or the adhesive class to which the system belonged and whether the dentin/enamel is prepared or not. 2-Step self-etching- and 3-step etch&rinse systems shall be chosen over 1-step self-etching systems and glass ionomer derivates. The dentin (and enamel) surface shall be roughened before placement of the restoration.

The Tea4-PP1 landmark promotes local growth by dual Cdc42 GEF recruitment and GAP exclusion.

Cell polarization relies on small GTPases, such as Cdc42, which can break symmetry through self-organizing principles, and landmarks that define the axis of polarity. In fission yeast, microtubules deliver the Tea1-Tea4 complex to mark cell poles for growth, but how this complex activates Cdc42 is unknown. Here, we show that ectopic targeting of Tea4 to cell sides promotes the local activation of Cdc42 and cell growth. This activity requires that Tea4 binds the type I phosphatase (PP1) catalytic subunit Dis2 or Sds21, and ectopic targeting of either catalytic subunit is similarly instructive for growth. The Cdc42 guanine-nucleotide-exchange factor Gef1 and the GTPase-activating protein Rga4 are required for Tea4-PP1-dependent ectopic growth. Gef1 is recruited to ectopic Tea4 and Dis2 locations to promote Cdc42 activation. By contrast, Rga4 is locally excluded by Tea4, and its forced colocalization with Tea4 blocks ectopic growth, indicating that Rga4 must be present, but at sites distinct from Tea4. Thus, a Tea4-PP1 landmark promotes local Cdc42 activation and growth both through Cdc42 GEF recruitment and by creating a local trough in a Cdc42 GAP.

Bayesian image reconstruction with space-variant noise suppression

In this paper we present a Bayesian image reconstruction algorithm with entropy prior (FMAPE) that uses a space-variant hyperparameter. The spatial variation of the hyperparameter allows different degrees of resolution in areas of different statistical characteristics, thus avoiding the large residuals resulting from algorithms that use a constant hyperparameter. In the first implementation of the algorithm, we begin by segmenting a Maximum Likelihood Estimator (MLE) reconstruction. The segmentation method is based on using a wavelet decomposition and a self-organizing neural network. The result is a predetermined number of extended regions plus a small region for each star or bright object. To assign a different value of the hyperparameter to each extended region and star, we use either feasibility tests or cross-validation methods. Once the set of hyperparameters is obtained, we carried out the final Bayesian reconstruction, leading to a reconstruction with decreased bias and excellent visual characteristics. The method has been applied to data from the non-refurbished Hubble Space Telescope. The method can be also applied to ground-based images.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Paradigms of notch signaling in mammals.

Notch proteins regulate a broad spectrum of cell fate decisions and differentiation processes during fetal and postnatal life. These proteins are involved in organogenesis during embryonic development as well as in the maintenance of homeostasis of self-renewing systems. The paradigms of Notch function, such as stem and progenitor cell maintenance, lineage specification mediated by binary cell fate decisions, and induction of terminal differentiation, were initially established in invertebrates and subsequently confirmed in mammals. Moreover, aberrant Notch signaling is linked to tumorigenesis. In this review, we discuss the origin of postulated Notch functions, give examples from different mammalian organ systems, and try to relate them to the hematopoietic system.

Identification of different heart tissues from MRI C-SENC images using an unsupervised multi-stage fuzzy clustering technique.

PURPOSE: To objectively characterize different heart tissues from functional and viability images provided by composite-strain-encoding (C-SENC) MRI. MATERIALS AND METHODS: C-SENC is a new MRI technique for simultaneously acquiring cardiac functional and viability images. In this work, an unsupervised multi-stage fuzzy clustering method is proposed to identify different heart tissues in the C-SENC images. The method is based on sequential application of the fuzzy c-means (FCM) and iterative self-organizing data (ISODATA) clustering algorithms. The proposed method is tested on simulated heart images and on images from nine patients with and without myocardial infarction (MI). The resulting clustered images are compared with MRI delayed-enhancement (DE) viability images for determining MI. Also, Bland-Altman analysis is conducted between the two methods. RESULTS: Normal myocardium, infarcted myocardium, and blood are correctly identified using the proposed method. The clustered images correctly identified 90 +/- 4% of the pixels defined as infarct in the DE images. In addition, 89 +/- 5% of the pixels defined as infarct in the clustered images were also defined as infarct in DE images. The Bland-Altman results show no bias between the two methods in identifying MI. CONCLUSION: The proposed technique allows for objectively identifying divergent heart tissues, which would be potentially important for clinical decision-making in patients with MI.