Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Enquête sur les pratiques de gouvernance des systèmes d'information en matière de stratégie pilotage et organisation

Résumé Si l'impact de l'informatique ne fait généralement pas de doute, il est souvent plus problématique d'en mesurer sa valeur. Les Directeurs des Systèmes d'Information (DSI) expliquent l'absence de schéma directeur et de vision à moyen et long terme de l'entreprise, par un manque de temps et de ressources mais aussi par un défaut d'implication des directions générales et des directions financières. L'incapacité de mesurer précisément la valeur du système d'information engendre une logique de gestion par les coûts, néfaste à l'action de la DSI. Alors qu'une mesure de la valeur économique de l'informatique offrirait aux directions générales la matière leur permettant d'évaluer réellement la maturité et la contribution de leur système d'information. L'objectif de cette thèse est d'évaluer à la fois l'alignement de l'informatique avec la stratégie de l'entreprise, la qualité du pilotage (mesure de performance) des systèmes d'information, et enfin, l'organisation et le positionnement de la fonction informatique dans l'entreprise. La mesure de ces trois éléments clés de la gouvernance informatique a été réalisée par l'intermédiaire de deux vagues d'enquêtes successives menées en 2000/2001 (DSI) et 2002/2003 (DSI et DG) en Europe francophone (Suisse Romande, France, Belgique et Luxembourg). Abstract The impact of Information Technology (IT) is today a clear evidence to company stakeholders. However, measuring the value generated by IT is a real challenge. Chief Information Officers (CIO) explain the absence of solid IT Business Plans and clear mid/long term visions by a lack of time and resources but also by a lack of involvement of business senior management (e.g. CEO and CFO). Thus, being not able to measure the economic value of IT, the CIO will have to face the hard reality of permanent cost pressures and cost reductions to justify IT spending and investments. On the other side, being able to measure the value of IT would help CIO and senior business management to assess the maturity and the contribution of the Information System and therefore facilitate the decision making process. The objective of this thesis is to assess the alignment of IT with the business strategy, to assess the quality of measurement of the Information System and last but not least to assess the positioning of the IT organisation within the company. The assessment of these three key elements of the IT Governance was established with two surveys (first wave in 2000/2001 for CIO, second wave in 2002/2003 for CIO and CEO) in Europe (French speaking countries namely Switzerland, France, Belgium and Luxembourg).

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Peripheral blood fibrocytes: new information to explain the dynamics of Leishmania infection

Fibrocytes are important for understanding the progression of many diseases because they are present in areas where pathogenic lesions are generated. However, the morphology of fibrocytes and their interactions with parasites are poorly understood. In this study, we examined the morphology of peripheral blood fibrocytes and their interactions with Leishmania (L.) amazonensis . Through ultrastructural analysis, we describe the details of fibrocyte morphology and how fibrocytes rapidly internaliseLeishmania promastigotes. The parasites differentiated into amastigotes after 2 h in phagolysosomes and the infection was completely resolved after 72 h. Early in the infection, we found increased nitric oxide production and large lysosomes with electron-dense material. These factors may regulate the proliferation and death of the parasites. Because fibrocytes are present at the infection site and are directly involved in developing cutaneous leishmaniasis, they are targets for effective, non-toxic cell-based therapies that control and treat leishmaniasis.

Estimating Gross Value Added (GVA) across multiple scales: theoretical approach and empirical validation

This paper presents an application of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to the estimation of quantities of Gross Value Added (GVA) referring to economic entities defined at different scales of study. The method first estimates benchmark values of the pace of GVA generation per hour of labour across economic sectors. These values are estimated as intensive variables –e.g. €/hour– by dividing the various sectorial GVA of the country (expressed in € per year) by the hours of paid work in that same sector per year. This assessment is obtained using data referring to national statistics (top down information referring to the national level). Then, the approach uses bottom-up information (the number of hours of paid work in the various economic sectors of an economic entity –e.g. a city or a province– operating within the country) to estimate the amount of GVA produced by that entity. This estimate is obtained by multiplying the number of hours of work in each sector in the economic entity by the benchmark value of GVA generation per hour of work of that particular sector (national average). This method is applied and tested on two different socio-economic systems: (i) Catalonia (considered level n) and Barcelona (considered level n-1); and (ii) the region of Lima (considered level n) and Lima Metropolitan Area (considered level n-1). In both cases, the GVA per year of the local economic entity –Barcelona and Lima Metropolitan Area – is estimated and the resulting value is compared with GVA data provided by statistical offices. The empirical analysis seems to validate the approach, even though the case of Lima Metropolitan Area indicates a need for additional care when dealing with the estimate of GVA in primary sectors (agriculture and mining).

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Integrating forensic information in a crime intelligence database

Since 2008, Intelligence units of six states of the western part of Switzerland have been sharing a common database for the analysis of high volume crimes. On a daily basis, events reported to the police are analysed, filtered and classified to detect crime repetitions and interpret the crime environment. Several forensic outcomes are integrated in the system such as matches of traces with persons, and links between scenes detected by the comparison of forensic case data. Systematic procedures have been settled to integrate links assumed mainly through DNA profiles, shoemarks patterns and images. A statistical outlook on a retrospective dataset of series from 2009 to 2011 of the database informs for instance on the number of repetition detected or confirmed and increased by forensic case data. Time needed to obtain forensic intelligence in regard with the type of marks treated, is seen as a critical issue. Furthermore, the underlying integration process of forensic intelligence into the crime intelligence database raised several difficulties in regards of the acquisition of data and the models used in the forensic databases. Solutions found and adopted operational procedures are described and discussed. This process form the basis to many other researches aimed at developing forensic intelligence models.

The encouragement of the open access movement: an essential realm for health information professionals in the 21st century

According to the Bethesda Statement on Open Access Policy for libraries and the recommendations of the BOAI10, libraries and librarians have an important role to fulfil in the encouragement of open access. Taking into account the Competencies for Information Professionals of the 21st Century, elaborated by the Special Libraries Association, and the Librarians’ Competencies Profile for Scholarly Publishing and Open Access, we shall identify the competencies and new areas of knowledge and expertise that have been involved in the process of the development and upkeep of our institutional repository (Repositorio SSPA).

From the “Mining Triangle” to the “Greater Region“ (“Großregion”/”Grande Région”). The Institutionalisation of the “SaarLorLux” Euroregion

Gairebé 182 milions d'ciutadans de la Unió Europea (= 37,5% de la població total) viuen en aproximadament 130 regions frontereres i transfrontereres. Aquestes regions contribueixen significativament al procés d'integració europea. Aquesta importància es documenta pel paquet dels Fons Estructurals 2007-2013, que ha estat presentat per la Comissió Europea i que va ser aprovat recentment pel Parlament Europeu. Considerant que la UE ha gastat uns 4875 € milions per a la cooperació transfronterera, transnacional i interregional en el marc de la iniciativa Interreg per al període 2000-2006, la cooperació territorial europea es convertirà en un dels tres objectius dels fons estructurals i rebrà € 7750000000 (5,57 milions d'euros per a la cooperació transfronterera només) per al període 2007-2013 (Comissió Europea, 2006a, 2006b). A part d'això, un nou conjunt de normes per a l'establiment d'una "agrupació europea de cooperació territorial" (AECT) ha estat adoptat i que facilitarà la cooperació transboundray, transnacional i interregional a la UE. Aquest treball s'ocuparà de les estructures de la institucionalització, la presa de decisions i l'execució i les polítiques de la "Gran Regió" / "Großregion" (d'ara endavant: GR o Gran Regió).

Malaria in gold-mining areas in Colombia

Gold-mining may play an important role in the maintenance of malaria worldwide. Gold-mining, mostly illegal, has significantly expanded in Colombia during the last decade in areas with limited health care and disease prevention. We report a descriptive study that was carried out to determine the malaria prevalence in gold-mining areas of Colombia, using data from the public health surveillance system (National Health Institute) during the period 2010-2013. Gold-mining was more prevalent in the departments of Antioquia, Córdoba, Bolívar, Chocó, Nariño, Cauca, and Valle, which contributed 89.3% (270,753 cases) of the national malaria incidence from 2010-2013 and 31.6% of malaria cases were from mining areas. Mining regions, such as El Bagre, Zaragoza, and Segovia, in Antioquia, Puerto Libertador and Montelíbano, in Córdoba, and Buenaventura, in Valle del Cauca, were the most endemic areas. The annual parasite index (API) correlated with gold production (R2 0.82, p < 0.0001); for every 100 kg of gold produced, the API increased by 0.54 cases per 1,000 inhabitants. Lack of malaria control activities, together with high migration and proliferation of mosquito breeding sites, contribute to malaria in gold-mining regions. Specific control activities must be introduced to control this significant source of malaria in Colombia.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified