NUTRISOL: un programa informático para la evaluación nutricional comunitaria y hospitalaria de acceso libre.

We have developed the computer programme NUTRISOL, a nutritional programme destined to analysis of dietary intake by means of the food transformation to nutrient. It has been performed under Windows operative system, using Visual Basic 6.0. It is presented in a CD-Rom. We have used the Spanish CSIC Food Composition Table and domestic food measures commonly used in Spain which could be modified and updated. Diverse kind of diets and reference anthropometric data are also presented. The results may be treated using various statistical programmes. The programme contains three modules: 1) Nutritional epidemiology, which allows to create or open a data base, sample management, analyse food intake, consultation of nutrient content and exportation of data to statistical programmes. 2) Analyses of diets and recipes, creation or modification of new ones. 3) To ask different diets for prevalent pathologies. Independent tools for modifying the original tables, calculate energetic needs, recommend nutrient intake and anthropometric indexes are also offered. In conclusion, NUTRISOL Programme is an application which runs in PC computers with minimal equipment in a friendly interface, of easy use, freeware, which may be adapted to each country, and has demonstrated its usefulness and reliability in different epidemiologic studies. Furthermore, it may become an efficient instrument for clinical nutrition and health promotion.

Liver safety assessment: required data elements and best practices for data collection and standardization in clinical trials.

A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials. In a breakout session, workshop attendees discussed necessary data elements and standards for the accurate measurement of DILI risk associated with new therapeutic agents in clinical trials. There was agreement that in order to achieve this goal the systematic acquisition of protocol-specified clinical measures and lab specimens from all study subjects is crucial. In addition, standard DILI terms that address the diverse clinical and pathologic signatures of DILI were considered essential. There was a strong consensus that clinical and lab analyses necessary for the evaluation of cases of acute liver injury should be consistent with the US Food and Drug Administration (FDA) guidance on pre-marketing risk assessment of DILI in clinical trials issued in 2009. A recommendation that liver injury case review and management be guided by clinicians with hepatologic expertise was made. Of note, there was agreement that emerging DILI signals should prompt the systematic collection of candidate pharmacogenomic, proteomic and/or metabonomic biomarkers from all study subjects. The use of emerging standardized clinical terminology, CRFs and graphic tools for data review to enable harmonization across clinical trials was strongly encouraged. Many of the recommendations made in the breakout session are in alignment with those made in the other parallel sessions on methodology to assess clinical liver safety data, causality assessment for suspected DILI, and liver safety assessment in special populations (hepatitis B, C, and oncology trials). Nonetheless, a few outstanding issues remain for future consideration.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Fracture imaging within a granitic rock aquifer using multiple-offset single-hole and cross-hole GPR reflection data

The sparsely spaced highly permeable fractures of the granitic rock aquifer at Stang-er-Brune (Brittany, France) form a well-connected fracture network of high permeability but unknown geometry. Previous work based on optical and acoustic logging together with single-hole and cross-hole flowmeter data acquired in 3 neighbouring boreholes (70-100 m deep) has identified the most important permeable fractures crossing the boreholes and their hydraulic connections. To constrain possible flow paths by estimating the geometries of known and previously unknown fractures, we have acquired, processed and interpreted multifold, single- and cross-hole GPR data using 100 and 250 MHz antennas. The GPR data processing scheme consisting of timezero corrections, scaling, bandpass filtering and F-X deconvolution, eigenvector filtering, muting, pre-stack Kirchhoff depth migration and stacking was used to differentiate fluid-filled fracture reflections from source generated noise. The final stacked and pre-stack depth-migrated GPR sections provide high-resolution images of individual fractures (dipping 30-90°) in the surroundings (2-20 m for the 100 MHz antennas; 2-12 m for the 250 MHz antennas) of each borehole in a 2D plane projection that are of superior quality to those obtained from single-offset sections. Most fractures previously identified from hydraulic testing can be correlated to reflections in the single-hole data. Several previously unknown major near vertical fractures have also been identified away from the boreholes.

Probabilistic base calling of Solexa sequencing data.

BACKGROUND: Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology. RESULTS: We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. CONCLUSION: We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.

Tree-based message diffusion for managing replicated data in unreliable and resource-constrained peer-to-peer environment

Abstract This thesis proposes a set of adaptive broadcast solutions and an adaptive data replication solution to support the deployment of P2P applications. P2P applications are an emerging type of distributed applications that are running on top of P2P networks. Typical P2P applications are video streaming, file sharing, etc. While interesting because they are fully distributed, P2P applications suffer from several deployment problems, due to the nature of the environment on which they perform. Indeed, defining an application on top of a P2P network often means defining an application where peers contribute resources in exchange for their ability to use the P2P application. For example, in P2P file sharing application, while the user is downloading some file, the P2P application is in parallel serving that file to other users. Such peers could have limited hardware resources, e.g., CPU, bandwidth and memory or the end-user could decide to limit the resources it dedicates to the P2P application a priori. In addition, a P2P network is typically emerged into an unreliable environment, where communication links and processes are subject to message losses and crashes, respectively. To support P2P applications, this thesis proposes a set of services that address some underlying constraints related to the nature of P2P networks. The proposed services include a set of adaptive broadcast solutions and an adaptive data replication solution that can be used as the basis of several P2P applications. Our data replication solution permits to increase availability and to reduce the communication overhead. The broadcast solutions aim, at providing a communication substrate encapsulating one of the key communication paradigms used by P2P applications: broadcast. Our broadcast solutions typically aim at offering reliability and scalability to some upper layer, be it an end-to-end P2P application or another system-level layer, such as a data replication layer. Our contributions are organized in a protocol stack made of three layers. In each layer, we propose a set of adaptive protocols that address specific constraints imposed by the environment. Each protocol is evaluated through a set of simulations. The adaptiveness aspect of our solutions relies on the fact that they take into account the constraints of the underlying system in a proactive manner. To model these constraints, we define an environment approximation algorithm allowing us to obtain an approximated view about the system or part of it. This approximated view includes the topology and the components reliability expressed in probabilistic terms. To adapt to the underlying system constraints, the proposed broadcast solutions route messages through tree overlays permitting to maximize the broadcast reliability. Here, the broadcast reliability is expressed as a function of the selected paths reliability and of the use of available resources. These resources are modeled in terms of quotas of messages translating the receiving and sending capacities at each node. To allow a deployment in a large-scale system, we take into account the available memory at processes by limiting the view they have to maintain about the system. Using this partial view, we propose three scalable broadcast algorithms, which are based on a propagation overlay that tends to the global tree overlay and adapts to some constraints of the underlying system. At a higher level, this thesis also proposes a data replication solution that is adaptive both in terms of replica placement and in terms of request routing. At the routing level, this solution takes the unreliability of the environment into account, in order to maximize reliable delivery of requests. At the replica placement level, the dynamically changing origin and frequency of read/write requests are analyzed, in order to define a set of replica that minimizes communication cost.

Sleep deprivation effects on circadian clock gene expression in the cerebral cortex parallel electroencephalographic differences among mouse strains.

Sleep deprivation (SD) results in increased electroencephalographic (EEG) delta power during subsequent non-rapid eye movement sleep (NREMS) and is associated with changes in the expression of circadian clock-related genes in the cerebral cortex. The increase of NREMS delta power as a function of previous wake duration varies among inbred mouse strains. We sought to determine whether SD-dependent changes in circadian clock gene expression parallel this strain difference described previously at the EEG level. The effects of enforced wakefulness of incremental durations of up to 6 h on the expression of circadian clock genes (bmal1, clock, cry1, cry2, csnk1epsilon, npas2, per1, and per2) were assessed in AKR/J, C57BL/6J, and DBA/2J mice, three strains that exhibit distinct EEG responses to SD. Cortical expression of clock genes subsequent to SD was proportional to the increase in delta power that occurs in inbred strains: the strain that exhibits the most robust EEG response to SD (AKR/J) exhibited dramatic increases in expression of bmal1, clock, cry2, csnkIepsilon, and npas2, whereas the strain with the least robust response to SD (DBA/2) exhibited either no change or a decrease in expression of these genes and cry1. The effect of SD on circadian clock gene expression was maintained in mice in which both of the cryptochrome genes were genetically inactivated. cry1 and cry2 appear to be redundant in sleep regulation as elimination of either of these genes did not result in a significant deficit in sleep homeostasis. These data demonstrate transcriptional regulatory correlates to previously described strain differences at the EEG level and raise the possibility that genetic differences underlying circadian clock gene expression may drive the EEG differences among these strains.

Parallel imaging with phase scrambling.

PURPOSE: Most existing methods for accelerated parallel imaging in MRI require additional data, which are used to derive information about the sensitivity profile of each radiofrequency (RF) channel. In this work, a method is presented to avoid the acquisition of separate coil calibration data for accelerated Cartesian trajectories. METHODS: Quadratic phase is imparted to the image to spread the signals in k-space (aka phase scrambling). By rewriting the Fourier transform as a convolution operation, a window can be introduced to the convolved chirp function, allowing a low-resolution image to be reconstructed from phase-scrambled data without prominent aliasing. This image (for each RF channel) can be used to derive coil sensitivities to drive existing parallel imaging techniques. As a proof of concept, the quadratic phase was applied by introducing an offset to the x(2) - y(2) shim and the data were reconstructed using adapted versions of the image space-based sensitivity encoding and GeneRalized Autocalibrating Partially Parallel Acquisitions algorithms. RESULTS: The method is demonstrated in a phantom (1 × 2, 1 × 3, and 2 × 2 acceleration) and in vivo (2 × 2 acceleration) using a 3D gradient echo acquisition. CONCLUSION: Phase scrambling can be used to perform parallel imaging acceleration without acquisition of separate coil calibration data, demonstrated here for a 3D-Cartesian trajectory. Further research is required to prove the applicability to other 2D and 3D sampling schemes. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

Inherently self-calibrating non-Cartesian parallel imaging.

The use of self-calibrating techniques in parallel magnetic resonance imaging eliminates the need for coil sensitivity calibration scans and avoids potential mismatches between calibration scans and subsequent accelerated acquisitions (e.g., as a result of patient motion). Most examples of self-calibrating Cartesian parallel imaging techniques have required the use of modified k-space trajectories that are densely sampled at the center and more sparsely sampled in the periphery. However, spiral and radial trajectories offer inherent self-calibrating characteristics because of their densely sampled center. At no additional cost in acquisition time and with no modification in scanning protocols, in vivo coil sensitivity maps may be extracted from the densely sampled central region of k-space. This work demonstrates the feasibility of self-calibrated spiral and radial parallel imaging using a previously described iterative non-Cartesian sensitivity encoding algorithm.

Three small RNAs jointly ensure secondary metabolism and biocontrol in Pseudomonas fluorescens CHA0.

In many Gram-negative bacteria, the GacS/GacA two-component system positively controls the expression of extracellular products or storage compounds. In the plant-beneficial rhizosphere bacterium Pseudomonas fluorescens CHA0, the GacS/GacA system is essential for the production of antibiotic compounds and hence for biological control of root-pathogenic fungi. The small (119-nt) RNA RsmX discovered in this study, together with RsmY and RsmZ, forms a triad of GacA-dependent small RNAs, which sequester the RNA-binding proteins RsmA and RsmE and thereby antagonize translational repression exerted by these proteins in strain CHA0. This small RNA triad was found to be both necessary and sufficient for posttranscriptional derepression of biocontrol factors and for protection of cucumber from Pythium ultimum. The same three small RNAs also positively regulated swarming motility and the synthesis of a quorum-sensing signal, which is unrelated to N-acyl-homoserine lactones, and which autoinduces the Gac/Rsm cascade. Expression of RsmX and RsmY increased in parallel throughout cell growth, whereas RsmZ was produced during the late growth phase. This differential expression is assumed to facilitate fine tuning of GacS/A-controlled cell population density-dependent regulation in P. fluorescens.

Extracção de areia na praia de Calhetona (Ilha de Santiago, Cabo Verde): causas, processos e consequências

A extracção clandestina de areia, nas faixas costeiras e nos leitos das ribeiras, tem sido prática de muitos agregados familiares cabo-verdianos. Nas últimas décadas, a praia de Calhetona (Ilha de Santiago) foi um dos muitos locais que sofreram degradação ambiental significativa, devido à realização desta actividade sem quaisquer planos de extracção e de posterior recuperação das áreas degradadas. Este trabalho, através da conjugação de recolha de dados por inquérito, observação directa e pesquisa documental e bibliográfica, teve como objectivos a caracterização da comunidade (que habita no bairro de Ponta Calhetona) que se dedica à extracção de areia na praia de Calhetona, a descrição da dinâmica da actividade extractiva, a avaliação da percepção que a comunidade tem relativamente às consequências da sua actividade e a descrição do impacte ambiental resultante da extracção de areia. Da análise dos inquéritos, efectuados em Fevereiro de 2012, a 25 chefes de agregados familiares que efectuam a extracção de areia na praia de Calhetona, constata-se que estes são maioritariamente mulheres, predominantemente com idade compreendida entre os 40 e os 59 anos, domésticas, com baixa escolaridade, com famílias numerosas e/ou alargadas a seu cargo e dedicando-se à extração de areia à mais de 10 anos. Os inquiridos, face à situação de vulnerabilidade económica, à falta de emprego e à grande procura de areia para a construção civil, vêem nesta actividade uma fonte de rendimento. Contudo, o proveito obtido desta actividade difícil e potencialmente perigosa é reduzido. Quem efectivamente beneficia são os camionistas que compram a areia a quem procede à extracção e a vendem ao consumidor final pelo dobro do preço. Os inquiridos demonstram uma consciência generalizada dos diversos impactes ambientais negativos resultantes da sua actividade, mas alegam que a extracção de areia é uma das poucas alternativas existentes para providenciar o sustento dos seus agregados familiares. Com base na comparação do estado actual da praia de Calhetona com relatos de habitantes locais, relativos às características da mesma no passado, verifica-se que nos últimos 40-50 anos, desde que se iniciou a intensa extracção de areia nesta praia, o seu aspecto físico se degradou claramente. Essa degradação caracteriza-se principalmente pelo recuo da linha de costa, pela quase ausência de areia e pela salinização dos solos localizados nas proximidades da praia, para além dos consequentes impactes negativos sobre a desova das tartarugas e o turismo balnear.

Establishment of the epithelial-specific transcriptome of normal and malignant human breast cells based on MPSS and array expression data.

INTRODUCTION: Diverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells. METHODS: Malignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays. RESULTS: MPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours. CONCLUSION: Using highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

Structural and optical properties of dilute InAsN grown by molecular beam epitaxy

We perform a structural and optical characterization of InAs1¿xNx epilayers grown by molecular beam epitaxy on InAs substrates x 2.2% . High-resolution x-ray diffraction HRXRD is used to obtain information about the crystal quality and the strain state of the samples and to determine the N content of the films. The composition of two of the samples investigated is also obtained with time-of-flight secondary ion mass spectroscopy ToF-SIMS measurements. The combined analysis of the HRXRD and ToF-SIMS data suggests that the lattice parameter of InAsN might significantly deviate from Vegard"s law. Raman scattering and far-infrared reflectivity measurements have been carried out to investigate the incorporation of N into the InAsN alloy. N-related local vibrational modes are detected in the samples with higher N content. The origin of the observed features is discussed. We study the compositional dependence of the room-temperature band gap energy of the InAsN alloy. For this purpose, photoluminescence and optical absorption measurements are presented. The results are analyzed in terms of the band-anticrossing BAC model. We find that the room-temperature coupling parameter for InAsN within the BAC model is CNM=2.0 0.1 eV.

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.

On the use of spatially discrete data to compute energy and mass balance

In many practical applications the state of field soils is monitored by recording the evolution of temperature and soil moisture at discrete depths. We theoretically investigate the systematic errors that arise when mass and energy balances are computed directly from these measurements. We show that, even with no measurement or model errors, large residuals might result when finite difference approximations are used to compute fluxes and storage term. To calculate the limits set by the use of spatially discrete measurements on the accuracy of balance closure, we derive an analytical solution to estimate the residual on the basis of the two key parameters: the penetration depth and the distance between the measurements. When the thickness of the control layer for which the balance is computed is comparable to the penetration depth of the forcing (which depends on the thermal diffusivity and on the forcing period) large residuals arise. The residual is also very sensitive to the distance between the measurements, which requires accurately controlling the position of the sensors in field experiments. We also demonstrate that, for the same experimental setup, mass residuals are sensitively larger than the energy residuals due to the nonlinearity of the moisture transport equation. Our analysis suggests that a careful assessment of the systematic mass error introduced by the use of spatially discrete data is required before using fluxes and residuals computed directly from field measurements.