Effect of fibers and whole grain content on quality attributes

Incorporation of fiber in cereals may lead to quality issues, thus decreasing consumer acceptance. This is partially due to deterioration of the microstructure, one of the primary quality attributes of cereals. The objective of this study was to better understand the mechanisms by which dietary fibers affect the quality of cereal products during extrusioncooking. The study quantified the effect of amount and type of fiber and whole grain on (i) texture, (ii) structure, and (iii) rehydration properties of extruded cereals. New innovative methods were applied and combined with traditional techniques to characterize both the structure and the rehydration properties. Extruded cereals were produced using a starch-based recipe (whole and wheat flours) and two sources of fibers (oat bran concentrate and wheat bran). The oat and wheat bran levels used in this study were 0, 10, and 20%. The different mixtures were extruded in a pilot twinscrew extruder BC21 (Clextral) and then sugar coated after drying. Mechanical properties of extruded cereals were investigated by compression test. The cellular structure was observed by X-ray tomography. The quality of coating (thickness, homogeneity) was analyzed by optical coherence tomography. The rehydration properties of such cereals in milk were evaluated by magnetic resonance imaging and optical coherence tomography. This work revealed that structure assessment of extruded cereals may lead to a better understanding of the effect of fiber addition on texture and rehydration properties. The application of innovative methods, such as optical coherence tomography and magnetic resonance imaging, was found to be useful to quantify the structural properties.

Tools for Search Tree Visualization: The APT Tool

The control part of the execution of a constraint logic program can be conceptually shown as a search-tree, where nodes correspond to calis, and whose branches represent conjunctions and disjunctions. This tree represents the search space traversed by the program, and has also a direct relationship with the amount of work performed by the program. The nodes of the tree can be used to display information regarding the state and origin of instantiation of the variables involved in each cali. This depiction can also be used for the enumeration process. These are the features implemented in APT, a tool which runs constraint logic programs while depicting a (modified) search-tree, keeping at the same time information about the state of the variables at every moment in the execution. This information can be used to replay the execution at will, both forwards and backwards in time. These views can be abstracted when the size of the execution requires it. The search-tree view is used as a framework onto which constraint-level visualizations (such as those presented in the following chapter) can be attached.

A generic preprocessor for program validation and debugging

We present a generic preprocessor for combined static/dynamic validation and debugging of constraint logic programs. Passing programs through the preprocessor prior to execution allows detecting many bugs automatically. This is achieved by performing a repertoire of tests which range from simple syntactic checks to much more advanced checks based on static analysis of the program. Together with the program, the user may provide a series of assertions which trigger further automatic checking of the program. Such assertions are written using the assertion language presented in Chapter 2, which allows expressing a wide variety of properties. These properties extend beyond the predefined set which may be understandable by the available static analyzers and include properties defined by means of user programs. In addition to user-provided assertions, in each particular CLP system assertions may be available for predefined system predicates. Checking of both user-provided assertions and assertions for system predicates is attempted first at compile-time by comparing them with the results of static analysis. This may allow statically proving that the assertions hold (Le., they are validated) or that they are violated (and thus bugs detected). User-provided assertions (or parts of assertions) which cannot be statically proved ñor disproved are optionally translated into run-time tests. The implementation of the preprocessor is generic in that it can be easily customized to different CLP systems and dialects and in that it is designed to allow the integration of additional analyses in a simple way. We also report on two tools which are instances of the generic preprocessor: CiaoPP (for the Ciao Prolog system) and CHIPRE (for the CHIP CLP(FL>) system). The currently existing analyses include types, modes, non-failure, determinacy, and computational cost, and can treat modules separately, performing incremental analysis.

Debugging of constraint programs: The DiSCiPl methodology and tools

This introduction gives a general perspective of the debugging methodology and the tools developed in the ESPRIT IV project DiSCiPl Debugging Systems for Constraint Programming. It has been prepared by the editors of this volume by substantial rewriting of the DiSCiPl deliverable CP Debugging Tools [1]. This introduction is organised as follows. Section 1 outlines the DiSCiPl view of debugging, its associated debugging methodology, and motivates the kinds of tools proposed: the assertion based tools, the declarative diagnoser and the visualisation tools. Sections 2 through 4 provide a short presentation of the tools of each kind. Finally, Section 5 presents a summary of the tools developed in the project. This introduction gives only a general view of the DiSCiPl debugging methodology and tools. For details and for specific bibliographic referenees the reader is referred to the subsequent chapters.

Tools for constraint visualization: The VIFID/TRIFID tool

Visualization of program executions has been used in applications which include education and debugging. However, traditional visualization techniques often fall short of expectations or are altogether inadequate for new programming paradigms, such as Constraint Logic Programming (CLP), whose declarative and operational semantics differ in some crucial ways from those of other paradigms. In particular, traditional ideas regarding the behavior of data often cannot be lifted in a straightforward way to (C)LP from other families of programming languages. In this chapter we discuss techniques for visualizing data evolution in CLP. We briefly review some previously proposed visualization paradigms, and also propose a number of (to our knowledge) novel ones. The graphical representations have been chosen based on the perceived needs of a programmer trying to analyze the behavior and characteristics of an execution. In particular, we concéntrate on the representation of the run-time valúes of the variables, and the constraints among them. Given our interest in visualizing large executions, we also pay attention to abstraction techniques, i.e., techniques which are intended to help in reducing the complexity of the visual information.

Spatio-temporal filtering with morphological operators for robust cell migration estimation in "in-vivo" images

The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the "in-toto" reconstruction based on different modalities of "in-vivo" imaging techniques -spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive manual interaction -time and human resources- is always required to enforce coherence. Because of this limitation it is necessary to restrict the experiments or assume an uncontrolled error rate. Is it possible to obtain automated reliable measurements of migration? can we provide a seed for biologists to complete cell lineages efficiently? We propose a filtering technique that considers trajectories as spatio-temporal connected structures that prunes out those that might introduce noise and false positives by using multi-dimensional morphological operators.

Merging person-specific bio-markers for predicting oral cancer recurrence through an ontology

One of the major problems related to cancer treatment is its recurrence. Without knowing in advance how likely the cancer will relapse, clinical practice usually recommends adjuvant treatments that have strong side effects. A way to optimize treatments is to predict the recurrence probability by analyzing a set of bio-markers. The NeoMark European project has identified a set of preliminary bio-markers for the case of oral cancer by collecting a large series of data from genomic, imaging, and clinical evidence. This heterogeneous set of data needs a proper representation in order to be stored, computed, and communicated efficiently. Ontologies are often considered the proper mean to integrate biomedical data, for their high level of formality and for the need of interoperable, universally accepted models. This paper presents the NeoMark system and how an ontology has been designed to integrate all its heterogeneous data. The system has been validated in a pilot in which data will populate the ontology and will be made public for further research.

Brain tissue segmentation on Diffusion Weighted Magnetic Resonance data

Introduction Diffusion weighted Imaging (DWI) techniques are able to measure, in vivo and non-invasively, the diffusivity of water molecules inside the human brain. DWI has been applied on cerebral ischemia, brain maturation, epilepsy, multiple sclerosis, etc. [1]. Nowadays, there is a very high availability of these images. DWI allows the identification of brain tissues, so its accurate segmentation is a common initial step for the referred applications. Materials and Methods We present a validation study on automated segmentation of DWI based on the Gaussian mixture and hidden Markov random field models. This methodology is widely solved with iterative conditional modes algorithm, but some studies suggest [2] that graph-cuts (GC) algorithms improve the results when initialization is not close to the final solution. We implemented a segmentation tool integrating ITK with a GC algorithm [3], and a validation software using fuzzy overlap measures [4]. Results Segmentation accuracy of each tool is tested against a gold-standard segmentation obtained from a T1 MPRAGE magnetic resonance image of the same subject, registered to the DWI space. The proposed software shows meaningful improvements by using the GC energy minimization approach on DTI and DSI (Diffusion Spectrum Imaging) data. Conclusions The brain tissues segmentation on DWI is a fundamental step on many applications. Accuracy and robustness improvements are achieved with the proposed software, with high impact on the application’s final result.

Simulation-based evaluation of susceptibility distortion correction methods in diffusion MRI for connectivity analysis

Connectivity analysis on diffusion MRI data of the whole-brain suffers from distortions caused by the standard echo-planar imaging acquisition strategies. These images show characteristic geometrical deformations and signal destruction that are an important drawback limiting the success of tractography algorithms. Several retrospective correction techniques are readily available. In this work, we use a digital phantom designed for the evaluation of connectivity pipelines. We subject the phantom to a “theoretically correct” and plausible deformation that resembles the artifact under investigation. We correct data back, with three standard methodologies (namely fieldmap-based, reversed encoding-based, and registration- based). Finally, we rank the methods based on their geometrical accuracy, the dropout compensation, and their impact on the resulting connectivity matrices.

3D Frangi-based lung vessel enhancement filter penalizing airways

This paper describes a fully automatic simultaneous lung vessel and airway enhancement filter. The approach consists of a Frangi-based multiscale vessel enhancement filtering specifically designed for lung vessel and airway detection, where arteries and veins have high contrast with respect to the lung parenchyma, and airway walls are hollow tubular structures with a non negative response using the classical Frangi's filter. The features extracted from the Hessian matrix are used to detect centerlines and approximate walls of airways, decreasing the filter response in those areas by applying a penalty function to the vesselness measure. We validate the segmentation method in 20 CT scans with different pathological states within the VESSEL12 challenge framework. Results indicate that our approach obtains good results, decreasing the number of false positives in airway walls.

QuantiDOPA: A Quantification Software for Dopaminergic Neurotransmission SPECT

Quantification of neurotransmission Single-Photon Emission Computed Tomography (SPECT) studies of the dopaminergic system can be used to track, stage and facilitate early diagnosis of the disease. The aim of this study was to implement QuantiDOPA, a semi-automatic quantification software of application in clinical routine to reconstruct and quantify neurotransmission SPECT studies using radioligands which bind the dopamine transporter (DAT). To this end, a workflow oriented framework for the biomedical imaging (GIMIAS) was employed. QuantiDOPA allows the user to perform a semiautomatic quantification of striatal uptake by following three stages: reconstruction, normalization and quantification. QuantiDOPA is a useful tool for semi-automatic quantification inDAT SPECT imaging and it has revealed simple and flexible

Caracterización de nanopartículas magnéticas y de oro para posibles aplicaciones biomédicas en diagnóstico y terapia

Los nanomateriales han adquirido recientemente un gran interés debido a la gran variedad de aplicaciones que pueden llegar a tener en el ámbito de la biomedicina. Este trabajo recoge las posibilidades tanto diagnósticas como terapéuticas que presentan dos modalidades de nanomateriales: nanopartículas de óxido de hierro y nanopartículas de oro. Para ello, en una primera aproximación se ha llevado a cabo la caracterización de las nanopartículas desde el punto de vista de la biocompatibilidad asociada a su tamaño y al tiempo de contacto o circulación en células y tejidos, ensayada tanto in vitro como in vivo así como la cinética de acumulación de dichas nanopartículas en el organismo vivo. Posteriormente se ha realizado la biofuncionalización de los dos tipos de nanopartículas para reconocer dianas moleculares específicas y poder ser utilizadas en el futuro en dos aplicaciones biomédicas diferentes: diagnóstico de enfermedad de Alzheimer mediante imagen de resonancia magnética y destrucción selectiva de células tumorales mediante hipertermia óptica. ABSTRACT Nanomaterials have recently gained a great interest due to the variety of applications that can have in the field of biomedicine. This work covers both diagnostic and therapeutic possibilities that present two types of nanomaterials: iron oxide nanoparticles and gold nanoparticles. Therefore, in a first approximation it has performed the characterizing of nanoparticles from the standpoint of biocompatibility associated with their size and time of contact or movement in cells and tissues, tested both in vitro and in vivo as well as the kinetics of accumulation of the nanoparticles into the living organism. Subsequently the biofunctionalization of two types of nanoparticles was made to recognize specific molecular targets and can be used in the future in two different biomedical applications: diagnosis of Alzheimer's disease by magnetic resonance imaging and selective destruction of tumor cells by optical hyperthermia.

Nanoinformatics approaches for information extraction and text mining in nanomedical research texts

La nanotecnología es un área de investigación de reciente creación que trata con la manipulación y el control de la materia con dimensiones comprendidas entre 1 y 100 nanómetros. A escala nanométrica, los materiales exhiben fenómenos físicos, químicos y biológicos singulares, muy distintos a los que manifiestan a escala convencional. En medicina, los compuestos miniaturizados a nanoescala y los materiales nanoestructurados ofrecen una mayor eficacia con respecto a las formulaciones químicas tradicionales, así como una mejora en la focalización del medicamento hacia la diana terapéutica, revelando así nuevas propiedades diagnósticas y terapéuticas. A su vez, la complejidad de la información a nivel nano es mucho mayor que en los niveles biológicos convencionales (desde el nivel de población hasta el nivel de célula) y, por tanto, cualquier flujo de trabajo en nanomedicina requiere, de forma inherente, estrategias de gestión de información avanzadas. Desafortunadamente, la informática biomédica todavía no ha proporcionado el marco de trabajo que permita lidiar con estos retos de la información a nivel nano, ni ha adaptado sus métodos y herramientas a este nuevo campo de investigación. En este contexto, la nueva área de la nanoinformática pretende detectar y establecer los vínculos existentes entre la medicina, la nanotecnología y la informática, fomentando así la aplicación de métodos computacionales para resolver las cuestiones y problemas que surgen con la información en la amplia intersección entre la biomedicina y la nanotecnología. Las observaciones expuestas previamente determinan el contexto de esta tesis doctoral, la cual se centra en analizar el dominio de la nanomedicina en profundidad, así como en el desarrollo de estrategias y herramientas para establecer correspondencias entre las distintas disciplinas, fuentes de datos, recursos computacionales y técnicas orientadas a la extracción de información y la minería de textos, con el objetivo final de hacer uso de los datos nanomédicos disponibles. El autor analiza, a través de casos reales, alguna de las tareas de investigación en nanomedicina que requieren o que pueden beneficiarse del uso de métodos y herramientas nanoinformáticas, ilustrando de esta forma los inconvenientes y limitaciones actuales de los enfoques de informática biomédica a la hora de tratar con datos pertenecientes al dominio nanomédico. Se discuten tres escenarios diferentes como ejemplos de actividades que los investigadores realizan mientras llevan a cabo su investigación, comparando los contextos biomédico y nanomédico: i) búsqueda en la Web de fuentes de datos y recursos computacionales que den soporte a su investigación; ii) búsqueda en la literatura científica de resultados experimentales y publicaciones relacionadas con su investigación; iii) búsqueda en registros de ensayos clínicos de resultados clínicos relacionados con su investigación. El desarrollo de estas actividades requiere el uso de herramientas y servicios informáticos, como exploradores Web, bases de datos de referencias bibliográficas indexando la literatura biomédica y registros online de ensayos clínicos, respectivamente. Para cada escenario, este documento proporciona un análisis detallado de los posibles obstáculos que pueden dificultar el desarrollo y el resultado de las diferentes tareas de investigación en cada uno de los dos campos citados (biomedicina y nanomedicina), poniendo especial énfasis en los retos existentes en la investigación nanomédica, campo en el que se han detectado las mayores dificultades. El autor ilustra cómo la aplicación de metodologías provenientes de la informática biomédica a estos escenarios resulta efectiva en el dominio biomédico, mientras que dichas metodologías presentan serias limitaciones cuando son aplicadas al contexto nanomédico. Para abordar dichas limitaciones, el autor propone un enfoque nanoinformático, original, diseñado específicamente para tratar con las características especiales que la información presenta a nivel nano. El enfoque consiste en un análisis en profundidad de la literatura científica y de los registros de ensayos clínicos disponibles para extraer información relevante sobre experimentos y resultados en nanomedicina —patrones textuales, vocabulario en común, descriptores de experimentos, parámetros de caracterización, etc.—, seguido del desarrollo de mecanismos para estructurar y analizar dicha información automáticamente. Este análisis concluye con la generación de un modelo de datos de referencia (gold standard) —un conjunto de datos de entrenamiento y de test anotados manualmente—, el cual ha sido aplicado a la clasificación de registros de ensayos clínicos, permitiendo distinguir automáticamente los estudios centrados en nanodrogas y nanodispositivos de aquellos enfocados a testear productos farmacéuticos tradicionales. El presente trabajo pretende proporcionar los métodos necesarios para organizar, depurar, filtrar y validar parte de los datos nanomédicos existentes en la actualidad a una escala adecuada para la toma de decisiones. Análisis similares para otras tareas de investigación en nanomedicina ayudarían a detectar qué recursos nanoinformáticos se requieren para cumplir los objetivos actuales en el área, así como a generar conjunto de datos de referencia, estructurados y densos en información, a partir de literatura y otros fuentes no estructuradas para poder aplicar nuevos algoritmos e inferir nueva información de valor para la investigación en nanomedicina. ABSTRACT Nanotechnology is a research area of recent development that deals with the manipulation and control of matter with dimensions ranging from 1 to 100 nanometers. At the nanoscale, materials exhibit singular physical, chemical and biological phenomena, very different from those manifested at the conventional scale. In medicine, nanosized compounds and nanostructured materials offer improved drug targeting and efficacy with respect to traditional formulations, and reveal novel diagnostic and therapeutic properties. Nevertheless, the complexity of information at the nano level is much higher than the complexity at the conventional biological levels (from populations to the cell). Thus, any nanomedical research workflow inherently demands advanced information management. Unfortunately, Biomedical Informatics (BMI) has not yet provided the necessary framework to deal with such information challenges, nor adapted its methods and tools to the new research field. In this context, the novel area of nanoinformatics aims to build new bridges between medicine, nanotechnology and informatics, allowing the application of computational methods to solve informational issues at the wide intersection between biomedicine and nanotechnology. The above observations determine the context of this doctoral dissertation, which is focused on analyzing the nanomedical domain in-depth, and developing nanoinformatics strategies and tools to map across disciplines, data sources, computational resources, and information extraction and text mining techniques, for leveraging available nanomedical data. The author analyzes, through real-life case studies, some research tasks in nanomedicine that would require or could benefit from the use of nanoinformatics methods and tools, illustrating present drawbacks and limitations of BMI approaches to deal with data belonging to the nanomedical domain. Three different scenarios, comparing both the biomedical and nanomedical contexts, are discussed as examples of activities that researchers would perform while conducting their research: i) searching over the Web for data sources and computational resources supporting their research; ii) searching the literature for experimental results and publications related to their research, and iii) searching clinical trial registries for clinical results related to their research. The development of these activities will depend on the use of informatics tools and services, such as web browsers, databases of citations and abstracts indexing the biomedical literature, and web-based clinical trial registries, respectively. For each scenario, this document provides a detailed analysis of the potential information barriers that could hamper the successful development of the different research tasks in both fields (biomedicine and nanomedicine), emphasizing the existing challenges for nanomedical research —where the major barriers have been found. The author illustrates how the application of BMI methodologies to these scenarios can be proven successful in the biomedical domain, whilst these methodologies present severe limitations when applied to the nanomedical context. To address such limitations, the author proposes an original nanoinformatics approach specifically designed to deal with the special characteristics of information at the nano level. This approach consists of an in-depth analysis of the scientific literature and available clinical trial registries to extract relevant information about experiments and results in nanomedicine —textual patterns, common vocabulary, experiment descriptors, characterization parameters, etc.—, followed by the development of mechanisms to automatically structure and analyze this information. This analysis resulted in the generation of a gold standard —a manually annotated training or reference set—, which was applied to the automatic classification of clinical trial summaries, distinguishing studies focused on nanodrugs and nanodevices from those aimed at testing traditional pharmaceuticals. The present work aims to provide the necessary methods for organizing, curating and validating existing nanomedical data on a scale suitable for decision-making. Similar analysis for different nanomedical research tasks would help to detect which nanoinformatics resources are required to meet current goals in the field, as well as to generate densely populated and machine-interpretable reference datasets from the literature and other unstructured sources for further testing novel algorithms and inferring new valuable information for nanomedicine.

World Space Observatory-Ultraviolet: ISSIS, the imaging instrument

The Imaging and Slitless Spectroscopy Instrument (ISSIS) will be flown as part of the science instrumentation in the World Space Observatory-Ultraviolet (WSO-UV). ISSIS will be the first UV imager to operate in a high Earth orbit from a 2 m class space telescope. In this contribution, the science driving the ISSIS design and the main characteristics of this instrument are presented.

Thermal and mechanical properties of recycled poly(Lactic acid)

Biodegradable polymers have experienced increased attention in recent years because of their wide range of applications in biomedical, packaging and agriculture fields. PLA, poly(lactic acid), is a linear aliphatic biodegradable thermoplastic polyester, with good mechanical properties, thermal stability, processability and low environmental impact, widely used as an alternative to conventional polymers. PLA products can be recycled after use either by remelting and reprocessing the material, or by hydrolysis to basic lactic acid [1]. The object of this communication is the study of the possible variation in physical properties induced by sub sequent reprocessing cycles of PLA.