Residual effect of organic zinc complexes in acid and calcareous soils on navy bean (phaseolus vulgaris l.) and flax (linum usitatissimum l.) crops under greenhouse conditions. Influence of the moisture conditions = Efecto residual de complejos orgánicos de zinc en suelos ácido y calizo en cultivos de judía (phaseolus vulgaris l.) y lino (linum usitatissimum l.) Realizados en condiciones de invernadero. Influencia de las diferentes condiciones de humedad

El Zn es un elemento esencial para el crecimiento saludable y reproducción de plantas, animales y humanos. La deficiencia de Zn es una de las carencias de micronutrientes más extendidas en muchos cultivos, afectando a grandes extensiones de suelos en diferentes áreas agrícolas. La biofortificación agronómica de diferentes cultivos, incrementando la concentración de micronutriente Zn en la planta, es un medio para evitar la deficiencia de Zn en animales y humanos. Tradicionalmente se han utilizado fertilizantes de Zn inorgánicos, como el ZnSO4, aunque en los últimos años se están utilizado complejos de Zn como fuentes de este micronutriente, obteniéndose altas concentraciones de Zn soluble y disponible en el suelo. Sin embargo, el envejecimiento de la fuente en el suelo puede causar cambios importantes en su disponibilidad para las plantas. Cuando se añaden al suelo fuentes de Zn inorgánicas, las formas de Zn más solubles pierden actividad y extractabilidad con el paso del tiempo, transformándose a formas más estables y menos biodisponibles. En esta tesis se estudia el efecto residual de diferentes complejos de Zn de origen natural y sintético, aplicados en cultivos previos de judía y lino, bajo dos condiciones de riego distintas (por encima y por debajo de la capacidad de campo, respectivamente) y en dos suelos diferentes (ácido y calizo). Los fertilizantes fueron aplicados al cultivo previo en tres dosis diferentes (0, 5 y 10 mg Zn kg-1 suelo). El Zn fácilmente lixiviable se estimó con la extracción con BaCl2 0,1M. Bajo condiciones de humedad por encima de la capacidad de campo se obtuvieron mayores porcentajes de Zn lixiviado en el suelo calizo que en el suelo ácido. En el caso del cultivo de judía realizado en condiciones de humedad por encima de la capacidad de campo se compararon las cantidades extraídas con el Zn lixiviado real. El análisis de correlación entre el Zn fácilmente lixiviable y el estimado sólo fue válido para complejos con alta movilidad y para cada suelo por separado. Bajo condiciones de humedad por debajo de la capacidad de campo, la concentración de Zn biodisponible fácilmente lixiviable presentó correlaciones positivas y altamente significativas con la concentración de Zn disponible en el suelo. El Zn disponible se estimó con varios métodos de extracción empleados habitualmente: DTPA-TEA, DTPA-AB, Mehlich-3 y LMWOAs. Estas concentraciones fueron mayores en el suelo ácido que en el calizo. Los diferentes métodos utilizados para estimar el Zn disponible presentaron correlaciones positivas y altamente significativas entre sí. La distribución del Zn en las distintas fracciones del suelo fue estimada con diferentes extracciones secuenciales. Las extracciones secuenciales mostraron un descenso entre los dos cultivos (el anterior y el actual) en la fracción de Zn más lábil y un aumento en la concentración de Zn asociado a fracciones menos lábiles, como carbonatos, óxidos y materia orgánica. Se obtuvieron correlaciones positivas y altamente significativas entre las concentraciones de Zn asociado a las fracciones más lábiles (WSEX y WS+EXC, experimento de la judía y lino, respectivamente) y las concentraciones de Zn disponible, estimadas por los diferentes métodos. Con respecto a la planta se determinaron el rendimiento en materia seca y la concentración de Zn en planta. Se observó un aumento del rendimiento y concentraciones con el efecto residual de la dosis mayores (10 mg Zn kg-1) con respecto a la dosis inferior (5 mg Zn 12 kg-1) y de ésta con respecto a la dosis 0 (control). El incremento de la concentración de Zn en todos los tratamientos fertilizantes, respecto al control, fue mayor en el suelo ácido que en el calizo. Las concentraciones de Zn en planta indicaron que, en el suelo calizo, serían convenientes nuevas aplicaciones de Zn en posteriores cultivos para mantener unas adecuadas concentraciones en planta. Las mayores concentraciones de Zn en la planta de judía, cultivada bajo condiciones de humedad por encima de la capacidad de campo, se obtuvieron en el suelo ácido con el efecto residual del Zn-HEDTA a la dosis de 10 mg Zn kg-1 (280,87 mg Zn kg-1) y en el suelo calizo con el efecto residual del Zn-DTPA-HEDTA-EDTA a la dosis de 10 mg Zn kg-1 (49,89 mg Zn kg-1). En el cultivo de lino, cultivado bajo condiciones de humedad por debajo de la capacidad de campo, las mayores concentraciones de Zn en planta ese obtuvieron con el efecto residual del Zn-AML a la dosis de 10 mg Zn kg-1 (224,75 mg Zn kg-1) y en el suelo calizo con el efecto residual del Zn-EDTA a la dosis de 10 mg Zn kg-1 (99,83 mg Zn kg-1). El Zn tomado por la planta fue determinado como combinación del rendimiento y de la concentración en planta. Bajo condiciones de humedad por encima de capacidad de campo, con lixiviación, el Zn tomado por la judía disminuyó en el cultivo actual con respecto al cultivo anterior. Sin embargo, en el cultivo de lino, bajo condiciones de humedad por debajo de la capacidad de campo, se obtuvieron cantidades de Zn tomado superiores en el cultivo actual con respecto al anterior. Esta tendencia también se observó, en ambos casos, con el porcentaje de Zn usado por la planta. Summary Zinc is essential for healthy growth and reproduction of plants, animals and humans. Zinc deficiency is one of the most widespread micronutrient deficiency in different crops, and affect different agricultural areas. Agronomic biofortification of crops produced by an increased of Zn in plant, is one way to avoid Zn deficiency in animals and humans Sources with inorganic Zn, such as ZnSO4, have been used traditionally. Although, in recent years, Zn complexes are used as sources of this micronutrient, the provide high concentrations of soluble and available Zn in soil. However, the aging of the source in the soil could cause significant changes in their availability to plants. When an inorganic source of Zn is added to soil, Zn forms more soluble and extractability lose activity over time, transforming into forms more stable and less bioavailable. This study examines the residual effect of different natural and synthetic Zn complexes on navy bean and flax crops, under two different moisture conditions (above and below field capacity, respectively) and in two different soils (acid and calcareous). Fertilizers were applied to the previous crop in three different doses (0, 5 y 10 mg Zn kg-1 soil). The easily leachable Zn was estimated by extraction with 0.1 M BaCl2. Under conditions of moisture above field capacity, the percentage of leachable Zn in the calcareous soil was higher than in acid soil. In the case of navy bean experiment, performed in moisture conditions of above field capacity, amounts extracted of easily leachable Zn were compared with the real leachable Zn. Correlation analysis between the leachable Zn and the estimate was only valid for complex with high mobility and for each soil separately. Under moisture conditions below field capacity, the concentration of bioavailable easily leachable Zn showed highly significant positive correlations with the concentration of available soil Zn. The available Zn was estimated with several commonly used extraction methods: DTPA-TEA, AB-DTPA, Mehlich-3 and LMWOAs. These concentrations were higher in acidic soil than in the calcareous. The different methods used to estimate the available Zn showed highly significant positive correlations with each other. The distribution of Zn in the different fractions of soil was estimated with different sequential extractions. The sequential extractions showed a decrease between the two crops (the previous and current) at the most labile Zn fraction and an increase in the concentration of Zn associated with the less labile fractions, such as carbonates, oxides and organic matter. A positive and highly significant correlation was obtained between the concentrations of Zn associated with more labile fractions (WSEX and WS + EXC, navy bean and flax experiments, respectively) and available Zn concentrations determined by the different methods. Dry matter yield and Zn concentration in plants were determined in plant. Yield and Zn concentration in plant were higher with the residual concentrations of the higher dose applied (10 mg Zn kg-1) than with the lower dose (5 mg Zn kg-1), also these parameters showed higher values with application of this dose than with not Zn application. The increase of Zn concentration in plant with Zn treatments, respect to the control, was greater in the acid soil than in the calcareous. The Zn concentrations in plant indicated that in the calcareous soil, new applications of Zn are desirable in subsequent crops to maintain suitable concentrations in plant. 15 The highest concentrations of Zn in navy bean plant, performed under moisture conditions above the field capacity, were obtained with the residual effect of Zn-HEDTA at the dose of 10 mg Zn kg-1 (280.87 mg Zn kg-1) in the acid soil, and with the residual effect of Zn- DTPA-HEDTA-EDTA at a dose of 10 mg Zn kg-1 (49.89 mg Zn kg-1) in the calcareous soil. In the flax crop, performed under moisture conditions below field capacity, the highest Zn concentrations in plant were obtained with the residual effect of Zn-AML at the dose of 10 mg Zn kg-1 (224.75 Zn mg kg-1) and with the residual effect of Zn-EDTA at a dose of 10 mg Zn kg-1 (99.83 mg Zn kg-1) in the calcareous soil. The Zn uptake was determined as a combination of yield and Zn concentration in plant. Under moisture conditions above field capacity, with leaching, Zn uptake by navy bean decreased in the current crop, respect to the previous crop. However, in the flax crop, under moisture conditions below field capacity, Zn uptake was higher in the current crop than in the previous. This trend is also observed in both cases, with the percentage of Zn used by the plant

Estudios de especiación de arsénico y acumulación de metales en muestras de interés medioambiental : Arsenic speciation and metal accumulation studies in environmental samples

Se ha estudiado la determinación de especies de arsénico y de contenidos totales de arsénico y metales pesados, específicamente cadmio, cromo, cobre, níquel, plomo y cinc, en muestras de interés medioambiental por su elevada capacidad acumuladora de metales, concretamente algas marinas comestibles y plantas terrestres procedentes de suelos contaminados por la actividad minera. La determinación de contenidos totales se ha llevado a cabo mediante espectrometría de emisión atómica con plasma de acoplamiento inductivo (ICP‐AES), así como por espectrometría de fluorescencia atómica con generación de hidruros (HG‐AFS), para bajos contenidos de arsénico. Las muestras fueron mineralizadas en medio ácido y calentamiento en horno de microondas. Los métodos fueron validados a través de su aplicación a materiales de referencia de matriz similar a la de las muestras, certificados en contenidos totales de los elementos seleccionados. Los resultados obtenidos mostraron su elevada capacidad de bioabsorción, especialmente en relación a los elevados contenidos de arsénico encontrados en algunas especies de algas pardas (Phaeophytas). En las plantas, se calcularon los factores de translocación, acumulación y biodisponibilidad de los elementos estudiados, permitiendo identificar a la especie Corrigiola telephiifolia como posible acumuladora de plomo e hiperacumuladora de arsénico. La determinación de especies de arsénico hidrosolubles en las muestras objeto de estudio, se llevó a cabo por cromatografía líquida de alta eficacia (HPLC) acoplado a ICP‐AES, HG‐ICP‐AES y HG‐AFS, incluyendo una etapa previa de foto‐oxidación. Los métodos desarrollados, mediante intercambio aniónico y catiónico, permitieron la diferenciación de hasta once especies de arsénico. Para el análisis de las muestras, fue necesaria la optimización de métodos de extracción, seleccionándose la extracción asistida por microondas (MAE) con agua desionizada. Asimismo, se realizaron estudios de estabilidad de arsénico total y de las especies hidrosolubles presentes en las algas, tanto sobre la muestra sólida como en sus extractos acuosos, evaluando las condiciones de almacenamiento adecuadas. En el caso de las plantas, la aplicación del diseño factorial de experimentos permitió optimizar el método de extracción y diferenciar entre las especies de arsénico presentes en forma de iones sencillos de mayor movilidad y el arsénico más fuertemente enlazado a componentes estructurales. Los resultados obtenidos permitieron identificar la presencia de arseniato (As(V)) y arsenito (As(III)) en las plantas, así como de ácido monometilarsónico (MMA) y óxido de trimetilarsina (TMAO) en algunas especies. En la mayoría de las algas se encontraron especies tóxicas, tanto mayoritarias (arseniato) como minoritarias (ácido dimetilarsínico (DMA)), así como hasta cuatro arsenoazúcares. Los resultados obtenidos y su estudio a través de la legislación vigente, mostraron la necesidad de desarrollar una reglamentación específica para el control de este tipo de alimentos. La determinación de especies de arsénico liposolubles en las muestras de algas se llevó a cabo mediante HPLC, en modo fase inversa, acoplado a espectrometría de masas con plasma de acoplamiento inductivo (ICP‐MS) y con ionización por electrospray (ESI‐MS), permitiendo la elucidación estructural de estos compuestos a través de la determinación de sus masas moleculares. Para ello, fue necesaria la puesta a punto de métodos extracción y purificación de los extractos. La metodología desarrollada permitió identificar hasta catorce especies de arsénico liposolubles en las algas, tres de ellas correspondientes a hidrocarburos que contienen arsénico, y once a arsenofosfolípidos, además de dos especies desconocidas. Las masas moleculares de las especies identificadas fueron confirmadas mediante cromatografía de gases acoplada a espectrometría de masas (GC‐MS) y espectrometría de masas de alta resolución (HR‐MS). ABSTRACT The determination of arsenic species and total arsenic and heavy metal contents (cadmium, chromium, cooper, nickel, lead and zinc) in environmental samples, with high metal accumulator capacity, has been studied. The samples studied were edible marine algae and terrestrial plants from soils polluted by mining activities. The determination of total element contents was performed by inductively coupled plasma atomic emission spectrometry (ICP‐AES), as well as by hydride generation atomic fluorescence spectrometry (HG‐AFS) for low arsenic contents. The samples studied were digested in an acidic medium by heating in a microwave oven. The digestion methods were validated against reference materials, with matrix similar to sample matrix and certified in total contents of the elements studied. The results showed the high biosorption capacity of the samples studied, especially regarding the high arsenic contents in some species of brown algae (Phaeophyta division). In terrestrial plants, the translocation, accumulation and bioavailability factors of the elements studied were calculated. Thus, the plant species Corrigiola telephiifolia was identified as possible lead accumulator and arsenic hyperaccumulator. The determination of water‐soluble arsenic species in the samples studied was carried out by high performance liquid chromatography (HPLC) coupled to ICP‐AES, HG‐ICP‐AES and HG‐AFS, including a prior photo‐oxidation step. The chromatographic methods developed, by anion and cation exchange, allowed us to differentiate up to eleven arsenic species. The sample analysis required the optimization of extraction methods, choosing the microwave assisted extraction (MAE) with deionized water. On the other hand, the stability of total arsenic and water‐soluble arsenic species in algae, both in the solid samples and in the water extracts, was studied, assessing the suitable storage conditions. In the case of plant samples, the application of a multivariate experimental design allowed us to optimize the extraction method and differentiate between the arsenic species present as simple ions of higher mobility and the arsenic more strongly bound to structural components. The presence of arsenite (As(III)) and arsenate (As(V)) was identified in plant samples, as well as monomethylarsonic acid (MMA) and trimethylarsine oxide (TMAO) in some cases. Regarding algae, toxic arsenic species were found in most of them, both As(V) and dimethylarsinic acid (DMA), as well as up to four arsenosugars. These results were discussed according to the current legislation, showing the need to develop specific regulations to control this kind of food products. The determination of lipid‐soluble arsenic species in alga samples was performed by reversed‐phase HPLC coupled to inductively coupled plasma and electrospray mass spectrometry (ICP‐MS and ESI‐MS), in order to establish the structure of these compounds by determining the corresponding molecular masses. For this purpose, it was necessary to develop an extraction method, as well as a clean‐up method of the extracts. The method developed permitted the identification of fourteen lipid‐soluble arsenic compounds in algae, corresponding to three arsenic‐hydrocarbons and eleven arsenosugarphospholipids, as well as two unknown compounds. Accurate mass measurements of the identified compounds were performed by gas chromatography coupled to mass spectrometry (GC‐MS) and high resolution mass spectrometry (HR‐MS).

Application of Independent Components Analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration

In recent years, Independent Components Analysis (ICA) has proven itself to be a powerful signal-processing technique for solving the Blind-Source Separation (BSS) problems in different scientific domains. In the present work, an application of ICA for processing NIR hyperspectral images to detect traces of peanut in wheat flour is presented. Processing was performed without a priori knowledge of the chemical composition of the two food materials. The aim was to extract the source signals of the different chemical components from the initial data set and to use them in order to determine the distribution of peanut traces in the hyperspectral images. To determine the optimal number of independent component to be extracted, the Random ICA by blocks method was used. This method is based on the repeated calculation of several models using an increasing number of independent components after randomly segmenting the matrix data into two blocks and then calculating the correlations between the signals extracted from the two blocks. The extracted ICA signals were interpreted and their ability to classify peanut and wheat flour was studied. Finally, all the extracted ICs were used to construct a single synthetic signal that could be used directly with the hyperspectral images to enhance the contrast between the peanut and the wheat flours in a real multi-use industrial environment. Furthermore, feature extraction methods (connected components labelling algorithm followed by flood fill method to extract object contours) were applied in order to target the spatial location of the presence of peanut traces. A good visualization of the distributions of peanut traces was thus obtained

Arsenic speciation in edible alga samples by microwave-assisted extraction and high performance liquid chromatography coupled to atomic fluorescence spectrometry

Twelve commercially available edible marine algae from France, Japan and Spain and the certified reference material (CRM) NIES No. 9 Sargassum fulvellum were analyzed for total arsenic and arsenic species. Total arsenic concentrations were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) after microwave digestion and ranged from 23 to 126 μg g−1. Arsenic species in alga samples were extracted with deionized water by microwave-assisted extraction and showed extraction efficiencies from 49 to 98%, in terms of total arsenic. The presence of eleven arsenic species was studied by high performance liquid chromatography–ultraviolet photo-oxidation–hydride generation atomic–fluorescence spectrometry (HPLC–(UV)–HG–AFS) developed methods, using both anion and cation exchange chromatography. Glycerol and phosphate sugars were found in all alga samples analyzed, at concentrations between 0.11 and 22 μg g−1, whereas sulfonate and sulfate sugars were only detected in three of them (0.6-7.2 μg g−1). Regarding arsenic toxic species, low concentration levels of dimethylarsinic acid (DMA) (<0.9 μg g−1) and generally high arsenate (As(V)) concentrations (up to 77 μg g−1) were found in most of the algae studied. The results obtained are of interest to highlight the need to perform speciation analysis and to introduce appropriate legislation to limit toxic arsenic species content in these food products.

Two Different Approaches of Feature Extraction for Classifying the EEG Signals

The focus of this chapter is to study feature extraction and pattern classification methods from two medical areas, Stabilometry and Electroencephalography (EEG). Stabilometry is the branch of medicine responsible for examining balance in human beings. Balance and dizziness disorders are probably two of the most common illnesses that physicians have to deal with. In Stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods are known as events. In this chapter, two feature extraction schemes have been developed to identify and characterise the events in Stabilometry and EEG signals. Based on these extracted features, an Adaptive Fuzzy Inference Neural network has been applied for classification of Stabilometry and EEG signals.

An investigation of the performance of a new Mechanical thrombectomy device using Bond Graph modelling: application to the extraction of blood clots in the middle cerebral artery

A number of thrombectomy devices using a variety of methods have now been developed to facilitate clot removal. We present research involving one such experimental device recently developed in the UK, called a ‘GP’ Thrombus Aspiration Device (GPTAD). This device has the potential to bring about the extraction of a thrombus. Although the device is at a relatively early stage of development, the results look encouraging. In this work, we present an analysis and modeling of the GPTAD by means of the bond graph technique; it seems to be a highly effective method of simulating the device under a variety of conditions. Such modeling is useful in optimizing the GPTAD and predicting the result of clot extraction. The aim of this simulation model is to obtain the minimum pressure necessary to extract the clot and to verify that both the pressure and the time required to complete the clot extraction are realistic for use in clinical situations, and are consistent with any experimentally obtained data. We therefore consider aspects of rheology and mechanics in our modeling.

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

Extraction of subjective properties in image processing

Most of the present digital images processing methods are related with objective characterization of external properties as shape, form or colour. This information concerns objective characteristics of different bodies and is applied to extract details to perform several different tasks. But in some occasions, some other type of information is needed. This is the case when the image processing system is going to be applied to some operation related with living bodies. In this case, some other type of object information may be useful. As a matter of fact, it may give additional knowledge about its subjective properties. Some of these properties are object symmetry, parallelism between lines and the feeling of size. These types of properties concerns more to internal sensations of living beings when they are related with their environment than to the objective information obtained by artificial systems. This paper presents an elemental system able to detect some of the above-mentioned parameters. A first mathematical model to analyze these situations is reported. This theoretical model will give the possibility to implement a simple working system. The basis of this system is the use of optical logic cells, previously employed in optical computing.

New method for analytical photovoltaic parameter extraction

Correct modeling of the equivalent circuits regarding solar cell and panels is today an essential tool for power optimization. However, the parameter extraction of those circuits is still a quite difficult task that normally requires both experimental data and calculation procedures, generally not available to the normal user. This paper presents a new analytical method that easily calculates the equivalent circuit parameters from the data that manufacturers usually provide. The analytical approximation is based on a new methodology, since methods developed until now to obtain the aforementioned equivalent circuit parameters from manufacturer's data have always been numerical or heuristic. Results from the present method are as accurate as the ones resulting from other more complex (numerical) existing methods in terms of calculation process and resources.

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.

Image processing methods for human brain connectivity analysis from in-vivo diffusion MRI

The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.