Chemical speciation and mobilization of copper and zinc in naturally contaminated mine soils with citric and tartaric acids

A one-step extraction procedure and a leaching column experiment were performed to assess the effects of citric and tartaric acids on Cu and Zn mobilization in naturally contaminated mine soils to facilitate assisted phytoextraction. A speciation modeling of the soil solution and the metal fractionation of soils were performed to elucidate the chemical processes that affected metal desorption by organic acids. Different extracting solutions were prepared, all of which contained 0.01 M KNO3 and different concentrations of organic acids: control without organic acids, 0.5 mM citric, 0.5 mM tartaric, 10 mM citric, 10 mM tartaric, and 5 mM citric +5 mM tartaric. The results of the extraction procedure showed that higher concentrations of organic acids increased metal desorption, and citric acid was more effective at facilitating metal desorption than tartaric acid. Metal desorption was mainly influenced by the decreasing pH and the dissolution of Fe and Mn oxides, not by the formation of soluble metal–organic complexes as was predicted by the speciation modeling. The results of the column study reported that low concentrations of organic acids did not significantly increase metal mobilization and that higher doses were also not able to mobilize Zn. However, 5–10 mM citric acid significantly promoted Cu mobilization (from 1 mg kg−1 in the control to 42 mg kg−1 with 10 mM citric acid) and reduced the exchangeable (from 21 to 3 mg kg−1) and the Fe and Mn oxides (from 443 to 277 mg kg−1) fractions. Citric acid could efficiently facilitate assisted phytoextraction techniques.

Effects of sheep and horse manure and pine bark amendments on metal distribution and chemical properties of contaminated mine soils.

Mine soils usually contain large levels of heavy metals and poor fertility conditions which limit their reclamation and the application of phyto-remediation technologies. Two organic waste materials (pine bark compost and sheep and horse manure compost), with different pHs and varying degrees of humification and nutrient contents, were applied as amendments to assess their effects on copper (Cu) and zinc (Zn) bioavailability and on fertility conditions of mine soils. Soil samples collected from two abandoned mining areas near Madrid (Spain) were mixed with 0, 30 and 60 t ha?1 of the organic amendments. The concentrations of metals among the different mineral and organic fractions of soil were determined by several extraction procedures to study the metal distribution in the solid phase of the soil affected by the organic amendments. The results showed that the manure amendment increased the soil pH and the cation exchange capacity and enhanced the nutrient levels of these soils. The pine bark amendment decreased the soil pH and did not significantly change the nutrient status of soil. Soil pH, organic matter content and its degree of humification, which were altered by the amendments, were the main factors affecting Cu fractionation. Zn fractionation was mainly affected by soil pH. The addition of manure not only improved soil fertility, but also decreased metal bioavailability resulting in a reduction of metal toxicity. Conversely, pine bark amendment increased metal ioavailability. The use of sheep and horse manure could be a cost-effective practice for the restoration of contaminated mine soils.

Chemical and structural analysis of Eucalyptus globulus and E. camaldulensis leaf cuticles: a lipidized cell wall region

The plant cuticle has traditionally been conceived as an independent hydrophobic layer that covers the external epidermal cell wall. Due to its complexity, the existing relationship between cuticle chemical composition and ultra-structure remains unclear to date. This study aimed to examine the link between chemical composition and structure of isolated, adaxial leaf cuticles of Eucalyptus camaldulensis and E. globulus by the gradual extraction and identification of lipid constituents (cutin and soluble lipids), coupled to spectroscopic and microscopic analyses. The soluble compounds and cutin monomers identified could not be assigned to a concrete internal cuticle ultra-structure. After cutin depolymerization, a cellulose network resembling the cell wall was observed, with different structural patterns in the regions ascribed to the cuticle proper and cuticular layer, respectively. Our results suggest that the current cuticle model should be revised, stressing the presence and major role of cell wall polysaccharides. It is concluded that the cuticle may be interpreted as a modified cell wall region which contains additional lipids. The major heterogeneity of the plant cuticle makes it difficult to establish a direct link between cuticle chemistry and structure with the existing methodologies.

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.