Development of hyaluronic acid, dextrin and extracellular matrix hydrogels for cell expansion

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Effect of acid or alkaline catalyst and of different capping agents on the optical properties of CdS nanoparticles incorporated within a diureasil hybrid matrix

CdS nanoparticles (NPs) were synthesized using colloidal methods and incorporated within a diureasil hybrid matrix. The surface capping of the CdS NPs by 3-mercaptopropyltrimethoxysilane (MPTMS) and 3-aminopropyltrimethoxysilane (APTMS) organic ligands during the incorporation of the NPs within the hybrid matrix has been investigated. The matrix is based on poly(ethylene oxide)/poly(propylene oxide) chains grafted to a siliceous skeleton through urea bonds and was produced by sol–gel process. Both alkaline and acidic catalysis of the sol–gel reaction were used to evaluate the effect of each organic ligand on the optical properties of the CdS NPs. The hybrid materials were characterized by absorption, steady-state and time-resolved photoluminescence spectroscopy and High Resolution Transmission Electron Microscopy (HR-TEM). The preservation of the optical properties of the CdS NPs within the diureasil hybrids was dependent on the experimental conditions used. Both organic ligands (APTMS and MPTMS) demonstrated to be crucial in avoiding the increase of size distribution and clustering of the NPs within the hybrid matrix. The use of organic ligands was also shown to influence the level of interaction between the hybrid host and the CdS NPs. The CdS NPs showed large Stokes shifts and long average lifetimes, both in colloidal solution and in the xerogels, due to the origin of the PL emission in surface states. The CdS NPs capped with MPTMS have lower PL lifetimes compared to the other xerogel samples but still larger than the CdS NPs in the original colloidal solution. An increase in PL lifetimes of the NPs after their incorporation within the hybrid matrix is related to interaction between the NPs and the hybrid host matrix.

Z boson production in p plus Pb collisions at root S-NN=5.02 TeV measured with the ATLAS detector

The ATLAS Collaboration measures the inclusive production of Z bosons via their decays into electron and muon pairs in p+Pb collisions at sNN−−−√=5.02TeV at the Large Hadron Collider. The measurements are made using data corresponding to integrated luminosities of 29.4 and 28.1 nb−1 for Z→ee and Z→μμ, respectively. The results from the two channels are consistent and combined to obtain a cross section times the Z→ℓℓ branching ratio, integrated over the rapidity region ∣∣y∗Z|<3.5, of 139.8±4.8(statistical)±6.2(systematic)±3.8 (luminosity) nb. Differential cross sections are presented as functions of the Z boson rapidity and transverse momentum and compared with models based on parton distributions both with and without nuclear corrections. The centrality dependence of Z boson production in p+Pb collisions is measured and analyzed within the framework of a standard Glauber model and the model's extension for fluctuations of the underlying nucleon-nucleon scattering cross section.

Biological behaviour of thin films consisting of Au nanoparticles dispersed in a TiO2 dielectric matrix

In this work it was studied the possible use of thin films, composed of Au nanoparticles (NPs) embedded in a TiO2 matrix, in biological applications, by evaluating their interaction with a well-known protein, Bovine Serum Albumin (BSA), as well as with microbial cells (Candida albicans). The films were produced by one-step reactive DC magnetron sputtering followed by heat-treatment. The samples revealed a composition of 8.3 at.% of Au and a stoichiometric TiO2 matrix. The annealing promoted grain size increase of the Au NPs from 3 nm (at 300 °C) to 7 nm (at 500 °C) and a progressive crystallization of the TiO2 matrix to anatase. A broad localized surface plasmon resonance (LSPR) absorption band (λ = 580–720 nm) was clearly observed in the sample annealed at 500 °C, being less intense at 300 °C. The biological tests indicated that the BSA adhesion is dependent on surface nanostructure morphology, which in turn depends on the annealing temperature that changed the roughness and wettability of the films. The Au:TiO2 thin films also induced a significant change of the microbial cell membrane integrity, and ultimately the cell viability, which in turn affected the adhesion on its surface. The microstructural changes (structure, grain size and surface morphology) of the Au:TiO2 films promoted by heat-treatment shaped the amount of BSA adhered and affected cell viability.

Acetylated bacterial cellulose coated with urinary bladder matrix as a substrate for retinal pigment epithelium

This work evaluated the effect of acetylated bacterial cellulose (ABC) substrates coated with urinary bladder matrix (UBM) on the behavior of Retinal Pigment Epithelium (RPE), as assessed by cell adhesion, proliferation and development of cell polarity exhibiting transepithelial resistance and polygonal shaped-cells with microvilli. Acetylation of bacterial cellulose (BC) generated a moderate hydrophobic surface (around 65°) while the adsorption of UBM onto these acetylated substrates did not affect significantly the surface hydrophobicity. The ABS substrates coated with UBM enabled the development of a cell phenotype closer to that of native RPE cells. These cells were able to express proteins essential for their cytoskeletal organization and metabolic function (ZO-1 and RPE65), while showing a polygonal shaped morphology with microvilli and a monolayer configuration. The coated ABC substrates were also characterized, exhibiting low swelling effect (between 1.52.0 swelling/mm3), high mechanical strength (2048 MPa) and non-pyrogenicity (2.12 EU/L). Therefore, the ABC substrates coated with UBM exhibit interesting features as potential cell carriers in RPE transplantation that ought to be further explored.

Comportamento tribológico de biocompósitos de matriz de titânio

Dissertação de mestrado integrado em Engenharia de Materiais

Development of a model for occupational risk acceptance criteria definition in industrial settings

Doctoral Dissertation for PhD degree in Industrial and Systems Engineering

Elaboration et caractérisation des nanocristaux de Zn F O enfouis 1-x x dans des diélectriques pour des applications en spin-électronique

Tese de Doutoramento em Ciências - Especialidade em Física

Investigating a galactomannan gel obtained from Cassia grandis seeds as immobilizing matrix for Cramoll lectin

Characterization, with emphasis on the rheological properties, of Cassia grandis seeds galactomannan gel containing immobilized Cramoll 1,4 is presented. The gels, with and without immobilized Cramoll 1,4, were evaluated along time by rheometry, pH, color, microbial contamination and lectin hemagglutinating activity (HA). Rheological determinations confirmed the gels to be very stable up to 30 days with variations occurring after this period. Rheological data also showed that the gel/Cramoll 1,4 immobilizing matrix loses its elastic modulus substantially after 60 days. Both gels presented no microbial contamination as well as a pH close to neutral. Colorimetric parameters demonstrated the gels transparency with occasional yellowness. The opacity of the galactomannan gel did not change significantly along the study; the same did not occur for the gel with immobilized Cramoll 1,4 as a statistically significant reduction of its opacity was observed. In what concerns immobilized Cramoll 1,4HA, up to 90% of its initial HA was maintained after 20 days, with a decrease to 60% after 60 days. These results combined with the thickening and stabilizing characteristics of the galactomannan gel make this gel a promising immobilizing matrix for Cramoll 1,4 that can be further exploited for clinical and cosmetic applications.

Estimation of statistical cure from cancer using population-based data

Dissertação de mestrado em Estatística

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.

Enalapril alters the formation of the collagen matrix in spontaneously hypertensive rats

OBJECTIVE: To assess the effect of the inhibition of the angiotensin-converting enzyme on the collagen matrix (CM) of the heart of newborn spontaneously hypertensive rats (SHR) during embryonic development. METHODS: The study comprised the 2 following groups of SHR (n=5 each): treated group - rats conceived from SHR females treated with enalapril maleate (15 mg. kg-1.day-1) during gestation; and nontreated group - offspring of nontreated females. The newborns were euthanized within the first 24 hours after birth and their hearts were removed and processed for histological study. Three fields per animal were considered for computer-assisted digital analysis and determination of the volume densities (Vv) of the nuclei and CM. The images were segmented with the aid of Image Pro Plus® 4.5.029 software (Media Cybernetics). RESULTS: No difference was observed between the treated and nontreated groups in regard to body mass, cardiac mass, and the relation between cardiac and body mass. A significant reduction in the Vv[matrix] and a concomitant increase in the Vv[nuclei] were observed in the treated group as compared with those in the nontreated group. CONCLUSION: The treatment with enalapril of hypertensive rats during pregnancy alters the collagen content and structure of the myocardium of newborns.

Desarrollos estadísticos para el procesamiento de información genómica masiva en agro-biotecnología. Statistical developments for processing massive genomic information in agro-biotechnology.

Nuevas biotecnologías, como los marcadores de la molécula de ADN, permiten caracterizar el genoma vegetal. El uso de la información genómica producida para cientos o miles de posiciones cromosómicas permite identificar genotipos superiores en menos tiempo que el requerido por la selección fenotípica tradicional. La mayoría de los caracteres de las especies vegetales cultivadas de importancia agronómica y económica, son controlados por poli-genes causantes de un fenotipo con variación continua, altamente afectados por el ambiente. Su herencia es compleja ya que resulta de la interacción entre genes, del mismo o distinto cromosoma, y de la interacción del genotipo con el ambiente, dificultando la selección. Estas biotecnologías producen bases de datos con gran cantidad de información y estructuras complejas de correlación que requieren de métodos y modelos biométricos específicos para su procesamiento. Los modelos estadísticos focalizados en explicar el fenotipo a partir de información genómica masiva requieren la estimación de un gran número de parámetros. No existen métodos, dentro de la estadística paramétrica capaces de abordar este problema eficientemente. Además los modelos deben contemplar no-aditividades (interacciones) entre efectos génicos y de éstos con el ambiente que son también dificiles de manejar desde la concepción paramétrica. Se hipotetiza que el análisis de la asociación entre caracteres fenotípicos y genotipos moleculares, caracterizados por abundante información genómica, podría realizarse eficientemente en el contexto de los modelos mixtos semiparamétricos y/o de métodos no-paramétricos basados en técnicas de aprendizaje automático. El objetivo de este proyecto es desarrollar nuevos métodos para análisis de datos que permitan el uso eficiente de información genómica masiva en evaluaciones genéticas de interés agro-biotecnológico. Los objetivos específicos incluyen la comparación, respecto a propiedades estadísticas y computacionales, de estrategias analíticas paramétricas con estrategias semiparamétricas y no-paramétricas. Se trabajará con aproximaciones por regresión del análisis de loci de caracteres cuantitativos bajo distintas estrategias y escenarios (reales y simulados) con distinto volúmenes de datos de marcadores moleculares. En el área paramétrica se pondrá especial énfasis en modelos mixtos, mientras que en el área no paramétrica se evaluarán algoritmos de redes neuronales, máquinas de soporte vectorial, filtros multivariados, suavizados del tipo LOESS y métodos basados en núcleos de reciente aparición. La propuesta semiparamétrica se basará en una estrategia de análisis en dos etapas orientadas a: 1) reducir la dimensionalidad de los datos genómicos y 2) modelar el fenotipo introduciendo sólo las señales moleculares más significativas. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, nuevas herramientas y procedimientos de análisis que permitan maximizar la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos y su aplicación en desarrollos agro-biotecnológicos.

Estrategias estadístico-computacionales avanzadas para análisis de expresión de proteínas/genes en cáncer. Advanced statistical and computational strategies for protein/gene expression analysis in cancer.

El objetivo de este proyecto, enmarcado en el área de metodología de análisis en bioingeniería-biotecnología aplicadas al estudio del cancer, es el análisis y caracterización a través modelos estadísticos con efectos mixtos y técnicas de aprendizaje automático, de perfiles de expresión de proteínas y genes de las vías metabolicas asociadas a progresión tumoral. Dicho estudio se llevará a cabo mediante la utilización de tecnologías de alto rendimiento. Las mismas permiten evaluar miles de genes/proteínas en forma simultánea, generando así una gran cantidad de datos de expresión. Se hipotetiza que para un análisis e interpretación de la información subyacente, caracterizada por su abundancia y complejidad, podría realizarse mediante técnicas estadístico-computacionales eficientes en el contexto de modelos mixtos y técnias de aprendizaje automático. Para que el análisis sea efectivo es necesario contemplar los efectos ocasionados por los diferentes factores experimentales ajenos al fenómeno biológico bajo estudio. Estos efectos pueden enmascarar la información subycente y así perder informacion relavante en el contexto de progresión tumoral. La identificación de estos efectos permitirá obtener, eficientemente, los perfiles de expresión molecular que podrían permitir el desarrollo de métodos de diagnóstico basados en ellos. Con este trabajo se espera poner a disposición de investigadores de nuestro medio, herramientas y procedimientos de análisis que maximicen la eficiencia en el uso de los recursos asignados a la masiva captura de datos genómicos/proteómicos que permitan extraer información biológica relevante pertinente al análisis, clasificación o predicción de cáncer, el diseño de tratamientos y terapias específicos y el mejoramiento de los métodos de detección como así tambien aportar al entendimieto de la progresión tumoral mediante análisis computacional intensivo.