Phosphate Deficiency Induces the Jasmonate Pathway and Enhances Resistance to Insect Herbivory.

During their life cycle, plants are typically confronted by simultaneous biotic and abiotic stresses. Low inorganic phosphate (Pi) is one of the most common nutrient deficiencies limiting plant growth in natural and agricultural ecosystems, while insect herbivory accounts for major losses in plant productivity and impacts ecological and evolutionary changes in plant populations. Here, we report that plants experiencing Pi deficiency induce the jasmonic acid (JA) pathway and enhance their defense against insect herbivory. Pi-deficient Arabidopsis (Arabidopsis thaliana) showed enhanced synthesis of JA and the bioactive conjugate JA-isoleucine, as well as activation of the JA signaling pathway, in both shoots and roots of wild-type plants and in shoots of the Pi-deficient mutant pho1 The kinetics of the induction of the JA signaling pathway by Pi deficiency was influenced by PHOSPHATE STARVATION RESPONSE1, the main transcription factor regulating the expression of Pi starvation-induced genes. Phenotypes of the pho1 mutant typically associated with Pi deficiency, such as high shoot anthocyanin levels and poor shoot growth, were significantly attenuated by blocking the JA biosynthesis or signaling pathway. Wounded pho1 leaves hyperaccumulated JA/JA-isoleucine in comparison with the wild type. The pho1 mutant also showed an increased resistance against the generalist herbivore Spodoptera littoralis that was attenuated in JA biosynthesis and signaling mutants. Pi deficiency also triggered increased resistance to S. littoralis in wild-type Arabidopsis as well as tomato (Solanum lycopersicum) and Nicotiana benthamiana, revealing that the link between Pi deficiency and enhanced herbivory resistance is conserved in a diversity of plants, including crops.

Quality balancing for parallel adaptive FEM

We present a dynamic distributed load balancing algorithm for parallel, adaptive finite element simulations using preconditioned conjugate gradient solvers based on domain-decomposition. The load balancer is designed to maintain good partition aspect ratios. It can calculate a balancing flow using different versions of diffusion and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. We show how to use information from the second step to guide the first. Experimental results using Bramble's preconditioner and comparisons to existing state-ot-the-art load balancers show the benefits of the construction.

Load balancing for parallel adaptive FEM

We present a dynamic distributed load balancing algorithm for parallel, adaptive finite element simulations using preconditioned conjugate gradient solvers based on domain-decomposition. The load balancer is designed to maintain good partition aspect ratios. It calculates a balancing flow using different versions of diffusion and a variant of breadth first search. Elements to be migrated are chosen according to a cost function aiming at the optimization of subdomain shapes. We show how to use information from the second step to guide the first. Experimental results using Bramble's preconditioner and comparisons to existing state-of-the-art balancers show the benefits of the construction.

Deep Crustal Structure of the North-West African Margin from Combined Wide-angle and Reflection Seismic Data (MIRROR Seismic Survey)

The structure of the Moroccan and Nova Scotia conjugate rifted margins is of key importance for understanding the Mesozoic break-up and evolution of the northern central Atlantic Ocean basin. Seven combined multichannel reflection (MCS) and wide-angle seismic (OBS) data profiles were acquired along the Atlantic Moroccan margin between the latitudes of 31.5° and 33° N during the MIRROR seismic survey in 2011, in order to image the transition from continental to oceanic crust, to study the variation in crustal structure and to characterize the crust under the West African Coast Magnetic Anomaly (WACMA). The data were modeled using a forward modeling approach. The final models image crustal thinning from 36 km thickness below the continent to approximately 8 km in the oceanic domain. A 100 km wide zone characterized by rough basement topography and high seismic velocities up to 7.4 km/s in the lower crust is observed westward of the West African Coast Magnetic Anomaly. No basin underlain by continental crust has been imaged in this region, as has been identified north of our study area. Comparison to the conjugate Nova Scotian margin shows a similar continental crustal thickness and layer geometry, and the existence of exhumed and serpentinized upper mantle material on the Canadian side only. The oceanic crustal thickness is lower on the Canadian margin.

Applications of functional nucleic acids in imaging, sensing and drug delivery and investigations of DNAzyme-metal interactions

Functional nucleic acids (FNA), including nucleic acids catalysts (ribozymes and DNAzymes) and ligands (aptamers), have been discovered in nature or isolated in a laboratory through a process called in vitro selection. They are nucleic acids with functions similar to protein enzymes or antibodies. They have been developed into sensors with high sensitivity and selectivity; it is realized by converting the reaction catalyzed by a DNAzyme/ribozyme or the binding event of an aptamer to a fluorescent, colorimetric or electrochemical signal. While a number of studies have been reported for in vitro sensing using DNAzymes or aptamers, there are few reports on in vivo sensing or imaging. MRI is a non-invasive imaging technique; smart MRI contrast agents were synthesized for molecular imaging purposes. However, their rational design remains a challenge due to the difficulty to predict molecular interactions. Chapter 2 focuses on rational design of smart T1-weighted MRI contrast agents with high specificity based on DNAzymes and aptamers. It was realized by changing the molecular weight of the gadolinium conjugated DNA strand with the analytes, which lead to analyte-specific water proton relaxation responses and contrast changes on an MRI image. The designs are general; the high selectivity of FNA was retained. Most FNA-based fluorescent sensors require covalent labeling of fluorophore/quencher to FNAs, which incurrs extra expenses and could interfere the function of FNAs. Chapter 3 describes a new sensor design avoiding the covalent labeling of fluorophore and quencher. The fluorescence of malachite green (MG) was regulated by the presence of adenosine. Conjugate of aptamers of MG and adenosine and a bridge strand were annealed in a solution containing MG. The MG aptamer did not bind MG because of its hybridization to the bridge strand, resulting in low fluorescence signal of MG. The hybridization was weakened in the presence of adenosine, leading to the binding of MG to its aptamer and a fluorescence increase. The sensor has comparable detection limit (20 micromolar) and specificity to its labeled derivatives. Enzymatic activity of most DNAzymes requires metal cations. The research on the metal-DNAzyme interaction is of interest and challenge to scientists because of the lack of structural information. Chapters 4 presents the research on the characterization of the interaction between a Cu2+-dependent DNAzyme and Cu2+. Electron paramagnetic resonance (EPR) and UV-Vis spectroscopy were used to probe the binding of Cu2+ to the DNAzyme; circular dichroism was used to probe the conformational change of the DNAzyme induced by Cu2+. It was proposed that the conformational change by the Cu2+ binding is important for the activity of the DNAzyme. Chapter 5 reports the dependence of the activity of 8-17 DNAzyme on the presence of both Pb2+ and other metal cations including Zn2+, Cd2+ and Mg2+. It was discovered that presence of those metal cations can be cooperative or inhibitive to 8-17 activity. It is hypothesized that the 8-17 DNAzyme had multiple binding sites for metal cations based on the results. Cisplatin is effective killing tumor cells, but with significant side effects, which can be minimized by its targeted delivery. Chapter 6 focuses on the effort to functionalize liposomes encapsulating cisplatin by an aptamer that selectively bind nucleolin, an overexpressed protein by breast cancer cells. The study proved the selective cytotoxicity to breast cancer cells of the aptamer-functionalized liposome.

Desenvolvimento de nanosistemas farmacêuticos para terapia gênica

Gene therapy is one of the major challenges of the post-genomic research and it is based on the transfer of genetic material into a cell, tissue or organ in order to cure or improve the patient s clinical status. In general, gene therapy consists in the insertion of functional genes aiming substitute, complement or inhibit defective genes. The achievement of a foreigner DNA expression into a population of cells requires its transfer to the target. Therefore, a key issue is to create systems, vectors, able to transfer and protect the DNA until it reaches the target. The disadvantages related to the use of viral vectors have encouraged efforts to develop emulsions as non-viral vectors. In fact, they are easy to produce, present suitable stability and enable transfection. The aim of this work was to evaluate two different non-viral vectors, cationic liposomes and nanoemulsions, and the possibility of their use in gene therapy. For the two systems, cationic lipids and helper lipids were used. Nanoemulsions were prepared using sonication method and were composed of Captex® 355; Tween® 80; Spam® 80; cationic lipid, Stearylamine (SA) or 1,2-dioleoyl-3-trimethylammoniumpropane (DOTAP) and water (Milli-Q®). These systems were characterized by average droplet size, Polidispersion Index (PI) and Zeta Potential. The stability of the systems; as well as the DNA compaction capacity; their cytotoxicity and the cytotoxicity of the isolated components; and their transfection capacity; were also evaluated. Liposomes were made by hydration film method and were composed of DOTAP; 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), containing or not Rhodaminephosphatidylethanolamine (PE- Rhodamine) and the conjugate Hyaluronic Acid DOPE (HA-DOPE). These systems were also characterized as nanoemulsions. Stability of the systems and the influence of time, size of plasmid and presence or absence of endotoxin in the formation of lipoplexes were also analyzed. Besides, the ophthalmic biodistribution of PE-Rhodamine containing liposomes was studied after intravitreal injection. The obtained results show that these systems are promising non-viral vector for further utilization in gene therapy and that this field seems to be very important in the clinical practice in this century. However, from the possibility to the practice, there is still a long way

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Dissertação de Mestrado para obtenção do grau de Mestre em Design de Comunicação, apresentada na Universidade de Lisboa - Faculdade de Arquitectura.

DESIGN, SYNTHESIS AND APPLICATIONS OF FLUORESCENT AND ELECTROCHEMICAL PROBES

“Seeing is believing” the proverb well suits for fluorescent imaging probes. Since we can selectively and sensitively visualize small biomolecules, organelles such as lysosomes, neutral molecules, metal ions, anions through cellular imaging, fluorescent probes can help shed light on the physiological and pathophysiological path ways. Since these biomolecules are produced in low concentrations in the biochemical pathways, general analytical techniques either fail to detect or are not sensitive enough to differentiate the relative concentrations. During my Ph.D. study, I exploited synthetic organic techniques to design and synthesize fluorescent probes with desirable properties such as high water solubility, high sensitivity and with varying fluorescent quantum yields. I synthesized a highly water soluble BOIDPY-based turn-on fluorescent probe for endogenous nitric oxide. I also synthesized a series of cell membrane permeable near infrared (NIR) pH activatable fluorescent probes for lysosomal pH sensing. Fluorescent dyes are molecular tools for designing fluorescent bio imaging probes. This prompted me to design and synthesize a hybrid fluorescent dye with a functionalizable chlorine atom and tested the chlorine re-activity for fluorescent probe design. Carbohydrate and protein interactions are key for many biological processes, such as viral and bacterial infections, cell recognition and adhesion, and immune response. Among several analytical techniques aimed to study these interactions, electrochemical bio sensing is more efficient due to its low cost, ease of operation, and possibility for miniaturization. During my Ph.D., I synthesized mannose bearing aniline molecule which is successfully tested as electrochemical bio sensor. A Ferrocene-mannose conjugate with an anchoring group is synthesized, which can be used as a potential electrochemical biosensor.

Sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution

Understanding how virus strains offer protection against closely related emerging strains is vital for creating effective vaccines. For many viruses, including Foot-and-Mouth Disease Virus (FMDV) and the Influenza virus where multiple serotypes often co-circulate, in vitro testing of large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross-protection between strains is important to help optimise vaccine choice. Vaccines will offer cross-protection against closely related strains, but not against those that are antigenically distinct. To be able to predict cross-protection we must understand the antigenic variability within a virus serotype, distinct lineages of a virus, and identify the antigenic residues and evolutionary changes that cause the variability. In this thesis we present a family of sparse hierarchical Bayesian models for detecting relevant antigenic sites in virus evolution (SABRE), as well as an extended version of the method, the extended SABRE (eSABRE) method, which better takes into account the data collection process. The SABRE methods are a family of sparse Bayesian hierarchical models that use spike and slab priors to identify sites in the viral protein which are important for the neutralisation of the virus. In this thesis we demonstrate how the SABRE methods can be used to identify antigenic residues within different serotypes and show how the SABRE method outperforms established methods, mixed-effects models based on forward variable selection or l1 regularisation, on both synthetic and viral datasets. In addition we also test a number of different versions of the SABRE method, compare conjugate and semi-conjugate prior specifications and an alternative to the spike and slab prior; the binary mask model. We also propose novel proposal mechanisms for the Markov chain Monte Carlo (MCMC) simulations, which improve mixing and convergence over that of the established component-wise Gibbs sampler. The SABRE method is then applied to datasets from FMDV and the Influenza virus in order to identify a number of known antigenic residue and to provide hypotheses of other potentially antigenic residues. We also demonstrate how the SABRE methods can be used to create accurate predictions of the important evolutionary changes of the FMDV serotypes. In this thesis we provide an extended version of the SABRE method, the eSABRE method, based on a latent variable model. The eSABRE method takes further into account the structure of the datasets for FMDV and the Influenza virus through the latent variable model and gives an improvement in the modelling of the error. We show how the eSABRE method outperforms the SABRE methods in simulation studies and propose a new information criterion for selecting the random effects factors that should be included in the eSABRE method; block integrated Widely Applicable Information Criterion (biWAIC). We demonstrate how biWAIC performs equally to two other methods for selecting the random effects factors and combine it with the eSABRE method to apply it to two large Influenza datasets. Inference in these large datasets is computationally infeasible with the SABRE methods, but as a result of the improved structure of the likelihood, we are able to show how the eSABRE method offers a computational improvement, leading it to be used on these datasets. The results of the eSABRE method show that we can use the method in a fully automatic manner to identify a large number of antigenic residues on a variety of the antigenic sites of two Influenza serotypes, as well as making predictions of a number of nearby sites that may also be antigenic and are worthy of further experiment investigation.

Cálculo de constantes ópticas de películas delgadas de Cu3BiS3 a través del método de Wolfe

Se calculó la obtención de las constantes ópticas usando el método de Wolfe. Dichas contantes: coeficiente de absorción (α), índice de refracción (n) y espesor de una película delgada (d ), son de importancia en el proceso de caracterización óptica del material. Se realizó una comparación del método del Wolfe con el método empleado por R. Swanepoel. Se desarrolló un modelo de programación no lineal con restricciones, de manera que fue posible estimar las constantes ópticas de películas delgadas semiconductoras, a partir únicamente, de datos de transmisión conocidos. Se presentó una solución al modelo de programación no lineal para programación cuadrática. Se demostró la confiabilidad del método propuesto, obteniendo valores de α = 10378.34 cm−1, n = 2.4595, d =989.71 nm y Eg = 1.39 Ev, a través de experimentos numéricos con datos de medidas de transmitancia espectral en películas delgadas de Cu3BiS3.

Peptidomimetic ligands for tuning integrin-mediated signalling: rational design, synthesis and theranostic applications

Integrins are α/β-heterodimeric transmembrane adhesion receptors that mediate cell-cell and cell-ECM interactions. Integrins are bidirectional signalling receptors that respond to external signals (“outside-in” signalling) and in parallel, transduce internal signals to the matrix (“inside-out” signalling), to regulate vital cellular functions including migration, survival, growth and differentiation. Therefore, dysregulation of these tightly regulated processes often results in uncontrolled integrin activation and abnormal tissue expression that is responsible for many diseases. Because of their important roles in physiological and pathological events, they represent a validated target for therapeutic and diagnostic purposes. The aim of the present Thesis was focused on the development of peptidic ligands for α4β1 and αvβ3 integrin subtypes, involved in inflammatory responses (leukocytes recruitment and extravasation) and cancer progression (angiogenesis, tumor growth, metastasis), respectively. Following the peptidomimetic strategy, we designed and synthesized a small library of linear and cyclic hybrid α/β-peptidomimetics based on the phenylureido-LDV scaffolds for the treatment of chronic inflammatory autoimmune diseases. In order to implement a fast and non-invasive diagnostic method for monitoring the course of the inflammatory processes, a flat glass-surface of dye-loaded Zeolite L-crystal nanoparticles was coated with bioactive α4β1-peptidomimetics to detect specific integrin-expressing cells as biomarkers of inflammatory diseases. Targeted drug delivery has been considered a promising alternative to overcome the pharmacokinetic limitations of conventional anticancer drugs. Thus, a novel Small-Molecule Drug Conjugate was synthesized by connecting the highly cytotoxic Cryptophycin to the tumor-targeting RGDfK-peptide through a protease-cleavable linker. Finally, in view to making the peptide synthesis more sustainable and greener, we developed an alternative method for peptide bonds formation employing solvent-free mechanochemistry and ultra-mild minimal solvent-grinding conditions in common, inexpensive laboratory equipment. To this purpose, standard amino acids, coupling agents and organic-green solvents were used in the presence of nanocrystalline hydroxyapatite as a reusable, bio-compatible inorganic basic catalyst.

Development of advanced methods for the simulation of the reacting mixture formation in internal combustion engines with the use of machine learning algorithms

Besides increasing the share of electric and hybrid vehicles, in order to comply with more stringent environmental protection limitations, in the mid-term the auto industry must improve the efficiency of the internal combustion engine and the well to wheel efficiency of the employed fuel. To achieve this target, a deeper knowledge of the phenomena that influence the mixture formation and the chemical reactions involving new synthetic fuel components is mandatory, but complex and time intensive to perform purely by experimentation. Therefore, numerical simulations play an important role in this development process, but their use can be effective only if they can be considered accurate enough to capture these variations. The most relevant models necessary for the simulation of the reacting mixture formation and successive chemical reactions have been investigated in the present work, with a critical approach, in order to provide instruments to define the most suitable approaches also in the industrial context, which is limited by time constraints and budget evaluations. To overcome these limitations, new methodologies have been developed to conjugate detailed and simplified modelling techniques for the phenomena involving chemical reactions and mixture formation in non-traditional conditions (e.g. water injection, biofuels etc.). Thanks to the large use of machine learning and deep learning algorithms, several applications have been revised or implemented, with the target of reducing the computing time of some traditional tasks by orders of magnitude. Finally, a complete workflow leveraging these new models has been defined and used for evaluating the effects of different surrogate formulations of the same experimental fuel on a proof-of-concept GDI engine model.

Characterization of a 3D-printed low-cost flexible dielectric material for the realization of innovative WPT wearable applications

The aim of this thesis is to demonstrate that 3D-printing technologies can be considered significantly attractive in the production of microwave devices and in the antenna design, with the intention of making them lightweight, cheaper, and easily integrable for the production of wireless, battery-free, and wearable devices for vital signals monitoring. In this work, a new 3D-printable, low-cost resin material, the Flexible80A, is proposed as RF substrate in the implementation of a rectifying antenna (rectenna) operating at 2.45 GHz for wireless power transfer. A careful and accurate electromagnetic characterization of the abovementioned material, revealing it to be a very lossy substrate, has paved the way for the investigation of innovative transmission line and antenna layouts, as well as etching techniques, possible thanks to the design freedom enabled by 3D-printing technologies with the aim of improving the wave propagation performance within lossy materials. This analysis is crucial in the design process of a patch antenna, meant to be successively connected to the rectifier. In fact, many different patch antenna layouts are explored varying the antenna dimensions, the substrate etchings shape and position, the feeding line technology, and the operating frequency. Before dealing with the rectification stage of the rectenna design, the hot and long-discussed topic of the equivalent receiving antenna circuit representation is addressed, providing an overview of the interpretation of different authors about the issue, and the position that has been adopted in this thesis. Furthermore, two rectenna designs are proposed and simulated with the aim of minimizing the dielectric losses. Finally, a prototype of a rectenna with the antenna conjugate matched to the rectifier, operating at 2.45 GHz, has been fabricated with adhesive copper on a substrate sample of Flexible80A and measured, in order to validate the simulated results.