Valoração do efluente da indústria processadora de pescado por incorporação de nutrientes em aphanothece microscopica nägeli

Nesta tese procurou-se demonstrar a valoração do efluente do processamento de pescado por incorporação dos nutrientes em Aphanothece microscopica Nägeli a diferentes temperaturas. Para tanto o trabalho é composto de cinco artigos que objetivaram avaliar sob o ponto de vista do tratamento do efluente pela cianobactéria Aphanothece e a separação e avaliação da biomassa gerada. O primeiro artigo intitula-se “Influência da temperatura na remoção de nutrientes do efluente da indústria de pescado por Aphanothece microscopica Nägeli”, e teve por objetivo avaliar a influência da temperatura (10, 20 e 30ºC) em um sistema de tratamento pela cianobactéria Aphanothece na remoção de matéria orgânica, nitrogênio e fósforo do efluente oriundo do processamento de pescado. A análise dos resultados mostrou que a temperatura influenciou significativamente na remoção de DQO, NTK, N-NH4 + e P-PO4 -3 . Para os experimentos a 20 e 30ºC todos os limites estabelecidos para os parâmetros avaliados foram atingidos. O segundo artigo intitulado “Efeito de coagulantes no efluente da indústria da pesca visando à separação de biomassa quando tratado por cianobactéria” avaliou o efeito da concentração e pH de dois tipos de coagulantes, cloreto férrico (FeCl3) e sulfato de alumínio (Al2(SO4)3), na separação da biomassa da cianobactéria Aphanothece microscopica Nägeli cultivada em efluente da indústria da pesca, assim como a remoção de matéria orgânica e nutrientes do efluente. Os resultados indicaram que o coagulante FeCl3 foi mais eficaz na remoção de todos os parâmetros testados. No que concerne à separação da biomassa, com um número de seis lavagens foi removido cerca de 97,6% da concentração de FeCl3 adicionado inicialmente. O terceiro artigo com o título “Caracterização da biomassa de Aphanothece microscopica Nägeli gerada no efluente da indústria da pesca em diferentes temperaturas de cultivo” avaliou a composição química da biomassa da cianobactéria Aphanothece microscopica Nägeli quando desenvolvida em meio de cultivo padrão BG11 e no efluente do processamento de pescado. O quarto artigo teve como título “Influência do meio de cultivo e temperatura em compostos nitrogenados na cianobactéria Aphanothece microscopica Nägeli” objetivou avaliar o teor de compostos nitrogenados presentes na biomassa da cianobactéria Aphanothece microscopica Nägeli quando cultivada em meio padrão e no efluente da indústria da pesca nas diferentes fases de crescimento. Para o estudo da composição química e nitrogenados no efluente foram realizados experimentos nas temperaturas de 10, 20 e 30ºC. As concentrações de proteína, cinzas e pigmentos aumentaram com o aumento da temperatura. Por outro lado, foi observada uma redução do teor de lipídios e carboidratos com o aumento da temperatura. O íon amônio juntamente com os ácidos nucléicos representa uma importante fração do nitrogênio não protéico presente na biomassa da cianobactéria Aphanothece. Ficou demonstrada a influência do meio de cultivo na concentração de nitrogênio, bem como a determinação de proteína pelo método de Kjeldahl superestima a concentração protéica em cianobactérias. O quinto artigo intitulado “Produção de proteína unicelular a partir do efluente do processamento do pescado: modelagem preditiva e simulação” avaliou a produção de proteína unicelular através do cultivo da cianobactéria Aphanothece microscopica Nägeli no efluente da indústria da pesca. Os dados cinéticos de crescimento celular foram ajustados a quatro modelos matemáticos (Logístico, Gompertz, Gompertz Modificado e Baranyi). Os resultados demonstraram que o modelo Logístico foi considerado o mais adequado para descrever a formação de biomassa. A análise preditiva mostrou a possibilidade da obtenção de 1,66, 18,96 e 57,36 kg.m-3.d-1 de biomassa por volume do reator em 1000 h de processo contínuo, para as temperaturas de 10, 20 e 30ºC, respectivamente.

Improving interfaces for nerve repair

Autologous nerve grafts are the current gold standard for the repair of peripheral nerve injuries. However, there is a need to develop an alternative to this technique, as donor-site morbidities such as neuroma formation and permanent loss of function are a few of the limitations concerned with this technique. Artificial nerve conduits have therefore emerged as an alternative for the repair of short peripheral nerve defects of less than 30 mm, however they do not surpass autologous nerve grafts clinically. To develop a nerve conduit that supports regeneration over long nerve gaps and in large diameter nerves, researchers have focused on functionalizing of the conduits by studying the components that enhance nerve regeneration such as micro/nano-topography, growth factor delivery systems, supportive cells and extracellular matrix (ECM) proteins as well as understanding the complex biological reactions that take place during peripheral nerve regeneration. This thesis presents strategies to improve peripheral nerve interfaces to better the regenerative potential by using dorsal root ganglions (DRGs) isolated from neonatal rats as an in vitro model of nerve regeneration. The work started off by investigating the usefulness of a frog foam protein Ranaspumin-2 (Rsn2) to coat biomaterials for compatibility, this lead to the discovery of temporary cell adhesion on polydimethylsiloxane (PDMS), which was investigated as a suitable tool to derive cell-sheets for nerve repair. The influence of Rsn2 anchored to specific adhesion peptide sequences, such as isoleucine-lysine-valine-alanine-valine (IKVAV), a sequence derived from laminin proven to promote cell adhesion and neurite outgrowth, was tested as a useful means to influence nerve regeneration. This approach improves the axonal outgrowth and maintains outgrowth long term. Based on the hypothesis that combinational modulation of substrate topography, stiffness and neurotrophic support, affects axonal outgrowth in whole DRGs, dissociated DRGs were used to assess if these factors similarly act at the single cell level. Rho associated protein kinase (ROCK) and myosin II inhibitors, which affect cytoskeletal contractility, were used to influence growth cone traction forces and have shown that these factors work in combination by interfering with growth cone dynamic creating a different response in axonal outgrowth at the single cell level.

Light and dark carbon uptake by Dinophysis species in comparison to other photosynthetic and heterotrophic dinoflagellates

The marine dinoflagellate genus Dinophysis includes species that are the causative agents of diarrhetic shellfish poisoning (DSP). Recent findings indicate that some Dinophysis species are mixotrophic, i.e. capable of both autotrophic and heterotrophic nutrition. We investigated inorganic (and organic) carbon uptake by several species of Dinophysis in the Light and dark using the 'single-cell C-14 method', and compared uptake rates with those of photosynthetic Ceratium species and heterotrophic dinoflagellates in the genus Protoperidinium. Experiments were conducted with water from the Gullmar Fjord and from the Koster Strait (Swedish west coast). Nutrient-enriched phytoplankton from surface water samples were concentrated (20 to 70 mu m) and incubated at in situ temperature under artificial light conditions with high concentrations of inorganic C-14 (1 mu Ci ml(-1)). Individual cells of each desired species were manually isolated under a microscope and transferred to scintillation vials. C. tripes showed net C-14 uptake only during light periods, whereas both C. lineatum and C. furca showed C-14 uptake in the Light as well as uptake (and sometimes losses) in the dark. Dinophysis species had similar carbon fixation rates in Light compared to Ceratium species. For D. acuminata and D. norvegica, net carbon uptake occurred in both Light and dark periods. D. acuta showed a loss of carbon in the dark in one experiment, but in another, dark C uptake was significantly higher than uptake in Light. When exposed to Light, C. furca, D. norvegica and D. acuta had high specific carbon uptake rates. Growth rates for the different species were calculated from C-14 uptake by the cells during the first hours of incubation in light. D. acuminata and D. norvegica had similar maximum growth rates, 0.59 and 0.63 d(-1) (mu); the maximum growth rate of D. acuta was lower (0.41 d(-1)). The positive dark carbon uptake by Dinophysis may suggest a mixotrophic mode of nutrition. In one experiment, both D. norvegica and D. acuta showed a significantly higher carbon uptake in a dark bottle than in a Light bottle, which would be consistent with uptake of C-14-labeled organic matter by D. norvegica and D. acuta. Demonstration of direct uptake of dissolved and particulate organic matter would provide conclusive evidence of mixotrophy and this will require the development of new protocols for measuring organic matter uptake applicable to Dinophysis in the natural assemblages.

Desenvolvimento de uma célula a combustível de glicerol direto em meio alcalino

Dissertação (mestrado)—Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2015.

Desenvolvimento de uma célula a combustível de glicerol direto em meio alcalino

Dissertação (mestrado)—Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2015.

Obtenção de polímeros de LCC para aplicação como antioxidante de biodiesel de soja

Biodiesel is a fuel obtained from vegetable oils, such as soy, castorbean, among others. The monoester of fatty acid of these oils have chains with mono, di and tri double connections. The presence of these insaturations are susceptible to oxidization. Antioxidants are substances able to prevent oxidization from oils, fats, fat foods, as well as esters of Alquila( biodiesel). The objective of this work is to summarize a new antioxidant from the Cashew Nut Shell Liquid (CNSL) using the electrolysis technique. A current of 2 amperes was used in a single cell of only one group and two eletrodos of stainless steel 304 in a solution of methanol, together with the eletrolits: acetic acid, sodium chloride and sodium hydroxide, for two hours of agitation. The electrolysis products are characterized by the techniques of cromatography in a thin layer, spectroscopy of infrared and gravimetric analysis. The material was submitted to tests of oxidative stability made by the techniques of spectropy of impendancy and Rancimat (EN 14112). The analyses of characterization suggest that the polimerization of the electrolytic material ocurred. The application results of these materials as antioxidants of soy biodiesel showed that the order of the oxidative stability was obtained by both techniques used

Physiological Effects of Alcohol on Crayfish Escape Circuitry

Alcohol is one of the oldest and most widely used drugs on the planet, but the cellular mechanisms by which it affects neural function are still poorly understood. Unlike other drugs of abuse, alcohol has no specific receptor in the nervous system, but is believed to operate through GABAergic and serotonergic neurotransmitter systems. Invertebrate models offer circuits of reduced numerical complexity and involve the same cell types and neurotransmitter systems as vertebrate circuits. The well-understood neural circuits controlling crayfish escape behavior offer neurons that are modulated by GABAergic inhibition, thus making tail-flip circuitry an effective circuit model to study the cellular mechanisms of acute alcohol exposure. Crayfish are capable of two stereotyped, reflexive escape behaviors known as tail-flips that are controlled by two different pairs of giant interneurons, the lateral giants (LG) and the medial giants (MG). The LG circuit has been an established model in the neuroscience field for more than 60 years and is almost completely mapped out. In contrast, the MG is still poorly understood, but has important behavioral implications in social behavior and value-based decision making. In this dissertation, I show that both crayfish tail-flip circuitry are physiologically sensitive to relevant alcohol concentrations and that this sensitivity is observable on the single cell level. I also show that this ethyl alcohol (EtOH) sensitivity in the LG can be changed by altering the crayfish’s recent social experience and by removing descending inputs to the LG. While the MG exhibits similar physiological sensitivity, its inhibitory properties have never been studied before this research. Through the use of electrophysiological and pharmacological techniques, I show that the MG exhibits many similar inhibitory properties as the LG that appear to be the result of GABA-mediated chloride currents. Finally, I present evidence that the EtOH-induced changes in the MG are blocked through pre-treatment of the potent GABAA receptor agonist, muscimol, which underlines the role of GABA in EtOH’s effects on crayfish tail-flip circuitry. The work presented here opens the way for crayfish tail-flip circuitry to be used as an effective model for EtOH’s acute effects on aggression and value-based decision making.

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Development of a lab-on-a-chip device for rapid nanotoxicity assessment in vitro

Increasing useof nanomaterials in consumer products and biomedical applications creates the possibilities of intentional/unintentional exposure to humans and the environment. Beyond the physiological limit, the nanomaterialexposure to humans can induce toxicity. It is difficult to define toxicity of nanoparticles on humans as it varies by nanomaterialcomposition, size, surface properties and the target organ/cell line. Traditional tests for nanomaterialtoxicity assessment are mostly based on bulk-colorimetric assays. In many studies, nanomaterials have found to interfere with assay-dye to produce false results and usually require several hours or days to collect results. Therefore, there is a clear need for alternative tools that can provide accurate, rapid, and sensitive measure of initial nanomaterialscreening. Recent advancement in single cell studies has suggested discovering cell properties not found earlier in traditional bulk assays. A complex phenomenon, like nanotoxicity, may become clearer when studied at the single cell level, including with small colonies of cells. Advances in lab-on-a-chip techniques have played a significant role in drug discoveries and biosensor applications, however, rarely explored for nanomaterialtoxicity assessment. We presented such cell-integrated chip-based approach that provided quantitative and rapid response of cellhealth, through electrochemical measurements. Moreover, the novel design of the device presented in this study was capable of capturing and analyzing the cells at a single cell and small cell-population level. We examined the change in exocytosis (i.e. neurotransmitterrelease) properties of a single PC12 cell, when exposed to CuOand TiO2 nanoparticles. We found both nanomaterials to interfere with the cell exocytosis function. We also studied the whole-cell response of a single-cell and a small cell-population simultaneously in real-time for the first time. The presented study can be a reference to the future research in the direction of nanotoxicity assessment to develop miniature, simple, and cost-effective tool for fast, quantitative measurements at high throughput level. The designed lab-on-a-chip device and measurement techniques utilized in the present work can be applied for the assessment of othernanoparticles' toxicity, as well.^

Development and validation of a computationally efficient pseudo 3D model for planar SOFC integrated with a heating furnace

Efficient numerical models facilitate the study and design of solid oxide fuel cells (SOFCs), stacks, and systems. Whilst the accuracy and reliability of the computed results are usually sought by researchers, the corresponding modelling complexities could result in practical difficulties regarding the implementation flexibility and computational costs. The main objective of this article is to adapt a simple but viable numerical tool for evaluation of our experimental rig. Accordingly, a model for a multi-layer SOFC surrounded by a constant temperature furnace is presented, trained and validated against experimental data. The model consists of a four-layer structure including stand, two interconnects, and PEN (Positive electrode-Electrolyte-Negative electrode); each being approximated by a lumped parameter model. The heating process through the surrounding chamber is also considered. We used a set of V-I characteristics data for parameter adjustment followed by model verification against two independent sets of data. The model results show a good agreement with practical data, offering a significant improvement compared to reduced models in which the impact of external heat loss is neglected. Furthermore, thermal analysis for adiabatic and non-adiabatic process is carried out to capture the thermal behaviour of a single cell followed by a polarisation loss assessment. Finally, model-based design of experiment is demonstrated for a case study.

Revêtement intelligent à base des silices mésoporeuses fonctionnalisées pour le relargage stimulé d’agents antimicrobiens

Les biofilms bactériens sont composés d’organismes unicellulaires vivants au sein d’une matrice protectrice, formée de macromolécules naturelles. Des biofilms non désirés peuvent avoir un certain nombre de conséquences néfastes, par exemple la diminution du transfert de chaleur dans les échangeurs de chaleurs, l’obstruction de membranes poreuses, la contamination des surfaces coques de navires, etc. Par ailleurs, les bactéries pathogènes qui prolifèrent dans un biofilm posent également un danger pour la santé s’ils croissent sur des surfaces médicales synthétiques comme des implants biomédicaux, cathéters ou des lentilles de vue. De plus, la croissance sur le tissu naturel par certaines souches des bactéries peut être fatale, comme Pseudomonas aeruginosa dans les poumons. Cependant, la présence de biofilms reste difficile à traiter, car les bactéries sont protégées par une matrice extracellulaire. Pour tenter de remédier à ces problèmes, nous proposons de développer une surface antisalissure (antifouling) qui libère sur demande des agents antimicrobiens. La proximité et la disposition du système de relargage placé sous le biofilm, assureront une utilisation plus efficace des molécules antimicrobiennes et minimiseront les effets secondaires de ces dernières. Pour ce faire, nous envisageons l’utilisation d’une couche de particules de silice mésoporeuses comme agents de livraison d’agents antimicrobiens. Les nanoparticules de silice mésoporeuses (MSNs) ont démontré un fort potentiel pour la livraison ciblée d’agents thérapeutiques et bioactifs. Leur utilisation en nano médecine découle de leurs propriétés de porosité intéressantes, de la taille et de la forme ajustable de ces particules, de la chimie de leur surface et leur biocompatibilité. Ces propriétés offrent une flexibilité pour diverses applications. De plus, il est possible de les charger avec différentes molécules ou biomolécules (de tailles variées, allant de l’ibuprofène à l’ARN) et d’exercer un contrôle précis des paramètres d’adsorption et des cinétiques de relargage (désorption). Mots Clés : biofilms, nanoparticules de silice mésoporeuses, microfluidique, surface antisalissure.

Studies on the Hippo Pathway: new insights about a multifaceted signalling

The Hippo pathway is a well-known master regulator of cell growth and proliferation. Many studies have shed light on the centrality of Hippo functions, as this signalling is able to respond to different stimuli and translate them into distinct transcriptional outputs. Therefore, it is clearly implicated in a number of important processes, which alteration has consequences on the correct specification of the single cell, as well as the whole tissue. Even if the core of the signalling has been extensively characterized, it remains unclear which are the “co-workers” that permit the Hippo pathway to answer to so many different stimuli and act as a coordinator of the growth/differentiation balance. Taking advantage of the Drosophila model, which has witnessed most of the discoveries on this signalling pathway, this thesis aims to add some new knowledge about the Hippo pathway molecular mechanisms in different contexts, from development to disease. In the first part I studied the dynamics of the Hippo core kinase protein Warts in the development of the pupal eye. I have found out a critical time point in which the expression and the localization of Warts change suddenly, suggesting the intervention of upstream regulators modulating its activity in an extremely narrow time window. The second goal was investigating the role of the Hippo pathway in the neurodegenerative Gaucher disease. Indeed, I have produced some preliminary results which demonstrate a growth deficit associated with a massive reduction of some Yki targets, supporting a Hyper-Hippo condition underlying this neuropathic syndrome. Finally, I have evaluated the transcription factor Orthodenticle as a co-factor of Yorkie in driving tissue overgrowth, and my findings support a model of interaction of these two molecules based on Yki conformational changes. Altogether, my results lay the foundation for new important studies on the molecular mechanisms ruling Hippo pathway activity.

Interrogation of human monoclonal antibodies induced by 4C-MenB to identify protective antigens contained in the OMV component

Neisseria meningitidis is a gram negative human obligated pathogen, mostly found as a commensal in the oropharyngeal mucosa of healthy individuals. It can invade this epithelium determining rare but devastating and fast progressing outcomes, such as meningococcal meningitidis and septicemia, leading to death (about 135000 per year worldwide). Conjugated vaccines for serogroups A, C, W135, X and Y were developed, while for N. meningitidis serogroup B (MenB) the vaccines were based on Outern Membrane Vesicles (OMV). One of them is the 4C-MenB (Bexsero). The antigens included in this vaccine’s formulation are, in addition to the OMV from New Zeland epidemic strain 98/254, three recombinant proteins: NadA, NHBA and fHbp. While the role of these recombinant components was deeply characterized, the vesicular contribution in 4C-MenB elicited protection is mediated mainly by porin A and other unidentified antigens. To unravel the relative contribution of these different antigens in eliciting protective antibody responses, we isolated human monoclonal antibodies (mAbs) from single-cell sorted plasmablasts of 3 adult vaccinees peripheral blood. mAbs have been screened for binding to 4C-MenB components by Luminex bead-based assay. OMV-specific mAbs were purified and tested for functionality by serum bactericidal assay (SBA) on 18 different MenB strains and characterized in a protein microarray containing a panel of prioritized meningococcal proteins. The bactericidal mAbs identified to recognize the outer membrane proteins PorA and PorB, stating the importance of PorB in cross-strain protection. In addition, RmpM, BamE, Hyp1065 and ComL were found as immunogenic components of the 4C-MenB vaccine.

Interpretable Convolutional Neural Networks for Decoding and Analyzing Neural Time Series Data

Machine learning is widely adopted to decode multi-variate neural time series, including electroencephalographic (EEG) and single-cell recordings. Recent solutions based on deep learning (DL) outperformed traditional decoders by automatically extracting relevant discriminative features from raw or minimally pre-processed signals. Convolutional Neural Networks (CNNs) have been successfully applied to EEG and are the most common DL-based EEG decoders in the state-of-the-art (SOA). However, the current research is affected by some limitations. SOA CNNs for EEG decoding usually exploit deep and heavy structures with the risk of overfitting small datasets, and architectures are often defined empirically. Furthermore, CNNs are mainly validated by designing within-subject decoders. Crucially, the automatically learned features mainly remain unexplored; conversely, interpreting these features may be of great value to use decoders also as analysis tools, highlighting neural signatures underlying the different decoded brain or behavioral states in a data-driven way. Lastly, SOA DL-based algorithms used to decode single-cell recordings rely on more complex, slower to train and less interpretable networks than CNNs, and the use of CNNs with these signals has not been investigated. This PhD research addresses the previous limitations, with reference to P300 and motor decoding from EEG, and motor decoding from single-neuron activity. CNNs were designed light, compact, and interpretable. Moreover, multiple training strategies were adopted, including transfer learning, which could reduce training times promoting the application of CNNs in practice. Furthermore, CNN-based EEG analyses were proposed to study neural features in the spatial, temporal and frequency domains, and proved to better highlight and enhance relevant neural features related to P300 and motor states than canonical EEG analyses. Remarkably, these analyses could be used, in perspective, to design novel EEG biomarkers for neurological or neurodevelopmental disorders. Lastly, CNNs were developed to decode single-neuron activity, providing a better compromise between performance and model complexity.

Development of unsupervised learning methods with applications to life sciences data

Machine Learning makes computers capable of performing tasks typically requiring human intelligence. A domain where it is having a considerable impact is the life sciences, allowing to devise new biological analysis protocols, develop patients’ treatments efficiently and faster, and reduce healthcare costs. This Thesis work presents new Machine Learning methods and pipelines for the life sciences focusing on the unsupervised field. At a methodological level, two methods are presented. The first is an “Ab Initio Local Principal Path” and it is a revised and improved version of a pre-existing algorithm in the manifold learning realm. The second contribution is an improvement over the Import Vector Domain Description (one-class learning) through the Kullback-Leibler divergence. It hybridizes kernel methods to Deep Learning obtaining a scalable solution, an improved probabilistic model, and state-of-the-art performances. Both methods are tested through several experiments, with a central focus on their relevance in life sciences. Results show that they improve the performances achieved by their previous versions. At the applicative level, two pipelines are presented. The first one is for the analysis of RNA-Seq datasets, both transcriptomic and single-cell data, and is aimed at identifying genes that may be involved in biological processes (e.g., the transition of tissues from normal to cancer). In this project, an R package is released on CRAN to make the pipeline accessible to the bioinformatic Community through high-level APIs. The second pipeline is in the drug discovery domain and is useful for identifying druggable pockets, namely regions of a protein with a high probability of accepting a small molecule (a drug). Both these pipelines achieve remarkable results. Lastly, a detour application is developed to identify the strengths/limitations of the “Principal Path” algorithm by analyzing Convolutional Neural Networks induced vector spaces. This application is conducted in the music and visual arts domains.