This thesis investigates the potential for monitoring current and historic blood serum concentrations of amino acids via transdermal extraction using phenylalanine as a case study. This work furthers the field of non-invasive monitoring of amino acid disorders which have several advantages over invasive methods such as blood tests. In this thesis we derive models to simulate blood serum concentrations, the formation of the skin reservoir and, finally, transdermal extraction of amino acids under an applied electric field. Chapter 1 concerns itself with the biological background and sets up motivation of the thesis by discussing amino acids, associated amino acid disorders, the overarching clinical problem, skin structure and transdermal extraction methods. Chapter 2 then considers mathematical techniques utilised throughout the thesis. Chapter 3 formulates a model for the distribution of phenylalanine in blood serum. One compartment and two compartment approaches are considered in both a fasting state and a non-fasting state. We consider if these have a noticeable effect on the blood serum concentration of phenylalanine. Having obtained a model for the distribution of phenylalanine in blood serum, chapter 4 models the formation of reservoirs of amino acids in the skin. Prior work has identified the existence of such a reservoir, but its formation has not been addressed. The models developed consider the effect of the removal of outer layers of skin, the stratum disjunctum, and production of amino acids in the skin. Unknown parameters are estimated by comparing the model to in vivo and in vitro data. Chapter 5 and 6 are concerned with transdermal extraction under an applied electric field. Chapter 5 formulates the velocity induced by applying an electric field across a charged interface. Chapter 6 utilises these results for modelling extraction of compounds through the skin under an applied electric field.

A resolução temporal é uma questão-chave em Paleontologia, uma vez que a sua magnitude define a precisão dos estudos não somente paleoecológicos como também evolutivos. A resolução temporal é estimada pela magnitude de time-averaging (mistura de gerações em uma camada, uma amostra). Tais estimativas têm sido amplamente conduzidas em ambientes marinhos recentes. A plataforma continental do sul do Brasil (PSB; 22°S – 34°S) tem sido um laboratório natural para estudos desta natureza desde o início do século XXI. Consequentemente, possui um amplo acervo de dados disponíveis para comparação. Neste contexto, esta tese visou responder (i) qual a magnitude do time-averaging em acumulações de bivalves da PSB? (ii) como este processo varia ao longo de gradientes espaciais? e (iii) como o time-averaging reflete na informação biológica preservada no registro fóssil? Para isto, mais de 140 espécimes de bivalves foram datados integrando racemização de aminoácidos e 14C AMS. Além disto, análises tafonômicas foram realizadas em todas as amostras datadas, incluindo mais sete amostras em sedimentos lamosos. A resolução temporal (time-averaging) e a variabilidade total de idades (mistura temporal) basearam-se em uma nova abordagem numérica, a estatística bayesiana, que integra os erros e as incertezas derivadas da distribuição posterior dos resíduos associados com os modelos resultantes das calibrações das idades. As tendências onshore-offshore — aumento da mediana e da uniformidade das curvas de frequência de distribuição de idades, redução da variabilidade tafonômica, ainda que a escala do time-averaging seja invariante — provavelmente refletem a interação entre as mudanças do nível relativo do mar e da bioprodutividade mais elevada em águas menos profundas. / The temporal resolution of the fossil record plays a key role in paleontology because it determines the scale and the precision of paleoecological and evolutionary studies. The temporal resolution of the fossil record is estimated by the magnitude of time-averaging (non-contemporaneous generations preserved in a single layer, a bulk-sample). Quantitative estimates of time-averaging have been conducted primarily on mollusk shells from modern shallow-water marine settings. Most of them have been addressed in the Southern Brazilian continental shelf (SBS; 22°S up to 34°S), which is considered a natural laboratory for several similar studies since the earlier of current century (XXI). Consequently, the SBS has several available datasets that allow comparisons of the new results displayed here with those previous data. Thus, this thesis aimed answer (i) what is the magnitude of time-averaging on SBS mollusk death assemblages? (ii) how does time-averaging vary across spatial gradients? and (iii) how does time-averaging can reflect on the preservation of the fossil record? Here, >140 specimens were individually dated using amino acid racemization calibrated using radiocarbon ages (14C). In addition, taphonomic analyses were conducted in all samples, including more seven muddy sites. The time-averaging and the total age variability was based on a Bayesian approach that integrates the estimation errors and uncertainties derived from the posterior distribution associated with the 14C–AAR calibration average model. The onshore-offshore trends — increased median age, decreased skewness of age distributions, decreased taphonomic variation, yet the invariant scale of time-averaging — likely reflect the interplay between sea-level changes and elevated bioproductivity in shallower water settings.

The ribosome is responsible for mRNA-templated protein translation in all living cells. The translational machinery (TM) has evolved to use 20 amino acids each esterified onto one of several tRNA bodies. While the active site of the ribosome, known as the peptidyl transferase center (PTC), is able to handle a remarkable amount of substrate diversity, many classes of unnatural amino acids are not compatible with the TM. For example, in the field of unnatural amino acid mutagenesis, the site-specific incorporation of biologically useful amino acids into proteins, such as fluorophores, has often proven to be unfeasible. This runs counter to the accepted notion that the ribosome is blind to the structure of the amino acid and is capable of accepting any amino acid as long as the mRNA codon: tRNA anticodon pairing is correct. Two studies by our group set out to test the hypothesis that the ribosome can indeed discriminate the structure of the amino acid. Using a fully purified E. coli translation system, the first study showed that natural amino acids misacylated onto fully modified but non-native tRNAs show small but reproducible effects on the steps of aminoacyl-tRNA (aa-tRNA) selection. The second study, in which I participated, utilized D-aa-tRNAs in the same E. coli translation system to study how amino acids of the inverted stereochemistry to those found in ribosomally-synthesized proteins affect translation elongation. We showed that these unnatural substrates serve as peptidyl acceptors but once translocated into the P-site of the ribosome, fail as peptidyl donors and stall translation elongation by inactivating the PTC. The motivation of my work has been to further characterize the effects of D-aa-tRNAs on translation elongation. To this end, I examined how the PTC is affected structurally and functionally by the presence of ribosomal substrates containing D-amino acids. Chapter one contains an introduction to this work. Chapter two describes chemical probing experiments that demonstrate that the presence of peptidyl-D-aminoacyl-tRNAs in the P-site of the ribosome allosterically modulates the secondary structure of ribosomal exit tunnel nucleotides A2058 and A2059. Chapter three describes how the reactivity of peptidyl-D-aminoacyl-tRNAs to form tripeptides is highly dependent on the identity of the amino acid it is reacting with; protein yields can be close to what is obtained with natural amino acids or almost completely abolished. Chapter four contains the methods used to do this research. From the observations presented here as well as from the work of other laboratories, a picture of the PTC emerges in which the pairing of the A- and P- site substrates is integral in either promoting or suppressing catalysis by the PTC. This work has implications for the field of unnatural amino acid mutagenesis, particularly for strategies to improve the incorporation of interesting unnatural amino acid by the ribosome. In addition, this work adds an important aspect to the growing body of knowledge of ribosome stalling at the PTC.

No description available.

<p>The ability to create surfaces with well-defined chemical properties is a major research field. One possibility to do this is to design peptides that bind with a specific secondary structure to silica nanoparticles. The peptides discussed in this thesis are constructed to be random coil in solution, but are “forced” to become helical when adsorbed to the particles. The positively charged side-chains on the peptides strongly disfavor an ordered structure in solution due to electrostatic repulsion. When the peptides are introduced to the particles these charges will strongly favor the structure because of ion pair bonding between the peptide and the negatively charged nanoparticles. The peptide-nanoparticle system has been thoroughly investigated by systematic variations of the side-chains. In order to determine which factors that contributes to the induced structure, several peptides with different amino acid sequences have been synthesized. Factors that have been investigated include 1) the positive charge density, 2) distribution of positive charges, 3) negative charge density, 4) increasing hydrophobicity, 5) peptide length, and 6) by incorporating amino acids with different helix propensities. Moreover, pH dependence and the effect of different nanoparticle curvature have also been investigated. It will also be shown that the system can be modified to incorporate a catalytic site that is only active when the helix is formed. This research will increase our understanding of peptide-surface interactions and might be of importance for both nanotechnology and medicine.</p>

Simultaneous measurements of energy and protein metabolism can provide valuable information about their interactions. Dietary lysine is limiting in typical feedstuffs fed to swine and, therefore, limits protein synthesis. Current recommendations for dietary amino acid and energy intakes may not be reflective of the requirements for modern, highly productive sows and, therefore, invalidate requirement estimates determined according to the factorial approach. Current feeding recommendations suggest a constant amino acid intake throughout gestation. However, the demands for amino acids changes from maternal tissue accretion in early-gestation to fetal, conceptus, and mammary tissue development in late-gestation. This thesis reports the method development associated with simultaneous measurements of energy and protein metabolism and its application to determine dietary lysine requirements in non-pregnant and pregnant sows using the indicator amino acid oxidation method. Two indirect calorimetry systems and an experimental feeding regimen were tested and validated for use in studies of amino acid requirements by stable isotope dilution. Protein and energy balance studies were performed in non-pregnant sows fed two distinct levels of energy and protein intake. The systems reacted appropriately to changes in gas concentrations induced by sow respiration. Protein and energy balance studies were also performed in pregnant and lactating sows fed typical diets. Sows appeared more anabolic during mid-gestation and were catabolic by late-gestation and through lactation, where additional energy intake provided by ad libitum feed intake increased milk energy output. The dietary lysine requirement in non-pregnant sows at maintenance was determined as 49 mg/kg0.75, 30% greater than current recommendations. The dietary lysine requirement was determined to be 10.1 g/d and 16.5 g/d, in early- and late-gestation, respectively. These results suggest that a constant diet formulation for the entirety of gestation is not appropriate. In conclusion, simultaneous measurements of energy and protein metabolism combining indirect calorimetry and stable isotope techniques may be used to define requirements for dietary amino acids in sows. Basic assumptions of the factorial approach to estimate requirements require further investigation, including the dietary lysine requirement. Application of phase feeding for sows during gestation can more correctly meet the demands for amino acids and energy, improving sow longevity. / Animal Science

The activity of glutamate transporters is essential for the temporal and spatial regulation of the neurotransmitter concentration in the synaptic cleft which is critical for proper neuronal signaling. Because of their role in controlling extracellular glutamate concentrations, dysfunctional glutamate transporters have been implicated in several neurodegenerative diseases and psychiatric disorders. Therefore, investigating the mechanism of substrate transport by these transporters is essential in understanding their behavior when they malfunction. A bacterial glutamate transporter homologue has been successfully crystallized revealing the molecular architecture of glutamate transporters. However, many important questions remain unanswered. In this thesis, I will address the role of D439 in the binding of Na+, and I will identify other electrogenic steps that contribute to the total electrogenicity of the transporter cycle. The role of D439 in the binding of Na+ to the transporter was explored previously in this lab. While it was proposed that the effect of D439 in Na+ binding is indirect, the results described in this thesis provides added support to this work. Here, I will show that the D439 mutation changed the pharmacology of EAAC1 such that THA was converted from a transported substrate to a competitive inhibitor. I will also show that Na+ binding to the substrate-bound mutant transporter occurred with the same affinity as that of Na+ to the substrate-bound wild-type transporter. Therefore, based on these results, D439 is not directly involved in the binding of Na+ to the substrate-bound transporter, but that its effect is rather indirect through changing the substrate binding properties. Na+ binding steps to the empty transporter and to the glutamate-bound EAAC1 contribute only 20% of the total electrogenicity of the glutamate transporter reactions cycle. While K+-induced relocation has been proposed to be electrogenic, there is no experimental evidence that supports it. In this work, I will show that the K+-induced relocation of the empty transporter is electrogenic. Moreover, the results in this work show that the K+-dependent steps are slower than the steps associated with the Na+/glutamate translocation suggesting that the K+-induced relocation determines the transporter?s properties at steady state.

The ability to create surfaces with well-defined chemical properties is a major research field. One possibility to do this is to design peptides that bind with a specific secondary structure to silica nanoparticles. The peptides discussed in this thesis are constructed to be random coil in solution, but are “forced” to become helical when adsorbed to the particles. The positively charged side-chains on the peptides strongly disfavor an ordered structure in solution due to electrostatic repulsion. When the peptides are introduced to the particles these charges will strongly favor the structure because of ion pair bonding between the peptide and the negatively charged nanoparticles. The peptide-nanoparticle system has been thoroughly investigated by systematic variations of the side-chains. In order to determine which factors that contributes to the induced structure, several peptides with different amino acid sequences have been synthesized. Factors that have been investigated include 1) the positive charge density, 2) distribution of positive charges, 3) negative charge density, 4) increasing hydrophobicity, 5) peptide length, and 6) by incorporating amino acids with different helix propensities. Moreover, pH dependence and the effect of different nanoparticle curvature have also been investigated. It will also be shown that the system can be modified to incorporate a catalytic site that is only active when the helix is formed. This research will increase our understanding of peptide-surface interactions and might be of importance for both nanotechnology and medicine.

This research investigates the interfacial interactions between biological entities and synthetic materials at two length scales: bulk and nanometer size. At the bulk scale, biomolecule adhesion is key for synthetic material incorporation in the body. Quantifying the adhesion strength becomes necessary. For the nanometer scale, the nanoparticles are generally delivered through the blood stream and their effect on the blood flow must be studied. An experimental approach was taken to study interaction at both material length scales. The cell/protein adhesion strength to bulk-sized materials was studied. The goal was to identify the most influential factor affecting adhesion: chemistry or surface roughness. The effects of nanoparticles on the viscosity of protein and amino acid solutions were measured. A statistical thermodynamic analysis was focused on the entropy change induced by the addition of gold nanoparticles to protein/amino acid solutions. Rheological studies were applied. A rheometer with a parallel plate was used to quantify the adhesion strength of cells and proteins to synthetic surfaces at the bulk scale. The adhesion strength depends on the applied shear stress and the radius of cells or proteins that remained attached to the surface after testing. At the nanometer scale, the viscosity of the nanoparticle enhanced protein or amino acid solutions were measured with a cone and plate. The adhesion studies were conducted with the following biological entities: fibroblasts, egg-white protein, and neurons. The fibroblast adhesion to poly(carbonate) and poly(methyl methacrylate) demonstrate fibroblasts are strongly attached to highly polar materials. Protein adhesion to titanium and chromium nitride coatings showed that chemical composition is the most influential factor. The neuron adhesion to poly-D-lysine coated glass demonstrated that neuron strengthening was due to an increase in adhesion molecules at the neuron/material interface. For nanoparticulates, it was found that the charged nanoparticles affect the protein and amino acid conformation and the potential energy of the solutions. Quantifying biomolecule adhesion to surfaces and predicting the behavior of nanoparticles inside a biological system are crucial for material selection and application. The major impact of this research lies in observing the interaction mechanisms at the interfaces of material-biological entities.

Proteins are the basic building blocks of biological organisms, and are responsible for a variety of functions within them. Proteins are composed of unique amino acid sequences. Some has only one sequence, while others contain several sequences that are combined together. These combined amino acid sequences fold to form a unique three-dimensional (3D) shape. Although the sequences may fold proteins into different 3D shapes in diverse environments, proteins with similar amino acid sequences typically have similar 3D shapes and functions. Knowledge of the 3D shape of a protein is important in both protein function analysis and drug design, for example when assessing the toxicity reduction associated with a given drug. Due to the complexity of protein 3D shapes and the close relationship between shapes and functions, the prediction of protein 3D shapes has become an important topic in bioinformatics. This research introduces a new approach to predict proteins’ 3D shapes, utilizing a multilayer artificial neural network. Our novel solution allows one to learn and predict the representations of the 3D shape associated with a protein by starting directly from its amino acid sequence descriptors. The input of the artificial neural network is a set of amino acid sequence descriptors we created based on a set of probability density functions. In our algorithm, the probability density functions are calculated by the correlation between the constituent amino acids, according to the substitution matrix. The output layer of the network is formed by 3D shape descriptors provided by an information retrieval system, called CAPRI. This system contains the pose invariant 3D shape descriptors, and retrieves proteins having the closest structures. The network is trained by proteins with known amino acid sequences and 3D shapes. Once the network has been trained, it is able to predict the 3D shape descriptors of the query protein. Based on the predicted 3D shape descriptors, the CAPRI system allows the retrieval of known proteins with 3D shapes closest to the query protein. These retrieved proteins may be verified as to whether they are in the same family as the query protein, since proteins in the same family generally have similar 3D shapes. The search for similar 3D shapes is done against a database of more than 45,000 known proteins. We present the results when evaluating our approach against a number of protein families of various sizes. Further, we consider a number of different neural network architectures and optimization algorithms. When the neural network is trained with proteins that are from large families where the proteins in the same family have similar amino acid sequences, the accuracy for finding proteins from the same family is 100%. When we employ proteins whose family members have dissimilar amino acid sequences, or those from a small protein family, in which case, neural networks with one hidden layer produce more promising results than networks with two hidden layers, and the performance may be improved by increasing the number of hidden nodes when the networks have one hidden layer.