Bisphenol A (BPA) and phthalates are chemicals found in many consumer products including water bottles, food packaging and cosmetics. Previous research has shown that there is potential for these compounds to contribute to obesity. In this analysis, the Canadian Health Measures Survey was used to investigate possible associations between urinary concentrations of these compounds and measures of adiposity. BPA urine concentrations were found to decrease with age, and significant associations with BMI and waist circumference were found in linear regression in adults. No associations with measures of adiposity were found in logistic regression for adults and significant negative associations were found in children. A similar discrepancy was found for mono-(2-ethyl-5-hydroxyhexyl) phthalate and mono-(2-ethyl-5-oxohexyl) phthalate, which were significantly associated with obesity in adults, but showed several significant negative associations in children. Overall, this analysis showed that it is unlikely that BPA and phthalates are contributing to adiposity in the Canadian population.

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack – localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack – localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component P∞. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erd ̋os-R ́enyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent λ. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks are much more vulnerable to localized attack compared with random attack. In the second part, we extend the tree-like generating function method to incorporating clustering structure in complex networks. We study the robustness of a complex network system, especially a network of networks (NON) with clustering structure in each network. We find that the system becomes less robust as we increase the clustering coefficient of each network. For a partially dependent network system, we also find that the influence of the clustering coefficient on network robustness decreases as we decrease the coupling strength, and the critical coupling strength qc, at which the first-order phase transition changes to second-order, increases as we increase the clustering coefficient.

In the first study presented here, the 2.5 Å crystal structure1 of the cytochrome <i>b₆f</i> complex obtained from the cyanobacterium Nostoc sp. PCC 7120 (pdb 4OGQ) was used as a guide for modification by site-directed mutagenesis in the cyanobacterium Synechococcus sp. PCC 7002 of the rate-limiting step in the central electron transport/proton translocation chain of oxygenic photosynthesis. This step is associated with the oxidation and deprotonation of plastoquinol on the electrochemically positive (p) side of the membrane. The mutagenesis strategy is based on structure studies of the <i>b₆f</i> complex in the absence and presence of quinol analogue inhibitors which bind and inhibit electron transport on the p-side of the thylakoid membrane. The strategy focused on two conserved prolines located on the p-side of the F-helix, proximal to the C-helix, in subunit IV of the seven subunit cytochrome <i>b₆f</i> complex. These prolines, residues 105 and 112 in the F-helix, are seen in the crystal structure to cause a bend in this helix away from the C-helix in the cytochrome b subunit. Thus, they are predicted to increase the portal aperture for the plastoquinol generated in the photosystem II reaction center complex that serves as the electron-proton donor to the [2Fe-2S] iron-sulfur protein and the pside b-heme. Changing the two prolines to alanine resulted in a decrease of 30-50 % in the logphase growth rate of the cell culture and reduction of photo-oxidized cytochrome f. The second study examines the binding thermodynamics of the cytochrome b6f complex and a purposed binding partner, PGRL1, using isothermal titration calorimetry. Proton Gradient Regulation-Like 1 (PGRL1) is thought to be necessary for efficient cyclic electron transfer, however, it’s mechanistic role is unknown. Here we examined for PGRL1 and cytochrome b6f complex binding and found there was no detectable interaction, indicating that PGRL1 is not a direct quinone/cyt b6f electron cofactor.<br>

The role of metal ions as catalysts for numerous biochemical reactions has been the subject of many investigations. One of the most important classes of ligands are phosphate esters. In this thesis I describe the investigation of some phosphate ester-metal ion equilibria. Formation constants for the complexation of p-nitrophenyl phosphate, phenyl phosphate, 1-naphthyl phosphate, α-D-glucose-1'-phosphate, glycerol-2-phosphate, methyl phosphate, 8-quinolyl phosphate, 8-quinolyl methyl phosphate, triphosphate and fluorotriphosphate with protons, copper, zinc and calcium ions were determined by potentiometry. In addition, the complexation of 1-naphthyl phosphate, 8-quinolyl phosphate and 8-quinolyl methyl phosphate with nickel and cobalt ions was also studied. Protonation enthalpies and copper complexation enthalpies of p-nitrophenyl phosphate, phenyl phosphate, 1-naphthyl phosphate, α-D-glucose-1'-phosphate, glycerol-2-phosphate and methyl phosphate were determined by calorimetry. A correlation between the nucleophilicity of the ester group and the magnitude of the stability constants of the proton, copper and zinc complexes of p-nitrophenyl phosphate, phenyl phosphate, 1-naphthyl phosphate, α-D-glucose-1'-phosphate, glycerol-2-phosphate and methyl phosphate is found and explained in terms of electronic induction effects, i.e. by polarisation of the phosphate oxygens by the ester group. The calorimetric results show that the desolvation of ligand and metal ion during the complexation plays an important role. The possibility of similar correlations for complexes of triphosphates is also discussed.

Mineral detection and geological mapping through conventional ground survey methods based on field observation and other geological techniques are tedious, time-consuming and expensive. Hence, the use of remote sensing in mineral detection and lithological mapping has become a generally accepted augmentative tool in exploration. With the advent of multispectral sensors (e.g. ASTER, Landsat and PlanetScope) having suitable wavelength coverage and bands in the Shortwave Infrared (SWIR) and Thermal Infrared (TIR) regions, multispectral sensors, along with common and advanced algorithms, have become efficient tools for routine lithological discrimination and mineral potential mapping. It is with this paradigm in mind that this project sought to evaluate and discuss the detection and mapping of magnetite on the Eastern Limb of the Bushveld Complex, using specialized common traditional and machine learning algorithms. Given the wide distribution of magnetite, its economic importance, and its potential as an indicator of many important geological processes, the delineation of magnetite is warranted. Before this study, few studies had looked at the detection and exploration of magnetite using remote sensing, although remote sensing tools have been regularly applied to diverse aspects of geosciences. Maximum Likelihood, Minimum Distance to Means, Artificial Neural Networks, Support Vector Machine classification algorithms were assessed for their respective ability to detect and map magnetite using the PlanetScope Analytic Ortho Tiles in ENVI, QGIS, and Python. For each classification algorithm, a thematic landcover map was attained and an error matrix, depicting the user's and producer's accuracies, as well as kappa statistics, was derived, which was used as a comparative measure of the accuracy of the four classification algorithms. The Maximum Likelihood Classifier significantly outperformed the other techniques, achieving an overall classification accuracy of 84.58% and an overall kappa value of 0.79. Magnetite was accurately discriminated from the other thematic landcover classes with a user’s accuracy of 76.41% and a producer’s accuracy of 88.66%. Despite the Maximum Likelihood classification algorithm illustrating better class categorization, a large proportion of the mining activity pixels were erroneously classified as magnetite. However, this observation was not merely limited to the Maximum Likelihood classification algorithm, but all image classifications algorithms. The overall results of this study illustrated that remote sensing techniques are effective instruments for geological mapping and mineral investigation, especially in iron oxide mineralization in the Eastern Limb of Bushveld Complex. / Dissertation (MSc)--University of Pretoria, 2019. / Geology / MSc / Unrestricted

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Neural circuits that mediate complex behaviors contain several cell types, yet little is known about the role of each cell type within these circuits. An example problem in the auditory domain is how cortical circuits process complex natural sounds amidst competing stimuli from different spatial sources, also known as the "cocktail party effect". A pre-study recorded cortical responses in songbirds and found that neurons are broadly tuned to sound location when only one sound is present; when a competing stimulus is introduced, neurons sharpen their spatial tuning. These results were visualized by "spatial grids" that show preferred sound source locations in the presence of competing stimuli. These experiments motivated a computational model which proposed that lateral inhibition between spatially tuned channels within cortex is a key mechanism for spatial sound segregation. Cortical circuits are known to contain both excitatory cells and subpopulations of inhibitory interneurons, the roles of which can be probed in vivo with optogenetic techniques. Motivated by these past results and the optogenetic tools readily available in the mouse model, I present experimental and computational approaches in uncovering the cortical circuits that aid in solving the cocktail party problem in mouse auditory cortex (ACx). First, I probe the role of parvalbumin-expressing (PV) interneurons in solving the cocktail party problem using optogenetic and electrophysiological techniques. I found that mice exhibit similar cortical spatial grids as in songbirds, and optogenetic suppression of PV neurons reduces discriminability between dynamic sounds in both clean and masked presentations of spatially distributed stimuli. To mechanistically explain these results, I create a two-layer computational model of ACx with PV subpopulations that respond to distinct temporal stimulus features. I found that differentially weighing inhibition from these interneurons captures the range of neural discriminability performances found in cortex and the effects of optogenetically suppressing PV cells. Next, I analyze the population coding of neurons during the cocktail party problem. Here, I found that a relatively compact and diverse population of neurons within cortex is sufficient for encoding sounds from competing spatial locations. Finally, I determine how changes in behavioral states via tone extinction tasks affect activity in ACx and medial prefrontal cortex (mPFC). Results show that alpha and beta oscillations (8-18 Hz) in response to unrewarded tones exhibited immediate and robust increases in both regions prior to behavioral changes. When subjects learned to suppress behavioral responses, coherence at 8-18 Hz between ACx and mPFC was enhanced and spiking at ACx in response to the unrewarded tone was decreased. Taken together, this work advances the knowledge of both bottom-up and top-down circuit mechanisms underlying the cocktail party problem. / 2024-01-16T00:00:00Z

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