This thesis has developed a suite of compound specific stable isotope tools to monitor landfill leachate and identify the infiltration of leachate to ground water and surface water. These tools have the power to indicate the fractional contribution multiple discrete sources of pollution are making to a single location. This journey began by developing two solid phase extraction (SPE) methods to extract non-polar and polar organic compounds from leachate with minimal fractionation of hydrogen or carbon isotopes. Non-polar compounds were successfully extracted using ENV+ SPE cartridges and polar compounds were successfully extracted using Strata-X SPE cartridges. The isotopic fractionation of non-polar compounds during ENV+ extraction varied significantly (up to 245⁰/₀₀ and 1.8⁰/₀₀ for D and ��C respectively, when eluted with acetonitrile and ethyl acetate, as recommended by manufacturers) but the fractionation of compounds eluted with dichloromethane was negligible (less than instrumental precision). Polar compounds were eluted from Strata-X cartridges with negligible isotopic fractionation using methanol. The direct comparison of SPE and liquid-liquid extraction found SPE to extract slightly more compound from leachate then liquid-liquid extraction (especially for polar compounds) and the isotopic compositions of compounds did not change with extraction methods. These new analytical methods subsequently were used to determine the isotopic compositions of organic compounds dissolved in leachates from three New Zealand landfills. The molecular and isotopic signature of leachate varied significantly between landfills, indicating the isotopic fingerprint of organic compounds in leachate is unsuitable as a universal tracer of leachate. However, compounds such as terpien-4-ol, methylethylbenzene and juvabione maintained their isotopic composition over short geographical distance-indicating their potential as site-specific tracers of leachate. Organic compounds analysed on a transect across the landfill boundary indicated polar compounds were more mobile than semi-volatile compounds and possessed a more conservative isotopic composition. However, hexadecanoic acid extracted from leachate and ground water was highly depleted in ��C (-72 ⁰/₀₀ to -40⁰/₀₀), indicative of methanogenic and sulfate reducing bacteria. These bacteria only live in highly reducing environments such as leachate; therefore their presence in the pristine environment can potentially indicate the release of leachate from the landfill. The final experiments traced the uptake and utilisation of leachate by periphyton. The isotopic composition of bulk periphyton, fatty acids and phytol indicated that microbial assimilation and utilisation of nutrients is a complex process. Fatty acid biomarkers for green algae and diatoms showed signs of leachate derived nutrients, however the availability of nutrients (carbon, nitrogen, water and light) caused significant changes in metabolic processes and isotopic compositions. Under slow growing conditions, the [delta]��C composition of periphyton became enriched in ��C as solar irradiation levels decreased (including shading by detritus and periphyton), while the [delta]D composition of fatty acid was controlled by the internal recycling of hydrogen. This study indicated the power of compound specific isotope analysis as a tool to detect the release of landfill leachate from a landfill, especially at locations with multiple potential sources of contaminants, and provides a sound platform for future research.

No description available.

At present several groups are analysing quasar absorption spectra to search for variation of the fine structure constant, alpha, across space and time. These studies compare the wavelengths of several transitions observed in the absorption clouds with those seen in the laboratory, and interpret anomalies as variation in alpha. One group has already presented evidence that alpha may have been smaller at an early epoch. Other groups using different telescopes see no variation. These studies use the ???many-multiplet??? method, which relies on the utilisation of many transitions in many ions to enhance the size of the effects and remove sources of systematic error. While this method offers an order-of-magnitude improvement in sensitivity over the previously used alkali-doublet method, the alpha-dependence (relativistic shift) of every transition used in the analysis must be calculated ab initio. In this thesis we present a method for the precise calculation of relativistic shifts, based on an energy calculation involving combination of the configuration interaction method and many-body perturbation theory. The many-multiplet method also introduces a potential systematic error: if the relative isotope abundances of the absorbers differ from terrestrial abundances then there can be spurious shifts in the measured wavelengths, which may be incorrectly interpreted as variation of alpha. A ???conspiracy??? of several isotopic abundances may provide an alternative explanation for the observed spectral anomalies. To account for these systematic errors we need accurate values of the isotope shift. We calculate these shifts using the finite-field method to reduce the problem to that of an energy calculation, which in turn is done using the same method used for the relativistic shift. We present the results of our calculations for a variety of atoms and ions seen in quasar absorption spectra. The results of this research should allow astrophysicists to measure isotope abundances in the absorbers directly. This can provide a test for models of nuclear reactions in stars and supernovae, and of the chemical evolution of the Universe. Our calculations can also be used in conjunction with measurements to extract changes in nuclear charge radii between isotopes.

Recombinant protein production by mammalian cells is a core component of today’s multi-billion dollar biopharmaceutical industry. Transcriptome and proteome technologies have been used to probe for cellular components that correlate with higher cell-specific productivity, but have yet to yield results that can be translated into practical metabolic engineering strategies. The recognition of cellular complexity has led to an increasing adoption of systems biology, a holistic investigation approach that aims to bring together different omics technologies and to analyze the resulting datasets under a unifying context. Fluxomics is chosen as the platform context to investigate cell metabolism because it captures the integrated effects of gene expression, enzyme activity, metabolite availability and regulation, thereby providing a global picture of the cell’s metabolic phenotype. At present, the routine quantification of cell metabolism revolves around very basic cellular parameters: growth, substrate utilization and product formation. For a systems approach, however, just measuring gross metabolic features is insufficient; we are compelled to perform high-resolution, large-scale fluxomics in order to match the scale of other omics datasets. The challenges of performing large-scale fluxomics come from two opposing fronts. Metabolic flux analysis (MFA) is the estimation of intracellular fluxes from experimental data using a stoichiometric model, a process very much susceptible to modelling biases. The in silico challenge is to construct the most comprehensive model to represent the metabolism of a specific cell, while the in vivo challenge is to resolve as many fluxes as possible using experimental measurements or constraints. A compromise needs to be established between maximizing the resolution of the MFA model and working within technical limitations of the flux experiment. Conventional MFA models assembled from textbook pathways have been available for animal cell culture for the past 15 years. A state-of-the-art model was developed and used to analyse continuous hybridoma culture and batch CHO cell culture data (Chapter 3). Reasonable metabolic assumptions combined with constraint based analysis exploiting irreversibility constraints enabled the resolution of most fluxes in central carbon metabolism. However, while the results appear consistent, there is insufficient information in conventional measurement of uptake, secretion and growth data to assess the completeness of the model and validity of all assumptions. 13C metabolic flux analysis (13C MFA) can potentially resolve fluxes in the central carbon metabolism using flux constraints generated from 13C enrichment patterns of metabolites, but the multitude of substrate uptakes (glucose and amino acids) seen in mammalian cells, in addition to the lack of 13C enrichment data from proteinogenic amino acids, makes it very difficult to anticipate how a labelling experiment should be carried out. The challenges above have led to the development of a systematic workflow to perform large-scale MFA for mammalian cells. A genome-scale model (GeMs), an accurate compilation of gene-protein-reaction-metabolite associations, is the starting basis to perform whole-cell fluxomics. A semi-automated method was developed in order to rapidly extract a prototype of GeM from KEGG and UniProtKB databases (Chapter 4). Core metabolic pathways in the mouse GeM are mostly complete, suggesting that these databases are comprehensive and sufficient. The rapid prototyping system takes advantage of this, making long term maintenance of an accurate and up-to-date GeM by an individual possible. A large number of under-determined pathways in the mouse GeM cannot be resolved by 13C MFA because they do not produce any distinctive 13C enrichment patterns among the carbon metabolites. This has led to the development of SLIPs (short linearly independent pathways) for visualizing these under-determined metabolic pathways contained in large-scale GeMs (Chapter 5). Certain SLIPs are subsequently removed based on careful consideration of their pathway functions and the implications of their removal. A majority of SLIPs have a cyclic configuration, sharing similar redox or energy co-metabolites; very few represent true conversion of substrates to products. Of the 266 under-determined SLIPs generated from the mouse GeM, only 27 SLIPs were incorporated into the final working model under the criterion that they are significant pathways and are potentially resolvable by tracer experiments. Most of these SLIPs are degradation pathways of essential amino acids and inter-conversion of non-essential amino acids (Chapter 8). In parallel, OpenFLUX was developed to perform large-scale isotopic 13C MFA (Chapter 6). This software was built to accept multiple labelled substrates, and no restriction has been placed on the model type or enrichment data. These are necessary features to support large-scale flux analysis for mammalian cells. This was followed by the development of a design strategy that uses analytical gradients of isotopomer measurements to predict resolvability of free fluxes, from which the effectiveness of various 13C experimental scenarios using different combinations of input substrates and isotopomer measurements can be evaluated (Chapter 7). Hypothetical and experimental results have confirmed the predictions that, when glucose and glutamate/glutamine are simultaneously consumed, two separate experiments using [U-13C]- and [1-13C]-glucose, respectively, should be performed. If there is a restriction to a single experiment, then the 80:20 mixture of [U-13C]- and [1-13C]-glucose can provide a better resolution than other labelled glucose mixtures (Chapter 7 and Chapter 8). The tools and framework developed in this thesis brings us within reach of performing large-scale, high-resolution fluxomics for animal cells and hence realising systems-level investigation of mammalian metabolism. Moreover, with the establishment of a more rigorous, systematic modelling approach and higher functioning computational tools, we are now at a position to validate mammalian cell culture flux experiments performed 15 years ago.

Recombinant protein production by mammalian cells is a core component of today’s multi-billion dollar biopharmaceutical industry. Transcriptome and proteome technologies have been used to probe for cellular components that correlate with higher cell-specific productivity, but have yet to yield results that can be translated into practical metabolic engineering strategies. The recognition of cellular complexity has led to an increasing adoption of systems biology, a holistic investigation approach that aims to bring together different omics technologies and to analyze the resulting datasets under a unifying context. Fluxomics is chosen as the platform context to investigate cell metabolism because it captures the integrated effects of gene expression, enzyme activity, metabolite availability and regulation, thereby providing a global picture of the cell’s metabolic phenotype. At present, the routine quantification of cell metabolism revolves around very basic cellular parameters: growth, substrate utilization and product formation. For a systems approach, however, just measuring gross metabolic features is insufficient; we are compelled to perform high-resolution, large-scale fluxomics in order to match the scale of other omics datasets. The challenges of performing large-scale fluxomics come from two opposing fronts. Metabolic flux analysis (MFA) is the estimation of intracellular fluxes from experimental data using a stoichiometric model, a process very much susceptible to modelling biases. The in silico challenge is to construct the most comprehensive model to represent the metabolism of a specific cell, while the in vivo challenge is to resolve as many fluxes as possible using experimental measurements or constraints. A compromise needs to be established between maximizing the resolution of the MFA model and working within technical limitations of the flux experiment. Conventional MFA models assembled from textbook pathways have been available for animal cell culture for the past 15 years. A state-of-the-art model was developed and used to analyse continuous hybridoma culture and batch CHO cell culture data (Chapter 3). Reasonable metabolic assumptions combined with constraint based analysis exploiting irreversibility constraints enabled the resolution of most fluxes in central carbon metabolism. However, while the results appear consistent, there is insufficient information in conventional measurement of uptake, secretion and growth data to assess the completeness of the model and validity of all assumptions. 13C metabolic flux analysis (13C MFA) can potentially resolve fluxes in the central carbon metabolism using flux constraints generated from 13C enrichment patterns of metabolites, but the multitude of substrate uptakes (glucose and amino acids) seen in mammalian cells, in addition to the lack of 13C enrichment data from proteinogenic amino acids, makes it very difficult to anticipate how a labelling experiment should be carried out. The challenges above have led to the development of a systematic workflow to perform large-scale MFA for mammalian cells. A genome-scale model (GeMs), an accurate compilation of gene-protein-reaction-metabolite associations, is the starting basis to perform whole-cell fluxomics. A semi-automated method was developed in order to rapidly extract a prototype of GeM from KEGG and UniProtKB databases (Chapter 4). Core metabolic pathways in the mouse GeM are mostly complete, suggesting that these databases are comprehensive and sufficient. The rapid prototyping system takes advantage of this, making long term maintenance of an accurate and up-to-date GeM by an individual possible. A large number of under-determined pathways in the mouse GeM cannot be resolved by 13C MFA because they do not produce any distinctive 13C enrichment patterns among the carbon metabolites. This has led to the development of SLIPs (short linearly independent pathways) for visualizing these under-determined metabolic pathways contained in large-scale GeMs (Chapter 5). Certain SLIPs are subsequently removed based on careful consideration of their pathway functions and the implications of their removal. A majority of SLIPs have a cyclic configuration, sharing similar redox or energy co-metabolites; very few represent true conversion of substrates to products. Of the 266 under-determined SLIPs generated from the mouse GeM, only 27 SLIPs were incorporated into the final working model under the criterion that they are significant pathways and are potentially resolvable by tracer experiments. Most of these SLIPs are degradation pathways of essential amino acids and inter-conversion of non-essential amino acids (Chapter 8). In parallel, OpenFLUX was developed to perform large-scale isotopic 13C MFA (Chapter 6). This software was built to accept multiple labelled substrates, and no restriction has been placed on the model type or enrichment data. These are necessary features to support large-scale flux analysis for mammalian cells. This was followed by the development of a design strategy that uses analytical gradients of isotopomer measurements to predict resolvability of free fluxes, from which the effectiveness of various 13C experimental scenarios using different combinations of input substrates and isotopomer measurements can be evaluated (Chapter 7). Hypothetical and experimental results have confirmed the predictions that, when glucose and glutamate/glutamine are simultaneously consumed, two separate experiments using [U-13C]- and [1-13C]-glucose, respectively, should be performed. If there is a restriction to a single experiment, then the 80:20 mixture of [U-13C]- and [1-13C]-glucose can provide a better resolution than other labelled glucose mixtures (Chapter 7 and Chapter 8). The tools and framework developed in this thesis brings us within reach of performing large-scale, high-resolution fluxomics for animal cells and hence realising systems-level investigation of mammalian metabolism. Moreover, with the establishment of a more rigorous, systematic modelling approach and higher functioning computational tools, we are now at a position to validate mammalian cell culture flux experiments performed 15 years ago.

"September, 1995" / Thesis (Ph.D.) -- Macquarie University, School of Earth Sciences, 1996. / Bibliography: leaves 171-183. / Introduction -- Australian ð¹³Corg-isotope profiles about the Permian-Triassic (P/TR) boundary -- Strontium isotope seawater curve in the late Permian of Australia -- ð¹³Cco₃ AND ð¹⁸Oco₃ seawater profiles through the Permian-Triassic of Australasia -- Paleomagnetic stratigraphy about the Permian/Triassic boundary in Australia -- Synthesis. / The Permian-Triassic boundary mass extinction is the largest in the Phanerozoic and therefore is the major event in the Phanerozoic. The mass extinction cause is problematical but studying global geochemical and geophysical signatures about the Permian-Triassic boundary can provide insights into the cause of the mass extinction. Global events about the Permian-Triassic boundary are marked by changes in: ð¹³C values of carbon ; ⁸⁷Sr/⁸⁶Sr in unaltered marine calcite ; magnetic polarity. -- This study aims to identify these features in the sedimentary record and to test the ca libration of the Australian biostratigraphical schemes to the global geological timescale. The following features are found in the Permian-Triassic sediments of Australia: a ð¹³Corg in Total Organic Carbon excursion in 12 marine and nonmarine sections from Northwest to Eastern Australia ; a ⁸⁷Sr/⁸⁶Sr minimum in a composite section mainly from the Bowen Basin ; a magnetic polarity reversal in the Cooper Basin, central Australia. The Australian sections are thus time correlated, as follows: The negative ð¹³Corg excursion indicates the Permian-Triassic boundary and occurs: 1) in Eastern and Central Australia at the change from coal measures to barren measures with red beds at the beginning of the Early Triassic coal gap; 2) in Northwest Australia about the boundary between the Hyland Bay Formation and the Mount Goodwin Formation in the Bonaparte Basin and at the boundary between the Hardman Formation and the Blina Shale in the Canning Basin. The base of the negative ð¹³Corg excursion lies at or near the base of the Protohaploxypinus microcorpuspalynological zone. The ⁸⁷Sr/⁸⁶Sr minimum determined about the Guadalupian/Ochoan stage boundary in North America is found in the Bowen Basin about the boundary between the Ingelara and Peawaddy Formations. The ð¹³Corg excursion in the Cooper Basin is near a magnetic reversal within the Permo-Triassic mixed superchron. The implications of these findings include: confirmation of the traditional placement of the Permian-Triassic boundary at the coal measures/barren measures with redbeds boundary in Eastern Australia ; the linking of the the Permian-Triassic boundary to a mass extinction of plant species on land and the beginning of the Triassic coal gap indicated by the Falcisporites Superzone base that is coincident with the negative ð¹³Corg excursion ; a mass extinction causal model that links the ⁸⁷Sr/⁸⁶Sr minimum determined about the Guadalupian/Ochoan stage boundary to a fall in sealevel that led to changing global environmental conditions. The model invokes greenhouse warming as a contributing cause of the mass extinction. / Mode of access: World Wide Web. / xii, 183 leaves ill., maps

Thesis (M.S. - Hydrology and Water Resources)--University of Arizona, 1982. / Includes bibliographical references (leaves 159-162).

Thesis (Ph.D.)--McMaster University (Canada), 1991. / Source: Dissertation Abstracts International, Volume: 53-11, Section: B, page: 5618. Supervisor: Henry P. Schwarcz.

Thesis (Ph.D.)--McMaster University (Canada), 1996. / Source: Dissertation Abstracts International, Volume: 57-10, Section: B, page: 6136. Adviser: M. J. McGlinchey.

Thesis (Ph.D.)--McMaster University (Canada), 1990. / Source: Dissertation Abstracts International, Volume: 62-13, Section: A, page: 0000.