Mineralogy, mineral chemistry, and genesis of precious metal-bearing volcanogenic massive sulfide deposits in the Newfoundland Appalachians, Canada: the Ming deposit as example

The Ming deposit, Newfoundland Appalachians, is a metamorphosed (upper greenschist to lower amphibolite facies), Cambro-Ordovician, bimodalmafic volcanogenic massive sulfide (VMS) deposit that consists of several, spatially-associated, elongated orebodies composed of stratabound semimassive to massive sulfides and/or discordant sulfide stringers in a rhyodacitic footwall. Copper is the main commodity; however, the deposit contains precious metal-bearing zones with elevated Au grades. In this study, field observations, microscopy, and micro-analytical tools including electron microprobe, laser ablation inductively coupled plasma mass spectrometry, and secondary ion mass spectrometry were used to constrain the relative timing of precious metal emplacement, the physico-chemical conditions of hydrothermal fluid precipitation, and the sources of sulfur, precious metals, semi-metals and metals. The ore mineral assemblage is complex and indicates an intermediate sulfidation state. Pyrite and chalcopyrite are the dominant ore minerals with minor sphalerite and pyrrhotite, and trace galena, arsenopyrite and cubanite. Additional trace phases include tellurides, NiSb phases, sulfosalts, electrum, AgHg±Au alloys, and oxides. Silver phases and precious metals occur predominantly in semi-massive and massive sulfides as free grains, and as grains spatially associated with arsenopyrite and/or sulfosalts. Precious metal phases occurring between recrystallized pyrite and within cataclastic pyrite are rare. Hence, the complex ore assemblage and textures strongly suggest syngenetic precious metal emplacement, whereas metamorphism and deformation only internally and locally remobilized precious metal phases. The ore assemblage formed from reduced, acidic hydrothermal fluids over a range of temperatures (≈350 to below 260ºC). The abundance of telluride and Ag-bearing tetrahedrite, however, varies strongly between the different orebodies indicating variable ƒTe₂, ƒSe₂, mBi, and mSb within the hydrothermal fluids. The variations in the concentrations of semi-metals and metals (As, Bi, Hg, Sb, Se, Te), as well as Au and Ag, were due to variations in temperature but also to a likely contribution of magmatic fluids into the VMS hydrothermal system from presumably different geothermal reservoirs. Sulfur isotope studies indicate at least two sulfur sources: sulfur from thermochemically-reduced seawater sulfate and igneous sulfur. The source of igneous sulfur is the igneous footwall, direct magmatic fluid/volatiles, or both. Upper greenschist to lower amphibolite metamorphic conditions and deformation had no significant effect on the sulfur isotope composition of the sulfides at the Ming deposit.

Ecohydrological separation in wet, low energy northern environments? A preliminary assessment using different soil water extraction techniques

Funded by European Research Council ERC. Grant Number: project GA 335910 VEWA

Ecohydrological separation in wet, low energy northern environments? A preliminary assessment using different soil water extraction techniques

Funded by European Research Council ERC. Grant Number: project GA 335910 VEWA

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Acoustic and Magnetic Techniques for the Isolation and Analysis of Cells in Microfluidic Platforms

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

Identifying the Structure and Fate of Wastewater Derived Organic Micropollutants by High-resolution Mass Spectrometry

Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

The application of aryne chemistry and use of α-diazo carbonyl derivatives in indazole synthesis with biological evaluation

This thesis outlines the synthetic chemistry involved in the preparation of a range of novel indazole compounds and details the subsequent investigation into their potential as biologically active agents. The synthetic route utilised in this research to form the indazole structure was the [3+2] dipolar cycloaddition of diazo carbonyl compounds with reactive aryne intermediates generated in situ. The preparation of further novel indazole derivatives containing different functional groups and substituents was performed by synthesising alternative 1,3- dipole and dipolarophile analogues and provided additionally diverse compounds. Further derivatisation of the indazole product was made possible by deacylation and alkylation methods. Transformation reactions were performed on alkenecontaining ester side chains to provide novel epoxide, aldehyde and tertiary amine derivatives. The first chapter is a review of the literature beginning with a short overview on the structure, reactivity and common synthetic routes to diazo carbonyl derivatives. More attention is given to the use of diazo compounds as 1,3-dipoles in cycloaddition reactions or where the diazo group is incorporated into the final product. A review of the interesting background, structure and reactivity of aryne intermediates is also presented. In addition, some common syntheses of indazole compounds are presented as well as a brief discussion on the importance of indazole compounds as therapeutic agents. The second chapter discusses the synthetic routes employed towards the synthesis of the range of indazoles. Initially, the syntheses of the diazo carbonyl and aryne precursors are described. Next, the synthetic methods to prepare the indazole compounds are provided followed by discussion on derivatisation of the indazole compounds including N-deacylation, N-benzylation and ester side-chain transformation of some alkene-containing indazoles. A series of novel indazole derivatives were submitted for anti-cancer screening at the U.S National Cancer Institute (NCI). A number of these derivatives were identified as hit compounds, with excellent growth inhibition. The results obtained from biological evaluation from the NCI are provided with further results pending from the Community for Open Antimicrobial Drug Discovery. The third chapter details the full experimental procedures, including spectroscopic and analytical data for all the compounds prepared during this research.

Development of a Surface-Enhanced Raman Spectroscopy Method for the Detection of Benzodiazepines in Urine

Benzodiazepines are among the most prescribed compounds for anti-anxiety and are present in many toxicological screens. These drugs are also prominent in the commission of drug facilitated sexual assaults due their effects on the central nervous system. Due to their potency, a low dose of these compounds is often administered to victims; therefore, the target detection limit for these compounds in biological samples is 10 ng/mL. Currently these compounds are predominantly analyzed using immunoassay techniques; however more specific screening methods are needed. The goal of this dissertation was to develop a rapid, specific screening technique for benzodiazepines in urine samples utilizing surface-enhanced Raman spectroscopy (SERS), which has previously been shown be capable of to detect trace quantities of pharmaceutical compounds in aqueous solutions. Surface enhanced Raman spectroscopy has the advantage of overcoming the low sensitivity and fluorescence effects seen with conventional Raman spectroscopy. The spectra are obtained by applying an analyte onto a SERS-active metal substrate such as colloidal metal particles. SERS signals can be further increased with the addition of aggregate solutions. These agents cause the nanoparticles to amass and form hot-spots which increase the signal intensity. In this work, the colloidal particles are spherical gold nanoparticles in aqueous solution with an average size of approximately 30 nm. The optimum aggregating agent for the detection of benzodiazepines was determined to be 16.7 mM MgCl2, providing the highest signal intensities at the lowest drug concentrations with limits of detection between 0.5 and 127 ng/mL. A supported liquid extraction technique was utilized as a rapid clean extraction for benzodiazepines from urine at a pH of 5.0, allowing for clean extraction with limits of detection between 6 and 640 ng/mL. It was shown that at this pH other drugs that are prevalent in urine samples can be removed providing the selective detection of the benzodiazepine of interest. This technique has been shown to provide rapid (less than twenty minutes), sensitive, and specific detection of benzodiazepines at low concentrations in urine. It provides the forensic community with a sensitive and specific screening technique for the detection of benzodiazepines in drug facilitated assault cases.

Development of Advanced Capillary Electrophoresis Techniques with UV and Mass Spectrometry Detection for Forensic, Pharmaceutical and Environmental Applications

Capillary electrophoresis (CE) is a modern analytical technique, which is electrokinetic separation generated by high voltage and taken place inside the small capillaries. In this dissertation, several advanced capillary electrophoresis methods are presented using different approaches of CE and UV and mass spectrometry are utilized as the detection methods. Capillary electrochromatography (CEC), as one of the CE modes, is a recent developed technique which is a hybrid of capillary electrophoresis and high performance liquid chromatography (HPLC). Capillary electrochromatography exhibits advantages of both techniques. In Chapter 2, monolithic capillary column are fabricated using in situ photoinitiation polymerization method. The column was then applied for the separation of six antidepressant compounds. Meanwhile, a simple chiral separation method is developed and presented in Chapter 3. Beta cycodextrin was utilized to achieve the goal of chiral separation. Not only twelve cathinone analytes were separated, but also isomers of several analytes were enantiomerically separated. To better understand the molecular information on the analytes, the TOF-MS system was coupled with the CE. A sheath liquid and a partial filling technique (PFT) were employed to reduce the contamination of MS ionization source. Accurate molecular information was obtained. It is necessary to propose, develop, and optimize new techniques that are suitable for trace-level analysis of samples in forensic, pharmaceutical, and environmental applications. Capillary electrophoresis (CE) was selected for this task, as it requires lower amounts of samples, it simplifies sample preparation, and it has the flexibility to perform separations of neutral and charged molecules as well as enantiomers. Overall, the study demonstrates the versatility of capillary electrophoresis methods in forensic, pharmaceutical, and environmental applications.

(Table T1) Pore water chemistry of ODP Site 195-1202 sediments, southern Okinawa Trough

Pore water was collected from sediment cores from Holes 1202A and 1202D in the southern Okinawa Trough during Ocean Drilling Program (ODP) Leg 195. Because drilling at this site was completed only a few hours out of port during the end of the leg, whole rounds of sediment core 5 or 10 cm long were sealed and stored at ~3°C until pore water could be extracted from them during Leg 196, using a titanium squeezer designed by Manheim and Sayles (1974) and standard handling techniques (Shipboard Scientific Party, 2002, doi:10.2973/odp.proc.ir.195.103.2002).

Cadmium analytical results from sediment and foraminifera shells

There has been a major contradiction between benthic foraminiferal Cd/Ca and d13C data concerning the labile nutrient chemistry of the Southern Ocean during the Last Glacial Maximum (LGM). Cd data indicates that LGM South Atlantic nutrient concentrations were as low as they are today, indicative of a persistent influx of nutrient-depleted North Atlantic Deep Water (NADW). d13C data indicates that LGM South Atlantic nutrient concentrations were much higher than at present (even higher than anywhere else in the ocean at that time), and these data have been interpreted as signifying the complete shutdown ofthe export of NADW into the global ocean. This paper examines both true geochemical differences and various confounding foraminiferal artifacts for both tracers. While many different processes and artifacts affect both tracers in the margin, we conclude the discrepancy is mainly due to the "Mackensen Effect" of low foraminiferal d13C as a result of high carbon flux to the sediments, and that LGM Atlantic Sector Southern Ocean nutrient concentrations remained similar to the levels encountered today.

Seawater carbonate chemistry, nutrients, and Calcidiscus leptoporus (strain RCC1135) growth rate and calcification rate during experiments, 2012

The coccolithophore Calcidiscus leptoporus was grown in batch culture under nitrogen (N) as well as phosphorus (P) limitation. Growth rate, particulate inorganic carbon (PIC), particulate organic carbon (POC), particulate organic nitrogen (PON), and particulate organic phosphorus (POP) production were determined and coccolith morphology was analysed. While PON production decreased by 70% under N-limitation and POP production decreased by 65% under P-limitation, growth rate decreased by 33% under N- as well as P-limitation. POC as well as PIC production (calcification rate) increased by 27% relative to the control under P-limitation, and did not change under N-limitation. Coccolith morphology did not change in response to either P or N limitation. While these findings, supported by a literature survey, suggest that coccolith morphogenesis is not hampered by either P or N limitation, calcification rate might be. The latter conclusion is in apparent contradiction to our data. We discuss the reasons for this inference.

Seawater carbonate chemistry and biological processes of Emiliania huxleyi (strains RCC1256 and NZEH) during experiments, 2011

With respect to their sensitivity to ocean acidification, calcifiers such as the coccolithophore Emiliania huxleyi have received special attention, as the process of calcification seems to be particularly sensitive to changes in the marine carbonate system. For E. huxleyi, apparently conflicting results regarding its sensitivity to ocean acidification have been published (Iglesias-Rodriguez et al., 2008a; Riebesell et al., 2000). As possible causes for discrepancies, intra-specific variability and different effects of CO2 manipulation methods, i.e. the manipulation of total alkalinity (TA) or total dissolved inorganic carbon (DIC), have been discussed. While Langer et al. (2009) demonstrate a high degree of intra-specific variability between strains of E. huxleyi, the question whether different CO2 manipulation methods influence the cellular responses has not been resolved yet. In this study, closed TA as well as open and closed DIC manipulation methods were compared with respect to E. huxleyi's CO2-dependence in growth rate, POC- and PIC-production. The differences in the carbonate chemistry between TA and DIC manipulations were shown not to cause any differences in response patterns, while the latter differed between open and closed DIC manipulation. The two strains investigated showed different sensitivities to acidification of seawater, RCC1256 being more negatively affected in growth rates and PIC production than NZEH.

Time series of seawater carbonate chemistry calculated throughout incubation periods of Boreogadus saida and Gadus morhua during exposure to different CO2 and temperature conditions

Oceans are experiencing increasing acidification in parallel to a distinct warming trend in consequence of ongoing climate change. Rising seawater temperatures are mediating a northward shift in distribution of Atlantic cod (Gadus morhua), into the habitat of polar cod (Boreogadus saida), that is associated with retreating cold water masses. This study investigates the competitive strength of the co-occurring gadoids under ocean acidification and warming (OAW) scenarios. Therefore, we incubated specimens of both species in individual tanks for 4 months, under different control and projected temperatures (polar cod: 0, 3, 6, 8 °C, Atlantic cod: 3, 8, 12, 16 °C) and PCO2 conditions (390 and 1170 µatm) and monitored growth, feed consumption and standard metabolic rate. Our results revealed distinct temperature effects on both species. While hypercapnia by itself had no effect, combined drivers caused nonsignificant trends. The feed conversion efficiency of normocapnic polar cod was highest at 0 °C, while optimum growth performance was attained at 6 °C; the long-term upper thermal tolerance limit was reached at 8 °C. OAW caused only slight impairments in growth performance. Under normocapnic conditions, Atlantic cod consumed progressively increasing amounts of feed than individuals under hypercapnia despite maintaining similar growth rates during warming. The low feed conversion efficiency at 3 °C may relate to the lower thermal limit of Atlantic cod. In conclusion, Atlantic cod displayed increased performance in the warming Arctic such that the competitive strength of polar cod is expected to decrease under future OAW conditions.

Chemical composition of ocean manganese nodules from the Pacific Ocean using different techniques

Mineralogical and chemical analyses performed on 67 ferromanganese nodules from widely varying locations and depths within the marine environment of the Pacific Ocean indicate that the minor element composition is controlled by the mineralogy and that the formation of the mineral phases is depth dependent. The pressure effect upon the thermodynamics or kinetics of mineral formation is suggested as the governing agent in the depth dependence of the mineralogy. The minor elements, Pb and Co, appear concentrated in the dMnO2 phase, whereas Cu and Ni are more or less excluded from this phase. In the manganites, Pb and Co are relatively low in concentration, whereas Cu and Ni are spread over a wide range of values. The oxidation of Pb and Co from divalent forms in sea water to higher states can explain their concentration in the dMnO2 phase.