Graduation date: 1995

No description available.

Contaminants introduced in solution to coastal waters eventually accumulate in sediment. Pollution by these contaminants is only evident when biological effects occur. Geochemical procedures lack the ability to identify biological effects of pollution. Biological methods (i.e. community structure analyses and/or bioassays) are currently the best available techniques for pollution assessment. Standardised and locally relevant protocols for pollution assessment are lacking in many developing countries, including South Africa. This study aims to develop a sediment toxicity testing protocol using an amphipod species endemic to South Africa, Grandidierella lignorum. Initial research focussed on establishing ranges of physico-chemical parameters (i.e. salinity, temperature, sediment grain size and organic matter content) within which sediment toxicity tests should be performed. The sensitivity of the amphipod was then determined by exposing the amphipod to cadmium, copper and zinc at various salinities. Lastly, the amphipod was exposed to effluents (to test the amphipod’s sensitivity in water only tests) and whole sediment (to tests the amphipod’s sensitivity to solid phase material). G. lignorum tolerates salinities between 0 and 56, but prefers salinities between 7 and 42. Preferred salinity range is modified by temperature, with salinity of 42 becoming less tolerable. Salinities between 7 and 35 are most preferred at 10-25°C. G. lignorum prefers fine- (27.48±12.13%), medium- (25.11±12.99%) and coarse-grained sand (21.45±8.02%). Sediment with low (≤2%) organic matter content is most preferable, regardless of sediment grain size or type of organic matter (protein-rich vs. carbohydrate-rich). Cadmium toxicity decreased with increasing salinity (LC₅₀: 0.34 ± 0.17 mg l⁻¹ (salinity of 7), 0.73 ± 0.05 mg l⁻¹ (salinity of 21) and 1.08 ± 0.49 mg l⁻¹ (salinity of 35)). Zinc toxicity increased with decreasing salinity (1.56 ± 0.33 mg l⁻¹ at a salinity of 21 to 0.99 ± 0.13 mg l⁻¹ at a salinity of 7) and with increasing salinity (from salinity of 21 to 0.82 ± 0.19 mg l⁻¹ at a salinity of 35). Copper toxicity did not differ significantly with salinity and ranged between 0.72 ± 0.18 mg l⁻¹ (salinity of 35) and 0.89 ± 0.24 mg l⁻¹ (salinity of 21). Toxicity testing using Grandidierella lignorum should be performed in coarse- to fine-grained sediment at salinities of 7 - 35, at 10 – 25°C. Amphipods do not need to be fed during toxicity testing. A control chart using cadmium as a reference toxicant was established to determine the acceptability of toxicity results. Toxicity test results should be accepted when cadmium toxicity falls between 0.49 and 4.02 mg l⁻¹. The amphipod responded consistently to effluents and was able to discriminate polluted and unpolluted sediment in Durban Bay. Recommendations for refining the effluent and sediment toxicity test are suggested. / Ph.D. University of KwaZulu-Natal, Durban 2013.

Preclinical testing is an important part of cancer drug development. The aim of this thesis was to establish and evaluate preclinical in vitro methods useful in the development of new anticancer drugs. In paper I, the development of non-clonogenic assays (FMCA-GM) using CD34+ stem cells for assessment of haematological toxicity was described. A high correlation was seen when comparing the 50% inhibitory concentrations (IC50) from FMCA-GM with the IC50 from the established clonogenic assay (CFU-GM). In paper II, FMCA-GM was complemented with additional cell models, establishing a normal cell panel. In vitro toxicity towards the five normal cell types was compared with known clinical adverse event profiles. The normal cell panel roughly reflected the tissue specific toxicities but was most useful in the prediction of therapeutic index. In paper III the use of peripheral blood lymphocytes from human, dog, rat and mouse to detect species differences in cellular drug sensitivity was described. Good agreement between our method and the established CFU-GM assay was observed. In paper II the benefit of using primary tumour cells from patients to predict cancer diagnosis-specific activity was studied. The in vitro activity of fourteen anticancer drugs was tested in tumour samples of both haematological and solid tumour origin. In general, clinical activity was well reflected. In paper IV, the efficacy and toxicity models were applied for experimental follow-up of a novel inhibitor of the ubiquitin-proteasome system, CB3 (Phosphoric acid, 2,3-dihydro-1,1-dioxido-3-thienyl diphenyl ester). In the preliminary characterization of CB3, antitumour activity and a favourable toxicity profile were displayed, although the exact mechanism of action remains to be elucidated. CB3 will therefore be further investigated. In conclusion, the work presented here contributes to different parts of the preclinical drug development and the methods may aid in the characterization of anticancer compounds

No description available.

Abstract available in file 07summary.pdf / Thesis (PhD (Microbiology))--University of Pretoria, 2007. / Microbiology and Plant Pathology / unrestricted

In vitro models are often used both to characterize and test therapeutics for neurodevelopmental disorders (‘NDDs’). While in vitro models have extraordinary potential to develop therapies for patients, they have historically been confounded by absence of robust phenotypes and/or in vitro phenotypes that fail to translate from laboratory bench to bedside. Within this thesis work, we attempt to address three areas in which in vitro models may be improved – gene selection, model validation and identification of disease-relevant functional assays suited for therapeutic testing. Publicly available databases aggregating identified and annotated disease-causing variants for Mendelian diseases have rapidly expanded over the past two decades. Elucidating mechanisms of disease and developing therapies using in vivo model systems often is both time and cost intensive. Thus, determining which subsets of genes are more likely to generate addressable signals in a dish may lead to more effective drug development. In chapter 1, we identify a set of genes ideally suited for therapeutic inhibition. Specifically, we leverage the aforementioned large genetic databases to identify a set of genes likely to act through a gain-of-function mechanism that are both tolerant to loss-of-function mutations and in the druggable genome. In chapter 2, we aim to characterize the degree of conservation of transcriptomic dysregulation between a human in vitro cortical organoid (‘hCOs’) model, and two mouse models of a severe neurodevelopmental disorder resulting from HNRNPU deficiency. Human model systems may improve upon animal models when human pathogenesis and patient phenotypes are divergent from animal models due to species-specific etiology. However, human model systems often lack the heterogeneity and cell-type specificity and maturity seen in primary fetal samples. Importantly, some mouse models of HNRNPU deficiency have muted phenotypes compared with human patients. We hypothesized that while there are distinctions between humans and mice with HNRNPU deficiency, there will be overlap in transcriptomic dysregulation between human and mouse models. In fact, we find 45-day-old HNRNPU+/- hCOs have consistent transcriptomic dysregulation to embryonic mouse models, but not to perinatal mice. Our findings suggest hCOs are a viable model for characterizing HNRNPU deficiency; however, such models may only be appropriate for elucidating a transcriptomic disease state at a specific developmental time period. Functional assays for neurodevelopmental disorders can aid in understanding whether transcriptomic dysregulation is relevant to patient symptoms, as genomic findings may not always correlate to disease-relevant phenotypes. Further, relevant functional phenotypes can then be utilized for testing potential therapeutics. Importantly, seizures are commonly present in a significant subset of neurodevelopmental disorders and seizure phenotypes have been described as driven by aberrant synchrony in neuronal networks. Using a multielectrode array platform, investigators can use a variety of computational methods to quantify aspects of synchrony in vitro. In chapter 3a, we introduce topological approaches capable of identifying novel synchrony phenotypes in primary neuronal networks from mouse models of neurodevelopmental disorders. Certain mouse models will be confounded by species-specific pathogenesis and/or vastly different developmental timelines and fail to generalize to human patients, motivating the need for functionally active and physiologically relevant human in vitro models. In chapter 3b, we attempt to generate human networks with balanced levels of excitation and inhibition and find confounding lack of functional maturation of inhibitory neuronal subtypes in 90-day-old stem cell-derived neuronal networks. Future work generating in vitro human neuronal networks with functionally mature inhibitory neurons would complement the findings in chapters 1 and 2 and allow for more efficient therapeutic development strategies that may lead to improved patient outcomes.

The problem of high proportion of zeroes has long been an interest in data analysis and modeling, however, there are no unique solutions to this problem. The solution to the individual problem really depends on its particular situation and the design of the experiment. For example, different biological, chemical, or physical processes may follow different distributions and behave differently. Different mechanisms may generate the zeroes and require different modeling approaches. So it would be quite impossible and inflexible to come up with a unique or a general solution. In this dissertation, I focus on cases where zeroes are produced by mechanisms that create distinct sub-populations of zeroes. The dissertation is motivated from problems of chronic toxicity testing which has a data set that contains a high proportion of zeroes. The analysis of chronic test data is complicated because there are two different sources of zeroes: mortality and non-reproduction in the data. So researchers have to separate zeroes from mortality and fecundity. The use of mixture model approach which combines the two mechanisms to model the data here is appropriate because it can incorporate the mortality kind of extra zeroes. A zero inflated Poisson (ZIP) model is used for modeling the fecundity in <i> Ceriodaphnia dubia</i> toxicity test. A generalized estimating equation (GEE) based ZIP model is developed to handle longitudinal data with zeroes due to mortality. A joint estimate of inhibition concentration (ICx) is also developed as potency estimation based on the mixture model approach. It is found that the ZIP model would perform better than the regular Poisson model if the mortality is high. This kind of toxicity testing also involves longitudinal data where the same subject is measured for a period of seven days. The GEE model allows the flexibility to incorporate the extra zeroes and a correlation structure among the repeated measures. The problem of zero-heavy data also exists in environmental studies in which the growth or reproduction rates of multi-species are measured. This gives rise to multivariate data. Since the inter-relationships between different species are imbedded in the correlation structure, the study of the information in the correlation of the variables, which is often accessed through principal component analysis, is one of the major interests in multi-variate data. In the case where mortality influences the variables of interests, but mortality is not the subject of interests, the use of the mixture approach can be applied to recover the information of the correlation structure. In order to investigate the effect of zeroes on multi-variate data, simulation studies on principal component analysis are performed. A method that recovers the information of the correlation structure is also presented. / Ph. D.

The compound p-(2-hydroxyethylsulfone) aniline was isolated from a reduced solution of a fiber-reactive azo dye. The identity and purity of this product was assessed through elemental composition analysis, high performance liquid chromatography (HPLC), gas chromatography/mass spectroscopy (GC/MS), and nuclear magnetic resonance spectroscopy (NMR). The toxicity of this purified compound was measured with Microtox and Daphnia pulex tests. Microtox tests were also performed on compounds with similar structures to p- (2-hydroxyethylsulfone) aniline. Wastewater samples containing textile dye wastes from a Publicly Owned Treatment Works (POTW) that treated textile dye wastes were monitored for the presence of p-(2-hydroxyethylsulfone) aniline using HPLC. Microtox testing was performed on these samples. Analytical tests confirmed the identity and purity of p-(2-hydroxyethylsulfone) aniline as the reduced product. Microtox tests revealed the concentration at which 50% of the light output was reduced (EC₅₀) after 5 minutes of exposure was 12.8 mg/L. Daphnia pulex testing yielded the concentration which was lethal to 50% of the tested organisms (LC₅₀) to be 113 mg/L. The 5-minute Microtox EC₅₀, values of aniline, sulfanilamide, 2-hydroxyethylsulfone, and 4-ethylaniline were 106.7, 8.15, >80, and 2.05 mg/L, respectively. The reduction product, p-(2-hydroxyethylsulfone)aniline, was not detected in textile-containing wastewater from the Martinsville POTW. The Microtox EC₅₀, for this wastewater, ranged from 6.05 to >75 mg/L. / Master of Science

by Chan Yu Keung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 133-141). / Abstract also in Chinese. / Acknowledgments --- p.i / Abstract --- p.ii / Table of Content --- p.iv / List of Figures --- p.ix / List of Tables --- p.xiv / Chapter 1. --- INTRODUCTION --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Textiles Industry in Hong Kong --- p.1 / Chapter 1.3 --- Processes Involved in Textiles Industry --- p.2 / Chapter 1.3.1 --- Typical Stages in Bleaching and Dyeing Step --- p.3 / Chapter 1.4 --- Characterization of Textile Wastewater --- p.6 / Chapter 1.4.1 --- Desizing --- p.6 / Chapter 1.4.2 --- Scouring --- p.6 / Chapter 1.4.3 --- Bleaching --- p.7 / Chapter 1.4.4 --- Mercerizing --- p.7 / Chapter 1.4.5 --- Dyeing and Printing --- p.7 / Chapter 1.4.6 --- Finishing --- p.8 / Chapter 1.5 --- Toxicity of Pollutants from Textiles Industry --- p.8 / Chapter 1.6 --- Related Environmental Legislation in Hong Kong --- p.9 / Chapter 1.6.1 --- Water Pollution Control Ordinance --- p.9 / Chapter 1.6.2 --- Waste Disposal Ordinance --- p.10 / Chapter 1.6.3 --- General Sewage Charge --- p.10 / Chapter 1.6.4 --- Trade Effluent Surcharge --- p.10 / Chapter 1.7 --- Chemical Specific Approach --- p.11 / Chapter 1.8 --- Toxicity Based Approach --- p.12 / Chapter 1.8.1 --- Selection of Organisms for Bioassays --- p.13 / Chapter 1.9 --- Whole-Effluent Toxicity (WET) Test --- p.14 / Chapter 1.10 --- Toxicity Identification Evaluation --- p.14 / Chapter 1.10.1 --- Phase I ´ؤ Toxicant Characterization --- p.15 / Chapter 1.10.2 --- Phase II - Toxicant Identification --- p.16 / Chapter 1.10.3 --- Phase III - Toxicant Confirmation --- p.16 / Chapter 1.11 --- Ecotoxicology --- p.16 / Chapter 2. --- OBJECTIVES --- p.18 / Chapter 3. --- MATERIALS AND METHODS --- p.19 / Chapter 3.1 --- Sources of Samples --- p.19 / Chapter 3.2 --- Whole Effluent Toxicity Test --- p.19 / Chapter 3.2.1 --- Microtox® test --- p.19 / Chapter 3.2.2 --- Growth inhibition test of a marine unicellular microalga Chlorella pyrenoidosa CU-2 --- p.22 / Chapter 3.2.3 --- Survival test of a marine amphipod Parhyale plumulosa --- p.25 / Chapter 3.2.4 --- Survival test of a marine fish Mylio macrocephalus --- p.29 / Chapter 3.3 --- Toxicity Identification Evaluation - Phase I --- p.33 / Chapter 3.3.1 --- pH adjustment filtration --- p.33 / Chapter 3.3.2 --- pH adjustment aeration --- p.35 / Chapter 3.3.3 --- Anion exchange --- p.37 / Chapter 3.3.4 --- Cation exchange --- p.38 / Chapter 3.3.5 --- pH adjustment C18 solid phase extraction (C18 SPE) --- p.40 / Chapter 3.3.6 --- Activated carbon extraction --- p.41 / Chapter 3.4 --- Toxicity Identification Evaluation - Phase II --- p.43 / Chapter 3.4.1 --- Determination of total organic carbon (TOC) --- p.43 / Chapter 3.4.2 --- Determination of metals --- p.46 / Chapter 3.4.3 --- Determination of anions --- p.48 / Chapter 4. --- RESULTS --- p.51 / Chapter 4.1 --- Sample Description --- p.51 / Chapter 4.2 --- Whole Effluent Toxicity Tests --- p.51 / Chapter 4.2.1 --- Toxicity of whole effluent samples on algal growth inhibition test using Chlorella pyrenoidosa CU-2 --- p.51 / Chapter 4.2.2 --- Toxicity of whole effluent samples on Microtox® test --- p.65 / Chapter 4.2.3 --- Toxicity of whole effluent samples on survival test of amphipod Parhyale plumulosa --- p.55 / Chapter 4.2.4 --- Toxicity of whole effluent samples on survival test of Mylio macrocephalus --- p.71 / Chapter 4.3 --- Toxicity Identification Evaluation - Phase I --- p.71 / Chapter 4.3.1 --- Effect of filtration at pH 3 on toxicity reduction --- p.71 / Chapter 4.3.2 --- Effect of filtration at pH 7 on toxicity reduction --- p.74 / Chapter 4.3.3 --- Effect of filtration at pHi on toxicity reduction --- p.74 / Chapter 4.3.4 --- Effect of aeration at pH 3 on toxicity reduction --- p.80 / Chapter 4.3.5 --- Effect of aeration at pH 7 on toxicity reduction --- p.80 / Chapter 4.3.6 --- Effect of aeration at pHi on toxicity reduction --- p.85 / Chapter 4.3.7 --- Effect of anion exchange on toxicity reduction --- p.85 / Chapter 4.3.8 --- Effect of cation exchange on toxicity reduction --- p.90 / Chapter 4.3.9 --- Effect of C18 extraction at pH3 on toxicity reduction --- p.90 / Chapter 4.3.10 --- Effect of C18 extraction at pH 7 on toxicity reduction --- p.95 / Chapter 4.3.11 --- Effect of C18 extraction at pH 9 on toxicity reduction --- p.95 / Chapter 4.3.12 --- Effect of activated carbon extraction on toxicity reduction --- p.101 / Chapter 4.4 --- Toxicity Identification Evaluation ´ؤ Phase II --- p.101 / Chapter 4.4.1 --- Effect of anion exchange on chemical reduction --- p.101 / Chapter 4.4.2 --- Effect of cation exchange on chemical reduction --- p.107 / Chapter 4.4.3 --- Effect of C18 extraction at pH 3 on chemical reduction --- p.107 / Chapter 4.4.4 --- Effect of C18 extraction at pH 7 on chemical reduction --- p.110 / Chapter 4.4.5 --- Effect of C18 extraction at pH 9 on chemical reduction --- p.110 / Chapter 4.4.6 --- Effect of activated carbon extraction on chemical reduction --- p.110 / Chapter 5. --- DISCUSSION --- p.114 / Chapter 5.1 --- Whole Effluent Toxicity Test --- p.114 / Chapter 5.1.1 --- Toxicity of whole effluent samples on algal growth inhibition test of Chlorella pyrenoidosa CU-2 --- p.114 / Chapter 5.1.2 --- Toxicity of whole effluent samples on Microtox® test --- p.116 / Chapter 5.1.3 --- Toxicity of whole effluent samples on survival test of amphipod Parhyale plumulosa --- p.117 / Chapter 5.1.4 --- Toxicity of whole effluent samples on survival test of fish Mylio macrocephalus --- p.118 / Chapter 5.1.5 --- Correlations among toxicity tests --- p.118 / Chapter 5.1.6 --- Factor analysis on whole effluent toxicity tests --- p.121 / Chapter 5.2 --- Toxicity Identification Evaluation ´ؤ Phase I --- p.122 / Chapter 5.2.1 --- pH adjustment filtration test --- p.124 / Chapter 5.2.2 --- pH adjustment aeration test --- p.124 / Chapter 5.2.3 --- Anion exchange test --- p.124 / Chapter 5.2.4 --- Cation exchange test --- p.125 / Chapter 5.2.5 --- pH adjustment C18 solid phase extraction test --- p.125 / Chapter 5.2.6 --- Activated carbon extraction test --- p.126 / Chapter 5.3 --- Toxicity Identification Evaluation Phase II --- p.126 / Chapter 5.3.1 --- Effect of anion exchange on chemical reduction --- p.126 / Chapter 5.3.2 --- Effect of cation exchange on chemical reduction --- p.127 / Chapter 5.3.3 --- Effect of C18 solid phase extraction on chemical reduction --- p.127 / Chapter 5.3.4 --- Effect of activated carbon extraction on chemical reduction --- p.127 / Chapter 5.4 --- Correlation between toxicity reduction and chemical reduction --- p.128 / Chapter 5.4.1 --- Anion exchange --- p.128 / Chapter 5.4.2 --- Cation exchange --- p.129 / Chapter 5.4.3 --- C18 solid phase extraction --- p.129 / Chapter 5.4.4 --- Activated carbon extraction --- p.130 / Chapter 6. --- CONCLUSIONS --- p.131 / Chapter 7. --- REFERENCE --- p.133