Chlorine contribution to quantitative structure and activity relationship models of disinfection by -products' quantum chemical descriptors and toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Chlorine Contribution to Quantitative Structure and Activity Relationship Models of Disinfection By-Products' Quantum Chemical Descriptors and Toxicities

Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

Stable isotopes reveal complex changes in trophic relationships following nutrient addition in a coastal marine ecosystem

Complex links between the top-down and bottomup forces that structure communities can be disrupted by anthropogenic alterations of natural habitats.We used relative abundance and stable isotopes to examine changes in epifaunal food webs in seagrass (Thalassia testudinum) beds following 6 months of experimental nutrient addition at two sites in Florida Bay (USA) with different ambient fertility. At a eutrophic site, nutrient addition did not strongly affect food web structure, but at a nutrient-poor site, enrichment increased the abundances of crustacean epiphyte grazers, and the diets of these grazers became more varied. Benthic grazers did not change in abundance but shifted their diet away from green macroalgae + associated epiphytes and towards an opportunistic seagrass (Halodule wrightii) that occurred only in nutrient addition treatments. Benthic predators did not change in abundance, but their diets were more varied in enriched plots. Food chain length was short and unaffected by site or nutrient treatment, but increased food web complexity in enriched plots was suggested by increasingly mixed diets. Strong bottom-up modifications of food web structure in the nutrient-limited site and the limited top-down influences of grazers on seagrass epiphyte biomass suggest that, in this system, the bottom-up role of nutrient enrichment can have substantial impacts on community structure, trophic relationships, and, ultimately, the productivity values of the ecosystem.

Synthetic Approaches to Flexible Fluorescent Conjugated Polymers

Conjugated polymers (CPs) are intrinsically fluorescent materials that have been used for various biological applications including imaging, sensing, and delivery of biologically active substances. The synthetic control over flexibility and biodegradability of these materials aids the understanding of the structure-function relationships among the photophysical properties, the self-assembly behaviors of the corresponding conjugated polymer nanoparticles (CPNs), and the cellular behaviors of CPNs, such as toxicity, cellular uptake mechanisms, and sub-cellular localization patterns. Synthetic approaches towards two classes of flexible CPs with well-preserved fluorescent properties are described. The synthesis of flexible poly(p-phenylenebutadiynylene)s (PPBs) uses competing Sonogashira and Glaser coupling reactions and the differences in monomer reactivity to incorporate a small amount (~10%) of flexible, non-conjugated linkers into the backbone. The reaction conditions provide limited control over the proportion of flexible monomer incorporation. Improved synthetic control was achieved in a series of flexible poly(p-phenyleneethynylene)s (PPEs) using modified Sonogashira conditions. In addition to controlling the degree of flexibility, the linker provides disruption of backbone conjugation that offers control of the length of conjugated segments within the polymer chain. Therefore, such control also results in the modulation of the photophysical properties of the materials. CPNs fabricated from flexible PPBs are non-toxic to cells, and exhibit subcellular localization patterns clearly different from those observed with non-flexible PPE CPNs. The subcellular localization patterns of the flexible PPEs have not yet been determined, due to the toxicity of the materials, most likely related to the side-chain structure used in this series. The study of the effect of CP flexibility on self-assembly reorganization upon polyanion complexation is presented. Owing to its high rigidity and hydrophobicity, the PPB backbone undergoes reorganization more readily than PPE. The effects are enhanced in the presence of the flexible linker, which enables more efficient π-π stacking of the aromatic backbone segments. Flexibility has minimal effects on the self-assembly of PPEs. Understanding the role of flexibility on the biophysical behaviors of CPNs is key to the successful development of novel efficient fluorescent therapeutic delivery vehicles.

Synthetic approaches to flexible fluorescent conjugated polymers

Conjugated polymers (CPs) are intrinsically fluorescent materials that have been used for various biological applications including imaging, sensing, and delivery of biologically active substances. The synthetic control over flexibility and biodegradability of these materials aids the understanding of the structure-function relationships among the photophysical properties, the self-assembly behaviors of the corresponding conjugated polymer nanoparticles (CPNs), and the cellular behaviors of CPNs, such as toxicity, cellular uptake mechanisms, and sub-cellular localization patterns. ^ Synthetic approaches towards two classes of flexible CPs with well-preserved fluorescent properties are described. The synthesis of flexible poly( p-phenylenebutadiynylene)s (PPBs) uses competing Sonogashira and Glaser coupling reactions and the differences in monomer reactivity to incorporate a small amount (∼10%) of flexible, non-conjugated linkers into the backbone. The reaction conditions provide limited control over the proportion of flexible monomer incorporation. Improved synthetic control was achieved in a series of flexible poly(p-phenyleneethynylene)s (PPEs) using modified Sonogashira conditions. In addition to controlling the degree of flexibility, the linker provides disruption of backbone conjugation that offers control of the length of conjugated segments within the polymer chain. Therefore, such control also results in the modulation of the photophysical properties of the materials. ^ CPNs fabricated from flexible PPBs are non-toxic to cells, and exhibit subcellular localization patterns clearly different from those observed with non-flexible PPE CPNs. The subcellular localization patterns of the flexible PPEs have not yet been determined, due to the toxicity of the materials, most likely related to the side-chain structure used in this series. ^ The study of the effect of CP flexibility on self-assembly reorganization upon polyanion complexation is presented. Owing to its high rigidity and hydrophobicity, the PPB backbone undergoes reorganization more readily than PPE. The effects are enhanced in the presence of the flexible linker, which enables more efficient π-π stacking of the aromatic backbone segments. Flexibility has minimal effects on the self-assembly of PPEs. Understanding the role of flexibility on the biophysical behaviors of CPNs is key to the successful development of novel efficient fluorescent therapeutic delivery vehicles.^

Ecosystem structure, nutrient dynamics, and hydrologic relationships in tree islands of the southern Everglades, Florida, USA

Tree islands are an important structural component of many graminoid-dominated wetlands because they increase ecological complexity in the landscape. Tree island area has been drastically reduced with hydrologic modifications within the Everglades ecosystem, yet still little is known about the ecosystem ecology of Everglades tree islands. As part of an ongoing study to investigate the effects of hydrologic restoration on short hydroperiod marshes of the southern Everglades, we report an ecosystem characterization of seasonally flooded tree islands relative to locations described by variation in freshwater flow (i.e. locally enhanced freshwater flow by levee removal). We quantified: (1) forest structure, litterfall production, nutrient utilization, soil dynamics, and hydrologic properties of six tree islands and (2) soil and surface water physico-chemical properties of adjacent marshes. Tree islands efficiently utilized both phosphorus and nitrogen, but indices of nutrient-use efficiency indicated stronger P than N limitation. Tree islands were distinct in structure and biogeochemical properties from the surrounding marsh, maintaining higher organically bound P and N, but lower inorganic N. Annual variation resulting in increased hydroperiod and lower wet season water levels not only increased nitrogen use by tree species and decreased N:P values of the dominant plant species (Chrysobalanus icaco), but also increased soil pH and decreased soil temperature. When compared with other forested wetlands, these Everglades tree islands were among the most nutrient efficient, likely a function of nutrient immobilization in soils and the calcium carbonate bedrock. Tree islands of our study area are defined by: (1) unique biogeochemical properties when compared with adjacent short hydroperiod marshes and other forested wetlands and (2) an intricate relationship with marsh hydrology. As such, they may play an important and disproportionate role in nutrient and carbon cycling in Everglades wetlands. With the loss of tree islands that has occurred with the degradation of the Everglades system, these landscape processes may have been altered. With this baseline dataset, we have established a long-term ecosystem-scale experiment to follow the ecosystem trajectory of seasonally flooded tree islands in response to hydrologic restoration of the southern Everglades.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.