6 resultados para agro-industrial by-products

em Digital Commons at Florida International University


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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.

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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.

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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.

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Owing to an increased risk of aging population and a higher incidence of coronary artery disease (CAD), there is a need for more reliable and safer treatments. Numerous varieties of durable polymer-coated drug eluting stents (DES) are available in the market in order to mitigate in-stent restenosis. However, there are certain issues regarding their usage such as delayed arterial healing, thrombosis, inflammation, toxic corrosion by-products, mechanical stability and degradation. As a result, significant amount of research has to be devoted to the improvement of biodegradable polymer-coated implant materials in an effort to enhance their bioactive response. ^ In this investigation, magneto-electropolished (MEP) and a novel biodegradable polymer coated ternary Nitinol alloys, NiTiTa and NiTiCr were prepared to study their bio and hemocompatibility properties. The initial interaction of a biomaterial with its surroundings is dependent on its surface characteristics such as, composition, corrosion resistance, work of adhesion and morphology. In-vitro corrosion tests such as potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) studies were conducted to determine the coating stability and longevity. In-vitro hemocompatibility studies and HUVEC cell growth was performed to determine their thrombogenic and biocompatibility properties. Critical delamination load of the polymer coated Nitinol alloys was determined using Nano-scratch analysis. Sulforhodamine B (SRB) assays were performed to elucidate the effect of metal ions leached from Nitinol alloys on the viability of HUVEC cells. Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), contact angle meter and X-ray diffraction (XRD) were used to characterize the surface of the alloys. ^ MEP treated and polymer coated (PC) Nitinol alloys displayed a corrosion resistant polymer coating as compared to uncoated alloys. MEP and PC has resulted in reduced Ni and Cr ion leaching from NiTi5Cr and subsequently low cytotoxicity. Thrombogenicity tests revealed significantly less platelet adhesion and confluent endothelial cell growth on polymer coated and uncoated ternary MEP Nitinol alloys. Finally, this research addresses the bio and hemocompatibility of MEP + PC ternary Nitinol alloys that could be used to manufacture blood contacting devices such as stents and vascular implants which can lead to lower U.S. healthcare spending.^

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Owing to an increased risk of aging population and a higher incidence of coronary artery disease (CAD), there is a need for more reliable and safer treatments. Numerous varieties of durable polymer-coated drug eluting stents (DES) are available in the market in order to mitigate in-stent restenosis. However, there are certain issues regarding their usage such as delayed arterial healing, thrombosis, inflammation, toxic corrosion by-products, mechanical stability and degradation. As a result, significant amount of research has to be devoted to the improvement of biodegradable polymer-coated implant materials in an effort to enhance their bioactive response. In this investigation, magneto-electropolished (MEP) and a novel biodegradable polymer coated ternary Nitinol alloys, NiTiTa and NiTiCr were prepared to study their bio and hemocompatibility properties. The initial interaction of a biomaterial with its surroundings is dependent on its surface characteristics such as, composition, corrosion resistance, work of adhesion and morphology. In-vitro corrosion tests such as potentiodynamic polarization and electrochemical impedance spectroscopic (EIS) studies were conducted to determine the coating stability and longevity. In-vitro hemocompatibility studies and HUVEC cell growth was performed to determine their thrombogenic and biocompatibility properties. Critical delamination load of the polymer coated Nitinol alloys was determined using Nano-scratch analysis. Sulforhodamine B (SRB) assays were performed to elucidate the effect of metal ions leached from Nitinol alloys on the viability of HUVEC cells. Scanning Electron Microscopy (SEM), X-ray Photoelectron Spectroscopy (XPS), contact angle meter and X-ray diffraction (XRD) were used to characterize the surface of the alloys. MEP treated and polymer coated (PC) Nitinol alloys displayed a corrosion resistant polymer coating as compared to uncoated alloys. MEP and PC has resulted in reduced Ni and Cr ion leaching from NiTi5Cr and subsequently low cytotoxicity. Thrombogenicity tests revealed significantly less platelet adhesion and confluent endothelial cell growth on polymer coated and uncoated ternary MEP Nitinol alloys. Finally, this research addresses the bio and hemocompatibility of MEP + PC ternary Nitinol alloys that could be used to manufacture blood contacting devices such as stents and vascular implants which can lead to lower U.S. healthcare spending.

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This research was conducted to study the use of radiation in water treatment as an alternative to chlorination which has caused health concerns due to the formation of harmful disinfection by-products. Groundwater solutions from the Biscayne aquifer were radiated with Cobalt-60 gamma radiation and studied for changes in dissolved organic carbon (DOC), UV absorbance at 254 nm (UV254), fluorescence and trihalomethane formation potential (THMFP). Molecular fractionations were conducted by ultrafiltration. Effect of the combination of radiation/peroxide was studied for DOC and UV254. Radiation showed significant removal in DOC and THMFP. Similar results were seen in the fluorescence and UV absorbance experiments. Radiation/peroxide did not improve the DOC removal. Radiation of the groundwater samples broke the larger molecular weight fractions in to smaller fractions.