Inflammation is implicated in diseases such as hypertension and rheumatoid arthritis (RA). A mechanistic understanding of inflammatory processes as it relates to the disease state and injury needs to be developed. Specifically, the role and modulation of inflammation needs to be assessed, as well as the mechanism that produces arachidonic acid (AA) metabolites (eicosanoids). Eicosanoids are specific biomarkers of inflammation. Their biosynthesis from arachidonic acid can be catalyzed by either free radicals or enzymes such as lipoxygenases (LOX), cyclooxygenase-2 (COX-2) and cytochrome P450. Depending on the pathway or parent molecule, different distributions of eicosanoids are found. The oxidation of AA gives hydroxyeicosatetraenoic acids (HETEs), dihydroxyeicosatetraenoic acids (DHETEs), epoxyeicosatetraenoic acids (EETs), prostaglandins (PGs), isoprostanes (Isops) and thromboxanes (TXs). It is our hypothesis that AA metabolites will help in understanding the progression of inflammatory diseases. To confirm this hypothesis, analytical methods including HPLC-UV and LC-MS were developed. The developed and validated HPLC method was applied to study the effect of acute exercise on prostanoids in hypertensive African American subjects. It was our theory that urinary 6-keto PGF1&alpha and 11-dehydro TXB2 can be used to assess the role of exercise in hypertension. Moreover, we assume that 8-iso PGF2 levels can be used as an indicator to determine the relationship of oxidative stress and endothelial dysfunction in hypertension. The HPLC method involved separating urinary 8-iso PGF2, PGE2, PGD2, PGF2, 6-keto PGF1&alpha and 11-dehydro TXB2 on a SymmetryShield Rp18 column (250mm ¡Á 4.6mm) by an isocratic elution of 17 mM phosphoric acid and acetonitrile in the ratio of 65:35 and at a flow rate of 1.3 ml/min. The wavelength used for detection was 196 nm. Specificity was confirmed by LC-MS. The method was fully validated and was found to be having sufficient sensitivity (limit of quantification - 7.5 ng - 30 ng) for many biological matrices and applications. The accuracy and precision were within bioanalytical method validation limits (90.3 to 112.8 % and RSD < 10%, respectively) and the method was linear over three orders of magnitude. In addition, a HPLC-UV method for the simultaneous determination of urinary creatinine and prostanoids was also developed and validated as it is necessary to monitor creatinine levels in addition to biomarkers when the measurement is done in urine. The method was found to be linear over three orders of magnitude and is sensitive enough for the analysis of creatinine and prostanoids in urine. The advantage of this method was that one can determine the levels of these prostanoids normalized by urinary creatinine in a single analysis and in less than 17 min. The LC- ESI (electrospray ionization) MS method, on the other hand was used to determine the role of HETEs in the initiation, progression and resolution phases of inflammation in RA. It is our assumption that 12/15 HETE can be used as novel targets for the treatment of RA. The separation was performed on a C18 column using a gradient elution of 0.1% formic acid in water and 0.1% formic acid in acetonitrile. The flow rate was 1 ml/min and the run time was 75 mins. The method was found to be specific, sensitive and precise. This LCMS method was also used to develop a retention model for complex regioisomers. Quantitative structure- (chromatographic) retention relationship (QSRR) was used to develop a predictive retention model for fatty acid metabolites. Retention behaviors of the lipid biomarkers were characterized by application of QSRR analysis utilizing Austin Model 1 mode semi-empirical computations. The retention data of these fatty acids were obtained from an RP-HPLC method utilizing a Symmetry C18 column under gradient elution. Molecular descriptors that take into account the polarity; chemical reactivity and hydrophobicity of the analytes were calculated using the semi-empirical AM1 mode. It is our hypothesis that QSRR will give insight into molecular mechanism of separation of lipid biomarkers operating in a given chromatographic system and can predict retention of a new analyte and/or to identify unknown analytes. / Chemistry
| Identifer | oai:union.ndltd.org:TEMPLE/oai:scholarshare.temple.edu:20.500.12613/3994 |
| Date | January 2012 |
| Creators | Varma, Deepti |
| Contributors | Varnum, Susan A., Stanley, Robert J., Zdilla, Michael J., 1978-, Brown, Michael D. |
| Publisher | Temple University. Libraries |
| Source Sets | Temple University |
| Language | English |
| Detected Language | English |
| Type | Thesis/Dissertation, Text |
| Format | 279 pages |
| Rights | IN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available., http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | http://dx.doi.org/10.34944/dspace/3976, Theses and Dissertations |
Page generated in 0.0016 seconds