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Tandem Mass Spectrometric Analysis of Ammonium and Sodium Oligoperoxide Adducts with the Application of Two-Dimensional Correlation Spectroscopy and Computational Chemistry
Title
Tandem Mass Spectrometric Analysis of Ammonium and Sodium Oligoperoxide Adducts with the Application of Two-Dimensional Correlation Spectroscopy and Computational Chemistry.
Creator
Frisch, Jessica, Sigman, Michael, Fookes, Barry, Hampton, Michael, University of Central Florida
Abstract / Description
Oligoperoxides, H[OO(CH3)2C]nOOH, are formed as side products in the synthesis of the primary high explosive triacetone triperoxide (TATP). Previous tandem mass spectrometry (MSn) experiments using a quadrupole ion trap reported that the open-chained oligoperoxide adducts of ammonium or sodium resulted in different product ions in the mass spectra. Dissociation mechanisms were previously proposed based on MSn experiments, where n(>)2; however, a dissociation pathway achieved by an MSn...
Show moreOligoperoxides, H[OO(CH3)2C]nOOH, are formed as side products in the synthesis of the primary high explosive triacetone triperoxide (TATP). Previous tandem mass spectrometry (MSn) experiments using a quadrupole ion trap reported that the open-chained oligoperoxide adducts of ammonium or sodium resulted in different product ions in the mass spectra. Dissociation mechanisms were previously proposed based on MSn experiments, where n(>)2; however, a dissociation pathway achieved by an MSn experiment, where n(>)2, may not necessarily be the same pathway achieved in an MS2 experiment. For this dissertation research, the collision induced dissociation pathways were investigated for the open-chained oligoperoxides in MS2 experiments utilizing a quadrupole ion trap. Tandem mass spectral experiments were performed for the open-chained oligoperoxides ranging from the trimer to the octamer (n=3-8), including both ammonium and sodium adducts. The dissociation pathways were proposed as a result of two-dimensional correlation spectroscopy applied to the mass spectral data, which was referred to as two-dimensional correlation mass spectrometry (2D-CMS). The 2D-CMS method was first validated by analysis of simple and more complex kinetic models followed by simple and more complex molecules. To further aid in the elucidation of the dissociation mechanisms, computational chemistry was performed for the optimization of stable precursor and product ion structures and calculations of their relative energies and adduct dissociation energies.
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Date Issued
2012
Identifier
CFE0004377, ucf:49371
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004377
Immuno-PCR detection of Lyme borreliosis
Title
Immuno-PCR detection of Lyme borreliosis.
Creator
Halpern, Micah, Ballantyne, John, Cunningham, Glenn, Fookes, Barry, University of Central Florida
Abstract / Description
Lyme borreliosis, more commonly referred to as Lyme disease, is the fastest growing zoonotic disease in North America with approximately 30,000 confirmed cases and 300,000 estimated infections per year. In nature, the causative agent of Lyme disease, the bacterium Borrelia burgdorferi, cycles between Ixodes sp. ticks and small mammals. Humans become infected with Lyme disease after being bitten by an infected tick. The primary indicator of a Borrelia burgdorferi infection is a bull's eye rash...
Show moreLyme borreliosis, more commonly referred to as Lyme disease, is the fastest growing zoonotic disease in North America with approximately 30,000 confirmed cases and 300,000 estimated infections per year. In nature, the causative agent of Lyme disease, the bacterium Borrelia burgdorferi, cycles between Ixodes sp. ticks and small mammals. Humans become infected with Lyme disease after being bitten by an infected tick. The primary indicator of a Borrelia burgdorferi infection is a bull's eye rash typically followed by flu-like symptoms with treatment consisting of a 2-4 week course of antibiotics. If not treated, later stages of the disease can result in arthritis, cardiovascular and neurological symptoms. Diagnosis of Lyme disease is challenging and currently requires a complex laboratory diagnostic using indirect detection of host-generated antibodies by a two-tiered approach consisting of an enzyme linked immunosorbent assay (ELISA) followed by IgM and IgG immunoblots. Although two-tier testing has provided an adequate approach for Lyme disease diagnosis, it has weaknesses including subjective analysis, complex protocols and lack of reagent standardization. Immuno-PCR (iPCR) is a method that combines ELISA-based detection specificity with the sensitivity of PCR signal amplification and has demonstrated increased sensitivity for many applications such as detection of disease biomarkers but has yet to be applied for diagnosis of Lyme disease.Herein, using iPCR and recombinant B. burgdorferi antigens, an assay for both the direct and the indirect detection of Lyme disease was developed and demonstrated improved sensitivity for detection of B. burgdorferi antibodies using a murine model. Moreover, we present evidence using human Lyme disease patient serum samples that iPCR using both multiple antigens and a unique single hybrid antigen is capable of achieving increased sensitivity and specificity compared to existing methodology. These data represent the first demonstration of iPCR for Lyme disease diagnosis and support the replacement of two-tier testing with a more simplified and objective approach.
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Date Issued
2013
Identifier
CFE0005346, ucf:50470
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005346
Chemical Analysis, Databasing, and Statistical Analysis of Smokeless Powders for Forensic Application
Title
Chemical Analysis, Databasing, and Statistical Analysis of Smokeless Powders for Forensic Application.
Creator
Dennis, Dana-Marie, Sigman, Michael, Campiglia, Andres, Yestrebsky, Cherie, Fookes, Barry, Ni, Liqiang, University of Central Florida
Abstract / Description
Smokeless powders are a set of energetic materials, known as low explosives, which are typically utilized for reloading ammunition. There are three types which differ in their primary energetic materials; where single base powders contain nitrocellulose as their primary energetic material, double and triple base powders contain nitroglycerin in addition to nitrocellulose, and triple base powders also contain nitroguanidine. Additional organic compounds, while not proprietary to specific...
Show moreSmokeless powders are a set of energetic materials, known as low explosives, which are typically utilized for reloading ammunition. There are three types which differ in their primary energetic materials; where single base powders contain nitrocellulose as their primary energetic material, double and triple base powders contain nitroglycerin in addition to nitrocellulose, and triple base powders also contain nitroguanidine. Additional organic compounds, while not proprietary to specific manufacturers, are added to the powders in varied ratios during the manufacturing process to optimize the ballistic performance of the powders. The additional compounds function as stabilizers, plasticizers, flash suppressants, deterrents, and opacifiers. Of the three smokeless powder types, single and double base powders are commercially available, and have been heavily utilized in the manufacture of improvised explosive devices.Forensic smokeless powder samples are currently analyzed using multiple analytical techniques. Combined microscopic, macroscopic, and instrumental techniques are used to evaluate the sample, and the information obtained is used to generate a list of potential distributors. Gas chromatography (-) mass spectrometry (GC-MS) is arguably the most useful of the instrumental techniques since it distinguishes single and double base powders, and provides additional information about the relative ratios of all the analytes present in the sample. However, forensic smokeless powder samples are still limited to being classified as either single or double base powders, based on the absence or presence of nitroglycerin, respectively. In this work, the goal was to develop statistically valid classes, beyond the single and double base designations, based on multiple organic compounds which are commonly encountered in commercial smokeless powders. Several chemometric techniques were applied to smokeless powder GC-MS data for determination of the classes, and for assignment of test samples to these novel classes. The total ion spectrum (TIS), which is calculated from the GC-MS data for each sample, is obtained by summing the intensities for each mass-to-charge (m/z) ratio across the entire chromatographic profile. A TIS matrix comprising data for 726 smokeless powder samples was subject to agglomerative hierarchical cluster (AHC) analysis, and six distinct classes were identified. Within each class, a single m/z ratio had the highest intensity for the majority of samples, though the m/z ratio was not always unique to the specific class. Based on these observations, a new classification method known as the Intense Ion Rule (IIR) was developed and used for the assignment of test samples to the AHC designated classes.Discriminant models were developed for assignment of test samples to the AHC designated classes using k-Nearest Neighbors (kNN) and linear and quadratic discriminant analyses (LDA and QDA, respectively). Each of the models were optimized using leave-one-out (LOO) and leave-group-out (LGO) cross-validation, and the performance of the models was evaluated by calculating correct classification rates for assignment of the cross-validation (CV) samples to the AHC designated classes. The optimized models were utilized to assign test samples to the AHC designated classes. Overall, the QDA LGO model achieved the highest correct classification rates for assignment of both the CV samples and the test samples to the AHC designated classes.In forensic application, the goal of an explosives analyst is to ascertain the manufacturer of a smokeless powder sample. In addition, knowledge about the probability of a forensic sample being produced by a specific manufacturer could potentially decrease the time invested by an analyst during investigation by providing a shorter list of potential manufacturers. In this work, Bayes' Theorem and Bayesian Networks were investigated as an additional tool to be utilized in forensic casework. Bayesian Networks were generated and used to calculate posterior probabilities of a test sample belonging to specific manufacturers. The networks were designed to include manufacturer controlled powder characteristics such as shape, color, and dimension; as well as, the relative intensities of the class associated ions determined from cluster analysis. Samples were predicted to belong to a manufacturer based on the highest posterior probability. Overall percent correct rates were determined by calculating the percentage of correct predictions; that is, where the known and predicted manufacturer were the same. The initial overall percent correct rate was 66%. The dimensions of the smokeless powders were added to the network as average diameter and average length nodes. Addition of average diameter and length resulted in an overall prediction rate of 70%.
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Date Issued
2015
Identifier
CFE0005784, ucf:50059
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005784