Doctor of Philosophy, The Ohio State University, 2025, Comparative Biomedical Sciences

Despite the high prevalence of feline chronic kidney disease (CKD), there are still aspects of disease onset, progression, and subtyping that we do not fully understand. Mass spectrometry-based proteomics is a technique with increasing applications in veterinary medicine that can offer disease insights into CKD in cats. The objective of this work is to advance biofluid selection and biomarker discovery techniques in feline medicine to identify pathophysiological insights into feline CKD. We demonstrate a mass spectrometry-based workflow where paired urine, plasma, and serum samples are processed in parallel, to evaluate biofluid interchangeability and protein overlap. This data is summarized in our reference dataset, “CATalog,” with the intent of assisting in biofluid selection for feline assay development. These results suggested that, when processed correctly, urine is a valuable representation of disease without requiring a blood draw. Therefore, we measured the urinary proteome of cats with and without CKD to evaluate the changes in pathophysiology between stages for disease characterization and biomarker discovery. We observed that the urinary proteome changes across different disease stages, and may be representative of disease severity. Hierarchical clustering revealed distinct protein groups associated with pathways related to different causes of CKD, and we were able to categorize proteins by how they trend across disease states using k-means clustering. This research advances our knowledge of this highly prevalent disease to eventually improve the detection, treatment, and prognosis of CKD in cats.

Doctor of Philosophy, The Ohio State University, 2025, Chemistry

Nuclear Magnetic Resonance (NMR) spectroscopy is an analytical technique used to study a wide range of molecules ranging from proteins to small molecules. A crucial aspect of protein NMR studies is the investigation of conformational dynamics because of the insights one can get about the biological activity of proteins. The motions found in biological processes occur on various timescales that only NMR is able to study with atomic resolution. Unfortunately, studying proteins in this matter is time-consuming because the NMR experiments one needs to run are pseudo-3D experiments that take a day to a week to complete. One method to minimize the time needed to acquire multidimensional NMR experiments is called “NMR by Ordered Acquisition using 1H-detection” or NOAH. NOAH aims to concatenate two or more different pulse sequences in order to share one single recovery delay time. The recovery delay is the period that one needs to wait for the magnetization to return to equilibrium on a timescale of seconds, while the timescale for most pulses and delays is of the order of µs to ms. Thus, concatenating two or more sequences leads to substantial time gains provided that there is no loss in sensitivity and assuming that the spectra do not change in any significant way. NMR is also used extensively in small molecule studies. For example, the field of metabolomics aims at identifying and quantifying metabolites in a complex biological system, such as serum, urine, cell extracts, or food. Several software programs exist to aid researchers to achieve this task. Previously, we have published web servers such as COLMAR (Complex Mixture Analysis by NMR) that attempt to automatically or semi-automatically identify metabolites by comparing their chemical shifts with database chemical shifts in 2D NMR experiments (COLMARm) and quantify them (COLMARq). Until now, however, we did not have a web server to do quantification of 1D spectra. Such a tool is useful as it can significantly spee (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2025, Physics

Chromatography approaches are ubiquitous in chemical separations, but their characterization, optimization, and scale-up rely on trial-and-error adjustments done at the ensemble level. Such empirical methods are costly in terms of energy, time, and money, while obscuring the molecular behavior that leads to the success or failure of a separation. In this work, we develop and apply experimental techniques to probe mass transport and adsorption kinetics of solid-liquid chromatography stationary-phase materials to inform separations design. Uniquely, we develop methods for 3D spatiotemporal analysis of commercial porous resins for chiral separations, as well as novel materials for rare earth element separations. We seek to deconvolve the contributions of transport and heterogeneous adsorption, while simultaneously informing and expanding kinetic models for predicting the performance and behavior of bulk-scale separations. We primarily rely on single-molecule fluorescence microscopy to probe nano-scale heterogeneities in adsorption and quantify the rare long-lasting adsorptions that complicate separations. Our in-situ imaging unveils the inaccessibility of the inner functionalized porous volume of industry-used resins, and then we show how to recover that access. By quantifying the effects that functionalization, solution environment and flow-through conditions have on nano-scale adsorptions, we demonstrate that experimentally informed single-molecule models can predict bulk-scale chromatographic separations. Through adsorption-desorption experiments, we further demonstrate and establish how first principles models can deconvolve the complex binding behavior of rare-earth-element binding proteins. We hope these studies inform the design and use of chromatography adsorbers and demonstrate how single-molecule methods and relatively simple models can provide a new avenue to characterize and direct separations design from the bottom-up.

Master of Science (MS), Wright State University, 2024, Chemistry

This study examines the complexation behavior of methylthymol blue (MTB) with strontium, particularly focusing on its application in addressing environmental concerns related to radiotoxic 90Sr. Using spectrophotometric techniques, the binding interactions were analyzed at pH = 7.50, 9.60, and 12.20. Results indicate that MTB forms a 1:1 complex with strontium at pH = 7.50, while at pH = 9.60 and 12.20 were assumed to influence complexation due to changes in ligand deprotonation and electrostatic interactions. Equilibrium constants (K1) = 22 (± 2) and molar absorptivities, ε1 = 6.3 x 10^3 (± 0.0008) L·mol⁻¹·cm⁻¹, and ε2 = 9.73 x (± 0.2)10^3 L·mol⁻¹·cm⁻¹ were determined using Beer's law, alpha fraction plots, and 1:1 Single K model fitting was done in Igor Pro 9 software. These findings highlight MTB's potential for environmental remediation of strontium in aqueous solution, with future research suggested to optimize MTB effectiveness as metal ion indicator.

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Arts and Sciences

Over the past 60 years, mass spectrometry (MS) has emerged as a premier analytical technique for fatty acid (FA) analysis due to its exceptional sensitivity and selectivity. Techniques combining chromatography with MS, such as liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), have significantly enhanced the accuracy and robustness of FA quantification. Among FA metabolites, polyunsaturated fatty acids (PUFAs), particularly arachidonic acid-derived eicosanoids, play crucial roles in inflammation and disease pathology. Dysregulated eicosanoids are implicated in various diseases, underscoring the need for precise quantification in biological samples. LC-MS is the preferred method for eicosanoid analysis due to their low concentrations in biological matrices. The first part of this dissertation presents the development and validation of an LC-MS/MS method for quantifying 11-dehydrothromboxane B2 (11-DHTXB2) in human urine, a stable metabolite of thromboxane A2. Elevated urinary 11-DHTXB2 levels serve as a robust prognostic biomarker for atherosclerosis progression, offering the potential for monitoring disease progression and evaluating the efficacy of anti-atherogenic therapies. Short-chain fatty acids (SCFAs), produced by bacterial fermentation of undigested dietary components, are vital gut health biomarkers. Alterations in SCFA concentrations reflect gut microbial imbalances and are linked to inflammatory bowel disease (IBD), which arises from genetic, environmental, and microbial factors leading to an aberrant immune response. IBD-associated gut dysbiosis involves a reduction in SCFA-producing bacteria such as Bacteroides, Firmicutes, and Lactobacillus, resulting in significantly altered SCFA levels. GC-MS, widely regarded as the gold standard for analyzing volatile and semi-volatile compounds, excels in SCFA analysis due to its superior separation capabilities. The second part of this dissertation explores the use (open full item for complete abstract)

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Arts and Sciences

Phenolic acids are microbial products of non-absorbed fibers that are fermented by bacteria using indigestible components that reach the gastrointestinal (GI) tract. It has been shown that phenolic acid compounds significantly impact the human body, particularly their microbial metabolism and their ability to influence several aspects of gut homeostasis. For this reason, more attention should be placed on investigating these metabolites. Multiple factors may influence the biosynthesis of phenolic acids, including age, medications, and several environmental factors, but the production of gut metabolites is primarily affected by diet. In this research we aim to enhance the knowledge on the synergistic relationship between gut microbes, diets, and the biosynthesis of phenolic acids. Chapter I summarizes our current understanding of phenolic acid in the GI tract, fermentative pathways, etiology, and beneficial impacts of phenolic acids. In chapter II we aim to construct an in vitro fermentation model to find efficient ways to increase the generation of phenolic acids in the gut using different combinations of probiotics, prebiotics, and other factors, including fats, sugars, and amino acids. Chapter III discusses the development and complete validation of a high-throughput, fast, and reliable liquid chromatography-mass spectrometry method to quantify phenolic acids (ferulic acid, caffeic acid, and gallic acid) in biological samples. In conclusion, there are many studies that support the benefits of prebiotics on our health, but further investigations are needed to understand the interactions between prebiotics and the gut microbiota as they alter the biosynthesis of phenolic acids, which may be vital in enhancing health benefits, including reduced levels of oxidative stress, reduction of inflammation, enhancement of gut microbiota composition, improvement of metabolic health, and contribution to the prevention of chronic diseases such as obesity, diabetes, cardiovascula (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Arts and Sciences: Chemistry

Neurochemicals play a significant role in our health and in devastating diseases. In the last several decades, since they were discovered, they have mainly been researched in the context of their effect on the nervous system. Recently, scientists have uncovered that many neurochemicals play significant roles in the immune system. There is a need to understand what cells release these neurochemicals, and the effect that these molecules have on the surrounding area. In this dissertation, we address these limitations by developing tools to study neuropeptide release in both the nervous and immune systems. Additionally, we worked to resolve neurochemical signaling capabilities in immune cells like CD4 + T cells. Chapter 1 provides a review on the important components of the nervous system and the immune system that are relevant to neurochemical signaling in the spleen and from immune cells. It broadly reviews the function of both DNA and adaptive immune systems along with the cells they use, and how the nervous system operates any important components for neuroimmune signaling in the spleen and with immune cells. Chapter 2 details our development of an electrochemical aptamer-based sensor for neuropeptide Y. This sensor is capable of making dynamic measurements of neuropeptide Y across a biologically relevant concentration range with high specificity. Chapter 3 gives an overview of the state of the field for fluorescent and electrochemical neuropeptide sensors. We highlight the advancements and the current limitations of each of these techniques, with a focus on how the field needs to advance electrochemical sensors to fill the current gaps in neuropeptide signaling. Chapter 4 details are extensive research into neurochemical signaling from CD4+ T cells. In this research, we have discovered that CD4+ T cells release a wide variety of neurochemicals, including serotonin and dopamine. We have also resolved the subsecond signaling of serotonin from the cells. The d (open full item for complete abstract)

PhD, University of Cincinnati, 2024, Arts and Sciences: Chemistry

Surface-enhanced Raman scattering (SERS) has emerged as a versatile tool for biological analysis due to its high sensitivity, high information content, and preparation-free analysis. Gold nanostars (NS) have proven to be particularly effective in SERS applications because of their tunable localized surface plasmon resonance (LSPR) and ease of synthesis. In this work, we explored the reshaping behavior of surfactant-free gold NS, investigating how changes in their morphology affect the LSPR and SERS signal. By monitoring the reshaping kinetics and correlating them with LSPR shifts, we developed a predictive model for optimal SERS substrate fabrication with only a 3% deviation in LSPR. Using SERS substrates, we explored the integration of SERS with an electrokinetic microchip to enhance liquid biopsy capabilities, particularly in cancer diagnostics. By combining this approach with machine learning (ML) and explainable AI methods, we successfully modeled the vibrational fingerprints of small extracellular vesicles (sEVs), providing interpretable predictions for cancer diagnostics. Additionally, we demonstrated SERS' ability to rapidly assess the molecular responses of Escherichia coli to antibacterial agents, differentiating between various mechanisms of action through multivariate analysis. Our study highlights SERS' potential as a robust, non-invasive tool for both diagnostic applications and antibacterial research, offering significant advantages over traditional methods such as genome sequencing and mass spectrometry. To expand this work, we explored surface modifications on plasmonic surfaces, resulting in improving SERS response for the target analyte.

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

Micrometer-size particles of the entropy-stabilized transition metal-based oxide (Mg0.2Co0.2Ni0.2Cu0.2Zn0.2)O (TM-HEO) have demonstrated long-term cycling stability and excellent rate performance against lithium-ion batteries. Such a feat has only been achieved with nanometer-size transition metal binary oxides. This electrochemical performance has been attributed to the structural stabilization effect of magnesium, the intrinsic role of cobalt as the main redox active species, and the entropy stabilization effect demonstrated in this material. Here, we demonstrate the formation of single-phase so-called “medium-entropy” oxides, (Co0.25Ni0.25Cu0.25Zn0.25)O (TM-MEO(–Mg)) and (Mg0.25Ni0.25Cu0.25Zn0.25)O (TM-MEO(–Co)), and show that their electrochemical behavior is similar to that of TM-HEO. The slight difference in capacities is attributed to the number of charges stored per formula unit of material rather than the nature of TM-HEO. The mechanism of lithium interaction with these materials is still poorly understood, partly due to the difficulties characterizing structure at the nanoscale. Operando 7Li nuclear magnetic resonance (NMR) and electrochemical techniques are used to demonstrate that the (de)lithiation of these compounds proceeds via a partially reversible conversion-type reaction mechanism involving the reduction of the transition metal cations to their metallic form during lithiation and the oxidation of these individual metal particles to their oxides form, losing the initial single-phase compound after the first lithiation cycle. This proposed lithiation/delithiation mechanism highly contradicts existing ones in the literature. In addition, the 7Li NMR and electrochemical methods reveal that the conductive carbon black used as an electronic conductor can store a significant amount of charge at low voltage, indicating that it is a major contributor to the additional capacity observed in these entropy-stabilized oxides and transition metal salts. Such (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), University of Dayton, 2024, Mechanical Engineering

Aviation turbine fuel is a complex mixture comprised of thousands of compounds. While organo-oxygen, nitrogen, and sulfur heteroatomic compounds are present in minute quantities (<0.1% by mass), their presence significantly influences fuel thermal stability. In response to the limitations of existing analytical methods, this study developed and validated a novel analytical approach employing hydrophilic interaction liquid chromatography (HILIC) in conjunction with high performance liquid chromatography (HPLC) with electrospray ionization and quadrupole time-of-flight mass spectrometry (ESI-QTOF). The HILIC method offers numerous advantages including rapid and straightforward sample preparation, without the need for extraction, thereby preserving compounds of interest. Moreover, it offers a way to capture precise compound data enabling chemometric analysis for the prediction of the behavior of the complex mixture that is aviation turbine fuel. Development of the HILIC method found column configuration, mobile phase composition, solvent gradient, re-equilibration time, injection volume, dilution factor, and sample solvent to be significant factors effecting separation efficiency and repeatability. For a sample dataset, optimized using a single aviation turbine fuel, retention time shift was able to be reduced from 0.4 minutes and 2.0% relative standard deviation (RSD) to approximately 0.1 minutes with RSD of 0.4% using the newly developed method. In addition, a high number of untargeted molecular features (944) and targeted amines (121) were able to be identified when using optimal method conditions. The optimized HILIC method was used to measure the heteroatom make up of a set of aviation turbine fuels; the subsequent data was then subjected to a rigorous statistical analysis using multiple techniques. Statistical analysis tools including principal component analysis (PCA) and fold change (FC) analysis offer a look inside the chemically complex composition of (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

Colon cancer is projected to become the third leading cause of death amongst Americans by 2024. Early onset colorectal cancer (CRC) is also increasing, with predictions showing CRC to be the leading cause of cancer mortality in people between the ages of 20 and 49 in the United States (US) by 2030. Increasing our understanding of this disease will allow quicker, less invasive, and more accurate diagnosis and treatment options. One such tool to deepen our chemical understanding of CRC is mass spectrometry. Mass spectrometry (MS) has allowed us to broadly survey the proteins (proteomics), lipids (lipidomics), and metabolites (metabolomics) within a biological sample. All of these -omics disciplines using MS are able to identify a peptide and/or small molecule by matching various tandem MS spectra to either previously collected or in silico generated library of tandem MS spectra. Statistical analysis of the normalized intensities of these molecules are compared to control samples to determine if a particular analyte is differentially expressed. A literature review of these topics is described in Chapter 1 of this thesis. Starting in Chapter 2, this thesis describes how MS-based omics has been used to deepen our understanding of the biology of a three-dimensional CRC cell culture model when exposed to various different chemotherapeutics. Chapters 2 and 3 describe the distinct molecular differences between two different CRC cell lines inhibited with two generations of Fatty Acid Synthase (FAS) inhibitors. FAS is the enzyme responsible for synthesizing the 16- chain saturated fatty acid (FA) palmitate, supplying the cellular FA pool with palmitate to be used to synthesize more complex lipids. FAS is also observed to be upregulated in various cancers, increasing the interest in drugging this target for therapy. It was observed that the first generation inhibitor caused drastic morphological changes to CRC spheroids. Using untargeted (open full item for complete abstract)

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Arts and Sciences

This dissertation explores the influence of mobile phase (MP) polarity on the separation of steroid enantiomer pairs in reversed-phase high-performance liquid chromatography. Previous studies varied the concentration of a single organic modifier in binary MPs, affecting both the MP strength and polarity. This work isolates the effect of MP polarity on separation alone by using a ternary MP. In this work, MP strength is kept constant by varying the percent water, while the MP polarity is changed by varying the ratio of the two organic modifiers. The combined ET(30) and Kamlet-Taft polarity model for MP polarity components of acidity, basicity, and dipolarity/polarizability was studied. The bile acid enantiomer pairs analyzed were alpha-muricholic acid and beta-muricholic acid, and omega-muricholic acid and gamma-muricholic acid. The separation factor (α) did not correlate with the total MP polarity, but did with a specific combined component polarity. The α versus the summed MP dipolarity/polarizability and basicity plot for all non-acetonitrile (ACN) ternary MPs experiments considered as a whole (six different organic pairs of methanol, isopropanol, dioxane, tetrahydrofuran in water), showed good correlation, except for the dioxane-containing MPs. Examination of previously obtained data of five other steroid enantiomer pairs (3β5β+3α5β-, 3β5α+3α5α-, 5α+5β-abiraterones, 17α- + 17β-estradiol, 11α- +11β-hydroxyprogesterone) showed good correlation with component polarity, excluding different aberrant organic modifier (isopropanol or methanol) MPs for several of these pairs. ACN-containing MPs demonstrated different separation characteristics, showing no correlation with non-ACN phases. The dissertation also reports the separation versus component polarity of non-enantiomer compounds (theophylline, caffeine), revealing that changing the polarity of the non-ACN-containing MPs did not result in a significant change in separation. Plots for the ACN-containing MPs wer (open full item for complete abstract)

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Arts and Sciences

Metabolomics is the study of small molecules (also termed as metabolites) in biological or botanical specimens using highly sophisticated analytical instruments, such as ultrahigh-performance liquid chromatography coupled with mass spectrometry (UHPLC-MS). The concept of computational chemistry is using software and algorithm-based analysis to pinpoint biomarkers by uncovering the molecular mechanisms that are helpful for treatment strategies. Integrating these two techniques (metabolomics and computational chemistry) enables a deeper understanding of the molecular mechanisms underlying diseases and therapeutic interventions, facilitating the identification of novel drug targets, biomarkers, and personalized treatment strategies. This integrative approach enhances our ability to unravel the complexity of biological networks and improve drug development and precision medicine. In the first half of the work, we developed a UHPLC-QTOF/MS-based untargeted metabolomics method to establish a biological model for allergic rhinitis by identifying, analyzing the regulation, and semiquantitative the key metabolites and exploring the impacted biological pathways. A computational chemistry approach was developed and applied to identify the potential therapeutic bioactive components of Astragalus radix, a traditional Chinese medicine, for allergic rhinitis treatment. In this, the protein targets were mined, and networks were constructed and analyzed to identify vital protein targets. Then, molecular docking simulations were conducted to identify the potential therapeutic components. Following this, the previously established metabolomics approach was used to investigate the therapeutic effects of the bioactive components on allergic rhinitis-induced human mast cells. In the second half of this work, we developed and validated a targeted metabolomic UHPLC-MS/MS analytical method for star anise samples. Building on our previous laboratory work, we quantified the three therapeuti (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

The development of commercially available single particle inductively coupled plasma time of flight mass spectrometers (spICP-TOFMS) has made it possible to measure the elemental compositions, mass equivalent diameters, and number concentrations (number of particles detected per volume of analyzed sample) of thousands of individual multi-element nanoparticles and microparticles using a small volume (<10 mL) of sample suspension in minutes. Effective particle analysis by spICP-TOFMS requires a deep understanding of the technical challenges and limitations of the technique. Solution-NP and NP# transport efficiency methods can vary up to a factor of two, resulting in a 20% difference in particle mass equivalent diameters and a factor of two difference in particle number concentrations. Particle transport efficiency depends on the uptake rate. Nanoparticles transport efficiency is ~30% and ~20% at 20 and 60 µL/minute, respectively. Particle transport efficiency decreases for particles larger than ~500 nm. Element- and sample-dependent quasi-continuous backgrounds limit the smallest particle mass equivalent diameter that can be determined in samples. Diluting a sample can reduce element thresholds by a factor of ~2. The smallest detectable amount of each element is sample and isotope dependent. The linear dynamic required to measure nanoparticles and fine microparticles is over seven orders of magnitude. Particles as large as 3170 nm are vaporized, atomized, and ionized in the ICP but produce signals outside the linear dynamic range the instrument using optimized sensitivity. Four ice core samples from the Alto Dell'Ortles glacier, Italy, from pre-Roman (780 BCE) to modern (1955 CE) times with a focus on lead (Pb)-bearing particles were measured by spICP-TOFMS. The number concentration and mass equivalent diameter distributions of all detected insoluble mineral particles were similar in the four samples. However, the number concentration and the mass fraction of Pb i (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

Detecting, quantifying, and identifying flowing samples is imperative to many applications including pharmaceutical development and manufacturing, diagnostics, forensics, and environmental studies. Surface enhanced Raman spectroscopy (SERS) is a nondestructive, water insensitive, and highly sensitive method that can be applied to these areas. Raman spectroscopy provides information regarding molecular bonds based on the inelastic scattering of light. SERS increases the efficacy of Raman spectroscopy by utilizing plasmonic metal nanostructures to enhance signals by up to 108. Utilizing SERS detection for flowing solutions allows for minimal sample preparation, short analysis time, and sample recovery after analysis. This dissertation focuses on applying SERS in flow to low concentration samples to detect single molecules and analytes that are traditionally difficult to detect and differentiate. Chapter 1 introduces Raman and SERS as analytical tools and describes how these methods can be used for flow through analysis of both single molecules and sugars. Past literature of SERS in flow experiments and single molecule experiments are discussed to support the work shown in later chapters. Additional information regarding sugars, glycosylation, and chemometrics is provided. Chapter 2 focuses on a method for single molecule detection and quantification in flow. By utilizing fast acquisition SERS, a planar silver substrate, and chemometric analysis, the linear dynamic range of this technique is able to be lowered into the stochastic, or “event counting” regime instead of the traditional ensemble or “intensity based” regime. This allows for the limit of detection of Nile Blue A to be lowered by 16 times, and single molecules to be detected and counted. Chapter 3 discusses a method for detecting and differentiating monosaccharides in both flowing and static environments using a simple benchtop conjugation reaction, SERS detection, and chemometric methods for ana (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

My dissertation research develops Raman spectroscopy-based sensors to measure aspects of human and plant health or disease states at the point of need, specifically in areas where current sensing methods are insufficient. The first main project area involves monitoring plant health, specifically soil ecology, in real time without harvesting the plant. Sensors are needed to non-invasively observe chemical changes expressed in plant leaves which result from nutrition conditions in the soil. These sensors would be especially useful to inform fertilization practices, increasing efficiency and sustainability. The second major project area focuses on developing a rapid and accurate diagnostic assay for COVID-19. The limitations of established testing methods, such as at-home antigen tests and polymerase chain reaction (PCR) assays, motivate the exploration of alternative techniques that do not sacrifice accuracy for speed. To tackle these sensing challenges, my research employs Raman spectroscopy, which uses light to probe the molecular composition of a sample. Each molecule has a unique Raman signature, and Raman signal is proportional to the concentration of molecules present in the sample, making the technique highly advantageous for identification and quantification. Raman signals can be collected quickly and non-destructively with minimal sample preparation. To detect low concentrations of analytes or poorly scattering analytes, we use surface enhanced Raman spectroscopy (SERS), a technique in which metal nanostructures amplify the Raman signals of the molecules near the nanostructures. Overall, this dissertation work focuses on optimizing portable Raman and SERS methods to non-invasively assess plant health and to detect COVID, all in a matter of seconds. Chapter 1 introduces the background and motivation for these projects, as well as the analytical techniques used to address them. Chapter 2 describes the development of handheld Raman techniques to monitor th (open full item for complete abstract)

Doctor of Philosophy in Clinical-Bioanalytical Chemistry, Cleveland State University, 2024, College of Arts and Sciences

Barth Syndrome is a rare life-threatening X-linked recessive disease caused by a mutation in the TAZ gene, which codes for the protein taffazin. A mutation in the taffazin gene causes an inborn error in phospholipid metabolism that affects multiple physiological systems. This disease is characterized by cardiomyopathy, skeletal muscle weakness, neutropenia, growth retardation, 3-methylglutaconic (3-MGC), low plasma arginine, muscle hypoplasia, and weakness/exercise intolerance. TAZ mutations lead to mitochondrial dysfunction leading to reduced energy production and increased reactive oxygen species. There is no correlation between a specific mutation and the severity of symptoms. This leads to the need for personalized medicine. Currently, there is no FDAapproved treatment for Barth syndrome. We proposed an isogenic Barth Syndrome model utilizing human-induced pluripotent stem cells (iPSCs) with or without the TAZ mutation. We also implored the use of patient-derived fibroblasts, with or without the Barth Syndrome mutation. We have investigated TAZ metabolism via stable isotope tracing, targeted colorimetric assay, and untargeted metabolomics. These investigations revealed the possibility of anaplerotic supplementation as well as the phenotypic variability of the TAZ mutation. The research presented here offers new insights into iPSC and fibroblast models that express key characteristics of Barth syndrome and resemble the human phenotype. Various therapeutic treatments were used demonstrating variability in TAZ mutation response and demonstrating that XJB-5-131 and Triheptanoin may be promising therapeutic treatments.

Master of Science (MS), Wright State University, 2024, Chemistry

Previously, mineral nucleation was described by Classical Nucleation Theory (CNT), a theory based on the thermodynamic properties of bulk materials. However, an alternative model, known as the Prenucleation Cluster Pathway, has been increasingly used to describe nucleation of minerals. This model considers the presence of thermodynamically stable ion clusters known as “prenucleation clusters” (PNCs). In the present research, the nucleation mechanism of calcium fluoride was investigated to identify evidence of PNCs by means of the ion-selective electrode (ISE) method, where a CaCl2 solution was titrated into a NaF solution while investigating the effects of saturation level and the aqueous ratio of [Ca2+] to [F-]. It was concluded that the nucleation of fluorite is better supported by the Prenucleation Cluster Pathway rather than CNT. However further analysis of the accuracy of ion-pair formation constants is necessary in order to confirm.

Doctor of Philosophy, The Ohio State University, 2024, Chemistry

Mass spectrometry-based techniques are powerful analytical tools for observing and characterizing the structure of proteins at various levels, ranging from primary to quaternary structures. The advancement of mass spectrometry instrumentation and methods has enabled researchers to not only measure an analyte's mass-to-charge (m/z) ratio but also to probe gas-phase dissociation behaviors and conformations of peptides, proteins, and protein complexes. These advancements have greatly expanded the capabilities of researchers in the field. In the past few decades, native mass spectrometry (nMS) has become a popular technique for probing the intact structures of proteins and protein complexes. Using tandem mass spectrometry, specifically surface-induced dissociation (SID), to fragment precursor ions of interest helps in understanding protein complex connectivity, stoichiometry, and gas-phase structural rearrangement. However, most of the mass spectrometers currently on the market are not designed for nMS, and the SID is also not commercially available for most of them. By collaborating with industrial partners, we adapted a commercial trapped ion mobility spectrometry time-of-flight mass spectrometer (TIMS-Q-TOF), timsTOF Pro, for nMS with a TIMS convex cartridge device, which has a low radio frequency (RF) driver to trap high m/z ions. A low RF quadrupole driver is also designed for this instrument to extend the isolation m/z range for high m/z ions. To design and add a SID device to this instrument for SID capability, it is crucial to understand the fundamentals of SID, especially the surface material of the SID surface (Chapter 2). Based on the outcomes, we designed a 2-lens version SID device with a stainless-steel surface for this prototype instrument iii (Chapter 3). This simplified 2-lens SID device streamlines the operation and allows for SID parameters to be saved with the instrument tune file. With these advantages, we coupled a high-performance liquid chrom (open full item for complete abstract)

Master of Science (M.S.), University of Dayton, 2024, Chemistry

Linear polyenes are a class of compounds containing two or more alternating carbon-carbon double and single bonds that have a range of applications from antioxidants in nature to non-linear optical switches. More recently, other related π conjugated systems (like cinnamaldehyde) with heteroatoms within the π-conjugation are being used as chemical additives in fracturing fluids (or “fracking”) in our continued exploration of crude oil. Though this class of chemicals is considered non-hazardous, they are susceptible to oxidative additions initiated with a free radical oxidant. Because of their relative insolubility in water and high solubility in non-polar solvents, the protonation of conjugated polyenes represents a potential pathway to create novel cyclic conjugated structures in one step or hazardous products in the environment. I will present a systematic approach to analyzing the numerous products from the reaction of linear polyenes with trifluoroacetic acid under Airfree conditions to compare to the relative product distributions. The data generated in this project also provides insight into the relative stability of carbocation intermediates that are potentially created. Based on the structure of the products, we will propose mechanisms for the resulting reactions based on multivariate spectroscopic data sets. Some of the spectroscopic techniques include 1D and 2D NMR, UV-vis spectroscopy, fluorescence spectroscopy, and Mass Spectroscopy. The products that were isolated thus far indicate that inter- and intramolecular cyclization are occurring after the protonation of the polyene occurs.