In vivo proton magnetic resonance spectroscopy (1H MRS) is the only method available to measure small-molecule metabolites in living human tissue, including the brain, without ionizing radiation or invasive medical procedures. Despite its attendant potential for supporting clinical diagnostics in a range of neurological and psychiatric conditions, the metabolite concentration estimates produced by 1H-MRS experiments, and therefore their sensitivity and specificity to any particular biological phenomenon under study, are readily distorted by a number of confounds. These include but are not limited to static and radiofrequency field characteristics, signal relaxation dynamics, macromolecule and lipid contributions to the spectral baseline, spectral fitting artifacts, and other uncontrolled idiosyncrasies of 1H-MRS data acquisition, processing, and quantification. Using 1H-MRS data obtained via 3-Tesla and 7-Tesla magnetic resonance (MR) scanners from healthy controls, individuals with progressive and relapsing-remitting multiple sclerosis (MS), and individuals with post-traumatic stress disorder (PTSD) and/or major depressive disorder (MDD), this work therefore aims to build and apply a framework for quantifying and thereby reducing such confounds introduced to 1H-MRS estimates of in vivo metabolite concentrations at the steps of data processing and quantification, with an ultimate aim to maximizing the potential of 1H MRS for supporting sensitive and specific clinical diagnosis of neurological or psychiatric disease. The steps examined include spectral quantification by linear combination modeling (Chapter 2), absolute quantification by internal concentration referencing (Chapter 3), and cross-sectional statistical analysis of results (Chapters 4 and 5). Chapter 2 designs and implements a graphical user interface (GUI)-supported validation pipeline for measuring how data quality, spectral baseline, and baseline model affect the precision and accuracy of 1H-MR spectral quantification by linear combination modeling. This validation pipeline is then used to show that spectral data quality indices signal to noise ratio (SNR) and full width at half maximum (FWHM) interact with spectral baseline to influence not only the precision but also the accuracy of resultant metabolite concentration estimates, with fit residuals poorly indicative of true fit error and spectral baselines modeled as regularized cubic splines not significantly outperformed by those employing simulated macromolecules. A novel method for extending the commonly used spectral quantification precision estimate Cramér-Rao Lower Bound (CRLB) to incorporate considerations of continuous and piecewise polynomial baseline shapes is therefore presented, tested, and similarly integrated into a GUI-supported toolkit to improve the correspondence between estimated CRLB and metabolite fit error variability when this now empirically justified approach to spectral baseline modeling is used. In Chapter 3, age- and disease-associated differences in transverse (T2) water signal relaxation measured at 7 Tesla in the prefrontal cortex of individuals with progressive (N=21) relative to relapsing-remitting (N=26) or no (N=25) multiple sclerosis are shown to influence absolute quantification of metabolite concentrations by internal referencing to water. In Chapter 4, these findings from Chapters 2 and 3 are used to justify an evidence-based 1H-MR spectral processing and quantification protocol that focuses optimization efforts on baseline modeling approach and references metabolite concentration estimates to internal creatine instead of water. When this protocol is applied to 7-Tesla prefrontal cortex 1H-MR spectra from the aforementioned multiple sclerosis and control cohorts, it supports metabolite concentration estimates that, in the absence of any additional supporting data, inform supervised-learning-enabled identification of progressive multiple sclerosis at nearly 80% held-out validation sensitivity and specificity. Finally, in Chapter 5, the same processing, quantification, and machine-learning pipeline employed in Aim 3 is independently applied to a new set of 7-Tesla prefrontal cortex 1H-MRS raw data from an entirely different cohort of individuals with (N=20) and without (N=18) PTSD and/or comorbid or primary MDD. Here the processing, quantification, and statistics procedures designed using lessons in Chapters 2 and 3 and optimized for classifying multiple sclerosis phenotype in Chapter 4 generalize directly to metabolite-only classification of PTSD and/or MDD with sensitivity and specificity similarly near to or greater than 80%. In both Chapters 4 and 5, supervised learning avoids dimensionally reducing metabolite feature sets in order to pinpoint the specific metabolites most informative for identifying each disease group. Taken together, these findings justify the potential and continued development of 1H MRS, at least as applied in the human brain and especially as supported by multivariate approaches including supervised learning, as an auxiliary or mainstay of clinical diagnostics for neurological or psychiatric disease.

TCTP est une petite protéine globulaire (20~kDa) qui interagit avec de nombreux partenaires et qui est impliquée dans diverses fonctions cellulaires et physiologiques, avec un rôle bien documenté dans la réversion tumorale qui est un phénomène rare et spontané où une cellule cancereuse perd tout ou partie de son phénotype malin et retrouve des caractéristiques associées aux cellules bénignes telles que la sensibilité à l'apoptose. Dans les cellules cancéreuses, TCTP inhibe la dégradation de MDM2, diminuant ainsi les niveaux de p53 et favorisant le maintien et la progression du cancer. TCTP contient également un motif BH3-like connu pour réguler les membres de la famille Bcl-2 et elle interagit directement avec Bcl-xL et Mcl-1 pour renforcer leurs propriétés anti-apoptotiques. Dans la structure TCTP, le motif BH3-like n'est pas facilement accessible pour une interaction avec un partenaire. Conformément à son importance dans le maintien de la tumeur, TCTP est une cible pharmacologique validée dans le traitement du cancer et fait l’objet d’essais cliniques en cours avec une molécule d'abord connue comme anti-depresseur, la sertraline. Cependant, on en sait peu sur la structure de TCTP en complexe avec ses partenaires, ce qui entrave le développement de médicaments et ne permet pas de comprendre comment TCTP peut s'adapter à une telle variété de partenaires. Ainsi, nous avons étudié le mécanisme moléculaire par lequel TCTP s'associe à des protéines et à des ligands en utilisant diverses méthodes biophysiques (RMN, SAXS, CD, SEC, DSF...). Nous avons démontré que la protéine TCTP se lie à Bcl-xL et à Mcl-1 dans le sillon de liaison des motifs BH3. Dans les complexes, la région BH3-like est engagée dans l'interface intermoléculaire et la structure centrale de TCTP est déstabilisée dans un état de globule fondu (molten-globule). Nous avons en outre montré que seule une forme mineure pré-existante de TCTP, à savoir TCTP*, est compétente pour les interactions avec les partenaires Bcl-xL et Mcl-1. Dans TCTP*, la région BH3-like est détachée du domaine structuré et elle est accessible aux protéines Bcl-xL/Mcl-1 tandis qu'on retrouve un état globule fondu dans la partie globulaire de TCTP*. Nous avons également collecté des données d'interaction préliminaires entre TCTP et la sertraline, des ARN, la protéine YB-1 se liant à l'ARN et le domaine N-terminal de MDM2. Enfin, nous avons caractérisé TCTP phosphorylé (pTCTP) au résidu S46 en utilisant la Plk-1 car cette modification a un impact sur les interactions et est un marqueur de l'aggressivité tumorale. En résumé, ces travaux ont établi la versatilité de TCTP en terme de structure et ont montré que cette versatilité est indispensable pour exercer ses fonctions cellulaires. En conséquence, ceci devrait être pris en compte dans les stratégies de développement de nouvelles molécules thérapeutiques ciblant TCTP. / TCTP is a small (20~kDa) globular protein that interacts with many partners with consequences in various cellular and physiological functions, with well-documented roles in tumoral reversion program. Cells that undergo such program spontaneously loose their malignant phenotype and recover characteristics associated with benign cells, such as apoptosis. In cancer cells, TCTP inhibits MDM2 degradation, thus decreasing p53 levels and favoring tumor maintenance and progression. TCTP also contains a BH3-like motif known to regulate Bcl-2 family members and TCTP directly interacts with Bcl-xL and Mcl-1 to reinforce their pro-survival properties. In TCTP structure, the BH3-like motif is not readily accessible for interaction. Consistently with its importance in tumor maintenance, TCTP is a validated pharmacological target in cancer treatment with ongoing clinical trials using the TCTP-targeting antidepressant drug sertraline. However, little is known about TCTP structure in complex with partners, thus impeding the development of drugs and the understanding of how TCTP could adapt to its myriad of partners. Thus, we investigated the molecular mechanism by which TCTP associates with proteins and ligands using various biophysical methods (NMR, SAXS, CD, SEC, DSF...). We have demonstrated that full length TCTP binds to Bcl-xL and Mcl-1 in their BH3-binding groove. In the complexes, the TCTP BH3-like region is engaged in the intermolecular interface and the core TCTP structure is destabilized into a molten-globule (MG) state. We further showed that only a minor pre-existing form of TCTP, namely TCTP*, is competent for interactions with the Bcl-2 protein partners. In TCTP*, the BH3-like region is unpinned and accessible to Bcl-xL/Mcl-1 proteins and the core structure is also in MG state. We also collected preliminary interaction data between TCTP and sertraline, RNA, the RNA binding YB-1 protein and the MDM2 N-terminal domain. Finally, we characterized the Plk-1-mediated S46 phosphorylated TCTP (pTCTP), a marker of tumor aggressivity and its interaction properties. Overall, this work established the structural versatility of TCTP that is mandatory to exert its cellular functions and this versatility should be taken into account in drug-design strategies targeting TCTP.

Indiana University-Purdue University Indianapolis (IUPUI) / Omega-3 polyunsaturated fatty acids (n-3 PUFAs) relieve the symptoms of a wide variety of chronic inflammatory disorders. Typically, they must be obtained in the diet from sources such as fish oils. Docosahexaenoic acid (DHA) is one of these n-3 PUFAs. As yet the structural mechanism responsible for the health benefits within the body is not completely understood. One model that has emerged from biochemical and imaging studies of cells suggests that n-3 PUFAs are taken up into phospholipids in the plasma membrane. Thus the focus here is on the plasma membrane as a site of potential structural modification by DHA. Within cellular membranes, the huge variety of molecules (called lipids) which constitute the membrane suggest inhomogeneous mixing, thus domain formation. One potential domain of interest is called the lipid raft, which is primarily composed of sphingomyelin (SM) and cholesterol (chol). Here the molecular organization of [2H31]-N-palmitoylsphingomyelin (PSM-d31) mixed with 1-palmitoyl-2-docosahexaenoylphosphatylcholine (PDPC) or 1-palmitoyl-2-oleoylphosphatidylcholine (POPC), as a monounsaturated control, and cholesterol (chol) (1:1:1 mol) in a model membrane was examined by solid state 2H NMR spectroscopy. Solid state 2H NMR spectroscopy extracts details of molecular orientation and anisotropy of molecular reorientation by analysis of the lineshape. This essentially non-invasive technique allows for a direct measurement of dynamics in bulk materials which has been extensively applied to biological materials. It is a niche area of NMR for which standard software often lack necessary features. Two software programs, “EchoNMR processor” and “EchoNMR simulator”, collectively known as “EchoNMR tools”, that were developed to quickly process and analyze one-dimensional solid-state NMR data, will be described along with some theoretical background of the techniques used. EchoNMR tools has been designed with a focus on usability and the open-source mindset. This is achieved in the in the MATLAB® programming environment which allows for the development of the graphical user interfaces and runs as an interpreter which allows the code to be open-source. The research described here on model membranes demonstrates the utility of the software. The NMR spectra for PSM-d31 in mixtures with PDPC or POPC with cholesterol were interpreted in terms of the presence of nano-sized SM-rich/chol-rich (raft-like) and PC-rich/chol-poor (non-raft) domains that become larger when POPC was replaced by PDPC. An increase in the differential in order and/or thickness between the two types of domains is responsible. The observation of separate signals from PSM-d31, and correspondingly from [3α-2H1]cholesterol (chol-d1) and 1-[2H31]palmitoyl-2-docosahexaenoylphosphatidylcholine (PDPC-d31), attributed to the raft-like and non-raft domains enabled the determination of the composition of the domains. Most of the SM (84%) and cholesterol (88%) was found in the raft-like domain. There was also a substantial amount of PDPC (70%) in the raft-like domain that appears to have minimal effect on the order of SM. PDPC molecules sequestering into small groups to minimize the contact of DHA chains with cholesterol is one possible explanation that would also have implications on raft continuity. These results refine the understanding of how DHA may modulate the structure of raft domains in membranes.

Mixes with lower water to cement (w/c) ratio and supplementary cementing materials produce strong and durable concrete. The consequence of lowering w/c is an increase in autogenous shrinkage (AS), which contributes to concrete cracking. Internal curing (IC) is shown to mitigate AS, however improper dosing of IC material can negatively affect the concrete properties. The effectiveness of IC material, such as superabsorbent polymer (SAP), depends on the 1) amount of water stored, 2) particle distribution, and 3) ability to deliver water. The objective of this research is to quantify the in-situ efficiency of SAP by investigating its effect on the cement chemical reaction using non-destructive testing methods, specifically isothermal calorimetry and nuclear magnetic resonance (NMR). IC was tested with varying quantities of SAP in plain cement paste using white Portland cement and three w/c (0.30, 0.32, 0.35). Overdosing of the SAP material was found to significantly affect the hydration reaction and reduce the efficiency of the material. The initial porosity of the paste influences the ability of IC to provide water. However, the extra porosity provided by SAP needs to be considered when calculating the degree of hydration. Particle agglomeration occurs when the mass of SAP to IC water is greater than 5% and is the main factor causing loss of efficiency. A new geometric model was developed to estimate the SAP distribution within the cement paste. The model employs the SAP absorption determined by NMR and assumes that the SAP particles are spherical, of equal diameter, and individual particles absorb the same amount of pore solution. The results reveal that particle spacing increases with agglomeration and reduces the IC efficiency. A hybrid 1-D finite element transient flow model was developed to reverse engineer the effective diffusion coefficient from the NMR water distribution. The gel solid volume fraction and its impedance to water transfer were accounted for through the cement degree of hydration and tortuosity factor, respectively. Model results reveal that the effective water diffusion coefficient depends on w/c, gel volume fraction, and tortuosity once the cement gel fractions start to connect, i.e., after 20% cement degree of hydration. The diffusion length quantifies the distance water can transfer from the SAP to the cement paste. / Thesis / Doctor of Philosophy (PhD)

Electrostatic interactions such as halogen bonding and pnictogen bonding interactions have gained a lot of interest in the field of crystal engineering and pharmaceutical science. In the first part of this thesis, we expand our knowledge on anion coordinated halogen bonded cocrystals by looking at a series of cocrystals made from 3-iodoethynyl pyridine and 3-iodoethynylbenzoic acid. We utilize the power of mechanochemistry to create the new cocrystals made with phosphonium salts and use multinuclear solid-state nuclear magnetic resonance spectroscopy and X-ray diffraction and characterize them. We found that mechanochemistry is a fast and powerful tool to explore and synthesize new halogen bonded cocrystals and ³¹P solid-state NMR is a rapid way to identify the formation of a cocrystal. In the second part, we look at the versatility of the pnictogen atom, specifically antimony, as a pnictogen bond donor and a halogen bond acceptor. We evaluate these electrostatic interactions with nuclear quadrupolar resonance and found that nuclear quadrupole resonance is a strong spectroscopy tool to probe these types of electrostatic interactions.

Due to the successful commercialization of lithium-ion batteries (LIBs), there is a growing interest in developing new battery materials with beneficial electrochemical properties. However, the uneven distribution of lithium resources and the low abundance of lithium in the earth crust are the main obstacles for further development and large-scale production of LIBs. Sodium-ion batteries (SIBs), an alternative that can partly meet the energy storage challenges, are getting attentions of researchers due to the wide availability and lower cost of sodium resources. Nevertheless, the conventional liquid electrolytes of either LIBs or SIBs composed of fluorinated salts dissolved in volatile organic solvents, posing serious safety issues due to the instability of the salts and flammability of the solvents. There is an urge to develop new fluorine-free electrolytes with improved physicochemical and electrochemical properties. In this context, the conventional fluorinated salts should be replaced with fluorine-free salts and the flammable solvents should be substituted with non-flammable solvents. There are a number of strategies to develop high-performant electrolytes including ambient-temperature ionic liquids (ILs), organic ionic plastic crystals (OIPCs) and highly concentrated electrolytes (HCEs) utilizing new salts and solvents. In this thesis, novel phosphorus-based ionic materials and electrolytes are introduced and their properties are thoroughly investigated. In the first part (Paper I), fluorine-free NaDEEP salt and TEOP solvent are employed to make “solvent-in-salt” (SIS) sodium electrolytes, also known as HCEs. Unexpectedly, the addition of TEOP solvent lead to an increase in the oxidation stability of the SIS electrolytes. In addition, an unusual ionic conductivity behavior is found – the ionic conductivities of Na electrolytes increase with increasing salt concentration. The “salt-rich” and “solvent-rich” phases formed within the electrolytes are investigated using multinuclear liquid-state NMR spectroscopy and NMR diffusometry. In the second part (Paper II), a series of orthoborate-based ionic materials, specifically OIPCs, containing phosphonium/ammonium cations are prepared to compare with the popular fluorine-free, bis(oxalato)borate (BOB) salts. The tetrabutyl phosphonium bis(glycolato)borate ([P4444][BGB]) OIPC displays much higher decomposition temperature than the structural analogous [P4444][BOB] IL. The crystal structures of LiBGB and NaBGB salts are resolved using single-crystal X-ray diffraction analysis. Unlike LiBOB, the BGB-based salts revealed excellent moisture stability over an extended time of up to 8-weeks air exposure. Multinuclear solid-state NMR spectroscopy indicates weaker cation-anion interactions in phosphonium-based salts than the ammonium-based ones. Finally, in the third part (Paper III), two-component and three-component eutectic electrolytes, composed of pyrrolidinium saccharin (PySc), lithium saccharin (LiSc) and/or [P4444][BGB] salt. The resulting mixtures showed significantly lower melting temperatures than the neat salts. The physicochemical and thermal properties of these salts are thoroughly investigated and discussed.

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