Statins, common cholesterol control drugs, are appreciated to have promising anticancer activity through inhibition of the mevalonate pathway. Several lines of evidence suggest that certain tumours are susceptible to statins, but the underlying molecular features arbitrating this sensitivity remain unknown. We hypothesize that (i) not all statins will behave equivalently in the context of anticancer therapy, and (ii) a molecularly-defined subset of tumours are intrinsically sensitive to statins. My objectives have therefore been to further our understanding of functional differences between statins influencing their anticancer effects, and to investigate molecular features associated with statin sensitivity in breast cancer. Specifically, this thesis addresses two aims: (i) to characterize differential interactions between four statins and the xenobiotic transporter P-glycoprotein (P-gp; also known as ABCB1), and (ii) to identify molecular features associated with fluvastatin and lovastatin sensitivity in breast tumour cell lines. We first characterized the interactions of statins with P-gp in vitro and in multidrug-resistant (MDR) tumour cells. While lovastatin could directly bind to P-gp and modulate MDR, no significant interactions were observed with fluvastatin. Fluvastatin may therefore be appropriate for use in unselected patients, to avoid adverse drug interactions with coadministered P-gp substrate chemotherapeutics. Fluvastatin has also shown promise in breast cancer treatment, where molecular features predictive of statin sensitivity would be particularly valuable. A panel of 19 immortalized breast cell lines was therefore characterized for sensitivity to fluvastatin and lovastatin. Relatively statin-sensitive cells underwent apoptosis upon statin treatment, and were more likely to have an estrogen receptor alpha (ERα)-negative, basal-like phenotype. By mining available baseline gene expression data, a candidate 10-gene signature predictive of fluvastatin sensitivity was also generated. Taken together, this research provides insight into molecular markers of statin sensitivity that may facilitate fast-tracking of these drugs to clinical trials in subsets of cancer patients most likely to respond.

Introduction Radiologic Technologists exposed to continuous low dose radiation may have an increased risk for spontaneous abortions. Although the federally mandated radiation dose limit to the developing fetus of an occupational worker is 5mSv, well below the documented threshold of 100mSv, some studies have suggested an increased risk for spontaneous abortions in occupationally exposed females. The effects of exposure to low levels of radiation are difficult to discern from the usual occurrence and are limited in the literature because of the large sample size needed to achieve statistical power. This study contains data from 152,439 self-reported pregnancies and possesses the appropriate sample size to assess the risk of spontaneous abortions incident to radiologic technologists who maintain fetal radiation dose levels within federal guidelines. Methods This non-experimental retrospective designed study uses data from the United States Radiologic Technologist Study (USRTS). The USRTS began in 1982 as a joint effort between the American Registry of Radiologic Technologists (ARRT),UniversityofMinnesotaand the National Cancer Institute to study the radiation effects from low-dose occupational exposure. This longitudinal study follows more than 90,000 current and former technologists through periodic surveys and contains a sufficient sample size to overcome statistical power concerns. The provided data included the order and outcome of each self-reported pregnancy as well as the year of each live birth. The data were therefore manipulated to provide a likely gestational interval for both a reported live birth and spontaneous abortion. After calculating the spontaneous abortion rate for the final sample, a binary logistic regression was performed to determine if levels of estimated fetal radiation dose are associated with predicting the odds of a reported spontaneous abortion. A linear regression analysis was then performed to assess the relationship between the calculated odds ratios of a reported spontaneous abortion as a function of estimated fetal radiation dose, specifically to determine the significance of the linear relationship Results The overall spontaneous abortion incidence to the cohort reporting at least one live birth or spontaneous abortion was 14.8%, lower than the reported national incidence of 15-20%. Using up to 1mSv as the reference fetal radiation dose category, the odds ratios of a spontaneous abortion for 1-2mSv, 2-3mSv, 3-4mSv and 4-5mSv were calculated as 1.57, 1.82, 2.11 and 2.15 respectively. This increase in odds was linear with estimated fetal radiation dose as demonstrated by the significant regression equation (F=29.93, p = .01) and an R2 of 0.9089. Conclusions By demonstrating an increased risk at levels of radiation as low as natural background, and further demonstrating the risk increases linearly with radiation dose, the Linear Non-Threshold Theory appears to be the more likely risk model for predicting spontaneous abortions in lieu of the belief that a 100mSv threshold must first be exceeded for a radiation induced spontaneous abortion to occur. Application of this model demonstrates the risk of a spontaneous abortion is twice as likely in occupational workers whose fetal radiation doses are closer to the maximum allowable limit of 5mSv compared with those who maintain fetal radiation doses below 1mSv.

The complexity of the interface between the muscular system and the nervous system is still elusive. We investigated how the neuromuscular system functions and how it is influenced by various perturbations. Postural stability was selected as the model system, because this system provides complex output, which could indicate underlying mechanisms and feedback loops of the neuromuscular system. We hypothesized that aging, physical pain, and mental and physical perturbations affect balancing strategy, and based on these observations, we constructed a model that simulates many aspects of the neuromuscular system. Our results show that aging changes the control strategy of balancing from more chaotic to more repetitive. The chaotic elements ensure quick reactions and strong capacity to compensate for the perturbations; this adeptly reactive state changes into a less reactive, slower, probably less mechanically costly balancing strategy. Mental tasks during balancing also decreased the chaotic elements in balancing strategy, especially if the subject experienced chronic pain. Additional motoric tasks, such as tying knots while balancing, were correlated with age but unaffected by chronic pain. Our model competently predicted the experimental findings, and we proceeded to use the model with an external data set from Physionet to predict the balancing strategy of Parkinson’s patients. Our neurological model, comprised of RLC circuits, provides a mechanistic explanation for the neuromuscular system adaptations.

Statins, common cholesterol control drugs, are appreciated to have promising anticancer activity through inhibition of the mevalonate pathway. Several lines of evidence suggest that certain tumours are susceptible to statins, but the underlying molecular features arbitrating this sensitivity remain unknown. We hypothesize that (i) not all statins will behave equivalently in the context of anticancer therapy, and (ii) a molecularly-defined subset of tumours are intrinsically sensitive to statins. My objectives have therefore been to further our understanding of functional differences between statins influencing their anticancer effects, and to investigate molecular features associated with statin sensitivity in breast cancer. Specifically, this thesis addresses two aims: (i) to characterize differential interactions between four statins and the xenobiotic transporter P-glycoprotein (P-gp; also known as ABCB1), and (ii) to identify molecular features associated with fluvastatin and lovastatin sensitivity in breast tumour cell lines. We first characterized the interactions of statins with P-gp in vitro and in multidrug-resistant (MDR) tumour cells. While lovastatin could directly bind to P-gp and modulate MDR, no significant interactions were observed with fluvastatin. Fluvastatin may therefore be appropriate for use in unselected patients, to avoid adverse drug interactions with coadministered P-gp substrate chemotherapeutics. Fluvastatin has also shown promise in breast cancer treatment, where molecular features predictive of statin sensitivity would be particularly valuable. A panel of 19 immortalized breast cell lines was therefore characterized for sensitivity to fluvastatin and lovastatin. Relatively statin-sensitive cells underwent apoptosis upon statin treatment, and were more likely to have an estrogen receptor alpha (ERα)-negative, basal-like phenotype. By mining available baseline gene expression data, a candidate 10-gene signature predictive of fluvastatin sensitivity was also generated. Taken together, this research provides insight into molecular markers of statin sensitivity that may facilitate fast-tracking of these drugs to clinical trials in subsets of cancer patients most likely to respond.

A remote-sensing acoustic method for implementing position control feedback in Scanning Probe Microscopy (SPM) is presented. The capabilities of this feedback control using the new Whispering Gallery Acoustic Sensing (WGAS) method is demonstrated in a Shear-force Scanning Probe Microscope that uses a sharp probe attached to a piezoelectric Quartz Tuning Fork (QTF) firmly mounted on the microscope's frame. As the QTF is electrically driven its mechanical response reaches the SPM frame which then acts as a resonant cavity producing acoustic modes measured with an acoustic sensor strategically placed on the SPM head. The novelty of the WGAS resides in using an SPM frame with a perimeter closely matching the intervening acoustic wavelength to act as a resonant cavity. The whispering gallery cavity constitutes an acoustic amplifier for the mechanical motion of the QTF probe. The observed monotonic behavior of the whispering gallery acoustic signal as a function of the probe sample distance is exploited here for tip-sample distance control with nanometer sensitivity, thus allowing topographic characterization as the probe is scanned across the sample's surface. This thesis includes a description of a Labview based programming for the Field Programmable Gate Array (FPGA) card used in the automated control of the WGAS feedback microscope, a solution for improving the effective resolution of the Digital to Analog Converter (DAC) and initial results towards theoretically modeling the WGAS working principle.

<p>Simultaneous dual-isotope SPECT imaging has a number of applications, for exam- ple, cardiac, brain and cancer imaging. The major concern in simultaneous dual- isotope SPECT is the significant crosstalk contamination between the different isotopes used. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using ^99mTc/¹¹¹In and breast SPECT using ^99mTc/¹²³I. Monte Carlo (MC), which is thought to offer the most realistic crosstalk and scatter compensation modelling, in typical implementations, has inherent long calculation times (often several hours or days) associated with it. This makes MC unsuitable for clinical applications. We have previously incorporated convolution based forced detection into SIMIND Monte Carlo (MC) program which have made MC feasible to use in clinical time frames. In order to evaluate the accuracy of our accelerated MC program a number of point source simulation results were compared to experimentally acquired data in terms of spatial resolution and detector sensitivity. We have developed an iterative MC based image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. The MC based estimation of scatter contamination contained in projection views is then used to compensate for the photon contamination during iterative reconstruction. We use a modified ordered subset expectation maximization (OSEM) alogrithm, named as simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach in case of both of the dual-isotope combinations (i.e. ^99mTc/¹¹¹In and ^99mTc/¹²³I). In breast SPECT studies three different breast sizes were simulated. For each of the breast sizes ten combinations of lesions with 3 lesions per combination, were selected randomly for acquisition and reconstruction of simulation data. The images reconstructed using Sim-OSEM showed crosstalk compensation when compared with images reconstructed using simultaneously (with crosstalk) acquired projection data using analytical attenuation based reconstruction. In case of Sim-OSEM the lesion to background ratios were much closer to actual values compared to images reconstructed for both separately (without crosstalk) and simultaneously (with crosstalk) acquired projection data using analytical attenuation based reconstruction. Activity estimation is also possible with Sim-OSEM and yielded accurate estimates of lesion activities with relatively small error compared to deposited activities. The proposed reconstruction technique also evaluated by reconstruction of experimentally acquired projection phantom data in case of ^99mTc/¹¹¹In. Reconstruction using Sim-OSEM showed very promising results in terms of crosstalk and small angle scatter compensation and uniformity of background compared to analytical attenuation based reconstruction after triple energy window (TEW) based scatter correction of projection data. In our case images obtained using Sim-OSEM showed more uniform background even when compared to the images reconstructed for separately acquired projection data using analytical attenuation based reconstruction may be due to better correction of photons scattered at small angle and got detected under photopeak.</p> / Master of Science (MSc)

Cardiac arrhythmias are caused by a disruption of the normal initiation or propagation of electrical impulses in the heart. Hundreds of mutations in genes encoding ion channels or ion channel regulatory proteins are linked to congenital arrhythmia syndromes that increase the risk for sudden cardiac death. This dissertation focuses on how mutations in a gene (KCNQ1) that encodes a voltage-gated K+ ion channel (Kv7.1) can disrupt proper channel function and lead to abnormal repolarization of atrial and ventricular cardiomyocytes. In the heart, Kv7.1 coassembles with a regulatory protein to conduct the slowly activating delayed rectifier K+ current (IKs). Loss-of-function KCNQ1 mutations are linked to type 1 long QT syndrome (LQT1), and typically decrease IKs, which can lead to ventricular action potential (AP) prolongation. In patients, LQT1 is often characterized by an abnormally long corrected QT (QTc) interval on an electrocardiogram (ECG), and increases the risk for polymorphic ventricular tachycardias. KCNQ1 mutations are also linked to atrial fibrillation (AF), but cause a gain-of-function phenotype that increases IKs. Surprisingly, patients diagnosed with both LQT1 and AF are increasingly identified as genotype positive for a KCNQ1 mutation. The first aim of this dissertation was to determine a unique functional phenotype of KCNQ1 mutations linked to both arrhythmia syndromes by functional analyses via the whole-cell patch clamp technique in HEK293 cells. A proportion of patients with LQT1-linked KCNQ1 mutations do not have abnormal QTc prolongation known as latent LQT1. Interestingly, exercise can reveal abnormal QTc prolongation in these patients. During exercise, beta-adrenergic activation stimulates PKA to phosphorylate Kv7.1, causing an increase in IKs to prevent ventricular AP prolongation. Therefore, the second aim of this dissertation was to determine a molecular mechanism of latent LQT1 through functional analyses in HEK293 cells while incorporating pharmacological and phosphomimetic approaches to study PKA regulation of mutant Kv7.1 channels. The findings in this dissertation provide new insight into how KCNQ1 mutations disrupt the function of Kv7.1 in a basal condition or during beta-adrenergic activation. Also, this dissertation suggests these approaches will improve patient management by identifying mutation specific risk factors for patients with KCNQ1 mutations.

Dual-energy computed tomography (DECT) has shown great potential in the reduction of uncertainties of proton ranges and low energy photon cross section estimation used in radiation therapy planning. The work presented herein investigated three contributions for advancing DECT applications. 1) A linear and separable two-parameter DECT, the basis vector model (BVM) was used to estimate proton stopping power. Compared to other nonlinear two-parameter models in the literature, the BVM model shows a comparable accuracy achieved for typical human tissues. This model outperforms other nonlinear models in estimations of linear attenuation coefficients. This is the first study to clearly illustrate the advantages of linear model not only in accurately mapping radiological quantities for radiation therapy, but also in providing a unique model for accurate linear forward projection modelling, which is needed by the statistical iterative reconstruction (SIR) and other advanced DECT reconstruction algorithms. 2) Accurate DECT requires knowledge of x-ray beam properties. Using the Birch-Marshall1 model and beam hardening correction coefficients encoded in a CT scanner’s sinogram header files, an efficient and accurate way to estimate the x-ray spectrum is proposed. The merits of the proposed technique lie in requiring no physical transmission measurement after a one-time calibration against an independently measured spectrum. This technique can also be used in monitoring the aging of x-ray CT tubes. 3) An iterative filtered back projection with anatomical constraint (iFBP-AC) algorithm was also implemented on a digital phantom to evaluate its ability in mitigating beam hardening effects and supporting accurate material decomposition for in vivo imaging of photon cross section and proton stopping power. Compared to iFBP without constraints, both algorithms demonstrate high efficiency of convergence. For an idealized digital phantom, similar accuracy was observed under a noiseless situation. With clinically achievable noise level added to the sinograms, iFBP-AC greatly outperforms iFBP in prediction of photon linear attenuation at low energy, i.e., 28 keV. The estimated mean errors of iFBP and iFBP-AC for cortical bone are 1% and 0.7%, respectively; the standard deviations are 0.6% and 5%, respectively. The achieved accuracy of iFBP-AC shows robustness versus contrast level. Similar mean errors are maintained for muscle tissue. The standard deviation achieved by iFBP-AC is 1.2%. In contrast, the standard deviation yielded by iFBP is about 20.2%. The algorithm of iFBP-AC shows potential application of quantitative measurement of DECT. The contributions in this thesis aim to improve the clinical performance of DECT.

Ligands of the human monoamine transporters encompass a wide range of both illicit and therapeutic drugs that act upon neural circuitry related to reward, motivation, and the processing of salient stimuli. The present study utilizes two methods for analyzing transporter substrates and inhibitors in order to characterize activity and assess potency. The first measures transient changes in intracellular calcium as a surrogate for transporter activity by harnessing the electrical coupling of monoamine transporters and L-type calcium channels. This is used to analyze novel chimera of the strong hDAT inhibitors methylphenidate and 𝛼-PPP in order to assess the contribution of specific moieties to potency. The observed reduction in potency suggests that methylphenidate may bind to the transporter in a manner distinct from 𝛼-PPP, as chimera would otherwise be expected to show similar activity to parent compounds. These results highlight the importance of 𝛼-carbon substituents and the relatively small contribution of beta-carbon groups to inhibitor potency at hDAT, while the lack of activity at hSERT suggests potency is not strongly influenced by beta-carbon or N-alkyl substituents. In order to further characterize drug-transporter interaction, a method was developed to analyze the kinetics of binding and unbinding using both known and novel hNET ligands, including a series of N-alkyl derivatives of 4-methylamphetamine. The study emphasizes the importance of both association and dissociation kinetics to affinity and sets up a methodological framework with two ways for determining Kd, with notable advantages over current models. The results indicate that lengthening the N-alkyl chain of 4-methylamphetamine leads to a decrease in potency and a shift in activity from substrate to blocker, with the results of N-propyl 4-methylamphetamine in particular indicating the potential existence of multiple low-affinity binding sites, each with distinct on and off kinetics. The implications of these results help elucidate the mechanism of action of transporter ligands and set up a framework for future studies that can more specifically classify the interaction between transporters and inhibitors or releasing agents.

A major challenge of cancer treatment is successful discrimination of cancer cells from healthy cells. Nanotechnology offers multiple venues for efficient cancer targeting. Magnetoelectric nanoparticles (MENs) are a novel, multifaceted, physics-based cancer treatment platform that enables high specificity cancer targeting and externally controlled loaded drug release. The unique magnetoelectric coupling of MENs allows them to convert externally applied magnetic fields into intrinsic electric signals, which allows MENs to both be drawn magnetically towards the cancer site and to electrically interface with cancer cells. Once internalized, the MEN payload release can be externally triggered with a magnetic field. MENs uniquely allow for discrete manipulation of the drug delivery and drug release mechanisms to allow an unprecedented level of control in cancer targeting. In this study, we demonstrate the physics behind the MEN drug delivery platform, test the MEN drug delivery platform for the first time in a humanized mouse model of cancer, and characterize the biodistribution and clearance of MENs. We found that MENs were able to fully cure the model cancer, which in this case was human ovarian carcinoma treated with paclitaxel. When compared to conventional magnetic nanoparticles and FDA approved organic PLGA nanoparticles, MENs are the highest performing treatment, even in the absence of peripheral active targeting molecules. We also mapped the movement through peripheral organs and established clearance trends of the MENs. The MENs cancer treatment platform has immense potential for future medicine, as it is generalizable, personalizable, and readily traceable in the context of treating essentially any type of cancer.