Thoracic target volume delineation using various maximum-intensity projection computed tomography image sets for stereotactic body radiation therapy

The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.

Spectroscopic and functional investigations of the AMPA subtype of ionotropic glutamate receptors

Ion channels play a crucial role in the functioning of different systems of the body because of their ability to bridge the cell membrane and allow ions to pass in and out of the cell. Ionotropic glutamate receptors are one class of these important proteins and have been shown to be critical in propagating synaptic transmission in the central nervous system and in other diverse functions throughout the body. Because of their wide-ranging effects, this family of receptors is an important target for structure-function investigations to understand their mechanism of action. ^ α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors are one subtype of glutamate receptors and have been shown to be the primary receptors involved in rapid excitatory signaling in the central nervous system. Agonist binding to the extracellular ligand binding domain of these receptors causes various conformational changes that culminate in formation of the ion channel. Previous structural investigations have provided important information about their mechanism of action, including uncovering a relationship between the degree of cleft closure in the binding domain and activation of the receptor. However, what question remains unanswered is how specific interactions between the agonist and the protein interplay with cleft closure to mediate receptor activation. ^ To investigate this question, I applied a multiscale approach to investigate the effects of agonist binding on various levels. Vibrational spectroscopy was utilized to investigate molecular-level interactions in the binding pocket, and fluorescence resonance energy transfer (FRET) was employed to measure cleft closure in the isolated ligand binding domain. The results of these studies in the isolated binding domain were then correlated to activation of the full receptor. These investigations showed a relationship between the strength of the interaction at the α-amine group of the agonist and extent of receptor activation, where a stronger interaction correlated to a larger activation, which was upheld even when the extent of cleft closure did not correlate to activation. These results show that this interaction at the α-amine group is critical in mediating the allosteric mechanism of activation and provide a bit more insight into how agonist binding is coupled to channel gating in AMPA receptors. ^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^