Marketing physical activity and healthy eating: A literature review of recent social marketing campaigns and development of a social marketing plan for the CATCH program

Background. This culminating experience project was inspired by an independent study conducted at The University of Texas School of Public Health with Dr. Andrew Springer, DrPH, who works on the evaluation of the Coordinated Approach to Child Health (CATCH) program in Travis County, Texas. It was indicated that a social marketing plan could enhance current efforts for the CATCH program. The aims of the project were to (1) review and synthesize literature on social marketing, with a specific focus on diet, physical activity, and obesity prevention; and (2) apply the gained knowledge toward a practical solution – a social marketing plan for the CATCH program.^ Methods. The literature review aimed to answer the following questions: (1) What audiences (ethnic and age groups), settings, health behaviors, and behavioral science theories have been used in social marketing campaigns? (2) What features of social marketing were used (e.g. formative research, segmentation, and the marketing mix - including promotional strategies and communication channels)? (3) What were the outcomes of the social marketing campaigns? The search aimed to identify studies that met the following inclusion criteria: (a) The study explicitly stated that social marketing was used; (b) The intervention promoted physical activity and/or healthy eating; (c) The population was children, adolescents, young adults, and/or parents; (d) Results of the intervention were available in the published literature The literature review includes studies from the past five years (2004 to 2009). After reviewing the social marketing literature, the insight and knowledge gained was applied to develop a social marketing plan for the CATCH program. The plan was guided by Hands-on Social Marketing, A Step-by-Step Guide and the Center for Disease Control and Prevention's Social Marketing web course.^

Renal Cryoablation: Investigation of Periprocedural Visualization Tools and Treatment Response Quantification

Cryoablation for small renal tumors has demonstrated sufficient clinical efficacy over the past decade as a non-surgical nephron-sparing approach for treating renal masses for patients who are not surgical candidates. Minimally invasive percutaneous cryoablations have been performed with image guidance from CT, ultrasound, and MRI. During the MRI-guided cryoablation procedure, the interventional radiologist visually compares the iceball size on monitoring images with respect to the original tumor on separate planning images. The comparisons made during the monitoring step are time consuming, inefficient and sometimes lack the precision needed for decision making, requiring the radiologist to make further changes later in the procedure. This study sought to mitigate uncertainty in these visual comparisons by quantifying tissue response to cryoablation and providing visualization of the response during the procedure. Based on retrospective analysis of MR-guided cryoablation patient data, registration and segmentation algorithms were investigated and implemented for periprocedural visualization to deliver iceball position/size with respect to planning images registered within 3.3mm with at least 70% overlap and a quantitative logit model was developed to relate perfusion deficit in renal parenchyma visualized in verification images as a result of iceball size visualized in monitoring images. Through retrospective study of 20 patient cases, the relationship between likelihood of perfusion loss in renal parenchyma and distance within iceball was quantified and iteratively fit to a logit curve. Using the parameters from the logit fit, the margin for 95% perfusion loss likelihood was found to be 4.28 mm within the iceball. The observed margin corresponds well with the clinically accepted margin of 3-5mm within the iceball. In order to display the iceball position and perfusion loss likelihood to the radiologist, algorithms were implemented to create a fast segmentation and registration module which executed in under 2 minutes, within the clinically-relevant 3 minute monitoring period. Using 16 patient cases, the average Hausdorff distance was reduced from 10.1mm to 3.21 mm with average DSC increased from 46.6% to 82.6% before and after registration.

Volume and shape in feature space on adaptive FCM in MRI segmentation.

Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.

Molecular and biochemical analysis of the {\it Drosophila\/} segmentation gene {\it runt\/}

Genetic evidence has indicated that the segmentation gene runt plays a key role in regulating gene expression of the pair-rule genes hairy, even-skipped, and fushi tarazu. In contrast to other pair-rule genes, sequence data of the runt open reading frame did not reveal homologies to DNA-binding motifs of known transcriptional regulatory proteins. This thesis project examined several properties of the runt gene based on the sequence of the transcription unit, including the subcellular localization of the protein in vivo, its ability to bind DNA, and the functionality of a putative nucleotide binding domain.^ A runt-specific antibody was generated and used to demonstrate that runt is localized in the nucleus. Since the precise overlap of the pair-rule stripes is thought to be critical for the determination of cellular identity along the anterior-posterior axis, phasing of early runt expression in the blastoderm was examined with regard to the segmentation genes hairy, even-skipped, and fushi tarazu. runt was also expressed at later stages of embryogenesis, including expression in neuroblasts, and ganglion mother cells of the developing nervous system. Expression at this stage was required for the subsequent formation of specific neurons and runt was extensively expressed in the central and peripheral nervous systems.^ Several experiments were done to address the biochemical function of the runt protein. A direct interaction of runt with DNA was first examined. Although bacterial expressed runt was found to bind dsDNA-cellulose, subsequent experiments failed to detect sequence-specific interactions with DNA. Inter-species conservation of the putative nucleotide binding domain suggested that this region was functionally important, and runt protein bound a labeled ATP analog with high affinity in vitro. Finally, the effect of substitution of a critical residue of the nucleotide binding domain on runt activity was examined in vivo. Ectopic expression of the mutant protein indicated that this conserved substitution altered, but did not eliminate, runt activity as evaluated by segmentation phenotype and viability. ^

Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

Positional cloning and characterization of the human aniridia and murine small eye genes

Aniridia (AN) is a congenital, panocular disorder of the eye characterized by the complete or partial absence of the iris. The disease can occur in both the sporadic and familial forms which, in the latter case, is inherited as an autosomal dominant trait with high penetrance. The objective of this study was to isolate and characterize the genes involved in AN and Sey, and thereby to gain a better understanding of the molecular basis of the two disorders.^ Using a positional cloning strategy, I have approached and cloned from the AN locus in human chromosomal band 11p13 a cDNA that is deleted in two patients with AN. The deletions in these patients overlap by about 70 kb and encompass the 3$\sp\prime$ end of the cDNA. This cDNA detects a 2.7 kb mRNA encoded by a transcription unit estimated to span approximately 50 kb of genomic DNA. The message is specifically expressed in all tissues affected in all forms of AN, namely within the presumptive iris, lens, neuroretina, the superficial layers of the cornea, the olfactory bulbs, and the cerebellum. Sequence analysis of the AN cDNA revealed a number of motifs characteristic of certain transcription factors. Chief among these are the presence of the paired domain, the homeodomain, and a carboxy-terminal domain rich in serine, threonine and proline residues. The overall structure shows high homology to the Drosophila segmentation gene paired and members of the murine Pax family of developmental control genes.^ Utilizing a conserved human genomic DNA sequence as probe, I was able to isolate an embryonic murine cDNA which is over 92% homologous in nucleotide sequence and virtually identical at the amino acid level to the human AN cDNA. The expression pattern of the murine gene is the same as that in man, supporting the conclusion that it probably corresponds to the Sey gene. Its specific expression in the neuroectodermal component of the eye, in glioblastomas, but not in the neural crest-derived PC12 pheochromocytoma cell line, suggests that a defect in neuroectodermal rather mesodermal development might be the common etiological factor underlying AN and Sey. ^

Improved Techniques for Acquisition and Analysis of Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Detecting Vascular Permeability in the Central Nervous System

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive technique for quantitative assessment of the integrity of blood-brain barrier and blood-spinal cord barrier (BSCB) in the presence of central nervous system pathologies. However, the results of DCE-MRI show substantial variability. The high variability can be caused by a number of factors including inaccurate T1 estimation, insufficient temporal resolution and poor contrast-to-noise ratio. My thesis work is to develop improved methods to reduce the variability of DCE-MRI results. To obtain fast and accurate T1 map, the Look-Locker acquisition technique was implemented with a novel and truly centric k-space segmentation scheme. In addition, an original multi-step curve fitting procedure was developed to increase the accuracy of T1 estimation. A view sharing acquisition method was implemented to increase temporal resolution, and a novel normalization method was introduced to reduce image artifacts. Finally, a new clustering algorithm was developed to reduce apparent noise in the DCE-MRI data. The performance of these proposed methods was verified by simulations and phantom studies. As part of this work, the proposed techniques were applied to an in vivo DCE-MRI study of experimental spinal cord injury (SCI). These methods have shown robust results and allow quantitative assessment of regions with very low vascular permeability. In conclusion, applications of the improved DCE-MRI acquisition and analysis methods developed in this thesis work can improve the accuracy of the DCE-MRI results.