'Reform' of the British national health service after the election of a labour government: Understanding the policy development process

The policy development process leading to the Labour government's white paper of December 1997—The new NHS: Modern, Dependable—is the focus of this project and the public policy development literature is used to aid in the understanding of this process. Policy makers who had been involved in the development of the white paper were interviewed in order to acquire a thorough understanding of who was involved in this process and how they produced the white paper. A theoretical framework is used that sorts policy development models into those that focus on knowledge and experience, and those which focus on politics and influence. This framework is central to understanding the evidence gathered from the individuals and associations that participated in this policy development process. The main research question to be asked in this project is to what extent do either of these sets of policy development models aid in understanding and explicating the process by which the Labour government's policies were developed. The interview evidence, along with published evidence, show that a clear pattern of policy change emerged from this policy development process, and the Knowledge-Experience and Politics-Influence policy making models both assist in understanding this process. The early stages of the policy development process were characterized as hierarchical and iterative, yet also very collaborative among those participating, with knowledge and experience being quite prevalent. At every point in the process, however, informal networks of political influence were used and noted to be quite prevalent by all of the individuals interviewed. The later stages of the process then became increasingly noninclusive, with decisions made by a select group of internal and external policy makers. These policy making models became an important tool with which to understand the policy development process. This Knowledge-Experience and Politics-Influence dichotomy of policy development models could therefore be useful in analyzing other types of policy development. ^

Molecular cross talk between misfolded proteins in animal models of Alzheimer's and prion diseases.

The central event in protein misfolding disorders (PMDs) is the accumulation of a misfolded form of a naturally expressed protein. Despite the diversity of clinical symptoms associated with different PMDs, many similarities in their mechanism suggest that distinct pathologies may cross talk at the molecular level. The main goal of this study was to analyze the interaction of the protein misfolding processes implicated in Alzheimer's and prion diseases. For this purpose, we inoculated prions in an Alzheimer's transgenic mouse model that develop typical amyloid plaques and followed the progression of pathological changes over time. Our findings show a dramatic acceleration and exacerbation of both pathologies. The onset of prion disease symptoms in transgenic mice appeared significantly faster with a concomitant increase on the level of misfolded prion protein in the brain. A striking increase in amyloid plaque deposition was observed in prion-infected mice compared with their noninoculated counterparts. Histological and biochemical studies showed the association of the two misfolded proteins in the brain and in vitro experiments showed that protein misfolding can be enhanced by a cross-seeding mechanism. These results suggest a profound interaction between Alzheimer's and prion pathologies, indicating that one protein misfolding process may be an important risk factor for the development of a second one. Our findings may have important implications to understand the origin and progression of PMDs.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Household Hardships, Public Programs, and Their Associations with the Health and Development of Very Young Children: Insights from Children’s HealthWatch

America’s low-income families struggle to protect their children from multiple threats to their health and growth. Many research and advocacy groups explore the health and educational effects of food insecurity, but less is known about these effects on very young children. Children’s HealthWatch, a group of pediatric clinicians and public health researchers, has continuously collected data on the effects of food insecurity alone and in conjunction with other household hardships since 1998. The group’s peer reviewed research has shown that a number of economic risks at the household level, including food, housing and energy insecurity, tend to be correlated. These insecurities alone or in conjunction increase the risk that a young child will suffer various negative health consequences, including increases in lifetime hospitalizations, parental report of fair or poor health,1 or risk for developmental delays.2 Child food insecurity is an incremental risk indicator above and beyond the risk imposed by household-level food insecurity. The Children’sHealthwatch research also suggests public benefits programs modify some of these effects for families experiencing hardships. This empirical evidence is presented in a variety of public venues outside the usual scientific settings, such as congressional hearings, to support the needs of America’s most vulnerable population through policy change. Children’s HealthWatch research supports legislative solutions to food insecurity, including sustained funding for public programs and re-evaluation of the use of the Thrifty Food Plan as the basis of SNAP benefits calculations. Children’s HealthWatch is one of many models to support the American Academy of Pediatrics’ call to “stand up, speak up, and step up for children.”3 No isolated group or single intervention will solve child poverty or multiple hardships. However, working collaboratively each group has a role to play in supporting the health and well-being of young children and their families. 1. Cook JT, Frank DA, Berkowitz C, et al. Food insecurity is associated with adverse health outcomes among human infants and toddlers. J Nutr. 2004;134:1432-1438. 2. Rose-Jacobs R, Black MM, Casey PH, et al. Household food insecurity: associations with at-risk infant and toddler development. Pediatrics. 2008;121:65-72. 3. AAP leader says to stand up, speak up, and step up for child health [news release]. Boston, MA: American Academy of Pediatrics; October 11, 2008. http://www2.aap.org/pressroom/nce/nce08childhealth.htm. Accessed January 1, 2012.

Mouse models and quantitative trait loci of susceptibility to bleomycin- and radiation-induced pulmonary fibrosis

Radiotherapy involving the thoracic cavity and chemotherapy with the drug bleomycin are both dose limited by the development of pulmonary fibrosis. From evidence that there is variation in the population in susceptibility to pulmonary fibrosis, and animal data, it was hypothesized that individual variation in susceptibility to bleomycin-induced, or radiation-induced, pulmonary fibrosis is, in part, genetically controlled. In this thesis a three generation mouse genetic model of C57BL/6J (fibrosis prone) and C3Hf/Kam (fibrosis resistant) mouse strains and F1 and F2 (F1 intercross) progeny derived from the parental strains was developed to investigate the genetic basis of susceptibility to fibrosis. In the bleomycin studies the mice received 100 mg/kg (125 for females) of bleomycin, via mini osmotic pump. The animals were sacrificed at eight weeks following treatment or when their breathing rate indicated respiratory distress. In the radiation studies the mice were given a single dose of 14 or 16 Gy (Co$\sp{60})$ to the whole thorax and were sacrificed when moribund. The phenotype was defined as the percent of fibrosis area in the left lung as quantified with image analysis of histological sections. Quantitative trait loci (QTL) mapping was used to identify the chromosomal location of genes which contribute to susceptibility to bleomycin-induced pulmonary fibrosis in C57BL/6J mice compared to C3Hf/Kam mice and to determine if the QTL's which influence susceptibility to bleomycin-induced lung fibrosis in these progenitor strains could be implicated in susceptibility to radiation-induced lung fibrosis. For bleomycin, a genome wide scan revealed QTL's on chromosome 17, at the MHC, (LOD = 11.7 for males and 7.2 for females) accounting for approximately 21% of the phenotypic variance, and on chromosome 11 (LOD = 4.9), in male mice only, adding 8% of phenotypic variance. The bleomycin QTL on chromosome 17 was also implicated for susceptibility to radiation-induced fibrosis (LOD = 5.0) and contributes 7% of the phenotypic variance in the radiation study. In conclusion, susceptibility to both bleomycin-induced and radiation-induced pulmonary fibrosis are heritable traits, and are influenced by a genetic factor which maps to a genomic region containing the MHC. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Development of prostate cancer gene therapy

Osseous metastases account for most of the morbidity and mortality associated with prostate cancer, for which there are currently no effective therapies. In the skeletal metastatic environment, neoplastic prostatic epithelial cells interact in a bidirectional stimulatory manner with osteoblastic stromal cells. Similarly, the presence of osteoblastic cells is essential for the survival and maintenance of intraosseous prostate cancer cells. In this thesis, I have developed novel gene therapy strategies for the treatment of androgen-independent human prostate cancers in experimental animal models. First, Ad-CMV-p53, a recombinant adenovirus (Ad) containing p53 tumor suppressor gene driven by the universal cytomegalovirus promoter, was effective in inhibiting prostate cancer cell growth, and direct intratumoral injections of Ad-CMV-p53 resulted in tumor regression. Second, because prostate cancer cells as well as osteoblastic cells produce osteocalcin (OC), OC promoter mediated tissue/tumor specific toxic gene therapy is developed to interrupt stromal-epithelial communications by targeting both cell types. Ad-OC-TK, a recombinant Ad containing the herpes simplex virus thymidine kinase (TK) gene driven by the OC promoter, was generated to inhibit the growth of osteoblastic osteosarcoma with prodrug acyclovir (ACV). Ad-OC-TK/ACV also inhibited the growth of prostate cancer cells and suppressed the growth of subcutaneous and intraosseous prostate tumor. In order to combine treatment modalities to maximize tumor cell-kill with minimized host toxicities, Ad-OC-TK/ACV was applied in combination with low dose methotrexate to eradicate osteoblastic osteosarcoma. In targeting of micrometastatic disease, intravenous Ad-OC-TK/ACV treatment resulted in significant tumor nodule reduction and prolonged the survival of animals harboring osteosarcoma lung metastases without significant host toxicity. Ad-OC-TK is a rational choice for the treatment of prostate cancer skeletal metastasis because OC is uniformly detected in both primary and metastatic human prostate cancer specimens by immunohistochemistry. Ad-OC-TK/ACV inhibits the growth not only of prostate cancer cells but also of their supporting bone stromal cells. Targeting both prostate cancer epithelium and its supporting stroma may be most efficacious for the treatment of prostate cancer osseous metastases. ^

THE DESIGN AND DEVELOPMENT OF A SURVEY INSTRUMENT FOR THE ASSESSMENT OF OCCUPATIONAL STRESS

Using stress and coping as a unifying theoretical concept, a series of five models was developed in order to synthesize the survey questions and to classify information. These models identified the question, listed the research study, described measurements, listed workplace data, and listed industry and national reference data.^ A set of 38 instrument questions was developed within the five coping correlate categories. In addition, a set of 22 stress symptoms was also developed. The study was conducted within two groups, police and professors, on a large university campus. The groups were selected because their occupations were diverse, but they were a part of the same macroenvironment. The premise was that police officers would be more highly stressed than professors.^ Of a total study group of 80, there were 37 respondents. The difference in the mean stress responses was observable between the two groups. Not only were the responses similar within each group, but the stress level of response was also similar within each group. While the response to the survey instrument was good, only 3 respondents answered the stress symptom survey properly. It was determined that none of the 37 respondents believed that they were ill. This perception of being well was also evidenced by the grand mean of the stress scores of 2.76 (3.0 = moderate stress). This also caused fewer independent variables to be entered in the multiple regression model.^ The survey instrument was carefully designed to be universal. Universality is the ability to transcend occupational or regional definitions as applied to stress. It is the ability to measure responses within broad categories such as physiological, emotional, behavioral, social, and cognitive functions without losing the ability to measure the detail within the individual questions, or the relationships between questions and categories.^ Replication is much easier to achieve with standardized categories, questions, and measurement procedures such as those developed for the universal survey instrument. Because the survey instrument is universal it can be used as an analytical device, an assessment device, a basic tool for planning and a follow-up instrument to measure individual response to planned reductions in occupational stress. (Abstract shortened with permission of author.) ^

The utility of rapid participatory appraisal for community assessment, diagnosis, and policy development

The selection of a model to guide the understanding and resolution of community problems is an important issue relating to the foundation of public health practice: assessment, policy development, and assurance. Many assessment models produce a diagnosis of community weaknesses, but fail to promote planning and interventions. Rapid Participatory Appraisal (RPA) is a participatory action research model which regards assessment as the first step in the problem solving process, and claims to achieve assessment and policy development within limited resources of time and money. Literature documenting the fulfillment of these claims, and thereby supporting the utility of the model, is relatively sparse and difficult to obtain. Very few articles discuss the changes resulting from RPA assessments in urban areas, and those that do describe studies conducted outside the U.S.A. ^ This study examines the utility of the RPA model and its underlying theories: systems theory, grounded theory, and principles of participatory change, as illustrated by the case study of a community assessment conducted for the Texas Diabetes Institute (TDI), San Antonio, Texas, and subsequent outcomes. Diabetes has a high prevalence and is a major issue in San Antonio. Faculty and students conducted the assessment by informal collaboration between two nursing and public health assessment courses, providing practical student experiences. The study area was large, and the flexibility of the model tested by its use in contiguous sub-regions, reanalyzing aggregated results for the study area. Official TDI reports, and a mail survey of agency employees, described policy development resulting from community diagnoses revealed by the assessment. ^ The RPA model met the criteria for utility from the perspectives of merit, worth, efficiency, and effectiveness. The RPA model best met the agencies' criteria (merit), met the data needs of TDI in this particular situation (worth), provided valid results within budget, time, and personnel constraints (efficiency), and stimulated policy development by TDI (effectiveness). ^ The RPA model appears to have utility for community assessment, diagnosis, and policy development in circumstances similar to the TDI diabetes study. ^

Molecular genetic analyses of extracellular signaling pathways during murine retinal development

Extracellular signaling pathways initiated by secreted proteins are important in the co-ordination of tissue interactions in multi-cellular organisms, particularly during embryonic development. These signaling cascades direct diverse cellular events, including proliferation, differentiation and migration, in both autocrine and paracrine modes. In adult animals, abnormal function of these proteins often results in degenerative and tumourigenic syndromes. In this study, I have focused on elucidating the role of Bone Morphogenetic Protein (Bmp) signal transduction during neuronal specification and differentiation in the vertebrate embryo, using the mouse retina as a model. Using tissue-specific conditional knock-out approaches, the consequences of genetic loss-of-function of this signaling pathway on retinal physiology were examined. Mutant mice lacking Bmp type I receptor function displayed a range of retinal phenotypes, each of which appeared to be regulated at a different threshold of Bmp receptor activity. Novel essential functions for Bmp signaling were uncovered for retinal neurogenesis, cell survival, and axonal pathfinding at the optic disc. Further, BmprIa and BmprIa exhibited genetic interactions suggestive of functional redundancy. To further characterize the underlying molecular bases for the pleiotropic effects of Bmp receptors, retina-specific loss-of-function mutants of the obligate Bmp-activated transcriptional mediator Smad4 were generated. A comparison of the retina-specific Smad4 mutant phenotypes with those of the Bmp receptor mutant retina revealed that only a subset of retinal phenotypes, namely optic disc axon pathfinding and axial patterning were common for both classes of mutant animals. Thus, these results suggest that, contrary to the classic scheme of Bmp signal transduction, Smad4-independent pathways may be operative downstream of the type I receptors. Indeed, such alternative intracellular signaling cascades may constitute a molecular basis for the multiple cellular responses elicited by Bmp signaling. Finally, I tested whether the potential Bmp pathway targets, the extracellular ligands Fgf9 and Fgf15, mediate essential cellular processes in the retina. The analyses of Fgf9 −/−; Fgf15−/− mutant mice posit a novel shared role for these genes in intra-retinal axon pathfinding. Collectively, these studies have elucidated part of the molecular machinery directing mammalian neuro-retinal development, and provided useful in vivo models to study visual function. ^

The critical role and regulation of transcription factor FoxM1 in gastric cancer development and progression

The mammalian Forkhead Box (Fox) transcription factor (FoxM1) is implicated in tumorgenesis. However, the role and regulation of FoxM1 in gastric cancer remain unknown.^ I examined FoxM1 expression in 86 cases of primary gastric cancer and 57 normal gastric tissue specimens. I found weak expression of FoxM1 protein in normal gastric mucosa, whereas I observed strong staining for FoxM1 in tumor-cell nuclei in various gastric tumors and lymph node metastases. The aberrant FoxM1 expression is associated with VEGF expression and increased angiogenesis in human gastric cancer. A Cox proportional hazards model revealed that FoxM1 expression was an independent prognostic factor in multivariate analysis. Furthermore, overexpression of FoxM1 by gene transfer significantly promoted the growth and metastasis of gastric cancer cells in orthotopic mouse models, whereas knockdown of FoxM1 expression by small interfering RNA did the opposite. Next, I observed that alteration of tumor growth and metastasis by elevated FoxM1 expression was directly correlated with alteration of VEGF expression and angiogenesis. In addition, promotion of gastric tumorigenesis by FoxM1 directly and significantly correlated with transactivation of vascular endothelial growth factor (VEGF) expression and elevation of angiogenesis. ^ To further investigate the underlying mechanisms that result in FoxM1 overexpression in gastric cancer, I investigated FoxM1 and Krüppel-like factor 4 (KLF4) expressions in primary gastric cancer and normal gastric tissue specimens. Concomitance of increased expression of FoxM1 protein and decreased expression of KLF4 protein was evident in human gastric cancer. Enforced KLF4 expression suppressed FoxM1 protein expression. Moreover, a region within the proximal FoxM1 promoter was identified to have KLF4-binding sites. Finally, I found an increased FoxM1 expression in gastric mucosa of villin-Cre -directed tissue specific Klf4-null mice.^ In summary, I offered both clinical and mechanistic evidence that dysregulated expression of FoxM1 play an important role in gastric cancer development and progression, while KLF4 mediates negative regulation of FoxM1 expression and its loss significantly contributes to FoxM1 dysregulation. ^

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

FEMALE SEXUAL MATURATION AND BLOOD PRESSURE (SECONDARY-SEX CHARACTERISTICS, GROWTH, DEVELOPMENT)

This study described the relationship of sexual maturation and blood pressure in a sample (n = 361) of white females, ages seven through 18, attending public schools in a defined area of Central Texas during October through December, 1984. Other correlates of blood pressure were also described for this sample.^ A survey was performed to obtain the data on height, weight, body mass, pulse rate, upper arm circumference and length, and blood pressure. Each subject self-assessed her secondary sex characteristics (breast and pubic hair) according to drawings of the Tanner stages of maturation. The subjects were interviewed to obtain data on personal health habits and menstrual status. Student age, ethnic group and place of residence were abstracted from school records. Parents or guardians of the subjects responded to a questionnaire pertaining to parental and subject health history and parents' occupation and educational attainment.^ In the simple linear regression analysis, sexual maturation and variables of body size were significantly (p < 0.001) and positively associated with systolic and fourth- and fifth-phase diastolic blood pressure. The demographic and socioeconomic variables were not sufficiently variant in this population to have differential effects on the relation between blood pressure and maturation. Stepwise multiple regression was used to assess the contribution of sexual maturation to the variance of blood pressure after accounting for the variables of body size. Sexual maturation (breast stage) along with weight, height and body mass remained in the multiple regression models for fourth- and fifth-phase diastolic blood pressure. Only height and body mass remained in the regression model for systolic blood pressure; sexual maturation did not contribute more to the explanation of the systolic blood pressure variance.^ The association of sexual maturation with blood pressure level was established in this sample of young white females. More research is needed first, to determine if this relationship prevails in other populations of young females, and second, to determine the relationship of sexual maturation sequence and change with the change of blood pressure during childhood and adolescence. ^

DEVELOPMENT AND IMPLEMENTATION OF A REMOTE AUDIT TOOL FOR HIGH DOSE RATE (HDR) 192IR BRACHYTHERAPY USING OPTICALLY STIMULATED LUMINESCENCE DOSIMETRY

This work aimed to create a mailable and OSLD-based phantom with accuracy suitable for RPC audits of HDR brachytherapy sources at institutions participating in NCI-funded cooperative clinical trials. An 8 × 8 × 10 cm3 prototype with two slots capable of holding nanoDot Al2O3:C OSL dosimeters (Landauer, Glenwood, IL) was designed and built. The phantom has a single channel capable of accepting all 192Ir HDR brachytherapy sources in current clinical use in the United States. Irradiations were performed with an 192Ir HDR source to determine correction factors for linearity with dose, dose rate, and the combined effect of irradiation energy and phantom construction. The uncertainties introduced by source positioning in the phantom and timer resolution limitations were also investigated. It was found that the linearity correction factor was where dose is in cGy, which differed from that determined by the RPC for the same batch of dosimeters under 60Co irradiation. There was no significant dose rate effect. Separate energy+block correction factors were determined for both models of 192Ir sources currently in clinical use and these vendor-specific correction factors differed by almost 2.6%. For Nucletron sources, this correction factor was 1.026±0.004 (99% Confidence Interval) and for Varian sources it was 1.000±0.007 (99% CI). Reasonable deviations in source positioning within the phantom and the limited resolution of the source timer had insignificant effects on the ability to measure dose. Overall measurement uncertainty of the system was estimated to be ±2.5% for both Nucletron and Varian source audits (95% CI). This uncertainty was sufficient to establish a ±5% acceptance criterion for source strength audits under a formal RPC audit program. Trial audits of eight participating institutions resulted in an average RPC-to-institution dose ratio of 1.000 with a standard deviation of 0.011.

Targeting TRAF6 for Cancer Therapeutical Development

Tumor necrosis factor (TNF)-Receptor Associated Factors (TRAFs) are a family of signal transducer proteins. TRAF6 is a unique member of this family in that it is involved in not only the TNF superfamily, but the toll-like receptor (TLR)/IL-1R (TIR) superfamily. The formation of the complex consisting of Receptor Activator of Nuclear Factor κ B (RANK), with its ligand (RANKL) results in the recruitment of TRAF6, which activates NF-κB, JNK and MAP kinase pathways. TRAF6 is critical in signaling with leading to release of various growth factors in bone, and promotes osteoclastogenesis. TRAF6 has also been implicated as an oncogene in lung cancer and as a target in multiple myeloma. In the hopes of developing small molecule inhibitors of the TRAF6-RANK interaction, multiple steps were carried out. Computational prediction of hot spot residues on the protein-protein interaction of TRAF6 and RANK were examined. Three methods were used: Robetta, KFC2, and HotPoint, each of which uses a different methodology to determine if a residue is a hot spot. These hot spot predictions were considered the basis for resolving the binding site for in silico high-throughput screening using GOLD and the MyriaScreen database of drug/lead-like compounds. Computationally intensive molecular dynamics simulations highlighted the binding mechanism and TRAF6 structural changes upon hit binding. Compounds identified as hits were verified using a GST-pull down assay, comparing inhibition to a RANK decoy peptide. Since many drugs fail due to lack of efficacy and toxicity, predictive models for the evaluation of the LD50 and bioavailability of our TRAF6 hits, and these models can be used towards other drugs and small molecule therapeutics as well. Datasets of compounds and their corresponding bioavailability and LD50 values were curated based, and QSAR models were built using molecular descriptors of these compounds using the k-nearest neighbor (k-NN) method, and quality of these models were cross-validated.