Involvement of heparin-like glycosaminoglycans and expression of a novel heparan sulfate binding protein (p24) during human placentation and in a model for human implantation

Previous studies in our laboratory have indicated that heparan sulfate proteoglycans (HSPGs) play an important role in murine embryo implantation. To investigate the potential function of HSPGs in human implantation, two human cell lines (RL95 and JAR) were selected to model uterine epithelium and embryonal trophectoderm, respectively. A heterologous cell-cell adhesion assay showed that initial binding between JAR and RL95 cells is mediated by cell surface glycosaminoglycans (GAG) with heparin-like properties, i.e., heparan sulfate and dermatan sulfate. Furthermore, a single class of highly specific, protease-sensitive heparin/heparan sulfate binding sites exist on the surface of RL95 cells. Three heparin binding, tryptic peptide fragments were isolated from RL95 cell surfaces and their amino termini partially sequenced. Reverse transcription-polymerase chain reaction (RT-PCR) generated 1 to 4 PCR products per tryptic peptide. Northern blot analysis of RNA from RL95 cells using one of these RT-PCR products identified a 1.2 Kb mRNA species (p24). The amino acid sequence predicted from the cDNA sequence contains a putative heparin-binding domain. A synthetic peptide representing this putative heparin binding domain was used to generate a rabbit polyclonal antibody (anti-p24). Indirect immunofluorescence studies on RL95 and JAR cells as well as binding studies of anti-p24 to intact RL95 cells demonstrate that p24 is distributed on the cell surface. Western blots of RL95 membrane preparations identify a 24 kDa protein (p24) highly enriched in the 100,000 g pellet plasma membrane-enriched fraction. p24 eluted from membranes with 0.8 M NaCl, but not 0.6 M NaCl, suggesting that it is a peripheral membrane component. Solubilized p24 binds heparin by heparin affinity chromatography and $\sp{125}$I-heparin binding assays. Furthermore, indirect immunofluorescence studies indicate that cytotrophoblast of floating and attached villi of the human fetal-maternal interface are recognized by anti-p24. The study also indicates that the HSPG, perlecan, accumulates where chorionic villi are attached to uterine stroma and where p24-expressing cytotrophoblast penetrate the stroma. Collectively, these data indicate that p24 is a cell surface membrane-associated heparin/heparan sulfate binding protein found in cytotrophoblast, but not many other cell types of the fetal-maternal interface. Furthermore, p24 colocalizes with HSPGs in regions of cytotrophoblast invasion. These observations are consistent with a role for HSPGs and HSPG binding proteins in human trophoblast-uterine cell interactions. ^

The role of nitric oxide in small intestinal motility in a model of acute inflammation

Motility responses of the small intestine of iNOS deficient mice (iNOS −/−) and their wildtype littermates (iNOS+/+) to the inflammatory challenge of lipopolysaccharide (LPS) were investigated. LPS administration failed to attenuate intestinal transit in iNOS−/− mice but depressed transit in their iNOS+/+ littermates. Supporting an inhibitory role for sustained nitric oxide (NO) synthesis in the regulation of intestinal motility during inflammation, iNOS immunoreactivity was upregulated in all regions of the small intestine of iNOS+/+ mice. In contrast, neuronal NOS was barely affected. Cyclooxygenase activation was determined by prostaglandin E2 (PGE2) concentration. Following LPS challenge, PGE2 levels were elevated in all intestinal segments in both animal groups. Moreover, COX-1 and COX-2 protein levels were elevated in iNOS+/+ mice in response to LPS, while COX-2 levels were similarly increased in iNOS −/− intestine. However, no apparent relationship was observed between increased prostaglandin concentrations and attenuated intestinal transit. The presence of heme oxygenase 1 (HO-1) in the murine small intestine was also investigated. In both animal groups HO-1 immunoreactivity in the proximal intestine increased in response to treatment, while the constitutive protein levels detected in the middle and distal intestine were unresponsive to LPS administration. No apparent correlation of HO-1 to the suppression of small intestinal motility induced by LPS administration was detected. The presence of S-nitrosylated contractile proteins in the small intestine was determined. γ-smooth muscle actin was basally nitrosylated as well as in response to LPS, but myosin light chain kinase and myosin regulatory chain (MLC20) were not. In conclusion, in a model of acute intestinal inflammation, iNOS-produced NO plays a significant role in suppressing small intestinal motility while nNOS, COX-1, COX-2 and HO-1 do not participate in this event. S-nitrosylation of γ-smooth muscle actin is associated with elevated levels of nitric oxide in the smooth muscle of murine small intestine. ^

Errors in the administration of medication in inpatient hospitals: A systematic review of the research literature on commercial computerized physician order entry systems

Errors in the administration of medication represent a significant loss of medical resources and pose life altering or life threatening risks to patients. This paper considered the question, what impact do Computerized Physician Order Entry (CPOE) systems have on medication errors in the hospital inpatient environment? Previous reviews have examined evidence of the impact of CPOE on medication errors, but have come to ambiguous conclusions as to the impact of CPOE and decision support systems (DSS). Forty-three papers were identified. Thirty-one demonstrated a significant reduction in prescribing error rates for all or some drug types; decreases in minor errors were most often reported. Several studies reported increases in the rate of duplicate orders and failures to remove contraindicated drugs, often attributed to inappropriate design or to an inability to operate the system properly. The evidence on the effectiveness of CPOE to reduce errors in medication administration is compelling though it is limited by modest study sample sizes and designs. ^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

ROLE OF MIR-19A RELEASED BY INFLAMMATORY BREAST CANCER CELLS IN THE REGULATION OF DENDRITIC CELL FUNCTIONS: IN VITRO MODEL OF CROSSTALK IN THE TUMOR MICROENVIRONMENT OF INFLAMMATORY BREAST CANCER

Inflammatory breast cancer (IBC) is a rare but very aggressive form of locally advanced breast cancer (1-6% of total breast cancer patients in United States), with a 5-year overall survival rate of only 40.5%, compared with 85% of the non-IBC patients. So far, a unique molecular signature for IBC able to explain the dramatic differences in the tumor biology between IBC and non-IBC has not been identified. As immune cells in the tumor microenvironment plays an important role in regulating tumor progression, we hypothesized that tumor-associated dendritic cells (TADC) may be responsible for regulating the development of the aggressive characteristics of IBC. MiRNAs can be released into the extracellular space and mediate the intercellular communication by regulating target gene expression beyond their cells of origin. We hypothesized that miRNAs released by IBC cells can induce an increased activation status, secretion of pro-inflammatory cytokines and migration ability of TADC. In an in vitro model of IBC tumor microenvironment, we found that the co-cultured of the IBC cell line SUM-149 with immature dendritic cells (iDCSUM-149) induced a higher degree of activation and maturation of iDCSUM-149 upon stimulation with lipopolysaccharide (LPS) compared with iDCs co-cultured with the non-IBC cell line SUM-159 (iDCSUM-159), resulting in: increased expression of the costimulatory and activation markers; higher production of pro-inflammatory cytokines (TNF-a, IL-6); and 3) higher migratory ability. These differences were due to the exosome-mediated transfer of miR-19a and miR-146a from SUM-149 and SUM-159, respectively, to iDCs, causing the downregulation of the miR-19a target genes PTEN, SOCS-1 and the miR-146a target genes IRAK1, TRAF6. PTEN, SOCS-1 and IRAK1, TRAF6 are important negative and positive regulator of cytokine- and TLR-mediated activation/maturation signaling pathway in DCs. Increased levels of IL-6 induced the upregulation of miR-19a synthesis in SUM-149 cells that was associated with the induction of CD44+CD24-ALDH1+ cancer stem cells (CSCs) with epithelial-to-mesenchymal transition (EMT) characteristics. In conclusion, in IBC tumor microenvironment IL-6/miR-19a axis can represent a self-sustaining loop able to maintain a pro-inflammatory status of DCs, leading to the development of tumor cells with high metastatic potential (EMT CSCs) responsible of the poor prognosis in IBC patients.

STUDYING AGGREGATE FORMATION BY AMYOTROPHIC LATERAL SCLEROSIS-ASSOCIATED MUTANT SOD1 PROTEIN IN DROSOPHILA MODEL

A common pathological hallmark of most neurodegenerative disorders is the presence of protein aggregates in the brain. Understanding the regulation of aggregate formation is thus important for elucidating disease pathogenic mechanisms and finding effective preventive avenues and cures. Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, is a selective neurodegenerative disorder predominantly affecting motor neurons. The majority of ALS cases are sporadic, however, mutations in superoxide dismutase 1 (SOD1) are responsible for about 20% of familial ALS (fALS). Mutated SOD1 proteins are prone to misfold and form protein aggregates, thus representing a good candidate for studying aggregate formation. The long-term goal of this project is to identify regulators of aggregate formation by mutant SOD1 and other ALS-associated disease proteins. The specific aim of this thesis project is to assess the possibility of using the well-established Drosophila model system to study aggregation by human SOD1 (hSOD1) mutants. To this end, using wild type and the three mutant hSOD1 (A4V, G85R and G93A) most commonly found among fALS, I have generated 16 different SOD1 constructs containing either eGFP or mCherry in-frame fluorescent reporters, established and tested both cell- and animal-based Drosophila hSOD1 models. The experimental strategy allows for clear visualization of ectopic hSOD1 expression as well as versatile co-expression schemes to fully investigate protein aggregation specifically by mutant hSOD1. I have performed pilot cell-transfection experiments and verified induced expression of hSOD1 proteins. Using several tissue- or cell type-specific Gal4 lines, I have confirmed the proper expression of hSOD1 from established transgenic fly lines. Interestingly, in both Drosophila S2 cells and different fly tissues including the eye and motor neurons, robust aggregate formation by either wild type or mutant hSOD1 proteins was not observed. These preliminary observations suggest that Drosophila might not be a good experimental organism to study aggregation and toxicity of mutant hSOD1 protein. Nevertheless this preliminary conclusion implies the potential existence of a potent protective mechanism against mutant hSOD1 aggregation and toxicity in Drosophila. Thus, results from my SOD1-ALS project in Drosophila will help future studies on how to best employ this classic model organism to study ALS and other human brain degenerative diseases.

UNDERSTANDING INTERRUPTIONS IN HEALTHCARE: DEVELOPING A MODEL

Developing a Model Interruption is a known human factor that contributes to errors and catastrophic events in healthcare as well as other high-risk industries. The landmark Institute of Medicine (IOM) report, To Err is Human, brought attention to the significance of preventable errors in medicine and suggested that interruptions could be a contributing factor. Previous studies of interruptions in healthcare did not offer a conceptual model by which to study interruptions. As a result of the serious consequences of interruptions investigated in other high-risk industries, there is a need to develop a model to describe, understand, explain, and predict interruptions and their consequences in healthcare. Therefore, the purpose of this study was to develop a model grounded in the literature and to use the model to describe and explain interruptions in healthcare. Specifically, this model would be used to describe and explain interruptions occurring in a Level One Trauma Center. A trauma center was chosen because this environment is characterized as intense, unpredictable, and interrupt-driven. The first step in developing the model began with a review of the literature which revealed that the concept interruption did not have a consistent definition in either the healthcare or non-healthcare literature. Walker and Avant’s method of concept analysis was used to clarify and define the concept. The analysis led to the identification of five defining attributes which include (1) a human experience, (2) an intrusion of a secondary, unplanned, and unexpected task, (3) discontinuity, (4) externally or internally initiated, and (5) situated within a context. However, before an interruption could commence, five conditions known as antecedents must occur. For an interruption to take place (1) an intent to interrupt is formed by the initiator, (2) a physical signal must pass a threshold test of detection by the recipient, (3) the sensory system of the recipient is stimulated to respond to the initiator, (4) an interruption task is presented to recipient, and (5) the interruption task is either accepted or rejected by v the recipient. An interruption was determined to be quantifiable by (1) the frequency of occurrence of an interruption, (2) the number of times the primary task has been suspended to perform an interrupting task, (3) the length of time the primary task has been suspended, and (4) the frequency of returning to the primary task or not returning to the primary task. As a result of the concept analysis, a definition of an interruption was derived from the literature. An interruption is defined as a break in the performance of a human activity initiated internal or external to the recipient and occurring within the context of a setting or location. This break results in the suspension of the initial task by initiating the performance of an unplanned task with the assumption that the initial task will be resumed. The definition is inclusive of all the defining attributes of an interruption. This is a standard definition that can be used by the healthcare industry. From the definition, a visual model of an interruption was developed. The model was used to describe and explain the interruptions recorded for an instrumental case study of physicians and registered nurses (RNs) working in a Level One Trauma Center. Five physicians were observed for a total of 29 hours, 31 minutes. Eight registered nurses were observed for a total of 40 hours 9 minutes. Observations were made on either the 0700–1500 or the 1500-2300 shift using the shadowing technique. Observations were recorded in the field note format. The field notes were analyzed by a hybrid method of categorizing activities and interruptions. The method was developed by using both a deductive a priori classification framework and by the inductive process utilizing line-byline coding and constant comparison as stated in Grounded Theory. The following categories were identified as relative to this study: Intended Recipient - the person to be interrupted Unintended Recipient - not the intended recipient of an interruption; i.e., receiving a phone call that was incorrectly dialed Indirect Recipient – the incidental recipient of an interruption; i.e., talking with another, thereby suspending the original activity Recipient Blocked – the intended recipient does not accept the interruption Recipient Delayed – the intended recipient postpones an interruption Self-interruption – a person, independent of another person, suspends one activity to perform another; i.e., while walking, stops abruptly and talks to another person Distraction – briefly disengaging from a task Organizational Design – the physical layout of the workspace that causes a disruption in workflow Artifacts Not Available – supplies and equipment that are not available in the workspace causing a disruption in workflow Initiator – a person who initiates an interruption Interruption by Organizational Design and Artifacts Not Available were identified as two new categories of interruption. These categories had not previously been cited in the literature. Analysis of the observations indicated that physicians were found to perform slightly fewer activities per hour when compared to RNs. This variance may be attributed to differing roles and responsibilities. Physicians were found to have more activities interrupted when compared to RNs. However, RNs experienced more interruptions per hour. Other people were determined to be the most commonly used medium through which to deliver an interruption. Additional mediums used to deliver an interruption vii included the telephone, pager, and one’s self. Both physicians and RNs were observed to resume an original interrupted activity more often than not. In most interruptions, both physicians and RNs performed only one or two interrupting activities before returning to the original interrupted activity. In conclusion the model was found to explain all interruptions observed during the study. However, the model will require an even more comprehensive study in order to establish its predictive value.

TIME SERIES ANALYSIS AS INPUT FOR PREDICTIVE MODELING: PREDICTING CARDIAC ARREST IN A PEDIATRIC INTENSIVE CARE UNIT

The first manuscript, entitled "Time-Series Analysis as Input for Clinical Predictive Modeling: Modeling Cardiac Arrest in a Pediatric ICU" lays out the theoretical background for the project. There are several core concepts presented in this paper. First, traditional multivariate models (where each variable is represented by only one value) provide single point-in-time snapshots of patient status: they are incapable of characterizing deterioration. Since deterioration is consistently identified as a precursor to cardiac arrests, we maintain that the traditional multivariate paradigm is insufficient for predicting arrests. We identify time series analysis as a method capable of characterizing deterioration in an objective, mathematical fashion, and describe how to build a general foundation for predictive modeling using time series analysis results as latent variables. Building a solid foundation for any given modeling task involves addressing a number of issues during the design phase. These include selecting the proper candidate features on which to base the model, and selecting the most appropriate tool to measure them. We also identified several unique design issues that are introduced when time series data elements are added to the set of candidate features. One such issue is in defining the duration and resolution of time series elements required to sufficiently characterize the time series phenomena being considered as candidate features for the predictive model. Once the duration and resolution are established, there must also be explicit mathematical or statistical operations that produce the time series analysis result to be used as a latent candidate feature. In synthesizing the comprehensive framework for building a predictive model based on time series data elements, we identified at least four classes of data that can be used in the model design. The first two classes are shared with traditional multivariate models: multivariate data and clinical latent features. Multivariate data is represented by the standard one value per variable paradigm and is widely employed in a host of clinical models and tools. These are often represented by a number present in a given cell of a table. Clinical latent features derived, rather than directly measured, data elements that more accurately represent a particular clinical phenomenon than any of the directly measured data elements in isolation. The second two classes are unique to the time series data elements. The first of these is the raw data elements. These are represented by multiple values per variable, and constitute the measured observations that are typically available to end users when they review time series data. These are often represented as dots on a graph. The final class of data results from performing time series analysis. This class of data represents the fundamental concept on which our hypothesis is based. The specific statistical or mathematical operations are up to the modeler to determine, but we generally recommend that a variety of analyses be performed in order to maximize the likelihood that a representation of the time series data elements is produced that is able to distinguish between two or more classes of outcomes. The second manuscript, entitled "Building Clinical Prediction Models Using Time Series Data: Modeling Cardiac Arrest in a Pediatric ICU" provides a detailed description, start to finish, of the methods required to prepare the data, build, and validate a predictive model that uses the time series data elements determined in the first paper. One of the fundamental tenets of the second paper is that manual implementations of time series based models are unfeasible due to the relatively large number of data elements and the complexity of preprocessing that must occur before data can be presented to the model. Each of the seventeen steps is analyzed from the perspective of how it may be automated, when necessary. We identify the general objectives and available strategies of each of the steps, and we present our rationale for choosing a specific strategy for each step in the case of predicting cardiac arrest in a pediatric intensive care unit. Another issue brought to light by the second paper is that the individual steps required to use time series data for predictive modeling are more numerous and more complex than those used for modeling with traditional multivariate data. Even after complexities attributable to the design phase (addressed in our first paper) have been accounted for, the management and manipulation of the time series elements (the preprocessing steps in particular) are issues that are not present in a traditional multivariate modeling paradigm. In our methods, we present the issues that arise from the time series data elements: defining a reference time; imputing and reducing time series data in order to conform to a predefined structure that was specified during the design phase; and normalizing variable families rather than individual variable instances. The final manuscript, entitled: "Using Time-Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit" presents the results that were obtained by applying the theoretical construct and its associated methods (detailed in the first two papers) to the case of cardiac arrest prediction in a pediatric intensive care unit. Our results showed that utilizing the trend analysis from the time series data elements reduced the number of classification errors by 73%. The area under the Receiver Operating Characteristic curve increased from a baseline of 87% to 98% by including the trend analysis. In addition to the performance measures, we were also able to demonstrate that adding raw time series data elements without their associated trend analyses improved classification accuracy as compared to the baseline multivariate model, but diminished classification accuracy as compared to when just the trend analysis features were added (ie, without adding the raw time series data elements). We believe this phenomenon was largely attributable to overfitting, which is known to increase as the ratio of candidate features to class examples rises. Furthermore, although we employed several feature reduction strategies to counteract the overfitting problem, they failed to improve the performance beyond that which was achieved by exclusion of the raw time series elements. Finally, our data demonstrated that pulse oximetry and systolic blood pressure readings tend to start diminishing about 10-20 minutes before an arrest, whereas heart rates tend to diminish rapidly less than 5 minutes before an arrest.

A cladistic analysis of apolipoprotein B gene variation and plasma lipid and apolipoprotein B levels, using familial data

Any functionally important mutation is embedded in an evolutionary matrix of other mutations. Cladistic analysis, based on this, is a method of investigating gene effects using a haplotype phylogeny to define a set of tests which localize causal mutations to branches of the phylogeny. Previous implementations of cladistic analysis have not addressed the issue of analyzing data from related individuals, though in human studies, family data are usually needed to obtain unambiguous haplotypes. In this study, a method of cladistic analysis is described in which haplotype effects are parameterized in a linear model which accounts for familial correlations. The method was used to study the effect of apolipoprotein (Apo) B gene variation on total-, LDL-, and HDL-cholesterol, triglyceride, and Apo B levels in 121 French families. Five polymorphisms defined Apo B haplotypes: the signal peptide Insertion/deletion, Bsp 1286I, XbaI, MspI, and EcoRI. Eleven haplotypes were found, and a haplotype phylogeny was constructed and used to define a set of tests of haplotype effects on lipid and apo B levels.^ This new method of cladistic analysis, the parametric method, found significant effects for single haplotypes for all variables. For HDL-cholesterol, 3 clusters of evolutionarily-related haplotypes affecting levels were found. Haplotype effects accounted for about 10% of the genetic variance of triglyceride and HDL-cholesterol levels. The results of the parametric method were compared to those of a method of cladistic analysis based on permutational testing. The permutational method detected fewer haplotype effects, even when modified to account for correlations within families. Simulation studies exploring these differences found evidence of systematic errors in the permutational method due to the process by which haplotype groups were selected for testing.^ The applicability of cladistic analysis to human data was shown. The parametric method is suggested as an improvement over the permutational method. This study has identified candidate haplotypes for sequence comparisons in order to locate the functional mutations in the Apo B gene which may influence plasma lipid levels. ^

Behavioral effects of plasma tryptophan depletion in aggressive and nonaggressive men

Serotonin (5-HT) neurotransmission deficits have been implicated in impulsive aggression. A Trp-free beverage of amino acids competitively inhibits Trp uptake into the brain for 5-HT synthesis and also lowers endogenous plasma Trp for several hours. This has worsened mood and/or increased aggressive behavior, especially in hostile persons or those with histories of depression. In 24 community-recruited men (12 each with and without significant aggression histories), aggressive and impulsive behavior in the laboratory was assessed before and after plasma Trp depletion and Trp loading. In the aggression model, subjects were provoked by periodic subtractions of participation earnings, and these subtractions were blamed on a ficitious other participant. Aggression was measured as the responses the subject made to subtract money from his antagonist. Impulsiveness was operationalized as: (1) the choice of smaller reward after a shorter delay over having to wait longer to receive a larger reward, and (2) “false alarm” commission errors in a modified Continuous Performance Task, which represent a failure to inhibit responding to stimuli similar (but not identical) to target stimuli. Finally, plasma cortisol and Trp were measured under each condition immediately following a aggression testing session when subjects were highly provoked. I hypothesized that 5-HT may tonically modulate (inhibit) the hypothalmnic-pituitary-adrenal stress response, such that Trp depletion may enhance the cortisol response to high provocation in aggressive men. ^ Trp depletion had no effect in the laboratory tasks purported to measure impulsive behavior, and failed to cause increases in aggressive behavior under low provocation conditions. Under higher provocation, however, aggressive responses we re elevated under Trp-depleted conditions relative to Trp-loaded conditions in aggressive men, whereas the reverse was true in nonaggressive men. Cortisol levels nonsignificantly paralled the group differences in aggression under Trp-depleted and Trp-loaded conditions. Aggressive men achieved lower plasma Trp levels after Trp loading than did nonaggressive men, possibly due to heavy alcohol use histories. The high post-loading plasma Trp levels in nonaggressive men tended also to correlate with their aggressive responding rates, due perhaps to increases in other psychoactive Trp metabolites. ^

Depressive symptoms and sexual risk behaviors in adolescents

The purpose of this study was to determine whether depression is a factor in explaining the difference in sex behaviors among adolescents with different ethnic backgrounds, family and school contexts. We hypothesize that adolescents with a higher number of depressive symptoms are more likely to engage in sexual risk behaviors than adolescents with fewer depressive symptoms. Further, adolescent depression and sexual behaviors are mediated or moderated by individual characteristics, family and school contexts. ^ Background. large ethnic disparities exist in adolescent engagement in risky sexual behaviors, yet, there is little in the literature that explains these disparities. Studies of sexual behavior of youths abound; yet, there is little literature on the prevalence and correlates of depression or the association between depression and sexual behaviors among different ethnic groups. Objectives. (1) To determine ethnic differences in the prevalence of depressive symptoms using data collected through the National Longitudinal Study of Adolescent Health (Add Health). (2) To determine predictors of sex risk behaviors among adolescents, including the role of depression. (3) To identify predictors of depression among these adolescents. Methods. Add Health data from wave 1 and wave 2 interviews of 7th–12th graders were analyzed using multivariate models constructed with both depression and sexual behavior as outcome variables. Logistic regression models determined whether and to what extent the independent variables, including depression, sex behaviors, demographic factors, individual and family characteristics, and school context were related to the probability of engaging in risky sexual behaviors. Results. Ethnic differences in depressive symptoms did not persist after demographic and contextual variables were included in the model. Sex behaviors all shared the hypothesized relationship with depressive symptoms. The odds of risky sex behaviors increased as number of depressive symptoms increased. Depression was predicted by marijuana use and having a serious argument with father for males at Wave 1 and by age and future orientation for females. Wave 2 depression was predicted by Wave 1 depression. ^

Impact of a modified dietary plan on the health related quality of life of minority participants in the Women's Healthy Eating and Living (WHEL) Study

Advances in medical technology, in genetics, and in clinical research have led to early detection of cancer, precise diagnosis, and effective treatment modalities. Decline in cancer incidence and mortality due to cancer has led to increased number of long-term survivors. However, the ethnic minority population has not experienced this decline and still continues to carry a disparate proportion of the cancer burden. Majority of the clinical research including survivorship studies have recruited and continue to recruit a convenient sample of middle- to upper-class Caucasian survivors. Thus, minorities are underrepresented in cancer research in terms of both clinical studies and in health related quality of life (HRQOL) studies. ^ Life style and diet have been associated with increased risk of breast cancer. High vegetable low fat diet has been shown to reduce recurrence of breast cancer and early death. The Women's Healthy Eating and Living Study is an ongoing multi-site randomized controlled trial that is evaluating the high-vegetable low fat diet in reducing the recurrence of breast cancer and early death. The purpose of this dissertation was to (1) compare the impact of the modified diet on the HRQOL during the first 12-month period on specific Minorities and matched Caucasians; (2) identify predictors that significantly impact the HRQOL of the study participants; and (3) using the structural equation modeling assess the impact of nutrition on the HRQOL of the intervention group participants. Findings suggest that there are no significant differences in change in HRQOL between Minorities and Caucasians; between Minorities in the intervention group and those in the comparison group; and between women in the intervention group and those in the comparison group. Minority indicator variable and Intervention/Comparison group indicator variable were not found to be good predictors of HRQOL. Although the structural equation models suggested viable representation of the relationship between the antecedent variables, the mediating variables and the two outcome variables, the impact of nutrition was not statistically significant to be included in the model. This dissertation, by analyzing the HRQOL of minorities in the WHEL Study, attempted to add to the knowledge base specific to minority cancer survivors. ^

Metastatic lung cancer in a new mouse model inheriting p53 and latent K-ras mutations

Lung cancer is a devastating disease with very poor prognosis. The design of better treatments for patients would be greatly aided by mouse models that closely resemble the human disease. The most common type of human lung cancer is adenocarcinoma with frequent metastasis. Unfortunately, current models for this tumor are inadequate due to the absence of metastasis. Based on the molecular findings in human lung cancer and metastatic potential of osteosarcomas in mutant p53 mouse models, I hypothesized that mice with both K-ras and p53 missense mutations might develop metastatic lung adenocarcinomas. Therefore, I incorporated both K-rasLA1 and p53RI72HΔg alleles into mouse lung cells to establish a more faithful model for human lung adenocarcinoma and for translational and mechanistic studies. Mice with both mutations ( K-rasLA1/+ p53R172HΔg/+) developed advanced lung adenocarcinomas with similar histopathology to human tumors. These lung adenocarcinomas were highly aggressive and metastasized to multiple intrathoracic and extrathoracic sites in a pattern similar to that seen in lung cancer patients. This mouse model also showed gender differences in cancer related death and developed pleural mesotheliomas in 23.2% of them. In a preclinical study, the new drug Erlotinib (Tarceva) decreased the number and size of lung lesions in this model. These data demonstrate that this mouse model most closely mimics human metastatic lung adenocarcinoma and provides an invaluable system for translational studies. ^ To screen for important genes for metastasis, gene expression profiles of primary lung adenocarcinomas and metastases were analyzed. Microarray data showed that these two groups were segregated in gene expression and had 79 highly differentially expressed genes (more than 2.5 fold changes and p<0.001). Microarray data of Bub1b, Vimentin and CCAM1 were validated in tumors by quantitative real-time PCR (QPCR). Bub1b , a mitotic checkpoint gene, was overexpressed in metastases and this correlated with more chromosomal abnormalities in metastatic cells. Vimentin, a marker of epithelial-mesenchymal transition (EMT), was also highly expressed in metastases. Interestingly, Twist, a key EMT inducer, was also highly upregulated in metastases by QPCR, and this significantly correlated with the overexpression of Vimentin in the same tumors. These data suggest EMT occurs in lung adenocarcinomas and is a key mechanism for the development of metastasis in K-ras LA1/+ p53R172HΔg/+ mice. Thus, this mouse model provides a unique system to further probe the molecular basis of metastatic lung cancer.^

High-resolution microarray analysis of chromosome 20q in human colon cancer metastasis model systems

Amplification of human chromosome 20q DNA is the most frequently occurring chromosomal abnormality detected in sporadic colorectal carcinomas and shows significant correlation with liver metastases. Through comprehensive high-resolution microarray comparative genomic hybridization and microarray gene expression profiling, we have characterized chromosome 20q amplicon genes associated with human colorectal cancer metastasis in two in vitro metastasis model systems. The results revealed increasing complexity of the 20q genomic profile from the primary tumor-derived cell lines to the lymph node and liver metastasis derived cell lines. Expression analysis of chromosome 20q revealed a subset of over expressed genes residing within the regions of genomic copy number gain in all the tumor cell lines, suggesting these are Chromosome 20q copy number responsive genes. Bases on their preferential expression levels in the model system cell lines and known biological function, four of the over expressed genes mapping to the common intervals of genomic copy gain were considered the most promising candidate colorectal metastasis-associated genes. Validation of genomic copy number and expression array data was carried out on these genes, with one gene, DNMT3B, standing out as expressed at a relatively higher levels in the metastasis-derived cell lines compared with their primary-derived counterparts in both the models systems analyzed. The data provide evidence for the role of chromosome 20q genes with low copy gain and elevated expression in the clonal evolution of metastatic cells and suggests that such genes may serve as early biomarkers of metastatic potential. The data also support the utility of the combined microarray comparative genomic hybridization and expression array analysis for identifying copy number responsive genes in areas of low DNA copy gain in cancer cells. ^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^