A dose-response analysis of a school-based nutrition intervention in middle school children

Childhood obesity in the US has reached epidemic proportions. Minority children are affected the most by this epidemic. Although there is no clear relationship between obesity and fruits and vegetables consumption, studies suggest that eating fruits and vegetables could be helpful in preventing childhood obesity. A few school-based interventions targeting youth have been effective at increasing fruits and vegetables intake.^ In Austin, Texas, the Sustainable Food Center delivered the Sprouting Healthy Kids (SHK) program that targeted low socio-economic status children in four intervention middle schools. The SHK program delivered six intervention components. This school-based intervention included: a cafeteria component, in-class lessons, an after-school garden program, a field trip to a local farm, food tasting, and farmers' visits to schools. This study aimed to determine the effects of the SHK intervention in middle school students' preferences, motivation, knowledge, and self-efficacy towards fruits and vegetables intake, as well as the actual fruits and vegetables intake. The study also aimed to determine the effects of exposure to different doses of the SHK intervention on participants' fruits and vegetable intake.^ The SHK was delivered during Spring 2009. A total of 214 students completed the pre-and-posttest surveys measuring self-report fruits and vegetables intake as well as intrapersonal factors. The results showed that the school cafeteria, the food tasting, the after school program, and the farmers' visits had a positive effect on the participants' motivation, knowledge, and self-efficacy towards fruits and vegetables intake. The farmers' visits and the food tasting components increased participants' fruits and vegetables intake. Exposure to two or more intervention components increased participants' fruits and vegetables intake. The statistically significant dose-response effect size was .352, which suggests that each intervention component increased participants' fruits and vegetables consumption this amount. Certain intervention components were more effective than others. Food tasting and farmers visits increased participants fruits and vegetables intake, therefore these components should be offered in an ongoing basis. This study suggests that exposure to multiple intervention components increased behaviors and attitudes towards fruits and vegetables consumption. Findings are consistent that SHK can influence behaviors of middle school students.^

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Transcriptional analysis of liver-specific expression and differential interleukin-6 response of rat kininogen genes

Analyses of rat T1 kininogen gene/chloramphenicol acetyltransferase (T1K/CAT) constructs revealed two regions important for tissue-specific and induced regulation of T1 kininogen.^ Although the T1 kininogen gene is inducible by inflammatory cytokines, a highly homologous K kininogen gene is minimally responsive. Moreover, the basal expression of a KK/CAT construct was 5- to 7-fold higher than that of the analogous T1K/CAT construct. To examine the molecular basis of this differential regulation, a series of promoter swapping experiments was carried out. Our transfection results showed that at least two regions in the K kininogen gene are important for its high basal expression: a distal 19-bp region (C box) constituted a binding site for CCAAT/enhancer binding protein (C/EBP) family proteins and a proximal 66-bp region contained two adjacent binding sites for hepatocyte nuclear factor-3 (HNF-3). The distal HNF-3 binding site from the K kininogen promoter demonstrated a stronger affinity than that from the T1 kininogen promoter. Since C/EBP and HNF-3 are highly enriched in the liver and known to enhance transcription of liver-specific genes, differential binding affinities of these factors accounted for the higher basal expression of the K kininogen gene.^ In contrast to the K kininogen C box, the T1 kininogen C box does not bind C/EBP presumably due to their two-nucleotide divergence. This sequence divergence, however, converts it to a consensus binding sequence for two IL-6-inducible transcription factors--IL-6 response element binding protein and acute-phase response factor. To functionally determine whether C box sequences are important for their differential acute-phase response, T1 and K kininogen C boxes were swapped and analyzed after transfection into Hep3B cells. Our results showed that the T1 kininogen C box is indeed one of the IL-6 response elements in T1 kininogen promoter. Furthermore, its function can be modulated by a 5$\sp\prime$-adjacent C/EBP-binding site (B box) whose mutation significantly reduced the overall induced activity. Moreover, this B box is the target site for binding and transactivation of another IL-6 inducible transcription factor C/EBP$\delta.$ Evolutionary divergence of a few critical nucleotides can either lead to subtle changes in the binding affinities of a given transcription factor or convert a binding sequence for a constitutive factor to a site recognized by an inducible factor. (Abstract shortened by UMI.) ^

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Immune response to hepatitis B vaccination in drug using populations: A systematic review and meta-regression analysis

Hepatitis B virus (HBV) is a significant cause of liver diseases and related complications worldwide. Both injecting and non-injecting drug users are at increased risk of contracting HBV infection. Scientific evidence suggests that drug users have subnormal response to HBV vaccination and the seroprotection rates are lower than that in the general population; potentially due to vaccine factors, host factors, or both. The purpose of this systematic review is to examine the rates of seroprotection following HBV vaccination in drug using populations and to conduct a meta-analysis to identify the factors associated with varying seroprotection rates. Seroprotection is defined as developing an anti-HBs antibody level of ≥ 10 mIU/ml after receiving the HBV vaccine. Original research articles were searched using online databases and reference lists of shortlisted articles. HBV vaccine intervention studies reporting seroprotection rates in drug users and published in English language during or after 1989 were eligible. Out of 235 citations reviewed, 11 studies were included in this review. The reported seroprotection rates ranged from 54.5 – 97.1%. Combination vaccine (HAV and HBV) (Risk ratio 12.91, 95% CI 2.98-55.86, p = 0.003), measurement of anti-HBs with microparticle immunoassay (Risk ratio 3.46, 95% CI 1.11-10.81, p = 0.035) and anti-HBs antibody measurement at 2 months after the last HBV vaccine dose (RR 4.11, 95% CI 1.55-10.89, p = 0.009) were significantly associated with higher seroprotection rates. Although statistically nonsignificant, the variables mean age>30 years, higher prevalence of anti-HBc antibody and anti-HIV antibody in the sample population, and current drug use (not in drug rehabilitation treatment) were strongly associated with decreased seroprotection rates. Proportion of injecting drug users, vaccine dose and accelerated vaccine schedule were not predictors of heterogeneity across studies. Studies examined in this review were significantly heterogeneous (Q = 180.850, p = 0.000) and factors identified should be considered when comparing immune response across studies. The combination vaccine showed promising results; however, its effectiveness compared to standard HBV vaccine needs to be examined systematically. Immune response in DUs can possibly be improved by the use of bivalent vaccines, booster doses, and improving vaccine completion rates through integrated public programs and incentives.^