Translating Research into Practice: HEADS UP and K-12 Science Inspiring Health and Careers in Youth

Introduction: HEADS UP {Health Education And Discovering Science while Unlocking Potential} aims to improve health literacy and increase student interest in health science careers by providing cutting-edge content from world-renowned researchers in the Texas Medical Center and beyond to the K-12 school community. [See PDF for complete abstract]

Application of Cognitive Engineering Principles to the Redesign of a Dichotomous Identification Key for Parasitology

Dichotomous identification keys are used throughout biology for identification of plants, insects, and parasites. However, correct use of identification keys can be difficult as they are not usually intended for novice users who may not be familiar with the terminology used or with the morphology of the organism being identified. Therefore, we applied cognitive engineering principles to redesign a parasitology identification key for the Internet. We addressed issues of visual clutter and spatial distance by displaying a single question couplet at a time and by switching to the appropriate next couplet after the user made a choice. Our analysis of the original paper-based key versus the Web-based approach found that of 26 applicable cognitive engineering principles, the paper key did not meet 4 (15%) and partially met 11 (42%). In contrast, the redesigned key met 100% of 32 applicable cognitive engineering principles.

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.

Detection of nonrandom association of alleles from the distribution of the number of heterozygous loci in a sample.

The distribution of the number of heterozygous loci in two randomly chosen gametes or in a random diploid zygote provides information regarding the nonrandom association of alleles among different genetic loci. Two alternative statistics may be employed for detection of nonrandom association of genes of different loci when observations are made on these distributions: observed variance of the number of heterozygous loci (s2k) and a goodness-of-fit criterion (X2) to contrast the observed distribution with that expected under the hypothesis of random association of genes. It is shown, by simulation, that s2k is statistically more efficient than X2 to detect a given extent of nonrandom association. Asymptotic normality of s2k is justified, and X2 is shown to follow a chi-square (chi 2) distribution with partial loss of degrees of freedom arising because of estimation of parameters from the marginal gene frequency data. Whenever direct evaluations of linkage disequilibrium values are possible, tests based on maximum likelihood estimators of linkage disequilibria require a smaller sample size (number of zygotes or gametes) to detect a given level of nonrandom association in comparison with that required if such tests are conducted on the basis of s2k. Summarization of multilocus genotype (or haplotype) data, into the different number of heterozygous loci classes, thus, amounts to appreciable loss of information.

Polymorphisms, linkage and mapping of four enzyme loci in the fish genus Xiphophorus (Poeciliidae).

Electrophoretic variants at four additional enzyme loci--two esterases (Est-2, Est-3), retinal lactate dehydrogenase (LDH-1) and mannose phosphate isomerase (MPI)--among three species and four subspecies of fish of the genus Xiphophorus were observed. Electrophoretic patterns in F1 hybrid heterozygotes confirmed the monomeric structures of MPI and the esterase and the tetrametric structure of LDH in these fishes. Variant alleles of all four loci displayed normal Mendelian segregation in backcross and F2 hybrids. Recombination data from backcross hybrids mapped with Haldane's mapping function indicate the four loci to be linked as Est-2--0.43--Est3--0.26--LDH-1--0.19--MPI. Significant interference was detected and apparently concentrated in the Est-3 to MPI region. No significant sex-specific differences in recombination were observed. This group (designated linkage group II) was shown to assort independently from the three loci of linkage group I (adenosine deaminase, glucose-6-phosphate dehydrogenase, and 6-phosphogluconate dehydrogenase) and from glyceraldehyde-3-phosphate dehydrogenase and two isocitrate dehydrogenase loci. Evidence for conservation of the linkage group, at least in part, in other vertebrate species is presented.

Encouraging adolescents toward mental health careers via website biographies.

This project designed, developed, implemented and is currently evaluating the effectiveness of an interactive, multi-media website designed to encourage adolescents to consider careers in mental health. This Web-based learning environment features biographies of mental health scientists. Evaluation is conducted in a systematic, structured way using cognitive achievement, usability (ease of use), and affective scales (e.g., fun to use) as outcome measures

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Parentage analysis with genetic markers in natural populations. I. The expected proportion of offspring with unambiguous paternity.

Recent studies indicate that polymorphic genetic markers are potentially helpful in resolving genealogical relationships among individuals in a natural population. Genetic data provide opportunities for paternity exclusion when genotypic incompatibilities are observed among individuals, and the present investigation examines the resolving power of genetic markers in unambiguous positive determination of paternity. Under the assumption that the mother for each offspring in a population is unambiguously known, an analytical expression for the fraction of males excluded from paternity is derived for the case where males and females may be derived from two different gene pools. This theoretical formulation can also be used to predict the fraction of births for each of which all but one male can be excluded from paternity. We show that even when the average probability of exclusion approaches unity, a substantial fraction of births yield equivocal mother-father-offspring determinations. The number of loci needed to increase the frequency of unambiguous determinations to a high level is beyond the scope of current electrophoretic studies in most species. Applications of this theory to electrophoretic data on Chamaelirium luteum (L.) shows that in 2255 offspring derived from 273 males and 70 females, only 57 triplets could be unequivocally determined with eight polymorphic protein loci, even though the average combined exclusionary power of these loci was 73%. The distribution of potentially compatible male parents, based on multilocus genotypes, was reasonably well predicted from the allele frequency data available for these loci. We demonstrate that genetic paternity analysis in natural populations cannot be reliably based on exclusionary principles alone. In order to measure the reproductive contributions of individuals in natural populations, more elaborate likelihood principles must be deployed.

NEW TARGET GENES FOR TUMOR SUPPRESSORS p53 AND p73 IN REGENERATING LIVER

The p53-family of proteins regulates expression of target genes during tissue development and differentiation. Within the p53-family, p53 and p73 have hepatic-specific functions in development and tumor suppression. Despite a growing list of p53/p73 target genes, very few of these have been studied in vivo, and the knowledge regarding functions of p53 and p73 in normal tissues remains limited. p53+/-p73+/- mice develop hepatocellular carcinoma (HCC), whereas overexpression of p53 in human HCC leads to tumor regression. However, the mechanism of p53/p73 function in liver remains poorly characterized. Here, the model of mouse liver regeneration is used to identify new target genes for p53/p73 in normal quiescent vs. proliferating cells. In response to surgical removal of ~2/3 of liver mass (partial hepatectomy, PH), the remaining hepatocytes exit G0 of cell cycle and undergo proliferation to reestablish liver mass. The hypothesis tested in this work is that p53/p73 functions in cell cycle arrest, apoptosis and senescence are repressed during liver regeneration, and reactivated at the end of the regenerative response. Chromatin immunoprecipitation (ChIP), with a p73-antibody, was used to probe arrayed genomic sequences (ChIP-chip) and uncover 158 potential targets of p73-regulation in normal liver. Global microarray analysis of mRNA levels, at T=0-48h following PH, revealed sets of genes that change expression during regeneration. Eighteen p73-bound genes changed expression after PH. Four of these genes, Foxo3, Jak1, Pea15, and Tuba1 have p53 response elements (p53REs), identified in silico within the upstream regulatory region. Forkhead transcription factor Foxo3 is the most responsive gene among transcription factors with altered expression during regenerative, cellular proliferation. p53 and p73 bind a Foxo3 p53RE and maintain active expression in quiescent liver. During liver regeneration, binding of p53 and p73, recruitment of acetyltransferase p300, and an active chromatin structure of Foxo3 are disrupted, alongside loss of Foxo3 expression. These parameters of Foxo3 regulation are reestablished at completion of liver growth and regeneration, supporting a temporary suspension of p53 and p73 regulatory functions in normal cells during tissue regeneration.

Regulation of survivin gene expression in the human endometrium and endometrial cancer

In the United States, endometrial cancer is the leading cancer of the female reproductive tract. There are 40,100 new cases and 7,470 deaths from endometrial cancer estimated for 2008 (47). The average five year survival rate for endometrial cancer is 84% however, this figure is substantially lower in patients diagnosed with late stage, advanced disease and much higher for patients diagnosed in early stage disease (47). Endometrial cancer (EC) has been associated with several risk factors including obesity, diabetes, hypertension, previously documented occurrence of hereditary non-polyposis colorectal cancer (HNPCC), and heightened exposure to estrogen (25). As of yet, there has not been a dependable molecular predictor of endometrial cancer occurrence in women with these predisposing factors. The goal of our lab is to identify genes that are aberrantly expressed in EC and may serve as molecular biomarkers of EC progression. One candidate protein that we are exploring as a biomarker of EC progression is the cell survival protein survivin.

Randomized comparisons among health informatics students identify hypertutorial features as improving web-based instruction.

Hypertutorials optimize five features - presentation, learner control, practice, feedback, and elaborative learning resources. Previous research showed graduate students significantly and overwhelmingly preferred Web-based hypertutorials to conventional "Book-on-the-Web" statistics or research design lessons. The current report shows that the source of hypertutorials' superiority in student evaluations of instruction lies in their hypertutorial features. Randomized comparisons between the two methodologies were conducted in two successive iterations of a graduate level health informatics research design and evaluation course. The two versions contained the same text and graphics, but differed in the presence or absence of hypertutorial features: Elaborative learning resources, practice, feedback, and amount of learner control. Students gave high evaluations to both Web-based methodologies, but consistently rated the hypertutorial lessons as superior. Significant differences localized in the hypertutorial subscale that measured student responses to hypertutorial features.