Learning reward timing in cortex through reward dependent expression of synaptic plasticity.

The ability to represent time is an essential component of cognition but its neural basis is unknown. Although extensively studied both behaviorally and electrophysiologically, a general theoretical framework describing the elementary neural mechanisms used by the brain to learn temporal representations is lacking. It is commonly believed that the underlying cellular mechanisms reside in high order cortical regions but recent studies show sustained neural activity in primary sensory cortices that can represent the timing of expected reward. Here, we show that local cortical networks can learn temporal representations through a simple framework predicated on reward dependent expression of synaptic plasticity. We assert that temporal representations are stored in the lateral synaptic connections between neurons and demonstrate that reward-modulated plasticity is sufficient to learn these representations. We implement our model numerically to explain reward-time learning in the primary visual cortex (V1), demonstrate experimental support, and suggest additional experimentally verifiable predictions.

Insights into transcription enhancer factor 1 (TEF-1) activity from the solution structure of the TEA domain.

Transcription enhancer factor 1 is essential for cardiac, skeletal, and smooth muscle development and uses its N-terminal TEA domain (TEAD) to bind M-CAT elements. Here, we present the first structure of TEAD and show that it is a three-helix bundle with a homeodomain fold. Structural data reveal how TEAD binds DNA. Using structure-function correlations, we find that the L1 loop is essential for cooperative loading of TEAD molecules on to tandemly duplicated M-CAT sites. Furthermore, using a microarray chip-based assay, we establish that known binding sites of the full-length protein are only a subset of DNA elements recognized by TEAD. Our results provide a model for understanding the regulation of genome-wide gene expression during development by TEA/ATTS family of transcription factors.

Altered transmission of HOX and apoptotic SNPs identify a potential common pathway for clubfoot.

Clubfoot is a common birth defect that affects 135,000 newborns each year worldwide. It is characterized by equinus deformity of one or both feet and hypoplastic calf muscles. Despite numerous study approaches, the cause(s) remains poorly understood although a multifactorial etiology is generally accepted. We considered the HOXA and HOXD gene clusters and insulin-like growth factor binding protein 3 (IGFBP3) as candidate genes because of their important roles in limb and muscle morphogenesis. Twenty SNPs from the HOXA and HOXD gene clusters and 12 SNPs in IGFBP3 were genotyped in a sample composed of non-Hispanic white and Hispanic multiplex and simplex families (discovery samples) and a second sample of non-Hispanic white simplex trios (validation sample). Four SNPs (rs6668, rs2428431, rs3801776, and rs3779456) in the HOXA cluster demonstrated altered transmission in the discovery sample, but only rs3801776, located in the HOXA basal promoter region, showed altered transmission in both the discovery and validation samples (P = 0.004 and 0.028). Interestingly, HOXA9 is expressed in muscle during development. An SNP in IGFBP3, rs13223993, also showed altered transmission (P = 0.003) in the discovery sample. Gene-gene interactions were identified between variants in HOXA, HOXD, and IGFBP3 and with previously associated SNPs in mitochondrial-mediated apoptotic genes. The most significant interactions were found between CASP3 SNPS and variants in HOXA, HOXD, and IGFBP3. These results suggest a biologic model for clubfoot in which perturbation of HOX and apoptotic genes together affect muscle and limb development, which may cause the downstream failure of limb rotation into a plantar grade position.

Genetic and hormonal factors modulate spreading depression and transient hemiparesis in mouse models of familial hemiplegic migraine type 1.

Familial hemiplegic migraine type 1 (FHM1) is an autosomal dominant subtype of migraine with aura that is associated with hemiparesis. As with other types of migraine, it affects women more frequently than men. FHM1 is caused by mutations in the CACNA1A gene, which encodes the alpha1A subunit of Cav2.1 channels; the R192Q mutation in CACNA1A causes a mild form of FHM1, whereas the S218L mutation causes a severe, often lethal phenotype. Spreading depression (SD), a slowly propagating neuronal and glial cell depolarization that leads to depression of neuronal activity, is the most likely cause of migraine aura. Here, we have shown that transgenic mice expressing R192Q or S218L FHM1 mutations have increased SD frequency and propagation speed; enhanced corticostriatal propagation; and, similar to the human FHM1 phenotype, more severe and prolonged post-SD neurological deficits. The susceptibility to SD and neurological deficits is affected by allele dosage and is higher in S218L than R192Q mutants. Further, female S218L and R192Q mutant mice were more susceptible to SD and neurological deficits than males. This sex difference was abrogated by ovariectomy and senescence and was partially restored by estrogen replacement, implicating ovarian hormones in the observed sex differences in humans with FHM1. These findings demonstrate that genetic and hormonal factors modulate susceptibility to SD and neurological deficits in FHM1 mutant mice, providing a potential mechanism for the phenotypic diversity of human migraine and aura.

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

Multiple independent genetic factors at NOS1AP modulate the QT interval in a multi-ethnic population.

Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD); thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072). The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005) and Black (P = 3.6 x 10(-5)) participants, with the same direction of effect in Hispanics (P = 0.17), and further showed a significant SNP x sex-interaction (P = 0.03). A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01), with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC) and Cardiovascular Health Study (CHS) cohorts, we validated both the second locus at rs16856785 (P = 7.63 x 10(-8)), as well as the sex-interaction with rs16847548 (P = 8.68 x 10(-6)). These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval.

EFFECTS OF INFORMATION DISPLAY ON THE CONSTRUCTION OF CLINICIAN MENTAL MODELS

Objective: To determine how a clinician’s background knowledge, their tasks, and displays of information interact to affect the clinician’s mental model. Design: Repeated Measure Nested Experimental Design Population, Sample, Setting: Populations were gastrointestinal/internal medicine physicians and nurses within the greater Houston area. A purposeful sample of 24 physicians and 24 nurses were studied in 2003. Methods: Subjects were randomized to two different displays of two different mock medical records; one that contained highlighted patient information and one that contained non-highlighted patient information. They were asked to read and summarize their understanding of the patients aloud. Propositional analysis was used to understand their comprehension of the patients. Findings: Different mental models were found between physicians and nurses given the same display of information. The information they shared was very minor compared to the variance in their mental models. There was additionally more variance within the nursing mental models than the physician mental models given different displays of the same information. Statistically, there was no interaction effect between the display of information and clinician type. Only clinician type could account for the differences in the clinician comprehension and thus their mental models of the cases. Conclusion: The factors that may explain the variance within and between the clinician models are clinician type, and only in the nursing group, the use of highlighting.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

BTG/TOB factors impact deadenylases.

BTG/TOB factors are a family of antiproliferative proteins whose expression is altered in numerous cancers. They have been implicated in cell differentiation, development and apoptosis. Although proposed to affect transcriptional regulation, these factors interact with CAF1, a subunit of the main eukaryotic deadenylase, and with poly(A)-binding-proteins, strongly suggesting a role in post-transcriptional regulation of gene expression. The recent determination of the structures of BTG2, TOB1 N-terminal domain (TOB1N138) and TOB1N138-CAF1 complexes support a role for BTG/TOB proteins in mRNA deadenylation, a function corroborated by recently published functional characterizations. We highlight molecular mechanisms by which BTG/TOB proteins influence deadenylation and discuss the need for a better understanding of BTG/TOB physiological functions.

A prospective cohort study evaluating the state of medical readiness in the United States Air Force and risk factors to improve the medical readiness posture

A cohort of 418 United States Air Force (USAF) personnel from over 15 different bases deployed to Morocco in 1994. This was the first study of its kind and was designed with two primary goals: to determine if the USAF was medically prepared to deploy with its changing mission in the new world order, and to evaluate factors that might improve or degrade USAF medical readiness. The mean length of deployment was 21 days. The cohort was 95% male, 86% enlisted, 65% married, and 78% white.^ This study shows major deficiencies indicating the USAF medical readiness posture has not fully responded to meet its new mission requirements. Lack of required logistical items (e.g., mosquito nets, rainboots, DEET insecticide cream, etc.) revealed a low state of preparedness. The most notable deficiency was that 82.5% (95% CI = 78.4, 85.9) did not have permethrin pretreated mosquito nets and 81.0% (95% CI = 76.8, 84.6) lacked mosquito net poles. Additionally, 18% were deficient on vaccinations and 36% had not received a tuberculin skin test. Excluding injections, the overall compliance for preventive medicine requirements had a mean frequency of only 50.6% (95% CI = 45.36, 55.90).^ Several factors had a positive impact on compliance with logistical requirements. The most prominent was "receiving a medical intelligence briefing" from the USAF Public Health. After adjustment for mobility and age, individuals who underwent a briefing were 17.2 (95% CI = 4.37, 67.99) times more likely to have received an immunoglobulin shot and 4.2 (95% CI = 1.84, 9.45) times more likely to start their antimalarial prophylaxsis at the proper time. "Personnel on mobility" had the second strongest positive effect on medical readiness. When mobility and briefing were included in models, "personnel on mobility" were 2.6 (95% CI = 1.19, 5.53) times as likely to have DEET insecticide and 2.2 (95% CI = 1.16, 4.16) times as likely to have had a TB skin test.^ Five recommendations to improve the medical readiness of the USAF were outlined: upgrade base level logistical support, improve medical intelligence messages, include medical requirements on travel orders, place more personnel on mobility or only deploy personnel on mobility, and conduct research dedicated to capitalize on the powerful effect from predeployment briefings.^ Since this is the first study of its kind, more studies should be performed in different geographic theaters to assess medical readiness and establish acceptable compliance levels for the USAF. ^

A study of the relationship between physical activity and cardiovascular fitness and coronary heart disease risk factors in female adolescents

The association of measures of physical activity with coronary heart disease (CHD) risk factors in children, especially those for atherosclerosis, is unknown. The purpose of this study was to determine the association of physical activity and cardiovascular fitness with blood lipids and lipoproteins in pre-adolescent and adolescent girls.^ The study population was comprised of 131 girls aged 9 to 16 years who participated in the Children's Nutrition Research Center's Adolescent Study. The dependent variables, blood lipids and lipoproteins, were measured by standard techniques. The independent variables were physical activity measured as the difference between total energy expenditure (TEE) and basal metabolic rate (BMR), and cardiovascular fitness, VO$\rm\sb{2max}$(ml/min/kg). TEE was measured by the doubly-labeled water (DLW) method, and BMR by whole-room calorimetry. Cardiovascular fitness, VO$\rm\sb{2max}$(ml/min/kg), was measured on a motorized treadmill. The potential confounding variables were sexual maturation (Tanner breast stage), ethnic group, body fat percent, and dietary variables. A systematic strategy for data analysis was used to isolate the effects of physical activity and cardiovascular fitness on blood lipids, beginning with assessment of confounding and interaction. Next, from regression models predicting each blood lipid and controlling for covariables, hypotheses were evaluated by the direction and value of the coefficients for physical activity and cardiovascular fitness.^ The main result was that cardiovascular fitness appeared to be more strongly associated with blood lipids than physical activity. An interaction between cardiovascular fitness and sexual maturation indicated that the effect of cardiovascular fitness on most blood lipids was dependent on the stage of sexual maturation.^ A difference of 760 kcal/d physical activity (which represents the difference between the 25th and 75th percentile of physical activity) was associated with negligible differences in blood lipids. In contrast, a difference in 10 ml/min/kg of VO$\rm\sb{2max}$ or cardiovascular fitness (which represents the difference between the 25th and 75th percentile in cardiovascular fitness) in the early stages of sexual maturation was associated with an average positive difference of 15 mg/100 ml ApoA-1 and 10 mg/100 ml HDL-C. ^

Nonviolent factors: Variables associated with ethnic violence, and factors which are associated with nonviolent response to grievances toward members of other ethnic groups

Ethnic violence appears to be the major source of violence in the world. Ethnic hostilities are potentially all-pervasive because most countries in the world are multi-ethnic. Public health's focus on violence documents its increasing role in this issue.^ The present study is based on a secondary analysis of a dataset of responses by 272 individuals from four ethnic groups (Anglo, African, Mexican, and Vietnamese Americans) who answered questions regarding variables related to ethnic violence from a general questionnaire which was distributed to ethnically diverse purposive, nonprobability, self-selected groups of individuals in Houston, Texas, in 1993.^ One goal was psychometric: learning about issues in analysis of datasets with modest numbers, comparison of two approaches to dealing with missing observations not missing at random (conducting analysis on two datasets), transformation analysis of continuous variables for logistic regression, and logistic regression diagnostics.^ Regarding the psychometric goal, it was concluded that measurement model analysis was not possible with a relatively small dataset with nonnormal variables, such as Likert-scaled variables; therefore, exploratory factor analysis was used. The two approaches to dealing with missing values resulted in comparable findings. Transformation analysis suggested that the continuous variables were in the correct scale, and diagnostics that the model fit was adequate.^ The substantive portion of the analysis included the testing of four hypotheses. Hypothesis One proposed that attitudes/efficacy regarding alternative approaches to resolving grievances from the general questionnaire represented underlying factors: nonpunitive social norms and strategies for addressing grievances--using the political system, organizing protests, using the system to punish offenders, and personal mediation. Evidence was found to support all but one factor, nonpunitive social norms.^ Hypothesis Two proposed that the factor variables and the other independent variables--jail, grievance, male, young, and membership in a particular ethnic group--were associated with (non)violence. Jail, grievance, and not using the political system to address grievances were associated with a greater likelihood of intergroup violence.^ No evidence was found to support Hypotheses Three and Four, which proposed that grievance and ethnic group membership would interact with other variables (i.e., age, gender, etc.) to produce variant levels of subgroup (non)violence.^ The generalizability of the results of this study are constrained by the purposive self-selected nature of the sample and small sample size (n = 272).^ Suggestions for future research include incorporating other possible variables or factors predictive of intergroup violence in models of the kind tested here, and the development and evaluation of interventions that promote electoral and nonelectoral political participation as means of reducing interethnic conflict. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Crossing the border for dental care: Factors related to dental health among the south Texas border region

Objectives. The purpose of this thesis is to understand the underlying socioeconomic characteristics affecting dental insurance coverage, yearly dental visits, and factors related to visiting a dentist in Mexico among border region residents. Methods. Using data from the Border Epidemiological Study of Aging, dental utilization in the previous 12 months, dental visits to Mexico, and dental insurance (proxy) were calculated utilizing logistic regression. Three different models were utilized for the dependent variables adjusting for diverse socioeconomic characteristics such as gender, age, marital status, income, education, years of residence in the United States (for immigrants), English proficiency, general health status, employment and dental insurance. Results. After adjustment, diverse variables were significant for the three different models calculated. Conclusion. Although the Mexican health market constitutes a viable option for dental services for border residents, dental insurance and dental yearly visits were lower in this region when compared to national averages. ^

Gender associated risk factors of aortic aneurysms and dissections

Objectives. Predict who will develop a dissection. To create male and female prediction models using the risk factors: age, ethnicity, hypertension, high cholesterol, smoking, alcohol use, diabetes, heart attack, congestive heart failure, congenital and non-congenital heart disease, Marfan syndrome, and bicuspid aortic valve. ^ Methods. Using 572 patients diagnosed with aortic aneurysms, a model was developed for each of males and females using 80% of the data and then verified using the remaining 20% of the data. ^ Results. The male model predicted the probability of a male in having a dissection (p=0.076) and the female model predicted the probability of a female in having a dissection (p=0.054). The validation models did not support the choice of the developmental models. ^ Conclusions. The best models obtained suggested that those who are at a greater risk of having a dissection are males with non-congenital heart disease and who drink alcohol, and females with non-congenital heart disease and bicuspid aortic valve.^