13 resultados para cognitive studies and clown

em DigitalCommons@The Texas Medical Center


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Latinos have the highest teen birth rate nationally. Cameron County, Texas is primarily Latino (Mexican-American). This mixed-method study (n=43) examines Mexican-American parents of adolescents' beliefs, attitudes and practices regarding communication with their adolescent children about sex. Social Cognitive Theory (SCT) constructs self-efficacy, behavioral determinism, environment, outcome expectations and reciprocal determinism can be influences on frequency and quality of parent-adolescent sex communication.^ This study describes Mexican-American parents' of adolescents recollections of their own experiences associated with learning about sexuality. It also examines the attitudes and practices regarding communication about sex and the self-efficacy and behavioral capability of participants to teach their adolescent children about sex and sexually transmitted infections. ^ Negative childhood experiences (shame, lies and trauma) of the parents in this study played a key role in terms of their desire to communicate more comprehensively about sexuality with their own children than did their parents. While participants' reported low self-efficacy and behavioral capability to communicate with their adolescent children about sex, they reported relatively high frequency and quality of communication, with 75% of participants receiving a high quality score and over 44% reporting frequent communication with their adolescent children about sex. A Chi square analysis and Fisher's Exact Score revealed no association between acculturation status, gender or having a child who has mothered/fathered a baby and the frequency or quality of communication about sex with adolescent children. Study participants also gave specific recommendations for method, content and setting of sex education for their children and themselves. Promotora delivery of information and education in a comfortable, culturally appropriate neighborhood setting, as well as parent –child learning sessions were identified as possible approaches to address improve self-efficacy and behavioral capability of parents communicating with their adolescent children about sex.^ The results of this analysis provide public health practitioners and interested community entities data to identify and develop interventions that use a theoretical, evidence-based framework for culturally appropriate interventions to encourage and equip Mexican-American parents to effectively communicate with their adolescent children about sexuality, and ultimately to address the high rates of teen pregnancy in this U.S.-Mexico border community. ^

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Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

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Is the solution for medical errors medical or cognitive? In this AMIA2001 panel on medical error, we argued that medical error is primarily an issue for cognitive science and engineering, not for medicine, although the knowledge of the practice of medicine is essential for the research and prevention of medical errors. The three panelists presented studies that demonstrate that cognitive research is the foundation for theories of medical errors and interventions of error reductions.

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Tuberous sclerosis complex (TSC) is a multisystem, autosomal dominant disorder affecting approximately 1 in 6000 births. Developmental brain abnormalities cause substantial morbidity and mortality and often lead to neurological disease including epilepsy, cognitive disabilities, and autism. TSC is caused by inactivating mutations in either TSC1 or TSC2, whose protein products are known inhibitors of mTORC1, an important kinase regulating translation and cell growth. Nonetheless, neither the pathophysiology of the neurological manifestations of TSC nor the extent of mTORC1 involvement in the development of these lesions is known. Murine models would greatly advance the study of this debilitating disorder. This thesis will describe the generation and characterization of a novel brain-specific mouse model of TSC, Tsc2flox/ko;hGFAP-Cre. In this model, the Tsc2 gene has been removed from most neurons and glia of the cortex and hippocampus by targeted Cre-mediated deletion in radial glial neuroprogenitor cells. The Tsc2flox/ko;hGFAP-Cre mice fail to thrive beginning postnatal day 8 and die from seizures around 23 days. Further characterization of these mice demonstrated megalencephaly, enlarged neurons, abnormal neuronal migration, altered progenitor pools, hypomyelination, and an astrogliosis. The similarity of these defects to those of TSC patients establishes this mouse as an excellent model for the study of the neuropathology of TSC and testing novel therapies. We further describe the use of this mouse model to assess the therapeutic potential of the macrolide rapamycin, an inhibitor of mTORC1. We demonstrate that rapamycin administered from postnatal day 10 can extend the life of the mutant animals 5 fold. Since TSC is a neurodevelopmental disorder, we also assessed in utero and/or immediate postnatal treatment of the animals with rapamycin. Amazingly, combined in utero and postnatal rapamycin effected a histologic rescue that was almost indistinguishable from control animals, indicating that dysregulation of mTORC1 plays a large role in TSC neuropathology. In spite of the almost complete histologic rescue, behavioral studies demonstrated that combined treatment resulted in poorer learning and memory than postnatal treatment alone. Postnatally-treated animals behaved similarly to treated controls, suggesting that immediate human treatment in the newborn period might provide the most opportune developmental timepoint for rapamycin administration.

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Not enough research efforts on depression have been carried out up to now in Latin America. The knowledge that has resulted from research activities in the United States or Europe offers limited generalizability to other regions of the world, including Latin America. In the Andean highlands of Ecuador, we found very high rates of moderate and severe depressive symptoms, a finding that must be interpreted within its cultural context. Somatic manifestations of depression predominated over cognitive manifestations, and higher education level was protective against depression. These findings call for an appreciation of culturally-specific manifestations of depression and the social factors that influence them. These factors must be further studied in order to give them the deserved priority, allocate resources appropriately, and formulate innovative psychosocial interventions.

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Background: Given that an alarming 1 in 5 children in the USA are at risk of hunger (1 in 3 among black and Latino children), and that 3.9 million households with children are food insecure, it is crucial to understand how household food insecurity (HFI) affects the present and future well-being of our children. Purpose: The objectives of this review article are to: (i) examine the association between HFI and child intellectual, behavioral and psycho-emotional development, controlling for socio-economic indicators; (ii) review the hypothesis that HFI is indeed a mediator of the relationship between poverty and poor child development outcomes; (iii) examine if the potential impact of HFI on caregivers’ mental health well-being mediates the relationship between HFI and child development outcomes. Methods: Pubmed search using the key words “food insecurity children.” For articles to be included they had to: (i) be based on studies measuring HFI using an experience-based scale, (ii) be peer reviewed, and (iii) include child intellectual, behavioral and/or socio-emotional development outcomes. Studies were also selected based on backward and forward Pubmed searches, and from the authors’ files. After reviewing the abstracts based on inclusion criteria a total of 26 studies were selected. Results: HFI represents not only a biological but also a psycho-emotional and developmental challenge to children exposed to it. Children exposed to HFI are more likely to internalize or externalize problems, as compared to children not exposed to HFI. This in turn is likely to translate into poor academic/cognitive performance and intellectual achievement later on in life. A pathway through which HFI may affect child development is possibly mediated by caregivers’ mental health status, especially parental stress and depression. Thus, HFI is likely to foster dysfunctional family environments. Conclusion: Findings indicate that food insecure households may require continued food assistance and psycho-emotional support until they transition to a “stable” food secure situation. This approach will require a much better integration of social policies and access to programs offering food assistance and mental health services to those in need. Findings also fully justify increased access of vulnerable children to programs that promote early in life improved nutrition as well as early psycho-social and cognitive stimulation opportunities.

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This study examines the relationship among psychological resources (generalized resistance resources), care demands (demands for care, competing demands, perception of burden) and cognitive stress in a selected population of primary family caregivers. The study utilizes Antonovsky's Salutogenic Model of Health, specifically the concept of generalized resistance resources (GRRs), to analyze the relative effect of these resources on mediating cognitive stress, controlling for other care demands. The study is based on a sample of 784 eligible caregivers who (1) were relatives, (2) had the main responsibility for care, defined as a primary caregiver, and (3) provided a scaled stress score for the amount of overall care given to the care recipient (family member). The sample was drawn from the 1982 National Long-Term Care Survey (NLTCS) of individuals who assisted a given NLTCS sample person with ADL limitations.^ The study tests the following hypotheses: (a) There will be a negative relationship between generalized resistance resources (GRRs) and cognitive stress controlling for care demands (demands for care, competing demands, and perceptions of burden); (b) of the specific GRRs (material, cognitive, social, cultural-environmental) the social domain will represent the most significant factor predicting a decrease in cognitive stress; and (c) the social domain will be more significant for the female than the male primary family caregiver in decreasing cognitive stress.^ The study found that GRRs had a statistically significant mediating effect on cognitive stress, but the GRRs were a less significant predictor of stress than perception of burden and demands for care. Thus, although the analysis supported the underlying hypothesis, the specific hypothesis regarding GRRs' greater significance in buffering cognitive stress was not supported. Second, the results did not demonstrate the statistical significance or differences among the GRR domains. The hypothesis that the social GRR domain was most significant in mediating stress of family caregivers was not supported. Finally, the results confirmed that there are differences in the importance of social support help in mediating stress based on gender. It was found that gender and social support help were related to cognitive stress and gender had a statistically significant interaction effect with social support help. Implications for clinical practice, public health policy, and research are discussed. ^

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The VirB11 ATPase is an essential component of an Agrobacterium tumefaciens type IV bacterial secretion system that transfers oncogenic nucleoprotein complexes to susceptible plant cells. This dissertation investigates the subcellular localization and homo-oligomeric state of the VirB11 ATPase in order to provide insights about the assembly of the protein as a subunit of this membrane-associated transfer system. Subcellular fractionation studies and quantitative immunoblot analysis demonstrated that $\sim$30% of VirB11 partitioned as soluble protein and $\sim$70% was tightly associated with the bacterial cytoplasmic membrane. No differences were detected in VirB11 subcellular localization and membrane association in the presence or absence of other transport system components. Mutations in virB11 affecting protein function were mapped near the amino terminus, just upstream of a region encoding a Walker 'A' nucleotide-binding site, and within the Walker 'A' motif partitioned almost exclusively with the cytoplasmic membrane, suggesting that an activity associated with nucleotide binding could modulate the affinity of VirB11 for the cytoplasmic membrane. Merodiploid analysis of VirB11 mutant and truncation derivatives provided strong evidence that VirB11 functions as a homo- or heteromultimer and that the C-terminal half of VirB11 contains a protein interaction domain. A combination of biochemical and molecular genetic approaches suggested that VirB11 and the green fluorescence protein (GFP) formed a mixed multimer as demonstrated by immunoprecipitation experiments with anti-GFP antibodies. Second, a hybrid protein composed of VirB11 fused to the N-terminal DNA-binding domain of bacteriophage $\lambda$ cI repressor conferred immunity to $\lambda$ superinfection, demonstrating that VirB11 self-association promotes dimerization of the chimeric repressor. A conserved Walker 'A' motif, though required for VirB11 function in T-complex export, was not necessary for VirB11 self-association. Sequences in both the N- and the C-terminal halves of the protein were found to contribute to self-association of the full length protein. Chemical cross-linking experiments with His$\sb6$ tagged VirB11 suggested that VirB11 probably assembles into a higher order homo-oligomeric complex. ^

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Linkage disequilibrium (LD) is defined as the nonrandom association of alleles at two or more loci in a population and may be a useful tool in a diverse array of applications including disease gene mapping, elucidating the demographic history of populations, and testing hypotheses of human evolution. However, the successful application of LD-based approaches to pertinent genetic questions is hampered by a lack of understanding about the forces that mediate the genome-wide distribution of LD within and between human populations. Delineating the genomic patterns of LD is a complex task that will require interdisciplinary research that transcends traditional scientific boundaries. The research presented in this dissertation is predicated upon the need for interdisciplinary studies and both theoretical and experimental projects were pursued. In the theoretical studies, I have investigated the effect of genotyping errors and SNP identification strategies on estimates of LD. The primary importance of these two chapters is that they provide important insights and guidance for the design of future empirical LD studies. Furthermore, I analyzed the allele frequency distribution of 26,530 single nucleotide polymorphisms (SNPs) in three populations and generated the first-generation natural selection map of the human genome, which will be an important resource for explaining and understanding genomic patterns of LD. Finally, in the experimental study, I describe a novel and simple, low-cost, and high-throughput SNP genotyping method. The theoretical analyses and experimental tools developed in this dissertation will facilitate a more complete understanding of patterns of LD in human populations. ^

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Identifying and characterizing the genes responsible for inherited human diseases will ultimately lead to a more holistic understanding of disease pathogenesis, catalyze new diagnostic and treatment modalities, and provide insights into basic biological processes. This dissertation presents research aimed at delineating the genetic and molecular basis of human diseases through epigenetic and functional studies and can be divided into two independent areas of research. The first area of research describes the development of two high-throughput melting curve based methods to assay DNA methylation, referred to as McMSP and McCOBRA. The goal of this project was to develop DNA methylation methods that can be used to rapidly determine the DNA methylation status at a specific locus in a large number of samples. McMSP and McCOBRA provide several advantages over existing methods, as they are simple, accurate, robust, and high-throughput making them applicable to large-scale DNA methylation studies. McMSP and McCOBRA were then used in an epigenetic study of the complex disease Ankylosing spondylitis (AS). Specifically, I tested the hypothesis that aberrant patterns of DNA methylation in five AS candidate genes contribute to disease susceptibility. While no statistically significant methylation differences were observed between cases and controls, this is the first study to investigate the hypothesis that epigenetic variation contributes to AS susceptibility and therefore provides the conceptual framework for future studies. ^ In the second area of research, I performed experiments to better delimit the function of aryl hydrocarbon receptor-interacting protein-like 1 (AIPL1), which when mutated causes various forms of inherited blindness such as Leber congenital amaurosis. A yeast two-hybrid screen was performed to identify putative AIPL1-interacting proteins. After screening 2 × 106 bovine retinal cDNA library clones, 6 unique putative AIPL1-interacting proteins were identified. While these 6 AIPL1 protein-protein interactions must be confirmed, their identification is an important step in understanding the functional role of AIPL1 within the retina and will provide insight into the molecular mechanisms underlying inherited blindness. ^

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Objective. The main aim of our study is to assess the effect of hypertension on the decline in cognitive impairment among Alzheimer’s patients. Methods. We analyzed the data of AD patients enrolled in Baylor ADMDC in a prospective study design. We divided AD patients into two groups based on the definition of hypertension. We described a decline in cognitive impairment as a change of 5 points in mini-mental state examination score (MMSE) from the baseline visit. Results. Independent of covariates, AD patients with hypertension did not exhibit a significant decline in cognitive impairment after adjustment of covariates, age, race and education (Hazard Ratio (HR) = 1.07, p value 0.58, 95% confidence interval 0.84-1.39) than AD patients without hypertension. In addition, AD patients with hypertension did not experience decline in cognitive impairment sooner than AD patients without hypertension. (P value 0.83). Conclusions . Hypertension is not associated with cognitive impairment over time among patients with Alzheimer’s disease enrolled in Baylor ADMDC after other potential confounders were taken into account. These findings should not be interpreted as a basis for discouraging appropriate medical treatment of hypertension in AD patients. Greater efforts should be made to improve the recognition of hypertension as a modifiable risk factor for decline in cognitive impairment in AD population. ^

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Background. This study was designed to evaluate the effects of the Young Leaders for Healthy Change program, an internet-delivered program in the school setting that emphasized health advocacy skills-development, on nutrition and physical activity behaviors among older adolescents (13–18 years). The program consisted of online curricular modules, training modules, social media, peer and parental support, and a community service project. Module content was developed based on Social Cognitive Theory and known determinants of behavior for older adolescents. ^ Methods. Of the 283 students who participated in the fall 2011 YL program, 38 students participated in at least ten of the 12 weeks and were eligible for this study. This study used a single group-only pretest/posttest evaluation design. Participants were 68% female, 58% white/Caucasian, 74% 10th or 11th graders, and 89% mostly A and/or B students. The primary behavioral outcomes for this analysis were participation in 60-minutes of physical activity per day, 20-minutes of vigorous- or moderate- intensity physical activity (MVPA) participation per day, television and computer time, fruit and vegetable (FV) intake, sugar-sweetened beverage intake, and consumption of breakfast, home-cooked meals, and fast food. Other outcomes included knowledge, beliefs, and attitudes related to healthy eating, physical activity, and advocacy skills. ^ Findings. Among the 38 participants, no significant changes in any variables were observed. However, among those who did not previously meet behavioral goals there was an 89% increase in students who participated in more than 20 minutes of MVPA per day and a 58% increase in students who ate home-cooked meals 5–7 days per week. The majority of participants met program goals related to knowledge, beliefs, and attitudes prior to the start of the program. Participants reported either maintaining or improving to the goal at posttest for all items except FV intake knowledge, taste and affordability of healthy foods, interest in teaching others about being healthy, and ease of finding ways to advocate in the community. ^ Conclusions. The results of this evaluation indicated that promoting healthy behaviors requires different strategies than maintaining healthy behaviors among high school students. In the school setting, programs need to target the promotion and maintenance of health behaviors to engage all students who participate in the program as part of a class or club activity. Tailoring the program using screening and modifying strategies to meet the needs of all students may increase the potential reach of the program. The Transtheoretical Model may provide information on how to develop a tailored program. Additional research on how to utilize the constructs of TTM effectively among high school students needs to be conducted. Further evaluation studies should employ a more expansive evaluation to assess the long-term effectiveness of health advocacy programming.^

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Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.