933 resultados para causal chain analysis


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Degenerate oligonucleotide primers derived from conserved cysteine protease sequences were used in the reverse transcription polymerase chain reaction to amplify seven different cysteine protease cDNA clones, Fcp1-7, from RNA isolated from adult Fasciola hepatica. Five of the amplified F. hepatica sequences showed homology to the cathepsin L type and two were more related to the cathepsin B type. Southern blot analysis suggests that some members of this protease gene family are present in multiple copies. Northern blot analysis revealed differences in the levels of steady state mRNA expression for some of these proteases. The 5' and the 3' regions of Fcp1 were amplified using the rapid amplification of cDNA ends PCR protocol (RACE-PCR) and an additional clone was obtained by screening a lambda gt10 cDNA library using Fcp1 as a probe. The Fcp1 cDNA fragment was also subcloned in the expression vector pGEX and expressed as a glutathione-S-transferase (GST) fusion protein in Escherichia coli. Antibodies, raised in rabbits against the GST:Fcp1 fusion protein, were used in western blot analysis to examine expression in different life-cycle stages of F. hepatica. In extracts from adult and immature parasites, the immune serum recognised predominantly two proteins of 30 kDa and 38 kDa. In other parasite stages, proteins of different molecular weight were recognised by the anti-GST:Fcp1 antiserum, indicating stage-specific gene expression or processing of Fcp1. In gelatine substrate gel analysis, strong proteolytic activity could be detected at 30 kDa, but not at 38 kDa, suggesting that the 30 kDa protein represents the mature enzyme and the 38 kDa protein the proenzyme.

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INTRODUCTION Although hepatitis C virus (HCV) screening is recommended for all HIV-infected patients initiating antiretroviral therapy, data on epidemiologic characteristics of HCV infection in resource-limited settings are scarce. METHODS We searched PubMed and EMBASE for studies assessing the prevalence of HCV infection among HIV-infected individuals in Africa and extracted data on laboratory methods used. Prevalence estimates from individual studies were combined for each country using random-effects meta-analysis. The importance of study design, population and setting as well as type of test (anti-HCV antibody tests and polymerase chain reactions) was examined with meta-regression. RESULTS Three randomized controlled trials, 28 cohort studies and 121 cross-sectional analyses with 108,180 HIV-infected individuals from 35 countries were included. The majority of data came from outpatient populations (55%), followed by blood donors (15%) and pregnant women (14%). Based on estimates from 159 study populations, anti-HCV positivity prevalence ranged between 3.3% (95% confidence interval (CI) 1.8-4.7) in Southern Africa and 42.3% (95% CI 4.1-80.5) in North Africa. Study design, type of setting and age distribution did not influence this prevalence significantly. The prevalence of replicating HCV infection, estimated from data of 29 cohorts, was 2.0% (95% CI 1.5-2.6). Ten studies from nine countries reported the HCV genotype of 74 samples, 53% were genotype 1, 24% genotype 2, 14% genotype 4 and 9% genotypes 3, 5 or 6. CONCLUSIONS The prevalence of anti-HCV antibodies is high in HIV-infected patients in Africa, but replicating HCV infection is rare and varies widely across countries.

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Few studies have investigated causal pathways linking psychosocial factors to each other and to screening mammography. Conflicting hypotheses exist in the theoretic literature regarding the role and importance of subjective norms, a person's perceived social pressure to perform the behavior and his/her motivation to comply. The Theory of Reasoned Action (TRA) hypothesizes that subjective norms directly affect intention; while the Transtheoretical Model (TTM) hypothesizes that attitudes mediate the influence of subjective norms on stage of change. No one has examined which hypothesis best predicts the effect of subjective norms on mammography intention and stage of change. Two statistical methods are available for testing mediation, sequential regression analysis (SRA) and latent variable structural equation modeling (LVSEM); however, software to apply LVSEM to dichotomous variables like intention has only recently become available. No one has compared the methods to determine whether or not they yield similar results for dichotomous variables. ^ Study objectives were to: (1) determine whether the effect of subjective norms on mammography intention and stage of change are mediated by pros and cons; and (2) compare mediation results from the SRA and LVSEM approaches when the outcome is dichotomous. We conducted a secondary analysis of data from a national sample of women veterans enrolled in Project H.O.M.E. (H&barbelow;ealthy O&barbelow;utlook on the M&barbelow;ammography E&barbelow;xperience), a behavioral intervention trial. ^ Results showed that the TTM model described the causal pathways better than the TRA one; however, we found support for only one of the TTM causal mechanisms. Cons was the sole mediator. The mediated effect of subjective norms on intention and stage of change by cons was very small. These findings suggest that interventionists focus their efforts on reducing negative attitudes toward mammography when resources are limited. ^ Both the SRA and LVSEM methods provided evidence for complete mediation, and the direction, magnitude, and standard errors of the parameter estimates were very similar. Because SRA parameter estimates were not biased toward the null, we can probably assume negligible measurement error in the independent and mediator variables. Simulation studies are needed to further our understanding of how these two methods perform under different data conditions. ^

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Dynein light chain 1 (DLC1) is a highly conserved and ubiquitously expressed protein which might have critical cellular function as total loss of DLC1 caused Drosophila embryonic death. Despite many proteins and RNAs interaction with it identified, DLC1's function(s) and regulation are largely unknown. Recently, DLC1 was identified as a physiological substrate of P21-activate kinase 1(Pak1) kinase from a human mammary cDNA library in a yeast-2-hybridization screening assay. Studies in primary human tumors and cell culture implicated that DLC1 could promote mammary cancerous phenotypes, and more importantly, Ser88 phosphorylation of DLC1by Pak1 kinase was found to be essential for DLC1's tumorigenic activities. Based on the above tissue culture studies, we hypothesized that Ser88 phosphorylation regulates DLC1. ^ To test this hypothesis, we generated two transgenic mouse models: MMTV-DLC1 and MMTV-DLC1-S88A mice with mammary specific expression of the DLC1 and DLC1-S88A cDNAs. Both of the transgenic mice mammary glands showed rare tumor incidence which indicated DLC1 alone may not be sufficient for tumorigenesis in vivo. However, these mice showed a significant alteration of mammary development. Mammary glands from the MMTV-DLC1 mice had hyperbranching and alveolar hyperplasia, with elevated cell proliferation. Intriguingly, these phenotypes were not seen in the mammary glands from the MMTV-S88A mice. Furthermore, while MMTV-DLC1 glands were normal during involution, MMTV-S88A mice showed accelerated mammary involution with increase apoptosis and altered expression of involution-associated genes. Further analysis of the MMTV-S88A glands showed they had increased steady state level of Bim protein which might be responsible for the early involution. Finally, our in vitro data showed that Ser88 phosphorylation abolished DLC1 dimer and consequently might disturb its interaction with Bim and destabilize Bim. ^ Collectively, our findings provided in vivo evidence that Ser88 phosphorylation of DLC1 can regulate DLC1's function. In addition, Ser88 phosphorylation might be critical for DLC1 dimer-monomer transition. ^

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With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

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Mycobacterium tuberculosis, a bacillus known to cause disease in humans since ancient times, is the etiological agent of tuberculosis (TB). The infection is primarily pulmonary, although other organs may also be affected. The prevalence of pulmonary TB disease in the US is highest along the US-Mexico border, and of the four US states bordering Mexico, Texas had the second highest percentage of cases of TB disease among Mexico-born individuals in 1999 (CDC, 2001). Between the years of 1993 and 1998, the prevalence of drug-resistant (DR) TB was 9.1% among Mexican-born individuals and 4.4% among US-born individuals (CDC, 2001). In the same time period, the prevalence of multi-drug resistant (MDR) TB was 1.4% among Mexican-born individuals and 0.6% among US-born individuals (CDC, 2001). There is a renewed urgency in the quest for faster and more effective screening, diagnosis, and treatment methods for TB due to the resurgence of tuberculosis in the US during the mid-1980s and early 1990s (CDC, 2007a), and the emergence of drug-resistant, multidrug-resistant, and extremely drug-resistant tuberculosis worldwide. Failure to identify DR and MDR-TB quickly leads to poorer treatment outcomes (CDC, 2007b). The recent rise in TB/HIV comorbidity further complicates TB control efforts. The gold standard for identification of DR-TB requires mycobacterial growth in culture, a technique taking up to three weeks, during which time DR/MDR-TB individuals harboring resistant organisms may be receiving inappropriate treatment. The goal of this study was to determine the sensitivity and specificity of real-time quantitative polymerase chain reaction (qPCR) using molecular beacons in the Texas population. qPCR using molecular beacons is a novel approach to detect mycobacterial mutations conferring drug resistance. This technique is time-efficient and has been shown to have high sensitivity and specificity in several populations worldwide. Rifampin (RIF) susceptibility was chosen as the test parameter because strains of M. tuberculosis which are resistant to RIF are likely to also be MDR. Due to its status as a point of entry for many immigrants into the US, control efforts against TB and drug-resistant TB in Texas is a vital component of prevention efforts in the US as a whole. We show that qPCR using molecular beacons has high sensitivity and specificity when compared with culture (94% and 87%, respectively) and DNA sequencing (90% and 96%, respectively). We also used receiver operator curve analysis to calculate cutoff values for the objective determination of results obtained by qPCR using molecular beacons. ^

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In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

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Electronic waste is a fairly new and largely unknown phenomenon. Accordingly, governments have only recently acknowledged electronic waste as a threat to the environment and public health. In attempting to mitigate the hazards associated with this rapidly growing toxic waste stream, governments at all levels have started to implement e-waste management programs. The legislation enacted to create these programs is based on extended producer responsibility or EPR policy. ^ EPR shifts the burden of final disposal of e-waste from the consumer or municipal solid waste system to the manufacturer of electronic equipment. Applying an EPR policy is intended to send signals up the production chain to the manufacturer. The desired outcome is to change the methods of production in order to reduce production outputs/inputs with the ultimate goal of changing product design. This thesis performs a policy analysis of the current e-waste policies at the federal and state level of government, focusing specifically on Texas e-waste policies. ^ The Texas e-waste law known, as HB 2714 or the Texas Computer TakeBack Law, requires manufacturers to provide individual consumers with a free and convenient method for returning their used computers to manufacturers. The law is based on individual producer responsibility and shared responsibility among consumer, retailers, recyclers, and the TCEQ. ^ Using a set of evaluation criteria created by the Organization for Economic Co-operation and Development, the Texas e-waste law was examined to determine its effectiveness at reducing the threat of e-waste in Texas. Based on the outcomes of the analysis certain recommendations were made for the legislature to incorporate into HB 2714. ^ The results of the policy analysis show that HB 2714 is a poorly constructed law and does not provide the desired results seen in other states with EPR policies. The TakeBack Law does little to change the collection methods of manufacturers and even less to change their production habits. If the e-waste problem is to be taken seriously, HB 2714 must be amended to reflect the proposed changes in this thesis.^

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Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

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Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

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This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^

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To identify more mutations that can affect the early development of Myxococcus xanthus, the synthetic transposon TnT41 was designed and constructed. By virtue of its special features, it can greatly facilitate the processes of mutation screening/selection, mapping, cloning and DNA sequencing. In addition, it allows for the systematic discovery of genes in regulatory hierarchies using their target promoters. In this study, the minimal regulatory region of the early developmentally regulated gene 4521 was used as a reporter in the TnT41 mutagenesis. Both positive (P) mutations and negative (N) mutations were isolated based on their effects on 4521 expression.^ Four of these mutations, i.e. N1, N2, P52 and P54 were analyzed in detail. Mutations N1 and N2 are insertion mutations in a gene designated sasB. The sasB gene is also identified in this study by genetic and molecular analysis of five UV-generated 4521 suppressor mutations. The sasB gene encodes a protein without meaningful homology in the databases. The sasB gene negatively regulates 4521 expression possibly through the SasS-SasR two component system. A wild-type sasB gene is required for normal M. xanthus fruiting body formation and sporulation.^ Cloning and sequencing analysis of the P52 mutation led to the identification of an operon that encodes the M. xanthus high-affinity branched-chain amino acid transporter system. This liv operon consists of five genes designated livK, livH, livM, livC, and livF, respectively. The Liv proteins are highly similar to their counterparts from other bacteria in both amino acid sequences, functional motifs and predicted secondary structures. This system is required for development since liv null mutations cause abnormality in fruiting body formation and a 100-fold decrease in sporulation efficiency.^ Mutation P54 is a TnT41 insertion in the sscM gene of the ssc chemotaxis system, which has been independently identified by Dr. Shi's lab. The sscM gene encodes a MCP (methyl-accepting chemotaxis protein) homologue. The SscM protein is predicted to contain two transmembrane domains, a signaling domain and at least one putative methylation site. Null mutations of this gene abolish the aggregation of starving cells at a very early stage, though the sporulation levels of the mutant can reach 10% that of wild-type cells. ^

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Global and local climatic forcing, e.g. concentration of atmospheric CO2 or insolation, influence the distribution of C3 and C4 plants in southwest Africa. C4 plants dominate in more arid and warmer areas and are favoured by lower pCO2 levels. Several studies have assessed past and present continental vegetation by the analysis of terrestrial n-alkanes in near-coastal deep sea sediments using single samples or a small number of samples from a given climatic stage. The objectives of this study were to evaluate vegetation changes in southwest Africa with regard to climatic changes during the Late Pleistocene and the Holocene and to elucidate the potential of single sample simplifications. We analysed two sediment cores at high resolution, altogether ca. 240 samples, from the Southeast Atlantic Ocean (20°S and 12°S) covering the time spans of 18 to 1 ka and 56 to 2 ka, respectively. Our results for 20°S showed marginally decreasing C4 plant domination (of ca. 5%) during deglaciation based on average chain length (ACL27-33 values) and carbon isotopic composition of the C31 and C33 n-alkanes. Values for single samples from 18 ka and the Holocene overlap and, thus, are not significantly representative of the climatic stages they derive from. In contrast, at 12°S the n-alkane parameters show a clear difference of plant type for the Late Pleistocene (C4 plant domination, 66% C4 on average) and the Holocene (C3 plant domination, 40% C4 on average). During deglaciation vegetation change highly correlates with the increase in pCO2 (r² = 0.91). Short-term climatic events such as Heinrich Stadials or Antarctic warming periods are not reflected by vegetation changes in the catchment area. Instead, smaller vegetation fluctuations during the Late Pleistocene occur in accordance with local variations of insolation.

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Sediments recovered at ODP Site 984 on the Reykjanes Ridge provided multicentennial-scale records (SST, planktic and benthic delta18O, IRD and magnetic susceptibility) of Late Pliocene climate change over the onset of Northern Hemisphere glaciation (NHG), 2.95-2.82 Ma. Short-term climate variations prior and after the onset of continent-wide glaciation were compared to test the hypothesis, whether Dansgaard-Oeschger (DO) cycles may have been triggered by continental ice breakouts. By means of spectral analyses for two selected interglacial stages prior to and after NHG (G15 and G1), we found that climate variability resembled that of the Holocene and the mid-Pliocene warm period. In contrast, DO-like periodicities near 1470, 2900, and 4400 yr indeed only occurred in glacial stages after the onset of NHG (G14, G6, and 104), but hardly in stage G20 prior to the onset. These results suggest a causal link between DO cycles and the Late Pliocene onset of major NHG and ice breakouts in the North Atlantic. This data set provides all primary data and spectral analysis related to this scientific work.