954 resultados para Pair Linkage
Resumo:
The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism) depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.
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BACKGROUND Little is known on the risk of cancer in HIV-positive children in sub-Saharan Africa. We examined incidence and risk factors of AIDS-defining and other cancers in pediatric antiretroviral therapy (ART) programs in South Africa. METHODS We linked the records of five ART programs in Johannesburg and Cape Town to those of pediatric oncology units, based on name and surname, date of birth, folder and civil identification numbers. We calculated incidence rates and obtained hazard ratios (HR) with 95% confidence intervals (CI) from Cox regression models including ART, sex, age, and degree of immunodeficiency. Missing CD4 counts and CD4% were multiply imputed. Immunodeficiency was defined according to World Health Organization 2005 criteria. RESULTS Data of 11,707 HIV-positive children were included in the analysis. During 29,348 person-years of follow-up 24 cancers were diagnosed, for an incidence rate of 82 per 100,000 person-years (95% CI 55-122). The most frequent cancers were Kaposi Sarcoma (34 per 100,000 person-years) and Non Hodgkin Lymphoma (31 per 100,000 person-years). The incidence of non AIDS-defining malignancies was 17 per 100,000. The risk of developing cancer was lower on ART (HR 0.29, 95%CI 0.09-0.86), and increased with age at enrolment (>10 versus <3 years: HR 7.3, 95% CI 2.2-24.6) and immunodeficiency at enrolment (advanced/severe versus no/mild: HR 3.5, 95%CI 1.1-12.0). The HR for the effect of ART from complete case analysis was similar but ceased to be statistically significant (p=0.078). CONCLUSIONS Early HIV diagnosis and linkage to care, with start of ART before advanced immunodeficiency develops, may substantially reduce the burden of cancer in HIV-positive children in South Africa and elsewhere.
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DNA duplexes containing unnatural base-pair surrogates are attractive biomolecular nanomaterials with potentially beneficial photophysical or electronic properties. Herein we report the first X-ray structure of a duplex containing a phen-pair in the center of the double helix in a zipper like stacking arrangement.
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The surveillance of HIV-related cancers in South Africa is hampered by the lack of systematic collection of cancer diagnoses in HIV cohorts and the absence of HIV status in cancer registries. To improve cancer ascertainment and estimate cancer incidence, we linked records of adults (aged ≥ 16 years) on antiretroviral treatment (ART) enrolled at Sinikithemba HIV clinic, McCord Hospital in KwaZulu-Natal (KZN) with the cancer records of public laboratories in KZN province using probabilistic record linkage methods. We calculated incidence rates for all cancers, Kaposi sarcoma (KS), cervix, non-Hodgkin's lymphoma and non-AIDS defining cancers (NADCs) before and after inclusion of linkage-identified cancers with 95% confidence intervals (CI). A total of 8,721 records of HIV-positive patients were linked with 35,536 cancer records. Between 2004 and 2010 we identified 448 cancers, 82% (n=367) were recorded in the cancer registry only, 10% (n=43) in the HIV cohort only and 8% (n=38) both in the HIV cohort and the cancer registry. The overall cancer incidence rate in patients starting ART increased from 134 (95% CI 91-212) to 877 (95% CI 744-1,041) after inclusion of linkage-identified cancers. Incidence rates were highest for KS (432, 95% CI 341-555), followed by cervix (259, 95% CI 179-390) and NADCs (294, 95% CI 223-395) per 100,000 person-years. Ascertainment of cancer in HIV cohorts is incomplete, probabilistic record linkage is both feasible and essential for cancer ascertainment. This article is protected by copyright. All rights reserved.
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Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^
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Currently there is no general method to study the impact of population admixture within families on the assumptions of random mating and consequently, Hardy-Weinberg equilibrium (HWE) and linkage equilibrium (LE) and on the inference obtained from traditional linkage analysis. ^ First, through simulation, the effect of admixture of two populations on the log of the odds (LOD) score was assessed, using Prostate Cancer as the typical disease model. Comparisons between simulated mixed and homogeneous families were performed. LOD scores under both models of admixture (within families and within a data set of homogeneous families) were closest to the homogeneous family scores of the population having the highest mixing proportion. Random sampling of families or ascertainment of families with disease affection status did not affect this observation, nor did the mode of inheritance (dominant/recessive) or sample size. ^ Second, after establishing the effect of admixture on the LOD score and inference for linkage, the presence of induced disequilibria by population admixture within families was studied and an adjustment procedure was developed. The adjustment did not force all disequilibria to disappear but because the families were adjusted for the population admixture, those replicates where the disequilibria exist are no longer affected by the disequilibria in terms of maximization for linkage. Furthermore, the adjustment was able to exclude uninformative families or families that had such a high departure from HWE and/or LE that their LOD scores were not reliable. ^ Together these observations imply that the presence of families of mixed population ancestry impacts linkage analysis in terms of the LOD score and the estimate of the recombination fraction. ^
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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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With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^
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Following up genetic linkage studies to identify the underlying susceptibility gene(s) for complex disease traits is an arduous yet biologically and clinically important task. Complex traits, such as hypertension, are considered polygenic with many genes influencing risk, each with small effects. Chromosome 2 has been consistently identified as a genomic region with genetic linkage evidence suggesting that one or more loci contribute to blood pressure levels and hypertension status. Using combined positional candidate gene methods, the Family Blood Pressure Program has concentrated efforts in investigating this region of chromosome 2 in an effort to identify underlying candidate hypertension susceptibility gene(s). Initial informatics efforts identified the boundaries of the region and the known genes within it. A total of 82 polymorphic sites in eight positional candidate genes were genotyped in a large hypothesis-generating sample consisting of 1640 African Americans, 1339 whites, and 1616 Mexican Americans. To adjust for multiple comparisons, resampling-based false discovery adjustment was applied, extending traditional resampling methods to sibship samples. Following this adjustment for multiple comparisons, SLC4A5, a sodium bicarbonate transporter, was identified as a primary candidate gene for hypertension. Polymorphisms in SLC4A5 were subsequently genotyped and analyzed for validation in two populations of African Americans (N = 461; N = 778) and two of whites (N = 550; N = 967). Again, SNPs within SLC4A5 were significantly associated with blood pressure levels and hypertension status. While not identifying a single causal DNA sequence variation that is significantly associated with blood pressure levels and hypertension status across all samples, the results further implicate SLC4A5 as a candidate hypertension susceptibility gene, validating previous evidence for one or more genes on chromosome 2 that influence hypertension related phenotypes in the population-at-large. The methodology and results reported provide a case study of one approach for following up the results of genetic linkage analyses to identify genes influencing complex traits. ^
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Apolipoprotein E (ApoE) plays a major role in the metabolism of high density and low density lipoproteins (HDL and LDL). Its common protein isoforms (E2, E3, E4) are risk factors for coronary artery disease (CAD) and explain between 16 to 23% of the inter-individual variation in plasma apoE levels. Linkage analysis has been completed for plasma apoE levels in the GENOA study (Genetic Epidemiology Network of Atherosclerosis). After stratification of the population by lipoprotein levels and body mass index (BMI) to create more homogeneity with regard to biological context for apoE levels, Hispanic families showed significant linkage on chromosome 17q for two strata (LOD=2.93 at 104 cM for a low cholesterol group, LOD=3.04 at 111 cM for a low cholesterol, high HDLC group). Replication of 17q linkage was observed for apoB and apoE levels in the unstratified Hispanic and African-American populations, and for apoE levels in African-American families. Replication of this 17q linkage in different populations and strata provides strong support for the presence of gene(s) in this region with significant roles in the determination of inter-individual variation in plasma apoE levels. Through a positional and functional candidate gene approach, ten genes were identified in the 17q linked region, and 62 polymorphisms in these genes were genotyped in the GENOA families. Association analysis was performed with FBAT, GEE, and variance-component based tests followed by conditional linkage analysis. Association studies with partial coverage of TagSNPs in the gene coding for apolipoprotein H (APOH) were performed, and significant results were found for 2 SNPs (APOH_20951 and APOH_05407) in the Hispanic low cholesterol strata accounting for 3.49% of the inter-individual variation in plasma apoE levels. Among the other candidate genes, we identified a haplotype block in the ACE1 gene that contains two major haplotypes associated with apoE levels as well as total cholesterol, apoB and LDLC levels in the unstratified Hispanic population. Identifying genes responsible for the remaining 60% of inter-individual variation in plasma apoE level, will yield new insights into the understanding of genetic interactions involved in the lipid metabolism, and a more precise understanding of the risk factors leading to CAD. ^
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Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^
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The Laredo Epidemiology Project is a study of the patterns of degenerative disease, particularly cancer, in the families of Laredo, Texas. The genealogical history of Laredo was reconstructed by the grouping of 350,000 individual church and civil vital event records into multi-generational families, with record linkage based on matching names. Mortality data from death records are mapped onto these pedigrees for analysis. This dissertation describes the construction of the data base and the logic upon which decisions were based. ^
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Rising levels of atmospheric CO2 are responsible for a change in the carbonate chemistry of seawater with associated pH drops (acidification) projected to reach 0.4 units from 1950 to 2100. We investigated possible indirect effects of seawater acidification on the feeding, fecundity, and hatching success of the calanoid copepod Acartia grani, mediated by potential CO2-induced changes in the nutritional characteristics of their prey. We used as prey the autotrophic dinoflagellate Heterocapsa sp., cultured at three distinct pH levels (control: 8.17, medium: 7.96, and low: 7.75) by bubbling pure CO2 via a computer automated system. Acartia grani adults collected from a laboratory culture were acclimatized for 3 d at food suspensions of Heterocapsa from each pH treatment (ca. 500 cells/ml; 300 ?g C/l). Feeding and egg production rates of the preconditioned females did not differ significantly among the three Heterocapsa diets. Egg hatching success, monitored once per day for the 72 h, did not reveal significant difference among treatments. These results are in agreement with the lack of difference in the cellular stoichiometry (C : N, C : P, and N : P ratios) and fatty acid concentration and composition encountered between the three tested Heterocapsa treatments. Our findings disagree with those of other studies using distinct types of prey, suggesting that this kind of indirect influence of acidification on copepods may be largely associated with interspecific differences among prey items with regard to their sensitivity to elevated CO2 levels.
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This study reports the results of a water footprint (WF) assessment of five types of textiles commonly used for the production of jeans, including two different fibres (cotton and Lyocell fibre) and five corresponding production methods for spinning, dyeing and weaving. The results show that the fibre production is the stage with the highest water consumption, being cotton production particularly relevant. Therefore, the study pays particular attention to the water footprint of cotton production and analyses the effects of external factors influencing the water footprint of a product, in this case, the incentives provided by the EU Common Agricultural Policy (CAP), and the relevance of agricultural practices to the water footprint of a product is emphasised. An extensification of the crop production led to higher WF per unit, but a lower overall pressure on the basins water resources. This study performs a sustainability assessment of the estimated cotton WFs with the water scarcity index, as proposed by Hoekstra et al. (2011), and shows their variations in different years as a result of different water consumption by crops in the rest of the river basin. In our case, we applied the assessment to the Guadalquivir, Guadalete and Barbate river basins, three semi-arid rivers in South Spain. Because they are found to be relevant, the available water stored in dams and the outflow are also incorporated as reference points for the sustainability assessment. The study concludes that, in the case of Spanish cotton production, the situation of the basin and the policy impact are more relevant for the status of the basin s water resources than the actual WF of cotton production. Therefore, strategies aimed at reducing the impact of the water footprint of a product need to analyse both the WF along the value chain and within the local context.