11 resultados para Native Range Studies

em DigitalCommons@The Texas Medical Center


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Purpose: The rapid distal falloff of a proton beam allows for sparing of normal tissues distal to the target. However proton beams that aim directly towards critical structures are avoided due to concerns of range uncertainties, such as CT number conversion and anatomy variations. We propose to eliminate range uncertainty and enable prostate treatment with a single anterior beam by detecting the proton’s range at the prostate-rectal interface and adaptively adjusting the range in vivo and in real-time. Materials and Methods: A prototype device, consisting of an endorectal liquid scintillation detector and dual-inverted Lucite wedges for range compensation, was designed to test the feasibility and accuracy of the technique. Liquid scintillation filled volume was fitted with optical fiber and placed inside the rectum of an anthropomorphic pelvic phantom. Photodiode-generated current signal was generated as a function of proton beam distal depth, and the spatial resolution of this technique was calculated by relating the variance in detecting proton spills to its maximum penetration depth. The relative water-equivalent thickness of the wedges was measured in a water phantom and prospectively tested to determine the accuracy of range corrections. Treatment simulation studies were performed to test the potential dosimetric benefit in sparing the rectum. Results: The spatial resolution of the detector in phantom measurement was 0.5 mm. The precision of the range correction was 0.04 mm. The residual margin to ensure CTV coverage was 1.1 mm. The composite distal margin for 95% treatment confidence was 2.4 mm. Planning studies based on a previously estimated 2mm margin (90% treatment confidence) for 27 patients showed a rectal sparing up to 51% at 70 Gy and 57% at 40 Gy relative to IMRT and bilateral proton treatment. Conclusion: We demonstrated the feasibility of our design. Use of this technique allows for proton treatment using a single anterior beam, significantly reducing the rectal dose.

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A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

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Native peoples of the New World, including Amerindians and admixed Latin Americans such as Mexican-Americans, are highly susceptible to diseases of the gallbladder. These include cholesterol cholelithiasis (gallstones) and its complications, as well as cancer of the gallbladder. Although there is clearly some necessary dietary or other environmental risk factor involved, the pattern of disease prevalence is geographically associated with the distribution of genes of aboriginal Amerindian origin, and levels of risk generally correspond to the degree of Amerindian admixture. This pattern differs from that generally associated with Westernization, which suggests a gene-environment interaction, and that within an admixed population there is a subset whose risk is underestimated when admixture is ignored. The risk that an individual of a susceptible New World genotype will undergo a cholecystectomy by age 85 can approach 40% in Mexican-American females, and their risk of gallbladder cancer can reach several percent. These are heretofore unrecognized levels of risk, especially of the latter, because previous studies have not accounted for admixture or for the loss of at-risk individuals due to cholecystectomy. A genetic susceptibility may, thus, be as "carcinogenic" in New World peoples as any known major environmental exposure; yet, while the risk has a genetic basis, its expression as gallbladder cancer is so delayed as to lead only very rarely to multiply-affected families. Estimates in this paper are derived in part from two studies of Mexican-Americans in Starr County and Laredo, Texas.

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Advances in radiotherapy have generated increased interest in comparative studies of treatment techniques and their effectiveness. In this respect, pediatric patients are of specific interest because of their sensitivity to radiation induced second cancers. However, due to the rarity of childhood cancers and the long latency of second cancers, large sample sizes are unavailable for the epidemiological study of contemporary radiotherapy treatments. Additionally, when specific treatments are considered, such as proton therapy, sample sizes are further reduced due to the rareness of such treatments. We propose a method to improve statistical power in micro clinical trials. Specifically, we use a more biologically relevant quantity, cancer equivalent dose (DCE), to estimate risk instead of mean absorbed dose (DMA). Our objective was to demonstrate that when DCE is used fewer subjects are needed for clinical trials. Thus, we compared the impact of DCE vs. DMA on sample size in a virtual clinical trial that estimated risk for second cancer (SC) in the thyroid following craniospinal irradiation (CSI) of pediatric patients using protons vs. photons. Dose reconstruction, risk models, and statistical analysis were used to evaluate SC risk from therapeutic and stray radiation from CSI for 18 patients. Absorbed dose was calculated in two ways: with (1) traditional DMA and (2) with DCE. DCE and DMA values were used to estimate relative risk of SC incidence (RRCE and RRMA, respectively) after proton vs. photon CSI. Ratios of RR for proton vs. photon CSI (RRRCE and RRRMA) were then used in comparative estimations of sample size to determine the minimal number of patients needed to maintain 80% statistical power when using DCE vs. DMA. For all patients, we found that protons substantially reduced the risk of developing a second thyroid cancer when compared to photon therapy. Mean RRR values were 0.052±0.014 and 0.087±0.021 for RRRMA and RRRCE, respectively. However, we did not find that use of DCE reduced the number of patents needed for acceptable statistical power (i.e, 80%). In fact, when considerations were made for RRR values that met equipoise requirements and the need for descriptive statistics, the minimum number of patients needed for a micro-clinical trial increased from 17 using DMA to 37 using DCE. Subsequent analyses revealed that for our sample, the most influential factor in determining variations in sample size was the experimental standard deviation of estimates for RRR across the patient sample. Additionally, because the relative uncertainty in dose from proton CSI was so much larger (on the order of 2000 times larger) than the other uncertainty terms, it dominated the uncertainty in RRR. Thus, we found that use of corrections for cell sterilization, in the form of DCE, may be an important and underappreciated consideration in the design of clinical trials and radio-epidemiological studies. In addition, the accurate application of cell sterilization to thyroid dose was sensitive to variations in absorbed dose, especially for proton CSI, which may stem from errors in patient positioning, range calculation, and other aspects of treatment planning and delivery.

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RecA in Escherichia coli and it's homologue, ScRad51 in Saccharomyces cerevisiae, play important roles in recombinational repair. ScRad51 homologues have been discovered in a wide range of organisms including Schizosaccharomyces pombe, lily, chicken, mouse and human. To date there is no direct evidence to describe that mouse Rad51(MmRad51) is involved in DNA double-strand break repair. In order to elucidate the role of MmRad51 in vivo, it was mutated by the embryonic stem (ES) cell/gene targeting technology in mice. The mutant embryos arrested in development shortly after implantation. There was a decrease in cell proliferation followed by programmed cell death, and trophectoderm-derived cells were sensitive to $\gamma$-radiation. Severe chromosome loss was observed in most mitotically dividing cells. The mutant embryos lived longer and developed further in a p53 mutant background; however, double-mutant embryonic fibroblasts failed to proliferate in tissue culture, reflecting the embryos limited life span. Based on these data, MmRad51 repairs DNA damage induced by $\gamma$-radiation, is needed to maintain euplody, and plays an important role in proliferating cells.^ Ku is a heterodimer of 70 and 80 kDs subunit, which binds to DNA ends and other altered DNA structures such as hairpins, nicks, and gaps. In addition, Ku is required for DNA-PK activity through a direct association. Although the biochemical properties of Ku and DNA-PKcs have been characterized in cells, their physiological functions are not clear. In order to understand the function of Ku in vivo, we generated mice homozygous for a mutation of the Ku80 gene. Ku80-deficient mice, like scid mice, showed severe immunodeficiency due to a impairment of V(D)J recombination. Mutant mice were semiviable and runted, cells derived from mutant embryos displayed hypersensitivity to $\gamma$-radiation, a decreased growth rate, a slow entry into S phase, altered colony size distributions, and a short life span. Based on these results, mutant cells and mice appeared to prematurely age. ^

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Human a2 -macroglobulin ( a2 M; homotetramer, Mr 720 kDa) is an essential scavenger of proteinases in the serum. Each of its four subunits has a ‘bait region’, with cleavage sequences for almost all endo-proteinases, an unusual thiol ester moiety and a receptor-binding domain (RBD). Bait region cleavage in native a2 M ( a2 M-N) by a proteinase results in rapid thiol ester breakage, with a large-scale structural transformation, in which a2 M uniquely entraps the proteinase in a cage-like structure and exposes receptor-binding domains for rapid endocytosis. Transformed a2 M ( a2 M-TR) contains up to two proteinases, which remain active to small substrates. 3-D electron microscopy is optimally suited to study this unusual structural change at resolutions near (1/30) Å−1. ^ The structural importance of the thiol esters was demonstrated by a genetically-engineered a2 M, with the cysteines involved in thiol ester formation mutated to serines, which appeared structurally homologous to a2 M-TR. This demonstrates that the four highly labile thiol esters alone maintain the a2 M-N structure, while the ‘closed trap’ formed by a2 M-TR is a more stable structural form. ^ Half-transformed a2 M ( a2 M-HT), with cleaved bait regions and thiol esters in only two of its four subunits, provides an important structural link between a2 M-N and a2 M-TR. A comparison with a2 M-N showed the two proteinase-entrapping domains were above and below the plane bisecting the long axis. Both a2 M-N and a2 M-TR consist of two dense, oppositely twisted strands with significant interconnections, indicating that the structural change involves a rotation of these strands. In a2 M-HT these strands were partially untwisted with large central openings, revealing the manner in which the proteinase enters the internal cavity of a2 M. ^ In reconstructions of a2 M-N, a2 M-HT and a2 M-TR labeled with a monoclonal Fab, the Fabs were located on distal ends of each constitutive strand, demonstrating an anti-parallel arrangement of the subunits. Separation between the top and bottom pairs of Fabs was nearly the same on all structures, but the pairs were rotated about the long axis. Taken together, these results indicate that upon proteinase cleavage the two strands in a2 M-N separate. The proteinase enters the structure, while the strands re-twist to encage it. In a2 M-TR, which displays receptor-binding arms, more than two subunits are transformed as strands in the transformed half of a2 M-HT were not separated. ^

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Leukopenia, the leukocyte count, and prognosis of disease are interrelated; a systematic search of the literature was undertaken to ascertain the strength of the evidence. One hundred seventy-one studies were found from 1953 onward pertaining to the predictive capabilities of the leukocyte count. Of those studies, 42 met inclusion criteria. An estimated range of 2,200cells/μL to 7,000cells/μL was determined as that which indicates good prognosis in disease and indicates the least amount of risk to an individual overall. Tables of the evidence are included indicating the disparate populations examined and the possible degree of association. ^

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Interim clinical trial monitoring procedures were motivated by ethical and economic considerations. Classical Brownian motion (Bm) techniques for statistical monitoring of clinical trials were widely used. Conditional power argument and α-spending function based boundary crossing probabilities are popular statistical hypothesis testing procedures under the assumption of Brownian motion. However, it is not rare that the assumptions of Brownian motion are only partially met for trial data. Therefore, I used a more generalized form of stochastic process, called fractional Brownian motion (fBm), to model the test statistics. Fractional Brownian motion does not hold Markov property and future observations depend not only on the present observations but also on the past ones. In this dissertation, we simulated a wide range of fBm data, e.g., H = 0.5 (that is, classical Bm) vs. 0.5< H <1, with treatment effects vs. without treatment effects. Then the performance of conditional power and boundary-crossing based interim analyses were compared by assuming that the data follow Bm or fBm. Our simulation study suggested that the conditional power or boundaries under fBm assumptions are generally higher than those under Bm assumptions when H > 0.5 and also matches better with the empirical results. ^

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Orosomucoid (ORM) or alpha-1 acid glycoprotein is an acute phase protein of human plasma whose function is suggested to be the competitive inhibition of cellular recognition by infective agents. Isoelectric focusing (IEF) and immunoblotting have been combined and optimum conditions have been determined for reliable classification of different ORM phenotypes. Addition of 6 M urea in an IEF gel revealed additional microheterogeneity in the ORM system which has not been previously reported. 1,667 individuals from different native ethnic groups of North and South America, Africa and New Guinea have been screened to determine the distribution of ORM alleles. Two common alleles, ORM1*1 and ORM1*2 have been observed and their frequencies were determined. Genetically independent variation consistent with expression of the ORM2 locus was observed in American and African blacks but was not observed in other sampled populations. The population allele frequencies for this new locus were 0.958, 0.025, 0.006, 0.011, for alleles ORM2*1, ORM2*2, ORM2*3, ORM2*4, respectively. Family studies confirm the autosomal codominant inheritance of the phenotypes observed at both ORM loci. ^

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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.

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The Reoviridae virus family is a group of economically and pathologically important viruses that have either single-, double-, or triple-shelled protein layers enclosing a segmented double stranded RNA genome. Each virus particle in this family has its own viral RNA dependent RNA polymerase and the enzymatic activities necessary for the mature RNA synthesis. Based on the structure of the inner most cores of the viruses, the Reoviridae viruses can be divided into two major groups. One group of viruses has a smooth surfaced inner core, surrounded by complete outer shells of one or two protein layers. The other group has an inner core decorated with turrets on the five-fold vertices, and could either completely lack or have incomplete outer protein layers. The structural difference is one of the determinant factors for their biological differences during the infection. ^ Cytoplasmic polyhedrosis virus (CPV) is a single-shelled, turreted virus and the structurally simplest member in Reoviridae. It causes specific chronic infections in the insect gut epithelial cells. Due to its wide range of insect hosts, CPV has been engineered as a potential insecticide for use in fruit and vegetable farming. Its unique structural simplicity, unparalleled capsid stability and ease of purification make CPV an ideal model system for studying the structural basis of dsRNA virus assembly at the highest possible resolution by electron cryomicroscopy (cryoEM) and three-dimensional (3D) reconstruction. ^ In this thesis work, I determined the first 3D structure of CPV capsids using 100 kV cryoEM. At an effective resolution of 17 Å, the full capsid reveals a 600-Å diameter, T = 1 icosahedral shell decorated with A and B spikes at the 5-fold vertices. The internal space of the empty CPV is unoccupied except for 12 mushroom-shaped densities that are attributed to the transcriptional enzyme complexes. The inside of the full capsid is packed with icosahedrally-ordered viral genomic RNA. The interactions of viral RNA with the transcriptional enzyme complexes and other capsid proteins suggest a mechanism for RNA transcription and subsequent release. ^ Second, the interactions between the turret proteins (TPs) and the major capsid shell protein (CSPs) have been identified through 3D structural comparisons of the intact CPV capsids with the spikeless CPV capsids, which were generated by chemical treatments. The differential effects of these chemical treatment experiments also indicated that CPV has a significantly stronger structural integrity than other dsRNA viruses, such as the orthoreovirus subcores, which are normally enclosed within outer protein shells. ^ Finally, we have reconstructed the intact CPV to an unprecendented 8 Å resolution from several thousand of 400kV cryoEM images. The 8 Å structure reveals interactions among the 120 molecules of each of the capsid shell protein (CSP), the large protrusion protein (LPP), and 60 molecules of the turret protein (TP). A total of 1980 α-helices and 720 β-sheets have been identified in these capsid proteins. The CSP structure is largely conserved, with the majority of the secondary structures homologous to those observed in the x-ray structures of corresponding proteins of other reoviruses, such as orthoreovirus and bluetongue virus. The three domains of TP are well positioned to play multifunctional roles during viral transcription. The completely non-equivalent interactions between LPP and CSP and those between the anchoring domain of TP and CSP account for the unparalleled stability of this structurally simplest member of the Reoviridae. ^