20 resultados para Low dose


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The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

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Cyclosporine A (CSA) is a cyclic eleven amino acid, lipophilic molecule used therapeutically as an immunosuppressive agent. Cyclosporine can specifically inhibit the transcription of a number of different genes. It is known that CSA is bound almost exclusively to lipoproteins in plasma, however, the relationship between the low density lipoprotein (LDL), the LDL receptor, and CSA has not been fully elucidated. The exact mechanism of cellular uptake of CSA is unknown, but it is believed to be by simple passive diffusion across the cell membrane. In addition, it has been recently shown that the frequent finding of hypercholesterolemia seen in patients treated with CSA can be explained by a CSA-induced effect. The mechanism by which CSA induces hypercholesterolemia is not known. We have used an LDL receptor-deficient animal model, the Watanabe Heritable Hyperlipidemic (WHHL) rabbit to investigate the role of LDL and the LDL receptor in the cellular uptake of CSA. Using this animal model, we have shown that CSA uptake by lymphocytes is predominantly LDL receptor-mediated. Chemical modification of apoB-100 on LDL particles abolishes their ability to bind to the LDL receptor. When CSA is incubated with modified LDL much less is taken-up than when native LDL is incubated with CSA. Treatment of two human cell lines with CSA results in a dose-dependent decrease in LDL receptor mRNA levels. Using a novel transfection system involving the 5$\sp\prime$-flanking region of the LDL receptor gene, we have found that CSA decreases the number of transcripts, but is dependent on whether or not cholesterol is present and the stage of growth of the cells. ^

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Childhood obesity in the US has reached epidemic proportions. Minority children are affected the most by this epidemic. Although there is no clear relationship between obesity and fruits and vegetables consumption, studies suggest that eating fruits and vegetables could be helpful in preventing childhood obesity. A few school-based interventions targeting youth have been effective at increasing fruits and vegetables intake.^ In Austin, Texas, the Sustainable Food Center delivered the Sprouting Healthy Kids (SHK) program that targeted low socio-economic status children in four intervention middle schools. The SHK program delivered six intervention components. This school-based intervention included: a cafeteria component, in-class lessons, an after-school garden program, a field trip to a local farm, food tasting, and farmers' visits to schools. This study aimed to determine the effects of the SHK intervention in middle school students' preferences, motivation, knowledge, and self-efficacy towards fruits and vegetables intake, as well as the actual fruits and vegetables intake. The study also aimed to determine the effects of exposure to different doses of the SHK intervention on participants' fruits and vegetable intake.^ The SHK was delivered during Spring 2009. A total of 214 students completed the pre-and-posttest surveys measuring self-report fruits and vegetables intake as well as intrapersonal factors. The results showed that the school cafeteria, the food tasting, the after school program, and the farmers' visits had a positive effect on the participants' motivation, knowledge, and self-efficacy towards fruits and vegetables intake. The farmers' visits and the food tasting components increased participants' fruits and vegetables intake. Exposure to two or more intervention components increased participants' fruits and vegetables intake. The statistically significant dose-response effect size was .352, which suggests that each intervention component increased participants' fruits and vegetables consumption this amount. Certain intervention components were more effective than others. Food tasting and farmers visits increased participants fruits and vegetables intake, therefore these components should be offered in an ongoing basis. This study suggests that exposure to multiple intervention components increased behaviors and attitudes towards fruits and vegetables consumption. Findings are consistent that SHK can influence behaviors of middle school students.^

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The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.

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The electron pencil-beam redefinition algorithm (PBRA) of Shiu and Hogstrom has been developed for use in radiotherapy treatment planning (RTP). Earlier studies of Boyd and Hogstrom showed that the PBRA lacked an adequate incident beam model, that PBRA might require improved electron physics, and that no data existed which allowed adequate assessment of the PBRA-calculated dose accuracy in a heterogeneous medium such as one presented by patient anatomy. The hypothesis of this research was that by addressing the above issues the PBRA-calculated dose would be accurate to within 4% or 2 mm in regions of high dose gradients. A secondary electron source was added to the PBRA to account for collimation-scattered electrons in the incident beam. Parameters of the dual-source model were determined from a minimal data set to allow ease of beam commissioning. Comparisons with measured data showed 3% or better dose accuracy in water within the field for cases where 4% accuracy was not previously achievable. A measured data set was developed that allowed an evaluation of PBRA in regions distal to localized heterogeneities. Geometries in the data set included irregular surfaces and high- and low-density internal heterogeneities. The data was estimated to have 1% precision and 2% agreement with accurate, benchmarked Monte Carlo (MC) code. PBRA electron transport was enhanced by modeling local pencil beam divergence. This required fundamental changes to the mathematics of electron transport (divPBRA). Evaluation of divPBRA with the measured data set showed marginal improvement in dose accuracy when compared to PBRA; however, 4% or 2mm accuracy was not achieved by either PBRA version for all data points. Finally, PBRA was evaluated clinically by comparing PBRA- and MC-calculated dose distributions using site-specific patient RTP data. Results show PBRA did not agree with MC to within 4% or 2mm in a small fraction (<3%) of the irradiated volume. Although the hypothesis of the research was shown to be false, the minor dose inaccuracies should have little or no impact on RTP decisions or patient outcome. Therefore, given ease of beam commissioning, documentation of accuracy, and calculational speed, the PBRA should be considered a practical tool for clinical use. ^