Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children under the age of 15. At present, diagnosis, prognosis and treatment decisions are made based upon blood and bone marrow laboratory testing. With advances in microarray technology it is becoming more feasible to perform genetic assessment of individual patients as well. We used Singular Value Decomposition (SVD) on Illumina SNP, Affymetrix and cDNA gene-expression data and performed aggressive attribute se- lection using random forests to reduce the number of attributes to a manageable size. We then explored clustering and prediction of patient-specific properties such as disease sub-classification, and especially clinical outcome. We determined that integrating multiple types of data can provide more meaningful information than individual datasets, if combined properly. This method is able to capture the cor- relation between the attributes. The most striking result is an apparent connection between genetic background and patient mortality under existing treatment regimes. We find that we can cluster well using the mortality label of the patients. Also, using a Support Vector Machine (SVM) we can predict clinical outcome with high accu-racy. This thesis will discuss the data-mining methods used and their application to biomedical research, as well as our results and how this will affect the diagnosis and treatment of ALL in the future. / Thesis (Master, Computing) -- Queen's University, 2010-01-12 18:40:44.2

Diss. (sammanfattning) Uppsala : Univ., 2001. / Härtill 4 uppsatser.

Thesis (M.Sc. (Physiology)) -- Mahidol University, 1971.

Proefschrift Maastricht. / Lit. opg. - Met een samenvatting in het Nederlands.

Proefschrift Universiteit Maastricht. / Met lit. opg. - Met samenvatting in het Nederlands.

Thesis (M.D.)—Boston University

Epigenetic regulators are commonly mutated in cancer. Activating mutations and overexpression of EZH2 occur in lymphoma and other malignancies, while loss-of-function mutations are found in myeloid malignancies. This thesis is a study of this apparent contradiction, examining the importance of cellular context for Ezh2 loss during the evolution of a single malignancy, Acute Myeloid Leukaemia (AML). This work demonstrates diametrically opposite functions for Ezh2 at early and late stages during the evolution of leukemias generated by disparate AML-associated fusion-oncogenes. Ezh2 functions as an oncogene that may be therapeutically targeted during disease maintenance. In contrast, Ezh2 behaves as a tumour suppressor gene during AML induction. Integrated genomic analysis demonstrates that largely different expression programmes are de-repressed during disease induction and maintenance following Ezh2 loss. Studying disease induction, Ezh2 represses a subset of bivalent promoters that resolve towards gene activation upon Ezh2 loss, inducing a feto-oncogene programme including genes like Plag1, whose overexpression phenocopies Ezh2 loss to accelerate AML induction in mouse models. This data highlights the importance of cellular context and phase of disease evolution for Ezh2 function. Moreover, the work herein identifies EZH2 as a potential target in AML, whilst providing reassurance of the safety of this therapeutic strategy.

Acute Liver Failure (ALF) is a devastating ailment with a high mortality rate and limited treatment alternatives. This study presents a methodology for the design and development of a bio-artificial bioreactor to be used in a Bio-Artificial Liver Support System. The system will ultimately be used either to bridge a patient to orthotopic liver transplant (OLT), the only current cure for end stage ALF, or spontaneous recovery. Methods to optimize and visualize the flow and related mass transfer in the BR are presented. The use of magnetic resonance imaging (MRI), scanning electron microscopy (SEM) and simple testing methodology is applied with emphasis on modeling the flow conditions in the BR. The bioreactor (BR) used in the Bio-Artificial Liver Support System (BALSS), currently under-going animal trials at the University of Pretoria, was modeled and simulated for the flow conditions in the device. Two different perfusion steps were modeled including the seeding of hepatocyte cells and later the clinical perfusion step. It was found that the BR geometry was not optimal with “dead spots” and regions of retarded flow. This would restrict the effective transport of nutrients and oxygen to the cells. The different perfusion rates for the seeding and clinical perfusion steps allowed for different velocity contours with cells seeing inconsistent flow patterns and mass transfer gradients. An optimized BR design is suggested and simulated, that effectively reduces the areas of retarded flow (dead spots) and increases the flow speed uniformly through the BR to an order of magnitude similar to that found in the sinusoidal range. The scaffolding volume was also decreased to allow a larger local cell density promoting cell-cell interaction. Finally a summarized design table for the design of a hepatic BR is presented. / Dissertation (MEng (Mechanical))--University of Pretoria, 2008. / Mechanical and Aeronautical Engineering / unrestricted

No description available.

京都大学 / 0048 / 新制・課程博士 / 博士(薬学) / 甲第18214号 / 薬博第804号 / 新制||薬||237(附属図書館) / 31072 / 京都大学大学院薬学研究科生命薬科学専攻 / (主査)教授 金子 周司, 教授 髙倉 喜信, 教授 竹島 浩 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM