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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

An expression profiling study of human nuclear receptor super-family in prostate cancer cells. / 人類核受體超家族在前列腺癌的表達譜研究 / Ren lei he shou ti chao jia zu zai qian lie xian ai de biao da pu yan jiu

January 2011 (has links)
Cheng, Cho Yiu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 186-217). / Abstracts in English and Chinese. / Acknowledgements --- p.1 / Abstract of thesis --- p.2 / Abstract of thesis in Chinese --- p.7 / Presentation attended --- p.9 / Chapter Chapter 1: --- Introduction and Background --- p.13 / Chapter 1.1 --- Anatomy and functions of human prostate gland --- p.13 / Chapter 1.2 --- Worldwide epidemiology of prostate cancer --- p.15 / Chapter 1.3 --- Prostate cancer stages and treatments in clinic --- p.21 / Chapter 1.4 --- Introduction to nuclear receptors --- p.23 / Chapter 1.5 --- Nuclear receptor structure --- p.24 / Chapter 1.6 --- Nuclear receptors nomenclature and classification --- p.28 / Chapter 1.7 --- Mode of action for nuclear receptors --- p.34 / Chapter 1.8 --- Co-regulators of nuclear receptors --- p.35 / Chapter 1.9 --- Nuclear receptors related to prostate cancer --- p.43 / Chapter Chapter 2: --- Aim of study and experimental design --- p.59 / Chapter 2.1 --- Aim of study --- p.59 / Chapter 2.2 --- In vitro cell lines models used in the study --- p.60 / Chapter Chapter 3: --- Materials and methods --- p.64 / Chapter 3.1 --- Apparatus and preparation throughout the study --- p.64 / Chapter 3.2 --- Cells culture --- p.64 / Chapter 3.3 --- RNA extraction --- p.67 / Chapter 3.4 --- Reverse transcription --- p.68 / Chapter 3.5 --- Primers specificity checking --- p.69 / Chapter 3.6 --- Real time quantitative polymerase chain reaction --- p.84 / Chapter 3.7 --- Data analysis --- p.90 / Chapter Chapter 4: --- Results --- p.92 / Chapter 4.1 --- Expression of nuclear receptors transcripts in each prostatic cell lines used --- p.92 / Chapter 4.2 --- Expression of nuclear receptor transcripts in immortalized prostatic epithelial BPH-1 and BPH-1 derived cell lines model --- p.116 / Chapter 4.3 --- Expression of nuclear receptor transcripts in androgen-dependent and androgen-independent classical prostatic cancer cell lines model --- p.121 / Chapter 4.4 --- Expression of nuclear receptor transcripts in androgen-independent and antiandrogen-resistant LNCaP derived cell lines model --- p.125 / Chapter Chapter 5: --- Discussion --- p.129 / Chapter 5.1 --- Special expression pattern of some nuclear receptors in the prostatic cell lines or prostatic cancer cell lines --- p.129 / Chapter 5.2 --- BPH-1 and BPH-1 derived cell lines model --- p.138 / Chapter 5.2.1 --- Prostatic cell lines model studying the transformation and invasion in prostate cancer (BPH-1 Snail & BPH-1 CAFTDs versus BPH-1) --- p.138 / Chapter 5.2.2 --- Prostatic cell lines model studying the transformation and invasion in prostate cancer (BPH-1 Snail & BPH-1 CAFTDs versus BPH-1 AR) --- p.159 / Chapter 5.3.3 --- classical prostatic cancer cell lines model --- p.162 / Chapter 5.3.1 --- Prostatic cancer cell lines model studying androgen-dependence and androgen-independence (DU145 & PC-3 versus LNCaP) --- p.163 / Chapter 5.4 --- LNCaP and LNCaP derived cell lines model --- p.170 / Chapter 5.4.1 --- Prostatic cancer cell lines model studying androgen-independence and antiandrogen-resistance (LNCaP-abl & LNCaP-BCs versus LNCaP) --- p.171 / Chapter Chapter 6: --- Conclusion --- p.179 / References --- p.186
2

Mineração de dados para modelagem de risco de metástase em tumor de próstata / Data mining for the modeling of metastasis risk on prostate tumor

Chahine, Gabriel Jorge, 1982- 23 August 2018 (has links)
Orientadores: Laercio Luis Vendite, Stanley Robson de Medeiros Oliveira / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-23T23:19:05Z (GMT). No. of bitstreams: 1 Chahine_GabrielJorge_M.pdf: 1229228 bytes, checksum: fffd253696b5a9dee9870ae1910256e5 (MD5) Previous issue date: 2013 / Resumo: Dos cânceres do trato urinário, os mais comuns são os de Próstata e de Bexiga, sendo o primeiro a causa mais comum de morte por câncer e o carcinoma mais comum para homens. Nosso objetivo nesse trabalho é desenvolver modelos para determinar se um dado tumor irá aumentar e invadir outros órgãos ou se não apresenta esse risco e permanecerá contido. Para isso, coletamos dados de pacientes com câncer de próstata e analisamos quais variáveis mais impactam para ocorrência de metástase. Com isso construímos modelos de classificação, que, com os dados de um determinado paciente, detectam se naquele caso haverá ou não metástase à distância. Nesse trabalho apresentamos modelos para predição de ocorrência de metástases em câncer de próstata. As simulações foram feitas com dados cedidos pelo prof. Dr. Ubirajara Ferreira, responsável pela disciplina de Urologia da FCM da Unicamp, do Hospital das Clinicas - UNICAMP / Abstract: Of all the cancers of the urinary tract, the most common are the Prostate and Bladder. The first being the most common cause of death by cancer and the most common carcinoma in men. Our goal in this work is to develop predictive models to determine whether a given tumor will grow and invade other organs or, if it doesn't present this risk and will remain constrained. To do this, we collected data from patients with prostate cancer and assessed which variables were the most responsible for the occurrence of metastasis. Hence, we built predictive models that, with the data of a given patient, are able detect whether or not a distant metastasis would occur in. In this work we present models to predict the occurrence of metastasis in prostate cancer. The simulations were made with the data given by prof. Dr. Ubirajara Ferreira, responsible for the disciplines of Urology from Unicamp's Faculty of Medical Sciences / Mestrado / Matematica Aplicada e Computacional / Mestre em Matemática Aplicada e Computacional

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