Tsang Sup-Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 176-185). / Abstracts in English and Chinese. / Acknowledgments --- p.1 / Abstract --- p.2 / 摘要 --- p.4 / List of Abbreviation --- p.6 / Chapter Chapter 1 --- General Introduction / Chapter 1.1 --- Isolation and activation of mas oncogene --- p.11 / Chapter 1.2 --- Amino acid sequence of mas oncogene --- p.14 / Chapter 1.3 --- Expression of mas oncogene --- p.18 / Chapter 1.4 --- Possible physiological role of mas oncogene --- p.20 / Chapter 1.5 --- Gene related to mas family --- p.23 / Chapter 1.6 --- Aims of study --- p.26 / Chapter Chapter 2 --- Over-expression of mas oncogene / Chapter 2.1 --- Introduction --- p.28 / Chapter 2.2 --- Materials and Methods --- p.29 / Chapter 2.2.1 --- Materials --- p.30 / Chapter 2.2.1.1 --- Chemicals --- p.30 / Chapter 2.2.1.2 --- Enzyme --- p.30 / Chapter 2.2.1.3 --- DNA Purification Kit --- p.31 / Chapter 2.2.1.4 --- Others --- p.31 / Chapter 2.2.2 --- Methods --- p.31 / Chapter 2.2.2.1 --- Strategy of construct preparation --- p.31 / Chapter 2.2.2.2 --- "Preparation of linearized vector, pFRSV" --- p.32 / Chapter 2.2.2.2.1 --- Cloning of vectors --- p.32 / Chapter 2.2.2.2.2 --- Restriction enzyme digestion and DNA dephosphorylation --- p.34 / Chapter 2.2.2.2.3 --- DNA purification by agarose gel electro-elution --- p.34 / Chapter 2.2.2.3 --- Preparation of pFRSV/mas construct --- p.35 / Chapter 2.2.2.3.1 --- PCR amplification --- p.35 / Chapter 2.2.2.3.2 --- Restriction enzyme digestion --- p.36 / Chapter 2.2.2.4 --- Ligation and analysis --- p.37 / Chapter 2.2.2.5 --- Purification of DNA by cesium chloride --- p.38 / Chapter 2.2.2.5.1 --- Large-scale bacterial culturing --- p.38 / Chapter 2.2.2.5.2 --- Ethanol precipitation --- p.39 / Chapter 2.2.2.5.3 --- Cesium chloride purification --- p.39 / Chapter 2.2.2.5.4 --- Removal of DNA dye by dialysis and ethanol precipitation --- p.40 / Chapter 2.2.2.6 --- Transfection by electroporation --- p.41 / Chapter 2.2.2.7 --- Screening for the stably transfected cells --- p.42 / Chapter 2.2.2.8 --- RT-PCR analysis of the mas transfectant --- p.43 / Chapter 2.2.2.8.1 --- Isolation of the total RNA from the mas transfectants by TRIzol ® Reagent --- p.43 / Chapter 2.2.2.8.2 --- Reverse transcription of the total RNA into cDNA --- p.44 / Chapter 2.2.2.8.3 --- Analysis of the transfected mas expression by PCR --- p.44 / Chapter 2.2.2.8.4 --- Analysis of the transfected DHFR expression by PCR --- p.45 / Chapter 2.2.2.8.5 --- Analysis of endogenous GAPDH expression by PCR --- p.46 / Chapter 2.2.2.9 --- Amplification of mas transgene by using methotrexate --- p.47 / Chapter 2.2.2.9.1 --- Amplification by low dosage MTX treatment --- p.47 / Chapter 2.2.2.9.2 --- Amplification by high dosage MTX treatment --- p.49 / Chapter 2.2.2.10 --- Southern blot analysis --- p.50 / Chapter 2.2.2.10.1 --- Preparation of DIG-labelled mas probe --- p.51 / Chapter 2.2.2.10.2 --- Preparation of DIG-labelled DHFR probe --- p.51 / Chapter 2.2.2.10.3 --- Preparation of DIG-labelled GAPDH probe --- p.52 / Chapter 2.2.2.10.4 --- Isolation of Genomic DNA from the mas transfectants by DNAzol® Reagent / Chapter 2.2.2.10.5 --- Enzymatic restriction of genomic DNA and Gel electrophoresis --- p.54 / Chapter 2.2.2.10.6 --- DNA transferring to positive charged Nylon membrane --- p.54 / Chapter 2.2.2.10.7 --- Pre-hybridization and hybridization --- p.56 / Chapter 2.2.2.10.8 --- Post-hybridization washing and blocking --- p.56 / Chapter 2.2.2.10.9 --- Detection --- p.57 / Chapter 2.2.2.11 --- Northern blot analysis --- p.57 / Chapter 2.2.2.11.1 --- Preparation of the agarose gel containing formaldehyde --- p.58 / Chapter 2.2.2.11.2 --- Preparation of the RNA sample --- p.58 / Chapter 2.2.2.11.3 --- Gel electrophoresis and transferring --- p.59 / Chapter 2.2.2.11.5 --- Pre-hybridization and hybridization --- p.60 / Chapter 2.2.2.11.4 --- Post-hybridization washing and blocking --- p.60 / Chapter 2.2.2.11.6 --- Detection --- p.61 / Chapter 2.2.2.11.7 --- Stripping and rehybridization --- p.61 / Chapter 2.3 --- Results --- p.62 / Chapter 2.3.1 --- RT-PCR analysis of gene expression in the stably transfectant --- p.62 / Chapter 2.3.2 --- Morphology of the mas trasnfectant --- p.64 / Chapter 2.3.3 --- Determination of mas gene copy number by Southern blot analysis in the mas transfectants --- p.66 / Chapter 2.3.4 --- Northern blot analysis of the transcriptional level of mas transcriptsin mas transfectants --- p.76 / Chapter 2.4 --- Discussion --- p.87 / Chapter Chapter 3 --- In vivo study of physiological effect of over-expression of mas / Chapter 3.1 --- Introduction --- p.92 / Chapter 3.2 --- Materials and Methods --- p.93 / Chapter 3.2.1 --- Materials --- p.93 / Chapter 3.2.2 --- Methods --- p.93 / Chapter 3.2.2.1 --- Cell culture --- p.93 / Chapter 3.2.2.2 --- Subcutaneous injection of nude mice --- p.94 / Chapter 3.2.2.3 --- Isolation of the total RNA from the tumor tissues --- p.95 / Chapter 3.2.2.4 --- Northern blot analysis --- p.96 / Chapter 3.3 --- Results --- p.96 / Chapter 3.3.1 --- Tumorgenicity assay of mas oncogene in nude mice --- p.96 / Chapter 3.3.2 --- Northern blot analysis of mas expression in the tumor tissues --- p.103 / Chapter 3.4 --- Discussion --- p.109 / Chapter Chapter 4 --- Fluorescent differential display analysis of mas transfectants / Chapter 4.1 --- Introduction --- p.111 / Chapter 4.2 --- Materials and Methods --- p.112 / Chapter 4.2.1 --- Materials --- p.112 / Chapter 4.2.1.1 --- Chemicals --- p.112 / Chapter 4.2.1.2 --- Enzyme --- p.113 / Chapter 4.2.1.3 --- Kits --- p.113 / Chapter 4.2.1.4 --- Others --- p.114 / Chapter 4.2.2 --- Methods --- p.114 / Chapter 4.2.2.1 --- Isolation of the total RNA from the mas transfectants by TRIzol ® Reagent --- p.114 / Chapter 4.2.2.2 --- DNase I treatment --- p.115 / Chapter 4.2.2.3 --- Reverse transcription (RT) and non-fluorescent PCR --- p.116 / Chapter 4.2.2.4 --- Reverse transcription and fluorescent differential display-PCR --- p.118 / Chapter 4.2.2.5 --- High resolution fluorescent differential display (Fluoro DD) gel --- p.118 / Chapter 4.2.2.6 --- Gel band excision of differentially expressed cDNA fragments --- p.120 / Chapter 4.2.2.7 --- Gel band reamplification --- p.120 / Chapter 4.2.2.8 --- Subcloning of reamplified cDNA fragments --- p.121 / Chapter 4.2.2.9 --- Purification of plasmid DNA from recombinant clones for reverse dot blot analysis --- p.122 / Chapter 4.2.2.10 --- Reverse dot blot analysis --- p.123 / Chapter 4.2.2.10.1 --- Preparation of cDNA dot blot --- p.123 / Chapter 4.2.2.10.2 --- Preparation of DIG-labeled cDNA library probes --- p.124 / Chapter 4.2.2.10.3 --- Hybridization --- p.126 / Chapter 4.2.2.11 --- Northern blot analysis --- p.127 / Chapter 4.3 --- Results --- p.128 / Chapter 4.3.1 --- Fluorescent differential display (FluoroDD) --- p.128 / Chapter 4.3.2 --- Reverse dot blot analysis --- p.135 / Chapter 4.3.3 --- DNA sequencing analysis of the clones --- p.141 / Chapter 4.3.4 --- Confirmation of differential display pattern of the subclones by Northern blot analysis --- p.160 / Chapter 4.4 --- Discussion --- p.166 / Chapter Chapter 5 --- General Discussion / Chapter 5.1 --- General model for mos-induced tumor formation --- p.169 / Chapter 5.2 --- Future aspect --- p.174 / References --- p.176 / Appendix I Buffer composition --- p.186 / Appendix II Sequences of fluoroDD TMR-Anchored primers and arbitrary primers --- p.190

The cannabinoid system is involved in many functions of mammalian brain, such as learning and memory, pain perception and 'locomotion. The "brain type" cannabinoid receptor CB 1 is one of the key elements of the cannabinoid system. In this Thesis, some aspects of the neurobiology of mouse CB 1 are described. CB 1 mRNA distribution was analysed by single and double in situ hybridization (ISH), revealing the expression of the receptor in specific neuronal subpopulations. This expression pattern suggests many putative functional cross-talks between the cannabinoid system and other signalling molecules in the brain, such as glutamate, GABA, cholecystokinin and nitric oxide (NO). The putative functional interactions of the cannabinoid system with the NO pathway was studied by pharmacological treatment of neuronal NO synthase (nNOS) mutant mice with the CBI agonist A9-tetrahydrocannabinol (A9-THC). The results showed that nNOS is necessary for some central effects of A9-THC. Moreover, ISH analysis revealed. that nNOS-deficient mice contain levels of CBI lower than normal in selected brain regions. A "conditional" targeting approach was developed to gain insights into the specific functions of CB 1 in mouse brain. By gene targeting experiments, two mutant lines were obtained. The "Flox CB 1" mouse line, containing the whole open reading frame of CB I flanked by two loxP sites will be the key tool for the generation of mouse mutants with a spatiotemporal-restricted deletion of CB I. The "CBN" mice, carrying a "null" mutation of CB 1, were used for a study aimed to clarify some aspects of the in vitro neuroprotective activity of cannabinoids and, in particular, the involvement of CB 1. In vitro oxidative stress assays were performed on cell lines and on primary neuronal cultures derived from homozygous CBN/CBN mice and wild type littermates. The results indicate a differential protective activity of cannabinoids on cell lines and primary cultures. However, CBI does not appear to be involved in the in vitro leuroprotective effects of cannabinoids.

Face Detection has been applied in many fields such as surveillance, human machine interaction, entertainment and health care. Two main reasons for extensive attention on this typical research domain are: 1) a strong need for the face recognition system is obvious due to the widespread use of security, 2) face recognition is more user friendly and faster since it almost requests the users to do nothing. The system is based on ARM Cortex-A8 development board, including transplantation of Linux operating system, the development of drivers, detecting face by using face class Haar feature and Viola-Jones algorithm. In the paper, the face Detection system uses the AdaBoost algorithm to detect human face from the frame captured by the camera. The paper introduces the pros and cons between several popular images processing algorithm. Facial expression recognition system involves face detection and emotion feature interpretation, which consists of offline training and online test part. Active shape model (ASM) for facial feature node detection, optical flow for face tracking, support vector machine (SVM) for classification is applied in this research.

During the development of many diseases such as cancer and diabetes, the pattern of gene expression within certain cells changes. A vital part of understanding these diseases will come from understanding the factors governing gene expression. This thesis work focused on mining association rules in the context of gene expression. We designed and developed a tool that enables domain experts to interactively analyze association rules that describe relationships in genetic data. Association rules in their native form deal with sets of items and associations among them. But domain experts hypothesize that additional factors like relative ordering and spacing of these items are important aspects governing gene expression. We proposed hypothesis-based specializations of association rules to identify biologically significant relationships. Our approach also alleviates the limitations inherent in the conventional association rule mining that uses a support-confidence framework by providing filtering and reordering of association rules according to other measures of interestingness in addition to support and confidence. Our tool supports visualization of genetic data in the context of a rule, which facilitates rule analysis and rule specialization. The improvement in different measures of interestingness (e.g., confidence, lift, and p-value) enabled by our approach is used to evaluate the significance of the specialized rules.

There is significant variation between individual patients in the magnitude and pattern of their systemic response to cardiac surgery. Poor outcomes in these patients have been associated with a dysfunctional host response. This thesis seeks to define such variability at the level of gene expression by sequential analysis of transcription before and after surgery for a low risk group of patients undergoing elective cardiac surgery and cardiopulmonary bypass (CPB) patients using expression microarray profiling. To that aim, we analysed sequential global gene expression patterns in circulating peripheral blood leukocytes. We also investigated the role of DNA sequence variation in modulating the observed changes in gene expression. This approach allowed us to identify important genetic modulators and novel biological pathways and gain new insights into the mechanisms that regulate the host response to surgery.

Recently, large amounts of experimental data for complex biological systems have become available. We use tools and algorithms from machine learning to build data-driven predictive models. We first present a novel algorithm to discover gene sequence motifs associated with temporal expression patterns of genes. Our algorithm, which is based on partial least squares (PLS) regression, is able to directly model the flow of information, from gene sequence to gene expression, to learn cis regulatory motifs and characterize associated gene expression patterns. Our algorithm outperforms traditional computational methods e.g. clustering in motif discovery. We then present a study of extending a machine learning model for transcriptional regulation predictive of genetic regulatory response to Caenorhabditis elegans. We show meaningful results both in terms of prediction accuracy on the test experiments and biological information extracted from the regulatory program. The model discovers DNA binding sites ab intio. We also present a case study where we detect a signal of lineage-specific regulation. Finally we present a comparative study on learning predictive models for motif discovery, based on different boosting algorithms: Adaptive Boosting (AdaBoost), Linear Programming Boosting (LPBoost) and Totally Corrective Boosting (TotalBoost). We evaluate and compare the performance of the three boosting algorithms via both statistical and biological validation, for hypoxia response in Saccharomyces cerevisiae.

The purpose of this investigation was to expand the existing body of research on women's mental health outcomes, by examining the influences of conformity to feminine gender norms and womanist identity attitudes on mental health outcomes. Specifically, the present study examined whether there were patterns of womanist identity attitudes or conformity to feminine norms that were associated with higher levels of psychological well-being, and self esteem and lower levels of psychological distress. Furthermore, the study examined the combined impact of conformity to feminine norms and womanist identity attitudes on the measured mental health outcome variables. Three criterion related profile analyses were conducted entering the feminine norm subscales as predictors and psychological well-being, psychological distress and self-esteem as the criterions. Three criterion related profile analyses were conducted entering the womanist identity attitudes subscales as predictors, and the mental health outcome variables as the criterions. The results indicated that there were identified criterion patterns of conformity to feminine norms and womanist identity attitudes that were significantly related to higher levels of self-esteem, psychological well-being and lower levels of psychological distress. A cluster analysis was performed resulting in a three-cluster solution that categorized participants into groups based on similar endorsement to the predictor variables. The three cluster groups were entered into MANOVAs, which identified significant differences between the clusters on all of the measured mental health outcome variables. The findings, implications for clinical practice and future directions are discussed.

No description available.

Ma Junhao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 111-123). / Abstracts in English and Chinese. / Thesis Committee --- p.i / Statement --- p.ii / Abstract --- p.iii / Acknowledgements --- p.vii / General Abbreviations --- p.ix / Abbreviations of Chemicals --- p.xi / Table of Contents --- p.xii / List of Figures --- p.xvi / List of Tables --- p.xix / Chapter 1. --- Literature review --- p.1 / Chapter 1.1 --- Importance of amino acid metabolism --- p.1 / Chapter 1.1.1 --- Rice as the important source of essential amino acids --- p.1 / Chapter 1.1.2 --- Rice seeds are nutritionally incomplete --- p.2 / Chapter 1.1.3 --- The nitrogen source for aspartate family amino acid synthesis --- p.3 / Chapter 1.1.4 --- Synthesis of aspartate family amino acids in plants --- p.4 / Chapter 1.1.5 --- Regulation of the aspartate pathway at free amino acid level --- p.12 / Chapter 1.2 --- Regulation of amino acid metabolism during seed development --- p.14 / Chapter 1.3 --- Signalling system for nitrogen metabolism --- p.17 / Chapter 1.3.1 --- Nitrogen signalling in plants --- p.18 / Chapter 1.3.2 --- GCN signalling: another nitrogen signalling pathway --- p.21 / Chapter 1.3.2.1 --- Mechanism of GCN signalling pathway in yeast --- p.21 / Chapter 1.3.2.2 --- GCN in mammalian --- p.24 / Chapter 1.3.2.3 --- GCN in higher plant --- p.24 / Chapter 1.3.3 --- Relationship between carbon and nitrogen metabolic signaling in plants --- p.26 / Chapter 1.3.4 --- Paradigm for elucidating new signal transduction pathways --- p.29 / Chapter 1.4 --- Hypothesis of this thesis work --- p.30 / Chapter 2. --- Materials and Methods --- p.32 / Chapter 2.1. --- Materials --- p.32 / Chapter 2.1.1 --- Plants --- p.32 / Chapter 2.1.2 --- Bacterial strains and vectors --- p.32 / Chapter 2.1.3 --- Chemicals and reagents --- p.33 / Chapter 2.1.4 --- Buffer，solution and gel --- p.33 / Chapter 2.1.5 --- Commercial kits --- p.33 / Chapter 2.1.6 --- Equipments and facilities used --- p.33 / Chapter 2.1.6 --- Growth medium --- p.34 / Chapter 2.2 --- Methods --- p.34 / Chapter 2.2.1 --- Profiling genes expression pattern in developing rice seeds --- p.34 / Chapter 2.2.1.1 --- Growth conditions of rice --- p.34 / Chapter 2.2.1.2 --- Collection of developing rice seeds --- p.35 / Chapter 2.2.1.3 --- Total RNA extraction from rice seeds --- p.37 / Chapter 2.2.1.4 --- Total RNA extraction from plant leaf --- p.37 / Chapter 2.2.1.5 --- Gel electrophoresis --- p.38 / Chapter 2.2.1.6 --- First strand cDNA synthesis from rice total RNA --- p.39 / Chapter 2.2.1.7 --- Search for the coding sequence of rice genes related to amino acid metabolism --- p.39 / Chapter 2.2.1.8 --- Alignment of homologous coding sequence between family member genes --- p.42 / Chapter 2.2.1.9 --- Primer design --- p.42 / Chapter 2.2.1.10 --- Quantitation of total RNA and determination of internal control --- p.45 / Chapter 2.2.1.11 --- PCR to amplify the DNA fragments --- p.45 / Chapter 2.2.1.12 --- DNA Sequencing --- p.46 / Chapter 2.2.1.13 --- Generation and testing of single-stranded DIG-labelled DNA probes --- p.46 / Chapter 2.2.1.14 --- Northern blot --- p.47 / Chapter 2.2.1.15 --- RT-PCR (Reverse-transcription polymerase chain reaction) --- p.48 / Chapter 2.2.2 --- Expression assay of selected genes in herbicide treated plants --- p.49 / Chapter 2.2.2.1 --- Growing conditions and herbicide treatments --- p.49 / Chapter 2.2.2.2 --- GCN2 homologue in Arabidopsis and rice --- p.51 / Chapter 2.2.2.3 --- RT-PCR to analyze the change in expression level of selected genes in herbicide treated plants --- p.53 / Chapter 2.2.3 --- Generation of transgenic Arabidopsis --- p.56 / Chapter 2.2.3.1 --- Preparation of T-vector for T-ligation --- p.56 / Chapter 2.2.3.2 --- Cloning of Arabidopsis GCN2 gene --- p.56 / Chapter 2.2.3.3 --- Transformation of the plasmid into DH5a competent cell --- p.57 / Chapter 2.2.3.4 --- Screening of right recombinants --- p.58 / Chapter 2.2.3.5 --- Construction of chimeric AtGCN2 genes --- p.59 / Chapter 2.2.3.6 --- Transformation of electro-competent Agrobacterium cell --- p.60 / Chapter 2.2.3.7 --- Transformation of Arabidopsis by vacuum infiltration --- p.61 / Chapter 2.2.3.8 --- Selection of hemizygous and homozygous transgenic plants --- p.61 / Chapter 2.2.3.9 --- Screening of the T3 transformants --- p.63 / Chapter 2.2.3.10 --- Expression analysis of homozygous AtGCN2 transgenic Arabidopsis --- p.63 / Chapter 3. --- Results --- p.63 / Chapter 3.1 --- Profiling genes expression pattern in developing rice seeds --- p.63 / Chapter 3.1.1 --- Quantification of total RNA from seeds at different developing stages --- p.63 / Chapter 3.1.2 --- DNA sequence analysis --- p.66 / Chapter 3.1.3 --- Profiling the gene expression in developing rice seeds --- p.67 / Chapter 3.1.3.1 --- Expression profiles of nitrogen assimilation related genes --- p.67 / Chapter 3.1.3.2 --- Expression profiles of aspartate pathway genes --- p.72 / Chapter 3.1.3.3 --- Expression profiles of branched-chain amino acid synthesis pathway genes --- p.78 / Chapter 3.2 --- Relationship between GCN2 and amino acid metabolism in plants --- p.82 / Chapter 3.2.1 --- GCN2 homologue in A. thaliana and rice --- p.82 / Chapter 3.2.2 --- GCN2 and amino acid starvation --- p.85 / Chapter 3.2.3 --- Effects of amino acid starvation on GCN2 expression --- p.90 / Chapter 3.2.3 --- Changes in the expression level AK and BCAT genes in herbicide treated rice and A. thaliana --- p.93 / Chapter 3.3 --- Characterization of GCN2 transgenic A. thaliana --- p.96 / Chapter 3.3.1 --- Construct of pBI121-AtGCN2 --- p.96 / Chapter 3.3.2 --- Construction of GCN2 transgenic A. thaliana --- p.96 / Chapter 3.3.3 --- Expression of GCN2 in transgenic A. thaliana --- p.97 / Chapter 3.3.4 --- Expression level changes of AK and BCAT in transgenic A. thaliana --- p.99 / Chapter 4. --- Discussions --- p.101 / Chapter 4.1 --- Expression pattern of selected metabolic genes in developing plant seeds --- p.101 / Chapter 4.1.1 --- Most genes studied displayed a similar pattern --- p.101 / Chapter 4.1.2 --- Regulation of gene expression in developing rice seeds --- p.105 / Chapter 4.2 --- GCN2 and its role in higher plants --- p.106 / Chapter 4.2.1 --- The existence of the GCN2 gene in rice --- p.106 / Chapter 4.2.2 --- GCN2 responses solely to amino acid starvation --- p.106 / Chapter 5. --- Conclusion and Prospective --- p.109 / Reference --- p.111 / Appendix I: Chemicals and reagents --- p.124 / "Appendix II: Buffer, solution and gel" --- p.126 / Appendix III: Commercial kits --- p.128 / Appendix IV: Equipments and facilities used --- p.128

by Vong Puinga Queenie Maria. / "August 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 176-194). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.