The regulated differentiation and polarisation of macrophages are essential for successful wound healing process. During wound repair, macrophages are involved in the early inflammatory process of healing, as well in later regenerative phases by producing cytokines and growth factors relevant for each stage. Their plasticity made macrophages able to change their phenotype from M1 inflammatory during the inflammatory phase of healing to M2 reparative during regenerative phases of healing. Diabetes affects the ability of macrophages to mature from the bone marrow and on their ability to polarise to different phenotypic subsets. Whereas the non-diabetic macrophages can mature normally to M2 macrophages during mid-stages of healing, diabetic wound continues o display immature proinflammatory macrophages resulting in mixed M1/M2 macrophages in the wound that remain until late stages of healing. We previously showed that sustained expression of Hoxa3 reduced the-the excessive number of leukocytes recruited to the wound, suggesting an anti-inflammatory effect of Hoxa3 upon all leukocytes population. Hoxa3 protein transduction also promoted the differentiation of HSC/P into pro-angiogenic Gr1+CD11b+ myeloid cells. Here we showed that Hoxa3 promoted the differentiation of macrophages and upregulated the transcriptional machinery controlling macrophage differentiation, in THP-1 monocytes and primary macrophages from non-diabetic and diabetic mice. Using qRT-PCR and protein analysis of bone marrow derived macrophages from diabetic mice, we showed that Hoxa3 upregulated the master regulator of macrophages differentiation, Pu.1 transcriptionally and post- transcriptionally and that Hoxa3 protein interacted with Pu.1 protein in vitro and in vivo within macrophages proposing a mechanism of their regulation. Hoxa3 also inhibited proinflammatory markers in classically activated macrophages and augmented pro-healing markers in alternatively activated macrophages. Investigating the IL-4/Stat6 pathway of M2 macrophage activation revealed that Hoxa3 upregulated Stat6 and increased Stat6 phosphorylation, a novel effect of Hoxa3 on the signaling pathway of alternative macrophage activation. In vivo analysis of Hoxa3's effect on wound derived macrophages in diabetic mice, confirmed that Hoxa3 promoted the generation of pro-healing macrophages and showed reduced Nos2+ (M1) cells and increased Arg1+ (M2) cells suggesting that Hoxa3 can rescue the phenotype of diabetic macrophages in the wound. Altogether, this work has delineated the specific role of Hoxa3 in rescuing maturation and phenotype of diabetic macrophages thereby providing a better understanding of the therapeutic role of this transcription factor for myeloid cells dysregulation in diabetes.

Cheung Tsz Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 187-203). / Abstracts in English and Chinese. / Acknowledgements --- p.is / Abbreviations --- p.II / Abstracts --- p.V / List of Figures --- p.IX / List of Tables --- p.XIII / Contents / Chapter Chapter 1. --- General Introduction / Chapter 1.1 --- Cancer --- p.1 / Chapter 1.2 --- Growth Factor --- p.2 / Chapter 1.3 --- Growth Factor and Growth Factor Receptor --- p.4 / Chapter Chapter 2. --- Alteration of EGF Responses and EGFR Signaling in EGF-conditioned A431 cells / Chapter 2.1 --- Background Information / Chapter 2.1.1 --- Epidermal Growth Factor (EGF) --- p.6 / Chapter 2.1.2 --- Epidermal Growth Factor Receptor (EGFR) --- p.10 / Chapter 2.1.2.1 --- The Structure of EGFR --- p.10 / Chapter 2.1.2.2 --- The EGFR Family --- p.11 / Chapter 2.1.2.3 --- EGFR Activation --- p.13 / Chapter 2.1.3 --- The Intracellular Signal Transduction Pathways in EGFR Signaling --- p.18 / Chapter 2.1.3.1 --- The Ras/Raf/MAPK Pathway (MAPK pathway) --- p.19 / Chapter 2.1.3.2 --- The Jak/Stat Pathway --- p.23 / Chapter 2.1.3.3 --- The PI3K/Akt Pathway --- p.28 / Chapter 2.1.4 --- EGFR and Cancer --- p.31 / Chapter 2.1.5 --- EGFR-targeted Cancer Therapy --- p.35 / Chapter 2.1.5.1 --- Monoclonal Antibody (MAb) --- p.36 / Chapter 2.1.5.2 --- Immunotoxin Conjugates --- p.37 / Chapter 2.1.5.3 --- Bispecific Antibody --- p.37 / Chapter 2.1.5.4 --- Small-molecule EGFR Tyrosine Kinase Inhibitor (EGFR-TKI) --- p.38 / Chapter 2.1.5.5 --- Antisense Oligonucleotide --- p.39 / Chapter 2.2 --- Objectives --- p.41 / Chapter 2.3 --- Materials and Methods / Chapter 2.3.1 --- Materials --- p.42 / Chapter 2.3.2 --- Methods / Chapter 2.3.2.1 --- Cell Lines --- p.44 / Chapter 2.3.2.1.1 --- Establishment of Epidermal Growth Factor (EGF)-conditioned A431 Cells (EGF-conditioned Cells) ´ؤ AC Cells --- p.44 / Chapter 2.3.2.2 --- Growth Curve between A431 Parent Cells and EGF-conditioned Cells --- p.45 / Chapter 2.3.2.3 --- Epidermal Growth Factor (EGF) Sensitivity Assay --- p.45 / Chapter 2.3.2.4 --- Western Blot Analysis --- p.47 / Chapter 2.3.2.4.1 --- Protein Samples Preparation --- p.47 / Chapter 2.3.2.4.2 --- Protein Assay (by BCA Protein Assay Reagent) --- p.48 / Chapter 2.3.2.4.3 --- Protein Electrophoresis --- p.49 / Chapter 2.3.2.4.4 --- Electroblot (Protein Transfer) --- p.50 / Chapter 2.3.2.4.5 --- Antibody Probing (Immunoblotting) --- p.51 / Chapter 2.4 --- Results / Chapter 2.4.1 --- Growth Curve --- p.53 / Chapter 2.4.2 --- EGF Responses of A431 Parent Cells and EGF-conditioned Cells by MTT Assay --- p.55 / Chapter 2.4.3 --- The EGFR Expression Levels in A431 Parent Cells and EGF-conditioned Cells by Western Blot Analysis --- p.57 / Chapter 2.4.4 --- EGF-induced Protein Tyrosine Phosphorylation Pattern in A431 Parent Cells and EGF-conditioned Cells by Western Blot Analysis --- p.59 / Chapter 2.4.5 --- The Expression Profiles of EGFR Signaling Molecules in A431 Parent Cells and EGF-conditioned Cells by Western Blot Analysis --- p.61 / Chapter 2.4.5.1 --- The Ras/Raf/MAPK Pathway --- p.62 / Chapter 2.4.5.2 --- The Jak/Stat Pathway --- p.63 / Chapter 2.4.5.3 --- The PI3K/Akt Pathway --- p.64 / Chapter 2.4.6 --- The Cellular Responses to the Modifiers that Targeting the EGFR Signaling --- p.68 / Chapter 2.4.6.1 --- The Sensitivity of A431 Parent Cells and EGF-conditioned Cells to Various Signaling Modifiers --- p.69 / Chapter 2.4.6.2 --- The Influence of EGFR Signaling Modifiers on EGF --- p.76 / Chapter 2.5 --- Discussion --- p.85 / Chapter Chapter 3. --- The Inter-relationship between the Differential Anti-cancer Drugs Sensitivity and Alteration of EGFR Signaling in EGF-conditioned A431 Cells / Chapter 3.1 --- Background Information / Chapter 3.1.1 --- Drug Resistance and its Mechanisms in Tumor Cells --- p.90 / Chapter 3.1.2 --- Anti-cancer Drugs ´ؤ Introduction / Chapter 3.1.2.1 --- Camptothecin (CPT) --- p.93 / Chapter 3.1.2.2 --- Methotrexate (MTX) --- p.95 / Chapter 3.1.2.3 --- 5-fluorouracil (5-Fu) --- p.98 / Chapter 3.1.2.4 --- Vincristine (VCR) and Taxol --- p.104 / Chapter 3.1.2.5 --- Cisplatin (cis-DDP) --- p.108 / Chapter 3.2 --- Objectives --- p.110 / Chapter 3.3. --- Materials and Methods / Chapter 3.3.1 --- Materials --- p.112 / Chapter 3.3.2 --- Methods / Chapter 3.3.2.1 --- Cell Lines --- p.115 / Chapter 3.3.2.2 --- Determination of Drug Sensitivity by MTT Assay --- p.115 / Chapter 3.3.2.2.1 --- Determination the Influence of EGFR Signaling Modifiers on the Differential Anticancer Drugs Sensitivity by MTT Assay --- p.115 / Chapter 3.3.2.3 --- Semi-quantitative RT-PCR --- p.116 / Chapter 3.3.2.3.1 --- Preparation of RNA Samples --- p.116 / Chapter 3.3.2.3.2 --- RT-PCR --- p.117 / Chapter 3.3.2.4 --- DNA Fragmentation Assay --- p.118 / Chapter 3.3.2.5 --- Western Blot Analysis --- p.120 / Chapter 3.3.2.6 --- Northern Blot Analysis --- p.120 / Chapter 3.4 --- Results / Chapter 3.4.1 --- The Responses to Various Anti-cancer Drugs / Agents in A431 Parent Cells and EGF-conditioned Cells --- p.122 / Chapter 3.4.2 --- The Expressions of Classical Cellular Drug Resistant Factors in EGF-conditioning-associated Differential Anti-cancer Drugs Sensitivity --- p.126 / Chapter 3.4.2.1 --- Camptothecin Sensitivity --- p.126 / Chapter 3.4.2.2 --- Methotrexate Sensitivity --- p.130 / Chapter 3.4.2.3 --- 5-fluorouracil Sensitivity --- p.135 / Chapter 3.4.2.4 --- Vincristine and Taxol Sensitivity --- p.141 / Chapter 3.4.3 --- EGFR Signaling Modifiers and Differential Anti-cancer Drugs Sensitivity by MTT Assay --- p.143 / Chapter 3.4.3.1 --- Methotrexate --- p.143 / Chapter 3.4.3.2 --- Vincristine --- p.147 / Chapter 3.4.3.3 --- Taxol --- p.149 / Chapter 3.5 --- Discussion --- p.153 / Chapter Chapter 4. --- Identification of Differentially Expressed Genes in A431 Parent Cells and EGF-conditioned Cells by Differential Display (DD) / Chapter 4.1 --- Introduction 一 Differential Display (DD) --- p.156 / Chapter 4.2 --- Objectives --- p.160 / Chapter 4.3 --- Materials and Methods / Chapter 4.3.1 --- Materials --- p.161 / Chapter 4.3.2 --- Methods / Chapter 4.3.2.1 --- Cell Lines --- p.163 / Chapter 4.3.2.2 --- RT-PCR-based mRNA Differential Display --- p.163 / Chapter 4.3.2.2.1 --- Preparation of RNA Samples --- p.163 / Chapter 4.3.2.2.2 --- Identification of Differentially Expressed Genes by RT-PCR --- p.164 / Chapter 4.3.2.2.3 --- Reamplification of cDNA Probes --- p.164 / Chapter 4.3.2.2.4 --- Subcloning of the Differentially Expressed cDNAs --- p.165 / Chapter 4.3.2.2.4.1 --- Preparation of the Ultra-competent E.coli Cells for Transformation --- p.165 / Chapter 4.3.2.2.4.2 --- Preparation of Cloning Vector --- p.166 / Chapter 4.3.2.2.4.3 --- Transformation --- p.166 / Chapter 4.3.2.2.5 --- Verification of cDNA Differentially Expression by Colony-PCR and Northern Blot Analysis --- p.167 / Chapter 4.3.2.2.5.1 --- Colony-PCR --- p.167 / Chapter 4.3.2.2.5.2 --- Preparation of Cloned Plasmid cDNA and Bacterial Glycerol Stocks --- p.167 / Chapter 4.3.2.2.5.3 --- Preparation of cDNA Probes for Northern Blot Analysis --- p.168 / Chapter 4.3.2.2.5.4 --- Northern Blot Analysis --- p.168 / Chapter 4.3.2.2.6 --- Sequencing of the Desired Cloned cDNA Inserts --- p.170 / Chapter 4.3 --- Results --- p.171 / Chapter 4.4 --- Discussion --- p.180 / Chapter Chapter 5. --- General Conclusion and Future Perspectives / Chapter 5.1 --- General Conclusion --- p.182 / Chapter 5.2 --- Future Perspectives --- p.185 / References --- p.187

Today's society is on several levels dependent on organizations and their maintaining of work and production which demands that people can find motivation to do tasks within their workrole. This study will examine how employees in for-profit organizations is motivated to fulfill their working tasks. The purpose of this study will be answered partly by examining how employees experience motivation but also adding how employers perceive the experienced motivation. This is a qualitative comparative case-study which in addition to the central purpose also answers if there are differences and similarities about work motivation between an organization within the public and private sector. The study proceeds from several themes which is based on previous research and theory and uses a theoretical framework “intrinsic and extrinsic motivation” to delimit the study. The results shows that work motivation is something subjective and that both intrinsic and extrinsic factors affect motivation in different ways. The themes that were chosen proved to be of importance although the study illuminate that they affect people in different ways in various situations. The results of this study proved that there were many similarities between the public and private sector in what motivates employees.

"February 2002." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (p. 171-209). / 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.

In mammals, there are two isoforms of eukaryotic translation elongation factor 1A (eEF1A) called eEF1A1 and eEF1A2. They share 98% similarity at the amino acid level, and the main function of both is to facilitate the elongation process in protein translation. However, they have very different expression patterns. While eEF1A1 is universally expressed, eEF1A2 is strictly expressed in muscle, brain and heart. The over-expression of eEF1A2 has been found in cancers, such as ovarian and breast cancer. The factors influencing the different expression patterns of the two isoforms and the mechanisms by which eEF1A2 can act as an oncogene are not clear, therefore, the main aim of this study was to further investigate these two areas. The first aim was to find out whether the resveratrol induced down-regulation of eEF1A2 was mediated by miR-663. Western blotting in MCF7 cells showed that the level of endogenous eEF1A2 was decreased after resveratrol treatment while eEF1A1 remained stable. In contrast, NIH-3T3 stable cell lines which stably express the eEF1A2 coding sequence (CDS) only did not show this down-regulation, suggesting that the untranslated regions (UTRs) might play a role in this regulation. I then showed that miR-663 has ability to down-regulate a reporter linked to the UTRs of eEF1A2. The same reporter gene harbouring UTRs in which the binding sites of miR-663 had been deleted also showed down-regulation after resveratrol treatment, suggesting that the UTRs of EEF1A2 are key to the down-regulation of eEF1A2 by resveratrol but that miR-663 does not mediate this decrease. The second project aimed to address why eEF1A2 is an oncogene but eEF1A1 is not. The 3D structure of human eEF1A1 and eEF1A2 shows that the most of the highly conserved amino acids differences between the two isoforms are Ser and Thr residues, which are potential sites for phosphorylation. I mutated these three sites in eEF1A2 expression constructs to the equivalent amino acid from eEF1A1. Firstly, by transient transfection, all the mutant eEF1A2 were shown expressed and the sub-cellular locations of eEF1A2 remain unchanged after site-directed mutagenesis. Then, stable cell lines were generated. Anchorage independent growth (soft agar) and focus formation assays showed that the stable cell lines harbouring wild type eEF1A2 were significantly more transformed that those expressing the eEF1A2 mutants. However, there was no apparent difference in global protein synthesis between these cell lines. The results suggest that the potential phosphorylated sites in eEF1A2 play an important role in its oncogenicity and that this oncogenicity is not related to the canonical function of eEF1A2.

It has been long known that algae have the potential to produce a diverse range of metabolic products including lipid and starch, which could be utilized as a fuel feedstock. Despite the capacity of algae to synthesize and store large amounts of lipids and starch, algae are not currently a commercially viable feedstock for biofuel. The metabolite storage in algae can depend on the availability of nutrients such that nutrient starvation can boost the storage of lipid and carbohydrate. These nutrient-status-induced changes in lipid and starch are underpinned by altered expression of several metabolite-related genes. However, many aspects of fatty acid and carbohydrate biosynthesis are not well understood. Furthermore, the genetic regulators of nutrient starvation-induced carbohydrate and lipid accumulation are unknown in microalgae. Therefore, this PhD focused on screening cultivation conditions, in particular Phosphorus (P) and Nitrogen (N) limited conditions that induce metabolic changes, evaluated a rapid microalgal screening method, which was used to identify putative metabolism regulators, and characterized in detail the role of one P-starvation regulator, called PSR1 (Phosphorus starvation response 1). For establishing suitable culture conditions, the microalga Chlamydomonas reinhardtii was cultured in five different P and N-limited conditions and screened for metabolic changes using Fourier transform infrared spectroscopy (FT-IR) at different phases of growth. The FT-IR spectral changes were visualized by multivariate statistical tools such as principal component analysis (PCA) and principal component-discriminant function analysis (PC-DFA). Clear clustering based on nutrient availability and metabolic changes demonstrates the potential and sensitivity of FT-IR in screening multiple culture conditions. The potential of FT-IR was further tested by screening mutant strains of C. reinhardtii that were defective in response to nutrient starvation. Nine lines with mutation in one or more of the PSR1, SNRK2.1 or SNRK2.2 genes and a wild type were screened by FT-IR for P and N starvation-induced metabolic changes. PCA, PC-DFA and predictive partial least squares discriminant analysis (PLS-DA) of FT-IR spectra, clearly distinguished wild type from mutant strains and clustered mutants with similar genetic backgrounds, demonstrating the potential of FT-IR to detect and differentiate specific genetic traits. The changes in lipid and carbohydrate profile under nutrient stress and in the different strains were validated by biochemical analysis and liquid chromatography-mass spectrometry (LC-MS).This thesis demonstrated that PSR1 is an important regulator of neutral lipid and starch biosynthesis. Transcriptomic analysis on wild type and psr1 mutant under P-starvation was performed to identify transcripts induced by P-starvation that were mis-regulated in psr1. Mainly transcripts encoding starch and triacylglycerol enzymes were affected. To further evaluate the role of PSR1 in regulating lipid and starch metabolism, complementation of psr1 and overexpression by PSR1 was performed. The P-starvation phenotype was clearly rescued in the complementation lines, and overexpression lines showed increased expression of P homeostasis genes and increased Pi accumulation in cells, with an increase in total starch content and number of starch granules. Clear increases in expression of key starch biosynthesis genes such as soluble starch synthase (SSS1, SSS5) and starch phosphorylase (SP1) was observed, which correlated with increased starch content in the overexpression lines. A carbon shift was observed as a decrease in neutral lipid was coupled with the increase in starch content. All together these findings suggest that PSR1 is a key transcriptional regulator of global metabolism, and demonstrated successful transcriptional engineering of microalgae.

Eukaryotic Elongation Factor 1A (eEF1A) exists in two forms in vertebrates. The first form, eEF1A1, is expressed ubiquitously throughout development but is downregulated postdevelopmentally and replaced with eEF1A2, an isoform sharing 92% amino acid identity, in neurons and muscle. The primary function of eEF1A is to recruit amino-acylated tRNAs in a GTP-dependent manner to the A site of the ribosome during protein translation, but it also has non-canonical roles in the cell, some of which are isoform dependent. The reasons for the cell-type dependent switch from eEF1A1 to eEF1A2 are poorly understood. The first aim of this project was to examine the role played by eEF1A isoforms in neuritogenesis. To do this I used RNAi to significantly reduce expression of one or other isoform in neuronal cells and measure the effects this had on neurite outgrowth. Neurite outgrowth was significantly reduced in cells depleted of eEF1A1, but not eEF1A2. The complete loss of eEF1A2 is fatal, as has been demonstrated in the wasted mouse, an eEF1A2-null model characterised by muscle wastage, neurodegeneration and death at 4 weeks of age. Mice heterozygous for the wasted mutation have normal motor function. Recent work has found that heterozygous missense mutations in eEF1A2 can cause epilepsy and intellectual disability. It is not yet known whether the seven different de novo mutations identified to date confer loss or gain of function – a crucial piece of information required before possible treatments can be sought. The second aim of this project therefore was to investigate the role of eEF1A2 in epilepsy and intellectual disability. I achieved this by using CRISPR in two ways; firstly to model one of the mutations, D252H, in vitro in a neuronal cell line, and secondly to model another of the mutations, G70S, in vivo. No mice that recapitulated the human disease condition of EEF1A2G70S/+ were obtained however, due to the error-prone nature of the non-homologous end joining repair pathway activated by CRISPR-mediated DNA cleavage, 17 of the 35 mice born were found to be homozygous nulls at the Eef1a2 locus. Nine of these had fatal audiogenic seizures caused by sudden loud noises within the animal unit. Three mice were Eef1a2G70S/- and one Eef1a2G70S/G70S but these nonetheless showed a wasted phenotype, indicating that this mutant form of eEF1A2 has compromised function, at least in terms of translation elongation. Whether it has a toxic function ca not yet be known, but the severity of the phenotype in the G70S homozygous animal could suggest a gain of function. In in vitro experiments with exogenous eEF1A2 carrying the epilepsy-causing mutation R423C, protein expression of the mutant construct in immortalised cell lines was significantly higher when cotransfected with the wildtype construct, which mirrors the condition in humans, than when transfected alone, so the mutant protein could be stabilised in the presence of wildtype eEF1A2. I used CRISPR on LUHMES cells to make a mutant neuronal cell line containing the D252H mutation in eEF1A2. Due to time restraints no phenotypic differences between the wild type line and the D252H mutation line have yet been identified, but would form the focus of a future project.

SR蛋白在前體信使核糖核酸(pre-mRNA)的組成性剪接和選擇性剪接中扮演者重要的角色，在這個過程中它需要被SR蛋白激酶(SRPK) 燐酸化才能正常行使功能。經典的SR蛋白是由N端一到二個RNA識別基序(RRM) 以及C端一串精氨酸－絲氨酸(RS) 二肽所構成。SR蛋白的燐酸化調控它的亞細胞定位以及生理功能。此外，SR 蛋白激酶1(SRPK1) 和SR蛋白原型ASF/SF2的復合物結構顯示底物的結合需要第二個非標準的RRM結構域以及在N端可以被燐酸化的RS結構域，但是，第一個標準的RRM結構域對於SR 蛋白激酶1的結合卻是可以或缺的。 / 在這裡，我們展示了SR蛋白激酶2(SRPK2) 結合並且燐酸化SRp20的RS結構域，SRp20是另外一個只包含一個RNA識別基序(RRM) 的SR蛋白。與ASF/SF2相似的是，SRp20中的標準RNA識別基序對於SRPK2的結合並不是必要的。與此同時，我們發現錨定槽對於底物的識別作用在SRPK2中也是保守的，因為，錨定槽中四個關鍵氨基酸的突變會削弱它對SRp20的結合。 / 此外，現在認為SRPK2的功能已經不限於對前體信使核糖核酸(pre-mRNA) 的剪接調控。最近發現，SRPK2也可以燐酸化Tau蛋白並且介導阿爾茨海默疾病中的認知性缺陷。組成性的激活是SR蛋白激酶中的一個固有特性，然而人們對於它的調控機制還不是很清楚。因此, 為了更好的瞭解SRPK2，我們采用酵母雙雜交的方法並且最終發現一個新的SRPK2相互作用蛋白: ZNF187。 / ZNF187是一個可以結合血清反應元件(SRE) 的轉綠因子。我們的研究發現，它可以正向調控SRE的轉錄激活。然而，SRPK2在EGF的刺激下卻起着抑制的效果，其中EGF的刺激會促使SRPK2進入細胞核。進一步證實，通過RNAi干擾的方法敲掉SRPK2可以增加ZNF187誘導的SRE活性。在共轉染實驗中，SRPK2可以把ZNF187誘導的SRE活性逆轉到本底水平。對於可以和EGF刺激的SRPK2有着相似細胞定位的缺失或者突變研究發現，它們都可以產生相一致的抑制現象。於此相反，對於和SRPK2有着不同細胞定位的突變，它卻不能產生抑制效果。因此，我們認為在EGF的刺激下，SRPK2進入細胞核並且負向的調控ZNF187激活的SRE。令人驚訝的是，如果細胞在FBS的刺激下，SRPK2卻上調SRE活性，並且它可以協同增加ZNF187對於SRE的誘導。這些結果表明SRPK2對於ZNF187誘導的SRE轉綠調控是刺激物依賴的。 / SR proteins are critical players in regulating both constitutive and alternative pre-mRNA splicing, during which the phosphorylation by SR Protein Kinases (SRPKs) is required. Classical SR proteins contain one or two RNA Recognition Motifs (RRM) in their N terminus and a stretch of Arginine-Serine (RS) dipeptides in C terminus. Phosphorylation status of SR proteins regulates their subcellular localization as well as physiological function. In addition, complex structure of SRPK1 with ASF/SF2, a prototype of SR protein, shows that substrate binding requires non-canonicalRRM2 domain and RS domain, which can be extensivelyphosphorylated. However, the canonical RRM1 domain is dispensable for such interaction. / Here we show that SRPK2 binds and phosphorylates SRp20, a classical single RRM domain-containing SR protein, at its RS domain. Similarly with ASF/SF2, the canonical RRM domain of SRp20 is dispensable for interacting with SRPK2. Meanwhile, we also find that a docking groove that iscritical for substrate binding in SRPK1 is also conserved in SRPK2, since mutations on four key residues in docking groove impair its binding affinity with SRp20. / In addition, SRPK2 is now known to function more then regulating mRNA splicing, such as cell proliferation and cell apoptosis. Recently, SRPK2 is also shown to be a kinase phosphorylating Tau and mediate the cognitive defects in Alzheimer’s disease (AD). Besides, an intrinsic character of SRPKs lies in that they are constitutively active, but the regulation mechanism is not well understood. Therefore, in order to obtain a better recognition about SRPK2, we applied yeast two-hybrid assay and eventually anew interaction partner called ZNF187 was identified. / ZNF187 is a transcriptional factor that binds with Serum Response Element (SRE). Our studies showed that it isa positive regulator of SRE activity. However, SRPK2 showed inhibiting effect on SRE activation with the treatment of EGF, which could induce its nucleus entry, when co-transfected, it reversed the stimulating effect on SRE by ZNF187 to basal level. Furthermore, knockdown of SRPK2 by RNAi would enhance ZNF187-stimuated SRE activation. Studies on truncation and mutations that have the similar effect with EGF-induced subcellular localization of SRPK2 also generated the same inhibiting phenomenon. In contrast, mutant that has distinct localization with SRPK2 wild type failed to exert suppression. Therefore, we conclude that with the treatment of EGF, SRPK2 moves into nucleus and negatively regulates ZNF187-stimulated transactivation of SRE. Surprisingly, when cells were treated with FBS, SRPK2 showed stimulation on SRE activity and it synergized ZNF187-stimulated effect on SRE, indicating that transcriptional regulation of SRPK2 on ZNF187-stimulated SRE activity is stimuli-dependent. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Shang, Yong. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 113-137). / Abstracts also in Chinese.

by Lai-pang Law. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 148-182). / ABSTRACT / LIST OF ILLUSTRATIONS / LIST OF TABLES / ACKNOWLEDGEMENTS / ABBREVIATIONS / Chapter CHAPTER I --- INTRODUCTION --- p.1 / Chapter CHAPTER II --- LITERATURE REVIEW --- p.4 / Chapter 2.1 --- The uterus and its changes in the normal menstrual cycle / Chapter 2.2 --- Anatomy and physiology of normal myometrium / Chapter 2.3 --- Clinical features and management of uterine leiomyoma / Chapter 2.4 --- Pathology of human uterine leiomyoma / Chapter 2.5 --- The relationship between growth fractions and ER in breast carcinoma / Chapter 2.6 --- Steroid receptors and epidermal growth factor receptor / Chapter 2.6.1 --- Steroid receptors / Chapter 2.6.2 --- Epidermal growth factor receptor / Chapter 2.7 --- "Structures of oestrogen receptor, progesterone receptor, Ki-67 and epidermal growth factor receptor" / Chapter 2.7.1 --- The structure of oestrogen receptor / Chapter 2.7.2 --- The structure of progesterone receptor / Chapter 2.7.3 --- The structure of Ki-67 / Chapter 2.7.4 --- The structure of epidermal growth factor receptor / Chapter 2.8 --- "Antibodies to steroid receptors, monoclonal Ki-67 and epidermal growth factor receptor" / Chapter 2.8.1 --- Steroid receptors / Chapter 2.8.2 --- Monoclonal Ki-67 / Chapter 2.8.3 --- Epidermal growth factor receptor / Chapter 2.9 --- "Functions of steroid receptors, Ki-67 and epidermal growth factor receptor" / Chapter 2.9.1 --- The functions of steroid receptors / Chapter 2.9.2 --- The functions of Ki-67 / Chapter 2.9.3 --- The functions of epidermal growth factor receptor / Chapter 2.10 --- Cell cycle / Chapter 2.11 --- Immunohistochemistry / Chapter 2.11.1 --- Introduction / Chapter 2.11.2 --- Methodology of immunostaining / Chapter 2.11.3 --- Avidin-biotin-peroxidase complex technique / Chapter 2.11.4 --- Chromogens / Chapter 2.11.5 --- Enhancement methods / Chapter 2.11.6 --- Fixation for immunohistochemistry / Chapter CHAPTER III --- MATERIALS AND METHODS --- p.63 / Chapter 3.1 --- Reagents and chemicals / Chapter 3.1.1 --- Primary monoclonal antibodies / Chapter 3.1.2 --- Secondary antibodies / Chapter 3.1.3 --- Avidin-biotin complex / Chapter 3.1.4 --- DAB solution / Chapter 3.1.5 --- Buffers / Chapter 3.1.6 --- Miscellaneous / Chapter 3.2 --- Patients and specimens / Chapter 3.2.1 --- Specimen collection / Chapter 3.2.2 --- Preparation of specimens / Chapter 3.3 --- Immunohistochemical staining / Chapter 3.3.1 --- Slide preparation / Chapter 3.3.2 --- Antigen retrieval / Chapter 3.3.3 --- Procedures of immunohistochemical staining / Chapter 3.3.4 --- Interpretation of immunostaining / Chapter CHAPTER IV --- RESULTS --- p.80 / Chapter 4.1 --- Clinical information / Chapter 4.2 --- Oestrogen receptor / Chapter 4.3 --- Progesterone receptor / Chapter 4.4 --- Epidermal growth factor receptor / Chapter 4.5 --- Ki-67 / Chapter CHAPTER V --- DISCUSSION --- p.120 / Chapter 5.1 --- Methods and interpretation of the results / Chapter 5.1.1 --- The advantages of the immunohistochemical staining technique / Chapter 5.1.2 --- Interpretation and reporting of immunohistochemical results / Chapter 5.1.3 --- Interpretation of the results by semi- quantitative assessment and statistical analysis / Chapter 5.2 --- The status of steroid receptors in uterine leiomyoma / Chapter 5.2.1 --- ER status in uterine leiomyoma and normal myometrium / Chapter 5.2.2 --- PR status in uterine leiomyoma and normal myometrium / Chapter 5.3 --- EGF-R status in uterine leiomyoma / Chapter 5.4 --- Ki-67 status in uterine leiomyoma and normal myometrium / Chapter 5.5 --- "The relationship between steroid receptors, Ki-67, EGF-R and uterine leiomyoma growth" / Chapter 5.6 --- Biological indices in the assessment of tumor / Chapter 5.7 --- Microwave technology in immunohistology for surgical pathology / Chapter CHAPTER VI --- CONCLUSIONS --- p.144 / REFERENCES --- p.148

by Jian-Qing Shi. / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 118-123). / Chapter Chapter 1. --- Introduction and overview --- p.1 / Chapter Chapter 2. --- General methodology --- p.8 / Chapter Chapter 3. --- A Bayesian approach to confirmatory factor analysis --- p.16 / Chapter 3.1 --- Confirmatory factor analysis model and its prior --- p.16 / Chapter 3.2 --- The algorithm of data augmentation --- p.19 / Chapter 3.2.1 --- Data augmentation and one-run method --- p.19 / Chapter 3.2.2 --- Rao-Blackwellized estimation --- p.22 / Chapter 3.3 --- Asymptotic properties --- p.28 / Chapter 3.3.1 --- Asymptotic normality and posterior covariance matrix --- p.28 / Chapter 3.3.2 --- Goodness-of-fit statistic --- p.31 / Chapter Chapter 4. --- Bayesian inference for structural equation models --- p.34 / Chapter 4.1 --- LISREL Model and prior information --- p.34 / Chapter 4.2 --- Algorithm and conditional distributions --- p.38 / Chapter 4.2.1 --- Data augmentation algorithm --- p.38 / Chapter 4.2.2 --- Conditional distributions --- p.39 / Chapter 4.3 --- Posterior analysis --- p.44 / Chapter 4.3.1 --- Rao-Blackwellized estimation --- p.44 / Chapter 4.3.2 --- Asymptotic properties and goodness-of-fit statistic --- p.45 / Chapter 4.4 --- Simulation study --- p.47 / Chapter Chapter 5. --- A Bayesian estimation of factor score with non-standard data --- p.52 / Chapter 5.1 --- General Bayesian approach to polytomous data --- p.52 / Chapter 5.2 --- Covariance matrix of the posterior distribution --- p.61 / Chapter 5.3 --- Data augmentation --- p.65 / Chapter 5.4 --- EM algorithm --- p.68 / Chapter 5.5 --- Analysis of censored data --- p.72 / Chapter 5.5.1 --- General Bayesian approach --- p.72 / Chapter 5.5.2 --- EM algorithm --- p.76 / Chapter 5.6 --- Analysis of truncated data --- p.78 / Chapter Chapter 6. --- Structural equation model with continuous and polytomous data --- p.82 / Chapter 6.1 --- Factor analysis model with continuous and polytomous data --- p.83 / Chapter 6.1.1 --- Model and Bayesian inference --- p.83 / Chapter 6.1.2 --- Gibbs sampler algorithm --- p.85 / Chapter 6.1.3 --- Thresholds parameters --- p.89 / Chapter 6.1.4 --- Posterior analysis --- p.92 / Chapter 6.2 --- LISREL model with continuous and polytomous data --- p.94 / Chapter 6.2.1 --- LISREL model and Bayesian inference --- p.94 / Chapter 6.2.2 --- Posterior analysis --- p.101 / Chapter 6.3 --- Simulation study --- p.103 / Chapter Chapter 7. --- Further development --- p.108 / Chapter 7.1 --- More about one-run method --- p.108 / Chapter 7.2 --- Structural equation model with censored data --- p.111 / Chapter 7.3 --- Multilevel structural equation model --- p.114 / References --- p.118 / Appendix --- p.124 / Chapter A.1 --- The derivation of conditional distribution --- p.124 / Chapter A.2 --- Generate a random variate from normal density which restricted in an interval --- p.129 / Tables --- p.132 / Figures --- p.155