150 resultados para Gene Therapy -- methods


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The molecular mechanism between atherosclerosis formation and periodontal pathogens is not clear although positive correlation between periodontal infections and cardiovascular diseases has been reported. Objective: To determine if atherosclerosis related genes were affected in foam cells during and after its formation by P. gingivalis lipopolysaccharide (LPS) stimulation. Methods: Macrophages from human THP-1 monocytes were treated with oxidized low density lipoprotein (oxLDL) to induce the formation of foam cells. P. gingivalis LPS was added to cultures of either oxLDL-induced macrophages or foam cells. The expression of atherosclerosis related genes was assayed by quantitative real time PCR and the protein production of granulocyte-macrophage colony-stimulating factor(GM-CSF), monocyte chemotactic protein-1 (MCP-1), IL-1β, IL-10 and IL-12 was determined by ELISA. Nuclear translocation of NF-κB P65 was detected by immunocytochemistry and western blot was used to evaluate IKB-α degradation to confirm the NF-κB pathway activation. Results: P. gingivalis LPS stimulated atherosclerosis related gene expression in foam cells and increased oxLDL induced expression of chemokines, adhesion molecules, growth factors, apoptotic genes, and nuclear receptors in macrophages. Transcription of the pro-inflammatory cytokines IL-1β and IL-12 was elevated in response to LPS in both macrophages and foam cells, whereas the anti-inflammatory cytokine IL-10 was not affected. Increased NF-κB pathway activation was also observed in LPS and oxLDL co-stimulated macrophages. Conclusion: P. gingivalis LPS appears to be an important factor in the development of atherosclerosis by stimulation of atherosclerosis related gene expression in both macrophages and foam cells via activation of the NF-κB pathway.

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Introduction and aims: For a scaffold material to be considered effective and efficient for tissue engineering it must be biocompatible as well as bioinductive. Silk fiber is a natural biocompatible material suitable for scaffold fabrication; however, silk is tissue-conductive and lacks tissue-inductive properties. One proposed method to make the scaffold tissue-inductive is to introduce plasmids or viruses encoding a specific growth factor into the scaffold. In this study, we constructed adenoviruses encoding bone morphogenetic protein-7 (BMP-7) and incorporated these into silk scaffolds. The osteo-inductive and new bone formation properties of these constructs were assessed in vivo in a critical-sized skull defect animal model. Materials and methods: Silk fibroin scaffolds containing adenovirus particles coding BMP-7 were prepared. The release of the adenovirus particles from the scaffolds was quantified by tissue-culture infective dose (TCID50) and the bioactivity of the released viruses was evaluated on human bone marrow mesenchymal stromal cells (BMSCs). To demonstrate the in vivo bone forming ability of the virus-carrying silk fibroin scaffold, the scaffold constructs were implanted into calvarial defects in SCID mice. Results: In vitro studies demonstrated that the virus-carrying silk fibroin scaffold released virus particles over a 3 week period while preserving their bioactivity. In vivo test of the scaffold constructs in critical-sized skull defect areas revealed that silk scaffolds were capable of delivering the adenovirus encoding BMP-7, resulting significantly enhanced new bone formation. Conclusions: Silk scaffolds carrying BMP-7 encoding adenoviruses can effectively transfect cells and enhance both in vitro and in vivo osteogenesis. The findings of this study indicate silk fibroin is a promising biomaterial for gene delivery to repair critical-sized bone defects.

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Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

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In the analysis of medical images for computer-aided diagnosis and therapy, segmentation is often required as a preliminary step. Medical image segmentation is a complex and challenging task due to the complex nature of the images. The brain has a particularly complicated structure and its precise segmentation is very important for detecting tumors, edema, and necrotic tissues in order to prescribe appropriate therapy. Magnetic Resonance Imaging is an important diagnostic imaging technique utilized for early detection of abnormal changes in tissues and organs. It possesses good contrast resolution for different tissues and is, thus, preferred over Computerized Tomography for brain study. Therefore, the majority of research in medical image segmentation concerns MR images. As the core juncture of this research a set of MR images have been segmented using standard image segmentation techniques to isolate a brain tumor from the other regions of the brain. Subsequently the resultant images from the different segmentation techniques were compared with each other and analyzed by professional radiologists to find the segmentation technique which is the most accurate. Experimental results show that the Otsu’s thresholding method is the most suitable image segmentation method to segment a brain tumor from a Magnetic Resonance Image.

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BACKGROUND Endometriosis is a polygenic disease with a complex and multifactorial aetiology that affects 8-10% of women of reproductive age. Epidemiological data support a link between endometriosis and cancers of the reproductive tract. Fibroblast growth factor receptor 2 (FGFR2) has recently been implicated in both endometrial and breast cancer. Our previous studies on endometriosis identified significant linkage to a novel susceptibility locus on chromosome 10q26 and the FGFR2 gene maps within this linkage region. We therefore hypothesized that variation in FGFR2 may contribute to the risk of endometriosis. METHODS We genotyped 13 single nucleotide polymorphisms (SNPs) densely covering a 27 kb region within intron 2 of FGFR2 including two SNPs (rs2981582 and rs1219648) significantly associated with breast cancer and a total 40 tagSNPs across 150 kb of the FGFR2 gene. SNPs were genotyped in 958 endometriosis cases and 959 unrelated controls. RESULTS We found no evidence for association between endometriosis and FGFR2 intron 2 SNPs or SNP haplotypes and no evidence for association between endometriosis and variation across the FGFR2 gene. CONCLUSIONS Common variation in the breast-cancer implicated intron 2 and other highly plausible causative candidate regions of FGFR2 do not appear to be a major contributor to endometriosis susceptibility in our large Australian sample.

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Sing & Grow is an early intervention music therapy project that provides community group music therapy programs to families with young children who encounter risk factors that may impact on parenting and optimal child develop variety of evaluation tools were devised and used over the first 3 years of the project. Upon the subsequent funding and expansion of the project at the end of this period, it was necessary to find, test and devise more rigorous, valid and reliable measures to withstand the scrutiny of researchers, and to combat the concerns and criticisms associated with the previous methods of data collection. An action inquiry project was therefore undertaken with two groups of project participants to trial the use of the Parenting Stress Index and Depression, Anxiety and Stress Scales, both recommended by leading psychologists. Key findings that will be discussed include the friction between the deficit-focussed nature of many psychometric tools and the strengths-based approach taken in service delivery, the level of difficulty in terms of literacy and comprehension for vulnerable respondents, and the lack of one tool with the ability to comprehensively measure all aspects of a broad scoping program. Keywords: music therapy, evaluation, PSI, DASS, action inquiry.

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The Cancer Genome Project intends to search every human gene for cancer-related mutations. Its first success is the discovery of such mutations in the BRAF gene.

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Aims:  The primary objective was to describe the usage pattern of hormone therapy (HT) in a sample of urban Australian women in 2001 and to assess the characteristics of users vs. non-users. The second objective was to determine whether there had been any change in usage since the publication of the results of the combined oestrogen plus progestagen arm of the Women's Health Initiative (WHI) in 2002. Methods:  A cohort of 374 postmenopausal women aged 50–80 years participated in this substudy of the LAW (Longitudinal Assessment of Ageing in Women) project: a 5-year multidisciplinary, observational study. Participants completed an annual medical assessment including details of the use of HT and the reasons for use, as well as demographic and psychosocial data. Results:  In December 2001, 30.8% of the participants were using HT, whereas 55.4% were ever users. The management of vasomotor symptoms and mood disturbance were the primary reasons for use. Of those who had been using HT in December 2001 (24.4%) women ceased using HT in the 3 months following publication of the WHI results. The percentage of women using HT in December 2003 (13.9%) was less than half of that of December 2001. Conclusion:  The rate of HT use and the reasons for use, in 2001 in Brisbane was similar to that of other Australian regions. Usage of HT decreased since the publication of the WHI results in 2002 which may reflect changing attitudes by patients and practitioners regarding HT.

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Methodological differences among studies of vasomotor symptoms limit rigorous comparison or systematic review. Vasomotor symptoms generally include hot flushes and night sweats although other associated symptoms exist. Prevalence rates vary between and within populations, but different studies collect data on frequency, bothersomeness, and/or severity using different outcome measures and scales, making comparisons difficult. We reviewed only cross-cultural studies of menopausal symptoms that explicitly examined symptoms in general populations of women in different countries or different ethnic groups in the same country. This resulted in the inclusion of nine studies: Australian/Japanese Midlife Women's Health Study (AJMWHS), Decisions At Menopause Study (DAMeS), Four Major Ethnic Groups (FMEG), Hilo Women's Health Survey (HWHS), Mid-Aged Health in Women from the Indian Subcontinent (MAHWIS), Penn Ovarian Aging Study (POAS), Study of Women's Health Across the Nation (SWAN), Women's Health in Midlife National Study (WHiMNS), and Women's International Study of Health and Sexuality (WISHeS). These studies highlight the methodological challenges involved in conducting multi-population studies, particularly when languages differ, but also highlight the importance of performing multivariate and factor analyses. Significant cultural differences in one or more vasomotor symptoms were observed in 8 of 9 studies, and symptoms were influenced by the following determinants: menopausal status, hormones (and variance), age (or actually, the square of age, age2), BMI, depression, anxiety, poor physical health, perceived stress, lifestyle factors (hormone therapy use, smoking and exposure to passive smoke), and acculturation (in immigrant populations). Recommendations are made to improve methodological rigor and facilitate comparisons in future cross-cultural menopause studies.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

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Currently in the Australian higher education sector, the productivity benefits of occupational therapy clinical education placements are a contested issue. This article will report results of a study that developed a methodology for documenting time use during placements and investigated the productivity changes associated with occupational therapy clinical education placements in Queensland, Australia. Supervisors’ and students’ time use during placements and how this changed for supervisors compared to pre- and post-placement is also presented. Methods: Using a cohort survey design, participants were students from two Queensland universities, and their supervisors employed by Queensland Health. Time use was recorded in 30 minute blocks according to particular categories. Results: There was a significant increase in supervisors’ time spent in patient care activities (F = 94.0112,12.37 df, P < 0.001) between pre- and during placement (P < 0.001) and decrease between during and post-placement (P < 0.001). Supervisors’ time spent in all non-patient care activities was also significant (F = 4.5802,16 df, P = 0.027) increasing between pre- and during placement (P = 0.028). There was a significant decrease in supervisors’ time spent in placement activities (F = 5.1332,19.18 df, P = 0.016) from during to post-placement. Students spent more time than supervisors in patient care activities while on placement. Discussion: A novel method for reporting productivity and time-use changes during clinical education programs for occupational therapy has been applied. Supervisors spent considerable time in assessing and managing students and their clinical education role should be seen as core business in standard occupational therapy practice. This paper will contribute to future assessments of the economic.

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Background Late stage Ovarian Cancer is essentially incurable primarily due to late diagnosis and its inherent heterogeneity. Single agent treatments are inadequate and generally lead to severe side effects at therapeutic doses. It is crucial to develop clinically relevant novel combination regimens involving synergistic modalities that target a wider repertoire of cells and lead to lowered individual doses. Stemming from this premise, this is the first report of two- and three-way synergies between Adenovirus-mediated Purine Nucleoside Phosphorylase based gene directed enzyme prodrug therapy (PNP-GDEPT), docetaxel and/or carboplatin in multidrug-resistant ovarian cancer cells. Methods The effects of PNP-GDEPT on different cellular processes were determined using Shotgun Proteomics analyses. The in vitro cell growth inhibition in differentially treated drug resistant human ovarian cancer cell lines was established using a cell-viability assay. The extent of synergy, additivity, or antagonism between treatments was evaluated using CalcuSyn statistical analyses. The involvement of apoptosis and implicated proteins in effects of different treatments was established using flow cytometry based detection of M30 (an early marker of apoptosis), cell cycle analyses and finally western blot based analyses. Results Efficacy of the trimodal treatment was significantly greater than that achieved with bimodal- or individual treatments with potential for 10-50 fold dose reduction compared to that required for individual treatments. Of note was the marked enhancement in apoptosis that specifically accompanied the combinations that included PNP-GDEPT and accordingly correlated with a shift in the expression of anti- and pro-apoptotic proteins. PNP-GDEPT mediated enhancement of apoptosis was reinforced by cell cycle analyses. Proteomic analyses of PNP-GDEPT treated cells indicated a dowregulation of proteins involved in oncogenesis or cancer drug resistance in treated cells with accompanying upregulation of apoptotic- and tumour- suppressor proteins. Conclusion Inclusion of PNP-GDEPT in regular chemotherapy regimens can lead to significant enhancement of the cancer cell susceptibility to the combined treatment. Overall, these data will underpin the development of regimens that can benefit patients with late stage ovarian cancer leading to significantly improved efficacy and increased quality of life.

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Purpose: To determine whether uniform guidelines and training in the stabilization and formation of thermoplastic shells can improve the reproducibility of set-up for Head and Neck cancer patients. Methods and materials: Image based measurements of the planning and treatment positions for 35 head and neck cancer patients undergoing radical radiotherapy were analysed to provide a baseline of the reproducibility of thermoplastic immobilization. Radiation therapists (RT) were surveyed to establish a perception of their confidence in thermoplastic procedures. An evidence based staff training program was created and implemented. Set-up reproduction and staff perception were reviewed to measure the impact of the training program. Results: The mean (SD) 3D vectors of anatomical displacement, measured on the patient images, improved from 4.64 (2.03) for the baseline group compared to 3.02 (1.65) following training (p < 0.01). The proportion of 3D displacements of patient data exceeding 5 mm 3D vector was decreased from 37.1% to 5.7% (p < 0.001) and the 3 mm vector from 85.7% to 42.9% (p < 0.001). The post-training survey scores demonstrated improved confidence in reproducibility of set-up for head and neck patients. Conclusion: The Thermoplastic Shells Training Program has been found to improve the treatment reproducibility for head and neck radiation therapy patients. Uniform guidelines have increased RT confidence in thermoplastic procedures.

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BACKGROUND: Stromal signalling increases the lateral cell adhesions of prostate epithelial cells grown in 3D culture. The aim of this study was to use microarray analysis to identify significant epithelial signalling pathways and genes in this process. METHODS: Microarray analysis was used to identify genes that were differentially expressed when epithelial cells were grown in 3D Matrigel culture with stromal co-culture compared to without stroma. Two culture models were employed: primary epithelial cells (ten samples) and an epithelial cell line (three experiments). A separate microarray analysis was performed on each model system and then compared to identify tissue-relevant genes in a cell line model. RESULTS: TGF beta signalling was significantly ranked for both model systems and in both models the TGF beta signalling gene SOX4 was significantly down regulated. Analysis of all differentially expressed genes to identify genes that were common to both models found several morphology related gene clusters; actin binding (DIAPH2, FHOD3, ABLIM1, TMOD4, MYH10), GTPase activator activity (BCR, MYH10), cytoskeleton (MAP2, MYH10, TMOD4, FHOD3), protein binding (ITGA6, CD44), proteinaceous extracellular matrix (NID2, CILP2), ion channel/ ion transporter activity (CACNA1C, CACNB2, KCNH2, SLC8A1, SLC39A9) and genes associated with developmental pathways (POFUT1, FZD2, HOXA5, IRX2, FGF11, SOX4, SMARCC1). CONCLUSIONS: In 3D prostate cultures, stromal cells increase lateral epithelial cell adhesions. We show that this morphological effect is associated with gene expression changes to TGF beta signalling, cytoskeleton and anion activity.