235 resultados para galaxies : luminosity function, mass function

em Queensland University of Technology - ePrints Archive


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To date, attempts to regenerate a complete tooth, including the critical periodontal tissues associated with the tooth root, have not been successful. Controversy still exists regarding the origin of the cell source for cellular cementum (epithelial or mesenchymal). This disagreement may be partially due to a lack of understanding of the events leading to the initiation and development of the tooth roots and supportive tissues, such as the cementum. Osterix (OSX) is a transcriptional factor essential for osteogenesis, but its role in cementogenesis has not been addressed. In the present study, we first documented a close relationship between the temporal- and spatial-expression pattern of OSX and the formation of cellular cementum. We then generated 3.6 Col 1-OSX transgenic mice, which displayed accelerated cementum formation vs. WT controls. Importantly, the conditional deletion of OSX in the mesenchymal cells with two different Cre systems (the 2.3 kb Col 1 and an inducible CAG-CreER) led to a sharp reduction in cellular cementum formation (including the cementum mass and mineral deposition rate) and gene expression of dentin matrix protein 1 (DMP1) by cementocytes. However, the deletion of the OSX gene after cellular cementum formed did not alter the properties of the mature cementum as evaluated by backscattered SEM and resin-cast SEM. Transient transfection of Osx in the cementoblasts in vitro significantly inhibited cell proliferation and increased cell differentiation and mineralization. Taken together, these data support 1) the mesenchymal origin of cellular cementum (from PDL progenitor cells); 2) the vital role of OSX in controlling the formation of cellular cementum; and 3) the limited remodeling of cellular cementum in adult mice.

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Purpose Exercise for Health was a randomized, controlled trial designed to evaluate two modes of delivering (face-to-face [FtF] and over-the-telephone [Tel]) an 8-month translational exercise intervention, commencing 6-weeks post-breast cancer surgery (PS). Methods Outcomes included quality of life (QoL), function (fitness and upper-body) and treatment-related side effects (fatigue, lymphoedema, body mass index, menopausal symptoms, anxiety, depression and pain). Generalised estimating equation modelling determined time (baseline [5-weeks PS], mid-intervention [6-months PS], post-intervention [12-months PS]), group (FtF, Tel, Usual Care [UC]) and time-by-group effects. 194 women representative of the breast cancer population were randomised to the FtF (n=67), Tel (n=67) and UC (n=60) groups. Results: There were significant (p<0.05) interaction effects on QoL, fitness and fatigue, with differences being observed between the treatment groups and the UC group. Trends observed for the treatment groups were similar. The treatment groups reported improved QoL, fitness and fatigue over time and changes observed between baseline and post-intervention were clinically relevant. In contrast, the UC group experienced no change, or worsening QoL, fitness and fatigue, mid-intervention. Although improvements in the UC group occurred by 12-months post-surgery, the change did not meet the clinically relevant threshold. There were no differences in other treatment-related side-effects between groups. Conclusion This translational intervention trial, delivered either face-to-face or over-the-telephone, supports exercise as a form of adjuvant breast cancer therapy that can prevent declines in fitness and function during treatment and optimise recovery post-treatment.

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In this study, we have demonstrated that the preproghrelin derived hormones, ghrelin and obestatin, may play a role in ovarian cancer. Ghrelin and obestatin stimulated an increase in cell migration in ovarian cancer cell lines and may play a role in cancer progression. Ovarian cancer is the leading cause of death among gynaecological cancers and is the sixth most common cause of cancer-related deaths in women in developed countries. As ovarian cancer is difficult to diagnose at a low tumour grade, two thirds of ovarian cancers are not diagnosed until the late stages of cancer development resulting in a poor prognosis for the patient. As a result, current treatment methods are limited and not ideal. There is an urgent need for improved diagnostic markers, as well better therapeutic approaches and adjunctive therapies for this disease. Ghrelin has a number of important physiological effects, including roles in appetite regulation and the stimulation of growth hormone release. It is also involved in regulating the immune, cardiovascular and reproductive systems and regulates sleep, memory and anxiety, and energy metabolism. Over the last decade, the ghrelin axis, (which includes the hormones ghrelin and obestatin and their receptors), has been implicated in the pathogenesis of many human diseases and it may t may also play an important role in the development of cancer. Ghrelin is a 28 amino acid peptide hormone that exists in two forms. Acyl ghrelin (usually referred to as ghrelin), has a unique n-octanoic acid post-translational modification (which is catalysed by ghrelin O-acyltransferase, GOAT), and desacyl ghrelin, which is a non-octanoylated form. Octanoylated ghrelin acts through the growth hormone secretagogue receptor type 1a (GHSR1a). GHSR1b, an alternatively spliced isoform of GHSR, is C-terminally truncated and does not bind ghrelin. Ghrelin has been implicated in the pathophysiology of a number of diseases Obestatin is a 23 amino acid, C-terminally amidated peptide which is derived from preproghrelin. Although GPR39 was originally thought to be the obestatin receptor this has been disproven, and its receptor remains unknown. Obestatin may have as diverse range of roles as ghrelin. Obestatin improves memory, inhibits thirst and anxiety, increases pancreatic juice secretion and has cardioprotective effects. Obestatin also has been shown to regulate cell proliferation, differentiation and apoptosis in some cell types. Prior to this study, little was known regarding the functions and mechanisms of action ghrelin and obestatin in ovarian cancer. In this study it was demonstrated that the full length ghrelin, GHSR1b and GOAT mRNA transcripts were expressed in all of the ovarian-derived cell lines examined (SKOV3, OV-MZ-6 and hOSE 17.1), however, these cell lines did not express GHSR1a. Ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for ghrelin, obestatin, and GOAT, but not GHSR1a, or GHSR1b. No correlations between cancer grade and the level of expression of these transcripts were observed. This study demonstrated for the first time that both ghrelin and obestatin increase cell migration in ovarian cancer cell lines. Treatment with ghrelin (for 72 hours) significantly increased cell migration in the SKOV3 and OV-MZ-6 ovarian cancer cell lines. Ghrelin (100 nM) stimulated cell migration in the SKOV3 (2.64 +/- 1.08 fold, p <0.05) and OV-MZ-6 (1.65 +/- 0.31 fold, p <0.05) ovarian cancer cell lines, but not in the representative normal cell line hOSE 17.1. This increase in migration was not accompanied by an increase in cell invasion through Matrigel. In contrast to other cancer types, ghrelin had no effect on proliferation. Ghrelin treatment (10nM) significantly decreased attachment of the SKOV3 ovarian cancer cell line to collagen IV (24.7 +/- 10.0 %, p <0.05), however, there were no changes in attachment to the other extracellular matrix molecules (ECM) tested (fibronectin, vitronectin and collagen I), and there were no changes in attachment to any of the ECM molecules in the OV-MZ-6 or hOSE 17.1 cell lines. It is, therefore, unclear if ghrelin plays a role in cell attachment in ovarian cancer. As ghrelin has previously been demonstrated to signal through the ERK1/2 pathway in cancer, we investigated ERK1/2 signalling in ovarian cancer cell lines. In the SKOV3 ovarian cancer cell line, a reduction in ERK1/2 phosphorylation (0.58 fold +/- 0.23, p <0.05) in response to 100 nM ghrelin treatment was observed, while no significant change in ERK1/2 signalling was seen in the OV-MZ-6 cell line with treatment. This suggests that this pathway is unlikely to be involved in mediating the increased migration seen in the ovarian cancer cell lines with ghrelin treatment. In this study ovarian cancer tissue of varying stages and normal ovarian tissue expressed the coding region for obestatin, however, no correlation between cancer grade and level of obestatin transcript expression was observed. In the ovarian-derived cell lines studied (SKOV3, OV-MZ-6 and hOSE 17.1) it was demonstrated that the full length preproghrelin mRNA transcripts were expressed in all cell lines, suggesting they have the ability to produce mature obestatin. This is the first study to demonstrate that obestatin stimulates cell migration and cell invasion. Obestatin induced a significant increase in migration in the SKOV3 ovarian cancer cell line with 10 nM (2.80 +/- 0.52 fold, p <0.05) and 100 nM treatments (3.12 +/- 0.68 fold, p <0.05) and in the OV-MZ-6 cancer cell line with 10 nM (2.04 +/- 0.10 fold, p <0.01) and 100 nM treatments (2.00 +/- 0.37 fold, p <0.05). Obestatin treatment did no affect cell migration in the hOSE 17.1normal ovarian epithelial cell line. Obestatin treatment (100 nM) also stimulated a significant increase in cell invasion in the OV-MZ-6 ovarian cancer cell line (1.45 fold +/- 0.13, p <0.05) and in the hOSE17.1 normal ovarian cell line cells (1.40 fold +/- 0.04 and 1.55 fold +/- 0.05 respectively, p <0.01) with 10 nM and 100 nM treatments. Obestatin treatment did not stimulate cell invasion in the SKOV3 ovarian cancer cell line. This lack of obestatin-stimulated invasion in the SKOV3 cell line may be a cell line specific result. In this study, obestatin did not stimulate cell proliferation in the ovarian cell lines and it has previously been shown to have no effect on cell proliferation in the BON-1 pancreatic neuroendocrine and GC rat somatotroph tumour cell lines. In contrast, obestatin has been shown to affect cell proliferation in gastric and thyroid cancer cell lines, and in some normal cell lines. Obestatin also had no effect on attachment of any of the cell lines to any of the ECM components tested (fibronectin, vitronectin, collagen I and collagen IV). The mechanism of action of obestatin was investigated further using a two dimensional-difference in gel electrophoresis (2D-DIGE) proteomic approach. After treatment with obestating (0, 10 and 100 nM), SKOV3 ovarian cancer and hOSE 17.1 normal ovarian cell lines were collected and 2D-DIGE analysis and mass spectrometry were performed to identify proteins that were differentially expressed in response to treatment. Twenty-six differentially expressed proteins were identified and analysed using Ingenuity Pathway Analysis (IPA). This linked 16 of these proteins in a network. The analysis suggested that the ERK1/2 MAPK pathway was a major mediator of obestatin action. ERK1/2 has previously been shown to be associated with obestatin-stimulated cell proliferation and with the anti-apoptotic effects of obestatin. Activation of the ERK1/2 signalling pathway by obestatin was, therefore, investigated in the SKOV3 and OV-MZ-6 ovarian cancer cell lines using anti-active antibodies and Western immunoblots. Obestatin treatment significantly decreased ERK1/2 phosphorylation at higher obestatin concentrations in both the SKOV3 (100 nM and 1000 nM) and OV-MZ-6 (1000 nM) cell lines compared to the untreated controls. Currently, very little is known about obestatin signalling in cancer. This thesis has demonstrated for the first time that the ghrelin axis may play a role in ovarian cancer migration. Ghrelin and obestatin increased cell migration in ovarian cancer cell lines, indicating that they may be a useful target for therapies that reduce ovarian cancer progression. Further studies investigating the role of the ghrelin axis using in vivo ovarian cancer metastasis models are warranted.

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High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

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- Background This study examined relationships between adiposity, physical functioning and physical activity. - Methods Obese (N=107) and healthy-weight (N=132) children aged 10-13 years underwent assessments of percent body fat (%BF, dual energy X-ray absorptiometry), knee extensor strength (KE, isokinetic dynamometry), cardiorespiratory fitness (CRF, peak oxygen uptake by cycle ergometry), physical health-related quality of life (HRQOL), worst pain intensity and walking capacity [six-minute walk (6MWT)]. Structural equation modelling was used to assess relationships between variables. - Results Moderate relationships were observed between %BF and 6MWT, KE strength corrected for mass and CRF relative to mass (r -.36 to -.69, P≤.007). Weak relationships were found between: %BF and physical HRQOL (r -.27, P=.008); CRF relative to mass and physical HRQOL (r -.24, P=.003); physical activity and 6MWT (r .17, P=.004). Squared multiple correlations showed that 29.6% variance in physical HRQOL was explained by %BF, pain and CRF relative to mass, while 28% variance in 6MWT was explained by %BF and physical activity. - Conclusions It appears that children with a higher body fat percentage have poorer KE strength, CRF and overall physical functioning. Reducing percent fat appears to be the best target to improve functioning. However, a combined approach to intervention, targeting reductions in body fat percentage, pain and improvements in physical activity and CRF may assist physical functioning.

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Fleck and Johnson (Int. J. Mech. Sci. 29 (1987) 507) and Fleck et al. (Proc. Inst. Mech. Eng. 206 (1992) 119) have developed foil rolling models which allow for large deformations in the roll profile, including the possibility that the rolls flatten completely. However, these models require computationally expensive iterative solution techniques. A new approach to the approximate solution of the Fleck et al. (1992) Influence Function Model has been developed using both analytic and approximation techniques. The numerical difficulties arising from solving an integral equation in the flattened region have been reduced by applying an Inverse Hilbert Transform to get an analytic expression for the pressure. The method described in this paper is applicable to cases where there is or there is not a flat region.

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A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.