153 resultados para Continuous-time Markov Chain


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A major priority for cancer control agencies is to reduce geographical inequalities in cancer outcomes. While the poorer breast cancer survival among socioeconomically disadvantaged women is well established, few studies have looked at the independent contribution that area- and individual-level factors make to breast cancer survival. Here we examine relationships between geographic remoteness, area-level socioeconomic disadvantage and breast cancer survival after adjustment for patients’ socio- demographic characteristics and stage at diagnosis. Multilevel logistic regression and Markov chain Monte Carlo simulation were used to analyze 18 568 breast cancer cases extracted from the Queensland Cancer Registry for women aged 30 to 70 years diagnosed between 1997 and 2006 from 478 Statistical Local Areas in Queensland, Australia. Independent of individual-level factors, area-level disadvantage was associated with breast-cancer survival (p=0.032). Compared to women in the least disadvantaged quintile (Quintile 5), women diagnosed while resident in one of the remaining four quintiles had significantly worse survival (OR 1.23, 1.27, 1.30, 1.37 for Quintiles 4, 3, 2 and 1 respectively).) Geographic remoteness was not related to lower survival after multivariable adjustment. There was no evidence that the impact of area-level disadvantage varied by geographic remoteness. At the individual level, Indigenous status, blue collar occupations and advanced disease were important predictors of poorer survival. A woman’s survival after a diagnosis of breast cancer depends on the socio-economic characteristics of the area where she lives, independently of her individual-level characteristics. It is crucial that the underlying reasons for these inequalities be identified to appropriately target policies, resources and effective intervention strategies.

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A novel in-cylinder pressure method for determining ignition delay has been proposed and demonstrated. This method proposes a new Bayesian statistical model to resolve the start of combustion, defined as being the point at which the band-pass in-cylinder pressure deviates from background noise and the combustion resonance begins. Further, it is demonstrated that this method is still accurate in situations where there is noise present. The start of combustion can be resolved for each cycle without the need for ad hoc methods such as cycle averaging. Therefore, this method allows for analysis of consecutive cycles and inter-cycle variability studies. Ignition delay obtained by this method and by the net rate of heat release have been shown to give good agreement. However, the use of combustion resonance to determine the start of combustion is preferable over the net rate of heat release method because it does not rely on knowledge of heat losses and will still function accurately in the presence of noise. Results for a six-cylinder turbo-charged common-rail diesel engine run with neat diesel fuel at full, three quarters and half load have been presented. Under these conditions the ignition delay was shown to increase as the load was decreased with a significant increase in ignition delay at half load, when compared with three quarter and full loads.

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The emergence of pseudo-marginal algorithms has led to improved computational efficiency for dealing with complex Bayesian models with latent variables. Here an unbiased estimator of the likelihood replaces the true likelihood in order to produce a Bayesian algorithm that remains on the marginal space of the model parameter (with latent variables integrated out), with a target distribution that is still the correct posterior distribution. Very efficient proposal distributions can be developed on the marginal space relative to the joint space of model parameter and latent variables. Thus psuedo-marginal algorithms tend to have substantially better mixing properties. However, for pseudo-marginal approaches to perform well, the likelihood has to be estimated rather precisely. This can be difficult to achieve in complex applications. In this paper we propose to take advantage of multiple central processing units (CPUs), that are readily available on most standard desktop computers. Here the likelihood is estimated independently on the multiple CPUs, with the ultimate estimate of the likelihood being the average of the estimates obtained from the multiple CPUs. The estimate remains unbiased, but the variability is reduced. We compare and contrast two different technologies that allow the implementation of this idea, both of which require a negligible amount of extra programming effort. The superior performance of this idea over the standard approach is demonstrated on simulated data from a stochastic volatility model.

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This thesis introduced Bayesian statistics as an analysis technique to isolate resonant frequency information in in-cylinder pressure signals taken from internal combustion engines. Applications of these techniques are relevant to engine design (performance and noise), energy conservation (fuel consumption) and alternative fuel evaluation. The use of Bayesian statistics, over traditional techniques, allowed for a more in-depth investigation into previously difficult to isolate engine parameters on a cycle-by-cycle basis. Specifically, these techniques facilitated the determination of the start of pre-mixed and diffusion combustion and for the in-cylinder temperature profile to be resolved on individual consecutive engine cycles. Dr Bodisco further showed the utility of the Bayesian analysis techniques by applying them to in-cylinder pressure signals taken from a compression ignition engine run with fumigated ethanol.

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Background: Although rapid diagnostic tests (RDTs) for Plasmodium falciparum infection that target histidine rich protein 2 (PfHRP2) are generally sensitive, their performance has been reported to be variable. One possible explanation for variable test performance is differences in expression level of PfHRP in different parasite isolates. Methods: Total RNA and protein were extracted from synchronised cultures of 7 P. falciparum lines over 5 time points of the life cycle, and from synchronised ring stages of 10 falciparum lines. Using quantitative real-time polymerase chain reaction, Western blot analysis and ELISA we investigated variations in the transcription and protein levels of pfhrp2, pfhrp3 and PfHRP respectively in the different parasite lines, over the parasite intraerythrocytic life cycle. Results: Transcription of pfhrp2 and pfhrp3 in different parasite lines over the parasite life cycle was observed to vary relative to the control parasite K1. In some parasite lines very low transcription of these genes was observed. The peak transcription was observed in ring-stage parasites. Pfhrp2 transcription was observed to be consistently higher than pfhrp3 transcription within parasite lines. The intraerythrocytic lifecycle stage at which the peak level of protein was present varied across strains. Total protein levels were more constant relative to total mRNA transcription, however a maximum 24 fold difference in expression at ring-stage parasites relative to the K1 strain was observed. Conclusions: The levels of transcription of pfhrp2 and pfhrp3, and protein expression of PfHRP varied between different P. falciparum strains. This variation may impact on the detection sensitivity of PfHRP2-detecting RDTs.

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Cervical cancer is one of the world's major health issues. Despite many studies in this field, the carcinogenetic events of malignant conversion in cervical tumours have not been significantly characterised. The first aim of this project was to investigate the mutation status of the tumour suppressor gene- Phosphatase and Tension Homolog (PTEN)- in cervical cancer tissue. The second aim of this study was the analysis in the same cervical cancer tissue for aberrations in the mitochondrial electron transport chain subunit gene NDUFB8, which is localised to the same chromosomal contig as PTEN. The third aim was the evaluation of the potential therapeutic anti-cancer drug 2,4-Thiazolidinediones (TZDs) and its affect in regulating the PTEN protein in a cervical cancer cell line (HeLa). To approach the aims, paraffin-embedded cancerous cervical tissue and non-cancerous cervical tissue were obtained. DNA recovered from those tissues was then used to investigate the putative genomic changes regarding the NDUFB8 gene utilising SYBR Green I Real-Time PCR. The PTEN gene was studied via Dual-Labelled probe Real-Time PCR. To investigate the protein expression change of the PTEN protein, HeLa cells were firstly treated with different concentrations of 2,4-Thiazolidinediones and the level of PTEN protein expression was then observed utilising standard protein assays. Results indicated that there were putative copy-number changes between the cancerous cervical tissue and non-cancerous cervical tissue, with regard to the PTEN locus. This implies a potential gain of the PTEN gene in cancerous cervical tissue. With regards to normal cervical tissue versus cancerous cervical tissue no significant melting temperature differences were observed with the SYBR Green I Real-Time PCR in respect to the NDUFB8 gene. A putative up-regulation of PTEN protein was observed in TZD treated HeLa cells. © 2008 Springer Science+Business Media, LLC.

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The incidence of Squamous Cell Carcinoma (SCG) is growing in certain populations to the extent that it is now the most common skin lesion in young men and women in high ultraviolet exposure regions such as Queensland. In terms of incidence up to 40% of the Australian population over 40 years of age is thought to possess the precancerous Solar Keratosis (SK) lesion and with a small, but significant, chance of progression into SCC, understanding the genetic events that play a role in this process is essential. The major aims of this study were to analyse whole blood derived samples for DNA aberrations in genes associated with tumour development and cellular maintenance, with the ultimate aim of identifying genes associated with non-melanoma skin cancer development. More specifically the first aim of this project was to analyse the SDHD and MMP12 genes via Dual-Labelled Probe Real-Time PCR for copy number aberrations in an affected Solar Keratosis and control cohort. It was found that 12 samples had identifiable copy-number aberrations in either the SDHD or MMP12 gene (this means that a genetic section of either of these two genes is aberrantly amplified or deleted), with five of the samples exhibiting aberrations in both genes. The significance of this study is the contribution to the knowledge of the genetic pathways that are malformed in the progression and development of the pre-cancerous skin lesion Solar Keratosis. © 2008 Springer Science+Business Media, LLC.

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Recently, it has been suggested osteocytes control the activities of bone formation (osteoblasts) and resorption (osteoclast), indicating their important regulatory role in bone remodelling. However, to date, the role of osteocytes in controlling bone vascularisation remains unknown. Our aim was to investigate the interaction between endothelial cells and osteocytes and to explore the possible molecular mechanisms during angiogenesis. To model osteocyte/endothelial cell interactions, we co-cultured osteocyte cell line (MLOY4) with endothelial cell line (HUVECs). Co-cultures were performed in 1:1 mixture of osteocytes and endothelial cells or by using the conditioned media (CM) transfer method. Real-time cell migration of HUVECs was measured with the transwell migration assay and xCELLigence system. Expression levels of angiogenesis- related genes were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The effect of vascular endothelial growth factor (VEGF) and mitogen-activated phosphorylated kinase (MAPK) signaling were monitored by western blotting using relevant antibodies and inhibitors. During the bone formation, it was noted that osteocyte dendritic processes were closely connected to the blood vessels. The CM generated from MLOY4 cells-activated proliferation, migration, tube-like structure formation, and upregulation of angiogenic genes in endothelial cells suggesting that secretory factor(s) from osteocytes could be responsible for angiogenesis. Furthermore, we identified that VEGF secreted from MLOY4-activated VEGFR2–MAPK–ERK-signaling pathways in HUVECs. Inhibiting VEGF and/or MAPK–ERK pathways abrogated osteocyte-mediated angiogenesis in HUVEC cells. Our data suggest an important role of osteocytes in regulating angiogenesis.

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Background To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival. Methods Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007. Results Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas. Conclusions We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC.

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Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST) in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP) area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30°C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth) on LST and consequently to devise appropriate policy measures.

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A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

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Purpose: To identify a 15-KDa novel hypoxia-induced secreted protein in head and neck squamous cell carcinomas (HNSCC) and to determine its role in malignant progression. Methods: We used surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and tandem MS to identify a novel hypoxia-induced secreted protein in FaDu cells. We used immunoblots, real-time polymerase chain reaction (PCR), and enzyme-linked immunoabsorbent assay to confirm the hypoxic induction of this secreted protein as galectin-1 in cell lines and xenografts. We stained tumor tissues from 101 HNSCC patients for galectin-1, CA IX (carbonic anhydrase IX, a hypoxia marker) and CDS (a T-cell marker). Expression of these markers was correlated to each other and to treatment outcomes. Results: SELDI-TOF studies yielded a hypoxia-induced peak at 15 kDa that proved to be galectin-1 by MS analysis. Immunoblots and PCR studies confirmed increased galectin-1 expression by hypoxia in several cancer cell lines. Plasma levels of galectin-1 were higher in tumor-bearing severe combined immunodeficiency (SCID) mice breathing 10% O 2 compared with mice breathing room air. In HNSCC patients, there was a significant correlation between galectin-1 and CA IX staining (P = .01) and a strong inverse correlation between galectin-1 and CDS staining (P = .01). Expression of galectin-1 and CDS were significant predictors for overall survival on multivariate analysis. Conclusion: Galectin-1 is a novel hypoxia-regulated protein and a prognostic marker in HNSCC. This study presents a new mechanism on how hypoxia can affect the malignant progression and therapeutic response of solid tumors by regulating the secretion of proteins that modulate immune privilege. © 2005 by American Society of Clinical Oncology.

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RNA interference (RNAi) is widely used to silence genes in plants and animals. It operates through the degradation of target mRNA by endonuclease complexes guided by approximately 21 nucleotide (nt) short interfering RNAs (siRNAs). A similar process regulates the expression of some developmental genes through approximately 21 nt microRNAs. Plants have four types of Dicer-like (DCL) enzyme, each producing small RNAs with different functions. Here, we show that DCL2, DCL3 and DCL4 in Arabidopsis process both replicating viral RNAs and RNAi-inducing hairpin RNAs (hpRNAs) into 22-, 24- and 21 nt siRNAs, respectively, and that loss of both DCL2 and DCL4 activities is required to negate RNAi and to release the plant's repression of viral replication. We also show that hpRNAs, similar to viral infection, can engender long-distance silencing signals and that hpRNA-induced silencing is suppressed by the expression of a virus-derived suppressor protein. These findings indicate that hpRNA-mediated RNAi in plants operates through the viral defence pathway.

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Potato leafroll virus (PLRV) is a positive-strand RNA virus that generates subgenomic RNAs (sgRNA) for expression of 3' proximal genes. Small RNA (sRNA) sequencing and mapping of the PLRV-derived sRNAs revealed coverage of the entire viral genome with the exception of four distinctive gaps. Remarkably, these gaps mapped to areas of PLRV genome with extensive secondary structures, such as the internal ribosome entry site and 5' transcriptional start site of sgRNA1 and sgRNA2. The last gap mapped to ~500. nt from the 3' terminus of PLRV genome and suggested the possible presence of an additional sgRNA for PLRV. Quantitative real-time PCR and northern blot analysis confirmed the expression of sgRNA3 and subsequent analyses placed its 5' transcriptional start site at position 5347 of PLRV genome. A regulatory role is proposed for the PLRV sgRNA3 as it encodes for an RNA-binding protein with specificity to the 5' of PLRV genomic RNA. © 2013.

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The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.