454 resultados para Population parameters


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Breast cancer is a common disease in both developing and developed countries with early identification and treatment improving prognosis and survival. Heparan sulfate proteoglycans (HSPGs) are key components of the extracellular matrix (ECM) that mediate cell adhesion, motility, proliferation, invasion and cell signalling. Members of the syndecan family of HSPGs have been identified to be involved in breast cancer progression through their varied interactions with a number of growth factors, ligands and receptors. Specifically, high expression levels of syndecan-1 (SDC1) have been demonstrated in more invasive breast tumours while elevated syndecan-4 (SDC4) levels have been identified to correspond with improved prognosis. With genetic changes in the syndecans and their association with breast cancers plausible, we examined two single nucleotide polymorphisms in SDC1 (rs1131351) and SDC4 (rs67068737) within an Australian Caucasian breast cancer case/control population. No association was found with SDC4 and breast cancer in our population. However, a significant association between SDC1 and breast cancer was identified in both our case/control population and in a replication cohort. When both populations were combined for analysis, this association became more significant (genotype, p = 0.0003; allele, p = 0.0001). This data suggests an increased risk of developing breast cancer associated with the presence of the C allele of the SDC1 rs1131351 single nucleotide polymorphism (SNP) and may provide a marker toward early breast cancer detection.

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Background: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. Methods: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. Results: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9kg [2.0-11.3kg] and 5.2kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4kg [-1.9--24.6kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3kg; all p<0.05). Conclusions: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a contemporary public health issue and the integration of healthy weight education and support into standard breast cancer care has potential to significantly improve the length and quality of cancer survivorship.

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The preservation technique of drying offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Variations in porosity are just one of the microstructural changes that take place during the drying of most food materials. Some studies found that there may be a relationship between porosity and the properties of dried foods. However, no conclusive relationship has yet been established in the literature. This paper presents an overview of the factors that influence porosity, as well as the effects of porosity on dried food quality attributes. The effect of heat and mass transfer on porosity is also discussed along with porosity development in various drying methods. After an extensive review of the literature concerning the study of porosity, it emerges that a relationship between process parameters, food qualities, and sample properties can be established. Therefore, we propose a hypothesis of relationships between process parameters, product quality attributes, and porosity.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.

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Long-term systematic population monitoring data sets are rare but are essential in identifying changes in species abundance. In contrast, community groups and natural history organizations have collected many species lists. These represent a large, untapped source of information on changes in abundance but are generally considered of little value. The major problem with using species lists to detect population changes is that the amount of effort used to obtain the list is often uncontrolled and usually unknown. It has been suggested that using the number of species on the list, the "list length," can be a measure of effort. This paper significantly extends the utility of Franklin's approach using Bayesian logistic regression. We demonstrate the value of List Length Analysis to model changes in species prevalence (i.e., the proportion of lists on which the species occurs) using bird lists collected by a local bird club over 40 years around Brisbane, southeast Queensland, Australia. We estimate the magnitude and certainty of change for 269 bird species and calculate the probabilities that there have been declines and increases of given magnitudes. List Length Analysis confirmed suspected species declines and increases. This method is an important complement to systematically designed intensive monitoring schemes and provides a means of utilizing data that may otherwise be deemed useless. The results of List Length Analysis can be used for targeting species of conservation concern for listing purposes or for more intensive monitoring. While Bayesian methods are not essential for List Length Analysis, they can offer more flexibility in interrogating the data and are able to provide a range of parameters that are easy to interpret and can facilitate conservation listing and prioritization. © 2010 by the Ecological Society of America.

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Quantifying the competing rates of intake and elimination of persistent organic pollutants (POPs) in the human body is necessary to understand the levels and trends of POPs at a population level. In this paper we reconstruct the historical intake and elimination of ten polychlorinated biphenyls (PCBs) and five organochlorine pesticides (OCPs) from Australian biomonitoring data by fitting a population-level pharmacokinetic (PK) model. Our analysis exploits two sets of cross-sectional biomonitoring data for PCBs and OCPs in pooled blood serum samples from the Australian population that were collected in 2003 and 2009. The modeled adult reference intakes in 1975 for PCB congeners ranged from 0.89 to 24.5 ng/kg bw/day, lower than the daily intakes of OCPs ranging from 73 to 970 ng/kg bw/day. Modeled intake rates are declining with half-times from 1.1 to 1.3 years for PCB congeners and 0.83 to 0.97 years for OCPs. The shortest modeled intrinsic human elimination half-life among the compounds studied here is 6.4 years for hexachlorobenzene, and the longest is 30 years for PCB-74. Our results indicate that it is feasible to reconstruct intakes and to estimate intrinsic human elimination half-lives using the population-level PK model and biomonitoring data only. Our modeled intrinsic human elimination half-lives are in good agreement with values from a similar study carried out for the population of the United Kingdom, and are generally longer than reported values from other industrialized countries in the Northern Hemisphere.

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Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

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Polybrominated diphenyl ethers (PBDEs), a common class of brominated flame retardants, are a ubiquitous part of our built environment, and for many years have contributed to improved public safety by reducing the flammability of everyday goods. Recently, PBDEs have come under increased international attention because of their potential to impact upon the environment and human health. Some PBDE compounds have been nominated for possible inclusion on the Stockholm Convention on Persistent Organic Pollutants, to which Australia is a Party. Work under the Stockholm Convention has demonstrated the capacity of some PBDEs to persist and accumulate in the environment and to be carried long distances. Much is unknown about the impact of PBDEs on living organisms, however recent studies show that some PBDEs can inhibit growth in colonies of plankton and algae and depress the reproduction of zooplankton. Laboratory mice and rats have also shown liver disturbances and damage to developing nervous systems as a result of exposure to PBDEs. In 2004, the Australian Government Department of the Environment and Water Resources began three studies to examine levels of PBDEs in aquatic sediments, indoor environments and human blood, as knowledge about PBDEs in Australia was very limited. The aim of these studies was to improve this knowledge base so that governments were in a better position to consider appropriate management actions. Due to the high costs for laboratory analysis of PBDEs, the number of samples collected for each study was limited and so caution is required when interpreting the findings. Nevertheless, these studies will provide governments with an indication of how prevalent PBDEs are in the Australian population and the environment and will also contribute to international knowledge about these chemicals. The Department of the Environment and Water Resources will be working closely with othergovernment agencies, industry and the community to investigate any further action that may be required to address PBDEs in Australia.

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This study arose out of the 2002 Review of the PCB Management Plan by the Scheduled Waste Management Network (SWMN) and the National Advisory Body (NAB). The Review indicated it would be beneficial to obtain some data on the levels of organochlorine pesticides (OCPs) in the Australian population. In 2002, the Environment Protection and Heritage Standing Committee (EPHSC) agreed and noted that the Australian Government Department of the Environment and Heritage (DEH) would commission a study using the same samples from the National Dioxins Program (NDP) breast milk study collected in 2002- 03. The study, however, was also broadened to include polybrominated diphenyl ethers (PBDEs).

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Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.

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Purpose To investigate the frequency of convergence and accommodation anomalies in an optometric clinical setting in Mashhad, Iran, and to determine tests with highest accuracy in diagnosing these anomalies. Methods From 261 patients who came to the optometric clinics of Mashhad University of Medical Sciences during a month, 83 of them were included in the study based on the inclusion criteria. Near point of convergence (NPC), near and distance heterophoria, monocular and binocular accommodative facility (MAF and BAF, respectively), lag of accommodation, positive and negative fusional vergences (PFV and NFV, respectively), AC/A ratio, relative accommodation, and amplitude of accommodation (AA) were measured to diagnose the convergence and accommodation anomalies. The results were also compared between symptomatic and asymptomatic patients. The accuracy of these tests was explored using sensitivity (S), specificity (Sp), and positive and negative likelihood ratios (LR+, LR−). Results Mean age of the patients was 21.3 ± 3.5 years and 14.5% of them had specific binocular and accommodative symptoms. Convergence and accommodative anomalies were found in 19.3% of the patients; accommodative excess (4.8%) and convergence insufficiency (3.6%) were the most common accommodative and convergence disorders, respectively. Symptomatic patients showed lower values for BAF (p = .003), MAF (p = .001), as well as AA (p = .001) compared with asymptomatic patients. Moreover, BAF (S = 75%, Sp = 62%) and MAF (S = 62%, Sp = 89%) were the most accurate tests for detecting accommodative and convergence disorders in terms of both sensitivity and specificity. Conclusions Convergence and accommodative anomalies are the most common binocular disorders in optometric patients. Including tests of monocular and binocular accommodative facility in routine eye examinations as accurate tests to diagnose these anomalies requires further investigation.