217 resultados para nuclear division index


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Aim: The aim was to investigate whether the sleep practices in early childhood education (ECE) settings align with current evidence on optimal practice to support sleep. Background: Internationally, scheduled sleep times are a common feature of daily schedules in ECE settings, yet little is known about the degree to which care practices in these settings align with the evidence regarding appropriate support of sleep. Methods: Observations were conducted in 130 Australian ECE rooms attended by preschool children (Mean = 4.9 years). Of these rooms, 118 had daily scheduled sleep times. Observed practices were scored against an optimality index, the Sleep Environment and Practices Optimality Score, developed with reference to current evidence regarding sleep scheduling, routines, environmental stimuli, and emotional climate. Cluster analysis was applied to identify patterns and prevalence of care practices in the sleep time. Results: Three sleep practices types were identified. Supportive rooms (36%) engaged in practices that maintained regular schedules, promoted routine, reduced environmental stimulation, and maintained positive emotional climate. The majority of ECE rooms (64%), although offering opportunity for sleep, did not engage in supportive practices: Ambivalent rooms (45%) were emotionally positive but did not support sleep; Unsupportive rooms (19%) were both emotionally negative and unsupportive in their practices. Conclusions: Although ECE rooms schedule sleep time, many do not adopt practices that are supportive of sleep. Our results underscore the need for education about sleep supporting practice and research to ascertain the impact of sleep practices in ECE settings on children’s sleep health and broader well-being.

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The present study examined whether a specific property of cell microstructures may be useful as a biomarker of aging. Specifically, the association between age and changes of cellular structures reflected in electrophoretic mobility of cell nuclei index (EMN index) values across the adult lifespan was examined. This report considers findings from cross sections of females (n = 1273) aged 18–98 years, and males (n = 506) aged 19–93 years. A Biotest apparatus was used to perform intracellular microelectrophoresis on buccal epithelial cells collected from each individual. EMN index was calculated on the basis of the number of epithelial cells with mobile nuclei in reference to the cells with immobile nuclei per 100 cells. Regression analyses indicated a significant negative association between EMN index value and age for men (r = −0.71, p < 0.001) and women (r = −0.60, p < 0.001); demonstrating a key requirement that must be met by a biomarker of aging. The strength of association observed between EMN index and age for both men and women was encouraging and supports the potential use of EMN index for determining a biological age of an individual (or a group). In this study, a new attempt of complex explanation of cellular mechanisms contributing to age related changes of the EMN index was made. In this study, a new attempt of complex explanation of cellular mechanisms contributing to age related changes of the EMN index was made. EMN index has demonstrated potential to meet criteria proposed for biomarkers of aging and further investigations are necessary.

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This paper introduces an index of tax optimality that measures the distance of some current tax structure from the optimal tax structure in the presence of public goods. This index is defined on the [0, 1] interval and measures the proportion of the optimal tax rates that will achieve the same welfare outcome as some arbitrarily given initial tax structure. We call this number the Tax Optimality Index. We also show how the basic methodology can be altered to derive a revenue equivalent uniform tax, which measures the tax burden implied by the public sector. A numerical example is used to illustrate the method developed, and extensions of the analysis to handle models with multiple households and nonlinear taxation structures are undertaken.

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The Clancestry Conversation series forms part of QPAC's Clancestry Festival which is an annual celebration of the arts and cultural practices of the world's First Nations Peoples with a particular focus on Aboriginal and Torres Strait Islander peoples.

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Lung cancer is the second most common type of cancer in the world and is the most common cause of cancer-related death in both men and women. Research into causes, prevention and treatment of lung cancer is ongoing and much progress has been made recently in these areas, however survival rates have not significantly improved. Therefore, it is essential to develop biomarkers for early diagnosis of lung cancer, prediction of metastasis and evaluation of treatment efficiency, as well as using these molecules to provide some understanding about tumour biology and translate highly promising findings in basic science research to clinical application. In this investigation, two-dimensional difference gel electrophoresis and mass spectrometry were initially used to analyse conditioned media from a panel of lung cancer and normal bronchial epithelial cell lines. Significant proteins were identified with heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1), pyruvate kinase M2 isoform (PKM2), Hsc-70 interacting protein and lactate dehydrogenase A (LDHA) selected for analysis in serum from healthy individuals and lung cancer patients. hnRNPA2B1, PKM2 and LDHA were found to be statistically significant in all comparisons. Tissue analysis and knockdown of hnRNPA2B1 using siRNA subsequently demonstrated both the overexpression and potential role for this molecule in lung tumorigenesis. The data presented highlights a number of in vitro derived candidate biomarkers subsequently verified in patient samples and also provides some insight into their roles in the complex intracellular mechanisms associated with tumour progression.

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Objectives To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. Patients and Methods Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. Results In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. Conclusion These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.

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The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.