90 resultados para quantifying


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Aims/hypothesis Supraphysiological levels of the amyloidogenic peptide human islet amyloid polypeptide have been associated with beta cell endoplasmic reticulum (ER) stress. However, in human type 2 diabetes, levels of human IAPP are equivalent or decreased relative to matched controls. Thus, we sought to investigate whether ER stress is induced during amyloidogenesis at physiological levels of human IAPP.

Methods Islets from human IAPP transgenic mice that develop amyloid, and non-transgenic mice that do not, were cultured for up to 7 days in 11.1, 16.7 and 33.3 mmol/l glucose. Pancreases from human IAPP transgenic and non-transgenic mice and humans with or without type 2 diabetes were also evaluated. Amyloid formation was determined histologically. ER stress was determined in islets by quantifying mRNA levels of Bip, Atf4 and Chop (also known as Ddit3) and alternate splicing of Xbp1 mRNA, or in pancreases by immunostaining for immunoglobulin heavy chain-binding protein (BIP), C/EBP homologous protein (CHOP) and X-box binding protein 1 (XBP1).

Results Amyloid formation in human IAPP transgenic islets was associated with reduced beta cell area in a glucose- and time-dependent manner. However, amyloid formation was not associated with significant increases in expression of ER stress markers under any culture condition. Thapsigargin treatment, a positive control, did result in significant ER stress. Amyloid formation in vivo in pancreas samples from human IAPP transgenic mice or humans was not associated with upregulation of ER stress markers.

Conclusions/interpretation Our data suggest that ER stress is not an obligatory pathway mediating the toxic effects of amyloid formation at physiological levels of human IAPP.

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To assess the costs and benefits of young fish adopting different behavioural tactics, field studies of juvenile salmonines have assumed that (but did not test whether) the rate of foraging attempts predicts ingestion rate. We tested this assumption by quantifying capture, ingestion, and rejection rates of potential prey items for individual young-of-the-year brook trout (Salvelinus fontinalis) in a lake. Overall, capture rate (a conservative estimate of the rate of foraging attempts) was only a fair predictor of overall ingestion rate (Kendall's 1 = 0.54) and only 46% of captured items (number/minute) were ingested. Surface capture rate was a poor predictor of surface ingestion rate (T = 0.27) and only 1% of captured items were ingested. In contrast, subsurface capture rate was an excellent predictor of subsurface ingestion rate (T = 0.75) and 93% of captured items were ingested. No benthic prey captures were observed. Fish that ingested a low proportion of captured items spent a greater proportion of time moving, moved faster, and pursued prey further than fish that ingested a higher proportion of captured items. Rejection of captured items can represent a significant and little appreciated component of the foraging cycle for young salmonid fishes.

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Population genetic tools have the potential to answer key questions in pest management including quantifying the number of genetically distinct populations represented in an invasion, the number of individuals present, whether populations are expanding or contracting, identifying the origin of invasive individuals, the number of separate introduction events that have occurred and in which order, and the rate that individuals are moving between populations. Genetic methods have only recently gained sufficient resolution to address these questions due to advances in laboratory techniques coupled with an increase in computational power. In combination, these methods may lead to a more comprehensive understanding of the dynamics of invasions. The expansion of the European starling (Sturnus vulgaris) into Western Australia is used as an applied example of how genetic methods can be integrated to provide vital information to improve pest-management strategies. Invasion events also may provide a unique opportunity to test some of these methodologies.

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Accurate forecasting of wind farm power generation is essential for successful operation and management of wind farms and to minimize risks associated with their integration into energy systems. However, due to the inherent wind intermittency, wind power forecasts are highly prone to error and often far from being perfect. The purpose of this paper is to develop statistical methods for quantifying uncertainties associated with wind power generation forecasts. Prediction intervals (PIs) with a prescribed confidence level are constructed using the delta and bootstrap methods for neural network forecasts. The moving block bootstrap method is applied to preserve the correlation structure in wind power observations. The effectiveness and efficiency of these two methods for uncertainty quantification is examined using two month datasets taken from a wind farm in Australia. It is demonstrated that while all constructed PIs are theoretically valid, bootstrap PIs are more informative than delta PIs, and are therefore more useful for decision-making.

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Public accounting firms provide a necessary and important service for rural and regional areas. However, the provision of high-quality services is hindered by a number of factors. This paper reports the findings from a large-scale survey of professional accounting firm practitioners located in rural and regional Australia, identifying factors causing concerns and tensions and quantifying their scope and importance. Prominent concerns and tensions identified include adverse effects arising from the employment market, communications technology developments and legislation such as the Corporate Law Economic Reform Program (Audit Reform and Corporate Disclosure) Act 2004 and the Financial Services Reform Act 2001.

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Background Although physical therapy and falls prevention education are argued to reduce falls and disability in people with idiopathic Parkinson's disease, this has not yet been confirmed with a large scale randomised controlled clinical trial. The study will investigate the effects on falls, mobility and quality of life of (i) movement strategy training combined with falls prevention education, (ii) progressive resistance strength training combined with falls prevention education, (iii) a generic life-skills social program (control group).
Methods/Design
People with idiopathic Parkinson's disease who live at home will be recruited and randomly allocated to one of three groups. Each person shall receive therapy in an out-patient setting in groups of 3-4. Each group shall be scheduled to meet once per week for 2 hours for 8 consecutive weeks. All participants will also have a structured 2 hour home practice program for each week during the 8 week intervention phase. Assessments will occur before therapy, after the 8 week therapy program, and at 3 and 12 months after the intervention. A falls calendar will be kept by each participant for 12 months after outpatient therapy. Consistent with the recommendations of the Prevention of Falls Network Europe group, three falls variables will be used as the primary outcome measures: the number of fallers, the number of multiple fallers and the falls rate. In addition to quantifying falls, we shall measure mobility, activity limitations and quality of life as secondary outcomes.
Discussion
This study has the potential to determine whether outpatient movement strategy training combined with falls prevention education or progressive resistance strength training combined with falls prevention education are effective for reducing falls and improving mobility and life quality in people with Parkinson's disease who live at home.

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Areal bone mineral density is commonly categorised into normal bone mineral density, osteopaenia and osteoporosis on the basis of nominal thresholds recommended by the World Health Organization. However, bone mineral density is a continuous variable and there is a strong association between lower bone mineral density and greater risk for fracture. Fracture risk is not negligible in persons with moderate deficits in bone mineral density. Although absolute fracture risk is greatest for individuals with osteoporosis, more than half of the fractures arise from those with osteopaenia, and even normal bone mineral density, a probable consequence of greater numbers of individuals at risk in these categories. However, areal bone mineral density measurements used commonly in clinical practice do not detect differences in bone tissue properties, geometry and microarchitecture, which contribute to bone strength. Newer technologies such as high-resolution peripheral computed tomography have the advantage of assessing trabecular and cortical components of bone separately, in addition to geometric characteristics of the skeleton. Quantifying these parameters and considering clinical risk factors that affect fracture risk independent of bone quantity and quality, may better discriminate between high- and low-risk individuals. This would improve the decision-making for targeting appropriate interventions, either lifestyle or medication, to reduce thepublic health burden of fractures.

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The growth/survival trade-off is a fundamental aspect of life-history evolution that is often explained by the direct energetic requirement for growth that cannot be allocated into maintenance. However, there is currently no empirical consensus on whether fast-growing individuals have higher resting metabolic rates at thermoneutrality (RMRt) than slow growers. Moreover, the link between growth rate and daily energy expenditure (DEE) has never been tested in a wild endotherm. We assessed the energetic and survival costs of growth in juvenile eastern chipmunks (Tamias striatus) during a year of low food abundance by quantifying post-emergent growth rate (n = 88), RMRt (n = 66), DEE (n = 20), and overwinter survival. Both RMRt and DEE were significantly and positively related to growth rate. The effect size was stronger for DEE than RMRt, suggesting that the energy cost of growth in wild animals is more likely to be related to the maintenance of a higher foraging rate (included in DEE) than to tissue accretion (included in RMRt). Fast growers were significantly less likely to survive the following winter compared to slow growers. Juveniles with high or low RMRt were less likely to survive winter than juveniles with intermediate RMRt. In contrast, DEE was unrelated to survival. In addition, botfly parasitism simultaneously decreased growth rate and survival, suggesting that the energetic budget of juveniles was restricted by the simultaneous costs of growth and parasitism. Although the biology of the species (seed-storing hibernator) and the context of our study (constraining environmental conditions) were ideally combined to reveal a direct relationship between current use of energy and future availability, it remains unclear whether the energetic cost of growth was directly responsible for reduced survival.

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Social capital indicative of community interaction and support is intrinsically linked to mental health. Increasing online presence is now the norm. Whilst social capital and its impact on social networks has been examined, its underlying connection to emotional response such as mood, has not been investigated. This paper studies this phenomena, revisiting the concept of “online social capital†in social media communities using measurable aspects of social participation and social support. We establish the link between online capital derived from social media and mood, demonstrating results for different cohorts of social capital and social connectivity. We use novel Bayesian nonparametric factor analysis to extract the shared and individual factors in mood transition across groups of users of different levels of connectivity, quantifying patterns and degree of mood transitions. Using more than 1.6 million users from Live Journal, we show quantitatively that groups with lower social capital have fewer positive moods and more negative moods, than groups with higher social capital. We show similar effects in mood transitions. We establish a framework of how social media can be used as a barometer for mood. The significance lies in the importance of online social capital to mental well-being in overall. In establishing the link between mood and social capital in online communities, this work may suggest the foundation of new systems to monitor online mental well-being.

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The analysis of human crowds has widespread uses from law enforcement to urban engineering and traffic management. All of these require a crowd to first be detected, which is the problem addressed in this paper. Given an image, the algorithm we propose segments it into crowd and non-crowd regions. The main idea is to capture two key properties of crowds: (i) on a narrow scale, its basic element should look like a human (only weakly so, due to low resolution, occlusion, clothing variation etc.), while (ii) on a larger scale, a crowd inherently contains repetitive appearance elements. Our method exploits this by building a pyramid of sliding windows and quantifying how “crowd-like” each level of the pyramid is using an underlying statistical model based on quantized SIFT features. The two aforementioned crowd properties are captured by the resulting feature vector of window responses, describing the degree of crowd-like appearance around an image location as the surrounding spatial extent is increased.

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An important task in multiple-criteria decision making is how to learn the weights and parameters of an aggregation function from empirical data. We consider this in the context of quantifying ecological diversity, where such data is to be obtained as a set of pairwise comparisons specifying that one community should be considered more diverse than another. A problem that arises is how to collect a sufficient amount of data for reliable model determination without overloading individuals with the number of comparisons they need to make. After providing an algorithm for determining criteria weights and an overall ranking from such information, we then investigate the improvement in accuracy if ranked 3-tuples are supplied instead of pairs. We found that aggregation models could be determined accurately from significantly fewer 3-tuple comparisons than pairs. © 2013 IEEE.

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This study aimed to establish optimal conditions for a cell culture system that would allow the measurement of 18:3n-3 (ALA) bioconversion into n-3 long-chain polyunsaturated fatty acid (n-3 LC-PUFA), and to determine the overall pathway kinetics. Using rat hepatocytes (FaO) as model cells, it was established that a maximum 20:5n-3 (EPA) production from 50 mM ALA initial concentration was achieved after 3 days of incubation. Next, it was established that a gradual increase in the ALA concentration from 0 up to 125mM lead to a proportional increase in EPA, without concomitant increase in further elongated or desaturated products, such as 22:5n-3 (DPA) and 22:6n-3 (DHA) in 3 day incubations. Of interest, ALA bioconversion products were observed in the culture medium. Therefore, in vitro experiments disregarding the medium fatty acid content are underestimating the metabolism efficiency. The novel application of the fatty acid mass balance (FAMB) method on cell culture system (cells with medium) enabled quantifying the apparent enzymatic activities for the biosynthesis of n-3 LC-PUFA. The activity of the key enzymes was estimated and showed that, under these conditions, 50% (Km) of the theoretical maximal (Vmax = 3654 mmol.g21 of cell protein.hour21) Fads2 activity on ALA can be achieved with 81 mM initial ALA. Interestingly, the apparent activity of Elovl2 (20:5n-3 elongation) was the slowest amongst other biosynthesis steps. Therefore, the possible improvement of Elovl2 activity is suggested toward a more efficient DHA production from ALA. The present study proposed and described an ad hoc optimised cell culture conditions and methodology towards achieving a reliable experimental platform, using FAMB, to assist in studying the efficiency of ALA bioconversion into n-3 LC-PUFA in vitro. The FAMB proved to be a powerful and inexpensive method to generate a detailed description of the kinetics of n-3 LC-PUFA biosynthesis enzymes activities in vitro.

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There is an increasing demand for high strength materials with the development of technology and critical applications. Nano materials are newly developed materials with extremely high strength for this purpose. Nanobainite is a dual phase material containing alternate layers of bainitic ferrite in nano dimensions and retained austenite. Nanobainite is produced by isothermally holding austenitized steel at a temperature of 200°C or less, depending on the chemical composition, for 6 10 days until bainite forms and then cooling to room temperature using austempering. The experimental design consisted of face milling under 12 combinations of Depth of Cut (DOC)-1, 2 and 3mm; cutting speed-100 and 150m/min; constant feed-0.15mm/rev and coolant on/off. The machinability of the material is assessed by means of analysis, such as surface texture and microhardness. The assessment also involves microstructural comparisons before and after milling. Future work involves quantifying the microstructural phase before and after milling using XRD. The results obtained are used to assess the most favorable condition to cut this new variety of steel.

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The demand for high strength materials and improvements in heat treatment techniques has given rise to this new form of high strength steel known as nanobainite steel. The production of nanobainite steel involves slow isothermal holding of austenitic steel around 200oC for 10 days, in order to obtain a carbon enriched austenite and cooling to room temperature using austempering. The microstructure of nanobainite steel is dual phase consisting of alternate layers of bainitic ferrite and austenite. The experimental design consists of face milling under 12 combination of Depth of Cut (DoC)-1, 2 and 3mm; cutting speed-100 and 150m/min; constant feed- 0.15mm/rev and coolant on/off. The machinability of the material is assessed by means of analysis such as metallography and cutting force analysis. The results obtained are used to assess the most favorable condition to machine this new variety of steel. Future work involves study on phase transformation by quantifying the microstructural phase before and after milling using XRD.

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Landfill waste has a negative impact on the environment and small and medium sized enterprises (SMEs) are believed to be significant contributors. There is little government or scholarly research, however, quantifying the collective volume of waste SMEs send to landfill. Where studies do exist they measure total volumes (landfill and recycling combined) and/or do not distinguish between specific waste streams (e.g. wood) and subcategories (e.g. dust). This paper contributes to knowledge by giving insight into the collective volume of waste of 404 SMEs, reconceptualising SME waste into subcategories and by measuring landfill volumes. It presents findings from these 404 Australian SMEs which found that, in descending order, cardboard, paper, plastic wrap, wood dust and particleboard were the subcategories these SMEs sent to landfill in the greatest volumes. It also argues that this reconceptualisation, and associated data collection protocols, have the potential to enable scholars and policy makers to determine the waste subcategories to which SMEs contribute most, formulate targeted interventions and research or evaluate environmental outcomes. © 2014 © 2014 Environment Institute of Australia and New Zealand Inc.