987 resultados para Carpenter, Matthew H. (Matthew Hale), 1824-1881.
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Introduction: Unaccustomed eccentric exercise often results in muscle damage and neutrophil activation. We examined changes in plasma cytokines stress hormones, creatine kinase activity and myoglobin concentration, neutrophil surface receptor expression, degranulation, and the capacity of neutrophils to generate reactive oxygen species in response to in vitro stimulation after downhill running. Methods: Ten well-trained male runners ran downhill on a treadmill at a gradient of -10% for 45 min at 60% V̇O2max. Blood was sampled immediately before (PRE) and after (POST), 1 h (1 h POST), and 24 h (24 h POST) after exercise. Results: At POST, there were significant increases (P < 0.01) in neutrophil count (32%), plasma interleukin (IL)-6 concentration (460%), myoglobin (Mb) concentration (1100%), and creatine kinase (CK) activity (40%). At 1 h POST, there were further increases above preexercise values for neutrophil count (85%), plasma Mb levels (1800%), and CK activity (56%), and plasma IL-6 concentration remained above preexercise values (410%) (P < 0.01). At 24 h POST, neutrophil counts and plasma IL-6 levels had returned to baseline, whereas plasma Mb concentration (100%) and CK activity (420%) were elevated above preexercise values (P < 0.01). There were no significant changes in neutrophil receptor expression, degranulation and respiratory burst activity, and plasma IL-8 and granulocyte-colony stimulating factor concentrations at any time after exercise. Neutrophil count correlated with plasma Mb concentration at POST (r = 0.64, P < 0.05), and with plasma CK activity at POST (r = 0.83, P < 0.01) and 1 h POST (r = 0.78, P < 0.01). Conclusion: Neutrophil activation remains unchanged after downhill running in well-trained runners, despite increases in plasma markers of muscle damage.
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Intense exercise stimulates the systemic release of a variety of factors that alter neutrophil surface receptor expression and functional activity. These alterations may influence resistance to infection after intense exercise. The aim of this study was to examine the influence of exercise intensity on neutrophil receptor expression, degranulation (measured by plasma and intracellular myeloperoxidase concentrations), and respiratory burst activity. Ten well-trained male runners ran on a treadmill for 60 min at 60% [moderate-intensity exercise (MI)] and 85% maximal oxygen consumption [high-intensity exercise (HI)]. Blood was drawn immediately before and after exercise and at 1 h postexercise. Immediately after HI, the expression of the neutrophil receptor CD16 was significantly below preexercise values (P < 0.01), whereas MI significantly reduced CD35 expression below preexercise values (P < 0.05). One hour after exercise at both intensities, there was a significant decline in CD11b expression (P < 0.05) and a further decrease in CD16 expression compared with preexercise values (P < 0.01). CD16 expression was lower 1 h after HI than 1 h after MI (P < 0.01). Immediately after HI, intracellular myeloperoxidase concentration was less than preexercise values (P < 0.01), whereas plasma myeloperoxidase concentration was greater (P < 0.01), indicating that HI stimulated neutrophil degranulation. Plasma myeloperoxidase concentration was higher immediately after HI than after MI (P < 0.01). Neutrophil respiratory burst activity increased after HI (P < 0.01). In summary, both MI and HI reduced neutrophil surface receptor expression. Although CD16 expression was reduced to a greater extent after HI, this reduction did not impair neutrophil degranulation and respiratory burst activity.
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Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.
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Completing a PhD on time is a complex process, influenced by many interacting factors. In this paper we take a Bayesian Network approach to analyzing the factors perceived to be important in achieving this aim. Focusing on a single research group in Mathematical Sciences, we develop a conceptual model to describe the factors considered to be important to students and then quantify the network based on five individual perspectives: the students, a supervisor and a university research students centre manager. The resultant network comprised 37 factors and 40 connections, with an overall probability of timely completion of between 0.6 and 0.8. Across all participants, the four factors that were considered to most directly influence timely completion were personal aspects, the research environment, the research project, and incoming skills.
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We performed an integrated genomic, transcriptomic and proteomic characterization of 373 endometrial carcinomas using array- and sequencing-based technologies. Uterine serous tumours and ∼25% of high-grade endometrioid tumours had extensive copy number alterations, few DNA methylation changes, low oestrogen receptor/progesterone receptor levels, and frequent TP53 mutations. Most endometrioid tumours had few copy number alterations or TP53 mutations, but frequent mutations in PTEN, CTNNB1, PIK3CA, ARID1A and KRAS and novel mutations in the SWI/SNF chromatin remodelling complex gene ARID5B. A subset of endometrioid tumours that we identified had a markedly increased transversion mutation frequency and newly identified hotspot mutations in POLE. Our results classified endometrial cancers into four categories: POLE ultramutated, microsatellite instability hypermutated, copy-number low, and copy-number high. Uterine serous carcinomas share genomic features with ovarian serous and basal-like breast carcinomas. We demonstrated that the genomic features of endometrial carcinomas permit a reclassification that may affect post-surgical adjuvant treatment for women with aggressive tumours.
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Humans have altered environments and enhanced their wellbeing unlike any other creature on the planet (Hielman & Donda, 2007); this is no different whether the environment is ecological, social or organizational. In recent times, the debate regarding greenhouse effects on the global weather patterns and the sustainment of the earths temperature necessary for life support has become quite infamously problematic as society pushes to find new sources of energy both renewable and environmentally sustainable. The feedback received on CSG from both government and companies alike is that the opportunities this industry creates has a lasting range of social and economic benefits worth over fifty (50) billion dollars in projects (Queensland Government, 2013). This however, has been overshadowed by social activist and lobbyist groups as ‘Lock the Gate Alliance’ saying, as one part of their report noted from the National Water Commission, “coal seam gas development could cause significant social impacts by disrupting current land-use practices and the local environment through infrastructure construction and access” (Lock the Gate Alliance, n.d.), and “In recent years both a NSW and Federal Senate inquiry into coal seam gas production were deliberately mislead by an organization that claims to work on behalf of the farming community, This is the battle for the end of the fossil fuel industry. This is the end game..." (Ward, 2013).
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Biological systems involving proliferation, migration and death are observed across all scales. For example, they govern cellular processes such as wound-healing, as well as the population dynamics of groups of organisms. In this paper, we provide a simplified method for correcting mean-field approximations of volume-excluding birth-death-movement processes on a regular lattice. An initially uniform distribution of agents on the lattice may give rise to spatial heterogeneity, depending on the relative rates of proliferation, migration and death. Many frameworks chosen to model these systems neglect spatial correlations, which can lead to inaccurate predictions of their behaviour. For example, the logistic model is frequently chosen, which is the mean-field approximation in this case. This mean-field description can be corrected by including a system of ordinary differential equations for pair-wise correlations between lattice site occupancies at various lattice distances. In this work we discuss difficulties with this method and provide a simplication, in the form of a partial differential equation description for the evolution of pair-wise spatial correlations over time. We test our simplified model against the more complex corrected mean-field model, finding excellent agreement. We show how our model successfully predicts system behaviour in regions where the mean-field approximation shows large discrepancies. Additionally, we investigate regions of parameter space where migration is reduced relative to proliferation, which has not been examined in detail before, and our method is successful at correcting the deviations observed in the mean-field model in these parameter regimes.
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In a recent paper, Gordon, Muratov, and Shvartsman studied a partial differential equation (PDE) model describing radially symmetric diffusion and degradation in two and three dimensions. They paid particular attention to the local accumulation time (LAT), also known in the literature as the mean action time, which is a spatially dependent timescale that can be used to provide an estimate of the time required for the transient solution to effectively reach steady state. They presented exact results for three-dimensional applications and gave approximate results for the two-dimensional analogue. Here we make two generalizations of Gordon, Muratov, and Shvartsman’s work: (i) we present an exact expression for the LAT in any dimension and (ii) we present an exact expression for the variance of the distribution. The variance provides useful information regarding the spread about the mean that is not captured by the LAT. We conclude by describing further extensions of the model that were not considered by Gordon,Muratov, and Shvartsman. We have found that exact expressions for the LAT can also be derived for these important extensions...
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This thesis investigates whether receiving an important award in academia raises recipients’ subsequent research productivity and status compared to a synthetic control group of non-recipient scholars with similar previous research performance. It examines the case of being awarded the John Bates Clark Medal and becoming a Fellow of the Econometric Society finding evidence of positive incentive and status effects that raise both productivity and citation levels.
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Within criminological literature, there are growing references to a 'queer/ed criminology'. To date, ‘queer criminology’ remains a loose collection of studies and criminal-justice related commentary that uses the term 'queer'. Amid the growing calls for the more substantial development of these criminological studies, it is timely to reflect on the ways that the term ‘queer’ has been used in these discourses, to what ends, and with what effects. This paper considers the manner in which the term 'queer' has been used in these criminological and criminal justice discourses. It suggests that ‘queer’ has been used in two dominant ways: as an 'umbrella' term for lesbian, gay, bisexual, intersex, and queer-identified people; and to signify the use of theoretical tools with which to represent sexuality- and gender-diverse people more effectively within criminological research. The paper will argue that these ways of using ‘queer’ have a variety of implications and effects. Specifically, using ‘queer’ as an umbrella term has the potential to reinforce identity categories and the politics that surround identities (a critique that has often appeared in queer contexts), while using it as a theoretical tool potentially reproduces various investments in criminology and criminal justice institutions. Both uses may preclude other productive avenues for critique opened up by the term ‘queer’. The paper will conclude by suggesting that using ‘queer’ as a verb to signify a more deconstructive project directed towards criminology is a possible direction for these discussions. While this approach has its own effects, and articulates with existing deconstructive approaches in criminology, it is important to explore these possibilities at this point in the development of a ‘queer/ed criminology’ for two reasons: it highlights that multiple, and often competing, ‘queer/ed criminologies’ exist; and it expands the diverse possibilities heralded by the notion of ‘queer’.
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Practitioners from both the upstream oil and gas industry and the space and satellite sector have repeatedly noted several striking similarities between the two industries over the years, which have in turn resulted in many direct comparisons in the media and industry press. The two sectors have previously worked together and shared ideas in ways that have yielded some important breakthroughs, but relatively little sharing or cross-pollination has occurred in the area of asset maintenance. This is somewhat surprising in light of the fact that here, too, the sectors have much in common. This paper accordingly puts forward the viewpoint that the upstream oil and gas industry could potentially make significant improvements in asset maintenance—specifically, with regard to offshore platforms and remote pipelines—by selectively applying some aspects of the maintenance strategies and philosophies that have been learned in the space and satellite sector. The paper then offers a research agenda toward accelerating the rate of learning and sharing between the two industries in this domain, and concludes with policy recommendations that could facilitate this kind of cross-industry learning.
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Dr Kathy A. Mills provides a critical synthesis and review of the new book by Matthew W. Hughey entitle: White Bound: Nationalists, Antiractists, and the Shared Meanings of Race, published by Standford University Press in 2012. A sample of Dr Mills' review reads: "The author positions race squarely at the center to challenge the shared assumptions of white supremacist logic on both sides of the debate. The clever thesis blurs the boundaries between “good whites” and “bad whites”, rendering the white reader intellectually stimulated, but existentially unchanged – White Bound – as the author ponders: “Perhaps we have met the enemy, and he [it] is us” (p.193)...The unanswered question that remains is: How do we resist the various “shades” of white supremacy to pursue counter-hegemonic practices?"
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Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.
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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.
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Cell trajectory data is often reported in the experimental cell biology literature to distinguish between different types of cell migration. Unfortunately, there is no accepted protocol for designing or interpreting such experiments and this makes it difficult to quantitatively compare different published data sets and to understand how changes in experimental design influence our ability to interpret different experiments. Here, we use an individual based mathematical model to simulate the key features of a cell trajectory experiment. This shows that our ability to correctly interpret trajectory data is extremely sensitive to the geometry and timing of the experiment, the degree of motility bias and the number of experimental replicates. We show that cell trajectory experiments produce data that is most reliable when the experiment is performed in a quasi 1D geometry with a large number of identically{prepared experiments conducted over a relatively short time interval rather than few trajectories recorded over particularly long time intervals.