223 resultados para FRONTIERS


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Cough associated with exertion is often used as a surrogate marker of asthma. However, to date there are no studies that have objectively measured cough in association with exercise in children. Our primary aim was to examine whether children with a pre-existing cough have an increase in cough frequency during and post-exercise. We hypothesized that children with any coughing illness will have an increase in cough frequency post-exercise regardless of the presence of exercise-induced broncho-constriction (EIB) or atopy. In addition, we hypothesized that Fractional exhaled nitric oxide (FeNO) levels decreases post-exercise regardless of the presence of EIB or atopy. Children with chronic cough and a control group without cough undertook an exercise challenge, FeNO measurements and a skin prick test, and wore a 24-h voice recorder to objectively measure cough frequency. The association between recorded cough frequency, exercise, atopy, and presence of EIB was tested. We also determined if the change in FeNO post exercise related to atopy or EIB. Of the 50 children recruited (35 with cough, 15 control), 7 had EIB. Children with cough had a significant increase in cough counts (median 7.0, inter-quartile ranges, 0.5, 24.5) compared to controls (2.0, IQR 0, 5.0, p = 0.028) post-exercise. Presence of atopy or EIB did not influence cough frequency. FeNO level was significantly lower post-exercise in both groups but the change was not influenced by atopy or EIB. Cough post-exertion is likely a generic response in children with a current cough. FeNO level decreases post-exercise irrespective of the presence of atopy or EIB. A larger study is necessary confirm or refute our findings.

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Advances in medical science have presented both law and bioethics with some of the most fascinating questions of our time. As science continues to forge ahead into new frontiers, in fields such as reproductive technology, human genetics, cloning technologies, and stem cell research, questions have arisen over the role for law in regulating this new terrain. The speed with which medical science has advanced, and continues to advance, can make it difficult to formulate appropriate regulatory responses. The rapid pace of scientific change and the increasing complexity of the science can present hurdles and barriers to the engagement of the public with science and the legal and ethical issues raised by it.

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Background: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. Methods: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. Results: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging sub- stance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. Conclusion: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment.

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In this paper, we present fully Bayesian experimental designs for nonlinear mixed effects models, in which we develop simulation-based optimal design methods to search over both continuous and discrete design spaces. Although Bayesian inference has commonly been performed on nonlinear mixed effects models, there is a lack of research into performing Bayesian optimal design for nonlinear mixed effects models that require searches to be performed over several design variables. This is likely due to the fact that it is much more computationally intensive to perform optimal experimental design for nonlinear mixed effects models than it is to perform inference in the Bayesian framework. In this paper, the design problem is to determine the optimal number of subjects and samples per subject, as well as the (near) optimal urine sampling times for a population pharmacokinetic study in horses, so that the population pharmacokinetic parameters can be precisely estimated, subject to cost constraints. The optimal sampling strategies, in terms of the number of subjects and the number of samples per subject, were found to be substantially different between the examples considered in this work, which highlights the fact that the designs are rather problem-dependent and require optimisation using the methods presented in this paper.

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The endoplasmic reticulum (ER) is the central organelle in the eukaryotic secretory pathway. The ER functions in protein synthesis and maturation and is crucial for proper maintenance of cellular homeostasis and adaptation to adverse environments. Acting as a cellular sentinel, the ER is exquisitely sensitive to changing environments principally via the ER quality control machinery. When perturbed, ER-stress triggers a tightly regulated and highly conserved, signal transduction pathway known as the unfolded protein response (UPR) that prevents the dangerous accumulation of unfolded/misfolded proteins. In situations where excessive UPR activity surpasses threshold levels, cells deteriorate and eventually trigger programmed cell death (PCD) as a way for the organism to cope with dysfunctional or toxic signals. The programmed cell death that results from excessive ER stress in mammalian systems contributes to several important diseases including hypoxia, neurodegeneration, and diabetes. Importantly, hallmark features and markers of cell death that are associated with ER stress in mammals are also found in plants. In particular, there is a common, conserved set of chaperones that modulate ER cell death signaling. Here we review the elements of plant cell death responses to ER stress and note that an increasing number of plant-pathogen interactions are being identified in which the host ER is targeted by plant pathogens to establish compatibility.

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Purpose The purpose of this paper is to foster a common understanding of business process management (BPM) by proposing a set of ten principles that characterize BPM as a research domain and guide its successful use in organizational practice. Design/methodology/approach The identification and discussion of the principles reflects our viewpoint, which was informed by extant literature and focus groups, including 20 BPM experts from academia and practice. Findings We identify ten principles which represent a set of capabilities essential for mastering contemporary and future challenges in BPM. Their antonyms signify potential roadblocks and bad practices in BPM. We also identify a set of open research questions that can guide future BPM research. Research limitation/implication Our findings suggest several areas of research regarding each of the identified principles of good BPM. Also, the principles themselves should be systematically and empirically examined in future studies. Practical implications – Our findings allow practitioners to comprehensively scope their BPM initiatives and provide a general guidance for BPM implementation. Moreover, the principles may also serve to tackle contemporary issues in other management areas. Originality/value This is the first paper that distills principles of BPM in the sense of both good and bad practice recommendations. The value of the principles lies in providing normative advice to practitioners as well as in identifying open research areas for academia, thereby extending the reach and richness of BPM beyond its traditional frontiers.

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It has been shown that abilities in spatial learning and memory are adversely affected by aging. The present study was conducted to investigate whether increasing age has equal consequences for all types of spatial learning or impacts certain types of spatial learning selectively. Specifically, two major types of spatial learning, exploratory navigation and map reading, were contrasted. By combining a neuroimaging finding that the medial temporal lobe (MTL) is especially important for exploratory navigation and a neurological finding that the MTL is susceptible to age-related atrophy, it was hypothesized that spatial learning through exploratory navigation would exhibit a greater decline in later life than spatial learning through map reading. In an experiment, young and senior participants learned locations of landmarks in virtual environments either by navigating in them in the first-person perspective or by seeing aerial views of the environments. Results showed that senior participants acquired less accurate memories of the layouts of landmarks than young participants when they navigated in the environments, but the two groups did not differ in spatial learning performance when they viewed the environments from the aerial perspective. These results suggest that spatial learning through exploratory navigation is particularly vulnerable to adverse effects of aging, whereas elderly adults may be able to maintain their map reading skills relatively well.

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To provide card holder authentication while they are conducting an electronic transaction using mobile devices, VISA and MasterCard independently proposed two electronic payment protocols: Visa 3D Secure and MasterCard Secure Code. The protocols use pre-registered passwords to provide card holder authentication and Secure Socket Layer/ Transport Layer Security (SSL/TLS) for data confidentiality over wired networks and Wireless Transport Layer Security (WTLS) between a wireless device and a Wireless Application Protocol (WAP) gateway. The paper presents our analysis of security properties in the proposed protocols using formal method tools: Casper and FDR2. We also highlight issues concerning payment security in the proposed protocols.

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This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

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Chemotherapy resistance associated with recurrent disease is the major cause of poor survival of ovarian cancer patients. We have recently demonstrated activation of the JAK2/STAT3 pathway and the enhancement of a cancer stem cell (CSC)-like phenotype in ovarian cancer cells treated in vitro with chemotherapeutic agents. To elucidate further these mechanisms in vivo,we used a two-tiered paclitaxel treatment approach in nude mice inoculated with ovarian cancer cells. In the first approach, we demonstrate that a single intraperitoneal administration of paclitaxel in mice 7 days after subcutaneous transplantation of the HEY ovarian cancer cell line resulted in a significant increase in the expression of CA125, Oct4, and CD117 in mice xenografts compared to control mice xenografts which did not receive paclitaxel. In the second approach, mice were administered once weekly with paclitaxel and/or a daily dose of the JAK2-specific inhibitor, CYT387, over 4weeks. Mice receiving paclitaxel only demonstrated a significant decrease in tumor volume compared to control mice. At the molecular level, mouse tumors remaining after paclitaxel administration showed a significant increase in the expression of Oct4 and CD117 coinciding with a significant activation of the JAK2/STAT3 pathway compared to control tumors. The addition of CYT387 with paclitaxel resulted in the suppression of JAK2/STAT3 activation and abrogation of Oct4 and CD117 expression in mouse xenografts. This coincided with significantly smaller tumors in mice administered CYT387 in addition to paclitaxel, compared to the control group and the group of mice receiving paclitaxel only. These data suggest that the systemic administration of paclitaxel enhances Oct4- and CD117-associated CSC-like marker expression in surviving cancer cells in vivo, which can be suppressed by the addition of the JAK2-specific inhibitor CYT387, leading to a significantly smaller tumor burden. These novel findings have the potential for the development of CSC-targeted therapy to improve the treatment outcomes of ovarian cancer patients.

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The repair of DNA double-strand breaks (DSBs) is a critical cellular mechanism that exists to ensure genomic stability. DNA DSBs are the most deleterious type of insult to a cell’s genetic material and can lead to genomic instability, apoptosis, or senescence. Incorrectly repaired DNA DSBs have the potential to produce chromosomal translocations and genomic instability, potentially leading to cancer. The prevalence of DNA DSBs in cancer due to unregulated growth and errors in repair opens up a potential therapeutic window in the treatment of cancers. The cellular response to DNA DSBs is comprised of two pathways to ensure DNA breaks are repaired: homologous recombination and non-homologous end joining. Identifying chemotherapeutic compounds targeting proteins involved in these DNA repair pathways has shown promise as a cancer therapy for patients, either as a monotherapy or in combination with genotoxic drugs. From the beginning, there have been a number of chemotherapeutic compounds that have yielded successful responses in the clinic, a number that have failed (CGK-733 and iniparib), and a number of promising targets for future studies identified. This review looks in detail at how the cell responds to these DNA DSBs and investigates the chemotherapeutic avenues that have been and are currently being explored to target this repair process.

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This article presents a study of how humans perceive and judge the relevance of documents. Humans are adept at making reasonably robust and quick decisions about what information is relevant to them, despite the ever increasing complexity and volume of their surrounding information environment. The literature on document relevance has identified various dimensions of relevance (e.g., topicality, novelty, etc.), however little is understood about how these dimensions may interact. We performed a crowdsourced study of how human subjects judge two relevance dimensions in relation to document snippets retrieved from an internet search engine. The order of the judgment was controlled. For those judgments exhibiting an order effect, a q–test was performed to determine whether the order effects can be explained by a quantum decision model based on incompatible decision perspectives. Some evidence of incompatibility was found which suggests incompatible decision perspectives is appropriate for explaining interacting dimensions of relevance in such instances.

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Toll-like receptors (TLR) are key regulators of innate immune and inflammatory responses and their activation is linked to impaired glucose metabolism during metabolic disease. Determination of whether TLR4 signaling can be activated in the heart by insulin may shed light on the pathogenesis of diabetic cardiomyopathy, a process that is often complicated by obesity and insulin resistance. The aim of the current study was to determine if supraphysiological insulin concentrations alter the expression of TLR4, markers of TLR4 signaling and glucose transporters (GLUTs) in the heart. Firstly, the effect of insulin on TLR4 protein expression was investigated in vitro in isolated rat cardiac myocytes. Secondly, protein expression of TLR4, the pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) suppressor of cytokine signaling 3 (SOCS3) and GLUTs (1, 4, 8, 12) were examined in the equine ventricular myocardium following a prolonged, euglycemic, hyperinsulinemic clamp. Down-regulation of TLR4 protein content in rat cardiac myocytes was observed after incubation with a supraphysiologic concentration of insulin as well as in the equine myocardium after prolonged insulin infusion. Further, cardiac TLR4 expression was negatively correlated with serum insulin concentration. Markers of cardiac TLR4 signaling and GLUT expression were not affected by hyperinsulinemia and concomitant TLR4 down-regulation. Since TLRs are major determinants of the inflammatory response, our findings suggest that insulin infusion exerts an anti-inflammatory effect in the hearts of non-obese individuals. Understanding the regulation of cardiac TLR4 signaling during metabolic dysfunction will facilitate improved management of cardiac sequela to metabolic syndrome and diabetes.

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Bayesian experimental design is a fast growing area of research with many real-world applications. As computational power has increased over the years, so has the development of simulation-based design methods, which involve a number of algorithms, such as Markov chain Monte Carlo, sequential Monte Carlo and approximate Bayes methods, facilitating more complex design problems to be solved. The Bayesian framework provides a unified approach for incorporating prior information and/or uncertainties regarding the statistical model with a utility function which describes the experimental aims. In this paper, we provide a general overview on the concepts involved in Bayesian experimental design, and focus on describing some of the more commonly used Bayesian utility functions and methods for their estimation, as well as a number of algorithms that are used to search over the design space to find the Bayesian optimal design. We also discuss other computational strategies for further research in Bayesian optimal design.

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Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.