138 resultados para Response models
Resumo:
Background: The immune response to Porphyromonas gingivalis in the mouse abscess model is known to be dependent upon CD4 T-cell activation and the regulatory role of cytokines. The role of interleukin-10 (IL-10) in this mouse model was examined in vivo. Methods: One-week-old, female BALB/c mice were divided into 4 groups. Groups 1 and 2 were given intraperitoneal (ip) injections of phosphate buffered saline (PBS) weekly for 5 weeks. Group 3 was given an ip injection of rat immunoglobulin. Group 4 was injected with rat anti-IL-10 antibodies. At week 6, group 1 was sham-immunized with PBS, and groups 2, 3, and 4 were injected with P gingivalis lipopolysaccharide (Pg-LPS) weekly for 2 weeks. One week after the final immunization, delayed-type hypersensitivity (DTH) was assessed by footpad swelling to Pg-LPS. The level of serum antibodies to Pg-LPS and IFN-gamma (IFN-gamma) was determined by enzyme-linked immunosorbent assay. Dorsal abscess formation induced by the injection of viable P gingivalis was examined daily for 30 days. Results: The footpad swelling of the anti-IL-10-treated group (group 4) was significantly higher than that of groups 1 to 3. Similarly, the serum IFN-gamma level in group 4 was much higher than that of the other experimental groups. There was no significant difference in serum IgG antibodies to Pg-LPS in any of the experimental groups. However, the level of IgM antibodies in group 4 mice was significantly lower than that in groups 2 and 3. In addition, serum IgG1 was suppressed in group 4 mice, while IgG2a antibodies were raised. However, there was no difference observed between the levels of IgG2b and IgG3 antibodies in any group of mice. The lesions in sham-immunized mice (group 1) persisted for 30 days, and those in group 2 and 3 were undetected by day 18 and 20, respectively. In sharp contrast, lesions in group 4 had healed completely by day 13. Conclusions: This study has shown that IL-10 depletion in vivo in P gingivalis LPS-induced immune response in mice led to an elevated DTH response, an increase in serum IFN-gamma levels, and raised levels of IgG and IgG2a antibodies. Treatment with anti-IL-10 antibodies resulted in suppressed IgG I and IgM responses and a more rapid healing of abscesses than in non-IL-10-depleted mice. These results suggest that IL-10 depletion in Pg-LPS-induced immune response in mice may lead to a Th1-like immune response and provide strong protection against a subsequent challenge with live P gingivalis in an abscess model.
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Several cystic fibrosis (CF) mouse models demonstrate an increased susceptibility to Pseudomonas aeruginosa lung infection, characterized by excessive inflammation and high rates of mortality. Here we developed a model of chronic P. aeruginosa lung disease in mice homozygous for the murine CF transmembrane conductance regulator G551D mutation that provides an excellent model for CF lung disease. After 3 days of infection with mucoid P. aeruginosa entrapped in agar beads, the G551D animals lost substantially more body weight than non-CF control animals and were less able to control the infection, harboring over 40-fold more bacteria in the lung. The airways of infected G551D animals contained altered concentrations of the inflammatory mediators tumor necrosis factor-alpha, KC/N51, and macrophage inflammatory protein-2 during the first 2 days of infection, suggesting that an ineffective inflammatory response is partly responsible for the clearance defect.
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Background: Susceptibility to periodontal infections may, in part, be genetically determined. Porphyromonas gingivalis is a major periodontopathogen, and the immune response to this organism requires T-cell help. The aim of the present study was to examine the specific T-cell cytokine responses to P gingivalis outer membrane antigens in a mouse model and their relationship with H-2 haplotype. Methods: BALB/c and DBA/2J (H-2(d)), CBACaH (H-2(k)), and C57BL6 (H-2(b)) mice were immunized with P gingivalis outer membrane antigens weekly for 3 weeks. One week after the final injection, the spleens were removed, and 6 T-cell lines specific for P gingivalis were established for each mouse strain. The percentage of CD4 and CD8 cells in the P gingivalis-specific T-cell lines staining positive for intracytoplasmic interleukin (IL)-4, interferon (IFN)-gamma, and IL-10 was determined by 2-color flow cytometry. Results: The cytokine profiles of T-cell lines from BALB/c and DBA/2J mice showed no significant differences. Significantly fewer IL4+, IFN-gamma+, and IL-10+ CD4 cells than IL-4+, IFN-gamma+, and IL-10+ CD8 cells, respectively, were demonstrated for both strains. P gingivalis-specific T-cell lines generated from CBACaH mice were similar to those generated from BALB/c and DBA/2J mice; however, the mean percentage of IL4+ CD4 cells in CBACaH mice was lower than the percentage of IFN-gamma+ CD4 cells. Also, the mean percentage of IFN-gamma+ CD4 cells in CBACaH mice was significantly increased compared to DBA/2J mice. Unlike the other 3 strains, T-cell lines established from C57BL6 mice contained similar percentages of cytokine-positive cells, although the percentage of IL-4+ CD4 cells was reduced in comparison to the percentage of CD8 cells. However, comparisons with the other 3 strains demonstrated a higher percentage of IL-4+ CD4 cells than in lines established from the spleens of DBA/2J mice, IFN-gamma+ CD4 cells than in lines established from BALB/c and CBACaH mice, and IL-10+ CD4 cells than in lines established from all 3 other strains. No significant differences in the percentage of positive CD8 cells were demonstrated between lines in the 4 strains of mice. Conclusion: The specific T-cell response to P gingivalis in mice may, in the case of the CD4 response, depend on MHC genes. These findings are consistent with the concept that patient susceptibility is important to the outcome of periodontal infection and may, in part, be genetically determined.
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Using a student sample (n = 692) and an organization sample (n = 180), we scrutinized two morning-evening orientation scales using item response theory (IRT) methods. We used IRT to compare the measurement precision of the Composite Scale (CS) and the Early/Late Preferences Scale (PS). The CS had slightly higher measurement precision at all ranges of orientations, except for extreme morning and evening orientations for which the PS had slightly higher precision. IRT item-level statistics were also computed to try to understand how morning-orientation items functioned. Items that asked questions about morning activities tended to be more discriminating indicators of morning-orientation than items that asked about evening or peak performance activities. Items that involved unpleasant activities were less frequently endorsed than items that involved neutral or enjoyable activities. Implications for measurement of morning-evening orientation are discussed. (C) 2002 Elsevier Science Ltd. All rights reserved.
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The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.
Resumo:
The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.
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Blast fragmentation can have a significant impact on the profitability of a mine. An optimum run of mine (ROM) size distribution is required to maximise the performance of downstream processes. If this fragmentation size distribution can be modelled and controlled, the operation will have made a significant advancement towards improving its performance. Blast fragmentation modelling is an important step in Mine to Mill™ optimisation. It allows the estimation of blast fragmentation distributions for a number of different rock mass, blast geometry, and explosive parameters. These distributions can then be modelled in downstream mining and milling processes to determine the optimum blast design. When a blast hole is detonated rock breakage occurs in two different stress regions - compressive and tensile. In the-first region, compressive stress waves form a 'crushed zone' directly adjacent to the blast hole. The second region, termed the 'cracked zone', occurs outside the crush one. The widely used Kuz-Ram model does not recognise these two blast regions. In the Kuz-Ram model the mean fragment size from the blast is approximated and is then used to estimate the remaining size distribution. Experience has shown that this model predicts the coarse end reasonably accurately, but it can significantly underestimate the amount of fines generated. As part of the Australian Mineral Industries Research Association (AMIRA) P483A Mine to Mill™ project, the Two-Component Model (TCM) and Crush Zone Model (CZM), developed by the Julius Kruttschnitt Mineral Research Centre (JKMRC), were compared and evaluated to measured ROM fragmentation distributions. An important criteria for this comparison was the variation of model results from measured ROM in the-fine to intermediate section (1-100 mm) of the fragmentation curve. This region of the distribution is important for Mine to Mill™ optimisation. The comparison of modelled and Split ROM fragmentation distributions has been conducted in harder ores (UCS greater than 80 MPa). Further work involves modelling softer ores. The comparisons will be continued with future site surveys to increase confidence in the comparison of the CZM and TCM to Split results. Stochastic fragmentation modelling will then be conducted to take into account variation of input parameters. A window of possible fragmentation distributions can be compared to those obtained by Split . Following this work, an improved fragmentation model will be developed in response to these findings.
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For dynamic simulations to be credible, verification of the computer code must be an integral part of the modelling process. This two-part paper describes a novel approach to verification through program testing and debugging. In Part 1, a methodology is presented for detecting and isolating coding errors using back-to-back testing. Residuals are generated by comparing the output of two independent implementations, in response to identical inputs. The key feature of the methodology is that a specially modified observer is created using one of the implementations, so as to impose an error-dependent structure on these residuals. Each error can be associated with a fixed and known subspace, permitting errors to be isolated to specific equations in the code. It is shown that the geometric properties extend to multiple errors in either one of the two implementations. Copyright (C) 2003 John Wiley Sons, Ltd.
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Life cycle models have become important in explaining the changing size structure of firms based on the carrying capacity of regions or industries. In particular, the population ecology model predicts stages of growth, maturity and eventually decline in the number of firms in an industry. There has been criticism of such models because of their focus on external variables as pre-determinants of the potential for enterprise development. This paper attempts to reconcile the external focus of the population ecology model with relevant internal management factors in enterprise development. A survey was conducted of Australian services exporters, and the results not only confirm the existence of four separate life cycle stages in the population ecology model, but also identify the external and internal variables that are strategically relevant at each of the stages. The findings provide potentially useful information in a range of contexts including the design of small business assistance as well a providing “guide posts” to entrepreneurs engaged in enterprise development.
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We investigate whether relative contributions of genetic and shared environmental factors are associated with an increased risk in melanoma. Data from the Queensland Familial Melanoma Project comprising 15,907 subjects arising from 1912 families were analyzed to estimate the additive genetic, common and unique environmental contributions to variation in the age at onset of melanoma. Two complementary approaches for analyzing correlated time-to-onset family data were considered: the generalized estimating equations (GEE) method in which one can estimate relationship-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modeled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov Chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the free ware package BUGS. In addition, we also used a Bayesian model to investigate the relative contribution of genetic and environmental effects on the expression of naevi and freckles, which are known risk factors for melanoma.
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Descriptive models of social response are concerned with identifying and discriminating between different types of response to social influence. In a previous article (Nail, MacDonald, & Levy, 2000), the authors demonstrated that 4 conceptual dimensions are necessary to adequately distinguish between such phenomena as conformity, compliance, contagion, independence, and anticonformity in a single model. This article expands the scope of the authors' 4-dimensional approach by reviewing selected experimental and cultural evidence, further demonstrating the integrative power of the model. This review incorporates political psychology, culture and aggression, self-persuasion, group norms, prejudice, impression management, psychotherapy, pluralistic ignorance, bystander intervention/nonintervention, public policy, close relationships, and implicit attitudes.
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Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.
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In comments on G. MacDonald and M. R. Leary (2005), J. Panksepp (2005) argued for more emphasis on social pain mechanisms, whereas P. J. Corr (2005) argued for more emphasis on physical defense mechanisms. In response to the former, the authors clarify their positions on the topics of anger, the usefulness of rat models, the role of analgesic mechanisms, and basic motivational processes. In response to the latter, the authors clarify their positions on the topics of the relation of social exclusion to fear, the value of the pain affect construct, and the nature of the social pain experience. The authors conclude that consideration of the roles of both social pain and defense mechanisms is essential to best understand human response to social exclusion.
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Standard factorial designs sometimes may be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Exact designs are investigated for two applications, and their advantages over factorial and central composite designs are demonstrated.