947 resultados para Dependent variable problem
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Drosophila arginine methyl-transferase 4 (DART4) belongs to the type I class of arginine methyltransferases. It catalyzes the methylation of arginine residues to monomethylarginines and asymmetrical dimethylarginines. The DART4 sequence is highly similar to mammalian PRMT4/CARM1, and DART4 substrate specificity has been conserved, too. Recently it was suggested that DART4/Carmer functions in ecdysone receptor mediated apoptosis of the polytene larval salivary glands and an apparent up-regulation of DART4/Carmer mRNA levels before tissue histolysis was reported. Here we show that in Drosophila larvae, DART4 is mainly expressed in the imaginal disks and in larval brains, and to a much lesser degree in the polytene larval tissue such as salivary glands. In glands, DART4 protein is present in the cytoplasm and the nucleus. The nuclear signal emanates from the extrachromosomal domain and gets progressively restricted to the region of the nuclear lamina upon pupariation. Surprisingly, DART4 levels do not increase in salivary glands during pupariation, and overexpression of DART4 does not cause precautious cell death in the glands. Furthermore, over- and misexpression of DART4 under the control of the alpha tubulin promoter do not lead to any major problem in the life of a fly. This suggests that DART4 activity is regulated at the posttranslational level and/or that it acts as a true cofactor in vivo. We present evidence that nuclear localization of DART4 may contribute to its function because DART4 accumulation changes from a distribution with a strong cytoplasmic component during the transcriptional quiescence of the young embryo to a predominantly nuclear one at the onset of zygotic transcription.
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Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.
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Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.
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STATEMENT OF PROBLEM: A tapered implant with continuously changing threads purported to provide stable tissue support and allow immediate function has been developed. Treatment success and stabilization of supporting tissues over time require documentation. PURPOSE: The purpose of this prospective, randomized, controlled, multicenter study was to evaluate changes in bone level and soft tissue behavior between the novel implant (NobelActive/NA) and a standard tapered implant (NobelReplace Tapered Groovy/NR) with regard to immediate function. MATERIAL AND METHODS: A total of 177 patients randomly allocated to 3 treatment groups (2 different test implant groups: NA Internal (n=117; internal connection) and External (n=82), and 1 standard treatment group, NR (n=126)) received 325 implants. Implants were placed into healed sites, and all but 6 implants were immediately nonocclusally loaded. Clinical and radiographic evaluations of treatment success, crestal bone levels, and soft tissue changes were performed at the time of placement and after 3, 6, and 12 months. Log-Rank test was used to analyze the differences in survival rate. Marginal bone level was compared using the Kruskal-Wallis test and Mann-Whitney U-test (alpha=.05). RESULTS: One-year cumulative survival rates were comparable (96.6% for NA Internal; 96.3% for NA External; 97.6% for NR; P=.852; Log-Rank). Mean (SD) change in bone level was -0.95 mm (1.37) for NA Internal, -0.64 mm (0.97) for NA External, and -0.63 mm (1.18) for NR (P=.589; Kruskal-Wallis). Stable soft tissues and significantly increased papilla scores (P<.001; Wilcoxon signed-rank) were observed for all implant types. CONCLUSIONS: The novel implants showed high survival rates as well as stable bone and soft tissue levels after 1 year, and may be recommended for clinical use, even under immediate function.
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Increasing demand for marketing accountability requires an efficient allocation of marketing expenditures. Managers who know the elasticity of their marketing instruments can allocate their budgets optimally. Meta-analyses offer a basis for deriving benchmark elasticities for advertising. Although they provide a variety of valuable insights, a major shortcoming of prior meta-analyses is that they report only generalized results as the disaggregated raw data are not made available. This problem is highly relevant because coding of empirical studies, at least to a certain extent, involves subjective judgment. For this reason, meta-studies would be more valuable if researchers and practitioners had access to disaggregated data allowing them to conduct further analyses of individual, e.g., product-level-specific, interests. We are the first to address this gap by providing (1) an advertising elasticity database (AED) and (2) empirical generalizations about advertising elasticities and their determinants. Our findings indicate that the average current-period advertising elasticity is 0.09, which is substantially smaller than the value 0f 0.12 that was recently reported by Sethuraman, Tellis, and Briesch (2011). Furthermore, our meta-analysis reveals a wide range of significant determinants of advertising elasticity. For example, we find that advertising elasticities are higher (i) for hedonic and experience goods than for other goods; (ii) for new than for established goods; (iii) when advertising is measured in gross rating points (GRP) instead of absolute terms; and (iv) when the lagged dependent or lagged advertising variable is omitted.
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If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.
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An exact knowledge of the kinetic nature of the interaction between the stimulatory G protein (G$\sb{\rm s}$) and the adenylyl cyclase catalytic unit (C) is essential for interpreting the effects of Gs mutations and expression levels on cellular response to a wide variety of hormones, drugs, and neurotransmitters. In particular, insight as to the association of these proteins could lead to progress in tumor biology where single spontaneous mutations in G proteins have been associated with the formation of tumors (118). The question this work attempts to answer is whether the adenylyl cyclase activation by epinephrine stimulated $\beta\sb2$-adrenergic receptors occurs via G$\sb{\rm s}$ proteins by a G$\sb{\rm s}$ to C shuttle or G$\sb{\rm s}$-C precoupled mechanism. The two forms of activation are distinguishable by the effect of G$\sb{\rm s}$ levels on epinephrine stimulated EC50 values for cyclase activation.^ We have made stable transfectants of S49 cyc$\sp-$ cells with the gene for the $\alpha$ protein of G$\sb{\rm s}$ $(\alpha\sb{\rm s})$ which is under the control of the mouse mammary tumor virus LTR promoter (110). Expression of G$\sb{\rm s}\alpha$ was then controlled by incubation of the cells for various times with 5 $\mu$M dexamethasone. Expression of G$\sb{\rm s}\alpha$ led to the appearance of GTP shifts in the competitive binding of epinephrine with $\sp{125}$ICYP to the $\beta$-adrenergic receptors and to agonist dependent adenylyl cyclase activity. High expression of G$\sb{\rm s}\alpha$ resulted in lower EC50's for the adenylyl cyclase activity in response to epinephrine than did low expression. By kinetic modelling, this result is consistent with the existence of a shuttle mechanism for adenylyl cyclase activation by hormones.^ One item of concern that remains to be addressed is the extent to which activation of adenylyl cyclase occurs by a "pure" shuttle mechanism. Kinetic and biochemical experiments by other investigators have revealed that adenylyl cyclase activation, by hormones, may occur via a Gs-C precoupled mechanism (80, 94, 97). Activation of adenylyl cyclase, therefore, probably does not occur by either a pure "'Shuttle" or "Gs-C Precoupled" mechanism, but rather by a "Hybrid" mechanism. The extent to which either the shuttle or precoupled mechanism contributes to hormone stimulated adenylyl cyclase activity is the subject of on-going research. ^
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AIMS CO₂ is an intrinsic vasodilator for cerebral and myocardial blood vessels. Myocardial vasodilation without a parallel increase of the oxygen demand leads to changes in myocardial oxygenation. Because apnoea and hyperventilation modify blood CO₂, we hypothesized that voluntary breathing manoeuvres induce changes in myocardial oxygenation that can be measured by oxygenation-sensitive cardiovascular magnetic resonance (CMR). METHODS AND RESULTS Fourteen healthy volunteers were studied. Eight performed free long breath-hold as well as a 1- and 2-min hyperventilation, whereas six aquatic athletes were studied during a 60-s breath-hold and a free long breath-hold. Signal intensity (SI) changes in T₂*-weighted, steady-state free precession, gradient echo images at 1.5 T were monitored during breathing manoeuvres and compared with changes in capillary blood gases. Breath-holds lasted for 35, 58 and 117 s, and hyperventilation for 60 and 120 s. As expected, capillary pCO₂ decreased significantly during hyperventilation. Capillary pO₂ decreased significantly during the 117-s breath-hold. The breath-holds led to a SI decrease (deoxygenation) in the left ventricular blood pool, while the SI of the myocardium increased by 8.2% (P = 0.04), consistent with an increase in myocardial oxygenation. In contrast, hyperventilation for 120 s, however, resulted in a significant 7.5% decrease in myocardial SI/oxygenation (P = 0.02). Change in capillary pCO₂ was the only independently correlated variable predicting myocardial oxygenation changes during breathing manoeuvres (r = 0.58, P < 0.01). CONCLUSION In healthy individuals, breathing manoeuvres lead to changes in myocardial oxygenation, which appear to be mediated by CO₂. These changes can be monitored in vivo by oxygenation-sensitive CMR and thus, may have value as a diagnostic tool.
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The intensity of long-range correlations observed with the classical HMBC pulse sequence using static optimization of the long-range coupling delay is directly related to the size of the coupling constant and is often set as a compromise. As such, some long-range correlations might appear with a reduced intensity or might even be completely absent from the spectra. After a short introduction, this third manuscript will give a detailed review of some selected HMBC variants dedicated to improve the detection of long-range correlations, such as the ACCORD-HMBC, CIGAR-HMBC, and Broadband HMBC experiments. Practical details about the accordion optimization, which affords a substantial improvement in both the number and intensity of the long-range correlations observed, but introduces a modulation in F1, will be discussed. The incorporation of the so-called constant time variable delay in the CIGAR-HMBC experiment, which can trigger or even completely suppress 1H–1H coupling modulation inherent to the utilization of the accordion principle, will be also discussed. The broadband HMBC scheme, which consists of recording a series of HMBC spectra with different delays set as a function of the long-range heteronuclear coupling constant ranges and transverse relaxation times T2, is also examined.
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The production of electron–positron pairs in time-dependent electric fields (Schwinger mechanism) depends non-linearly on the applied field profile. Accordingly, the resulting momentum spectrum is extremely sensitive to small variations of the field parameters. Owing to this non-linear dependence it is so far unpredictable how to choose a field configuration such that a predetermined momentum distribution is generated. We show that quantum kinetic theory along with optimal control theory can be used to approximately solve this inverse problem for Schwinger pair production. We exemplify this by studying the superposition of a small number of harmonic components resulting in predetermined signatures in the asymptotic momentum spectrum. In the long run, our results could facilitate the observation of this yet unobserved pair production mechanism in quantum electrodynamics by providing suggestions for tailored field configurations.
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Pregnant BALB/c mice have been widely used as an in vivo model to study Neospora caninum infection biology and to provide proof-of-concept for assessments of drugs and vaccines against neosporosis. The fact that this model has been used with different isolates of variable virulence, varying infection routes and differing methods to prepare the parasites for infection, has rendered the comparison of results from different laboratories impossible. In most studies, mice were infected with similar number of parasites (2 × 10(6)) as employed in ruminant models (10(7) for cows and 10(6) for sheep), which seems inappropriate considering the enormous differences in the weight of these species. Thus, for achieving meaningful results in vaccination and drug efficacy experiments, a refinement and standardization of this experimental model is necessary. Thus, 2 × 10(6), 10(5), 10(4), 10(3) and 10(2) tachyzoites of the highly virulent and well-characterised Nc-Spain7 isolate were subcutaneously inoculated into mice at day 7 of pregnancy, and clinical outcome, vertical transmission, parasite burden and antibody responses were compared. Dams from all infected groups presented nervous signs and the percentage of surviving pups at day 30 postpartum was surprisingly low (24%) in mice infected with only 10(2) tachyzoites. Importantly, infection with 10(5) tachyzoites resulted in antibody levels, cerebral parasite burden in dams and 100% mortality rate in pups, which was identical to infection with 2 × 10(6) tachyzoites. Considering these results, it is reasonable to lower the challenge dose to 10(5) tachyzoites in further experiments when assessing drugs or vaccine candidates.
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Keel bone damage (KBD) is a critical issue facing the laying hen industry today as a result of the likely pain leading to compromised welfare and the potential for reduced productivity. Recent reports suggest that damage, while highly variable and likely dependent on a host of factors, extends to all systems (including battery cages, furnished cages, and non-cage systems), genetic lines, and management styles. Despite the extent of the problem, the research community remains uncertain as to the causes and influencing factors of KBD. Although progress has been made investigating these factors, the overall effort is hindered by several issues related to the assessment of KBD, including quality and variation in the methods used between research groups. These issues prevent effective comparison of studies, as well as difficulties in identifying the presence of damage leading to poor accuracy and reliability. The current manuscript seeks to resolve these issues by offering precise definitions for types of KBD, reviewing methods for assessment, and providing recommendations that can improve the accuracy and reliability of those assessments.
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Keel bone damage (KBD) is a critical issue facing the contemporary laying hen industry due to the likely pain leading to compromised welfare and reduced productivity. Recent reports suggest that KBD, while highly variable and likely dependent on a host of factors, extends to all housing systems (including traditional battery cages, furnished cages and non-cage systems), genetic lines, and management styles. Despite the extent of the problem, the research community remains uncertain as to the causes and influencing factors of KBD. To combat these issues, the current review was produced following discussions from the 1st International Keel Bone Damage Workshop held in Switzerland in April 2014. This exercise sought to assess current knowledge, foster novel collaborations, propose unique methodologies and highlight the key areas where innovative research is needed. The following paper is based on the content of those discussions and presents nine recommendations for future research efforts.
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This thesis project is motivated by the potential problem of using observational data to draw inferences about a causal relationship in observational epidemiology research when controlled randomization is not applicable. Instrumental variable (IV) method is one of the statistical tools to overcome this problem. Mendelian randomization study uses genetic variants as IVs in genetic association study. In this thesis, the IV method, as well as standard logistic and linear regression models, is used to investigate the causal association between risk of pancreatic cancer and the circulating levels of soluble receptor for advanced glycation end-products (sRAGE). Higher levels of serum sRAGE were found to be associated with a lower risk of pancreatic cancer in a previous observational study (255 cases and 485 controls). However, such a novel association may be biased by unknown confounding factors. In a case-control study, we aimed to use the IV approach to confirm or refute this observation in a subset of study subjects for whom the genotyping data were available (178 cases and 177 controls). Two-stage IV method using generalized method of moments-structural mean models (GMM-SMM) was conducted and the relative risk (RR) was calculated. In the first stage analysis, we found that the single nucleotide polymorphism (SNP) rs2070600 of the receptor for advanced glycation end-products (AGER) gene meets all three general assumptions for a genetic IV in examining the causal association between sRAGE and risk of pancreatic cancer. The variant allele of SNP rs2070600 of the AGER gene was associated with lower levels of sRAGE, and it was neither associated with risk of pancreatic cancer, nor with the confounding factors. It was a potential strong IV (F statistic = 29.2). However, in the second stage analysis, the GMM-SMM model failed to converge due to non- concaveness probably because of the small sample size. Therefore, the IV analysis could not support the causality of the association between serum sRAGE levels and risk of pancreatic cancer. Nevertheless, these analyses suggest that rs2070600 was a potentially good genetic IV for testing the causality between the risk of pancreatic cancer and sRAGE levels. A larger sample size is required to conduct a credible IV analysis.^
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It is well known that an identification problem exists in the analysis of age-period-cohort data because of the relationship among the three factors (date of birth + age at death = date of death). There are numerous suggestions about how to analyze the data. No one solution has been satisfactory. The purpose of this study is to provide another analytic method by extending the Cox's lifetable regression model with time-dependent covariates. The new approach contains the following features: (1) It is based on the conditional maximum likelihood procedure using a proportional hazard function described by Cox (1972), treating the age factor as the underlying hazard to estimate the parameters for the cohort and period factors. (2) The model is flexible so that both the cohort and period factors can be treated as dummy or continuous variables, and the parameter estimations can be obtained for numerous combinations of variables as in a regression analysis. (3) The model is applicable even when the time period is unequally spaced.^ Two specific models are considered to illustrate the new approach and applied to the U.S. prostate cancer data. We find that there are significant differences between all cohorts and there is a significant period effect for both whites and nonwhites. The underlying hazard increases exponentially with age indicating that old people have much higher risk than young people. A log transformation of relative risk shows that the prostate cancer risk declined in recent cohorts for both models. However, prostate cancer risk declined 5 cohorts (25 years) earlier for whites than for nonwhites under the period factor model (0 0 0 1 1 1 1). These latter results are similar to the previous study by Holford (1983).^ The new approach offers a general method to analyze the age-period-cohort data without using any arbitrary constraint in the model. ^