1,418 research outputs found

    The pathology of posttransplant lymphoproliferative disorders occurring in the setting of cyclosporine A-prednisone immunosuppression

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    Posttransplant lymphoproliferative disorders (PTLDs) were diagnosed in 43 patients from the Pittsburgh-Denver series between June 1980 and March 1987. This constitutes a detection rate of 1.7%. Major categories of clinical presentation included a mononucleosis-like syndrome, gastrointestinal/abdominal disease, and solid organ disease. The median time of onset in patients initially immunosuppressed with cyclosporine-A (CsA)-containing regimens was 4.4 months after transplant, regardless of tumor clonality. A strong association of PTLD with Epstein-Barr virus (EBV) was observed. A histologic spectrum of lesions from polymorphic to monomorphic was observed. Whereas polymorphic lesions could be either clonal or non-clonal, monomorphic lesions appeared to be clonal in composition. The presence of large atypical cells (atypical immunoblasts) or necrosis did not appreciably worsen the prognosis. Twelve patients had clonal, 13 had nonclonal, and five had both clonal and nonclonal tumors. Clonality was indeterminate in 13 cases. Most patients were treated with a regimen based on reduced immunosuppression and supportive surgery. Almost all nonclonal and about half of the clonal lesions respond to this conservative therapy, indicating that it is an appropriate first line of treatment. This behavior suggests that a spectrum of lesions ranging from infectious mononucleosis to malignant lymphoma constitutes the entity known as PTLD. Some monoclonal tumors can undergo regression, however, apparently in response to host immune control mechanisms. Because of its short latency and strong association with EBV, PTLD is an important model for the study of virus-associated tumor progression in humans

    Bootstrap-after-Bootstrap Model Averaging for Reducing Model Uncertainty in Model Selection for Air Pollution Mortality Studies

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    Ba c k g r o u n d: Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single “best ” model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. Objectives: To propose an extension (double BOOT) to a previously described bootstrap modelaveraging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike’s information criterion (AIC)]. Me t h o d: Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Re s u l t s: Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOTand BMA. Co n c l u s i o n s: Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM. Key w o r d s: air pollution, Bayesian, bootstrap, model averaging, mortality, particulate matter. Environ Health Perspect 118:131–136 (2010). doi:10.1289/ehp.0901007 available vi

    Multi-modal signal evolution in birds: re-examining a standard proxy for sexual selection

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    Sexual selection is proposed to be an important driver of speciation and phenotypic diversification in animal systems. However, previous phylogenetic tests have produced conflicting results, perhaps because they have focused on a single signalling modality (visual ornaments), whereas sexual selection may act on alternative signalling modalities (e.g. acoustic ornaments). Here, we compile phenotypic data from 259 avian sister species pairs to assess the relationship between visible plumage dichromatism-a standard index of sexual selection in birds-and macroevolutionary divergence in the other major avian signalling modality: song. We find evidence for a strong negative relationship between the degree of plumage dichromatism and divergence in song traits, which remains significant even when accounting for other key factors, including habitat type, ecological divergence and interspecific interactions. This negative relationship is opposite to the pattern expected by a straightforward interpretation of the sexual selection-diversification hypothesis, whereby higher levels of dichromatism indicating strong sexual selection should be related to greater levels of mating signal divergence regardless of signalling modality. Our findings imply a 'trade-off' between the elaboration of visual ornaments and the diversification of acoustic mating signals, and suggest that the effects of sexual selection on diversification can only be determined by considering multiple alternative signalling modalities

    Bayesian Multimodel Inference for Geostatistical Regression Models

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    The problem of simultaneous covariate selection and parameter inference for spatial regression models is considered. Previous research has shown that failure to take spatial correlation into account can influence the outcome of standard model selection methods. A Markov chain Monte Carlo (MCMC) method is investigated for the calculation of parameter estimates and posterior model probabilities for spatial regression models. The method can accommodate normal and non-normal response data and a large number of covariates. Thus the method is very flexible and can be used to fit spatial linear models, spatial linear mixed models, and spatial generalized linear mixed models (GLMMs). The Bayesian MCMC method also allows a priori unequal weighting of covariates, which is not possible with many model selection methods such as Akaike's information criterion (AIC). The proposed method is demonstrated on two data sets. The first is the whiptail lizard data set which has been previously analyzed by other researchers investigating model selection methods. Our results confirmed the previous analysis suggesting that sandy soil and ant abundance were strongly associated with lizard abundance. The second data set concerned pollution tolerant fish abundance in relation to several environmental factors. Results indicate that abundance is positively related to Strahler stream order and a habitat quality index. Abundance is negatively related to percent watershed disturbance

    Paleotemperature Proxies from Leaf Fossils Reinterpreted in Light of Evolutionary History

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    Present-day correlations between leaf physiognomic traits (shape and size) and climate are widely used to estimate paleoclimate using fossil floras. For example, leaf-margin analysis estimates paleotemperature using the modern relation of mean annual temperature (MAT) and the site-proportion of untoothed-leaf species (NT). This uniformitarian approach should provide accurate paleoclimate reconstructions under the core assumption that leaf-trait variation principally results from adaptive environmental convergence, and because variation is thus largely independent of phylogeny it should be constant through geologic time. Although much research acknowledges and investigates possible pitfalls in paleoclimate estimation based on leaf physiognomy, the core assumption has never been explicitly tested in a phylogenetic comparative framework. Combining an extant dataset of 21 leaf traits and temperature with a phylogenetic hypothesis for 569 species-site pairs at 17 sites, we found varying amounts of non-random phylogenetic signal in all traits. Phylogenetic vs. standard regressions generally support prevailing ideas that leaf-traits are adaptively responding to temperature, but wider confidence intervals, and shifts in slope and intercept, indicate an overall reduced ability to predict climate precisely due to the non-random phylogenetic signal. Notably, the modern-day relation of proportion of untoothed taxa with mean annual temperature (NT-MAT), central in paleotemperature inference, was greatly modified and reduced, indicating that the modern correlation primarily results from biogeographic history. Importantly, some tooth traits, such as number of teeth, had similar or steeper slopes after taking phylogeny into account, suggesting that leaf teeth display a pattern of exaptive evolution in higher latitudes. This study shows that the assumption of convergence required for precise, quantitative temperature estimates using present-day leaf traits is not supported by empirical evidence, and thus we have very low confidence in previously published, numerical paleotemperature estimates. However, interpreting qualitative changes in paleotemperature remains warranted, given certain conditions such as stratigraphically closely-spaced samples with floristic continuity

    Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

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    The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

    Winter Bird Assemblages in Rural and Urban Environments: A National Survey

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    Urban development has a marked effect on the ecological and behavioural traits of many living organisms, including birds. In this paper, we analysed differences in the numbers of wintering birds between rural and urban areas in Poland. We also analysed species richness and abundance in relation to longitude, latitude, human population size, and landscape structure. All these parameters were analysed using modern statistical techniques incorporating species detectability. We counted birds in 156 squares (0.25 km2 each) in December 2012 and again in January 2013 in locations in and around 26 urban areas across Poland (in each urban area we surveyed 3 squares and 3 squares in nearby rural areas). The influence of twelve potential environmental variables on species abundance and richness was assessed with Generalized Linear Mixed Models, Principal Components and Detrended Correspondence Analyses. Totals of 72 bird species and 89,710 individual birds were recorded in this study. On average (±SE) 13.3 ± 0.3 species and 288 ± 14 individuals were recorded in each square in each survey. A formal comparison of rural and urban areas revealed that 27 species had a significant preference; 17 to rural areas and 10 to urban areas. Moreover, overall abundance in urban areas was more than double that of rural areas. There was almost a complete separation of rural and urban bird communities. Significantly more birds and more bird species were recorded in January compared to December. We conclude that differences between rural and urban areas in terms of winter conditions and the availability of resources are reflected in different bird communities in the two environments

    Measuring the Meltdown: Drivers of Global Amphibian Extinction and Decline

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    Habitat loss, climate change, over-exploitation, disease and other factors have been hypothesised in the global decline of amphibian biodiversity. However, the relative importance of and synergies among different drivers are still poorly understood. We present the largest global analysis of roughly 45% of known amphibians (2,583 species) to quantify the influences of life history, climate, human density and habitat loss on declines and extinction risk. Multi-model Bayesian inference reveals that large amphibian species with small geographic range and pronounced seasonality in temperature and precipitation are most likely to be Red-Listed by IUCN. Elevated habitat loss and human densities are also correlated with high threat risk. Range size, habitat loss and more extreme seasonality in precipitation contributed to decline risk in the 2,454 species that declined between 1980 and 2004, compared to species that were stable (n = 1,545) or had increased (n = 28). These empirical results show that amphibian species with restricted ranges should be urgently targeted for conservation
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