Post-transplant lymphoproliferative disorders and Epstein-Barr virus DNAemia in a cohort of lung transplant recipients

<p>Abstract</p> <p>Background</p> <p>Post-transplant lymphoproliferative disorders (PTLD) are serious complications in lung transplant recipients. No consensus on EBV DNAemia levels predictive of PTLD has been reached. In addition, in many instances EBV DNAemia is determined in patients with suggestive symptoms only.</p> <p>Methods</p> <p>The characteristics of five patients with PTLD as well as the prevalence of EBV DNAmia in a cohort of 137 consecutive patients receiving lung transplantation are described.</p> <p>Results</p> <p>Twenty-six out of 137 patients (18.9%) were excluded from the analysis because lost at follow-up or dead from PTLD-independent reasons within three months of transplantation. EBV DNA in peripheral blood mononuclear cells (PBMC) was determined in 83/111 patients (74.8%) because of potential PTLD-related symptoms, while 28 patients (25.2%) showed no symptoms and were not examined. EBV DNAemia was positive in 53/83 patients (63.8%), and negative in 30/83 patients (36.2%). PTLD was diagnosed in five (4.5%) patients at a median time of 270 (range 120-870) days following transplantation. All five PTLD (three large B-cell lymphomas, one Hodgkin lymphoma and one possible pre-neoplastic lesion) were potentially associated with EBV infection. However, only 3/5 patients with PTLD had detectable EBV DNAemia: < 1,000 copies EBV DNA/1 × 10⁵PBMC in one patient and > 1,000 copies EBV DNA/1 × 10⁵PBMC in two patients.</p> <p>Conclusion</p> <p>A systematic multidisciplinary (clinical, radiologic, virologic and histologic) approach is mandatory for the diagnosis and management of PTLD in lung transplant recipients, while monitoring of symptomatic patients only may provide an incomplete or late picture of the clinical problem. In addition, staining for EBV antigens and quantification of EBV DNA in biopsy specimens should always be performed to understand the role of EBV infection in the pathogenesis of PTLD.</p

Transesterification of PHA to Oligomers Covalently Bonded with (Bio)Active Compounds Containing Either Carboxyl or Hydroxyl Functionalities

© 2015 The Authors. Published by Public Library of Science. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0120149This manuscript presents the synthesis and structural characterisation of novel biodegradable polymeric controlled-release systems of pesticides with potentially higher resistance to weather conditions in comparison to conventional forms of pesticides. Two methods for the preparation of pesticide-oligomer conjugates using the transesterification reaction were developed. The first method of obtaining conjugates, which consist of bioactive compounds with the carboxyl group and polyhydroxyalkanoates (PHAs) oligomers, is "one-pot" transesterification. In the second method, conjugates of bioactive compounds with hydroxyl group and polyhydroxyalkanoates oligomers were obtained in two-step method, through cyclic poly(3-hydroxybutyrate) oligomers. The obtained pesticide-PHA conjugates were comprehensively characterised using GPC, 1H NMR and mass spectrometry techniques. The structural characterisation of the obtained products at the molecular level with the aid of mass spectrometry confirmed that both of the synthetic strategies employed led to the formation of conjugates in which selected pesticides were covalently bonded to PHA oligomers via a hydrolysable ester bond

Infant and Child Mortality in India in the Last Two Decades: A Geospatial Analysis

Studies examining the intricate interplay between poverty, female literacy, child malnutrition, and child mortality are rare in demographic literature. Given the recent focus on Millennium Development Goals 4 (child survival) and 5 (maternal health), we explored whether the geographic regions that were underprivileged in terms of wealth, female literacy, child nutrition, or safe delivery were also grappling with the elevated risk of child mortality; whether there were any spatial outliers; whether these relationships have undergone any significant change over historical time periods.The present paper attempted to investigate these critical questions using data from household surveys like NFHS 1992-1993, NFHS 1998-1999 and DLHS 2002-2004. For the first time, we employed geo-spatial techniques like Moran's-I, univariate LISA, bivariate LISA, spatial error regression, and spatiotemporal regression to address the research problem. For carrying out the geospatial analysis, we classified India into 76 natural regions based on the agro-climatic scheme proposed by Bhat and Zavier (1999) following the Census of India Study and all estimates were generated for each of the geographic regions.This study brings out the stark intra-state and inter-regional disparities in infant and under-five mortality in India over the past two decades. It further reveals, for the first time, that geographic regions that were underprivileged in child nutrition or wealth or female literacy were also likely to be disadvantaged in terms of infant and child survival irrespective of the state to which they belong. While the role of economic status in explaining child malnutrition and child survival has weakened, the effect of mother's education has actually become stronger over time

Over-expression of the IGI1 leading to altered shoot-branching development related to MAX pathway in Arabidopsis

Shoot branching and growth are controlled by phytohormones such as auxin and other components in Arabidopsis. We identified a mutant (igi1) showing decreased height and bunchy branching patterns. The phenotypes reverted to the wild type in response to RNA interference with the IGI1 gene. Histochemical analysis by GUS assay revealed tissue-specific gene expression in the anther and showed that the expression levels of the IGI1 gene in apical parts, including flowers, were higher than in other parts of the plants. The auxin biosynthesis component gene, CYP79B2, was up-regulated in igi1 mutants and the IGI1 gene was down-regulated by IAA treatment. These results indicated that there is an interplay regulation between IGI1 and phytohormone auxin. Moreover, the expression of the auxin-related shoot branching regulation genes, MAX3 and MAX4, was down-regulated in igi1 mutants. Taken together, these results indicate that the overexpression of the IGI1 influenced MAX pathway in the shoot branching regulation

Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis

Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand) variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions

Under-Five Mortality in High Focus States in India: A District Level Geospatial Analysis

<div><h3>Background</h3><p>This paper examines if, when controlling for biophysical and geographical variables (including rainfall, productivity of agricultural lands, topography/temperature, and market access through road networks), socioeconomic and health care indicators help to explain variations in the under-five mortality rate across districts from nine high focus states in India. The literature on this subject is inconclusive because the survey data, upon which most studies of child mortality rely, rarely include variables that measure these factors. This paper introduces these variables into an analysis of 284 districts from nine high focus states in India.</p> <h3>Methodology/Principal Findings</h3><p>Information on the mortality indicator was accessed from the recently conducted Annual Health Survey of 2011 and other socioeconomic and geographic variables from Census 2011, District Level Household and Facility Survey (2007–08), Department of Economics and Statistics Divisions of the concerned states. Displaying high spatial dependence (spatial autocorrelation) in the mortality indicator (outcome variable) and its possible predictors used in the analysis, the paper uses the Spatial-Error Model in an effort to negate or reduce the spatial dependence in model parameters. The results evince that the coverage gap index (a mixed indicator of district wise coverage of reproductive and child health services), female literacy, urbanization, economic status, the number of newborn care provided in Primary Health Centers in the district transpired as significant correlates of under-five mortality in the nine high focus states in India. The study identifies three clusters with high under-five mortality rate including 30 districts, and advocates urgent attention.</p> <h3>Conclusion</h3><p>Even after controlling the possible biophysical and geographical variables, the study reveals that the health program initiatives have a major role to play in reducing under-five mortality rate in the high focus states in India.</p> </div

Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings