126 research outputs found

    Multidentate Terephthalamidate and Hydroxypyridonate Ligands: Towards New Orally Active Chelators

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    The limitations of current therapies for the treatment of iron overload or radioisotope contamination have stimulated efforts to develop new orally bioavailable iron and actinide chelators. Siderophore-inspired tetradentate, hexadentate and octadentate terephthalamidate and hydroxypyridonate ligands were evaluated in vivo as selective and efficacious iron or actinide chelating agents, with several metal loading and ligand assessment procedures, using {sup 59}Fe, {sup 238}Pu, and {sup 241}Am as radioactive tracers. The compounds presented in this study were compared to commercially available therapeutic sequestering agents [deferoxamine (DFO) for iron and diethylenetriaminepentaacetic acid (DPTA) for actinides] and are unrivaled in terms of affinity, selectivity and decorporation efficacy, which attests to the fact that high metal affinity may overcome the low bioavailability properties commonly associated to multidenticity

    Formation of regulatory modules by local sequence duplication

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    Turnover of regulatory sequence and function is an important part of molecular evolution. But what are the modes of sequence evolution leading to rapid formation and loss of regulatory sites? Here, we show that a large fraction of neighboring transcription factor binding sites in the fly genome have formed from a common sequence origin by local duplications. This mode of evolution is found to produce regulatory information: duplications can seed new sites in the neighborhood of existing sites. Duplicate seeds evolve subsequently by point mutations, often towards binding a different factor than their ancestral neighbor sites. These results are based on a statistical analysis of 346 cis-regulatory modules in the Drosophila melanogaster genome, and a comparison set of intergenic regulatory sequence in Saccharomyces cerevisiae. In fly regulatory modules, pairs of binding sites show significantly enhanced sequence similarity up to distances of about 50 bp. We analyze these data in terms of an evolutionary model with two distinct modes of site formation: (i) evolution from independent sequence origin and (ii) divergent evolution following duplication of a common ancestor sequence. Our results suggest that pervasive formation of binding sites by local sequence duplications distinguishes the complex regulatory architecture of higher eukaryotes from the simpler architecture of unicellular organisms

    Economic Impact of Dengue Illness and the Cost-Effectiveness of Future Vaccination Programs in Singapore

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    Dengue illness is a tropical disease transmitted by mosquitoes that threatens more than one third of the worldwide population. Dengue has important economic consequences because of the burden to hospitals, work absenteeism and risk of death of symptomatic cases. Governments attempt to reduce the disease burden using costly mosquito control strategies such as habitat reduction and spraying insecticide. Despite such efforts, the number of cases remains high. Dengue vaccines are expected to be available in the near future and there is an urgent need to evaluate their cost-effectiveness, i.e. whether their cost will be justified by the reduction in disease burden they bring. For such an evaluation, we estimated the economic impacts of dengue in Singapore and the expected vaccine costs for different prices. In this way we estimated price thresholds for which vaccination is not cost-effective. This research provides useful estimates that will contribute to informed decisions regarding the adoption of dengue vaccination programs

    Modeling the Evolution of Regulatory Elements by Simultaneous Detection and Alignment with Phylogenetic Pair HMMs

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    The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation

    State-of-the art data normalization methods improve NMR-based metabolomic analysis

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    Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples

    Transcriptomic Analysis of Toxoplasma Development Reveals Many Novel Functions and Structures Specific to Sporozoites and Oocysts

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    Sexual reproduction of Toxoplasma gondii occurs exclusively within enterocytes of the definitive felid host. The resulting immature oocysts are excreted into the environment during defecation, where in the days following, they undergo a complex developmental process. Within each oocyst, this culminates in the generation of two sporocysts, each containing 4 sporozoites. A single felid host is capable of shedding millions of oocysts, which can survive for years in the environment, are resistant to most methods of microbial inactivation during water-treatment and are capable of producing infection in warm-blooded hosts at doses as low as 1–10 ingested oocysts. Despite its extremely interesting developmental biology and crucial role in initiating an infection, almost nothing is known about the oocyst stage beyond morphological descriptions. Here, we present a complete transcriptomic analysis of the oocyst from beginning to end of its development. In addition, and to identify genes whose expression is unique to this developmental form, we compared the transcriptomes of developing oocysts with those of in vitro-derived tachyzoites and in vivo-derived bradyzoites. Our results reveal many genes whose expression is specifically up- or down-regulated in different developmental stages, including many genes that are likely critical to oocyst development, wall formation, resistance to environmental destruction and sporozoite infectivity. Of special note is the up-regulation of genes that appear “off” in tachyzoites and bradyzoites but that encode homologues of proteins known to serve key functions in those asexual stages, including a novel pairing of sporozoite-specific paralogues of AMA1 and RON2, two proteins that have recently been shown to form a crucial bridge during tachyzoite invasion of host cells. This work provides the first in-depth insight into the development and functioning of one of the most important but least studied stages in the Toxoplasma life cycle

    Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

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    BACKGROUND: We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm. RESULTS: We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. CONCLUSION: Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding. Constraining on alignment is a straightforward method of reducing the runtime and memory requirements of the algorithm. Five practical implementations of the pairwise Sankoff algorithm – this work (Consan), David Mathews' Dynalign, Ian Holmes' Stemloc, Ivo Hofacker's PMcomp, and Jan Gorodkin's FOLDALIGN – have comparable overall performance with different strengths and weaknesses

    Causes and Consequences of Past and Projected Scandinavian Summer Temperatures, 500–2100 AD

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    Tree rings dominate millennium-long temperature reconstructions and many records originate from Scandinavia, an area for which the relative roles of external forcing and internal variation on climatic changes are, however, not yet fully understood. Here we compile 1,179 series of maximum latewood density measurements from 25 conifer sites in northern Scandinavia, establish a suite of 36 subset chronologies, and analyse their climate signal. A new reconstruction for the 1483–2006 period correlates at 0.80 with June–August temperatures back to 1860. Summer cooling during the early 17th century and peak warming in the 1930s translate into a decadal amplitude of 2.9°C, which agrees with existing Scandinavian tree-ring proxies. Climate model simulations reveal similar amounts of mid to low frequency variability, suggesting that internal ocean-atmosphere feedbacks likely influenced Scandinavian temperatures more than external forcing. Projected 21st century warming under the SRES A2 scenario would, however, exceed the reconstructed temperature envelope of the past 1,500 years
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