Human Biodistribution and Dosimetry of 11C-CUMI-101, an Agonist Radioligand for Serotonin-1A Receptors in Brain

As a reported agonist,11C-CUMI-101 is believed to selectively bind the G-protein-coupled state of the serotonin-1A (5-HT1A) receptor, thereby providing a measure of the active subset of all 5-HT1A receptors in brain. Although 11C-CUMI-101 has been successfully used to quantify 5-HT1A receptors in human and monkey brain, its radiation exposure has not previously been reported. The purpose of this study was to calculate the radiation exposure to organs of the body based on serial whole-body imaging with positron emission tomography (PET) in human subjects

Analysis of meteorology-chemistry interactions during air pollution episodes using online coupled models within AQMEII Phase-2

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).This study reviews the top ranked meteorology and chemistry interactions in online coupled models recommended by an experts’ survey conducted in COST Action EuMetChem and examines the sensitivity of those interactions during two pollution episodes: the Russian forest fires 25 Jul -15 Aug 2010 and a Saharan dust transport event from 1 Oct -31 Oct 2010 as a part of the AQMEII phase-2 exercise. Three WRF-Chem model simulations were performed for the forest fire case for a baseline without any aerosol feedback on meteorology, a simulation with aerosol direct effects only and a simulation including both direct and indirect effects. For the dust case study, eight WRF-Chem and one WRF-CMAQ simulations were selected from the set of simulations conducted in the framework of AQMEII. Of these two simulations considered no feedbacks, two included direct effects only and five simulations included both direct and indirect effects. The results from both episodes demonstrate that it is important to include the meteorology and chemistry interactions in online-coupled models. Model evaluations using routine observations collected in AQMEII phase-2 and observations from a station in Moscow show that for the fire case the simulation including only aerosol direct effects has better performance than the simulations with no aerosol feedbacks or including both direct and indirect effects. The normalized mean biases are significantly reduced by 10-20% for PM10 when including aerosol direct effects. The analysis for the dust case confirms that models perform better when including aerosol direct effects, but worse when including both aerosol direct and indirect effects, which suggests that the representation of aerosol indirect effects needs to be improved in the model.Peer reviewedFinal Published versio

Substrate specificity of the TRAMP nuclear surveillance complexes

During nuclear surveillance in yeast and human cells, the RNA exosome functions together with the TRAMP complexes. Here, the authors defined the protein composition of the TRAMP complexes and identified specific RNA binding sites for the different TRAMP components

Improving the deterministic skill of air quality ensembles

<p><strong>Abstract.</strong> Forecasts from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as the model itself (e.g. physical parameterization, chemical mechanism). Multi-model ensemble forecasts can improve the forecast skill provided that certain mathematical conditions are fulfilled. We demonstrate through an intercomparison of two dissimilar air quality ensembles that unconditional raw forecast averaging, although generally successful, is far from optimum. One way to achieve an optimum ensemble is also presented. The basic idea is to either add optimum weights to members or constrain the ensemble to those members that meet certain conditions in time or frequency domain. The methods are evaluated against ground level observations collected from the EMEP and Airbase databases.<br><br> The two ensembles were created for the first and second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Verification statistics shows that the deterministic models simulate better O<sub>3</sub> than NO<sub>2</sub> and PM<sub>10</sub>, linked to different levels of complexity in the represented processes. The ensemble mean achieves higher skill compared to each station's best deterministic model at 39 %–63 % of the sites. The skill gained from the favourable ensemble averaging has at least double the forecast skill compared to using the full ensemble. The method proved robust for the 3-monthly examined time-series if the training phase comprises 60 days. Further development of the method is discussed in the conclusion.</p&gt

Distinct Roles of Non-Canonical Poly(A) Polymerases in RNA Metabolism

Trf4p and Trf5p are non-canonical poly(A) polymerases and are part of the heteromeric protein complexes TRAMP4 and TRAMP5 that promote the degradation of aberrant and short-lived RNA substrates by interacting with the nuclear exosome. To assess the level of functional redundancy between the paralogous Trf4 and Trf5 proteins and to investigate the role of the Trf4-dependent polyadenylation in vivo, we used DNA microarrays to compare gene expression of the wild-type yeast strain of S. cerevisiae with either that of trf4Δ or trf5Δ mutant strains or the trf4Δ mutant expressing the polyadenylation-defective Trf4(DADA) protein. We found little overlap between the sets of transcripts with altered expression in the trf4Δ or the trf5Δ mutants, suggesting that Trf4p and Trf5p target distinct groups of RNAs for degradation. Surprisingly, most RNAs the expression of which was altered by the trf4 deletion were restored to wild-type levels by overexpression of TRF4(DADA), showing that the polyadenylation activity of Trf4p is dispensable in vivo. Apart from previously reported Trf4p and Trf5p target RNAs, this analysis along with in vivo cross-linking and RNA immunopurification-chip experiments revealed that both the TRAMP4 and the TRAMP5 complexes stimulate the degradation of spliced-out introns via a mechanism that is independent of the polyadenylation activity of Trf4p. In addition, we show that disruption of trf4 causes severe shortening of telomeres suggesting that TRF4 functions in the maintenance of telomere length. Finally, our study demonstrates that TRF4, the exosome, and TRF5 participate in antisense RNA–mediated regulation of genes involved in phosphate metabolism. In conclusion, our results suggest that paralogous TRAMP complexes have distinct RNA selectivities with functional implications in RNA surveillance as well as other RNA–related processes. This indicates widespread and integrative functions of TRAMP complexes for the coordination of different gene expression regulatory processes

Sensing of Replication Stress and Mec1 Activation Act through Two Independent Pathways Involving the 9-1-1 Complex and DNA Polymerase ε

Following DNA damage or replication stress, budding yeast cells activate the Rad53 checkpoint kinase, promoting genome stability in these challenging conditions. The DNA damage and replication checkpoint pathways are partially overlapping, sharing several factors, but are also differentiated at various levels. The upstream kinase Mec1 is required to activate both signaling cascades together with the 9-1-1 PCNA-like complex and the Dpb11 (hTopBP1) protein. After DNA damage, Dpb11 is also needed to recruit the adaptor protein Rad9 (h53BP1). Here we analyzed the mechanisms leading to Mec1 activation in vivo after DNA damage and replication stress. We found that a ddc1Δdpb11-1 double mutant strain displays a synthetic defect in Rad53 and H2A phosphorylation and is extremely sensitive to hydroxyurea (HU), indicating that Dpb11 and the 9-1-1 complex independently promote Mec1 activation. A similar phenotype is observed when both the 9-1-1 complex and the Dpb4 non-essential subunit of DNA polymerase ε (Polε) are contemporarily absent, indicating that checkpoint activation in response to replication stress is achieved through two independent pathways, requiring the 9-1-1 complex and Polε

Image-Derived Input Function for Human Brain Using High Resolution PET Imaging with [11C](R)-rolipram and [11C]PBR28

The aim of this study was to test seven previously published image-input methods in state-of-the-art high resolution PET brain images. Images were obtained with a High Resolution Research Tomograph plus a resolution-recovery reconstruction algorithm using two different radioligands with different radiometabolite fractions. Three of the methods required arterial blood samples to scale the image-input, and four were blood-free methods. values was quantified using a scoring system. Using the image input methods that gave the most accurate results with Logan analysis, we also performed kinetic modelling with a two-tissue compartment model.)-rolipram, which has a lower metabolite fraction. Compartment modeling gave less reliable results, especially for the estimation of individual rate constants.C]PBR28), the more difficult it is to obtain a reliable image-derived input function; and 4) in association with image inputs, graphical analyses should be preferred over compartmental modelling

Genome-wide inference of regulatory networks in Streptomyces coelicolor

Background: The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. Results: In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Conclusions: Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.