Inhibition of Nuclear Factor of Activated T-Cells (NFAT) Suppresses Accelerated Atherosclerosis in Diabetic Mice

OBJECTIVE OF THE STUDY: Diabetic patients have a much more widespread and aggressive form of atherosclerosis and therefore, higher risk for myocardial infarction, peripheral vascular disease and stroke, but the molecular mechanisms leading to accelerated damage are still unclear. Recently, we showed that hyperglycemia activates the transcription factor NFAT in the arterial wall, inducing the expression of the pro-atherosclerotic protein osteopontin. Here we investigate whether NFAT activation may be a link between diabetes and atherogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: Streptozotocin (STZ)-induced diabetes in apolipoprotein E(-/-) mice resulted in 2.2 fold increased aortic atherosclerosis and enhanced pro-inflammatory burden, as evidenced by elevated blood monocytes, endothelial activation- and inflammatory markers in aorta, and pro-inflammatory cytokines in plasma. In vivo treatment with the NFAT blocker A-285222 for 4 weeks completely inhibited the diabetes-induced aggravation of atherosclerosis, having no effect in non-diabetic mice. STZ-treated mice exhibited hyperglycemia and higher plasma cholesterol and triglycerides, but these were unaffected by A-285222. NFAT-dependent transcriptional activity was examined in aorta, spleen, thymus, brain, heart, liver and kidney, but only augmented in the aorta of diabetic mice. A-285222 completely blocked this diabetes-driven NFAT activation, but had no impact on the other organs or on splenocyte proliferation or cytokine secretion, ruling out systemic immunosuppression as the mechanism behind reduced atherosclerosis. Instead, NFAT inhibition effectively reduced IL-6, osteopontin, monocyte chemotactic protein 1, intercellular adhesion molecule 1, CD68 and tissue factor expression in the arterial wall and lowered plasma IL-6 in diabetic mice. CONCLUSIONS: Targeting NFAT signaling may be a novel and attractive approach for the treatment of diabetic macrovascular complications

Towards a tensionless string field theory for the N=(2,0) CFT in d=6

We describe progress in using the field theory of tensionless strings to arrive at a Lagrangian for the six-dimensional $\mathcal N=(2,0)$ conformal theory. We construct the free part of the theory and propose an ansatz for the cubic vertex in light-cone superspace. By requiring closure of the $(2,0)$ supersymmetry algebra, we fix the cubic vertex up to two parameters.Comment: 46 pages, 2 figures. V2: references added; minor changes and improvement

Eurasian Arctic greening reveals teleconnections and the potential for novel ecosystems

Arctic warming has been linked to observed increases in tundra shrub cover and growth in recent decades on the basis of significant relationships between deciduous shrub growth/biomass and temperature. These vegetation trends have been linked to Arctic sea ice decline and thus to the sea ice/albedo feedback known as Arctic amplification. However, the interactions between climate, sea ice and tundra vegetation remain poorly understood. Here we reveal a 50- year growth response over a >100,000 km2 area to a rise in summer temperature for alder (Alnus) and willow (Salix), the most abundant shrub genera respectively at and north of the continental treeline. We demonstrate that whereas plant productivity is related to sea ice in late spring, the growing season peak responds to persistent synoptic-scale air masses over West Siberia associated with Fennoscandian weather systems through the Rossby wave train. Substrate is important for biomass accumulation, yet a strong correlation between growth and temperature encompasses all observed soil types. Vegetation is especially responsive to temperature in early summer. These results have significant implications for modelling present and future Low Arctic vegetation responses to climate change, and emphasize the potential for structurally novel ecosystems to emerge fromwithin the tundra zone.Vertaisarviointia edeltävä käsikirjoitu

Mapping poverty using mobile phone and satellite data

Poverty is one of the most important determinants of adverse health outcomes globally, a major cause of societal instability and one of the largest causes of lost human potential. Traditional approaches to measuring and targeting poverty rely heavily on census data, which in most low- and middle-income countries (LMICs) are unavailable or out-of-date. Alternate measures are needed to comp- lement and update estimates between censuses. This study demonstrates how public and private data sources that are commonly available for LMICs can be used to provide novel insight into the spatial distribution of poverty. We evalu- ate the relative value of modelling three traditional poverty measures using aggregate data from mobile operators and widely available geospatial data. Taken together, models combining these data sources providethebest predictive power (highest r 2 ¼ 0.78) and lowest error, but generally models employing mobile data only yield comparable results, offering the potential to measure poverty more frequently and at finer granularity. Stratifying models into urban and rural areas highlights the advantage of using mobile data in urban areas and different data in different contexts. The findings indicate the possibility to estimate and continually monitor poverty rates at high spatial resolution in countries with limited capacity to support traditional methods of datacollection

Geographic distribution at subspecies resolution level: closely related Rhodopirellula species in European coastal sediments.

Members of the marine genus Rhodopirellula are attached living bacteria and studies based on cultured Rhodopirellula strains suggested that three closely related species R. baltica, 'R. europaea' and 'R. islandica' have a limited geographic distribution in Europe. To address this hypothesis, we developed a nested PCR for a single gene copy detection of a partial acetyl CoA synthetase (acsA) from intertidal sediments collected all around Europe. Furthermore, we performed growth experiments in a range of temperature, salinity and light conditions. A combination of Basic Local Alignment Search Tool (BLAST) and Minimum Entropy Decomposition (MED) was used to analyze the sequences with the aim to explore the geographical distribution of the species and subspecies. MED has been mainly used for the analysis of the 16S rRNA gene and here we propose a protocol for the analysis of protein-coding genes taking into account the degeneracy of the codons and a possible overestimation of functional diversity. The high-resolution analysis revealed differences in the intraspecies community structure in different geographic regions. However, we found all three species present in all regions sampled and in agreement with growth experiments we demonstrated that Rhodopirellula species do not have a limited geographic distribution in Europe

arrayMap: A Reference Resource for Genomic Copy Number Imbalances in Human Malignancies

Background: The delineation of genomic copy number abnormalities (CNAs) from cancer samples has been instrumental for identification of tumor suppressor genes and oncogenes and proven useful for clinical marker detection. An increasing number of projects have mapped CNAs using high-resolution microarray based techniques. So far, no single resource does provide a global collection of readily accessible oncoge- nomic array data. Methodology/Principal Findings: We here present arrayMap, a curated reference database and bioinformatics resource targeting copy number profiling data in human cancer. The arrayMap database provides a platform for meta-analysis and systems level data integration of high-resolution oncogenomic CNA data. To date, the resource incorporates more than 40,000 arrays in 224 cancer types extracted from several resources, including the NCBI's Gene Expression Omnibus (GEO), EBIs ArrayExpress (AE), The Cancer Genome Atlas (TCGA), publication supplements and direct submissions. For the majority of the included datasets, probe level and integrated visualization facilitate gene level and genome wide data re- view. Results from multi-case selections can be connected to downstream data analysis and visualization tools. Conclusions/Significance: To our knowledge, currently no data source provides an extensive collection of high resolution oncogenomic CNA data which readily could be used for genomic feature mining, across a representative range of cancer entities. arrayMap represents our effort for providing a long term platform for oncogenomic CNA data independent of specific platform considerations or specific project dependence. The online database can be accessed at http://www.arraymap.org.Comment: 17 pages, 5 inline figures, 3 tables, supplementary figures/tables split into 4 PDF files; manuscript submitted to PLoS ON

Reconciled climate response estimates from climate models and the energy budget of Earth

Climate risks increase with mean global temperature, so knowledge about the amount of future global warming should better inform risk assessments for policymakers. Expected near-term warming is encapsulated by the transient climate response (TCR), formally defined as the warming following 70 years of 1% per year increases in atmospheric CO2 concentration, by which point atmospheric CO2 has doubled. Studies based on Earth’s historical energy budget have typically estimated lower values of TCR than climate models, suggesting that some models could overestimate future warming. However, energy-budget estimates rely on historical temperature records that are geographically incomplete and blend air temperatures over land and sea ice with water temperatures over open oceans. We show that there is no evidence that climate models overestimate TCR when their output is processed in the same way as the HadCRUT4 observation-based temperature record3, 4. Models suggest that air-temperature warming is 24% greater than observed by HadCRUT4 over 1861–2009 because slower-warming regions are preferentially sampled and water warms less than air5. Correcting for these biases and accounting for wider uncertainties in radiative forcing based on recent evidence, we infer an observation-based best estimate for TCR of 1.66 °C, with a 5–95% range of 1.0–3.3 °C, consistent with the climate models considered in the IPCC 5th Assessment Report

Characterisation and correction of signal fluctuations in successive acquisitions of microarray images

<p>Abstract</p> <p>Background</p> <p>There are many sources of variation in dual labelled microarray experiments, including data acquisition and image processing. The final interpretation of experiments strongly relies on the accuracy of the measurement of the signal intensity. For low intensity spots in particular, accurately estimating gene expression variations remains a challenge as signal measurement is, in this case, highly subject to fluctuations.</p> <p>Results</p> <p>To evaluate the fluctuations in the fluorescence intensities of spots, we used series of successive scans, at the same settings, of whole genome arrays. We measured the decrease in fluorescence and we evaluated the influence of different parameters (PMT gain, resolution and chemistry of the slide) on the signal variability, at the level of the array as a whole and by intensity interval. Moreover, we assessed the effect of averaging scans on the fluctuations. We found that the extent of photo-bleaching was low and we established that 1) the fluorescence fluctuation is linked to the resolution e.g. it depends on the number of pixels in the spot 2) the fluorescence fluctuation increases as the scanner voltage increases and, moreover, is higher for the red as opposed to the green fluorescence which can introduce bias in the analysis 3) the signal variability is linked to the intensity level, it is higher for low intensities 4) the heterogeneity of the spots and the variability of the signal and the intensity ratios decrease when two or three scans are averaged.</p> <p>Conclusion</p> <p>Protocols consisting of two scans, one at low and one at high PMT gains, or multiple scans (ten scans) can introduce bias or be difficult to implement. We found that averaging two, or at most three, acquisitions of microarrays scanned at moderate photomultiplier settings (PMT gain) is sufficient to significantly improve the accuracy (quality) of the data and particularly those for spots having low intensities and we propose this as a general approach. For averaging and precise image alignment at sub-pixel levels we have made a program freely available on our web-site <url>http://bioinfome.cgm.cnrs-gif.fr</url> to facilitate implementation of this approach.</p

Estimation of Parent Specific DNA Copy Number in Tumors using High-Density Genotyping Arrays

Chromosomal gains and losses comprise an important type of genetic change in tumors, and can now be assayed using microarray hybridization-based experiments. Most current statistical models for DNA copy number estimate total copy number, which do not distinguish between the underlying quantities of the two inherited chromosomes. This latter information, sometimes called parent specific copy number, is important for identifying allele-specific amplifications and deletions, for quantifying normal cell contamination, and for giving a more complete molecular portrait of the tumor. We propose a stochastic segmentation model for parent-specific DNA copy number in tumor samples, and give an estimation procedure that is computationally efficient and can be applied to data from the current high density genotyping platforms. The proposed method does not require matched normal samples, and can estimate the unknown genotypes simultaneously with the parent specific copy number. The new method is used to analyze 223 glioblastoma samples from the Cancer Genome Atlas (TCGA) project, giving a more comprehensive summary of the copy number events in these samples. Detailed case studies on these samples reveal the additional insights that can be gained from an allele-specific copy number analysis, such as the quantification of fractional gains and losses, the identification of copy neutral loss of heterozygosity, and the characterization of regions of simultaneous changes of both inherited chromosomes