9,425 research outputs found

    Dynamics of the Lyman alpha and C IV emitting gas in 3C 273

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    In this paper we study the variability properties of the Lyman alpha and C IV emission lines in 3C273 using archival IUE observations. Our data show for the first time the existence of variability on time scales of several years. We study the spatial distribution and the velocity field of the emitting gas by performing detailed analyses on the line variability using correlations, 1D and 2D response functions, and principal component analysis. In both lines we find evidence for two components, one which has the dynamic properties of gas in Keplerian motion around a black hole with a mass of the order of 10^9 Mo, and one which is characterized by high, blue-shifted velocities at large lag. There is no indication of the presence of optically thick emission medium neither in the Lya, nor in the Civ response functions. The component characterized by blue-shifted velocities, which is comparatively much stronger in Civ than in Lya, is more or less compatible with being the result of gas falling towards the central black hole with free-fall acceleration. We propose however that the line emission at high, blue-shifted velocities is better explained in terms of entrainment of gas clouds by the jet. This gas is therefore probably collisionally excited as a result of heating due to the intense infrared radiation from the jet, which would explain the strength of this component in Civ relative to Lya. This phenomenon might be a signature of disk-jet interaction.Comment: 16 pages, 10 figures. Accepted for publication in ApJ. Uses aaste

    Oligonucleotide Based Magnetic Bead Capture of Onchocerca volvulus DNA for PCR Pool Screening of Vector Black Flies

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    The absence of infective larvae of Onchocerca volvulus in the black fly vector of this parasite is a major criterion used to certify that transmission has been eliminated in a focus. This process requires screening large numbers of flies. Currently, this is accomplished by screening pools of flies using a PCR-based assay. The number of flies that may be included in each pool is currently limited by the DNA purification process to 50 flies for Latin American vectors and 100 flies for African vectors. Here, we describe a new method for DNA purification that relies upon a specific oligonucleotide to capture and immobilize the parasite DNA on a magnetic bead. This method permits the reliable detection of a single infective larva of O. volvulus in pools containing up to 200 individual flies. The method described here will dramatically improve the efficiency of pool screening of vector black flies, making the process of elimination certification easier and less expensive to implement

    Using molecular data for epidemiological inference: assessing the prevalence of Trypanosoma brucei rhodesiense in Tsetse in Serengeti, Tanzania

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    Background: Measuring the prevalence of transmissible Trypanosoma brucei rhodesiense in tsetse populations is essential for understanding transmission dynamics, assessing human disease risk and monitoring spatio-temporal trends and the impact of control interventions. Although an important epidemiological variable, identifying flies which carry transmissible infections is difficult, with challenges including low prevalence, presence of other trypanosome species in the same fly, and concurrent detection of immature non-transmissible infections. Diagnostic tests to measure the prevalence of T. b. rhodesiense in tsetse are applied and interpreted inconsistently, and discrepancies between studies suggest this value is not consistently estimated even to within an order of magnitude. Methodology/Principal Findings: Three approaches were used to estimate the prevalence of transmissible Trypanosoma brucei s.l. and T. b. rhodesiense in Glossina swynnertoni and G. pallidipes in Serengeti National Park, Tanzania: (i) dissection/microscopy; (ii) PCR on infected tsetse midguts; and (iii) inference from a mathematical model. Using dissection/microscopy the prevalence of transmissible T. brucei s.l. was 0% (95% CI 0–0.085) for G. swynnertoni and 0% (0–0.18) G. pallidipes; using PCR the prevalence of transmissible T. b. rhodesiense was 0.010% (0–0.054) and 0.0089% (0–0.059) respectively, and by model inference 0.0064% and 0.00085% respectively. Conclusions/Significance: The zero prevalence result by dissection/microscopy (likely really greater than zero given the results of other approaches) is not unusual by this technique, often ascribed to poor sensitivity. The application of additional techniques confirmed the very low prevalence of T. brucei suggesting the zero prevalence result was attributable to insufficient sample size (despite examination of 6000 tsetse). Given the prohibitively high sample sizes required to obtain meaningful results by dissection/microscopy, PCR-based approaches offer the current best option for assessing trypanosome prevalence in tsetse but inconsistencies in relating PCR results to transmissibility highlight the need for a consensus approach to generate meaningful and comparable data

    Naturally light right-handed neutrinos in a 3-3-1 Model

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    In this work we show that light right-handed neutrinos, with mass in the sub-eV scale, is a natural outcome in a 3-3-1 model. By considering effective dimension five operators, the model predicts three light right-handed neutrinos, weakly mixed with the left-handed ones. We show also that the model is able to explain the LSND experiment and still be in agreement with solar and atmospheric data for neutrino oscillation.Comment: About 5 pages, no-figure

    Re-thinking the Etiological Framework of Neurodegeneration

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    Neurodegenerative diseases are among the leading causes of disability and death worldwide. The disease-related socioeconomic burden is expected to increase with the steadily increasing life expectancy. In spite of decades of clinical and basic research, most strategies designed to manage degenerative brain diseases are palliative. This is not surprising as neurodegeneration progresses "silently" for decades before symptoms are noticed. Importantly, conceptual models with heuristic value used to study neurodegeneration have been constructed retrospectively, based on signs and symptoms already present in affected patients;a circumstance that may confound causes and consequences. Hence, innovative, paradigm-shifting views of the etiology of these diseases are necessary to enable their timely prevention and treatment. Here, we outline four alternative views, not mutually exclusive, on different etiological paths toward neurodegeneration. First, we propose neurodegeneration as being a secondary outcome of a primary cardiovascular cause with vascular pathology disrupting the vital homeostatic interactions between the vasculature and the brain, resulting in cognitive impairment, dementia, and cerebrovascular events such as stroke. Second, we suggest that the persistence of senescent cells in neuronal circuits may favor, together with systemic metabolic diseases, neurodegeneration to occur. Third, we argue that neurodegeneration may start in response to altered body and brain trophic interactions established via the hardwire that connects peripheral targets with central neuronal structures or by means of extracellular vesicle (E\-mediated communication. Lastly, we elaborate on how lifespan body dysbiosis may be linked to the origin of neurodegeneration. We highlight the existence of bacterial products that modulate the gut-brain axis causing neuroinflammation and neuronal dysfunction. As a concluding section, we end by recommending research avenues to investigate these etiological paths in the future. We think that this requires an integrated, interdisciplinary conceptual research approach based on the investigation of the multimodal aspects of physiology and pathophysiology. It involves utilizing proper conceptual models, experimental animal units, and identifying currently unused opportunities derived from human data. Overall, the proposed etiological paths and experimental recommendations will be important guidelines for future cross-discipline research to overcome the translational roadblock and to develop causative treatments for neurodegenerative diseases

    Synthetic Lethality of Chk1 Inhibition Combined with p53 and/or p21 Loss During a DNA Damage Response in Normal and Tumor Cells

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    Cell cycle checkpoints ensure genome integrity and are frequently compromised in human cancers. A therapeutic strategy being explored takes advantage of checkpoint defects in p53-deficient tumors in order to sensitize them to DNA-damaging agents by eliminating Chk1-mediated checkpoint responses. Using mouse models, we demonstrated that p21 is a key determinant of how cells respond to the combination of DNA damage and Chk1 inhibition (combination therapy) in normal cells as well as in tumors. Loss of p21 sensitized normal cells to the combination therapy much more than did p53 loss and the enhanced lethality was partially blocked by CDK inhibition. In addition, basal pools of p21 (p53 independent) provided p53 null cells with protection from the combination therapy. Our results uncover a novel p53-independent function for p21 in protecting cells from the lethal effects of DNA damage followed by Chk1 inhibition. As p21 levels are low in a significant fraction of colorectal tumors, they are predicted to be particularly sensitive to the combination therapy. Results reported in this study support this prediction

    The Snail repressor recruits EZH2 to specific genomic sites through the enrollment of the lncRNA HOTAIR in epithelial-to-mesenchymal transition

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    The transcription factor Snail is a master regulator of cellular identity and epithelial-to-mesenchymal transition (EMT) directly repressing a broad repertoire of epithelial genes. How chromatin modifiers instrumental to its activity are recruited to Snail-specific binding sites is unclear. Here we report that the long non-coding RNA (lncRNA) HOTAIR (for HOX Transcript Antisense Intergenic RNA) mediates a physical interaction between Snail and enhancer of zeste homolog 2 (EZH2), an enzymatic subunit of the polycomb-repressive complex 2 and the main writer of chromatin-repressive marks. The Snail-repressive activity, here monitored on genes with a pivotal function in epithelial and hepatic morphogenesis, differentiation and cell-type identity, depends on the formation of a tripartite Snail/HOTAIR/EZH2 complex. These results demonstrate an lncRNA-mediated mechanism by which a transcriptional factor conveys a general chromatin modifier to specific genes, thereby allowing the execution of hepatocyte transdifferentiation; moreover, they highlight HOTAIR as a crucial player in the Snail-mediated EMT.Oncogene advance online publication, 25 July 2016; doi:10.1038/onc.2016.260

    Automatic Selection of Molecular Descriptors using Random Forest: Application to Drug Discovery

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    The optimal selection of chemical features (molecular descriptors) is an essential pre-processing step for the efficient application of computational intelligence techniques in virtual screening for identification of bioactive molecules in drug discovery. The selection of molecular descriptors has key influence in the accuracy of affinity prediction. In order to improve this prediction, we examined a Random Forest (RF)-based approach to automatically select molecular descriptors of training data for ligands of kinases, nuclear hormone receptors, and other enzymes. The reduction of features to use during prediction dramatically reduces the computing time over existing approaches and consequently permits the exploration of much larger sets of experimental data. To test the validity of the method, we compared the results of our approach with the ones obtained using manual feature selection in our previous study (Perez-Sanchez et al., 2014). The main novelty of this work in the field of drug discovery is the use of RF in two different ways: feature ranking and dimensionality reduction, and classification using the automatically selected feature subset. Our RF-based method out-performs classification results provided by Support Vector Machine (SVM) and Neural Networks (NN) approaches
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