3,885 research outputs found

    Forecasting magma-chamber rupture at Santorini volcano, Greece

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    How much magma needs to be added to a shallow magma chamber to cause rupture, dyke injection, and a potential eruption? Models that yield reliable answers to this question are needed in order to facilitate eruption forecasting. Development of a long-lived shallow magma chamber requires periodic influx of magmas from a parental body at depth. This redistribution process does not necessarily cause an eruption but produces a net volume change that can be measured geodetically by inversion techniques. Using continuum-mechanics and fracture-mechanics principles, we calculate the amount of magma contained at shallow depth beneath Santorini volcano, Greece. We demonstrate through structural analysis of dykes exposed within the Santorini caldera, previously published data on the volume of recent eruptions, and geodetic measurements of the 2011–2012 unrest period, that the measured 0.02% increase in volume of Santorini’s shallow magma chamber was associated with magmatic excess pressure increase of around 1.1 MPa. This excess pressure was high enough to bring the chamber roof close to rupture and dyke injection. For volcanoes with known typical extrusion and intrusion (dyke) volumes, the new methodology presented here makes it possible to forecast the conditions for magma-chamber failure and dyke injection at any geodetically well-monitored volcano

    Sleep-wake sensitive mechanisms of adenosine release in the basal forebrain of rodents : an in vitro study

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    Adenosine acting in the basal forebrain is a key mediator of sleep homeostasis. Extracellular adenosine concentrations increase during wakefulness, especially during prolonged wakefulness and lead to increased sleep pressure and subsequent rebound sleep. The release of endogenous adenosine during the sleep-wake cycle has mainly been studied in vivo with microdialysis techniques. The biochemical changes that accompany sleep-wake status may be preserved in vitro. We have therefore used adenosine-sensitive biosensors in slices of the basal forebrain (BFB) to study both depolarization-evoked adenosine release and the steady state adenosine tone in rats, mice and hamsters. Adenosine release was evoked by high K+, AMPA, NMDA and mGlu receptor agonists, but not by other transmitters associated with wakefulness such as orexin, histamine or neurotensin. Evoked and basal adenosine release in the BFB in vitro exhibited three key features: the magnitude of each varied systematically with the diurnal time at which the animal was sacrificed; sleep deprivation prior to sacrifice greatly increased both evoked adenosine release and the basal tone; and the enhancement of evoked adenosine release and basal tone resulting from sleep deprivation was reversed by the inducible nitric oxide synthase (iNOS) inhibitor, 1400 W. These data indicate that characteristics of adenosine release recorded in the BFB in vitro reflect those that have been linked in vivo to the homeostatic control of sleep. Our results provide methodologically independent support for a key role for induction of iNOS as a trigger for enhanced adenosine release following sleep deprivation and suggest that this induction may constitute a biochemical memory of this state

    Astrobiological Complexity with Probabilistic Cellular Automata

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    Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

    2-Methoxyoestradiol-3,17-O,O-bis-sulphamate and 2-deoxy-D-glucose in combination: a potential treatment for breast and prostate cancer

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    Drug combination therapy is a key strategy to improve treatment efficacy and survival of cancer patients. In this study the effects of combining 2-methoxyoestradiol-3,17-O,O-bis-sulphamate (STX140), a microtubule disruptor, with 2-deoxy-D-glucose (2DG) were assessed in MCF-7 (breast) and LNCaP (prostate) xenograft models in vivo. In mice bearing MCF-7 xenografts, daily p.o. administration of STX140 (5 mg kg−1) resulted in a 46% (P<0.05) reduction of tumour volume. However, the combination of STX140 (5 mg kg−1 p.o.) and 2DG (2 g kg−1 i.p.) reduced tumour volume by 76% (P<0.001). 2-Methoxyoestradiol-3,17-O,O-bis-sulphamate also reduced tumour vessel density. 2-Deoxy-D-glucose alone had no significant effect on tumour volume or vessel density. A similar benefit of the combination treatment was observed in the LNCaP prostate xenograft model. In vitro the degree of inhibition of cell proliferation by STX140 was unaffected by oxygen concentrations. In contrast, the inhibition of proliferation by 2DG was enhanced under hypoxia by 20 and 25% in MCF-7 and LNCaP cells, respectively. The combination of STX140 and 2DG in LNCaP cells under normoxia or hypoxia inhibited proliferation to a greater extent than either compound alone. These results suggest that the antiangiogenic and microtubule disruption activities of STX140 may make tumours more susceptible to inhibition of glycolysis by 2DG. This is the first study to show the benefit of combining a microtubule disruptor with 2DG in the two most common solid tumours

    GraphCombEx: A Software Tool for Exploration of Combinatorial Optimisation Properties of Large Graphs

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    We present a prototype of a software tool for exploration of multiple combinatorial optimisation problems in large real-world and synthetic complex networks. Our tool, called GraphCombEx (an acronym of Graph Combinatorial Explorer), provides a unified framework for scalable computation and presentation of high-quality suboptimal solutions and bounds for a number of widely studied combinatorial optimisation problems. Efficient representation and applicability to large-scale graphs and complex networks are particularly considered in its design. The problems currently supported include maximum clique, graph colouring, maximum independent set, minimum vertex clique covering, minimum dominating set, as well as the longest simple cycle problem. Suboptimal solutions and intervals for optimal objective values are estimated using scalable heuristics. The tool is designed with extensibility in mind, with the view of further problems and both new fast and high-performance heuristics to be added in the future. GraphCombEx has already been successfully used as a support tool in a number of recent research studies using combinatorial optimisation to analyse complex networks, indicating its promise as a research software tool

    Robust Detection of Hierarchical Communities from Escherichia coli Gene Expression Data

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    Determining the functional structure of biological networks is a central goal of systems biology. One approach is to analyze gene expression data to infer a network of gene interactions on the basis of their correlated responses to environmental and genetic perturbations. The inferred network can then be analyzed to identify functional communities. However, commonly used algorithms can yield unreliable results due to experimental noise, algorithmic stochasticity, and the influence of arbitrarily chosen parameter values. Furthermore, the results obtained typically provide only a simplistic view of the network partitioned into disjoint communities and provide no information of the relationship between communities. Here, we present methods to robustly detect coregulated and functionally enriched gene communities and demonstrate their application and validity for Escherichia coli gene expression data. Applying a recently developed community detection algorithm to the network of interactions identified with the context likelihood of relatedness (CLR) method, we show that a hierarchy of network communities can be identified. These communities significantly enrich for gene ontology (GO) terms, consistent with them representing biologically meaningful groups. Further, analysis of the most significantly enriched communities identified several candidate new regulatory interactions. The robustness of our methods is demonstrated by showing that a core set of functional communities is reliably found when artificial noise, modeling experimental noise, is added to the data. We find that noise mainly acts conservatively, increasing the relatedness required for a network link to be reliably assigned and decreasing the size of the core communities, rather than causing association of genes into new communities.Comment: Due to appear in PLoS Computational Biology. Supplementary Figure S1 was not uploaded but is available by contacting the author. 27 pages, 5 figures, 15 supplementary file

    The morbidity and mortality following a diagnosis of peripheral arterial disease: Long-term follow-up of a large database

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    BACKGROUND: Awareness of the significance of peripheral arterial disease is increasing, but quantitative estimates of the ensuing burden and the impact of other risk factors remains limited. The objective of this study was to fill this need. METHODS: Morbidity and mortality were examined in 16,440 index patients diagnosed with peripheral arterial disease in Saskatchewan, Canada between 1985 and 1995. Medical history and patient characteristics were available retrospectively to January 1980 and follow-up was complete to March 1998. Crude and adjusted event rates were calculated and Kaplan-Meier survival curves estimated. Cox proportional hazards analyses were conducted to examine the effect of risk factors on these rates. Patients suffering a myocardial infarction or ischemic stroke in Saskatchewan provided two reference populations. RESULTS: Half of the index patients were male; the majority was over age 65; 73% had at least one additional risk factor at index diagnosis; 10% suffered a subsequent stroke, another 10% a myocardial infarction, and 49% died within the mean follow-up of 5.9 years. Annual mortality (8.2%) was higher among patients with PAD than after a myocardial infarction (6.3%) but slightly lower than that in patients suffering a stroke (11.3%). Index patients with comorbid disease (e.g., diabetes) were at highest risk of death and other events. CONCLUSION: A diagnosis of peripheral arterial disease is critical evidence of more widespread atherothrombotic disease, with substantial risks of subsequent cardiovascular events and death. Given that the majority has additional comorbidities, these risks are further increased

    Four patients with a history of acute exacerbations of COPD: implementing the CHEST/Canadian Thoracic Society guidelines for preventing exacerbations

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