1,399 research outputs found

    Changes in murine anorectum signaling across the life course

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    Background: Increasing age is associated with an increase in the incidence of chronic constipation and fecal impaction. The contribution of the natural aging process to these conditions is not fully understood. This study examined the effects of increasing age on the function of the murine anorectum.Methods: The effects of increasing age on cholinergic, nitrergic, and purinergic signaling pathways in the murine anorectum were examined using classical organ bath assays to examine tissue function and electrochemical sensing to determine age‐related changes in nitric oxide and acetylcholine release.Key Results: Nitrergic relaxation increased between 3 and 6 months, peaked at 12 months and declined in the 18 and 24 months groups. These changes were in part explained by an age‐related decrease in nitric oxide (NO) release. Cholinergic signaling was maintained with age by an increase in acetylcholine (ACh) release and a compensatory decrease in cholinesterase activity. Age‐related changes in purinergic relaxation were qualitatively similar to nitrergic relaxation although the relaxations were much smaller. Increasing age did not alter the response of the anorectum smooth muscle to exogenously applied ACh, ATP, sodium nitroprusside or KCl. Similarly, there was no change in basal tension developed by the anorectum.Conclusions and Inferences: The decrease in nitrergic signaling with increasing age may contribute to the age‐related fecal impaction and constipation previously described in this model by partially obstructing defecation

    Transparent and Flexible Thin Film Electroluminescent Devices Using HiTUS Deposition and Laser Processing Fabrication

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    Highly transparent thin film electroluminescent structures offering excellent switch on characteristics, high luminance and large break-down voltages have been deposited onto glass and flexible polymeric materials with no substrate heating using high target utilization sputtering. Deposition of ZnS:Mn as the active light emitting layer and Y2O3,Al2O3,Ta2O5, and HfO2 as dielectric materials arranged in single and multiple layer configurations were investigated. Devices incorporating Al2O3,HfO2 quadruple layers demonstrate the highest attainable luminance at low threshold voltage. Single pulse excimer laser irradiation of the phosphor layer prior to deposition of the top dielectric layer enhanced the luminance of the devices. The devices fabricated on glass and polymeric substrates exhibited a maximum luminance of 500 and 450 cdm−2 when driven at 270 VRMS and 220 VRMS, respectively, with a 1.0 kHz sine wave

    From policy to pedagogy: widening the discourse and practice of the learning society in the European Union

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    This paper explores the policy turn of the learning society, and how the academic world is responding to new social and political demands. It highlights some of the criticisms levelled at the learning society, as well as the voices of support. The paper also showcases the European Language Portfolio and the Transferable Skills project as two examples of good practice. Cet article examine le tournant de la politique de la socie´te´ du savoir ainsi que la re´ponse du monde intellectuel face aux nouvelles exigences sociales et politiques. Il met en lumie`re certaines des critiques souleve´es par la socie´te´ du savoir ainsi que par les voix favorables. L’article s’appuie sur deux exemples pratiques, a` savoir le Portfolio Europe´en des Langues et le Project des Compe´tences Transmissibles

    Schools and civil society : corporate or community governance

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    School improvement depends upon mediating the cultural conditions of learning as young people journey between their parochial worlds and the public world of cosmopolitan society. Governing bodies have a crucial role in including or diminishing the representation of different cultural traditions and in enabling or frustrating the expression of voice and deliberation of differences whose resolution is central to the mediation of and responsiveness to learning needs. A recent study of governing bodies in England and Wales argues that the trend to corporatising school governance will diminish the capacity of schools to learn how they can understand cultural traditions and accommodate them in their curricula and teaching strategies. A democratic, stakeholder model remains crucial to the effective practice of governing schools. By deliberating and reconciling social and cultural differences, governance constitutes the practices for mediating particular and cosmopolitan worlds and thus the conditions for engaging young people in their learning, as well as in the preparation for citizenship in civil society

    Some Effects of Oxygen Concentration on Levels of Respiratory Intermediates in Buckwheat Seedlings

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    G-protein Îąq gene expression plays a role in alcohol tolerance in Drosophila melanogaster

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    Ethanol is a psychoactive substance causing both short- and long-term behavioural changes in humans and animal models. We have used the fruit fly Drosophila melanogaster to investigate the effect of ethanol exposure on the expression of the GÎąq protein subunit. Repetitive exposure to ethanol causes a reduction in sensitivity (tolerance) to ethanol, which we have measured as the time for 50% of a set of flies to become sedated after exposure to ethanol (ST50). We demonstrate that the same treatment that induces an increase in ST50 over consecutive days (tolerance) also causes a decrease in GÎąq protein subunit expression at both the messenger RNA and protein level. To identify whether there may be a causal relationship between these two outcomes, we have developed strains of flies in which GÎąq messenger RNA expression is suppressed in a time- and tissue-specific manner. In these flies, the sensitivity to ethanol and the development of tolerance are altered. This work further supports the value of Drosophila as a model to dissect the molecular mechanisms of the behavioural response to alcohol and identifies G proteins as potentially important regulatory targets for alcohol use disorders

    Insights from agriculture for the management of insecticide resistance in disease vectors

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    Key to contemporary management of diseases such as malaria, dengue, and filariasis is control of the insect vectors responsible for transmission. Insecticide-based interventions have contributed to declines in disease burdens in many areas, but this progress could be threatened by the emergence of insecticide resistance in vector populations. Insecticide resistance is likewise a major concern in agriculture, where insect pests can cause substantial yield losses. Here, we explore overlaps between understanding and managing insecticide resistance in agriculture and in public health. We have used the Global Plan for Insecticide Resistance Management in malaria vectors, developed under the auspices of the World Health Organization Global Malaria Program, as a framework for this exploration because it serves as one of the few cohesive documents for managing a global insecticide resistance crisis. Generally, this comparison highlights some fundamental differences between insect control in agriculture and in public health. Moreover, we emphasize that the success of insecticide resistance management strategies is strongly dependent on the biological specifics of each system. We suggest that the biological, operational, and regulatory differences between agriculture and public health limit the wholesale transfer of knowledge and practices from one system to the other. Nonetheless, there are some valuable insights from agriculture that could assist in advancing the existing Global Plan for Insecticide Resistance Management framework

    Achieving Accuracy Requirements for Forest Biomass Mapping: A Data Fusion Method for Estimating Forest Biomass and LiDAR Sampling Error with Spaceborne Data

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    The synergistic use of active and passive remote sensing (i.e., data fusion) demonstrates the ability of spaceborne light detection and ranging (LiDAR), synthetic aperture radar (SAR) and multispectral imagery for achieving the accuracy requirements of a global forest biomass mapping mission. This data fusion approach also provides a means to extend 3D information from discrete spaceborne LiDAR measurements of forest structure across scales much larger than that of the LiDAR footprint. For estimating biomass, these measurements mix a number of errors including those associated with LiDAR footprint sampling over regional - global extents. A general framework for mapping above ground live forest biomass (AGB) with a data fusion approach is presented and verified using data from NASA field campaigns near Howland, ME, USA, to assess AGB and LiDAR sampling errors across a regionally representative landscape. We combined SAR and Landsat-derived optical (passive optical) image data to identify forest patches, and used image and simulated spaceborne LiDAR data to compute AGB and estimate LiDAR sampling error for forest patches and 100m, 250m, 500m, and 1km grid cells. Forest patches were delineated with Landsat-derived data and airborne SAR imagery, and simulated spaceborne LiDAR (SSL) data were derived from orbit and cloud cover simulations and airborne data from NASA's Laser Vegetation Imaging Sensor (L VIS). At both the patch and grid scales, we evaluated differences in AGB estimation and sampling error from the combined use of LiDAR with both SAR and passive optical and with either SAR or passive optical alone. This data fusion approach demonstrates that incorporating forest patches into the AGB mapping framework can provide sub-grid forest information for coarser grid-level AGB reporting, and that combining simulated spaceborne LiDAR with SAR and passive optical data are most useful for estimating AGB when measurements from LiDAR are limited because they minimized forest AGB sampling errors by 15 - 38%. Furthermore, spaceborne global scale accuracy requirements were achieved. At least 80% of the grid cells at 100m, 250m, 500m, and 1km grid levels met AGB density accuracy requirements using a combination of passive optical and SAR along with machine learning methods to predict vegetation structure metrics for forested areas without LiDAR samples. Finally, using either passive optical or SAR, accuracy requirements were met at the 500m and 250m grid level, respectively
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