857 research outputs found

    Modeling the impact of prevention policies on future diabetes prevalence in the United States: 2010-2030

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    Background Although diabetes is one of the most costly and rapidly increasing serious chronic diseases worldwide, the optimal mix of strategies to reduce diabetes prevalence has not been determined. Methods Using a dynamic model that incorporates national data on diabetes prevalence and incidence, migration, mortality rates, and intervention effectiveness, we project the effect of five hypothetical prevention policies on future US diabetes rates through 2030: 1) no diabetes prevention strategy; 2) a “high-risk” strategy, wherein adults with both impaired fasting glucose (IFG) (fasting plasma glucose of 100–124 mg/dl) and impaired glucose tolerance (IGT) (2-hour post-load glucose of 141–199 mg/dl) receive structured lifestyle intervention; 3) a “moderate-risk” strategy, wherein only adults with IFG are offered structured lifestyle intervention; 4) a “population-wide” strategy, in which the entire population is exposed to broad risk reduction policies; and 5) a “combined” strategy, involving both the moderate-risk and population-wide strategies. We assumed that the moderate- and high-risk strategies reduce the annual diabetes incidence rate in the targeted subpopulations by 12.5% through 2030 and that the population-wide approach would reduce the projected annual diabetes incidence rate by 2% in the entire US population. Results We project that by the year 2030, the combined strategy would prevent 4.6 million incident cases and 3.6 million prevalent cases, attenuating the increase in diabetes prevalence by 14%. The moderate-risk approach is projected to prevent 4.0 million incident cases, 3.1 million prevalent cases, attenuating the increase in prevalence by 12%. The high-risk and population approaches attenuate the projected prevalence increases by 5% and 3%, respectively. Even if the most effective strategy is implemented (the combined strategy), our projections indicate that the diabetes prevalence rate would increase by about 65% over the 23 years (i.e., from 12.9% in 2010 to 21.3% in 2030). Conclusions While implementation of appropriate diabetes prevention strategies may slow the rate of increase of the prevalence of diabetes among US adults through 2030, the US diabetes prevalence rate is likely to increase dramatically over the next 20 years. Demand for health care services for people with diabetes complications and diabetes-related disability will continue to grow, and these services will need to be strengthened along with primary diabetes prevention efforts

    Discovery of the peculiar supernova 1998bw in the error box of GRB980425

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    The discovery of X-ray, optical and radio afterglows of gamma-ray bursts (GRBs) and the measurements of the distances to some of them have established that these events come from Gpc distances and are the most powerful photon emitters known in the Universe, with peak luminosities up to 10^52 erg/s. We here report the discovery of an optical transient, in the BeppoSAX Wide Field Camera error box of GRB980425, which occurred within about a day of the gamma-ray burst. Its optical light curve, spectrum and location in a spiral arm of the galaxy ESO 184-G82, at a redshift z = 0.0085, show that the transient is a very luminous type Ic supernova, SN1998bw. The peculiar nature of SN1998bw is emphasized by its extraordinary radio properties which require that the radio emitter expand at relativistical speed. Since SN1998bw is very different from all previously observed afterglows of GRBs, our discovery raises the possibility that very different mechanisms may give rise to GRBs, which differ little in their gamma-ray properties.Comment: Under press embargo at Nature (submitted June 10, 1998

    X-ray Absorption and Reflection in Active Galactic Nuclei

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    X-ray spectroscopy offers an opportunity to study the complex mixture of emitting and absorbing components in the circumnuclear regions of active galactic nuclei, and to learn about the accretion process that fuels AGN and the feedback of material to their host galaxies. We describe the spectral signatures that may be studied and review the X-ray spectra and spectral variability of active galaxies, concentrating on progress from recent Chandra, XMM-Newton and Suzaku data for local type 1 AGN. We describe the evidence for absorption covering a wide range of column densities, ionization and dynamics, and discuss the growing evidence for partial-covering absorption from data at energies > 10 keV. Such absorption can also explain the observed X-ray spectral curvature and variability in AGN at lower energies and is likely an important factor in shaping the observed properties of this class of source. Consideration of self-consistent models for local AGN indicates that X-ray spectra likely comprise a combination of absorption and reflection effects from material originating within a few light days of the black hole as well as on larger scales. It is likely that AGN X-ray spectra may be strongly affected by the presence of disk-wind outflows that are expected in systems with high accretion rates, and we describe models that attempt to predict the effects of radiative transfer through such winds, and discuss the prospects for new data to test and address these ideas.Comment: Accepted for publication in the Astronomy and Astrophysics Review. 58 pages, 9 figures. V2 has fixed an error in footnote

    Computational exploration of molecular receptive fields in the olfactory bulb reveals a glomerulus-centric chemical map

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    © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Progress in olfactory research is currently hampered by incomplete knowledge about chemical receptive ranges of primary receptors. Moreover, the chemical logic underlying the arrangement of computational units in the olfactory bulb has still not been resolved. We undertook a large-scale approach at characterising molecular receptive ranges (MRRs) of glomeruli in the dorsal olfactory bulb (dOB) innervated by the MOR18-2 olfactory receptor, also known as Olfr78, with human ortholog OR51E2. Guided by an iterative approach that combined biological screening and machine learning, we selected 214 odorants to characterise the response of MOR18-2 and its neighbouring glomeruli. We found that a combination of conventional physico-chemical and vibrational molecular descriptors performed best in predicting glomerular responses using nonlinear Support-Vector Regression. We also discovered several previously unknown odorants activating MOR18-2 glomeruli, and obtained detailed MRRs of MOR18-2 glomeruli and their neighbours. Our results confirm earlier findings that demonstrated tunotopy, that is, glomeruli with similar tuning curves tend to be located in spatial proximity in the dOB. In addition, our results indicate chemotopy, that is, a preference for glomeruli with similar physico-chemical MRR descriptions being located in spatial proximity. Together, these findings suggest the existence of a partial chemical map underlying glomerular arrangement in the dOB. Our methodology that combines machine learning and physiological measurements lights the way towards future high-throughput studies to deorphanise and characterise structure-activity relationships in olfaction.Peer reviewe

    High Energy Neutrinos from Quasars

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    We review and clarify the assumptions of our basic model for neutrino production in the cores of quasars, as well as those modifications to the model subsequently made by other workers. We also present a revised estimate of the neutrino background flux and spectrum obtained using more recent empirical studies of quasars and their evolution. We compare our results with other thoeretical calculations and experimental upper limits on the AGN neutrino background flux. We also estimate possible neutrino fluxes from the jets of blazars detected recently by the EGRET experiment on the Compton Gamma Ray Observatory. We discuss the theoretical implications of these estimates.Comment: 14 pg., ps file (includes figures), To be published in Space Science Review

    Dynamic anoxic ferruginous conditions during the end-Permian mass extinction and recovery

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    The end-Permian mass extinction, ~252 million years ago, is notable for a complex recovery period of ~5 Myr. Widespread euxinic (anoxic and sulfidic) oceanic conditions have been proposed as both extinction mechanism and explanation for the protracted recovery period, yet the vertical distribution of anoxia in the water column and its temporal dynamics through this time period are poorly constrained. Here we utilize Fe–S–C systematics integrated with palaeontological observations to reconstruct a complete ocean redox history for the Late Permian to Early Triassic, using multiple sections across a shelf-to-basin transect on the Arabian Margin (Neo-Tethyan Ocean). In contrast to elsewhere, we show that anoxic non-sulfidic (ferruginous), rather than euxinic, conditions were prevalent in the Neo-Tethys. The Arabian Margin record demonstrates the repeated expansion of ferruginous conditions with the distal slope being the focus of anoxia at these times, as well as short-lived episodes of oxia that supported diverse biota

    Integration of decision support systems to improve decision support performance

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    Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

    Dynamic displacement of normal and detached semicircular canal cupula

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    © 2009 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial License. The definitive version was published in JARO - Journal of the Association for Research in Otolaryngology 10 (2009): 497-509, doi:10.1007/s10162-009-0174-y.The dynamic displacement of the semicircular canal cupula and modulation of afferent nerve discharge were measured simultaneously in response to physiological stimuli in vivo. The adaptation time constant(s) of normal cupulae in response to step stimuli averaged 36 s, corresponding to a mechanical lower corner frequency for sinusoidal stimuli of 0.0044 Hz. For stimuli equivalent to 40–200 deg/s of angular head velocity, the displacement gain of the central region of the cupula averaged 53 nm per deg/s. Afferents adapted more rapidly than the cupula, demonstrating the presence of a relaxation process that contributes significantly to the neural representation of angular head motions by the discharge patterns of canal afferent neurons. We also investigated changes in time constants of the cupula and afferents following detachment of the cupula at its apex—mechanical detachment that occurs in response to excessive transcupular endolymph pressure. Detached cupulae exhibited sharply reduced adaptation time constants (300 ms–3 s, n = 3) and can be explained by endolymph flowing rapidly over the apex of the cupula. Partially detached cupulae reattached and normal afferent discharge patterns were recovered 5–7 h following detachment. This regeneration process may have relevance to the recovery of semicircular canal function following head trauma.Financial support was provided by the NIDCD R01 DC06685 (Rabbitt) and NASA GSRP 56000135 & NSF IGERT DGE- 9987616 (Breneman)

    Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

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    <p>Abstract</p> <p>Background</p> <p>Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual <it>C. elegans </it>genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (<it>i.e</it>., editing) is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours.</p> <p>Results</p> <p>In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions) and train a support vector machine (SVM) classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at <url>http://starrynite.sourceforge.net</url>.</p> <p>Conclusions</p> <p>We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.</p
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